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Katsoulis M, Lai AG, Kipourou DK, Gomes M, Banerjee A, Denaxas S, Lumbers RT, Tsilidis K, Kostara M, Belot A, Dale C, Sofat R, Leyrat C, Hemingway H, Diaz-Ordaz K. On the estimation of the effect of weight change on a health outcome using observational data, by utilising the target trial emulation framework. Int J Obes (Lond) 2023; 47:1309-1317. [PMID: 37884665 PMCID: PMC10663146 DOI: 10.1038/s41366-023-01396-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 09/17/2023] [Accepted: 10/10/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND/OBJECTIVES When studying the effect of weight change between two time points on a health outcome using observational data, two main problems arise initially (i) 'when is time zero?' and (ii) 'which confounders should we account for?' From the baseline date or the 1st follow-up (when the weight change can be measured)? Different methods have been previously used in the literature that carry different sources of bias and hence produce different results. METHODS We utilised the target trial emulation framework and considered weight change as a hypothetical intervention. First, we used a simplified example from a hypothetical randomised trial where no modelling is required. Then we simulated data from an observational study where modelling is needed. We demonstrate the problems of each of these methods and suggest a strategy. INTERVENTIONS weight loss/gain vs maintenance. RESULTS The recommended method defines time-zero at enrolment, but adjustment for confounders (or exclusion of individuals based on levels of confounders) should be performed both at enrolment and the 1st follow-up. CONCLUSIONS The implementation of our suggested method [adjusting for (or excluding based on) confounders measured both at baseline and the 1st follow-up] can help researchers attenuate bias by avoiding some common pitfalls. Other methods that have been widely used in the past to estimate the effect of weight change on a health outcome are more biased. However, two issues remain (i) the exposure is not well-defined as there are different ways of changing weight (however we tried to reduce this problem by excluding individuals who develop a chronic disease); and (ii) immortal time bias, which may be small if the time to first follow up is short.
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Affiliation(s)
- M Katsoulis
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK.
| | - A G Lai
- Institute of Health Informatics, University College London, London, UK
| | - D K Kipourou
- Inequalities in Cancer Outcomes Network, Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- AstraZeneca, London, UK
| | - M Gomes
- Department of Applied Health Research, University College London, London, UK
| | - A Banerjee
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals NHS Trust, London, UK
- Barts Health NHS Trust, The Royal London Hospital, London, UK
| | - S Denaxas
- Institute of Health Informatics, University College London, London, UK
- Alan Turing Institute, London, UK
| | - R T Lumbers
- Institute of Health Informatics, University College London, London, UK
| | - K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Maria Kostara
- Department of Pediatrics, University Hospital of Ioannina, Ioannina, Greece
| | - A Belot
- Inequalities in Cancer Outcomes Network, Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - C Dale
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - R Sofat
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - C Leyrat
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - H Hemingway
- Institute of Health Informatics, University College London, London, UK
| | - K Diaz-Ordaz
- Dept of Statistical Science, Faculty of Maths & Physical Sciences, University College London, London, UK
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Lambarth A, Katsoulis M, Ju C, Warwick A, Takhar R, Dale C, Prieto-Merino D, Morris A, Sen D, Wei L, Sofat R. Prevalence of chronic pain or analgesic use in children and young people and its long-term impact on substance misuse, mental illness, and prescription opioid use: a retrospective longitudinal cohort study. Lancet Reg Health Eur 2023; 35:100763. [PMID: 38115960 PMCID: PMC10730316 DOI: 10.1016/j.lanepe.2023.100763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/11/2023] [Accepted: 10/12/2023] [Indexed: 12/21/2023]
Abstract
Background Epidemiological studies suggest chronic and recurrent pain affects around a quarter of children, while 8% report intense and frequent pain. The long-term implications of chronic pain in childhood are uncertain. Using electronic health records (EHRs) we used both disease codes and medicines prescription records to investigate the scale of chronic pain and long-term analgesic use in children and young people (CYP), and if chronic pain and/or use of analgesic medicines at an early age is associated with substance misuse, use of prescription opioids, and poor mental health in adulthood. Methods We conducted a cohort study using data from IQVIA Medical Research Data UK. We identified individuals aged 2-24 with exposure to either a diagnostic code indicating chronic pain (diagnosis-exposed), repeat prescription for medicines commonly used to treat pain (prescription-exposed), or both. Follow-up began at 25, and the unexposed population acted as comparators. We calculated hazard ratios (HR) for mental health and substance misuse outcomes, and rate ratios (RR) for opioid prescriptions in adulthood. Additionally, we investigated which diagnoses, if any, were over-represented in the prescription-exposed subgroup. Findings The cohort constituted 853,625 individuals; 146,431 had one or more of the exposures of interest (diagnosis-exposed = 115,101, prescription-exposed = 20,298, both-exposed = 11,032), leaving 707,194 as comparators. Median age at index exposure was 18.7 years (IQR 14.7-22.3). On average during follow-up, the pooled exposed group had, respectively, a 31% and 17% higher risk of adverse mental health and substance misuse outcomes (adjusted HR [95% CI] of 1.31 [1.29-1.32] and 1.17 [1.11-1.24]). Exposed individuals also received prescription opioids at double the rate of unexposed individuals on average during follow-up (adjusted RR 2.01 [95% CI 1.95-2.10]). Outcomes varied between exposure subgroups, with prescription- and both-exposure tending to have worse outcomes. Unlike these two subgroups, in the diagnosis-exposed subgroup we did not detect a greater risk of substance misuse. Interpretation Chronic pain in CYP is associated with increased prescription opioid use and adverse mental health outcomes in adulthood, as is repeat prescription for analgesic medicines, but only the latter is also associated with substance misuse in adulthood. It is essential to avoid the harms of under-treating pain in CYP while giving due consideration to the risks posed by analgesic medicines. Early recognition of chronic pain in CYP and utilising non-pharmacological management options may help minimise overprescribing, and long-term reliance on dependence-forming-drugs. Funding AL is an NIHR funded academic clinical fellow, and was supported by funding from UCLH Charities while carrying out this work. RS and DS are part of the Advanced Pain Discovery Platform and were supported by a UKRI and Versus Arthritis grant (MR/W002566/1) as part of the Consortium Against Pain Inequality. AW was supported by the Wellcome Trust (220558/Z/20/Z).
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Affiliation(s)
- Andrew Lambarth
- Department of Clinical Pharmacology and Therapeutics, St George's University of London, London, UK
- St George's University Hospitals NHS Foundation Trust, Cranmer Terrace, London, UK
| | - Michail Katsoulis
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Chengsheng Ju
- Research Department of Practice and Policy, University College London School of Pharmacy, 29-39 Brunswick Square, London, WC1N 1AX, UK
| | - Alasdair Warwick
- Institute of Cardiovascular Science, University College London, London, UK
- Moorfields Eye Hospital NHS Foundation Trust, London, UK
| | - Rohan Takhar
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Caroline Dale
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | | | - Andrew Morris
- Usher Institute, College of Medicine and Veterinary Medicine, The University of Edinburgh, Nine Edinburgh BioQuarter, 9 Little France Road, Edinburgh, EH16 4UX, UK
- Health Data Research UK, 215 Euston Road, London, NW1 2BE, UK
| | - Debajit Sen
- University College London Hospitals NHS Foundation Trust, 235 Euston Rd, London, NW1 2BU, UK
| | - Li Wei
- Research Department of Practice and Policy, University College London School of Pharmacy, 29-39 Brunswick Square, London, WC1N 1AX, UK
| | - Reecha Sofat
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- Health Data Research UK, 215 Euston Road, London, NW1 2BE, UK
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De Stavola BL, Gomes M, Katsoulis M. Transparency and Rigor: Target Trial Emulation Aims to Achieve Both. Epidemiology 2023:00001648-990000000-00148. [PMID: 37255253 DOI: 10.1097/ede.0000000000001638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Affiliation(s)
- Bianca L De Stavola
- Great Ormond Street Institute of Child Health, University College London, UK
| | - Manuel Gomes
- Institute of Epidemiology and Health, University College London, UK
| | - Michail Katsoulis
- MRC Unit for Lifelong Health and Aging, University College London, UK
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Speciani MC, Gargari G, Penagini R, Mutignani M, Ferraroni M, Natale A, Katsoulis M, Cintolo M, Leone P, Airoldi A, Vecchi M, Bonzi R, Ciafardini C, Oreggia B, Carnevali P, Guglielmetti S, Riso P, La Vecchia C, Rossi M. Garlic consumption in relation to colorectal cancer risk and to alterations of blood bacterial DNA. Eur J Nutr 2023:10.1007/s00394-023-03110-2. [PMID: 37093261 DOI: 10.1007/s00394-023-03110-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 01/31/2023] [Indexed: 04/25/2023]
Abstract
PURPOSE Garlic consumption has been inversely associated to intestinal adenoma (IA) and colorectal cancer (CRC) risk, although evidence is not consistent. Gut microbiota has been implied in CRC pathogenesis and is also influenced by garlic consumption. We analyzed whether dietary garlic influence CRC risk and bacterial DNA in blood. METHODS We conducted a case-control study in Italy involving 100 incident CRC cases, 100 IA and 100 healthy controls matched by center, sex and age. We used a validated food frequency questionnaire to assess dietary habits and garlic consumption. Blood bacterial DNA profile was estimated using qPCR and16S rRNA gene profiling. We derived odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) of IA and CRC according to garlic consumption from multiple conditional logistic regression. We used Mann-Whitney and chi-square tests to evaluate taxa differences in abundance and prevalence. RESULTS The OR of CRC for medium/high versus low/null garlic consumption was 0.27 (95% CI = 0.11-0.66). Differences in garlic consumption were found for selected blood bacterial taxa. Medium/high garlic consumption was associated to an increase of Corynebacteriales order, Nocardiaceae family and Rhodococcus genus, and to a decrease of Family XI and Finegoldia genus. CONCLUSIONS The study adds data on the protective effect of dietary garlic on CRC risk. Moreover, it supports evidence of a translocation of bacterial material to bloodstream and corroborates the hypothesis of a diet-microbiota axis as a mechanism behind the role of garlic in CRC prevention.
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Affiliation(s)
- Michela Carola Speciani
- Branch of Medical Statistics, Biometry, and Epidemiology "G. A. Maccacaro", Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Via Celoria 22, 20133, Milan, Italy
| | - Giorgio Gargari
- Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan, Italy
| | - Roberto Penagini
- Gastroenterology and Endoscopy Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Massimiliano Mutignani
- Digestive and Interventional Endoscopy Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Monica Ferraroni
- Branch of Medical Statistics, Biometry, and Epidemiology "G. A. Maccacaro", Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Via Celoria 22, 20133, Milan, Italy
| | - Arianna Natale
- Branch of Medical Statistics, Biometry, and Epidemiology "G. A. Maccacaro", Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Via Celoria 22, 20133, Milan, Italy
| | - Michail Katsoulis
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, UCL, London, UK
| | - Marcello Cintolo
- Digestive and Interventional Endoscopy Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Pierfrancesco Leone
- General Surgery Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Aldo Airoldi
- Hepatology and Gastroenterology Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Maurizio Vecchi
- Gastroenterology and Endoscopy Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Rossella Bonzi
- Branch of Medical Statistics, Biometry, and Epidemiology "G. A. Maccacaro", Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Via Celoria 22, 20133, Milan, Italy
| | - Clorinda Ciafardini
- Gastroenterology and Endoscopy Unit, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Ca' Granda Ospedale Maggiore Policlinico, 20122, Milan, Italy
| | - Barbara Oreggia
- General Surgery Unit, Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Pietro Carnevali
- Division of Minimally-Invasive Surgical Oncology, Niguarda Cancer Center, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Simone Guglielmetti
- Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan, Italy
| | - Patrizia Riso
- Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan, Italy
| | - Carlo La Vecchia
- Branch of Medical Statistics, Biometry, and Epidemiology "G. A. Maccacaro", Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Via Celoria 22, 20133, Milan, Italy
| | - Marta Rossi
- Branch of Medical Statistics, Biometry, and Epidemiology "G. A. Maccacaro", Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Via Celoria 22, 20133, Milan, Italy.
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Dale CE, Takhar R, Carragher R, Katsoulis M, Torabi F, Duffield S, Kent S, Mueller T, Kurdi A, Le Anh TN, McTaggart S, Abbasizanjani H, Hollings S, Scourfield A, Lyons RA, Griffiths R, Lyons J, Davies G, Harris D, Handy A, Mizani MA, Tomlinson C, Thygesen JH, Ashworth M, Denaxas S, Banerjee A, Sterne JAC, Brown P, Bullard I, Priedon R, Mamas MA, Slee A, Lorgelly P, Pirmohamed M, Khunti K, Morris AD, Sudlow C, Akbari A, Bennie M, Sattar N, Sofat R. The impact of the COVID-19 pandemic on cardiovascular disease prevention and management. Nat Med 2023; 29:219-225. [PMID: 36658423 DOI: 10.1038/s41591-022-02158-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 11/28/2022] [Indexed: 01/21/2023]
Abstract
How the Coronavirus Disease 2019 (COVID-19) pandemic has affected prevention and management of cardiovascular disease (CVD) is not fully understood. In this study, we used medication data as a proxy for CVD management using routinely collected, de-identified, individual-level data comprising 1.32 billion records of community-dispensed CVD medications from England, Scotland and Wales between April 2018 and July 2021. Here we describe monthly counts of prevalent and incident medications dispensed, as well as percentage changes compared to the previous year, for several CVD-related indications, focusing on hypertension, hypercholesterolemia and diabetes. We observed a decline in the dispensing of antihypertensive medications between March 2020 and July 2021, with 491,306 fewer individuals initiating treatment than expected. This decline was predicted to result in 13,662 additional CVD events, including 2,281 cases of myocardial infarction and 3,474 cases of stroke, should individuals remain untreated over their lifecourse. Incident use of lipid-lowering medications decreased by 16,744 patients per month during the first half of 2021 as compared to 2019. By contrast, incident use of medications to treat type 2 diabetes mellitus, other than insulin, increased by approximately 623 patients per month for the same time period. In light of these results, methods to identify and treat individuals who have missed treatment for CVD risk factors and remain undiagnosed are urgently required to avoid large numbers of excess future CVD events, an indirect impact of the COVID-19 pandemic.
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Affiliation(s)
- Caroline E Dale
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Rohan Takhar
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Raymond Carragher
- Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde, Glasgow, UK
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Michail Katsoulis
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Fatemeh Torabi
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | | | - Seamus Kent
- National Institute for Health and Care Excellence, London, UK
| | - Tanja Mueller
- Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde, Glasgow, UK
| | - Amanj Kurdi
- Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde, Glasgow, UK
- Department of Pharmacology, College of Pharmacy, Hawler Medical University, Erbil, Iraq
| | - Thu Nguyen Le Anh
- Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde, Glasgow, UK
| | | | - Hoda Abbasizanjani
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | | | | | - Ronan A Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Rowena Griffiths
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Jane Lyons
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Gareth Davies
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Daniel Harris
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Alex Handy
- Institute of Health Informatics, University College London, London, UK
| | - Mehrdad A Mizani
- Institute of Health Informatics, University College London, London, UK
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | | | - Johan H Thygesen
- Institute of Health Informatics, University College London, London, UK
| | | | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
- Health Data Research UK, London, UK
- BHF Accelerator, University College London, London, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
- Department of Cardiology, Barts Health NHS Trust, London, UK
| | - Jonathan A C Sterne
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
- Health Data Research UK South-West, Bristol, UK
| | | | | | - Rouven Priedon
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | | | | | - Paula Lorgelly
- Department of Applied Health Research, University College London, London, UK
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | | | - Cathie Sudlow
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
| | - Ashley Akbari
- Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, UK
| | - Marion Bennie
- Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde, Glasgow, UK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Reecha Sofat
- Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK.
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK.
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6
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Handy A, Banerjee A, Wood AM, Dale C, Sudlow CLM, Tomlinson C, Bean D, Thygesen JH, Mizani MA, Katsoulis M, Takhar R, Hollings S, Denaxas S, Walker V, Dobson R, Sofat R. Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort. Heart 2022; 108:923-931. [PMID: 35273122 PMCID: PMC8931797 DOI: 10.1136/heartjnl-2021-320325] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 01/24/2022] [Indexed: 01/06/2023] Open
Abstract
OBJECTIVE To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA2DS2-VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes. METHODS Individuals with AF and CHA2DS2-VASc score ≥2 on 1 January 2020 were identified using electronic health records for 56 million people in England and were followed up until 1 May 2021. Factors associated with pre-existing AT use were analysed using logistic regression. Differences in COVID-19-related hospitalisation and death were analysed using logistic and Cox regression in individuals with pre-existing AT use versus no AT use, anticoagulants (AC) versus antiplatelets (AP), and direct oral anticoagulants (DOACs) versus warfarin. RESULTS From 972 971 individuals with AF (age 79 (±9.3), female 46.2%) and CHA2DS2-VASc score ≥2, 88.0% (n=856 336) had pre-existing AT use, 3.8% (n=37 418) had a COVID-19 hospitalisation and 2.2% (n=21 116) died, followed up to 1 May 2021. Factors associated with no AT use included comorbidities that may contraindicate AT use (liver disease and history of falls) and demographics (socioeconomic status and ethnicity). Pre-existing AT use was associated with lower odds of death (OR=0.92, 95% CI 0.87 to 0.96), but higher odds of hospitalisation (OR=1.20, 95% CI 1.15 to 1.26). AC versus AP was associated with lower odds of death (OR=0.93, 95% CI 0.87 to 0.98) and higher hospitalisation (OR=1.17, 95% CI 1.11 to 1.24). For DOACs versus warfarin, lower odds were observed for hospitalisation (OR=0.86, 95% CI 0.82 to 0.89) but not for death (OR=1.00, 95% CI 0.95 to 1.05). CONCLUSIONS Pre-existing AT use may be associated with lower odds of COVID-19 death and, while not evidence of causality, provides further incentive to improve AT coverage for eligible individuals with AF.
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Affiliation(s)
- Alex Handy
- Institute of Health Informatics, University College London, London, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals National Health Service Trust, London, UK
- Barts Health National Health Service Trust, The Royal London Hospital, London, UK
| | - Angela M Wood
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Caroline Dale
- Institute of Health Informatics, University College London, London, UK
| | - Cathie L M Sudlow
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Usher Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Christopher Tomlinson
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals National Health Service Trust, London, UK
- UKRI Centre for Doctoral Training in AI-enabled Healthcare Systems, University College London, London, UK
- National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Daniel Bean
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Trust, London, UK
- Health Data Research UK London, University College London, London, UK
| | - Johan H Thygesen
- Institute of Health Informatics, University College London, London, UK
| | - Mehrdad A Mizani
- Institute of Health Informatics, University College London, London, UK
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
- MRC Unit for Lifelong Health and Ageing and Centre for Longitudinal Studies, University College London, London, UK
| | - Rohan Takhar
- Institute of Health Informatics, University College London, London, UK
| | | | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
- British Heart Foundation Data Science Centre, Health Data Research UK, London, UK
- National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
- British Heart Foundation Research Accelerator, University College London, London, UK
| | - Venexia Walker
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Richard Dobson
- Institute of Health Informatics, University College London, London, UK
- National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley National Health Service Trust, London, UK
- Health Data Research UK London, University College London, London, UK
| | - Reecha Sofat
- Institute of Health Informatics, University College London, London, UK
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
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7
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Polydora E, Alexandrou M, Tsipilis S, Athanasiou N, Katsoulis M, Rodopoulou A, Pappas A, Kalomenidis I. Predictors of high flow oxygen therapy failure in COVID-19-related severe hypoxemic respiratory failure. J Thorac Dis 2022; 14:851-856. [PMID: 35572875 PMCID: PMC9096326 DOI: 10.21037/jtd-21-1373] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 01/21/2022] [Indexed: 12/04/2022]
Abstract
Background During COVID-19 pandemic, people who developed pneumonia and needed supplemental oxygen, where treated with low-flow oxygen therapy systems and non-invasive methods, including oxygen therapy using high flow nasal cannula (HFNC) and the application of bi-level or continuous positive airway pressure (BiPAP or CPAP). We aimed to investigate the outcomes of critical COVID-19 patients treated with HFNC and unveil predictors of HFNC failure. Methods We retrospectively enrolled patients admitted to COVID-19 wards and treated with HFNC for COVID-19-related severe hypoxemic respiratory failure. The primary outcome of this study was treatment failure, such as the composite of intubation or death during hospital stay. The association between treatment failure and clinical features was evaluated using logistic regression models. Results One hundred thirty-two patients with a median (IQR) PaO2/FiO2 ratio 96 (63-173) mmHg at HFNC initiation were studied. Overall, 45.4% of the patients were intubated. Hospital mortality was 31.8%. Treatment failure (intubation or death) occurred in 50.75% and after adjustment for age, gender, Charlson Comorbidity index (CCI) score and National Early Warning Score 2 (NEWS2) score on admission and PaO2/FiO2 ratio and acute respiratory distress syndrome (ARDS) severity at the time of HFNO initiation, it was significantly associated with the presence of dyspnea [adjusted OR 2.48 (95% CI: 1.01-6.12)], and higher Urea serum levels [adjusted OR 1.25 (95% CI: 1.03-1.51) mg/dL]. Conclusions HFNC treatment was successful in almost half of the patients with severe COVID-19-related acute hypoxemic respiratory failure (AHRF). The presence of dyspnea and high serum Urea levels on admission are closely related to HFNC failure.
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Affiliation(s)
- Eftychia Polydora
- COVID-19 Unit, “Evaggelismos” General Hospital, Athens, Greece
- 1st Department of Critical Care and Pulmonary Medicine, National and Kapodistrian University of Athens, Evaggelismos Hospital, Athens, Greece
| | - Michaella Alexandrou
- COVID-19 Unit, “Evaggelismos” General Hospital, Athens, Greece
- 1st Department of Critical Care and Pulmonary Medicine, National and Kapodistrian University of Athens, Evaggelismos Hospital, Athens, Greece
| | - Stamatios Tsipilis
- COVID-19 Unit, “Evaggelismos” General Hospital, Athens, Greece
- Pulmonary Department, Evaggelismos Hospital, Athens, Greece
| | - Nikolaos Athanasiou
- COVID-19 Unit, “Evaggelismos” General Hospital, Athens, Greece
- Pulmonary Department, Evaggelismos Hospital, Athens, Greece
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
| | | | - Apostolos Pappas
- COVID-19 Unit, “Evaggelismos” General Hospital, Athens, Greece
- 1st Department of Critical Care and Pulmonary Medicine, National and Kapodistrian University of Athens, Evaggelismos Hospital, Athens, Greece
| | - Ioannis Kalomenidis
- COVID-19 Unit, “Evaggelismos” General Hospital, Athens, Greece
- 1st Department of Critical Care and Pulmonary Medicine, National and Kapodistrian University of Athens, Evaggelismos Hospital, Athens, Greece
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8
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Makri R, Katsoulis M, Fotiou A, Kanavou E, Stavrou M, Richardson C, Kanellopoulou A, Orfanos P, Benetou V, Kokkevi A. Prevalence of Overweight and Obesity and Associated Diet-Related Behaviours and Habits in a Representative Sample of Adolescents in Greece. Children (Basel) 2022; 9:children9010119. [PMID: 35053743 PMCID: PMC8774704 DOI: 10.3390/children9010119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 01/05/2022] [Accepted: 01/11/2022] [Indexed: 01/22/2023]
Abstract
Excessive body weight during adolescence represents a significant public health problem worldwide. Identifying factors associated with its development is crucial. We estimated the prevalence of overweight and obesity in a representative sample of 11, 13 and, 15-year-olds living in Greece and explored the association with diet-related behaviours and habits. Self-reported data on weight, height, diet-related behaviours and habits were used from 3816 students (1898 boys, 1918 girls) participants in the Greek arm of the international Health Behaviour in School-Aged Children (HBSC) study during 2018. Overweight and obesity were defined using the 2007 WHO growth charts classification. Prevalence of overweight was 19.4% in the total sample, 24.1% for boys and 14.7% for girls, and prevalence of obesity was 5.3% in the total sample, 7.3% for boys and 3.4% for girls, respectively. In the total sample, overweight (including obesity) was positively associated with male gender, low family affluence, skipping breakfast, and being on a diet, and inversely associated with age and being physically active. Eating rarely with the family was positively associated with overweight only among boys and eating snacks/meals in front of screens only among girls. No association was noted for eating in fast-food restaurants, consuming vegetables, fruits, sweets, and sugar-sweetened beverages.
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Affiliation(s)
- Rafaela Makri
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 115-27 Athens, Greece; (R.M.); (P.O.)
| | - Michail Katsoulis
- Institute of Health Informatics, Faculty of Population Health Sciences, University College London, London ΝW1 2DA, UK;
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, Faculty of Population Health Sciences, London WC1E 7HB, UK
| | - Anastasios Fotiou
- University Mental Health, Neurosciences, & Precision Medicine Research Institute “Costas Stefanis” (UMHRI), 115-27 Athens, Greece; (A.F.); (E.K.); (M.S.); (A.K.)
| | - Eleftheria Kanavou
- University Mental Health, Neurosciences, & Precision Medicine Research Institute “Costas Stefanis” (UMHRI), 115-27 Athens, Greece; (A.F.); (E.K.); (M.S.); (A.K.)
| | - Myrto Stavrou
- University Mental Health, Neurosciences, & Precision Medicine Research Institute “Costas Stefanis” (UMHRI), 115-27 Athens, Greece; (A.F.); (E.K.); (M.S.); (A.K.)
| | - Clive Richardson
- Department of Economic and Regional Development, Panteion University of Social and Political Sciences, 176-71 Athens, Greece;
| | - Afroditi Kanellopoulou
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, 451-10 Ioannina, Greece;
| | - Philippos Orfanos
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 115-27 Athens, Greece; (R.M.); (P.O.)
| | - Vassiliki Benetou
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 115-27 Athens, Greece; (R.M.); (P.O.)
- Correspondence: ; Tel.: +30-210-7462074
| | - Anna Kokkevi
- University Mental Health, Neurosciences, & Precision Medicine Research Institute “Costas Stefanis” (UMHRI), 115-27 Athens, Greece; (A.F.); (E.K.); (M.S.); (A.K.)
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9
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Bouras E, Karhunen V, Gill D, Huang J, Haycock PC, Gunter MJ, Johansson M, Brennan P, Key T, Lewis SJ, Martin RM, Murphy N, Platz EA, Travis R, Yarmolinsky J, Zuber V, Martin P, Katsoulis M, Freisling H, Nøst TH, Schulze MB, Dossus L, Hung RJ, Amos CI, Ahola-Olli A, Palaniswamy S, Männikkö M, Auvinen J, Herzig KH, Keinänen-Kiukaanniemi S, Lehtimäki T, Salomaa V, Raitakari O, Salmi M, Jalkanen S, Jarvelin MR, Dehghan A, Tsilidis KK. Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis. BMC Med 2022; 20:3. [PMID: 35012533 PMCID: PMC8750876 DOI: 10.1186/s12916-021-02193-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 11/18/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis. METHODS Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer). RESULTS There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses. CONCLUSIONS Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.
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Affiliation(s)
- Emmanouil Bouras
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George's University Hospitals NHS Foundation Trust, London, UK
- Clinical Pharmacology and Therapeutics Section, Institute for Infection and Immunity, St George's, University of London, London, UK
| | - Jian Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Philip C Haycock
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Mattias Johansson
- Genomics Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Paul Brennan
- Genomics Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Tim Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Sarah J Lewis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ruth Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - James Yarmolinsky
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Verena Zuber
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
| | - Paul Martin
- School of Biochemistry, University of Bristol, Bristol, UK
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Therese Haugdahl Nøst
- Department of Community Medicine, Faculty of Health Sciences, Arctic University of Norway, Tromsø, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nutehtal, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Laure Dossus
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute of Sinai Health System, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | | | - Ari Ahola-Olli
- The Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Saranya Palaniswamy
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
| | - Minna Männikkö
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Karl-Heinz Herzig
- Research Unit of Biomedicine, Medical Research Center, Faculty of Medicine, University of Oulu, and Oulu University Hospital, Oulu, Finland
| | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Veikko Salomaa
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Marko Salmi
- MediCity Research Laboratory, University of Turku, Turku, Finland
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Sirpa Jalkanen
- MediCity Research Laboratory, University of Turku, Turku, Finland
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- UK Dementia Research Institute at Imperial College London, London, UK
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece.
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London, W2 1PG, UK.
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10
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Chang WH, Katsoulis M, Tan YY, Mueller SH, Green K, Lai AG. Late effects of cancer in children, teenagers and young adults: Population-based study on the burden of 183 conditions, in-patient and critical care admissions and years of life lost. Lancet Reg Health Eur 2022; 12:100248. [PMID: 34950917 PMCID: PMC8672041 DOI: 10.1016/j.lanepe.2021.100248] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
BACKGROUND Children, teenagers and young adults who survived cancer are prone to developing late effects. The burden of late effects across a large number of conditions, in-patient hospitalisation and critical care admissions have not been described using a population-based dataset. We aim to systematically quantify the cumulative burden of late effects across all cancer subtypes, treatment modalities and chemotherapy drug classes. METHODS We employed primary care records linked to hospitals, the death registry and cancer registry from 1998-2020. CTYA survivors were 25 years or younger at the time of cancer diagnosis had survived ≥5 years post-diagnosis. Year-of-birth and sex-matched community controls were used for comparison. We considered nine treatment types, nine chemotherapy classes and 183 physical and mental health late effects. Cumulative burden was estimated using mean cumulative count, which considers recurring events. Multivariable logistic regression was used to investigate the association between treatment exposures and late effects. Excess years of life lost (YLL) attributable to late effects were estimated. FINDINGS Among 4,063 patients diagnosed with cancer, 3,466 survived ≥ 5 years (85%); 13,517 matched controls were identified. The cumulative burden of late effects at age 35 was the highest in survivors of leukaemia (23.52 per individual [95% CI:19.85-29.33]) and lowest in survivors of germ cell tumours (CI:6.04 [5.32-6.91]). In controls, the cumulative burden was 3.99 (CI:3.93-4.08) at age 35 years. When survivors reach age 45, the cumulative burden for immunological conditions and infections was the highest (3.27 [CI:3.01-3.58]), followed by cardiovascular conditions (3.08 [CI:1.98-3.29]). Survivors who received chemotherapy and radiotherapy had the highest disease burden compared to those who received surgery only. These patients also had the highest burden of hospitalisation (by age 45: 10.43 [CI:8.27-11.95]). Survivors who received antimetabolite chemotherapy had the highest disease and hospitalisation burden, while the lowest burden is observed in those receiving antitumour antibiotics. Regression analyses revealed that survivors who received only surgery had lower odds of developing cardiovascular (adjusted odds ratio 0.73 [CI:0.56-0.94]), haematological (aOR 0.51 [CI:0.37-0.70]), immunology and infection (aOR 0.84 [CI:0.71-0.99]) and renal (aOR 0.51 [CI:0.39-0.66]) late effects. By contrast, the opposite trend was observed in survivors who received chemo-radiotherapy. High antimetabolite chemotherapy cumulative dose was associated with increased risks of subsequent cancer (aOR 2.32 [CI:1.06-4.84]), metastatic cancer (aOR 4.44 [CI:1.29-11.66]) and renal (aOR 3.48 [CI:1.36-7.86]) conditions. Patients who received radiation dose of ≥50 Gy experienced higher risks of developing metastatic cancer (aOR 5.51 [CI:2.21-11.86]), cancer (aOR 3.77 [CI:2.22-6.34]), haematological (aOR 3.43 [CI:1.54-6.83]) and neurological (aOR 3.24 [CI:1.78-5.66]) conditions. Similar trends were observed in survivors who received more than three teletherapy fields. Cumulative burden analyses on 183 conditions separately revealed varying dominance of different late effects across cancer types, socioeconomic deprivation and treatment modalities. Late effects are associated with excess YLL (i.e., the difference in YLL between survivors with or without late effects), which was the most pronounced among survivors with haematological comorbidities. INTERPRETATION To our knowledge, this is the first study to dissect and quantify the importance of late morbidities on subsequent survival using linked electronic health records from multiple settings. The burden of late effects is heterogeneous, as is the risk of premature mortality associated with late effects. We provide an extensive knowledgebase to help inform treatment decisions at the point of diagnosis, future interventional trials and late-effects screening centred on the holistic needs of this vulnerable population.
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Affiliation(s)
- Wai Hoong Chang
- Institute of Health Informatics, University College London, London, United Kingdom of Great Britain and Northern Ireland
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, United Kingdom of Great Britain and Northern Ireland
| | - Yen Yi Tan
- Institute of Health Informatics, University College London, London, United Kingdom of Great Britain and Northern Ireland
| | - Stefanie H. Mueller
- Institute of Health Informatics, University College London, London, United Kingdom of Great Britain and Northern Ireland
| | - Katherine Green
- Great Ormond Street Hospital, London, United Kingdom of Great Britain and Northern Ireland
- Institute of Child Health, University College London, London, United Kingdom of Great Britain and Northern Ireland
| | - Alvina G. Lai
- Institute of Health Informatics, University College London, London, United Kingdom of Great Britain and Northern Ireland
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11
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Banerjee A, Chen S, Pasea L, Lai AG, Katsoulis M, Denaxas S, Nafilyan V, Williams B, Wong WK, Bakhai A, Khunti K, Pillay D, Noursadeghi M, Wu H, Pareek N, Bromage D, McDonagh TA, Byrne J, Teo JTH, Shah AM, Humberstone B, Tang LV, Shah ASV, Rubboli A, Guo Y, Hu Y, Sudlow CLM, Lip GYH, Hemingway H. Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic. Eur J Prev Cardiol 2021; 28:1599-1609. [PMID: 33611594 PMCID: PMC7928969 DOI: 10.1093/eurjpc/zwaa155] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 11/26/2020] [Accepted: 12/10/2020] [Indexed: 12/21/2022]
Abstract
AIMS Cardiovascular diseases (CVDs) increase mortality risk from coronavirus infection (COVID-19). There are also concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both 'direct', through infection, and 'indirect', through changes in healthcare. METHODS AND RESULTS We used (i) national mortality data for England and Wales to investigate trends in non-COVID-19 and CVD excess deaths; (ii) routine data from hospitals in England (n = 2), Italy (n = 1), and China (n = 5) to assess indirect pandemic effects on referral, diagnosis, and treatment services for CVD; and (iii) population-based electronic health records from 3 862 012 individuals in England to investigate pre- and post-COVID-19 mortality for people with incident and prevalent CVD. We incorporated pre-COVID-19 risk (by age, sex, and comorbidities), estimated population COVID-19 prevalence, and estimated relative risk (RR) of mortality in those with CVD and COVID-19 compared with CVD and non-infected (RR: 1.2, 1.5, 2.0, and 3.0).Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous (peak RR 1.14). CVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy, and England. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown and is still reduced in Italy and England. For total CVD (incident and prevalent), at 10% COVID-19 prevalence, we estimated direct impact of 31 205 and 62 410 excess deaths in England (RR 1.5 and 2.0, respectively), and indirect effect of 49 932 to 99 865 deaths. CONCLUSION Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the pandemic.
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Affiliation(s)
- Amitava Banerjee
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
- Department of Cardiology, Barts Health NHS Trust, Royal London Hospital, Whitechapel Road, London, UK, E1 1BB
- University College London Hospitals NHS Trust, 235 Euston Road, London, UK, NW1 2BU
| | - Suliang Chen
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
| | - Laura Pasea
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
| | - Alvina G Lai
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
| | - Vahe Nafilyan
- Office for National Statistics. 1 Drummond Gate, Pimlico, London, UK, SW1V 2QQ
| | - Bryan Williams
- University College London Hospitals NHS Trust, 235 Euston Road, London, UK, NW1 2BU
- Institute of Cardiovascular Science, University College London, London, UK, WC1E 6BT
- University College London Hospitals NIHR Biomedical Research Centre, Maple House, 1st Floor, 149 Tottenham Court Road, London, UK, W1T 7DN
| | - Wai Keong Wong
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- University College London Hospitals NHS Trust, 235 Euston Road, London, UK, NW1 2BU
| | - Ameet Bakhai
- Department of Cardiology, Royal Free Hospital, Pond Street, London, UK, NW3 2QG
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Gwendolen Rd, Leicester, UK, LE5 4PW
| | - Deenan Pillay
- Division of Infection and Immunity, UCL Cruciform Building, University College London, Gower Street, London, UK, WC1E 6BT
| | - Mahdad Noursadeghi
- University College London Hospitals NHS Trust, 235 Euston Road, London, UK, NW1 2BU
- Division of Infection and Immunity, UCL Cruciform Building, University College London, Gower Street, London, UK, WC1E 6BT
| | - Honghan Wu
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
- School of Computer and Software, Najing University of Information Science and Technology, Ningliu Road, Nanjing, Jiangsu Province, P.R.C. 210044, China
| | - Nilesh Pareek
- Kings College Hospital NHS Foundation Trust, Denmark Hill, Brixton, London, UK, SE5 9RS
| | - Daniel Bromage
- Kings College Hospital NHS Foundation Trust, Denmark Hill, Brixton, London, UK, SE5 9RS
- Kings College London British Heart Foundation Centre, School of Cardiovascular Medicine & Sciences, London, Strand, London WC2R 2LS. UK
| | - Theresa A McDonagh
- Kings College Hospital NHS Foundation Trust, Denmark Hill, Brixton, London, UK, SE5 9RS
- Kings College London British Heart Foundation Centre, School of Cardiovascular Medicine & Sciences, London, Strand, London WC2R 2LS. UK
| | - Jonathan Byrne
- Kings College Hospital NHS Foundation Trust, Denmark Hill, Brixton, London, UK, SE5 9RS
| | - James T H Teo
- Kings College Hospital NHS Foundation Trust, Denmark Hill, Brixton, London, UK, SE5 9RS
| | - Ajay M Shah
- Kings College Hospital NHS Foundation Trust, Denmark Hill, Brixton, London, UK, SE5 9RS
- Kings College London British Heart Foundation Centre, School of Cardiovascular Medicine & Sciences, London, Strand, London WC2R 2LS. UK
| | - Ben Humberstone
- Office for National Statistics. 1 Drummond Gate, Pimlico, London, UK, SW1V 2QQ
| | - Liang V Tang
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Anoop S V Shah
- Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent Edinburgh, UK. EH16 4TJ
| | - Andrea Rubboli
- Division of Cardiology, Ospedale S. Maria delle Croci, Viale Randi 5, 48121, Ravenna. Italy
| | - Yutao Guo
- PLA General Hospital, 28 Fuxing Road, Beijing, Haidian District, Beijing, China
| | - Yu Hu
- Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Cathie L M Sudlow
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, 9 Little France Road, Edinburgh BioQuarter City, Edinburgh, UK, EH16 4UX
- BHF Data Science Centre, Health Data Research, 215 Euston Road, London, UK, NW1 2BE
| | - Gregory Y H Lip
- Liverpool Centre for Cardiovascular Science, University of Liverpool,William Henry Duncan Building, 6 W Derby Street, Liverpool, UK, L7 8TX
- Liverpool Heart & Chest Hospital, Thomas Drive, Liverpool, UK, L14 3PE
- Department of Clinical Medicine, Aalborg Thrombosis Research Unit, Aalborg University, Søndre Skovvej 15, Forskningens Hus 9000, Aalborg, Denmark
| | - Harry Hemingway
- Institute of Health Informatics, University College London, 222 Euston Road, London, UK, NW1 1DA
- Health Data Research UK, Gibbs Building, 215 Euston Road, London, UK, NW1 2BE
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12
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Banerjee A, Pasea L, Manohar S, Lai AG, Hemingway E, Sofer I, Katsoulis M, Sood H, Morris A, Cake C, Fitzpatrick NK, Williams B, Denaxas S, Hemingway H. 'What is the risk to me from COVID-19?': Public involvement in providing mortality risk information for people with 'high-risk' conditions for COVID-19 (OurRisk.CoV). Clin Med (Lond) 2021; 21:e620-e628. [PMID: 34862222 DOI: 10.7861/clinmed.2021-0386] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Patients and public have sought mortality risk information throughout the pandemic, but their needs may not be served by current risk prediction tools. Our mixed methods study involved: (1) systematic review of published risk tools for prognosis, (2) provision and patient testing of new mortality risk estimates for people with high-risk conditions and (3) iterative patient and public involvement and engagement with qualitative analysis. Only one of 53 (2%) previously published risk tools involved patients or the public, while 11/53 (21%) had publicly accessible portals, but all for use by clinicians and researchers.Among people with a wide range of underlying conditions, there has been sustained interest and engagement in accessible and tailored, pre- and postpandemic mortality information. Informed by patient feedback, we provide such information in 'five clicks' (https://covid19-phenomics.org/OurRiskCoV.html), as context for decision making and discussions with health professionals and family members. Further development requires curation and regular updating of NHS data and wider patient and public engagement.
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Affiliation(s)
- Amitava Banerjee
- University College London, London, UK, honorary consultant cardiologist, University College London Hospitals NHS Trust, London, UK, and honorary consultant cardiologist, Barts Health NHS Trust, London, UK
| | | | | | - Alvina G Lai
- University College London, London, UK, and associate, Health Data Research UK, London, UK
| | | | | | | | - Harpreet Sood
- Health Education England, London, UK, and general practitioner, Hurley Group Practice, London, UK
| | | | | | - Natalie K Fitzpatrick
- University College London, London, UK, and associate, Health Data Research UK, London, UK
| | - Bryan Williams
- University College London Hospitals NHS Trust, London, UK, professor of medicine, University College London, London, UK, and director, UCL Hospitals NIHR Biomedical Research Centre
| | - Spiros Denaxas
- University College London, London, UK, associate, Health Data Research UK, and research fellow, Alan Turing Institute, London, UK
| | - Harry Hemingway
- University College London, London, UK, research director, Health Data Research UK, London, UK, and director of healthcare informatics, genomics/omics, data science, UCL Hospitals NIHR Biomedical Research Centre, London, UK
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13
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Lai AG, Chang WH, Parisinos CA, Katsoulis M, Blackburn RM, Shah AD, Nguyen V, Denaxas S, Davey Smith G, Gaunt TR, Nirantharakumar K, Cox MP, Forde D, Asselbergs FW, Harris S, Richardson S, Sofat R, Dobson RJB, Hingorani A, Patel R, Sterne J, Banerjee A, Denniston AK, Ball S, Sebire NJ, Shah NH, Foster GR, Williams B, Hemingway H. An informatics consult approach for generating clinical evidence for treatment decisions. BMC Med Inform Decis Mak 2021; 21:281. [PMID: 34641870 PMCID: PMC8506488 DOI: 10.1186/s12911-021-01638-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 09/27/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND An Informatics Consult has been proposed in which clinicians request novel evidence from large scale health data resources, tailored to the treatment of a specific patient. However, the availability of such consultations is lacking. We seek to provide an Informatics Consult for a situation where a treatment indication and contraindication coexist in the same patient, i.e., anti-coagulation use for stroke prevention in a patient with both atrial fibrillation (AF) and liver cirrhosis. METHODS We examined four sources of evidence for the effect of warfarin on stroke risk or all-cause mortality from: (1) randomised controlled trials (RCTs), (2) meta-analysis of prior observational studies, (3) trial emulation (using population electronic health records (N = 3,854,710) and (4) genetic evidence (Mendelian randomisation). We developed prototype forms to request an Informatics Consult and return of results in electronic health record systems. RESULTS We found 0 RCT reports and 0 trials recruiting for patients with AF and cirrhosis. We found broad concordance across the three new sources of evidence we generated. Meta-analysis of prior observational studies showed that warfarin use was associated with lower stroke risk (hazard ratio [HR] = 0.71, CI 0.39-1.29). In a target trial emulation, warfarin was associated with lower all-cause mortality (HR = 0.61, CI 0.49-0.76) and ischaemic stroke (HR = 0.27, CI 0.08-0.91). Mendelian randomisation served as a drug target validation where we found that lower levels of vitamin K1 (warfarin is a vitamin K1 antagonist) are associated with lower stroke risk. A pilot survey with an independent sample of 34 clinicians revealed that 85% of clinicians found information on prognosis useful and that 79% thought that they should have access to the Informatics Consult as a service within their healthcare systems. We identified candidate steps for automation to scale evidence generation and to accelerate the return of results. CONCLUSION We performed a proof-of-concept Informatics Consult for evidence generation, which may inform treatment decisions in situations where there is dearth of randomised trials. Patients are surprised to know that their clinicians are currently not able to learn in clinic from data on 'patients like me'. We identify the key challenges in offering such an Informatics Consult as a service.
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Affiliation(s)
- Alvina G Lai
- Institute of Health Informatics, University College London, London, UK.
- Health Data Research UK, London, UK.
| | - Wai Hoong Chang
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
| | | | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
| | - Ruth M Blackburn
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
| | - Anoop D Shah
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- University College London Hospitals NHS Trust, London, UK
| | - Vincent Nguyen
- Institute of Health Informatics, University College London, London, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- The Alan Turing Institute, London, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom R Gaunt
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Krishnarajah Nirantharakumar
- Health Data Research UK, London, UK
- Institute of Applies Health Research, University of Birmingham, Birmingham, UK
| | - Murray P Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
| | - Donall Forde
- Public Health Wales, University Hospital of Wales, Cardiff, UK
| | - Folkert W Asselbergs
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Institute of Cardiovascular Science, University College London, London, UK
| | - Steve Harris
- University College London Hospitals NHS Trust, London, UK
| | - Sylvia Richardson
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Reecha Sofat
- Institute of Health Informatics, University College London, London, UK
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
| | - Richard J B Dobson
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
- Department of Biostatistics and Health Informatics, King's College London, London, UK
| | - Aroon Hingorani
- Health Data Research UK, London, UK
- Institute of Cardiovascular Science, University College London, London, UK
| | - Riyaz Patel
- Institute of Cardiovascular Science, University College London, London, UK
| | - Jonathan Sterne
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
- Barts Health NHS Trust, The Royal London Hospital, Whitechapel Rd, London, UK
| | - Alastair K Denniston
- Health Data Research UK, London, UK
- University Hospitals Birmingham NHSFT, Birmingham, UK
| | - Simon Ball
- Health Data Research UK, London, UK
- University Hospitals Birmingham NHSFT, Birmingham, UK
| | - Neil J Sebire
- UCL Great Ormond Street Institute of Child Health, London, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, London, UK
| | - Nigam H Shah
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Graham R Foster
- Barts Liver Centre, Blizard Institute, Queen Mary University of London, London, UK
| | - Bryan Williams
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- Institute of Cardiovascular Science, University College London, London, UK
- University College London Hospitals NHS Trust, London, UK
| | - Harry Hemingway
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, London, UK
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14
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Katsoulis M, Lai AG, Diaz-Ordaz K, Gomes M, Pasea L, Banerjee A, Denaxas S, Tsilidis K, Lagiou P, Misirli G, Bhaskaran K, Wannamethee G, Dobson R, Batterham RL, Kipourou DK, Lumbers RT, Wen L, Wareham N, Langenberg C, Hemingway H. Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records. Lancet Diabetes Endocrinol 2021; 9:681-694. [PMID: 34481555 PMCID: PMC8440227 DOI: 10.1016/s2213-8587(21)00207-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/17/2021] [Accepted: 07/20/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Targeted obesity prevention policies would benefit from the identification of population groups with the highest risk of weight gain. The relative importance of adult age, sex, ethnicity, geographical region, and degree of social deprivation on weight gain is not known. We aimed to identify high-risk groups for changes in weight and BMI using electronic health records (EHR). METHODS In this longitudinal, population-based cohort study we used linked EHR data from 400 primary care practices (via the Clinical Practice Research Datalink) in England, accessed via the CALIBER programme. Eligible participants were aged 18-74 years, were registered at a general practice clinic, and had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, during the period when they had eligible linked data with at least 1 year of follow-up time. We calculated longitudinal changes in BMI over 1, 5, and 10 years, and investigated the absolute risk and odds ratios (ORs) of transitioning between BMI categories (underweight, normal weight, overweight, obesity class 1 and 2, and severe obesity [class 3]), as defined by WHO. The associations of demographic factors with BMI transitions were estimated by use of logistic regression analysis, adjusting for baseline BMI, family history of cardiovascular disease, use of diuretics, and prevalent chronic conditions. FINDINGS We included 2 092 260 eligible individuals with more than 9 million BMI measurements in our study. Young adult age was the strongest risk factor for weight gain at 1, 5, and 10 years of follow-up. Compared with the oldest age group (65-74 years), adults in the youngest age group (18-24 years) had the highest OR (4·22 [95% CI 3·86-4·62]) and greatest absolute risk (37% vs 24%) of transitioning from normal weight to overweight or obesity at 10 years. Likewise, adults in the youngest age group with overweight or obesity at baseline were also at highest risk to transition to a higher BMI category; OR 4·60 (4·06-5·22) and absolute risk (42% vs 18%) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23-6·59) and absolute risk (22% vs 5%) of transitioning from class 1 and 2 obesity to class 3 obesity. Other demographic factors were consistently less strongly associated with these transitions; for example, the OR of transitioning from normal weight to overweight or obesity in people living in the most socially deprived versus least deprived areas was 1·23 (1·18-1·27), for men versus women was 1·12 (1·08-1·16), and for Black individuals versus White individuals was 1·13 (1·04-1·24). We provide an open access online risk calculator, and present high-resolution obesity risk charts over a 1-year, 5-year, and 10-year follow-up period. INTERPRETATION A radical shift in policy is required to focus on individuals at the highest risk of weight gain (ie, young adults aged 18-24 years) for individual-level and population-level prevention of obesity and its long-term consequences for health and health care. FUNDING The British Hearth Foundation, Health Data Research UK, the UK Medical Research Council, and the National Institute for Health Research.
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Affiliation(s)
- Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK.
| | - Alvina G Lai
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - Karla Diaz-Ordaz
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Manuel Gomes
- Department of Applied Health Research, University College London, London, UK
| | - Laura Pasea
- Institute of Health Informatics, University College London, London, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK; University College London Hospitals NHS Trust, London, UK; Barts Health NHS Trust, The Royal London Hospital, London, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK; Alan Turing Institute, London, UK; National Institute of Health Research, University College London Hospitals Biomedical Research Centre, London, UK
| | - Kostas Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Pagona Lagiou
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | | | - Krishnan Bhaskaran
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Goya Wannamethee
- Department of Primary Care and Population Health, University College London, London, UK
| | - Richard Dobson
- Health Data Research UK, University College London, London, UK; Institute of Health Informatics, University College London, London, UK; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Rachel L Batterham
- Centre for Obesity Research, University College London, London, UK; National Institute of Health Research, University College London Hospitals Biomedical Research Centre, London, UK; University College London Hospitals Bariatric Centre for Weight Management and Metabolic Surgery, London, UK
| | - Dimitra-Kleio Kipourou
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - R Thomas Lumbers
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - Lan Wen
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK; Computational Medicine, Berlin Institute of Health, Charité-University Medicine Berlin, Berlin, Germany
| | - Harry Hemingway
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK; National Institute of Health Research, University College London Hospitals Biomedical Research Centre, London, UK
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15
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Katsoulis M, Stavola BD, Diaz-Ordaz K, Gomes M, Lai A, Lagiou P, Wannamethee G, Tsilidis K, Lumbers RT, Denaxas S, Banerjee A, Parisinos CA, Batterham R, Patel R, Langenberg C, Hemingway H. Weight Change and the Onset of Cardiovascular Diseases: Emulating Trials Using Electronic Health Records. Epidemiology 2021; 32:744-755. [PMID: 34348396 PMCID: PMC8318567 DOI: 10.1097/ede.0000000000001393] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 06/11/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND Cross-sectional measures of body mass index (BMI) are associated with cardiovascular disease (CVD) incidence, but less is known about whether weight change affects the risk of CVD. METHODS We estimated the effect of 2-y weight change interventions on 7-y risk of CVD (CVD death, myocardial infarction, stroke, hospitalization from coronary heart disease, and heart failure) by emulating hypothetical interventions using electronic health records. We identified 138,567 individuals with 45-69 years of age without chronic disease in England from 1998 to 2016. We performed pooled logistic regression, using inverse-probability weighting to adjust for baseline and time-varying confounders. We categorized each individual into a weight loss, maintenance, or gain group. RESULTS Among those of normal weight, both weight loss [risk difference (RD) vs. weight maintenance = 1.5% (0.3% to 3.0%)] and gain [RD = 1.3% (0.5% to 2.2%)] were associated with increased risk for CVD compared with weight maintenance. Among overweight individuals, we observed moderately higher risk of CVD in both the weight loss [RD = 0.7% (-0.2% to 1.7%)] and the weight gain group [RD = 0.7% (-0.1% to 1.7%)], compared with maintenance. In the obese, those losing weight showed lower risk of coronary heart disease [RD = -1.4% (-2.4% to -0.6%)] but not of stroke. When we assumed that chronic disease occurred 1-3 years before the recorded date, estimates for weight loss and gain were attenuated among overweight individuals; estimates for loss were lower among obese individuals. CONCLUSION Among individuals with obesity, the weight-loss group had a lower risk of coronary heart disease but not of stroke. Weight gain was associated with increased risk of CVD across BMI groups. See video abstract at, http://links.lww.com/EDE/B838.
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Affiliation(s)
- Michail Katsoulis
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
| | - Bianca D. Stavola
- Great Ormond Street Institute of Child Health, UCL, London, United Kingdom
| | - Karla Diaz-Ordaz
- Medical Statistics Department, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Manuel Gomes
- Institute of Epidemiology & Health Care, UCL, London, United Kingdom
| | - Alvina Lai
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
| | - Pagona Lagiou
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Goya Wannamethee
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantinos Tsilidis
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - R. Thomas Lumbers
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
- Bart’s Heart Centre, St Bartholomew’s Hospital, London, United Kingdom
| | - Spiros Denaxas
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
- The Alan Turing Institute, London, United Kingdom
- The National Institute for Health Research, University College London Hospitals Biomedical Research Centre, UCL, London, United Kingdom
- British Heart Foundation Research Accelerator, UCL, London, United Kingdom
| | - Amitava Banerjee
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
- Amrita Institute of Medical Sciences, Kochi, India
| | - Constantinos A. Parisinos
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
| | - Rachel Batterham
- The National Institute for Health Research, University College London Hospitals Biomedical Research Centre, UCL, London, United Kingdom
- Centre for Obesity Research, UCL, London, United Kingdom
- University College London Hospitals Bariatric Centre for Weight Management and Metabolic Surgery, London, United Kingdom
| | - Riyaz Patel
- Institute of Cardiovascular Science, UCL, London, United Kingdom
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Harry Hemingway
- From the Institute of Health Informatics, University College London (UCL), London, United Kingdom
- Health Data Research UK London, UCL, London, United Kingdom
- The National Institute for Health Research, University College London Hospitals Biomedical Research Centre, UCL, London, United Kingdom
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16
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Katsoulis M, Pasea L, Lai AG, Dobson RJB, Denaxas S, Hemingway H, Banerjee A. Obesity during the COVID-19 pandemic: both cause of high risk and potential effect of lockdown? A population-based electronic health record study. Public Health 2021; 191:41-47. [PMID: 33497994 PMCID: PMC7832229 DOI: 10.1016/j.puhe.2020.12.003] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/29/2020] [Accepted: 12/06/2020] [Indexed: 12/28/2022]
Abstract
OBJECTIVES Obesity is a modifiable risk factor for coronavirus disease 2019 (COVID-19)-related mortality. We estimated excess mortality in obesity, both 'direct', through infection, and 'indirect', through changes in health care, and also due to potential increasing obesity during lockdown. STUDY DESIGN The study design of this study is a retrospective cohort study and causal inference methods. METHODS In population-based electronic health records for 1,958,638 individuals in England, we estimated 1-year mortality risk ('direct' and 'indirect' effects) for obese individuals, incorporating (i) pre-COVID-19 risk by age, sex and comorbidities, (ii) population infection rate and (iii) relative impact on mortality (relative risk [RR]: 1.2, 1.5, 2.0 and 3.0). Using causal inference models, we estimated impact of change in body mass index (BMI) and physical activity during 3-month lockdown on 1-year incidence for high-risk conditions (cardiovascular diseases, diabetes, chronic obstructive pulmonary disease and chronic kidney disease), accounting for confounders. RESULTS For severely obese individuals (3.5% at baseline), at 10% population infection rate, we estimated direct impact of 240 and 479 excess deaths in England at RR 1.5 and 2.0, respectively, and indirect effect of 383-767 excess deaths, assuming 40% and 80% will be affected at RR = 1.2. Owing to BMI change during the lockdown, we estimated that 97,755 (5.4%: normal weight to overweight, 5.0%: overweight to obese and 1.3%: obese to severely obese) to 434,104 individuals (15%: normal weight to overweight, 15%: overweight to obese and 6%: obese to severely obese) would be at higher risk for COVID-19 over one year. CONCLUSIONS Prevention of obesity and promotion of physical activity are at least as important as physical isolation of severely obese individuals during the pandemic.
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Affiliation(s)
- M Katsoulis
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - L Pasea
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - A G Lai
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - R J B Dobson
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - S Denaxas
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - H Hemingway
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK
| | - A Banerjee
- Institute of Health Informatics, University College London, London, UK; Health Data Research UK, University College London, London, UK; University College London Hospitals NHS Trust, 235 Euston Road, London, UK; Barts Health NHS Trust, The Royal London Hospital, Whitechapel Rd, London, UK.
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17
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Ellingjord-Dale M, Papadimitriou N, Katsoulis M, Yee C, Dimou N, Gill D, Aune D, Ong JS, MacGregor S, Elsworth B, Lewis SJ, Martin RM, Riboli E, Tsilidis KK. Coffee consumption and risk of breast cancer: A Mendelian randomization study. PLoS One 2021; 16:e0236904. [PMID: 33465101 PMCID: PMC7815134 DOI: 10.1371/journal.pone.0236904] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 01/03/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Observational studies have reported either null or weak protective associations for coffee consumption and risk of breast cancer. METHODS We conducted a two-sample Mendelian randomization (MR) analysis to evaluate the relationship between coffee consumption and breast cancer risk using 33 single-nucleotide polymorphisms (SNPs) associated with coffee consumption from a genome-wide association (GWA) study on 212,119 female UK Biobank participants of White British ancestry. Risk estimates for breast cancer were retrieved from publicly available GWA summary statistics from the Breast Cancer Association Consortium (BCAC) on 122,977 cases (of which 69,501 were estrogen receptor (ER)-positive, 21,468 ER-negative) and 105,974 controls of European ancestry. Random-effects inverse variance weighted (IVW) MR analyses were performed along with several sensitivity analyses to assess the impact of potential MR assumption violations. RESULTS One cup per day increase in genetically predicted coffee consumption in women was not associated with risk of total (IVW random-effects; odds ratio (OR): 0.91, 95% confidence intervals (CI): 0.80-1.02, P: 0.12, P for instrument heterogeneity: 7.17e-13), ER-positive (OR = 0.90, 95% CI: 0.79-1.02, P: 0.09) and ER-negative breast cancer (OR: 0.88, 95% CI: 0.75-1.03, P: 0.12). Null associations were also found in the sensitivity analyses using MR-Egger (total breast cancer; OR: 1.00, 95% CI: 0.80-1.25), weighted median (OR: 0.97, 95% CI: 0.89-1.05) and weighted mode (OR: 1.00, CI: 0.93-1.07). CONCLUSIONS The results of this large MR study do not support an association of genetically predicted coffee consumption on breast cancer risk, but we cannot rule out existence of a weak association.
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Affiliation(s)
- Merete Ellingjord-Dale
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Nikos Papadimitriou
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Michail Katsoulis
- Institute of Health Informatics Research, Faculty of Population Health Sciences, University College London, London, United Kingdom
| | - Chew Yee
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Niki Dimou
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Dagfinn Aune
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Nutrition, Bjørknes University College, Oslo, Norway
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
| | - Jue-Sheng Ong
- Statistical Genetics, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Stuart MacGregor
- Statistical Genetics, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Benjamin Elsworth
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Sarah J. Lewis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Richard M. Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, United Kingdom
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Konstantinos K. Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece
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18
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Katsoulis M, Gomes M, Lai AG, Henry A, Denaxas S, Lagiou P, Nafilyan V, Humberstone B, Banerjee A, Hemingway H, Lumbers RT. Estimating the Effect of Reduced Attendance at Emergency Departments for Suspected Cardiac Conditions on Cardiac Mortality During the COVID-19 Pandemic. Circ Cardiovasc Qual Outcomes 2020; 14:e007085. [PMID: 33342219 PMCID: PMC7819531 DOI: 10.1161/circoutcomes.120.007085] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Michail Katsoulis
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom
| | - Manuel Gomes
- Institute of Epidemiology & Health Care (M.G.), University College London, United Kingdom
| | - Alvina G Lai
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom
| | - Albert Henry
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom
| | - Spiros Denaxas
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,The National Institute for Health Research University College London Hospitals Biomedical Research Centre (S.D., H.H., R.T.L), University College London, United Kingdom.,British Heart Foundation Research Accelerator (S.D.), University College London, United Kingdom.,The Alan Turing Institute, London, United Kingdom (S.D.)
| | - Pagona Lagiou
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Greece (P.L.).,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (P.L.)
| | - Vahe Nafilyan
- Office for National Statistics, Newport, United Kingdom (V.N., B.H.)
| | - Ben Humberstone
- Office for National Statistics, Newport, United Kingdom (V.N., B.H.)
| | - Amitava Banerjee
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Amrita Institute of Medical Sciences, Kochi, India (A.B.)
| | - Harry Hemingway
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom
| | - R Thomas Lumbers
- Institute of Health Informatics (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,Health Data Research UK London (M.K., A.G.L., A.H., S.D., A.B., H.H., R.T.L.), University College London, United Kingdom.,The National Institute for Health Research University College London Hospitals Biomedical Research Centre (S.D., H.H., R.T.L), University College London, United Kingdom.,Bart's Heart Centre, St. Bartholomew's Hospital, London, United Kingdom (R.T.L.)
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19
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Abstract
Many studies have focused on investigating deviations from additive interaction of two dichotomous risk factors on a binary outcome. There is, however, a gap in the literature with respect to interactions on the additive scale of >2 risk factors. In this paper, we present an approach for examining deviations from additive interaction among three or more binary exposures. The relative excess risk due to interaction (RERI) is used as measure of additive interaction. First, we concentrate on three risk factors – we propose to decompose the total RERI to: the RERI owned to the joint presence of all three risk factors and the RERI of any two risk factors, given that the third is absent. We then extend this approach, to >3 binary risk factors. For illustration, we use a sample from data from the Greek EPIC cohort and we investigate the association with overall mortality of Mediterranean diet, body mass index , and smoking. Our formulae enable better interpretability of any evidence for deviations from additivity owned to more than two risk factors and provide simple ways of communicating such results from a public health perspective by attributing any excess relative risk to specific combinations of these factors. Abbreviations: BMI: Body Mass Index; ERR: excess relative risk; EPIC: European Prospective Investigation into Cancer and nutrition; MD: Mediterranean diet; RERI: relative excess risk due to interaction; RR: relative risk; TotRERI: total relative excess risk due to interaction
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Affiliation(s)
- Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK.,Hellenic Health Foundation, Athens, Greece
| | - Manuel Gomes
- Institute of Epidemiology & Health Care, University College London, London, UK
| | - Christina Bamia
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
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20
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Lai AG, Pasea L, Banerjee A, Hall G, Denaxas S, Chang WH, Katsoulis M, Williams B, Pillay D, Noursadeghi M, Linch D, Hughes D, Forster MD, Turnbull C, Fitzpatrick NK, Boyd K, Foster GR, Enver T, Nafilyan V, Humberstone B, Neal RD, Cooper M, Jones M, Pritchard-Jones K, Sullivan R, Davie C, Lawler M, Hemingway H. Estimated impact of the COVID-19 pandemic on cancer services and excess 1-year mortality in people with cancer and multimorbidity: near real-time data on cancer care, cancer deaths and a population-based cohort study. BMJ Open 2020; 10:e043828. [PMID: 33203640 PMCID: PMC7674020 DOI: 10.1136/bmjopen-2020-043828] [Citation(s) in RCA: 185] [Impact Index Per Article: 46.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/20/2020] [Accepted: 10/23/2020] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVES To estimate the impact of the COVID-19 pandemic on cancer care services and overall (direct and indirect) excess deaths in people with cancer. METHODS We employed near real-time weekly data on cancer care to determine the adverse effect of the pandemic on cancer services. We also used these data, together with national death registrations until June 2020 to model deaths, in excess of background (pre-COVID-19) mortality, in people with cancer. Background mortality risks for 24 cancers with and without COVID-19-relevant comorbidities were obtained from population-based primary care cohort (Clinical Practice Research Datalink) on 3 862 012 adults in England. RESULTS Declines in urgent referrals (median=-70.4%) and chemotherapy attendances (median=-41.5%) to a nadir (lowest point) in the pandemic were observed. By 31 May, these declines have only partially recovered; urgent referrals (median=-44.5%) and chemotherapy attendances (median=-31.2%). There were short-term excess death registrations for cancer (without COVID-19), with peak relative risk (RR) of 1.17 at week ending on 3 April. The peak RR for all-cause deaths was 2.1 from week ending on 17 April. Based on these findings and recent literature, we modelled 40% and 80% of cancer patients being affected by the pandemic in the long-term. At 40% affected, we estimated 1-year total (direct and indirect) excess deaths in people with cancer as between 7165 and 17 910, using RRs of 1.2 and 1.5, respectively, where 78% of excess deaths occured in patients with ≥1 comorbidity. CONCLUSIONS Dramatic reductions were detected in the demand for, and supply of, cancer services which have not fully recovered with lockdown easing. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is urgent to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks.
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Affiliation(s)
- Alvina G Lai
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
| | - Laura Pasea
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
- Barts Health NHS Trust, The Royal London Hospital, Whitechapel Rd, London, UK
| | - Geoff Hall
- DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners, London, UK
- Leeds Institute of Medical Research, University of Leeds, Leeds, UK
- Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- The Alan Turing Institute, London, UK
| | - Wai Hoong Chang
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
| | - Bryan Williams
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- Institute of Cardiovascular Science, University College London, London, UK
- University College London Hospitals NHS Trust, London, UK
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, UK
| | - Mahdad Noursadeghi
- Division of Infection and Immunity, University College London, London, UK
| | - David Linch
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
- Department of Hematology, University College London Cancer Institute, London, UK
| | - Derralynn Hughes
- University College London Cancer Institute, London, UK
- Royal Free NHS Foundation Trust, London, UK
| | - Martin D Forster
- University College London Hospitals NHS Trust, London, UK
- University College London Cancer Institute, London, UK
| | - Clare Turnbull
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Natalie K Fitzpatrick
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
| | - Kathryn Boyd
- Northern Ireland Cancer Network, Northern Ireland, UK
| | - Graham R Foster
- Barts Liver Centre, Blizard Institute, Queen Mary University of London, London, UK
| | - Tariq Enver
- University College London Cancer Institute, London, UK
| | | | | | - Richard D Neal
- Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Matt Cooper
- DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners, London, UK
- Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Monica Jones
- DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners, London, UK
- Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Kathy Pritchard-Jones
- DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners, London, UK
- UCLPartners Academic Health Science Partnership, London, UK
- Centre for Cancer Outcomes, University College London Hospitals NHS Foundation Trust, London, UK
- UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Richard Sullivan
- Conflict and Health Research Group, Institute of Cancer Policy, King's College London, London, UK
| | - Charlie Davie
- DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners, London, UK
- Royal Free NHS Foundation Trust, London, UK
- UCLPartners Academic Health Science Partnership, London, UK
| | - Mark Lawler
- DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners, London, UK
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, Belfast, UK
| | - Harry Hemingway
- Institute of Health Informatics, University College London, London, UK
- Health Data Research UK, University College London, London, UK
- University College London Hospitals NIHR Biomedical Research Centre, London, UK
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21
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Banerjee A, Katsoulis M, Lai AG, Pasea L, Treibel TA, Manisty C, Denaxas S, Quarta G, Hemingway H, Cavalcante JL, Noursadeghi M, Moon JC. Clinical academic research in the time of Corona: A simulation study in England and a call for action. PLoS One 2020; 15:e0237298. [PMID: 32790708 PMCID: PMC7425844 DOI: 10.1371/journal.pone.0237298] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 07/24/2020] [Indexed: 01/17/2023] Open
Abstract
OBJECTIVES We aimed to model the impact of coronavirus (COVID-19) on the clinical academic response in England, and to provide recommendations for COVID-related research. DESIGN A stochastic model to determine clinical academic capacity in England, incorporating the following key factors which affect the ability to conduct research in the COVID-19 climate: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics). SETTING Clinical academics in primary and secondary care in England. PARTICIPANTS Equivalent of 3200 full-time clinical academics in England. INTERVENTIONS Four policy approaches to COVID-19 with differing population infection rates: "Italy model" (6%), "mitigation" (10%), "relaxed mitigation" (40%) and "do-nothing" (80%) scenarios. Low and high strain on the health system (no clinical academics able to do research at 10% and 5% infection rate, respectively. MAIN OUTCOME MEASURES Number of full-time clinical academics available to conduct clinical research during the pandemic in England. RESULTS In the "Italy model", "mitigation", "relaxed mitigation" and "do-nothing" scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively-with no clinical academics at all for 37 days in the "do-nothing" scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11, 12, 30 and 26 weeks respectively. CONCLUSIONS Pandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.
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Affiliation(s)
- Amitava Banerjee
- Barts NHS Trust, London, United Kingdom
- Health Data Research UK, University College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Michail Katsoulis
- Health Data Research UK, University College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Alvina G. Lai
- Health Data Research UK, University College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Laura Pasea
- Health Data Research UK, University College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Thomas A. Treibel
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Charlotte Manisty
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Spiros Denaxas
- Health Data Research UK, University College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - Giovanni Quarta
- Department of Cardiology, Ospedale Papa Giovanni XXIII, Bergamo, Italy
| | - Harry Hemingway
- Health Data Research UK, University College London, London, United Kingdom
- Institute of Health Informatics, University College London, London, United Kingdom
| | - João L. Cavalcante
- Minneapolis Heart Institute, Minneapolis, Minnesota, United States America
| | - Mahdad Noursadeghi
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - James C. Moon
- Barts NHS Trust, London, United Kingdom
- Institute of Cardiovascular Science, University College London, London, United Kingdom
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22
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Scully PR, Patel KP, Treibel TA, Thornton GD, Hughes RK, Chadalavada S, Katsoulis M, Hartman N, Fontana M, Pugliese F, Sabharwal N, Newton JD, Kelion A, Ozkor M, Kennon S, Mullen M, Lloyd G, Menezes LJ, Hawkins PN, Moon JC. Prevalence and outcome of dual aortic stenosis and cardiac amyloid pathology in patients referred for transcatheter aortic valve implantation. Eur Heart J 2020; 41:2759-2767. [PMID: 32267922 PMCID: PMC7395329 DOI: 10.1093/eurheartj/ehaa170] [Citation(s) in RCA: 108] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 12/07/2019] [Accepted: 03/05/2020] [Indexed: 12/20/2022] Open
Abstract
AIMS Cardiac amyloidosis is common in elderly patients with aortic stenosis (AS) referred for transcatheter aortic valve implantation (TAVI). We hypothesized that patients with dual aortic stenosis and cardiac amyloid pathology (AS-amyloid) would have different baseline characteristics, periprocedural and mortality outcomes. METHODS AND RESULTS Patients aged ≥75 with severe AS referred for TAVI at two sites underwent blinded bone scintigraphy prior to intervention (Perugini Grade 0 negative, 1-3 increasingly positive). Baseline assessment included echocardiography, electrocardiogram (ECG), blood tests, 6-min walk test, and health questionnaire, with periprocedural complications and mortality follow-up. Two hundred patients were recruited (aged 85 ± 5 years, 50% male). AS-amyloid was found in 26 (13%): 8 Grade 1, 18 Grade 2. AS-amyloid patients were older (88 ± 5 vs. 85 ± 5 years, P = 0.001), with reduced quality of life (EQ-5D-5L 50 vs. 65, P = 0.04). Left ventricular wall thickness was higher (14 mm vs. 13 mm, P = 0.02), ECG voltages lower (Sokolow-Lyon 1.9 ± 0.7 vs. 2.5 ± 0.9 mV, P = 0.03) with lower voltage/mass ratio (0.017 vs. 0.025 mV/g/m2, P = 0.03). High-sensitivity troponin T and N-terminal pro-brain natriuretic peptide were higher (41 vs. 21 ng/L, P < 0.001; 3702 vs. 1254 ng/L, P = 0.001). Gender, comorbidities, 6-min walk distance, AS severity, prevalence of disproportionate hypertrophy, and post-TAVI complication rates (38% vs. 35%, P = 0.82) were the same. At a median follow-up of 19 (10-27) months, there was no mortality difference (P = 0.71). Transcatheter aortic valve implantation significantly improved outcome in the overall population (P < 0.001) and in those with AS-amyloid (P = 0.03). CONCLUSIONS AS-amyloid is common and differs from lone AS. Transcatheter aortic valve implantation significantly improved outcome in AS-amyloid, while periprocedural complications and mortality were similar to lone AS, suggesting that TAVI should not be denied to patients with AS-amyloid.
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Affiliation(s)
- Paul R Scully
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
| | - Kush P Patel
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
| | - Thomas A Treibel
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
| | - George D Thornton
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
| | - Rebecca K Hughes
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
| | | | - Michail Katsoulis
- Institute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, UK
| | - Neil Hartman
- Nuclear Medicine, Abertawe Bro Morgannwg University Health Board, 4 Seaway Parade, Port Talbot SA12 7BR, UK
| | - Marianna Fontana
- National Amyloidosis Centre, University College London, Rowland Hill Street, London NW3 2PF, UK
| | - Francesca Pugliese
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Nikant Sabharwal
- John Radcliffe Hospital, Oxford University Hospitals, Headley Way, Headington, Oxford OX3 9DU, UK
| | - James D Newton
- John Radcliffe Hospital, Oxford University Hospitals, Headley Way, Headington, Oxford OX3 9DU, UK
| | - Andrew Kelion
- John Radcliffe Hospital, Oxford University Hospitals, Headley Way, Headington, Oxford OX3 9DU, UK
| | - Muhiddin Ozkor
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
| | - Simon Kennon
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
| | - Michael Mullen
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
| | - Guy Lloyd
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
- William Harvey Research Institute, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Leon J Menezes
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Nuclear Medicine, University College London, 235 Euston Road, London NW1 2BU, UK
- NIHR University College London Hospitals Biomedical Research Centre, 149 Tottenham Court Road, London W1T 7DN, UK
| | - Philip N Hawkins
- National Amyloidosis Centre, University College London, Rowland Hill Street, London NW3 2PF, UK
| | - James C Moon
- Barts Heart Centre, St Bartholomew’s Hospital, West Smithfield, London EC1A 7BE, UK
- Institute of Cardiovascular Science, University College London, Gower Street, London WC1E 6BT, UK
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Henry A, Katsoulis M, Masi S, Fatemifar G, Denaxas S, Acosta D, Garfield V, Dale CE. The relationship between sleep duration, cognition and dementia: a Mendelian randomization study. Int J Epidemiol 2019; 48:849-860. [PMID: 31062029 PMCID: PMC6659373 DOI: 10.1093/ije/dyz071] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/26/2019] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Short and long sleep duration have been linked with poorer cognitive outcomes, but it remains unclear whether these associations are causal. METHODS We conducted the first Mendelian randomization (MR) study with 77 single-nucleotide polymorphisms (SNPs) for sleep duration using individual-participant data from the UK Biobank cohort (N = 395 803) and summary statistics from the International Genomics of Alzheimer's Project (N cases/controls = 17 008/37 154) to investigate the potential impact of sleep duration on cognitive outcomes. RESULTS Linear MR suggested that each additional hour/day of sleep was associated with 1% [95% confidence interval (CI) = 0-2%; P = 0.008] slower reaction time and 3% more errors in visual-memory test (95% CI = 0-6%; P = 0.05). There was little evidence to support associations of increased sleep duration with decline in visual memory [odds ratio (OR) per additional hour/day of sleep = 1.10 (95% CI = 0.76-1.57); P = 0.62], decline in reaction time [OR = 1.28 (95% CI = 0.49-3.35); P = 0.61], all-cause dementia [OR = 1.19 (95% CI = 0.65-2.19); P = 0.57] or Alzheimer's disease risk [OR = 0.89 (95% CI = 0.67-1.18); P = 0.41]. Non-linear MR suggested that both short and long sleep duration were associated with poorer visual memory (P for non-linearity = 3.44e-9) and reaction time (P for non-linearity = 6.66e-16). CONCLUSIONS Linear increase in sleep duration has a small negative effect on reaction time and visual memory, but the true association might be non-linear, with evidence of associations for both short and long sleep duration. These findings suggest that sleep duration may represent a potential causal pathway for cognition.
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Affiliation(s)
- Albert Henry
- Institute of Health Informatics, University College London, London, UK
- Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, UK
| | - Michail Katsoulis
- Institute of Health Informatics, University College London, London, UK
| | - Stefano Masi
- Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, UK
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | - Spiros Denaxas
- Institute of Health Informatics, University College London, London, UK
| | - Dionisio Acosta
- Institute of Health Informatics, University College London, London, UK
| | - Victoria Garfield
- Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, UK
| | - Caroline E Dale
- Institute of Health Informatics, University College London, London, UK
- Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, University College London, London, UK
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Parisinos CA, Serghiou S, Katsoulis M, George MJ, Patel RS, Hemingway H, Hingorani AD. Variation in Interleukin 6 Receptor Gene Associates With Risk of Crohn's Disease and Ulcerative Colitis. Gastroenterology 2018; 155:303-306.e2. [PMID: 29775600 PMCID: PMC6083435 DOI: 10.1053/j.gastro.2018.05.022] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 04/27/2018] [Accepted: 05/06/2018] [Indexed: 12/02/2022]
Abstract
Interleukin 6 (IL6) is an inflammatory cytokine; signaling via its receptor (IL6R) is believed to contribute to development of inflammatory bowel diseases (IBD). The single nucleotide polymorphism rs2228145 in IL6R associates with increased levels of soluble IL6R (s-IL6R), as well as reduced IL6R signaling and risk of inflammatory disorders; its effects are similar to those of a therapeutic monoclonal antibody that blocks IL6R signaling. We used the effect of rs2228145 on s-IL6R level as an indirect marker to investigate whether reduced IL6R signaling associates with risk of ulcerative colitis (UC) or Crohn's disease (CD). In a genome-wide meta-analysis of 20,550 patients with CD, 17,647 patients with UC, and more than 40,000 individuals without IBD (controls), we found that rs2228145 (scaled to a 2-fold increase in s-IL6R) was associated with reduced risk of CD (odds ratio 0.876; 95% confidence interval 0.822-0.933; P = .00003) or UC (odds ratio 0.932; 95% confidence interval 0.875-0.996; P = .036). These findings indicate that therapeutics designed to block IL6R signaling might be effective in treatment of IBD.
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Affiliation(s)
- Constantinos A Parisinos
- Institute of Health Informatics Research, Faculty of Population Health Sciences, University College London, London, UK.
| | - Stylianos Serghiou
- Health Research and Policy, Epidemiology, Stanford University, Stanford, CA
| | - Michail Katsoulis
- Institute of Health Informatics Research, Faculty of Population Health Sciences, University College London, London, UK
| | - Marc Jonathan George
- Centre for Clinical Pharmacology, Division of Medicine, University College London, London, UK
| | - Riyaz S Patel
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
| | - Harry Hemingway
- Institute of Health Informatics Research, Faculty of Population Health Sciences, University College London, London, UK
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
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Hedström AK, Hössjer O, Katsoulis M, Kockum I, Olsson T, Alfredsson L. Organic solvents and MS susceptibility: Interaction with MS risk HLA genes. Neurology 2018; 91:e455-e462. [PMID: 29970406 PMCID: PMC6093765 DOI: 10.1212/wnl.0000000000005906] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Accepted: 04/27/2018] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE We hypothesize that different sources of lung irritation may contribute to elicit an immune reaction in the lungs and subsequently lead to multiple sclerosis (MS) in people with a genetic susceptibility to the disease. We aimed to investigate the influence of exposure to organic solvents on MS risk, and a potential interaction between organic solvents and MS risk human leukocyte antigen (HLA) genes. METHODS Using a Swedish population-based case-control study (2,042 incident cases of MS and 2,947 controls), participants with different genotypes, smoking habits, and exposures to organic solvents were compared regarding occurrence of MS, by calculating odds ratios with 95% confidence intervals using logistic regression. A potential interaction between exposure to organic solvents and MS risk HLA genes was evaluated by calculating the attributable proportion due to interaction. RESULTS Overall, exposure to organic solvents increased the risk of MS (odds ratio 1.5, 95% confidence interval 1.2-1.8, p = 0.0004). Among both ever and never smokers, an interaction between organic solvents, carriage of HLA-DRB1*15, and absence of HLA-A*02 was observed with regard to MS risk, similar to the previously reported gene-environment interaction involving the same MS risk HLA genes and smoke exposure. CONCLUSION The mechanism linking both smoking and exposure to organic solvents to MS risk may involve lung inflammation with a proinflammatory profile. Their interaction with MS risk HLA genes argues for an action of these environmental factors on adaptive immunity, perhaps through activation of autoaggressive cells resident in the lungs subsequently attacking the CNS.
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Affiliation(s)
- Anna Karin Hedström
- From the Department of Clinical Neuroscience and Institute of Environmental Medicine (A.K.H., L.A.), and Department of Clinical Neuroscience and Center for Molecular Medicine (I.K., T.O.), Karolinska Institutet, Stockholm; Mathematical Statistics (O.H.), Stockholm University, Sweden; UCL/Farr Institute of Health Informatics Research (M.K.), London, UK; and Centre for Occupational and Environmental Medicine (L.A.), Stockholm County Council, Sweden.
| | - Ola Hössjer
- From the Department of Clinical Neuroscience and Institute of Environmental Medicine (A.K.H., L.A.), and Department of Clinical Neuroscience and Center for Molecular Medicine (I.K., T.O.), Karolinska Institutet, Stockholm; Mathematical Statistics (O.H.), Stockholm University, Sweden; UCL/Farr Institute of Health Informatics Research (M.K.), London, UK; and Centre for Occupational and Environmental Medicine (L.A.), Stockholm County Council, Sweden
| | - Michail Katsoulis
- From the Department of Clinical Neuroscience and Institute of Environmental Medicine (A.K.H., L.A.), and Department of Clinical Neuroscience and Center for Molecular Medicine (I.K., T.O.), Karolinska Institutet, Stockholm; Mathematical Statistics (O.H.), Stockholm University, Sweden; UCL/Farr Institute of Health Informatics Research (M.K.), London, UK; and Centre for Occupational and Environmental Medicine (L.A.), Stockholm County Council, Sweden
| | - Ingrid Kockum
- From the Department of Clinical Neuroscience and Institute of Environmental Medicine (A.K.H., L.A.), and Department of Clinical Neuroscience and Center for Molecular Medicine (I.K., T.O.), Karolinska Institutet, Stockholm; Mathematical Statistics (O.H.), Stockholm University, Sweden; UCL/Farr Institute of Health Informatics Research (M.K.), London, UK; and Centre for Occupational and Environmental Medicine (L.A.), Stockholm County Council, Sweden
| | - Tomas Olsson
- From the Department of Clinical Neuroscience and Institute of Environmental Medicine (A.K.H., L.A.), and Department of Clinical Neuroscience and Center for Molecular Medicine (I.K., T.O.), Karolinska Institutet, Stockholm; Mathematical Statistics (O.H.), Stockholm University, Sweden; UCL/Farr Institute of Health Informatics Research (M.K.), London, UK; and Centre for Occupational and Environmental Medicine (L.A.), Stockholm County Council, Sweden
| | - Lars Alfredsson
- From the Department of Clinical Neuroscience and Institute of Environmental Medicine (A.K.H., L.A.), and Department of Clinical Neuroscience and Center for Molecular Medicine (I.K., T.O.), Karolinska Institutet, Stockholm; Mathematical Statistics (O.H.), Stockholm University, Sweden; UCL/Farr Institute of Health Informatics Research (M.K.), London, UK; and Centre for Occupational and Environmental Medicine (L.A.), Stockholm County Council, Sweden
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26
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Lassale C, Tzoulaki I, Moons KG, Sweeting M, Boer J, Johnson L, Huerta JM, Agnoli C, Freisling H, Weiderpass E, Wennberg P, van der A D, Arriola L, Benetou V, Boeing H, Bonnet F, Colorado-Yohar SM, Engström G, Eriksen AK, Ferrari P, Grioni S, Johansson M, Kaaks R, Katsoulis M, Katzke V, Key TJ, Matullo G, Melander O, Molina-Portillo E, Moreno-Iribas C, Norberg M, Overvad K, Panico S, Quirós JR, Saieva C, Skeie G, Steffen A, Stepien M, Tjønneland A, Trichopoulou A, Tumino R, van der Schouw YT, Verschuren W, Langenberg C, Di Angelantonio E, Riboli E, Wareham NJ, Danesh J, Butterworth AS. Separate and combined associations of obesity and metabolic health with coronary heart disease: a pan-European case-cohort analysis. Eur Heart J 2018; 39:397-406. [PMID: 29020414 PMCID: PMC6198928 DOI: 10.1093/eurheartj/ehx448] [Citation(s) in RCA: 173] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Accepted: 07/18/2017] [Indexed: 12/13/2022] Open
Abstract
Aims The hypothesis of 'metabolically healthy obesity' implies that, in the absence of metabolic dysfunction, individuals with excess adiposity are not at greater cardiovascular risk. We tested this hypothesis in a large pan-European prospective study. Methods and results We conducted a case-cohort analysis in the 520 000-person European Prospective Investigation into Cancer and Nutrition study ('EPIC-CVD'). During a median follow-up of 12.2 years, we recorded 7637 incident coronary heart disease (CHD) cases. Using cut-offs recommended by guidelines, we defined obesity and overweight using body mass index (BMI), and metabolic dysfunction ('unhealthy') as ≥ 3 of elevated blood pressure, hypertriglyceridaemia, low HDL-cholesterol, hyperglycaemia, and elevated waist circumference. We calculated hazard ratios (HRs) and 95% confidence intervals (95% CI) within each country using Prentice-weighted Cox proportional hazard regressions, accounting for age, sex, centre, education, smoking, diet, and physical activity. Compared with metabolically healthy normal weight people (reference), HRs were 2.15 (95% CI: 1.79; 2.57) for unhealthy normal weight, 2.33 (1.97; 2.76) for unhealthy overweight, and 2.54 (2.21; 2.92) for unhealthy obese people. Compared with the reference group, HRs were 1.26 (1.14; 1.40) and 1.28 (1.03; 1.58) for metabolically healthy overweight and obese people, respectively. These results were robust to various sensitivity analyses. Conclusion Irrespective of BMI, metabolically unhealthy individuals had higher CHD risk than their healthy counterparts. Conversely, irrespective of metabolic health, overweight and obese people had higher CHD risk than lean people. These findings challenge the concept of 'metabolically healthy obesity', encouraging population-wide strategies to tackle obesity.
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Affiliation(s)
- Camille Lassale
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Karel G.M. Moons
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Michael Sweeting
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jolanda Boer
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Laura Johnson
- Centre for Exercise, Nutrition and Health Sciences, School for Policy Studies, University of Bristol, Bristol, United Kingdom
| | - José María Huerta
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Heinz Freisling
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Elisabete Weiderpass
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
- Department of Research, Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Genetic Epidemiology Group, Folkhälsan Research Center, Helsinki, Finland
| | - Patrik Wennberg
- Department of Public Health and Clinical Medicine, Family medicine, Umeå University, Umeå, Sweden
| | - Daphne van der A
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Larraitz Arriola
- Public Health Division of Gipuzkoa, Instituto Bio-Donostia, Basque Government
| | - Vassiliki Benetou
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Dept. of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Greece
- Hellenic Health Foundation, Athens, Greece
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany
| | - Fabrice Bonnet
- Université de Rennes 1, CHU de Rennes, Rennes, France
- Inserm (Institut National De La Santé Et De La Recherche Médical), Centre for Research in Epidemiology and Population Health (CESP), U1018, Villejuif, France
| | - Sandra M. Colorado-Yohar
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- National School of Public Health, Research Group on Demography and Health, University of Antioquia, Medellín, Colombia
| | - Gunnar Engström
- Dept Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Anne K Eriksen
- Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Pietro Ferrari
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Matthias Johansson
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | | | - Verena Katzke
- German Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Heidelberg, Germany
| | - Timothy J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health University of Oxford, Oxford, United Kingdom
| | - Giuseppe Matullo
- Human Genetics Foundation, Turin, Italy
- Department of Medical Sciences, University of Turin, Italy
| | - Olle Melander
- Dept Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Elena Molina-Portillo
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
- Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.GRANADA. Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
| | | | - Margareta Norberg
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden
| | - Kim Overvad
- Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
- Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | | | - Calogero Saieva
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Guri Skeie
- Department of community medicine, University of Tromsø – the Arctic University of Norway, Tromsø, Norway
| | - Annika Steffen
- Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany
| | - Magdalena Stepien
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Anne Tjønneland
- Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Antonia Trichopoulou
- WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Dept. of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Greece
- Hellenic Health Foundation, Athens, Greece
| | - Rosario Tumino
- Cancer Registry and Histopathology Unit, Civic - M.P. Arezzo Hospital, ASP Ragusa, Italy
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - W.M.Monique Verschuren
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Emanuele Di Angelantonio
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Elio Riboli
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Nicholas J Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Dept of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK
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Chajès V, Assi N, Biessy C, Ferrari P, Rinaldi S, Slimani N, Lenoir GM, Baglietto L, His M, Boutron-Ruault MC, Trichopoulou A, Lagiou P, Katsoulis M, Kaaks R, Kühn T, Panico S, Pala V, Masala G, Bueno-de-Mesquita HB, Peeters PH, van Gils C, Hjartåker A, Standahl Olsen K, Borgund Barnung R, Barricarte A, Redondo-Sanchez D, Menéndez V, Amiano P, Wennberg M, Key T, Khaw KT, Merritt MA, Riboli E, Gunter MJ, Romieu I. A prospective evaluation of plasma phospholipid fatty acids and breast cancer risk in the EPIC study. Ann Oncol 2017; 28:2836-2842. [PMID: 28950350 DOI: 10.1093/annonc/mdx482] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/08/2023] Open
Abstract
BACKGROUND Intakes of specific fatty acids have been postulated to impact breast cancer risk but epidemiological data based on dietary questionnaires remain conflicting. MATERIALS AND METHODS We assessed the association between plasma phospholipid fatty acids and breast cancer risk in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition study. Sixty fatty acids were measured by gas chromatography in pre-diagnostic plasma phospholipids from 2982 incident breast cancer cases matched to 2982 controls. Conditional logistic regression models were used to estimate relative risk of breast cancer by fatty acid level. The false discovery rate (q values) was computed to control for multiple comparisons. Subgroup analyses were carried out by estrogen receptor (ER) and progesterone receptor expression in the tumours. RESULTS A high level of palmitoleic acid [odds ratio (OR) for the highest quartile compared with the lowest OR (Q4-Q1) 1.37; 95% confidence interval (CI), 1.14-1.64; P for trend = 0.0001, q value = 0.004] as well as a high desaturation index (DI16) (16:1n-7/16:0) [OR (Q4-Q1), 1.28; 95% C, 1.07-1.54; P for trend = 0.002, q value = 0.037], as biomarkers of de novo lipogenesis, were significantly associated with increased risk of breast cancer. Levels of industrial trans-fatty acids were positively associated with ER-negative tumours [OR for the highest tertile compared with the lowest (T3-T1)=2.01; 95% CI, 1.03-3.90; P for trend = 0.047], whereas no association was found for ER-positive tumours (P-heterogeneity =0.01). No significant association was found between n-3 polyunsaturated fatty acids and breast cancer risk, overall or by hormonal receptor. CONCLUSION These findings suggest that increased de novo lipogenesis, acting through increased synthesis of palmitoleic acid, could be a relevant metabolic pathway for breast tumourigenesis. Dietary trans-fatty acids derived from industrial processes may specifically increase ER-negative breast cancer risk.
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Affiliation(s)
- V Chajès
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon.
| | - N Assi
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
| | - C Biessy
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
| | - P Ferrari
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
| | - S Rinaldi
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
| | - N Slimani
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
| | | | - L Baglietto
- Institut Gustave Roussy, Villejuif; Université Paris-Saclay, Université Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
| | - M His
- Institut Gustave Roussy, Villejuif; Université Paris-Saclay, Université Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
| | - M C Boutron-Ruault
- Institut Gustave Roussy, Villejuif; Université Paris-Saclay, Université Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France
| | - A Trichopoulou
- Hellenic Health Foundation, Athens; WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - P Lagiou
- Hellenic Health Foundation, Athens; WHO Collaborating Center for Nutrition and Health, Unit of Nutritional Epidemiology and Nutrition in Public Health, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece; Department of Epidemiology, Harvard School of Public Health, Boston, USA
| | | | - R Kaaks
- The German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - T Kühn
- The German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - S Panico
- Dipartimento Di Medicina Clinica E Chirurgia, Federico II University, Naples
| | - V Pala
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan
| | - G Masala
- Cancer Risk Factors and Life-Style Epidemiology Unit, Cancer Research and Prevention Institute - ISPO, Florence, Italy
| | - H B Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK; Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - P H Peeters
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - C van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - A Hjartåker
- Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo
| | - K Standahl Olsen
- Department of Community Medicine, University of Tromsø-UiT-The Artic University of Norway, Tromsø, Norway
| | - R Borgund Barnung
- Department of Community Medicine, University of Tromsø-UiT-The Artic University of Norway, Tromsø, Norway
| | - A Barricarte
- Navarra Public Health Institute, Pamplona; Navarra Institute for Health Research (IdiSNA), Pamplona; CIBER Epidemiology and Public Health CIBERESP, Madrid
| | - D Redondo-Sanchez
- CIBER Epidemiology and Public Health CIBERESP, Madrid; Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.Granada, Hospitales Universitarios de Granada, Granada; Universidad de Granada, Granada
| | | | - P Amiano
- CIBER Epidemiology and Public Health CIBERESP, Madrid; Public Health Division of Gipuzkoa, Health Department, Basque Region, San Sebastian, Spain
| | - M Wennberg
- Public Health and Clinical Medicine, Nutritional Research, Umeå University, Umeå, Sweden
| | - T Key
- The Cancer Epidemiology Unit, University of Oxford, Oxford
| | - K T Khaw
- University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - M A Merritt
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - E Riboli
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - M J Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
| | - I Romieu
- Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon
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28
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Hedström AK, Katsoulis M, Hössjer O, Bomfim IL, Oturai A, Sondergaard HB, Sellebjerg F, Ullum H, Thørner LW, Gustavsen MW, Harbo HF, Obradovic D, Gianfrancesco MA, Barcellos LF, Schaefer CA, Hillert J, Kockum I, Olsson T, Alfredsson L. The interaction between smoking and HLA genes in multiple sclerosis: replication and refinement. Eur J Epidemiol 2017; 32:909-919. [PMID: 28597127 PMCID: PMC5680370 DOI: 10.1007/s10654-017-0250-2] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2016] [Accepted: 04/27/2017] [Indexed: 01/14/2023]
Abstract
Interactions between environment and genetics may contribute to multiple sclerosis (MS) development. We investigated whether the previously observed interaction between smoking and HLA genotype in the Swedish population could be replicated, refined and extended to include other populations. We used six independent case–control studies from five different countries (Sweden, Denmark, Norway, Serbia, United States). A pooled analysis was performed for replication of previous observations (7190 cases, 8876 controls). Refined detailed analyses were carried out by combining the genetically similar populations from the Nordic studies (6265 cases, 8401 controls). In both the pooled analyses and in the combined Nordic material, interactions were observed between HLA-DRB*15 and absence of HLA-A*02 and between smoking and each of the genetic risk factors. Two way interactions were observed between each combination of the three variables, invariant over categories of the third. Further, there was also a three way interaction between the risk factors. The difference in MS risk between the extremes was considerable; smokers carrying HLA-DRB1*15 and lacking HLA-A*02 had a 13-fold increased risk compared with never smokers without these genetic risk factors (OR 12.7, 95% CI 10.8–14.9). The risk of MS associated with HLA genotypes is strongly influenced by smoking status and vice versa. Since the function of HLA molecules is to present peptide antigens to T cells, the demonstrated interactions strongly suggest that smoking alters MS risk through actions on adaptive immunity.
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Affiliation(s)
- Anna Karin Hedström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Ola Hössjer
- Mathematical Statistics, Stockholm University, Stockholm, Sweden
| | - Izaura L. Bomfim
- Neuroimmunology Unit, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Annette Oturai
- Danish Multiple Sclerosis Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Helle Bach Sondergaard
- Danish Multiple Sclerosis Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Finn Sellebjerg
- Danish Multiple Sclerosis Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Ullum
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Lise Wegner Thørner
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Marte Wendel Gustavsen
- Department of Neurology, Oslo University Hospital, Ullevål, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Hanne F. Harbo
- Department of Neurology, Oslo University Hospital, Ullevål, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - Milena A. Gianfrancesco
- Genetic Epidemiology and Genomics Lab, Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3220 USA
| | - Lisa F. Barcellos
- Genetic Epidemiology and Genomics Lab, Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3220 USA
| | | | - Jan Hillert
- Neuroimmunology Unit, Department of Clinical Neuroscience and Center for Molecular Medicine, Karolinska Institutet at Karolinska University Hospital, Solna, Sweden
| | - Ingrid Kockum
- Neuroimmunology Unit, Department of Clinical Neuroscience and Center for Molecular Medicine, Karolinska Institutet at Karolinska University Hospital, Solna, Sweden
| | - Tomas Olsson
- Neuroimmunology Unit, Department of Clinical Neuroscience and Center for Molecular Medicine, Karolinska Institutet at Karolinska University Hospital, Solna, Sweden
| | - Lars Alfredsson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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Nimptsch K, Song M, Aleksandrova K, Katsoulis M, Freisling H, Jenab M, Gunter MJ, Tsilidis KK, Weiderpass E, Bueno-De-Mesquita HB, Chong DQ, Jensen MK, Wu C, Overvad K, Kühn T, Barrdahl M, Melander O, Jirström K, Peeters PH, Sieri S, Panico S, Cross AJ, Riboli E, Van Guelpen B, Myte R, Huerta JM, Rodriguez-Barranco M, Quirós JR, Dorronsoro M, Tjønneland A, Olsen A, Travis R, Boutron-Ruault MC, Carbonnel F, Severi G, Bonet C, Palli D, Janke J, Lee YA, Boeing H, Giovannucci EL, Ogino S, Fuchs CS, Rimm E, Wu K, Chan AT, Pischon T. Genetic variation in the ADIPOQ gene, adiponectin concentrations and risk of colorectal cancer: a Mendelian Randomization analysis using data from three large cohort studies. Eur J Epidemiol 2017; 32:419-430. [PMID: 28550647 PMCID: PMC5535815 DOI: 10.1007/s10654-017-0262-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 05/18/2017] [Indexed: 12/20/2022]
Abstract
Higher levels of circulating adiponectin have been related to lower risk of colorectal cancer in several prospective cohort studies, but it remains unclear whether this association may be causal. We aimed to improve causal inference in a Mendelian Randomization meta-analysis using nested case-control studies of the European Prospective Investigation into Cancer and Nutrition (EPIC, 623 cases, 623 matched controls), the Health Professionals Follow-up Study (HPFS, 231 cases, 230 controls) and the Nurses' Health Study (NHS, 399 cases, 774 controls) with available data on pre-diagnostic adiponectin concentrations and selected single nucleotide polymorphisms in the ADIPOQ gene. We created an ADIPOQ allele score that explained approximately 3% of the interindividual variation in adiponectin concentrations. The ADIPOQ allele score was not associated with risk of colorectal cancer in logistic regression analyses (pooled OR per score-unit unit 0.97, 95% CI 0.91, 1.04). Genetically determined twofold higher adiponectin was not significantly associated with risk of colorectal cancer using the ADIPOQ allele score as instrumental variable (pooled OR 0.73, 95% CI 0.40, 1.34). In a summary instrumental variable analysis (based on previously published data) with higher statistical power, no association between genetically determined twofold higher adiponectin and risk of colorectal cancer was observed (0.99, 95% CI 0.93, 1.06 in women and 0.94, 95% CI 0.88, 1.01 in men). Thus, our study does not support a causal effect of circulating adiponectin on colorectal cancer risk. Due to the limited genetic determination of adiponectin, larger Mendelian Randomization studies are necessary to clarify whether adiponectin is causally related to lower risk of colorectal cancer.
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Affiliation(s)
- Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Robert-Rössle-Straße 10, 13125, Berlin, Germany.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Mingyang Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Krasimira Aleksandrova
- Nutrition, Immunity and Metabolism Start-up Lab, Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbruecke, Nuthetal, Germany
| | - Michail Katsoulis
- Hellenic Health Foundation, Athens, Greece
- Farr Institute of Health Informatics Research at London, UCL, London, UK
| | - Heinz Freisling
- International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Mazda Jenab
- International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Elisabete Weiderpass
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
- Department of Research, Cancer Registry of Norway, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Samfundet Folkhälsan, Helsinki, Finland
| | - H Bas Bueno-De-Mesquita
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Dawn Q Chong
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Majken K Jensen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Chunsen Wu
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
- Odense University Hospital, Odense, Denmark
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Myrto Barrdahl
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Olle Melander
- Department of Clinical Sciences Lund, Lund University, Malmö, Sweden
| | - Karin Jirström
- Department of Clinical Sciences Lund, Lund University, Malmö, Sweden
| | - Petra H Peeters
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | | | - Robin Myte
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - José María Huerta
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Miguel Rodriguez-Barranco
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs, GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
| | | | - Miren Dorronsoro
- Public Health Direction and Biodonostia Research Institute- Ciberesp, Basque Regional Health Department, San Sebastian, Spain
| | | | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Ruth Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marie-Christine Boutron-Ruault
- Université Paris-Sud, UVSQ, CESP, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, 94805, Villejuif, France
| | - Franck Carbonnel
- Université Paris-Sud, UVSQ, CESP, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, 94805, Villejuif, France
- Department of Gastroenterology, Assistance Publique-Hôpitaux de Paris (AP-HP), University hospitals Paris-Sud, Site de Bicêtre, Paris Sud University, Paris XI, Le Kremlin Bicêtre, Villejuif, France
| | - Gianluca Severi
- Université Paris-Sud, UVSQ, CESP, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, 94805, Villejuif, France
- Human Genetics Foundation (HuGeF), Turin, Italy
- Cancer Council Victoria, Melbourne, Australia
- University of Melbourne, Melbourne, Australia
| | - Catalina Bonet
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Domenico Palli
- Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Jürgen Janke
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Robert-Rössle-Straße 10, 13125, Berlin, Germany
| | - Young-Ae Lee
- Genetics of Allergic Disease Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbruecke, Nuthetal, Germany
| | - Edward L Giovannucci
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
- Division of MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Charles S Fuchs
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Eric Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Kana Wu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Andrew T Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Robert-Rössle-Straße 10, 13125, Berlin, Germany
- Charité Universitätsmedizin, Berlin, Germany
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30
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Katsoulis M, Denaxas S, Patel R, Hemingway H. Low-density lipoprotein cholesterol and atrial fibrillation; A Mendelian randomization study using UK-Biobank data. Int J Popul Data Sci 2017. [PMCID: PMC9351030 DOI: 10.23889/ijpds.v1i1.322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Katsoulis M, La Vecchia C, Trichopoulou A, Lagiou P. Maternal height and breast cancer risk: results from a study nested within the EPIC-Greece cohort. Eur J Epidemiol 2017; 32:457-463. [PMID: 28417273 DOI: 10.1007/s10654-017-0245-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 04/06/2017] [Indexed: 12/27/2022]
Abstract
The positive association of adult height with breast cancer (BC) risk has been hypothesized to be partly accounted for by an association of this risk with maternal height (operating in utero to modify hormone effects). In a case-control study (271 BC patients and 791 controls) nested within the EPIC-Greece cohort, we applied mediation analysis to calculate the direct and indirect (through the woman's own height) effect of maternal height on BC risk. Per 5 cm increase in maternal height and depending on its reference value: the indirect effect odds ratio ranges from 1.02 to 1.07; the direct effect odds ratio from 1.06 to 1.11; and the total (direct and indirect effects) from 1.08 to 1.19. The effect sizes consistently increased for higher reference categories of maternal height, but did not generally reach statistical significance, possibly due to the limited sample size.
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Affiliation(s)
- Michail Katsoulis
- Hellenic Health Foundation, 13 Kaisareias and Alexandoupoleos Street, 115 27, Athens, Greece.,Farr Institute of Health Informatics Research, University College London, 222 Euston Road, London, NW1 2DA, UK
| | - Carlo La Vecchia
- Hellenic Health Foundation, 13 Kaisareias and Alexandoupoleos Street, 115 27, Athens, Greece.,Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Via Vanzetti, 5, 20133, Milan, Italy
| | - Antonia Trichopoulou
- Hellenic Health Foundation, 13 Kaisareias and Alexandoupoleos Street, 115 27, Athens, Greece.
| | - Pagona Lagiou
- Hellenic Health Foundation, 13 Kaisareias and Alexandoupoleos Street, 115 27, Athens, Greece.,Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 75 M. Asias Street, Goudi, 115 27, Athens, Greece.,Department of Epidemiology, Harvard T. H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA
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Karakatsani A, Katsoulis M, Klinaki E, Trichopoulou A. Kortykosteroidy a ryzyko złamania szyjki kości udowej u osób w podeszłym wieku cierpiących na choroby układu oddechowego: Wyniki analizy greckiej kohorty badania EPIC. Adv Respir Med 2017. [DOI: 10.5603/arm.50849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Wstęp: Wraz ze starzeniem się populacji w najbliższych latach należy spodziewać się wzrostu częstości występowania osteoporozy i chorób układu oddechowego. Kortykosteroidy—leki zwiększające ryzyko osteoporozy, są stosowane w różnych postaciach u chorych na schorzenia układu oddechowego, bez względu na zaawansowany wiek i zwiększone ryzyko złamań. Celem badania była ocena ryzyka złamania szyjki kości udowej u osób w wieku podeszłym, leczonych kortykosteroidami ze wskazań pulmonologicznych, z uwzględnieniem leków wziewnych. Materiał i metody: Dane na temat nowych złamań szyjki kości udowej zbierano za pomocą aktywnej obserwacji prospektywnej uczestników greckiego segmentu badania EPIC-Greece (EPIC-Greece, European Prospective Investigation into Cancer and Nutrition), którzy w momencie rekrutacji osiągnęli wiek co najmniej 60 lat i deklarowali chorobę układu oddechowego rozpoznaną przez lekarza. Dane na temat statusu socjoekonomicznego, stylu życia, stanu zdrowia oraz stosowania kortykosteroidów gromadzono za pomocą kwestionariuszy na początku i końcu badania. W celu oceny współczynnika ryzyka (HR) zastosowano model regresji Coxa, z uwzględnieniem czynników zakłócających. Wyniki: Stwierdzono wzrost ryzyka złamania szyjki kości udowej związany ze stosowaniem kortykosteroidów (HR: 1.68; 95% CI: 0.85–3.34). Zwiększone ryzyko utrzymywało się, gdy analizę ograniczono do osób przyjmujących jakiekolwiek kortykosteroidy z powodu chorób obturacyjnych (HR: 1.40; 95% CI: 0.64–3.06) oraz do osób przyjmujących wyłącznie leki wziewne (HR: 1.58; 95% CI: 0.71–3.50). Ta pozytywna zależność nie osiągnęła jednak poziomu istotności statystycznej, prawdopodobnie z powodu małej liczby osób ze złamaniami. Wnioski: Ryzyko złamania szyjki kości udowej powinno być brane pod uwagę w sytuacji, gdy zaleca się stosowanie kortykosteroidów ze wskazań pulmonologicznych osobom w podeszłym wieku. Problem ten dotyczy również leków wziewnych.
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Katsoulis M, Benetou V, Karapetyan T, Feskanich D, Grodstein F, Pettersson-Kymmer U, Eriksson S, Wilsgaard T, Jørgensen L, Ahmed LA, Schöttker B, Brenner H, Bellavia A, Wolk A, Kubinova R, Stegeman B, Bobak M, Boffetta P, Trichopoulou A. Excess mortality after hip fracture in elderly persons from Europe and the USA: the CHANCES project. J Intern Med 2017; 281:300-310. [PMID: 28093824 DOI: 10.1111/joim.12586] [Citation(s) in RCA: 213] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Hip fractures are associated with diminished quality of life and survival especially amongst the elderly. OBJECTIVE All-cause mortality after hip fracture was investigated to assess its magnitude. METHODS A total of 122 808 participants from eight cohorts in Europe and the USA were followed up for a mean of 12.6 years, accumulating 4273 incident hip fractures and 27 999 deaths. Incident hip fractures were assessed through telephone interviews/questionnaires or national inpatient/fracture registries, and causes of death were verified with death certificates. Cox proportional hazards models and the time-dependent variable methodology were used to assess the association between hip fracture and mortality and its magnitude at different time intervals after the injury in each cohort. We obtained the effect estimates through a random-effects meta-analysis. RESULTS Hip fracture was positively associated with increased all-cause mortality; the hazard ratio (HR) in the fully adjusted model was 2.12, 95% confidence interval (CI) 1.76-2.57, after adjusting for potential confounders. This association was stronger amongst men [HR: 2.39, 95% CI: 1.72-3.31] than amongst women [HR: 1.92, 95% CI: 1.54-2.39], although this difference was not significant. Mortality was higher during the first year after the hip fracture [HR: 2.78, 95% CI: 2.12-3.64], but it remained elevated without major fluctuations after longer time since hip fracture [HR (95% CI): 1.89 (1.50-2.37) after 1-4 years; 2.15 (1.81-2.55) after 4-8 years; 1.79 (1.57-2.05) after 8 or more years]. CONCLUSION In this large population-based sample of older persons across eight cohorts, hip fracture was associated with excess short- and long-term all-cause mortality in both sexes.
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Affiliation(s)
| | - V Benetou
- School of Medicine, Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Athens, Greece
| | | | - D Feskanich
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - F Grodstein
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - U Pettersson-Kymmer
- Department of Pharmacology and Clinical Neurosciences and Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - S Eriksson
- Faculty of Medicine, Department of Community Medicine and Rehabilitation, Geriatric Medicine, Umeå University, Umeå, Sweden
| | - T Wilsgaard
- Department of Community Medicine, UIT The Arctic University of Norway, Tromsø, Norway
| | - L Jørgensen
- Department of Health and Care Sciences, UIT The Arctic University of Norway, Tromsø, Norway
| | - L A Ahmed
- Department of Health and Care Sciences, UIT The Arctic University of Norway, Tromsø, Norway.,Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, UAE
| | - B Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - H Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - A Bellavia
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - A Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - R Kubinova
- National Institute of Public Health, Prague, Czech Republic
| | - B Stegeman
- Department of Epidemiology and Public Health, University College London, London, UK
| | - M Bobak
- Department of Epidemiology and Public Health, University College London, London, UK
| | - P Boffetta
- Hellenic Health Foundation, Athens, Greece.,Institute for Translational Epidemiology and Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Karakatsani A, Katsoulis M, Klinaki E, Trichopoulou A. Corticosteroids and hip fracture risk in elderly respiratory patients: EPIC-Greece cohort. Adv Respir Med 2017; 85:22-27. [DOI: 10.5603/arm.2017.0005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 02/13/2017] [Indexed: 11/25/2022]
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Ordóñez-Mena JM, Schöttker B, Mons U, Jenab M, Freisling H, Bueno-de-Mesquita B, O’Doherty MG, Scott A, Kee F, Stricker BH, Hofman A, de Keyser CE, Ruiter R, Söderberg S, Jousilahti P, Kuulasmaa K, Freedman ND, Wilsgaard T, de Groot LCPGM, Kampman E, Håkansson N, Orsini N, Wolk A, Nilsson LM, Tjønneland A, Pająk A, Malyutina S, Kubínová R, Tamosiunas A, Bobak M, Katsoulis M, Orfanos P, Boffetta P, Trichopoulou A, Brenner H. Quantification of the smoking-associated cancer risk with rate advancement periods: meta-analysis of individual participant data from cohorts of the CHANCES consortium. BMC Med 2016; 14:62. [PMID: 27044418 PMCID: PMC4820956 DOI: 10.1186/s12916-016-0607-5] [Citation(s) in RCA: 99] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2016] [Accepted: 03/18/2016] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Smoking is the most important individual risk factor for many cancer sites but its association with breast and prostate cancer is not entirely clear. Rate advancement periods (RAPs) may enhance communication of smoking related risk to the general population. Thus, we estimated RAPs for the association of smoking exposure (smoking status, time since smoking cessation, smoking intensity, and duration) with total and site-specific (lung, breast, colorectal, prostate, gastric, head and neck, and pancreatic) cancer incidence and mortality. METHODS This is a meta-analysis of 19 population-based prospective cohort studies with individual participant data for 897,021 European and American adults. For each cohort we calculated hazard ratios (HRs) for the association of smoking exposure with cancer outcomes using Cox regression adjusted for a common set of the most important potential confounding variables. RAPs (in years) were calculated as the ratio of the logarithms of the HRs for a given smoking exposure variable and age. Meta-analyses were employed to summarize cohort-specific HRs and RAPs. RESULTS Overall, 140,205 subjects had a first incident cancer, and 53,164 died from cancer, during an average follow-up of 12 years. Current smoking advanced the overall risk of developing and dying from cancer by eight and ten years, respectively, compared with never smokers. The greatest advancements in cancer risk and mortality were seen for lung cancer and the least for breast cancer. Smoking cessation was statistically significantly associated with delays in the risk of cancer development and mortality compared with continued smoking. CONCLUSIONS This investigation shows that smoking, even among older adults, considerably advances, and cessation delays, the risk of developing and dying from cancer. These findings may be helpful in more effectively communicating the harmful effects of smoking and the beneficial effect of smoking cessation.
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Affiliation(s)
- José Manuel Ordóñez-Mena
- />Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
- />Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany
| | - Ben Schöttker
- />Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
- />Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany
| | - Ute Mons
- />Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany
| | - Mazda Jenab
- />International Agency for Research on Cancer (IARC), Lyon, France
| | - Heinz Freisling
- />International Agency for Research on Cancer (IARC), Lyon, France
| | - Bas Bueno-de-Mesquita
- />Department of Chronic Diseases, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- />Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands
- />Division of Epidemiology and Biostatistics, the School of Public Health, Imperial College London, London, United Kingdom
- />Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Mark G. O’Doherty
- />UKCRC Centre of Excellence for Public Health, Queens University of Belfast, Belfast, UK
| | - Angela Scott
- />UKCRC Centre of Excellence for Public Health, Queens University of Belfast, Belfast, UK
| | - Frank Kee
- />UKCRC Centre of Excellence for Public Health, Queens University of Belfast, Belfast, UK
| | - Bruno H. Stricker
- />Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- />Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Rikje Ruiter
- />Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Stefan Söderberg
- />Department of Public Health and Clinical Medicine, Cardiology, and Heart Center, Umeå University, Umeå, Sweden
| | - Pekka Jousilahti
- />National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Kari Kuulasmaa
- />National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Neal D. Freedman
- />Nutritional Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, Rockville, MD USA
| | - Tom Wilsgaard
- />Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | | | - Ellen Kampman
- />Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands
| | - Niclas Håkansson
- />Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Nicola Orsini
- />Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Alicja Wolk
- />Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Lena Maria Nilsson
- />Nutritional Research, Department of Public Health and Clinical Medicine, and Arcum, Arctic Research Centre at Umeå University, Umeå, Sweden
| | - Anne Tjønneland
- />Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Andrzej Pająk
- />Jagiellonian University Medical College, Faculty of Health Sciences, Krakow, Poland
| | - Sofia Malyutina
- />Institute of Internal and Preventive Medicine, Novosibirsk, Russia
| | - Růžena Kubínová
- />National Institute of Public Health, Prague, Czech Republic
| | - Abdonas Tamosiunas
- />Institute of Cardiology of Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Martin Bobak
- />Department Epidemiology and Public Health, University College London, London, UK
| | | | - Philippos Orfanos
- />University of Athens, Medical School, Department of Hygiene, Epidemiology and Medical Statistics, Athens, Greece
| | - Paolo Boffetta
- />Hellenic Health Foundation, Athens, Greece
- />Institute for Translational Epidemiology and Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Antonia Trichopoulou
- />Hellenic Health Foundation, Athens, Greece
- />University of Athens, Medical School, Department of Hygiene, Epidemiology and Medical Statistics, Athens, Greece
| | - Hermann Brenner
- />Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
- />Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany
- />German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- />Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - on behalf of the Consortium on Health and Ageing: Network of Cohorts in Europe and the United States (CHANCES)
- />Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
- />Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, D-69120 Heidelberg, Germany
- />International Agency for Research on Cancer (IARC), Lyon, France
- />Department of Chronic Diseases, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- />Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands
- />Division of Epidemiology and Biostatistics, the School of Public Health, Imperial College London, London, United Kingdom
- />Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- />UKCRC Centre of Excellence for Public Health, Queens University of Belfast, Belfast, UK
- />Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- />Department of Public Health and Clinical Medicine, Cardiology, and Heart Center, Umeå University, Umeå, Sweden
- />National Institute for Health and Welfare (THL), Helsinki, Finland
- />Nutritional Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, Rockville, MD USA
- />Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- />Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands
- />Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- />Nutritional Research, Department of Public Health and Clinical Medicine, and Arcum, Arctic Research Centre at Umeå University, Umeå, Sweden
- />Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark
- />Jagiellonian University Medical College, Faculty of Health Sciences, Krakow, Poland
- />Institute of Internal and Preventive Medicine, Novosibirsk, Russia
- />National Institute of Public Health, Prague, Czech Republic
- />Institute of Cardiology of Lithuanian University of Health Sciences, Kaunas, Lithuania
- />Department Epidemiology and Public Health, University College London, London, UK
- />Hellenic Health Foundation, Athens, Greece
- />University of Athens, Medical School, Department of Hygiene, Epidemiology and Medical Statistics, Athens, Greece
- />Institute for Translational Epidemiology and Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA
- />German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- />Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Raaschou-Nielsen O, Beelen R, Wang M, Hoek G, Andersen ZJ, Hoffmann B, Stafoggia M, Samoli E, Weinmayr G, Dimakopoulou K, Nieuwenhuijsen M, Xun WW, Fischer P, Eriksen KT, Sørensen M, Tjønneland A, Ricceri F, de Hoogh K, Key T, Eeftens M, Peeters PH, Bueno-de-Mesquita HB, Meliefste K, Oftedal B, Schwarze PE, Nafstad P, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Penell J, De Faire U, Korek M, Pedersen N, Östenson CG, Pershagen G, Fratiglioni L, Concin H, Nagel G, Jaensch A, Ineichen A, Naccarati A, Katsoulis M, Trichpoulou A, Keuken M, Jedynska A, Kooter IM, Kukkonen J, Brunekreef B, Sokhi RS, Katsouyanni K, Vineis P. Particulate matter air pollution components and risk for lung cancer. Environ Int 2016; 87:66-73. [PMID: 26641521 DOI: 10.1016/j.envint.2015.11.007] [Citation(s) in RCA: 139] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Revised: 11/05/2015] [Accepted: 11/09/2015] [Indexed: 05/06/2023]
Abstract
BACKGROUND Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. METHODS We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. RESULTS The 245,782 cohort members contributed 3,229,220 person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100 ng/m(3)). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. CONCLUSIONS This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important.
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Affiliation(s)
- O Raaschou-Nielsen
- Danish Cancer Society Research Center, Copenhagen, Denmark; Department of Environmental Science, Aarhus University, Roskilde, Denmark.
| | - R Beelen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - M Wang
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - G Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Z J Andersen
- Danish Cancer Society Research Center, Copenhagen, Denmark; Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - B Hoffmann
- IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany; University of Düsseldorf, Düsseldorf, Germany
| | - M Stafoggia
- Department of Epidemiology, Lazio Regional Health Service, Local Health Unit ASL RME, Rome, Italy
| | - E Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - G Weinmayr
- IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany; University of Düsseldorf, Düsseldorf, Germany; Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - K Dimakopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - M Nieuwenhuijsen
- Center for Research in Environmental Epidemiology, Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain
| | - W W Xun
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - P Fischer
- National Institute for Public Health and the Environment, Center for Sustainability and Environmental Health, Bilthoven, The Netherlands
| | - K T Eriksen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - M Sørensen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - A Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - F Ricceri
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza, University of Turin and Center for Cancer Prevention, Turin, Italy
| | - K de Hoogh
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - T Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - M Eeftens
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - P H Peeters
- Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands; School of Public Health, Imperial College London, London, United Kingdom
| | - H B Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - K Meliefste
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - B Oftedal
- Norwegian Institute of Public Health, Oslo, Norway
| | - P E Schwarze
- Norwegian Institute of Public Health, Oslo, Norway
| | - P Nafstad
- Norwegian Institute of Public Health, Oslo, Norway; Institute of Health and Society, University of Oslo, Oslo, Norway
| | - C Galassi
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza, University of Turin and Center for Cancer Prevention, Turin, Italy
| | - E Migliore
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza, University of Turin and Center for Cancer Prevention, Turin, Italy
| | - A Ranzi
- Environmental Health Reference Centre, Regional Agency for Environmental Prevention of Emilia-Romagna, Modena, Italy
| | - G Cesaroni
- Department of Epidemiology, Lazio Regional Health Service, Local Health Unit ASL RME, Rome, Italy
| | - C Badaloni
- Department of Epidemiology, Lazio Regional Health Service, Local Health Unit ASL RME, Rome, Italy
| | - F Forastiere
- Department of Epidemiology, Lazio Regional Health Service, Local Health Unit ASL RME, Rome, Italy
| | - J Penell
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - U De Faire
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - M Korek
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - N Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - C-G Östenson
- Department of Molecular Medicine and Surgery, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden
| | - G Pershagen
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - L Fratiglioni
- Aging Research Centre, Department of Neurobiology, Care Sciences and Society, Karolinska Institute and Stockholm University, Stockholm, Sweden
| | - H Concin
- Agency for Preventive and Social Medicine, Bregenz, Austria
| | - G Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; Agency for Preventive and Social Medicine, Bregenz, Austria
| | - A Jaensch
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - A Ineichen
- Human Genetics Foundation, Molecular and Genetic Epidemiology Unit, Turin, Italy
| | - A Naccarati
- Human Genetics Foundation, Molecular and Genetic Epidemiology Unit, Turin, Italy
| | | | | | - M Keuken
- Netherlands Organisation for Applied Scientific Research, Utrecht, The Netherlands
| | - A Jedynska
- Netherlands Organisation for Applied Scientific Research, Utrecht, The Netherlands
| | - I M Kooter
- Netherlands Organisation for Applied Scientific Research, Utrecht, The Netherlands
| | - J Kukkonen
- Finnish Meteorological Institute, Helsinki, Finland
| | - B Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - R S Sokhi
- Centre for Atmospheric and Instrumentation Research, University of Hertfordshire, College Lane, Hatfield, United Kingdom
| | - K Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece; Department of Primary Care and Public Health Sciences and Environmental Research Group, King's College London, United Kingdom
| | - P Vineis
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
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Naska A, Katsoulis M, Orfanos P, Lachat C, Gedrich K, Rodrigues SSP, Freisling H, Kolsteren P, Engeset D, Lopes C, Elmadfa I, Wendt A, Knüppel S, Turrini A, Tumino R, Ocké MC, Sekula W, Nilsson LM, Key T, Trichopoulou A. Eating out is different from eating at home among individuals who occasionally eat out. A cross-sectional study among middle-aged adults from eleven European countries. Br J Nutr 2015; 113:1951-64. [PMID: 25907775 DOI: 10.1017/s0007114515000963] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Eating out has been linked to the current obesity epidemic, but the evaluation of the extent to which out of home (OH) dietary intakes are different from those at home (AH) is limited. Data collected among 8849 men and 14,277 women aged 35-64 years from the general population of eleven European countries through 24-h dietary recalls or food diaries were analysed to: (1) compare food consumption OH to those AH; (2) describe the characteristics of substantial OH eaters, defined as those who consumed 25 % or more of their total daily energy intake at OH locations. Logistic regression models were fit to identify personal characteristics associated with eating out. In both sexes, beverages, sugar, desserts, sweet and savoury bakery products were consumed more OH than AH. In some countries, men reported higher intakes of fish OH than AH. Overall, substantial OH eating was more common among men, the younger and the more educated participants, but was weakly associated with total energy intake. The substantial OH eaters reported similar dietary intakes OH and AH. Individuals who were not identified as substantial OH eaters reported consuming proportionally higher quantities of sweet and savoury bakery products, soft drinks, juices and other non-alcoholic beverages OH than AH. The OH intakes were different from the AH ones, only among individuals who reported a relatively small contribution of OH eating to their daily intakes and this may partly explain the inconsistent findings relating eating out to the current obesity epidemic.
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Affiliation(s)
- Androniki Naska
- WHO Collaborating Center for Food and Nutrition Policies, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens,75 Mikras Asias Street,Goudi, Athens11527,Greece
| | - Michail Katsoulis
- Hellenic Health Foundation,Kaisareias 13 and Alexandroupoleos,Athens11527,Greece
| | - Philippos Orfanos
- WHO Collaborating Center for Food and Nutrition Policies, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens,75 Mikras Asias Street,Goudi, Athens11527,Greece
| | - Carl Lachat
- Department of Food Safety and Food Quality,Faculty of Bioscience Engineering, Ghent University,Coupure links 653,9000Gent,Belgium
| | - Kurt Gedrich
- Technische Universität München, Center of Life and Food Sciences, Molecular Nutrition Unit,Gregor-Mendel-Strasse 2,85354Freising,Germany
| | - Sara S P Rodrigues
- Faculty of Nutrition and Food Sciences, University of Porto, Rua Dr Roberto Frias,4200-465Porto,Portugal
| | - Heinz Freisling
- International Agency for Research on Cancer (IARC-WHO),150, Cours Albert Thomas,69372Lyon Cedex 08,France
| | - Patrick Kolsteren
- Child Health and Nutrition Unit, Department of Public Health, Institute of Tropical Medicine,Nationalestraat 155,2000Antwerp,Belgium
| | - Dagrun Engeset
- Department of Community Medicine,Faculty of Health Sciences, University of Tromsø,N-9019Tromsø,Norway
| | - Carla Lopes
- Department of Clinical Epidemiology,Predictive Medicine and Public Health, Institute of Public Health, University of Porto, Alameda Professor Hernani Monteiro,4200-319Porto,Portugal
| | - Ibrahim Elmadfa
- Department of Nutritional Sciences,University of Vienna,Althanstrasse 14 (Pharmaziezentrum),A-1090Vienna,Austria
| | - Andrea Wendt
- Division of Cancer Epidemiology, German Cancer Research Centre (Deutsches Krebsforschungszentrum, DKFZ),Im Neuenheimer Feld 280,69120Heidelberg,Germany
| | - Sven Knüppel
- German Institute of Human Nutrition Potsdam-Rehbrücke, Department of Epidemiology,Arthur-Scheunert-Allee 114-116,14558Nuthetal,Germany
| | - Aida Turrini
- National Research Institute on Food and Nutrition (CRA-ex INRAN),Via Ardeatina 546,00178Rome,Italy
| | - Rosario Tumino
- Ragusa Cancer Registry,Azienda Ospedaliera 'Civile M. P. Arezzo' Via Dante N° 109,97100Ragusa,Italy
| | - Marga C Ocké
- National Institute for Public Health and the Environment,PO Box 1,3720BABilthoven,The Netherlands
| | - Wlodzimierz Sekula
- National Food and Nutrition Institute,61/63 Powsinska Street,02-903Warsaw,Poland
| | - Lena Maria Nilsson
- Public Health and Clinical Medicine, Nutritional Research, Umeå University,901 85Umeå,Sweden
| | - Tim Key
- Cancer Epidemiology Unit, University of Oxford, Richard Doll Building, Roosevelt Drive,OxfordOX3 7LF,UK
| | - Antonia Trichopoulou
- WHO Collaborating Center for Food and Nutrition Policies, Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens,75 Mikras Asias Street,Goudi, Athens11527,Greece
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38
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Beelen R, Hoek G, Raaschou-Nielsen O, Stafoggia M, Andersen ZJ, Weinmayr G, Hoffmann B, Wolf K, Samoli E, Fischer PH, Nieuwenhuijsen MJ, Xun WW, Katsouyanni K, Dimakopoulou K, Marcon A, Vartiainen E, Lanki T, Yli-Tuomi T, Oftedal B, Schwarze PE, Nafstad P, De Faire U, Pedersen NL, Östenson CG, Fratiglioni L, Penell J, Korek M, Pershagen G, Eriksen KT, Overvad K, Sørensen M, Eeftens M, Peeters PH, Meliefste K, Wang M, Bueno-de-Mesquita HB, Sugiri D, Krämer U, Heinrich J, de Hoogh K, Key T, Peters A, Hampel R, Concin H, Nagel G, Jaensch A, Ineichen A, Tsai MY, Schaffner E, Probst-Hensch NM, Schindler C, Ragettli MS, Vilier A, Clavel-Chapelon F, Declercq C, Ricceri F, Sacerdote C, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Katsoulis M, Trichopoulou A, Keuken M, Jedynska A, Kooter IM, Kukkonen J, Sokhi RS, Vineis P, Brunekreef B. Natural-cause mortality and long-term exposure to particle components: an analysis of 19 European cohorts within the multi-center ESCAPE project. Environ Health Perspect 2015; 123:525-33. [PMID: 25712504 PMCID: PMC4455583 DOI: 10.1289/ehp.1408095] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Accepted: 02/20/2015] [Indexed: 05/19/2023]
Abstract
BACKGROUND Studies have shown associations between mortality and long-term exposure to particulate matter air pollution. Few cohort studies have estimated the effects of the elemental composition of particulate matter on mortality. OBJECTIVES Our aim was to study the association between natural-cause mortality and long-term exposure to elemental components of particulate matter. METHODS Mortality and confounder data from 19 European cohort studies were used. Residential exposure to eight a priori-selected components of particulate matter (PM) was characterized following a strictly standardized protocol. Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM size fractions ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10) were estimated using land-use regression models. Cohort-specific statistical analyses of the associations between mortality and air pollution were conducted using Cox proportional hazards models using a common protocol followed by meta-analysis. RESULTS The total study population consisted of 291,816 participants, of whom 25,466 died from a natural cause during follow-up (average time of follow-up, 14.3 years). Hazard ratios were positive for almost all elements and statistically significant for PM2.5 sulfur (1.14; 95% CI: 1.06, 1.23 per 200 ng/m3). In a two-pollutant model, the association with PM2.5 sulfur was robust to adjustment for PM2.5 mass, whereas the association with PM2.5 mass was reduced. CONCLUSIONS Long-term exposure to PM2.5 sulfur was associated with natural-cause mortality. This association was robust to adjustment for other pollutants and PM2.5.
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Affiliation(s)
- Rob Beelen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
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Turati F, Dilis V, Rossi M, Lagiou P, Benetou V, Katsoulis M, Naska A, Trichopoulos D, La Vecchia C, Trichopoulou A. Glycemic load and coronary heart disease in a Mediterranean population: the EPIC Greek cohort study. Nutr Metab Cardiovasc Dis 2015; 25:336-342. [PMID: 25638596 DOI: 10.1016/j.numecd.2014.12.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Revised: 11/18/2014] [Accepted: 12/03/2014] [Indexed: 11/22/2022]
Abstract
BACKGROUND AND AIMS High glycemic load (GL) has been associated with increased coronary heart disease (CHD) risk. We evaluated whether preference of low-GL foods conveys incremental benefits with respect to CHD, especially to people adhering to the traditional Mediterranean diet (MD). METHODS AND RESULTS We analyzed data from the Greek European Prospective Investigation into Cancer and Nutrition, including 20,275 participants free of cardiovascular diseases, cancer, or diabetes at baseline and without incident diabetes. Subjects completed a validated, semi-quantitative food frequency questionnaire at enrollment. We calculated a 10-point MD adherence score and the dietary GL, and estimated hazard ratios (HRs) for CHD incidence and mortality through Cox proportional hazard regression. After a median follow-up of 10.4 years, 417 participants developed CHD, and 162 died from the disease. A significant positive association of GL with CHD incidence emerged (HR for the highest versus the lowest tertile = 1.41, 95% confidence interval, CI: 1.05-1.90). HRs for CHD mortality exceeded unity but were not statistically significant. The association with GL was stronger among subjects with higher body mass index. High adherence to MD with low/moderate GL was associated with lower risk of CHD incidence (HR = 0.61, CI: 0.39-0.95) and mortality (HR = 0.47, 95% CI: 0.23-96). CONCLUSION High dietary GL increases the risk of CHD. Compared to a high GL diet with suboptimal adherence to the traditional Mediterranean pattern, a low/moderate GL diet that also conforms to the traditional MD principles could lead to a 40% reduced risk for CHD, and over 50% reduced risk for death from CHD.
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Affiliation(s)
- F Turati
- Department of Epidemiology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - V Dilis
- Hellenic Health Foundation, Athens, Greece
| | - M Rossi
- Department of Epidemiology, IRCCS - Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
| | - P Lagiou
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens, Athens, Greece; Department of Epidemiology, Harvard School of Public Health, Boston, USA; Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
| | - V Benetou
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens, Athens, Greece
| | | | - A Naska
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens, Athens, Greece
| | - D Trichopoulos
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens, Athens, Greece; Department of Epidemiology, Harvard School of Public Health, Boston, USA; Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
| | - C La Vecchia
- Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Via Vanzetti 5, 20133 Milan, Italy.
| | - A Trichopoulou
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, University of Athens, Athens, Greece; Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
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Katsoulis M, Kyrozis A, Trichopoulou A, Bamia C, Trichopoulos D, Lagiou P. Cognitive impairment and cancer mortality: a biological or health care explanation? Cancer Causes Control 2014; 25:1565-70. [PMID: 25146445 DOI: 10.1007/s10552-014-0460-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 08/07/2014] [Indexed: 11/25/2022]
Abstract
PURPOSE To examine whether the documented association of suboptimal cognitive function with total and cardiovascular (CVD) mortality also applies to cancer mortality and probe whether the explanation for this association is biomedical or health care related. METHODS In a subsample of 733 participants of the EPIC-Greece cohort from Athens and surrounding area, we assessed cognitive function at age 65 or older in the period 2004-2006, using the Mini-Mental State Examination (MMSE). Incidence of cancer, mortality from cancer and CVD, and overall mortality were ascertained through active follow-up for a median of 4 years after MMSE assessment using Cox proportional hazards models. RESULTS A total of 86 participants died during follow-up. A 2-point decrease in MMSE score was associated with increase in overall (hazard ratio (HR) 1.26, 95 % confidence interval (CI) 1.11-1.43), CVD (HR 1.26, 95 % CI 1.02-1.56), and cancer (HR 1.32, 95 % CI 1.02-1.70) mortality. In contrast, there was no noticeable difference in cancer incidence associated with a 2-point decrease in MMSE score (HR 1.07, 95 % CI 0.79-1.45). CONCLUSIONS Cognitive function appears to be inversely associated not only with CVD and overall, but also with cancer mortality. Although for CVD mortality there is a biomedical explanation invoking vascular mechanisms, for cancer mortality we may need to focus on socially conditioned factors, such as compromised ability to identify early signs and suboptimal compliance to treatment. Our hypothesis-generating results need to be confirmed in larger studies, as the issue is of major importance, since cognitive decline is not uncommon among the elderly.
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Affiliation(s)
- Michail Katsoulis
- Hellenic Health Foundation, 13 Kaisareias Street, 115 27, Athens, Greece,
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Katsoulis M, Dimakopoulou K, Pedeli X, Trichopoulos D, Gryparis A, Trichopoulou A, Katsouyanni K. Long-term exposure to traffic-related air pollution and cardiovascular health in a Greek cohort study. Sci Total Environ 2014; 490:934-40. [PMID: 24908651 DOI: 10.1016/j.scitotenv.2014.05.058] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2014] [Revised: 05/08/2014] [Accepted: 05/09/2014] [Indexed: 05/06/2023]
Abstract
Our objective is to evaluate the association of exposure to traffic-related air pollution with the incidence of fatal and non-fatal ischemic heart disease (IHD), stroke and total cardiovascular disease (CVD) events in a Greek cohort. We used data from the European Prospective Investigation on Nutrition and Cancer (EPIC) for 2752 subjects followed from 1997 to 2011, whose residence was in 10 municipalities of the Greater Athens area. Air pollution exposure estimation was based on a spatio-temporal land use regression model linking geo-coded residential addresses to long-term average NO2 and PM10 concentrations. We conducted Cox proportional hazards regression analysis, adjusting for potential confounders. Hazard ratios (HR) above 1 (not all statistically significant) were associated with higher PM10 exposure for all outcomes. Weaker associations were found with NO2 exposure. Specifically, the estimated HR for a CVD event associated with 10 μg/m(3) increase in long-term exposure to PM10 was 1.50 (1.05-2.16, p-value: 0.027). The relationship was more evident for subjects ≤50 years old at recruitment. Associations of PM10 and NO2 exposure with IHD events were found only among women with HRs respectively of 2.24 (0.89-5.64, p-value: 0.086) and 1.54 (1.01-2.37, p-value: 0.046) associated with 10 μg/m(3) increase in the corresponding pollutant. In conclusion, the present study suggests that long-term exposure to traffic-related air pollution has an impact on CVD and IHD morbidity, particularly among women and younger subjects.
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Affiliation(s)
- Michail Katsoulis
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Konstantina Dimakopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Xanthi Pedeli
- Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Dimitrios Trichopoulos
- Department of Epidemiology, Harvard School of Public Health, Boston MA, USA; Bureau of Epidemiologic Research, Academy of Athens, Greece
| | - Alexandros Gryparis
- Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece; Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Athens, Greece; Department of Primary Care & Public Health Sciences, Environmental Research Group, King's College London, London, UK.
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Beelen R, Stafoggia M, Raaschou-Nielsen O, Andersen ZJ, Xun WW, Katsouyanni K, Dimakopoulou K, Brunekreef B, Weinmayr G, Hoffmann B, Wolf K, Samoli E, Houthuijs D, Nieuwenhuijsen M, Oudin A, Forsberg B, Olsson D, Salomaa V, Lanki T, Yli-Tuomi T, Oftedal B, Aamodt G, Nafstad P, De Faire U, Pedersen NL, Östenson CG, Fratiglioni L, Penell J, Korek M, Pyko A, Eriksen KT, Tjønneland A, Becker T, Eeftens M, Bots M, Meliefste K, Wang M, Bueno-de-Mesquita B, Sugiri D, Krämer U, Heinrich J, de Hoogh K, Key T, Peters A, Cyrys J, Concin H, Nagel G, Ineichen A, Schaffner E, Probst-Hensch N, Dratva J, Ducret-Stich R, Vilier A, Clavel-Chapelon F, Stempfelet M, Grioni S, Krogh V, Tsai MY, Marcon A, Ricceri F, Sacerdote C, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Tamayo I, Amiano P, Dorronsoro M, Katsoulis M, Trichopoulou A, Vineis P, Hoek G. Long-term exposure to air pollution and cardiovascular mortality: an analysis of 22 European cohorts. Epidemiology 2014; 25:368-78. [PMID: 24589872 DOI: 10.1097/ede.0000000000000076] [Citation(s) in RCA: 190] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. METHODS Data from 22 European cohort studies were used. Using a standardized protocol, study area-specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and 10 μm to 2.5 μm (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. RESULTS The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87-1.69) per 5 μg/m and for PM10, 1.22 (0.91-1.63) per 10 μg/m. CONCLUSION In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.
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Affiliation(s)
- Rob Beelen
- From the aInstitute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; bDepartment of Epidemiology, Lazio Regional Health Service, Rome, Italy; cDanish Cancer Society Research Center, Copenhagen, Denmark; dCenter for Epidemiology and Screening, Department of Public Health, University of Copenhagen, CSS, København K, Denmark; eMRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, United Kingdom; fUniversity College London, CeLSIUS, London, United Kingdom; gDepartment of Hygiene, Epidemiology, and Medical Statistics, Medical School, University of Athens, Athens, Greece; hJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; iInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; jIUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany, and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany; kInstitute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; lNational Institute for Public Health and the Environment, Bilthoven, The Netherlands; mCentre for Research in Environmental Epidemiology (CREAL), Barcelona, and Parc de Recerca Biomèdica de Barcelona-PRBB (office 183.05) C. Doctor Aiguader, Barcelona, Spain; nConsortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Melchor Fernández Almagro 3-5, Madrid, Spain; oDivision of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden; pNational Institute for Health and Welfare, Kuopio, Finland; qNorwegian Institute of Public Health, Oslo, Norway; rInstitute of Health and Society, University of Oslo, Oslo, Norway; sInstitute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; tDepartm
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Wang M, Beelen R, Stafoggia M, Raaschou-Nielsen O, Andersen ZJ, Hoffmann B, Fischer P, Houthuijs D, Nieuwenhuijsen M, Weinmayr G, Vineis P, Xun WW, Dimakopoulou K, Samoli E, Laatikainen T, Lanki T, Turunen AW, Oftedal B, Schwarze P, Aamodt G, Penell J, De Faire U, Korek M, Leander K, Pershagen G, Pedersen NL, Östenson CG, Fratiglioni L, Eriksen KT, Sørensen M, Tjønneland A, Bueno-de-Mesquita B, Eeftens M, Bots ML, Meliefste K, Krämer U, Heinrich J, Sugiri D, Key T, de Hoogh K, Wolf K, Peters A, Cyrys J, Jaensch A, Concin H, Nagel G, Tsai MY, Phuleria H, Ineichen A, Künzli N, Probst-Hensch N, Schaffner E, Vilier A, Clavel-Chapelon F, Declerq C, Ricceri F, Sacerdote C, Marcon A, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Katsoulis M, Trichopoulou A, Keuken M, Jedynska A, Kooter IM, Kukkonen J, Sokhi RS, Brunekreef B, Katsouyanni K, Hoek G. Long-term exposure to elemental constituents of particulate matter and cardiovascular mortality in 19 European cohorts: results from the ESCAPE and TRANSPHORM projects. Environ Int 2014; 66:97-106. [PMID: 24561271 DOI: 10.1016/j.envint.2014.01.026] [Citation(s) in RCA: 90] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2013] [Revised: 01/16/2014] [Accepted: 01/27/2014] [Indexed: 05/26/2023]
Abstract
BACKGROUND Associations between long-term exposure to ambient particulate matter (PM) and cardiovascular (CVD) mortality have been widely recognized. However, health effects of long-term exposure to constituents of PM on total CVD mortality have been explored in a single study only. AIMS The aim of this study was to examine the association of PM composition with cardiovascular mortality. METHODS We used data from 19 European ongoing cohorts within the framework of the ESCAPE (European Study of Cohorts for Air Pollution Effects) and TRANSPHORM (Transport related Air Pollution and Health impacts--Integrated Methodologies for Assessing Particulate Matter) projects. Residential annual average exposure to elemental constituents within particle matter smaller than 2.5 and 10 μm (PM2.5 and PM10) was estimated using Land Use Regression models. Eight elements representing major sources were selected a priori (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc). Cohort-specific analyses were conducted using Cox proportional hazards models with a standardized protocol. Random-effects meta-analysis was used to calculate combined effect estimates. RESULTS The total population consisted of 322,291 participants, with 9545 CVD deaths. We found no statistically significant associations between any of the elemental constituents in PM2.5 or PM10 and CVD mortality in the pooled analysis. Most of the hazard ratios (HRs) were close to unity, e.g. for PM10 Fe the combined HR was 0.96 (0.84-1.09). Elevated combined HRs were found for PM2.5 Si (1.17, 95% CI: 0.93-1.47), and S in PM2.5 (1.08, 95% CI: 0.95-1.22) and PM10 (1.09, 95% CI: 0.90-1.32). CONCLUSION In a joint analysis of 19 European cohorts, we found no statistically significant association between long-term exposure to 8 elemental constituents of particles and total cardiovascular mortality.
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Affiliation(s)
- Meng Wang
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
| | - Rob Beelen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | | | - Zorana Jovanovic Andersen
- Danish Cancer Society Research Center, Copenhagen, Denmark; Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Barbara Hoffmann
- IUF, Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany; University of Düsseldorf, Düsseldorf, Germany
| | - Paul Fischer
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - Danny Houthuijs
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | - Mark Nieuwenhuijsen
- Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Madrid, Spain
| | - Gudrun Weinmayr
- University of Düsseldorf, Düsseldorf, Germany; Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Paolo Vineis
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Wei W Xun
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom; University College London, London, United Kingdom
| | - Konstantina Dimakopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Tiina Laatikainen
- National Institute for Health and Welfare, Kuopio, Finland; Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Timo Lanki
- National Institute for Health and Welfare, Kuopio, Finland
| | - Anu W Turunen
- National Institute for Health and Welfare, Kuopio, Finland
| | | | - Per Schwarze
- Norwegian Institute of Public Health, Oslo, Norway
| | - Geir Aamodt
- Norwegian Institute of Public Health, Oslo, Norway
| | - Johanna Penell
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ulf De Faire
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Michal Korek
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Karin Leander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Claes-Göran Östenson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Laura Fratiglioni
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | | | - Mette Sørensen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | | | - Bas Bueno-de-Mesquita
- National Institute of Public Health and the Environment, Bilthoven, The Netherlands; School of Public Health, Imperial College London, London, United Kingdom
| | - Marloes Eeftens
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Michiel L Bots
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kees Meliefste
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Ursula Krämer
- IUF, Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center of Environmental Health, Neuherberg, Germany
| | - Dorothea Sugiri
- IUF, Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Timothy Key
- Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Kees de Hoogh
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | - Kathrin Wolf
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Josef Cyrys
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; University of Augsburg, Environmental Science Center, Augsburg, Germany
| | - Andrea Jaensch
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Hans Concin
- Agency for Preventive and Social Medicine, Bregenz, Austria
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; Agency for Preventive and Social Medicine, Bregenz, Austria
| | - Ming-Yi Tsai
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Harish Phuleria
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Alex Ineichen
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nino Künzli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Emmanuel Schaffner
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Alice Vilier
- Inserm, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health Team, Villejuif, France; University Paris Sud, UMRS 1018, Villejuif, France; IGR, Villejuif, France
| | - Françoise Clavel-Chapelon
- Inserm, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women's Health Team, Villejuif, France; University Paris Sud, UMRS 1018, Villejuif, France; IGR, Villejuif, France
| | - Christophe Declerq
- French Institute for Public Health Surveillance (InVS) 12, Saint-Maurice, France
| | | | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza, University of Turin and Center for Cancer Prevention, Turin, Italy
| | - Alessandro Marcon
- Unit of Epidemiology & Medical Statistics, Department of Public Health and Community Medicine, University of Verona, Italy
| | - Claudia Galassi
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza, University of Turin and Center for Cancer Prevention, Turin, Italy
| | - Enrica Migliore
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza, University of Turin and Center for Cancer Prevention, Turin, Italy
| | - Andrea Ranzi
- Environmental Health Reference Centre, Regional Agency for Environmental Prevention of Emilia-Romagna, Modena, Italy
| | - Giulia Cesaroni
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Chiara Badaloni
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | | | | | | | - Menno Keuken
- TNO, Netherlands Organisation for Applied Scientific Research, Utrecht, The Netherlands
| | - Aleksandra Jedynska
- TNO, Netherlands Organisation for Applied Scientific Research, Utrecht, The Netherlands
| | - Ingeborg M Kooter
- TNO, Netherlands Organisation for Applied Scientific Research, Utrecht, The Netherlands
| | | | - Ranjeet S Sokhi
- University of Hertfordshire College Lane, Hatfield, United Kingdom
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
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Beelen R, Raaschou-Nielsen O, Stafoggia M, Andersen ZJ, Weinmayr G, Hoffmann B, Wolf K, Samoli E, Fischer P, Nieuwenhuijsen M, Vineis P, Xun WW, Katsouyanni K, Dimakopoulou K, Oudin A, Forsberg B, Modig L, Havulinna AS, Lanki T, Turunen A, Oftedal B, Nystad W, Nafstad P, De Faire U, Pedersen NL, Östenson CG, Fratiglioni L, Penell J, Korek M, Pershagen G, Eriksen KT, Overvad K, Ellermann T, Eeftens M, Peeters PH, Meliefste K, Wang M, Bueno-de-Mesquita B, Sugiri D, Krämer U, Heinrich J, de Hoogh K, Key T, Peters A, Hampel R, Concin H, Nagel G, Ineichen A, Schaffner E, Probst-Hensch N, Künzli N, Schindler C, Schikowski T, Adam M, Phuleria H, Vilier A, Clavel-Chapelon F, Declercq C, Grioni S, Krogh V, Tsai MY, Ricceri F, Sacerdote C, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Tamayo I, Amiano P, Dorronsoro M, Katsoulis M, Trichopoulou A, Brunekreef B, Hoek G. Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project. Lancet 2014; 383:785-95. [PMID: 24332274 DOI: 10.1016/s0140-6736(13)62158-3] [Citation(s) in RCA: 726] [Impact Index Per Article: 72.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. METHODS We used data from 22 European cohort studies, which created a total study population of 367,251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and between 10 μm and 2.5 μm (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx), with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. FINDINGS The total study population consisted of 367,251 participants who contributed 5,118,039 person-years at risk (average follow-up 13.9 years), of whom 29,076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 μg/m(3) was recorded. No heterogeneity was noted between individual cohort effect estimates (I(2) p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 μg/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 μg/m(3) (1.07, 1.01-1.13). INTERPRETATION Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value. FUNDING European Community's Seventh Framework Program (FP7/2007-2011).
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Affiliation(s)
- Rob Beelen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands.
| | | | - Massimo Stafoggia
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Zorana Jovanovic Andersen
- Danish Cancer Society Research Center, Copenhagen, Denmark; Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Gudrun Weinmayr
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Barbara Hoffmann
- IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Kathrin Wolf
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Paul Fischer
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Mark Nieuwenhuijsen
- Centre for Research in Environmental Epidemiology (CREAL), Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain
| | - Paolo Vineis
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK
| | - Wei W Xun
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK; CeLSIUS, University College London, London, UK
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Konstantina Dimakopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Anna Oudin
- Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Bertil Forsberg
- Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Lars Modig
- Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Aki S Havulinna
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Timo Lanki
- Department of Environmental Health, National Institute for Health and Welfare, Kuopio, Finland
| | - Anu Turunen
- Department of Environmental Health, National Institute for Health and Welfare, Kuopio, Finland
| | - Bente Oftedal
- Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo, Norway
| | - Wenche Nystad
- Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo, Norway
| | - Per Nafstad
- Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo, Norway; Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Ulf De Faire
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Claes-Göran Östenson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Laura Fratiglioni
- Ageing Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Johanna Penell
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Michal Korek
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus C, Aarhus, Denmark
| | - Thomas Ellermann
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Marloes Eeftens
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Petra H Peeters
- Department of Epidemiology, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands; Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College, London, UK
| | - Kees Meliefste
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Meng Wang
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | | | - Dorothea Sugiri
- IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Ursula Krämer
- IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Centre of Environmental Health, Neuherberg, Germany
| | - Kees de Hoogh
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK
| | - Timothy Key
- Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Regina Hampel
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Hans Concin
- Agency for Preventive and Social Medicine, Bregenz, Austria
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; Agency for Preventive and Social Medicine, Bregenz, Austria
| | - Alex Ineichen
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Emmanuel Schaffner
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nino Künzli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Christian Schindler
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Tamara Schikowski
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Martin Adam
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Harish Phuleria
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Alice Vilier
- Inserm, Centre for Research in Epidemiology and Population Health, U1018, Nutrition, Hormones and Women's Health Team, Villejuif, France; University Paris Sud, UMRS 1018, F-94805, Villejuif, France; Institut Gustave Roussy, F-94805, Villejuif, France
| | - Françoise Clavel-Chapelon
- Inserm, Centre for Research in Epidemiology and Population Health, U1018, Nutrition, Hormones and Women's Health Team, Villejuif, France; University Paris Sud, UMRS 1018, F-94805, Villejuif, France; Institut Gustave Roussy, F-94805, Villejuif, France
| | - Christophe Declercq
- French Institute for Public Health Surveillance (InVS), Saint-Maurice, France
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Ming-Yi Tsai
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | | | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza-University of Turin and Centre for Cancer Prevention, Turin, Italy
| | - Claudia Galassi
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza-University of Turin and Centre for Cancer Prevention, Turin, Italy
| | - Enrica Migliore
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza-University of Turin and Centre for Cancer Prevention, Turin, Italy
| | - Andrea Ranzi
- Environmental Health Reference Centre-Regional Agency for Environmental Prevention of Emilia-Romagna, Modena, Italy
| | - Giulia Cesaroni
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Chiara Badaloni
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | | | - Ibon Tamayo
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, Basque Government, Gipuzkoa, Spain
| | - Pilar Amiano
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, Basque Government, Gipuzkoa, Spain
| | - Miren Dorronsoro
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, Basque Government, Gipuzkoa, Spain
| | | | | | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands; Department of Epidemiology, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
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Beelen R, Raaschou-Nielsen O, Stafoggia M, Andersen ZJ, Weinmayr G, Hoffmann B, Wolf K, Samoli E, Fischer P, Nieuwenhuijsen M, Vineis P, Xun WW, Katsouyanni K, Dimakopoulou K, Oudin A, Forsberg B, Modig L, Havulinna AS, Lanki T, Turunen A, Oftedal B, Nystad W, Nafstad P, De Faire U, Pedersen NL, Östenson CG, Fratiglioni L, Penell J, Korek M, Pershagen G, Eriksen KT, Overvad K, Ellermann T, Eeftens M, Peeters PH, Meliefste K, Wang M, Bueno-de-Mesquita B, Sugiri D, Krämer U, Heinrich J, de Hoogh K, Key T, Peters A, Hampel R, Concin H, Nagel G, Ineichen A, Schaffner E, Probst-Hensch N, Künzli N, Schindler C, Schikowski T, Adam M, Phuleria H, Vilier A, Clavel-Chapelon F, Declercq C, Grioni S, Krogh V, Tsai MY, Ricceri F, Sacerdote C, Galassi C, Migliore E, Ranzi A, Cesaroni G, Badaloni C, Forastiere F, Tamayo I, Amiano P, Dorronsoro M, Katsoulis M, Trichopoulou A, Brunekreef B, Hoek G. Effects of long-term exposure to air pollution on natural-cause mortality: an analysis of 22 European cohorts within the multicentre ESCAPE project. Lancet 2014. [PMID: 24332274 DOI: 10.1016/s01406736(13)62158-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
BACKGROUND Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects (ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. METHODS We used data from 22 European cohort studies, which created a total study population of 367,251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and between 10 μm and 2.5 μm (PMcoarse), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx), with land use regression models. We also investigated two traffic intensity variables-traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. FINDINGS The total study population consisted of 367,251 participants who contributed 5,118,039 person-years at risk (average follow-up 13.9 years), of whom 29,076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2.5 of 1.07 (95% CI 1.02-1.13) per 5 μg/m(3) was recorded. No heterogeneity was noted between individual cohort effect estimates (I(2) p value=0.95). HRs for PM2.5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 μg/m(3) (HR 1.06, 95% CI 1.00-1.12) or below 20 μg/m(3) (1.07, 1.01-1.13). INTERPRETATION Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value. FUNDING European Community's Seventh Framework Program (FP7/2007-2011).
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Affiliation(s)
- Rob Beelen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands.
| | | | - Massimo Stafoggia
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Zorana Jovanovic Andersen
- Danish Cancer Society Research Center, Copenhagen, Denmark; Center for Epidemiology and Screening, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Gudrun Weinmayr
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Barbara Hoffmann
- IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Kathrin Wolf
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Paul Fischer
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Mark Nieuwenhuijsen
- Centre for Research in Environmental Epidemiology (CREAL), Parc de Recerca Biomèdica de Barcelona, Barcelona, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain
| | - Paolo Vineis
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK
| | - Wei W Xun
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK; CeLSIUS, University College London, London, UK
| | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Konstantina Dimakopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, University of Athens, Athens, Greece
| | - Anna Oudin
- Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Bertil Forsberg
- Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Lars Modig
- Division of Occupational and Environmental Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Aki S Havulinna
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Timo Lanki
- Department of Environmental Health, National Institute for Health and Welfare, Kuopio, Finland
| | - Anu Turunen
- Department of Environmental Health, National Institute for Health and Welfare, Kuopio, Finland
| | - Bente Oftedal
- Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo, Norway
| | - Wenche Nystad
- Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo, Norway
| | - Per Nafstad
- Division of Environmental Medicine, Norwegian Institute of Public Health, Oslo, Norway; Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Ulf De Faire
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Claes-Göran Östenson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Laura Fratiglioni
- Ageing Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Johanna Penell
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Michal Korek
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus C, Aarhus, Denmark
| | - Thomas Ellermann
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Marloes Eeftens
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Petra H Peeters
- Department of Epidemiology, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands; Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College, London, UK
| | - Kees Meliefste
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Meng Wang
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | | | - Dorothea Sugiri
- IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Ursula Krämer
- IUF - Leibniz Research Institute for Environmental Medicine, Germany and Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Centre of Environmental Health, Neuherberg, Germany
| | - Kees de Hoogh
- MRC-HPA Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, St Mary's Campus, London, UK
| | - Timothy Key
- Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Regina Hampel
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Hans Concin
- Agency for Preventive and Social Medicine, Bregenz, Austria
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; Agency for Preventive and Social Medicine, Bregenz, Austria
| | - Alex Ineichen
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Emmanuel Schaffner
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nicole Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Nino Künzli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Christian Schindler
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Tamara Schikowski
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Martin Adam
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Harish Phuleria
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Alice Vilier
- Inserm, Centre for Research in Epidemiology and Population Health, U1018, Nutrition, Hormones and Women's Health Team, Villejuif, France; University Paris Sud, UMRS 1018, F-94805, Villejuif, France; Institut Gustave Roussy, F-94805, Villejuif, France
| | - Françoise Clavel-Chapelon
- Inserm, Centre for Research in Epidemiology and Population Health, U1018, Nutrition, Hormones and Women's Health Team, Villejuif, France; University Paris Sud, UMRS 1018, F-94805, Villejuif, France; Institut Gustave Roussy, F-94805, Villejuif, France
| | - Christophe Declercq
- French Institute for Public Health Surveillance (InVS), Saint-Maurice, France
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Ming-Yi Tsai
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | | | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza-University of Turin and Centre for Cancer Prevention, Turin, Italy
| | - Claudia Galassi
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza-University of Turin and Centre for Cancer Prevention, Turin, Italy
| | - Enrica Migliore
- Unit of Cancer Epidemiology, AO Citta' della Salute e della Scienza-University of Turin and Centre for Cancer Prevention, Turin, Italy
| | - Andrea Ranzi
- Environmental Health Reference Centre-Regional Agency for Environmental Prevention of Emilia-Romagna, Modena, Italy
| | - Giulia Cesaroni
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | - Chiara Badaloni
- Department of Epidemiology, Lazio Regional Health Service, Rome, Italy
| | | | - Ibon Tamayo
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, Basque Government, Gipuzkoa, Spain
| | - Pilar Amiano
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, Basque Government, Gipuzkoa, Spain
| | - Miren Dorronsoro
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Madrid, Spain; Public Health Division of Gipuzkoa, Basque Government, Gipuzkoa, Spain
| | | | | | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands; Department of Epidemiology, Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
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Yiannakouris N, Katsoulis M, Trichopoulou A, Ordovas JM, Trichopoulos D. Additive influence of genetic predisposition and conventional risk factors in the incidence of coronary heart disease: a population-based study in Greece. BMJ Open 2014; 4:e004387. [PMID: 24500614 PMCID: PMC3918976 DOI: 10.1136/bmjopen-2013-004387] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVES An additive genetic risk score (GRS) for coronary heart disease (CHD) has previously been associated with incident CHD in the population-based Greek European Prospective Investigation into Cancer and nutrition (EPIC) cohort. In this study, we explore GRS-'environment' joint actions on CHD for several conventional cardiovascular risk factors (ConvRFs), including smoking, hypertension, type-2 diabetes mellitus (T2DM), body mass index (BMI), physical activity and adherence to the Mediterranean diet. DESIGN A case-control study. SETTING The general Greek population of the EPIC study. PARTICIPANTS AND OUTCOME MEASURES 477 patients with medically confirmed incident CHD and 1271 controls participated in this study. We estimated the ORs for CHD by dividing participants at higher or lower GRS and, alternatively, at higher or lower ConvRF, and calculated the relative excess risk due to interaction (RERI) as a measure of deviation from additivity. RESULTS The joint presence of higher GRS and higher risk ConvRF was in all instances associated with an increased risk of CHD, compared with the joint presence of lower GRS and lower risk ConvRF. The OR (95% CI) was 1.7 (1.2 to 2.4) for smoking, 2.7 (1.9 to 3.8) for hypertension, 4.1 (2.8 to 6.1) for T2DM, 1.9 (1.4 to 2.5) for lower physical activity, 2.0 (1.3 to 3.2) for high BMI and 1.5 (1.1 to 2.1) for poor adherence to the Mediterranean diet. In all instances, RERI values were fairly small and not statistically significant, suggesting that the GRS and the ConvRFs do not have effects beyond additivity. CONCLUSIONS Genetic predisposition to CHD, operationalised through a multilocus GRS, and ConvRFs have essentially additive effects on CHD risk.
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Affiliation(s)
- Nikos Yiannakouris
- Hellenic Health Foundation, Athens, Greece
- Department of Nutrition and Dietetics, Harokopio University of Athens, Athens, Greece
| | | | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece
- Department of Hygiene, Epidemiology and Medical Statistics, WHO Collaborating Center for Food and Nutrition Policies, University of Athens Medical School, Athens, Greece
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, Jean Mayer—US Department of Agriculture, Human Nutrition Research Center on Aging (HNRCA) at Tufts University, Boston, Massachusetts, USA
- Department of Cardiovascular Epidemiology and Population Genetics, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
- Instituto Madrileño de Estudios Avanzados (IMDEA) Alimentacion, Madrid, Spain
| | - Dimitrios Trichopoulos
- Hellenic Health Foundation, Athens, Greece
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
- Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece
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Ferrari P, McKay JD, Jenab M, Brennan P, Canzian F, Vogel U, Tjønneland A, Overvad K, Tolstrup JS, Boutron-Ruault MC, Clavel-Chapelon F, Morois S, Kaaks R, Boeing H, Bergmann M, Trichopoulou A, Katsoulis M, Trichopoulos D, Krogh V, Panico S, Sacerdote C, Palli D, Tumino R, Peeters PH, van Gils CH, Bueno-de-Mesquita B, Vrieling A, Lund E, Hjartåker A, Agudo A, Suarez LR, Arriola L, Chirlaque MD, Ardanaz E, Sánchez MJ, Manjer J, Lindkvist B, Hallmans G, Palmqvist R, Allen N, Key T, Khaw KT, Slimani N, Rinaldi S, Romieu I, Boffetta P, Romaguera D, Norat T, Riboli E. Alcohol dehydrogenase and aldehyde dehydrogenase gene polymorphisms, alcohol intake and the risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition study. Eur J Clin Nutr 2012; 66:1303-8. [PMID: 23149980 DOI: 10.1038/ejcn.2012.173] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND/OBJECTIVES Heavy alcohol drinking is a risk factor of colorectal cancer (CRC), but little is known on the effect of polymorphisms in the alcohol-metabolizing enzymes, alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) on the alcohol-related risk of CRC in Caucasian populations. SUBJECTS/METHODS A nested case-control study (1269 cases matched to 2107 controls by sex, age, study centre and date of blood collection) was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) to evaluate the impact of rs1229984 (ADH1B), rs1573496 (ADH7) and rs441 (ALDH2) polymorphisms on CRC risk. Using the wild-type variant of each polymorphism as reference category, CRC risk estimates were calculated using conditional logistic regression, with adjustment for matching factors. RESULTS Individuals carrying one copy of the rs1229984(A) (ADH1B) allele (fast metabolizers) showed an average daily alcohol intake of 4.3 g per day lower than subjects with two copies of the rs1229984(G) allele (slow metabolizers) (P(diff)<0.01). None of the polymorphisms was associated with risk of CRC or cancers of the colon or rectum. Heavy alcohol intake was more strongly associated with CRC risk among carriers of the rs1573496(C) allele, with odds ratio equal to 2.13 (95% confidence interval: 1.26-3.59) compared with wild-type subjects with low alcohol consumption (P(interaction)=0.07). CONCLUSIONS The rs1229984(A) (ADH1B) allele was associated with a reduction in alcohol consumption. The rs1229984 (ADH1B), rs1573496 (ADH7) and rs441 (ALDH2) polymorphisms were not associated with CRC risk overall in Western-European populations. However, the relationship between alcohol and CRC risk might be modulated by the rs1573496 (ADH7) polymorphism.
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Affiliation(s)
- P Ferrari
- International Agency for Research on Cancer (IARC-WHO), Lyon, France.
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Katsetos CP, Kontoyannis MB, Koumousidis A, Petropoulou O, Delos C, Katsoulis M. Uncorrected tetralogy of Fallot and pregnancy: a case report. CLIN EXP OBSTET GYN 2012; 39:382-383. [PMID: 23157051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
We report a case of pregnancy in a 34-year-old woman with uncorrected tetralogy of Fallot (TOF). There are more risks in patients without surgical correction. In our case, haemoglobin and haematocrit were higher, oxygen saturation was lower, and right ventricular enlargement was observed. Pregnancy was resolved successfully by caesarean section. Improvement of fetomaternal outcome may be related to corrective procedures before conception to achieve better functional heart capacity. Delicate multidisciplinary medical management is essential for these limited cases to achieve optimal prognosis.
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Affiliation(s)
- C P Katsetos
- Department of Obstetrics and Gynaecology, Tzaneio General Hospital of Piraeus, Piraeus, Greece
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Keletzian E, Koumousidis A, Dimopoulos S, Varvayannis NJ, Kotelis A, Dimitroglou K, Kanellopoulos N, Katsoulis M. Contraceptive consciousness and sexual behavior in three different female age groups in Greece: a retrospective study of the evolution during the last three decades. CLIN EXP OBSTET GYN 2012; 39:160-167. [PMID: 22905455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
UNLABELLED The aim of the study is to describe the evolution of contraceptive and sexual behavior within our Greek society. MATERIALS, MEASURES AND METHODS We interviewed 508 females and made a statistical analysis of their answers. CONCLUSION We tried to underline a strategy for the best promotion of the values in question. General, sexual and contraceptive education as well as the use and type of contraception are the weapons that will lead our endeavors to decreased involuntary pregnancy and towards responsible sexual behavior.
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Affiliation(s)
- E Keletzian
- Tzaneio Hospital, General Hospital of Piraeus, Attiki, Greece
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Zizi-Sermpetzoglou A, Petrakopoulou N, Tepelenis N, Savvaidou V, Manoloudaki K, Katsoulis M. Pure Sertoli cell tumor. a case report and review of the literature. EUR J GYNAECOL ONCOL 2010; 31:117-119. [PMID: 20349797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Pure Sertoli cell tumor (SCT) is a rare sex cord tumor and a subtype of Sertoli-Leydig cell tumors according to the WHO Classification. They lack a Leydig cell component and do not contain the immature neoplastic stroma found in the neoplasms of the Sertoli-Leydig cell category. The age of the patients ranges between two and 79 years. Sertoli cell tumors occur in women of reproductive age but a few can also occur in children. The most common clinical presentation when occurring in children is isosexual pseudoprecocity. Women of reproductive age and postmenopausal women frequently present with abdominal pain, swelling and menstrual abnormalities. Occasionally SCTs occur in patients who have Peutz-Jeghers syndrome. The tumors are hormone functional in 40-60% of cases. They are often estrogenic, occasionally also androgenic or rarely both. Grossly they are usually yellow to brownish, solid or with several cystic areas. Microscopically they show always almost a tubular growth pattern, but they may also have other growth patterns which can be extensive, making the correct diagnosis difficult. These histologic patterns may result in SCTs mimicking other ovarian tumors. The immunohistochemical panel which usually includes EMA, inhibin, chromogranine, CD99 and calretinin is often helpful in establishing the diagnosis. Most SCTs are Stage I, unilateral, cytologically bland, and clinically benign, but occasional examples are high stage. About 11% of Stage I tumors have worrisome histologic features that may portend an adverse outcome.
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