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Hamilton FW, Hughes DA, Spiller W, Tilling K, Davey Smith G. Non-linear Mendelian randomization: detection of biases using negative controls with a focus on BMI, Vitamin D and LDL cholesterol. Eur J Epidemiol 2024:10.1007/s10654-024-01113-9. [PMID: 38789826 DOI: 10.1007/s10654-024-01113-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 03/07/2024] [Indexed: 05/26/2024]
Abstract
Mendelian randomisation (MR) is an established technique in epidemiological investigation, using the principle of random allocation of genetic variants at conception to estimate the causal linear effect of an exposure on an outcome. Extensions to this technique include non-linear approaches that allow for differential effects of the exposure on the outcome depending on the level of the exposure. A widely used non-linear method is the residual approach, which estimates the causal effect within different strata of the non-genetically predicted exposure (i.e. the "residual" exposure). These "local" causal estimates are then used to make inferences about non-linear effects. Recent work has identified that this method can lead to estimates that are seriously biased, and a new method-the doubly-ranked method-has been introduced as a possibly more robust approach. In this paper, we perform negative control outcome analyses in the MR context. These are analyses with outcomes onto which the exposure should have no predicted causal effect. Using both methods we find clearly biased estimates in certain situations. We additionally examined a situation for which there are robust randomised controlled trial estimates of effects-that of low-density lipoprotein cholesterol (LDL-C) reduction onto myocardial infarction, where randomised trials have provided strong evidence of the shape of the relationship. The doubly-ranked method did not identify the same shape as the trial data, and for LDL-C and other lipids they generated some highly implausible findings. Therefore, we suggest there should be extensive simulation and empirical methodological examination of performance of both methods for NLMR under different conditions before further use of these methods. In the interim, use of NLMR methods needs justification, and a number of sanity checks (such as analysis of negative and positive control outcomes, sensitivity analyses excluding removal of strata at the extremes of the distribution, examination of biological plausibility and triangulation of results) should be performed.
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Affiliation(s)
- Fergus W Hamilton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Road, BS8 2PS, Bristol, UK.
- Infection Science, North Bristol NHS Trust, Bristol, UK.
| | - David A Hughes
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Road, BS8 2PS, Bristol, UK
| | - Wes Spiller
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Road, BS8 2PS, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Road, BS8 2PS, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Road, BS8 2PS, Bristol, UK
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Burgess S, Sun YQ, Zhou A, Buck C, Mason AM, Mai XM. Body mass index and all-cause mortality in HUNT and UK biobank studies: revised non-linear Mendelian randomisation analyses. BMJ Open 2024; 14:e081399. [PMID: 38749693 PMCID: PMC11097829 DOI: 10.1136/bmjopen-2023-081399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 05/07/2024] [Indexed: 05/18/2024] Open
Abstract
OBJECTIVES To estimate the shape of the causal relationship between body mass index (BMI) and mortality risk in a Mendelian randomisation framework. DESIGN Mendelian randomisation analyses of two prospective population-based cohorts. SETTING Individuals of European ancestries living in Norway or the UK. PARTICIPANTS 56 150 participants from the Trøndelag Health Study (HUNT) in Norway and 366 385 participants from UK Biobank recruited by postal invitation. OUTCOMES All-cause mortality and cause-specific mortality (cardiovascular, cancer, non-cardiovascular non-cancer). RESULTS A previously published non-linear Mendelian randomisation analysis of these data using the residual stratification method suggested a J-shaped association between genetically predicted BMI and mortality outcomes with the lowest mortality risk at a BMI of around 25 kg/m2. However, the 'constant genetic effect' assumption required by this method is violated. The reanalysis of these data using the more reliable doubly-ranked stratification method provided some indication of a J-shaped relationship, but with much less certainty as there was less precision in estimates at the lower end of the BMI distribution. Evidence for a harmful effect of reducing BMI at low BMI levels was only present in some analyses, and where present, only below 20 kg/m2. A harmful effect of increasing BMI for all-cause mortality was evident above 25 kg/m2, for cardiovascular mortality above 24 kg/m2, for cancer mortality above 30 kg/m2 and for non-cardiovascular non-cancer mortality above 26 kg/m2. In UK Biobank, the association between genetically predicted BMI and mortality at high BMI levels was stronger in women than in men. CONCLUSION This research challenges findings from previous conventional observational epidemiology and Mendelian randomisation investigations that the lowest level of mortality risk is at a BMI level of around 25 kg/m2. Our results provide some evidence that reductions in BMI will increase mortality risk for a small proportion of the population, and clear evidence that increases in BMI will increase mortality risk for those with BMI above 25 kg/m2.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Yi-Qian Sun
- Department of Clinical and Molecular Medicine (IKOM), Norges teknisk-naturvitenskapelige universitet, Trondheim, Norway
- Department of Pathology, Clinic of Laboratory Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Center for Oral Health Services and Research Mid-Norway (TkMidt), Trondheim, Norway
| | - Ang Zhou
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Australian Centre for Precision Health, University of South Australia, Adelaide, South Australia, Australia
| | | | - Amy M Mason
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK
| | - Xiao-Mei Mai
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
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Zhang T, An Y, Shen Z, Yang H, Jiang J, Chen L, Lu Y, Xia Y. Serum urate levels and neurodegenerative outcomes: a prospective cohort study and mendelian randomization analysis of the UK Biobank. Alzheimers Res Ther 2024; 16:106. [PMID: 38730474 PMCID: PMC11088014 DOI: 10.1186/s13195-024-01476-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND Previous studies on the associations between serum urate levels and neurodegenerative outcomes have yielded inconclusive results, and the causality remains unclear. This study aimed to investigate whether urate levels are associated with the risks of Alzheimer's disease and related dementias (ADRD), Parkinson's disease (PD), and neurodegenerative deaths. METHODS This prospective study included 382,182 participants (45.7% men) from the UK Biobank cohort. Cox proportional hazards models were used to assess the associations between urate levels and risk of neurodegenerative outcomes. In the Mendelian randomization (MR) analysis, urate-related single-nucleotide polymorphisms were identified through a genome-wide association study. Both linear and non-linear MR approaches were utilized to investigate the potential causal associations. RESULTS During a median follow-up period of 12 years, we documented 5,400 ADRD cases, 2,553 PD cases, and 1,531 neurodegenerative deaths. Observational data revealed that a higher urate level was associated with a decreased risk of ADRD (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90, 0.96), PD (HR: 0.87, 95% CI: 0.82, 0.91), and neurodegenerative death (HR: 0.88, 95% CI: 0.83, 0.94). Negative linear associations between urate levels and neurodegenerative events were observed (all P-values for overall < 0.001 and all P-values for non-linearity > 0.05). However, MR analyses yielded no evidence of either linear or non-linear associations between genetically predicted urate levels and the risk of the aforementioned neurodegenerative events. CONCLUSION Although the prospective cohort study demonstrated that elevated urate levels were associated with a reduced risk of neurodegenerative outcomes, MR analyses found no evidence of causality.
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Affiliation(s)
- Tingjing Zhang
- School of Public Health, Wannan Medical College, Wuhu, China
- Institutes of Brain Science, Wannan Medical College, Wuhu, China
| | - Yu An
- Department of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Zhenfei Shen
- Department of Clinical Nutrition, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Honghao Yang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Jinguo Jiang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China
| | - Liangkai Chen
- Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yanhui Lu
- School of Nursing, Peking University, No. 38 Xueyuan Rd, Haidian District, Beijing, 100191, China.
| | - Yang Xia
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, No. 36, San Hao Street, Shenyang, Liaoning, 110004, China.
- Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China.
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Ferrari G, de Maio Nascimento M, Petermann-Rocha F, Rezende LFM, O'Donovan G, Gouveia ÉR, Cristi-Montero C, Marques A. Lifestyle risk factors and all-cause and cause-specific mortality in the Mexico City prospective study: Assessing the influence of reverse causation. J Affect Disord 2024; 352:517-524. [PMID: 38408614 DOI: 10.1016/j.jad.2024.02.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/15/2024] [Accepted: 02/19/2024] [Indexed: 02/28/2024]
Abstract
BACKGROUND We examined the association between individual lifestyle risk factors with all-cause and cause-specific mortality. METHODS Prospective cohort study including 155,002 participants from the Mexico City Prospective Study. Cox regression models were used to estimate the association between individual lifestyle risk factors and all-cause and cause-specific mortality. Participants with prevalent diseases at baseline and participants who died during the first 2, 5, 10, and 15 years of follow-up were excluded to account for reverse causation. RESULTS 27,469 people died during 18.3 years of follow-up years. Overweight and moderate alcohol consumption were inversely associated with all-cause mortality, while low physical activity and smoking were positively associated when all participants were included, regardless of prevalent disease or duration of follow-up. The direction of the association of overweight with all-cause mortality changed from inverse to positive after excluding the first 10 years of follow-up. Compared with normal weight, the hazard ratio (95 % confidence interval) was 1.17 (1.13,1.22) for obesity after excluding those who died in the first 5 years of follow-up and 1.71 (1.59,1.84) after excluding the first 15 years of follow-up. The magnitude of the association of alcohol intake, low physical activity, and smoking with mortality attenuated, whereas for fruits and vegetables increased, after excluding longer periods of follow-up. LIMITATIONS The data were collected exclusively in Mexico City; lifestyle risk factors were self-reported and thus prone to misclassification bias. CONCLUSIONS Reverse causation may influence both the magnitude and the direction of the associations between lifestyle risk factors and mortality.
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Affiliation(s)
- Gerson Ferrari
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Providencia, Chile; Universidad de Santiago de Chile (USACH), Escuela de Ciencias de la Actividad Física, el Deporte y la Salud, Santiago, Chile.
| | | | - Fanny Petermann-Rocha
- Centro de Investigación Biomédica, Facultad de Medicina, Universidad Diego Portales, Santiago, Chile
| | - Leandro F M Rezende
- Departamento de Medicina Preventiva, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Gary O'Donovan
- Instituto Masira, Universidad de Santander, Bucaramanga, Colombia; Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Facultad de Medicina, Universidad de los Andes, Bogotá, Colombia
| | - Élvio R Gouveia
- Department of Physical Education and Sport, University of Madeira, Funchal, Portugal; Laboratory of Robotics and Engineering Systems (LARSYS), Interactive Technologies Institute, Funchal, Portugal
| | - Carlos Cristi-Montero
- IRyS Group, Physical Education School, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile
| | - Adilson Marques
- CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal; Faculdade de Medicina, ISAMB, Universidade de Lisboa, Lisbon, Portugal
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Chen H, Zhao D, Guo Z, Ma D, Wu Y, Chen G, Liu Y, Kong T, Wang F. U-shaped relationship between lights-out time and nocturnal oxygen saturation during the first trimester: An analysis based on the nuMOM2b-SDB data. Heliyon 2024; 10:e29494. [PMID: 38681541 PMCID: PMC11053181 DOI: 10.1016/j.heliyon.2024.e29494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 05/01/2024] Open
Abstract
Objective Preventing adverse events due to unstable oxygen saturation (SpO2) at night in pregnant women is of utmost importance. Poor sleep has been demonstrated to impact SpO2 levels. Nowadays, many gravida have a habit of prolonged exposure to light before sleep, which can disrupt their sleep. Therefore, this study aimed at investigate the relationship between lights-out time, sleep parameters and SpO2, exploring the underlying mechanisms. Methods The data of 2881 eligible subjects from the Nulliparous Pregnancy Outcomes Study Monitoring Mothers-to-be and Sleep Disordered Breathing (nuMOM2b-SDB) database were analyzed. Multiple linear regression models were used to investigate the relationship between lights-out time and SpO2. In addition, restricted cubic splines (RCS) were employed to fit the nonlinear correlation between the two variables. The smoothing curve method was further utilized to depict the relationship between lights-out time and SpO2 based on various subgroup variables. Results All participants were categorized according to race/ethnicity. A negative correlation was observed between nighttime lights-out time and average value of SpO2 (Avg-SpO2) (β = -0.05, p = 0.010). RCS revealed a U-shaped relationship between lights-out time and Avg-SpO2, with the turning point at 22:00. The subcomponent stratification results indicated that the Avg-SpO2 and minimum value of SpO2(Min-SpO2) of advanced maternal age decreased as the lights-out time was delayed. Furthermore, overweight and obese gravida showed lower Avg-SpO2 and Min-SpO2 levels than normal weight. Conclusions A U-shaped relationship was identified between lights-out time and nocturnal Avg-SpO2 during early pregnancy, with the inflection at 22:00. Notably, later lights-out times are associated with lower levels of Min-SpO2 for advanced maternal age. The findings suggest that appropriately adjusting the duration of light exposure before sleep and maintaining a relatively restful state may be more beneficial for the stability of SpO2 in pregnant women. Conversely, deviations from these practices could potentially lead to pathological alterations in SpO2 levels.
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Affiliation(s)
- Hongxu Chen
- School of Public Health, Xinjiang Medical University, Urumqi, 830063, China
| | - Danyang Zhao
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot, 010110, China
| | - Zixuan Guo
- Medical Neurobiology Lab, Inner Mongolia Medical University, Huhhot, 010110, China
| | - Duo Ma
- Department of Ultrasonography, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China
| | - Yan Wu
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China
| | - Guangxue Chen
- Department of Gynaecology and Obstetrics, Beijing Jishuitan Hospital, Beijing, 102208, China
| | - Yanlong Liu
- School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China
| | - Tiantian Kong
- Xinjiang Key Laboratory of Neurological Disorder Research, The Second Affiliated Hospital of Xinjiang Medical University, Urumqi, 830063, China
| | - Fan Wang
- Beijing Hui-Long-Guan Hospital, Peking University, Beijing, 100096, China
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de Lima AP, Nunes APDOB, Nicoletti CF, Benatti FB. Trend in the Prevalence of Overweight and Obese Adults in São Paulo, Brazil: Analysis between the Years 2006 and 2019. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:502. [PMID: 38673413 PMCID: PMC11049843 DOI: 10.3390/ijerph21040502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/11/2024] [Accepted: 03/14/2024] [Indexed: 04/28/2024]
Abstract
The aim of this study was to investigate the trend in the prevalence of overweight and obese adults in São Paulo, Brazil, between 2006 and 2019 across chronic diseases and the domains of physical activity. A descriptive retrospective study was carried out on the trend in the prevalence of 26.612 overweight and obese adults (10.150 men and 16.462 women). All data analyzed were based on information from the national system for monitoring risk factors called Protective and Risk Factors for Chronic Diseases by Telephone Survey-VIGITEL. The variables obese and overweight were analyzed in general and stratified by sex, age group, education level, each type of physical activity domain (yes or no), presence of hypertension and diabetes (yes or no), and smoking (yes or no). The prevalence of obesity significantly increased from 11.1% in 2006 to 19.8% in 2019, regardless of age, sex, physical activity practice, and presence of diabetes or hypertension, except for people aged 55-64 y, working people, and smokers. The total prevalence of overweight adults significantly increased overall (from 30.5% in 2006 to 33.4% in 2019) but it significantly increased only in females, in people aged 18-24 y, those who are non-white, those with an education level of 9-11 y, those who are not working, those who are non-smokers, those who did not have diabetes or hypertension, and those who were not physically active during leisure time but physically active at work and at home. There was a significant increase in the prevalence of overweight adults and especially of obese adults living in the city of São Paulo (Brazil) between 2006 and 2019, the latter being observed in nearly every analyzed sub-category, regardless of age, sex, physical activity practice, and presence of diabetes or hypertension.
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Affiliation(s)
- Alisson Padilha de Lima
- School of Medicine, University of Sao Paulo-FMUSP, Sao Paulo 05508-220, SP, Brazil; (A.P.d.O.B.N.); (C.F.N.); (F.B.B.)
- School of Physical Education, Faculty IELUSC, Joinville 89201-270, SC, Brazil
| | | | - Carolina Ferreira Nicoletti
- School of Medicine, University of Sao Paulo-FMUSP, Sao Paulo 05508-220, SP, Brazil; (A.P.d.O.B.N.); (C.F.N.); (F.B.B.)
| | - Fabiana Braga Benatti
- School of Medicine, University of Sao Paulo-FMUSP, Sao Paulo 05508-220, SP, Brazil; (A.P.d.O.B.N.); (C.F.N.); (F.B.B.)
- Faculdade de Ciências Aplicadas, Universidade Estadual de Campinas, Limeira 13484-350, SP, Brazil
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Tao L, Miao L, Guo YJ, Liu YL, Xiao LH, Yang ZJ. Associations of body roundness index with cardiovascular and all-cause mortality: NHANES 2001-2018. J Hum Hypertens 2024; 38:120-127. [PMID: 37752175 DOI: 10.1038/s41371-023-00864-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 08/31/2023] [Accepted: 09/15/2023] [Indexed: 09/28/2023]
Abstract
Body roundness index (BRI) was associated with cardiovascular diseases. But the relationship between BRI with cardiovascular disease (CVD) mortality and all-cause mortality remains largely unknown in hypertensive patients. This prospective cohort study included patients with hypertension who participated in the National Health and Nutrition Examination Survey (NHANES) from 2001 through 2018, and aimed to evaluate the association between BRI with CVD mortality and all-cause mortality. A total of 15570 patients were included. Over a median follow-up of 8.0 years (interquartile range, 4.3-12.6 years), 3445 individuals died, including 1166 CVD deaths. Weighted restricted cubic spline regression results showed a nonlinear association between BRI and CVD mortality and all-cause mortality (both P for nonlinear trend <0.001). The weighted multivariate Cox proportional hazards regression showed the hazard ratio (HRs) for CVD mortality were 0.93 (95% CI: 0.84-1.03, P = 0.160) in the low levels of BRI (≤5.9) and 1.11 (95% CI: 1.05-1.19, P < 0.001) in the high levels of BRI (>5.9). Similar associations were observed for all-cause mortality, the HRs were 0.91 (95% CI: 0.87-0.96, P < 0.001) in the low levels of BRI (≤6.3) and 1.09 (95% CI: 1.05-1.13, P < 0.001) in the high levels of BRI (>6.3). This cohort study supported that BRI was nonlinearly associated with CVD mortality and all-cause mortality among patients with hypertension. The thresholds of 5.9 and 6.3 for CVD mortality and all-cause mortality, respectively, may represent intervention targets for lowering the risk of premature death, but this needs to be confirmed in large clinical trials.
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Affiliation(s)
- Lin Tao
- Departments of Cardiology, Liuzhou People's Hospital, 8 Wenchang Road, Liuzhou, 545006, Guangxi, People's Republic of China
| | - Liu Miao
- Departments of Cardiology, Liuzhou People's Hospital, 8 Wenchang Road, Liuzhou, 545006, Guangxi, People's Republic of China
| | - Yu-Jie Guo
- Departments of Cardiology, Liuzhou People's Hospital, 8 Wenchang Road, Liuzhou, 545006, Guangxi, People's Republic of China
| | - Yan-Li Liu
- Departments of Cardiology, Liuzhou People's Hospital, 8 Wenchang Road, Liuzhou, 545006, Guangxi, People's Republic of China
| | - Li-Hong Xiao
- Departments of General Medicine, Liuzhou People's Hospital, 8 Wenchang Road, Liuzhou, 545006, Guangxi, People's Republic of China
| | - Zhi-Jie Yang
- Departments of Cardiology, Liuzhou People's Hospital, 8 Wenchang Road, Liuzhou, 545006, Guangxi, People's Republic of China.
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Wang Y, Hua Y, Zhang H, Liang S, Cao Z, Chen L, Su Z, Zhang W. Ratio of waist circumference to body mass index: A novel predictor of clinical outcome in hypertension patients. J Clin Hypertens (Greenwich) 2024; 26:24-35. [PMID: 37864476 PMCID: PMC10795094 DOI: 10.1111/jch.14739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/05/2023] [Accepted: 10/13/2023] [Indexed: 10/22/2023]
Abstract
We aim to investigate the influence of waist circumference and body mass index (BMI) on all-cause death and cardiovascular-specific death in patients with hypertension. This prospective cohort study, based on waist circumference and body mass index measurements in patients with hypertension, provided risk estimates of all-cause mortality and cardiovascular events. The waist circumference-to-BMI ratio (WtBR) is an anthropometric measure integrating waist circumference and BMI. We utilized multivariable Cox regression analysis, restricted cubic spline model, Kaplan-Meier plot, random forest analysis, and sensitivity analysis to assess the relationship of WtBR with all-cause mortality. Subsequently, Fine-Gray competing risk regression models were applied to precisely evaluate the probability of cardiovascular-specific death attributed to high WtBR. The results indicate that thea deceased group showed significantly higher WtBR and lower BMI compared with the alive groups (P < .05), while no significant difference was observed in waist circumference (P = .373). When analyzed as continuous, the risk of all-cause death elevated with increasing WtBR in the adjusted model with an HR of 2.42 (95% CI, 2.06-2.85). The restricted cubic spline illustrated an elevated risk of all-cause mortality as WtBR increased (J-shaped curve). Nevertheless, WtBR showed no significant association with cardiovascular-specific death and the prediction model exhibited a reliable performance in the testing set. This study supported that WtBR, an anthropometric measure, is independently associated with all-cause death in hypertensive patients. It's advisable to routinely assess waist circumference in hypertensive patients regardless of BMI, in order to more effectively manage the risk of obesity-related health.
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Affiliation(s)
| | - Yang Hua
- Nanjing Medical UniversityNanjingChina
| | | | | | | | - Lu‐Lu Chen
- Department of Anatomy, Histology, and EmbryologyNanjing Medical UniversityNanjingChina
| | | | - Wei Zhang
- Department of Anatomy, Kangda CollegeNanjing Medical UniversityLianyungangJiangsuChina
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Al‐dolaimy F, Abdul‐Reda Hussein U, Hadi Kzar M, Saud A, Abed Jawad M, Yaseen Hasan S, Alhassan MS, Hussien Alawadi A, Alsaalamy A, Farzan R. Relationship between body mass index and mortality of burns patients: A systematic review and meta-analysis. Int Wound J 2024; 21:e14358. [PMID: 37654247 PMCID: PMC10781895 DOI: 10.1111/iwj.14358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 08/05/2023] [Accepted: 08/07/2023] [Indexed: 09/02/2023] Open
Abstract
This systematic review and meta-analysis aimed to evaluate the relationship between body mass index (BMI) and mortality of burn patients. A comprehensive, systematic search was conducted in different international electronic databases, such as Scopus, PubMed, Web of Science and Persian electronic databases such as Iranmedex, and Scientific Information Database (SID) using keywords extracted from Medical Subject Headings such as "Body mass index", "Burns" and "Mortality" from the earliest to the April 1, 2023. The quality of the studies included in this systematic review was evaluated using the appraisal tool for cross-sectional studies (AXIS tool). Finally, six articles were included in this systematic review and meta-analysis. A total of 16 154 burn patients participated in six studies. Their mean age was 46.32 (SD = 1.99). Of the participants, 71.7% were males. The mean length of hospitalization was 18.80 (SD = 8.08) days, and the average TBSA in burn patients was 38.32 (SD = 2.79) %. Also, the average BMI in burn patients was 27.10 (SD = 1.75). Results found mortality in patients with abnormal BMI (overweight to morbidity BMI) was 0.19 more than normal BMI (ES: 1.19, 95%CI: 0.76-1.87, Z = 0.75, I2 : 71.8%, p = 0.45). Results of linear dose-response showed each 5 kg/m2 increase in BMI was associated with a 5% increase in mortality that was marginally significant (ES: 1.05, 95%CI: 1.00-1.11, Z = 1.99, I2 : 22.2%, p = 0.047). There was a non-linear relationship between levels of BMI and mortality (Prob > χ2 = 0.02). There was an increase in mortality from percentile 10 to 50, although it was not significant (Correlational coefficient: 0.01, p = 0.85). Also, there was an increase in mortality rate from percentile 50 to 90 that was statistically significant (correlational coefficient: 0.06, p = 0.047). Finally, the results of the study indicated BMI can increase the chance of mortality by 0.19, although it was not significant. As a result, more studies are needed to better judge the relationship between BMI and mortality in burn victims.
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Affiliation(s)
| | | | - Mazin Hadi Kzar
- College of Physical Education and Sport SciencesAl‐Mustaqbal UniversityBabylonIraq
| | - Abdulnaser Saud
- Anesthesia Techniques DepartmentAl‐Hadi University CollegeBaghdadIraq
| | | | - Saif Yaseen Hasan
- College of Health and Medical TechnologyNational University of Science and TechnologyThi‐QarIraq
| | - Muataz S. Alhassan
- Division of advanced nano material technologies, Scientific Research CenterAl‐Ayen UniversityThi‐QarIraq
| | - Ahmed Hussien Alawadi
- College of Technical EngineeringThe Islamic UniversityNajafIraq
- College of Technical EngineeringThe Islamic University of Al DiwaniyahAl DiwaniyahIraq
- College of Technical EngineeringThe Islamic University of BabylonBabylonIraq
| | - Ali Alsaalamy
- College of Technical EngineeringImam Ja'afar Al‐Sadiq UniversityAl‐MuthannaIraq
| | - Ramyar Farzan
- Department of Plastic & Reconstructive Surgery, School of MedicineGuilan University of Medical SciencesRashtIran
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10
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Wang Z, Xiao Y, Lu J, Zou C, Huang W, Zhang J, Liu S, Han L, Jiao F, Tian D, Jiang Y, Du X, Ma RCW, Jiang G. Investigating linear and nonlinear associations of LDL cholesterol with incident chronic kidney disease, atherosclerotic cardiovascular disease and all-cause mortality: A prospective and Mendelian randomization study. Atherosclerosis 2023; 387:117394. [PMID: 38029611 DOI: 10.1016/j.atherosclerosis.2023.117394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND AIMS Observational studies suggest potential nonlinear associations of low-density lipoprotein cholesterol (LDL-C) with cardio-renal diseases and mortality, but the causal nature of these associations is unclear. We aimed to determine the shape of causal relationships of LDL-C with incident chronic kidney disease (CKD), atherosclerotic cardiovascular disease (ASCVD) and all-cause mortality, and to evaluate the absolute risk of adverse outcomes contributed by LDL-C itself. METHODS Observational analysis and one-sample Mendelian randomization (MR) with linear and nonlinear assumptions were performed using the UK Biobank of >0.3 million participants with no reported prescription of lipid-lowering drugs. Two-sample MR on summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen (N = 625,219) was employed to replicate the relationship for kidney traits. The 10-year probabilities of the outcomes was estimated by integrating the MR and Cox models. RESULTS Observationally, participants with low LDL-C were significantly associated with a decreased risk of ASCVD, but an increased risk of CKD and all-cause mortality. Univariable MR showed an inverse total effect of LDL-C on incident CKD (HR [95% CI]:0.84 [0.73-0.96]; p = 0.011), a positive effect on ASCVD (1.41 [1.29-1.53]; p<0.001), and no significant causal effect on all-cause mortality. Multivariable MR, controlling for high-density lipoprotein cholesterol (HDL-C) and triglycerides, identified a positive direct effect on ASCVD (1.32 [1.18-1.47]; p<0.001), but not on CKD and all-cause mortality. These results indicated that genetically predicted low LDL-C had an inverse indirect effect on CKD mediated by HDL-C and triglycerides, which was validated by a two-sample MR analysis using summary-level data from the Global Lipid Genetics Consortium (N = 296,680) and the CKDGen consortium (N = 625,219). Suggestive evidence of a nonlinear causal association between LDL-C and CKD was found. The 10-year probability curve showed that LDL-C concentrations below 3.5 mmol/L were associated with an increased risk of CKD. CONCLUSIONS In the general population, lower LDL-C was causally associated with lower risk of ASCVD, but appeared to have a trade-off for an increased risk of CKD, with not much effect on all-cause mortality. LDL-C concentration below 3.5 mmol/L may increase the risk of CKD.
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Affiliation(s)
- Zhenqian Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yang Xiao
- National Clinical Research Centre for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jiawen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Chenfeng Zou
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Wenyu Huang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Jiaying Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Liyuan Han
- Department of Global Health, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, China
| | - Feng Jiao
- Guangzhou Centre for Applied Mathematics, Guangzhou University, Guangzhou, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yawen Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China; Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, Guangdong, China; School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
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11
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Wade KH, Hamilton FW, Carslake D, Sattar N, Davey Smith G, Timpson NJ. Challenges in undertaking nonlinear Mendelian randomization. Obesity (Silver Spring) 2023; 31:2887-2890. [PMID: 37845826 PMCID: PMC7615556 DOI: 10.1002/oby.23927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 08/24/2023] [Accepted: 09/05/2023] [Indexed: 10/18/2023]
Abstract
Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J-shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization.
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Affiliation(s)
- Kaitlin H. Wade
- Medical Research Council (MRC) Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
| | - Fergus W. Hamilton
- Medical Research Council (MRC) Integrative Epidemiology UnitUniversity of BristolBristolUK
- Infection ScienceNorth Bristol NHS TrustBristolUK
| | - David Carslake
- Medical Research Council (MRC) Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research CentreUniversity of GlasgowGlasgowUK
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
| | - Nicholas J. Timpson
- Medical Research Council (MRC) Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
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12
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Gamwell JM, Paphiti K, Hodson L, Karpe F, Pinnick KE, Todorčević M. An optimised protocol for the investigation of insulin signalling in a human cell culture model of adipogenesis. Adipocyte 2023; 12:2179339. [PMID: 36763512 PMCID: PMC9980465 DOI: 10.1080/21623945.2023.2179339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 02/07/2023] [Indexed: 02/11/2023] Open
Abstract
While there is no standardized protocol for the differentiation of human adipocytes in culture, common themes exist in the use of supra-physiological glucose and hormone concentrations, and an absence of exogenous fatty acids. These factors can have detrimental effects on some aspects of adipogenesis and adipocyte function. Here, we present methods for modifying the adipogenic differentiation protocol to overcome impaired glucose uptake and insulin signalling in human adipose-derived stem cell lines derived from the stromal vascular fraction of abdominal and gluteal subcutaneous adipose tissue. By reducing the length of exposure to adipogenic hormones, in combination with a physiological glucose concentration (5 mM), and the provision of exogenous fatty acids (reflecting typical dietary fatty acids), we were able to restore early insulin signalling events and glucose uptake, which were impaired by extended use of hormones and a high glucose concentration, respectively. Furthermore, the addition of exogenous fatty acids greatly increased the storage of triglycerides and removed the artificial demand to synthesize all fatty acids by de novo lipogenesis. Thus, modifying the adipogenic cocktail can enhance functional aspects of human adipocytes in vitro and is an important variable to consider prior to in vitro investigations into adipocyte biology.
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Affiliation(s)
- Jonathan M. Gamwell
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Headington, UK
| | - Keanu Paphiti
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Headington, UK
| | - Leanne Hodson
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Headington, UK
- NIHR Oxford Biomedical Research Centre, OUH Foundation Trust, Oxford, UK
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Headington, UK
- NIHR Oxford Biomedical Research Centre, OUH Foundation Trust, Oxford, UK
| | - Katherine E. Pinnick
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Headington, UK
| | - Marijana Todorčević
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Churchill Hospital, Headington, UK
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13
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Wang Y, Liu X, Xue T, Chen Y, Yang Q, Tang Z, Chen L, Zhang L. Body mass index and risk of all-cause mortality among elderly Chinese: An empirical cohort study based on CLHLS data. Prev Med Rep 2023; 35:102308. [PMID: 37455755 PMCID: PMC10339046 DOI: 10.1016/j.pmedr.2023.102308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/28/2023] [Accepted: 06/29/2023] [Indexed: 07/18/2023] Open
Abstract
The aim of our study was to evaluate the relationship between body mass index (BMI) and all-cause mortality among elderly Chinese. The subjects of our study were a cohort of 13 319 elderly Chinese enrolled between 2008 and 2018. Participants were classified in three groups: underweight (<18.5 kg/m2), normal weight (18.5-24.9 kg/m2), overweight and obese (≥25 kg/m2) according to different BMI levels. Cox proportional-hazards regression model was used to analyze the association between BMI grouping and the risk of mortality among the three groups and each corresponding subgroup. The restricted cubic spline regression was performed to investigate the variation tendency of BMI and mortality in different groups and subgroups. We found that the hazard ratios (HRs) of mortality in the underweight and the normal-weight groups were 1.213 and 1.104, respectively, compared with those in the overweight and obesity groups. HR for mortality decreased as BMI increased, although this phenomenon was not observed as not a linear relationship in all participants. Nonetheless, this nonlinear relationship was significant in type 2 diabetes patients. Among subjects with non-type 2 diabetes, the shape of the negative curve, reflecting the HR for BMI and mortality, decreased when BMI increased. Our findings suggest that an obesity paradox exists in non-type 2 diabetes patients, in which BMI has a nonlinear negative relationship with mortality. Conversely, in type 2 diabetes patients there is a U-shaped association. Obesity may thus be protective for all-cause mortality among non-diabetic older populations.
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Affiliation(s)
- Yun Wang
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
| | - Xuekui Liu
- Department of Central Laboratory, Xuzhou Central Hospital, Xuzhou, Jiangsu, China
| | - Tongneng Xue
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
| | - Yu Chen
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
| | - Qianqian Yang
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
| | - Zhengwen Tang
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
| | - Lianhua Chen
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
| | - Liqin Zhang
- The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, Huaian, Jiangsu, China
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14
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Rudym D, Pham T, Rackley CR, Grasselli G, Anderson M, Baldwin MR, Beitler J, Agerstrand C, Serra A, Winston LA, Bonadonna D, Yip N, Emerson LJ, Dzierba A, Sonett J, Abrams D, Ferguson ND, Bacchetta M, Schmidt M, Brodie D. Mortality in Patients with Obesity and Acute Respiratory Distress Syndrome Receiving Extracorporeal Membrane Oxygenation: The Multicenter ECMObesity Study. Am J Respir Crit Care Med 2023; 208:685-694. [PMID: 37638735 PMCID: PMC10515561 DOI: 10.1164/rccm.202212-2293oc] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 07/19/2023] [Indexed: 08/29/2023] Open
Abstract
Rationale: Patients with obesity are at increased risk for developing acute respiratory distress syndrome (ARDS). Some centers consider obesity a relative contraindication to receiving extracorporeal membrane oxygenation (ECMO) support, despite growing implementation of ECMO for ARDS in the general population. Objectives: To investigate the association between obesity and mortality in patients with ARDS receiving ECMO. Methods: In this large, international, multicenter, retrospective cohort study, we evaluated the association of obesity, defined as body mass index ⩾ 30 kg/m2, with ICU mortality in patients receiving ECMO for ARDS by performing adjusted multivariable logistic regression and propensity score matching. Measurements and Main Results: Of 790 patients with ARDS receiving ECMO in our study, 320 had obesity. Of those, 24.1% died in the ICU, compared with 35.3% of patients without obesity (P < 0.001). In adjusted models, obesity was associated with lower ICU mortality (odds ratio, 0.63 [95% confidence interval, 0.43-0.93]; P = 0.018). Examined as a continuous variable, higher body mass index was associated with decreased ICU mortality in multivariable regression (odds ratio, 0.97 [95% confidence interval, 0.95-1.00]; P = 0.023). In propensity score matching of 199 patients with obesity to 199 patients without, patients with obesity had a lower probability of ICU death than those without (22.6% vs. 35.2%; P = 0.007). Conclusions: Among patients receiving ECMO for ARDS, those with obesity had lower ICU mortality than patients without obesity in multivariable and propensity score matching analyses. Our findings support the notion that obesity should not be considered a general contraindication to ECMO.
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Affiliation(s)
- Darya Rudym
- Department of Medicine, New York University Langone Health, New York, New York
| | - Tài Pham
- Service de Médecine Intensive-Réanimation, Assistance Publique–Hôpitaux de Paris, Hôpital de Bicêtre, DMU CORREVE, FHU SEPSIS, Groupe de Recherche CARMAS, Le Kremlin-Bicêtre, France
- Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Sud, Inserm U1018, Equipe d’Epidémiologie Respiratoire Intégrative, Centre d’Épidémiologie et de Santé des Populations, Villejuif, France
| | | | - Giacomo Grasselli
- Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italia
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Michaela Anderson
- Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Matthew R. Baldwin
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | - Jeremy Beitler
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Center for Acute Respiratory Failure and
| | - Cara Agerstrand
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Center for Acute Respiratory Failure and
| | - Alexis Serra
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
| | | | - Desiree Bonadonna
- Perfusion Services, Duke University Health System, Durham, North Carolina
| | - Natalie Yip
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Center for Acute Respiratory Failure and
| | - Logan J. Emerson
- Duke Respiratory Care Services, Duke University Hospital, Durham, North Carolina
| | - Amy Dzierba
- Center for Acute Respiratory Failure and
- Department of Pharmacy, NewYork-Presbyterian Hospital, New York, New York
| | | | - Darryl Abrams
- Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York
- Center for Acute Respiratory Failure and
| | - Niall D. Ferguson
- Interdepartmental Division of Critical Care Medicine
- Department of Medicine
- Department of Physiology, and
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Division of Respirology, University Health Network and Sinai Health, Toronto, Ontario, Canada
- Toronto General Hospital Research Institute, Toronto, Ontario, Canada
| | - Matthew Bacchetta
- Department of Cardiac Surgery, Vanderbilt Medical Center East, Nashville, Tennessee
| | - Matthieu Schmidt
- Sorbonne Université, GRC 30 RESPIRE, UMRS_1166-ICAN, Paris, France
- Service de Médecine Intensive-Réanimation, Institut de Cardiologie, Assistance Publique–Hôpitaux de Paris Hôpital Pitié–Salpêtrière, Paris, France; and
| | - Daniel Brodie
- Department of Medicine, School of Medicine, John Hopkins University, Baltimore, Maryland
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15
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Khan I, Chong M, Le A, Mohammadi-Shemirani P, Morton R, Brinza C, Kiflen M, Narula S, Akhabir L, Mao S, Morrison K, Pigeyre M, Paré G. Surrogate Adiposity Markers and Mortality. JAMA Netw Open 2023; 6:e2334836. [PMID: 37728925 PMCID: PMC10512100 DOI: 10.1001/jamanetworkopen.2023.34836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 08/15/2023] [Indexed: 09/22/2023] Open
Abstract
Importance Body mass index (BMI) is an easily obtained adiposity surrogate. However, there is variability in body composition and adipose tissue distribution between individuals with the same BMI, and there is controversy regarding the BMI associated with the lowest mortality risk. Objective To evaluate which of BMI, fat mass index (FMI), and waist-to-hip (WHR) has the strongest and most consistent association with mortality. Design, Setting, and Participant This cohort study used incident deaths from the UK Biobank (UKB; 2006-2022), which includes data from 22 clinical assessment centers across the United Kingdom. UKB British participants of British White ancestry (N = 387 672) were partitioned into a discovery cohort (n = 337 078) and validation cohort (n = 50 594), with the latter consisting of 25 297 deaths and 25 297 controls. The discovery cohort was used to derive genetically determined adiposity measures while the validation cohort was used for analyses. Exposure-outcome associations were analyzed through observational and mendelian randomization (MR) analyses. Exposures BMI, FMI, and WHR. Main Outcomes and Measures All-cause and cause-specific (cancer, cardiovascular disease [CVD], respiratory disease, or other causes) mortality. Results There were 387 672 and 50 594 participants in our observational (mean [SD] age, 56.9 [8.0] years; 177 340 [45.9%] male, 210 332 [54.2%], female), and MR (mean [SD] age, 61.6 [6.2] years; 30 031 [59.3%] male, 20 563 [40.6%], female) analyses, respectively. Associations between measured BMI and FMI with all-cause mortality were J-shaped, whereas the association of WHR with all-cause mortality was linear using the hazard ratio (HR) scale (HR per SD increase of WHR, 1.41 [95% CI, 1.38-1.43]). Genetically determined WHR had a stronger association with all-cause mortality than BMI (odds ratio [OR] per SD increase of WHR, 1.51 [95% CI, 1.32-1.72]; OR per SD increase of BMI, 1.29 [95% CI, 1.20-1.38]; P for heterogeneity = .02). This association was stronger in male than female participants (OR, 1.89 [95% CI, 1.54-2.32]; P for heterogeneity = .01). Unlike BMI or FMI, the genetically determined WHR-all-cause mortality association was consistent irrespective of observed BMI. Conclusions and Relevance In this cohort study, WHR had the strongest and most consistent association with mortality irrespective of BMI. Clinical recommendations should consider focusing on adiposity distribution compared with mass.
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Affiliation(s)
- Irfan Khan
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- College of Medicine and Health, University College Cork, Cork, Ireland
| | - Michael Chong
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Ann Le
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Pedrum Mohammadi-Shemirani
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Robert Morton
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Christina Brinza
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- School of Medicine, Queen’s University, Kingston, Ontario, Canada
| | - Michel Kiflen
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Temerty Faculty of Medicine, University of Toronto, Medical Sciences Building, Toronto, Ontario, Canada
| | - Sukrit Narula
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut
| | - Loubna Akhabir
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Shihong Mao
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Katherine Morrison
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada
- Centre for Metabolism, Obesity and Diabetes Research, McMaster University, Hamilton, Ontario, Canada
| | - Marie Pigeyre
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Guillaume Paré
- Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Hamilton, Ontario, Canada
- Thrombosis and Atherosclerosis Research Institute, David Barley Cardiac, Vascular and Stroke Research, Hamilton, Ontario, Canada
- Department of Pathology and Molecular Medicine, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
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16
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Burgess S. Violation of the Constant Genetic Effect Assumption Can Result in Biased Estimates for Non-Linear Mendelian Randomization. Hum Hered 2023; 88:79-90. [PMID: 37651993 PMCID: PMC10614256 DOI: 10.1159/000531659] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 06/12/2023] [Indexed: 09/02/2023] Open
Abstract
INTRODUCTION Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice. METHODS We use the recently developed doubly ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D (25[OH]D) used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality. RESULTS The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method but not for the doubly ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures and less reasonable for others. If the doubly ranked method indicates that this assumption is violated, then estimates from both the residual and doubly ranked methods can be biased, although bias was smaller on average in the doubly ranked method. CONCLUSION Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly ranked methods, as well as consider transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge, UK
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North TL, Harrison S, Bishop DC, Wootton RE, Carter AR, Richardson TG, Payne RA, Salisbury C, Howe LD. Educational inequality in multimorbidity: causality and causal pathways. A mendelian randomisation study in UK Biobank. BMC Public Health 2023; 23:1644. [PMID: 37641019 PMCID: PMC10463319 DOI: 10.1186/s12889-023-16369-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 07/24/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Multimorbidity, typically defined as having two or more long-term health conditions, is associated with reduced wellbeing and life expectancy. Understanding the determinants of multimorbidity, including whether they are causal, may help with the design and prioritisation of prevention interventions. This study seeks to assess the causality of education, BMI, smoking and alcohol as determinants of multimorbidity, and the degree to which BMI, smoking and alcohol mediate differences in multimorbidity by level of education. METHODS Participants were 181,214 females and 155,677 males, mean ages 56.7 and 57.1 years respectively, from UK Biobank. We used a Mendelian randomization design; an approach that uses genetic variants as instrumental variables to interrogate causality. RESULTS The prevalence of multimorbidity was 55.1%. Mendelian randomization suggests that lower education, higher BMI and higher levels of smoking causally increase the risk of multimorbidity. For example, one standard deviation (equivalent to 5.1 years) increase in genetically-predicted years of education decreases the risk of multimorbidity by 9.0% (95% CI: 6.5 to 11.4%). A 5 kg/m2 increase in genetically-predicted BMI increases the risk of multimorbidity by 9.2% (95% CI: 8.1 to 10.3%) and a one SD higher lifetime smoking index increases the risk of multimorbidity by 6.8% (95% CI: 3.3 to 10.4%). Evidence for a causal effect of genetically-predicted alcohol consumption on multimorbidity was less strong; an increase of 5 units of alcohol per week increases the risk of multimorbidity by 1.3% (95% CI: 0.2 to 2.5%). The proportions of the association between education and multimorbidity explained by BMI and smoking are 20.4% and 17.6% respectively. Collectively, BMI and smoking account for 31.8% of the educational inequality in multimorbidity. CONCLUSIONS Education, BMI, smoking and alcohol consumption are intervenable causal risk factors for multimorbidity. Furthermore, BMI and lifetime smoking make a considerable contribution to the generation of educational inequalities in multimorbidity. Public health interventions that improve population-wide levels of these risk factors are likely to reduce multimorbidity and inequalities in its occurrence.
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Affiliation(s)
- Teri-Louise North
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK.
| | - Sean Harrison
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
| | - Deborah C Bishop
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
| | - Robyn E Wootton
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Alice R Carter
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
| | - Rupert A Payne
- Centre for Academic Primary Care, Population Health Sciences, University of Bristol, Bristol, UK
- Exeter Collaboration for Academic Primary Care, Department of Health and Community Sciences, University of Exeter, Exeter, UK
| | - Chris Salisbury
- Centre for Academic Primary Care, Population Health Sciences, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, UK
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Feng Q, Grant AJ, Yang Q, Burgess S, Bešević J, Conroy M, Omiyale W, Sun Y, Allen N, Lacey B. Genetically Predicted Vegetable Intake and Cardiovascular Diseases and Risk Factors: An Investigation with Mendelian Randomization. Nutrients 2023; 15:3682. [PMID: 37686714 PMCID: PMC10490460 DOI: 10.3390/nu15173682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Revised: 08/17/2023] [Accepted: 08/19/2023] [Indexed: 09/10/2023] Open
Abstract
BACKGROUND The associations between vegetable intake and cardiovascular diseases have been demonstrated in observational studies, but less sufficiently in randomized trials. Mendelian randomization has been considered a promising alternative in causal inference. The separate effects of cooked and raw vegetable intake remain unclear. This study aimed to investigate the associations between cooked and raw vegetable intake with cardiovascular outcomes using MR. METHODS We identified 15 and 28 genetic variants statistically and biologically associated with cooked and raw vegetable intake, respectively, from previous genome-wide association studies, which were used as instrumental variables to estimate associations with coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF). The independent effects of genetically predicted cooked and raw vegetable intake were examined using multivariable MR analysis. We performed one-sample and two-sample MR analyses and combined their results using meta-analysis. Bonferroni correction was applied for multiple comparisons. We performed two-sample MR analysis for cardiometabolic risk factors (serum lipids, blood pressure, body mass index, and glycemic traits) to explore the potential mechanisms. RESULTS In the MR meta-analysis of 1.2 million participants, we found null evidence for associations between genetically predicted cooked and raw vegetable intake with CHD, HF, or AF. Raw vegetable intake was nominally associated with stroke (odds ratio [95% confidence interval] 0.82 [0.69-0.98] per 1 daily serving increase, p = 0.03), but this association did not pass the corrected significance level. We found consistently null evidence for associations with serum lipids, blood pressure, body mass index, or glycemic traits. CONCLUSIONS We found null evidence for associations between genetically predicted vegetable intake with CHD, AF, HF, or cardiometabolic risk factors in this MR study. Raw vegetable intake may reduce risk of stroke, but this warrants more research. True associations between vegetable intake and CVDs cannot be completely ruled out, and future investigations are required for causal inference in nutritional research.
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Affiliation(s)
- Qi Feng
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Andrew J. Grant
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Qian Yang
- MRC Integrative Epidemiology, University of Bristol, Bristol BS1 3NY, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS1 3NY, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Jelena Bešević
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Megan Conroy
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Wemimo Omiyale
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Yangbo Sun
- Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Naomi Allen
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Ben Lacey
- Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
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Wu W, Zhang R, Jin Y, Lu Y, Lu Z, Li T, Ye L, Lin L, Wei Y. Cancer trends and risk factors in China over the past 30 years (1990-2019). J Cancer 2023; 14:1935-1945. [PMID: 37476192 PMCID: PMC10355210 DOI: 10.7150/jca.83162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 06/18/2023] [Indexed: 07/22/2023] Open
Abstract
Objective: We retrospectively studied cancer mortality and incidence in China from 1990 to 2019, investigated the cancer trends and risk factors, and analyzed the effects of Gross Domestic Product (GDP) on cancer mortality and incidence. Methods: Data was obtained in "Our world in data" in October 2022 to explore mortality rates of different cancers and their trends and the roles of cancer risk factors, including GDP, air pollution, etc. Results: Over the past 30 years, cancer had been China's second leading cause of death. Tracheal, bronchial, and lung cancers, with an annual growth rate of 6.5%, were the most frequently diagnosed cancers. The burden of different cancers changed as the mortality rate of cancer changed. The age-standardized cancer mortality rate had decreased by 19.0%; cancer deaths in all age groups had increased. While the number of cancer deaths in the elderly aged ≥70 did not increase distinctively, its percentage increased by 52.1% and 1.7% annually. The percentage of patients with new-onset cancer increased by 240% and 8.6% annually. For every USD 1,000 increase in GDP, cancer deaths decreased by 2.3/100,000. Tobacco, meat, and alcohol consumption and BMI had increased and were not conducive to the future control of cancer. Conclusions: We summarized the incidence and mortality of major cancers and their trends in China over the past 30 years and analyzed the effects of GDP and the roles of cancer risk factors. Overall GDP growth and effective control of air pollution reduced cancer mortality, while population aging, smoking, alcohol consumption, BMI increasing, and meat consumption brought challenges for cancer control.
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Affiliation(s)
- Weiwei Wu
- Department of Neurology, Union Hospital, Fujian Medical University, Fuzhou, China
| | - Ruochen Zhang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
- Department of Urology, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
| | - Yiming Jin
- Department of Urology, Juntendo University School of Medicine, Tokyo, Japan
| | - Yan Lu
- Department of Urology, Juntendo University School of Medicine, Tokyo, Japan
| | - Zhonglei Lu
- College of Biological Science and Engineering, Fuzhou University, Fuzhou 350108, China
| | - Tao Li
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
- Department of Urology, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
| | - Liefu Ye
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
- Department of Urology, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
| | - Le Lin
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
- Department of Urology, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
| | - Yongbao Wei
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, 350001, China
- Department of Urology, Fujian Provincial Hospital, Fuzhou, 350001, Fujian, China
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20
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Tian H, Mason AM, Liu C, Burgess S. Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification method. PLoS Genet 2023; 19:e1010823. [PMID: 37390109 PMCID: PMC10343089 DOI: 10.1371/journal.pgen.1010823] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 07/13/2023] [Accepted: 06/10/2023] [Indexed: 07/02/2023] Open
Abstract
Non-linear Mendelian randomization is an extension to standard Mendelian randomization to explore the shape of the causal relationship between an exposure and outcome using an instrumental variable. A stratification approach to non-linear Mendelian randomization divides the population into strata and calculates separate instrumental variable estimates in each stratum. However, the standard implementation of stratification, referred to as the residual method, relies on strong parametric assumptions of linearity and homogeneity between the instrument and the exposure to form the strata. If these stratification assumptions are violated, the instrumental variable assumptions may be violated in the strata even if they are satisfied in the population, resulting in misleading estimates. We propose a new stratification method, referred to as the doubly-ranked method, that does not require strict parametric assumptions to create strata with different average levels of the exposure such that the instrumental variable assumptions are satisfied within the strata. Our simulation study indicates that the doubly-ranked method can obtain unbiased stratum-specific estimates and appropriate coverage rates even when the effect of the instrument on the exposure is non-linear or heterogeneous. Moreover, it can also provide unbiased estimates when the exposure is coarsened (that is, rounded, binned into categories, or truncated), a scenario that is common in applied practice and leads to substantial bias in the residual method. We applied the proposed doubly-ranked method to investigate the effect of alcohol intake on systolic blood pressure, and found evidence of a positive effect of alcohol intake, particularly at higher levels of alcohol consumption.
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Affiliation(s)
- Haodong Tian
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Amy M. Mason
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Cunhao Liu
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Stephen Burgess
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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Barry CJ, Carslake D, Wade KH, Sanderson E, Davey Smith G. Comparison of intergenerational instrumental variable analyses of body mass index and mortality in UK Biobank. Int J Epidemiol 2023; 52:545-561. [PMID: 35947758 PMCID: PMC10114047 DOI: 10.1093/ije/dyac159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 07/25/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND An increasing proportion of people have a body mass index (BMI) classified as overweight or obese and published studies disagree whether this will be beneficial or detrimental to health. We applied and evaluated two intergenerational instrumental variable methods to estimate the average causal effect of BMI on mortality in a cohort with many deaths: the parents of UK Biobank participants. METHODS In Cox regression models, parental BMI was instrumented by offspring BMI using an 'offspring as instrument' (OAI) estimation and by offspring BMI-related genetic variants in a 'proxy-genotype Mendelian randomization' (PGMR) estimation. RESULTS Complete-case analyses were performed in parents of 233 361 UK Biobank participants with full phenotypic, genotypic and covariate data. The PGMR method suggested that higher BMI increased mortality with hazard ratios per kg/m2 of 1.02 (95% CI: 1.01, 1.04) for mothers and 1.04 (95% CI: 1.02, 1.05) for fathers. The OAI method gave considerably higher estimates, which varied according to the parent-offspring pairing between 1.08 (95% CI: 1.06, 1.10; mother-son) and 1.23 (95% CI: 1.16, 1.29; father-daughter). CONCLUSION Both methods supported a causal role of higher BMI increasing mortality, although caution is required regarding the immediate causal interpretation of these exact values. Evidence of instrument invalidity from measured covariates was limited for the OAI method and minimal for the PGMR method. The methods are complementary for interrogating the average putative causal effects because the biases are expected to differ between them.
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Affiliation(s)
- Ciarrah-Jane Barry
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
- Department of Mathematical Sciences, University of Bath, Bath, UK
| | - David Carslake
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
| | - Kaitlin H Wade
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
| | - Eleanor Sanderson
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK
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22
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Oginni OA, Lim KX, Purves KL, Lu Y, Johansson A, Jern P, Rijsdijk FV. Causal Influences of Same-Sex Attraction on Psychological Distress and Risky Sexual Behaviors: Evidence for Bidirectional Effects. ARCHIVES OF SEXUAL BEHAVIOR 2023; 52:1213-1228. [PMID: 36331682 PMCID: PMC10102149 DOI: 10.1007/s10508-022-02455-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Revised: 10/11/2022] [Accepted: 10/13/2022] [Indexed: 05/11/2023]
Abstract
Although health disparities among same-sex attracted compared to heterosexual individuals are typically explained by minority stress, there is limited evidence for a causal effect. This study investigated whether same-sex attraction was causally associated with psychological distress and risky sexual behavior using sociosexual behavior as a proxy. The sample comprised monozygotic and dizygotic twins and their non-twin siblings (n = 2036, 3780 and 2356, respectively) genotyped and assessed for same-sex attraction, psychological distress (anxiety and depressive symptoms), and risky sexual behavior. Causal influences were investigated with same-sex attraction as the predictor and psychological distress and risky sexual behavior as the outcomes in two separate Mendelian Randomization-Direction of Causation (MRDoC) models using OpenMx in R. The MRDoC model improves on the Mendelian Randomization and Direction of Causation twin models by allowing analyses of variables with similar genetic architectures, incorporating polygenic scores as instrumental variables and specifying pleiotropy and residual covariance. There were significant causal influences flowing from same-sex attraction to psychological distress and risky sexual behavior (standardized coefficients = 0.13 and 0.16; 95% CIs 0.03-0.23 and 0.08-0.25, respectively). Further analyses also demonstrated causal influences flowing from psychological distress and risky sexual behavior toward same-sex attraction. Causal influences from same-sex attraction to psychological distress and risky sexual behavior may reflect minority stress, which reinforces ongoing measures to minimize social disparities. Causal influences flowing in the opposite direction may reflect rejection sensitivity, stigma-inducing outcomes of risky sexual behavior, and recall bias; however, further research is required to specifically investigate these processes.
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Affiliation(s)
- Olakunle Ayokunmi Oginni
- The Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, London, SE5 8AF, UK.
- Department of Mental Health, Obafemi Awolowo University, Ile-Ife, Nigeria.
| | - Kai Xiang Lim
- The Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, London, SE5 8AF, UK
| | - Kirstin Lee Purves
- The Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, London, SE5 8AF, UK
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Psychiatry Genomic Institute, Karolinska Institutet, Stockholm, Sweden
| | - Ada Johansson
- Department of Psychology, Åbo Akademi University, Åbo, Finland
| | - Patrick Jern
- Department of Psychology, Åbo Akademi University, Åbo, Finland
| | - Frühling Vesta Rijsdijk
- The Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, London, SE5 8AF, UK
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Kundu P, Burgess S, Chatterjee N. Estimating Burden of Mortality due to Excess Body Mass Index in the US Adult Population by Combining Evidence from a Mendelian Randomization Study and National Health Surveys. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.17.23287394. [PMID: 37034661 PMCID: PMC10081402 DOI: 10.1101/2023.03.17.23287394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
Importance Assessment of the burden of mortality due to excess body weight in a population and its subgroups is important for designing health policies for interventions. Mendelian randomization (MR) studies can provide an opportunity to correct for unmeasured confounding bias present in observational studies, but such evidence has not been used to assess population burden of mortality due to excess BMI. Objective Combine results from a recent Mendelian randomization (MR) study and data from the National Health Surveys to estimate preventable fraction (PF) of 10-year all-cause and cause-specific mortality by different degrees of BMI reduction in the US adult population and underlying risk strata. Designs We use cross-sectional data on the distribution of BMI and other risk factors of mortality from the National Health and Nutritional Examination Surveys (NHANES) across two-time spans (1999-2006 and 2017-2018). We use linked data from National Death Index to characterize the observed risk of 10-year mortality associated with BMI and other risk factors based on the NHANES 1999-2006 cohort. We further import results from an external MR study on linear and non-linear effects of BMI and use novel methods to estimate preventable fraction (PF) for deaths under different counterfactual scenarios of BMI reduction in the NHANES population. Settings Primary analysis is restricted to the NHANES non-Hispanic white population (age range 40-69 years) due to the unavailability of MR studies in other groups, but projections are provided for the African American population under the assumption of homogeneity of causal effects. Outcome Preventable fraction for 10-year all-cause mortality and cause-specific mortality due to 50% and 100% reduction of excess BMI (BMI>25.6 kg/m2) for the US adult population in the age range of 40-69 years. Results Nearly 33% and 43% of the NHANES 2017-2018 target population are overweight (25.6 kg/m2≤BMI<30.7 kg/m2) and obese (BMI>30.7 kg/m2), respectively, according to WHO definitions. Estimates of relative risks for different BMI categories (relative to normal BMI) from the external MR study range from 1.05 (25.6 kg/m2 ≤ BMI < 27.8 kg/m2) to 5.95 (BMI> 42.4 kg/m2). We estimate PF for 10-year all-cause mortality due to 50% and 100% reduction of excess BMI for the population to be 24% (95% CI: 14 - 34) and 35% (95% CI: 22-48), respectively. The estimate of PF of death due to heart disease and cancer for this population reaches up to 48% (95% CI: 25-71) and 18% (95% CI: -2-38), respectively. Partitioning of PF shows that 60% of all BMI-attributable deaths arise from only 12% of the population who are at the highest risk due to obesity and a combination of other risk factors. Conclusions Nearly one in three deaths in a contemporary US adult population can be attributed to overweight and obesity. A substantial fraction of these deaths are likely to be preventable through pragmatic and targeted BMI interventions.
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Affiliation(s)
- Prosenjit Kundu
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, US
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Nilanjan Chatterjee
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, US
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, US
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Preoperative Serum Cortisol Level Is Predictive of Weight Loss After Laparoscopic Sleeve Gastrectomy in Men with Severe Obesity but Not Women. Obes Surg 2023; 33:851-859. [PMID: 36626105 PMCID: PMC9988780 DOI: 10.1007/s11695-022-06415-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 11/30/2022] [Accepted: 12/09/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Bariatric surgery is an effective treatment for severe obesity and its associated medical problems. Preoperative factors that predict postoperative weight loss remain to be fully characterized, however. METHODS Anthropometric and laboratory data were collected retrospectively for severely obese patients who underwent laparoscopic sleeve gastrectomy (LSG) between April 2016 and July 2019 at our hospital. Preoperative factors that predicted weight loss at 1 year after LSG were investigated. RESULTS A total of 122 subjects (45 men and 77 women) underwent LSG. The mean ± SD age and body mass index at surgery were 44.4 ± 10.4 years and 40.7 ± 6.7 kg/m2. The percent total weight loss (%TWL) was 27.0 ± 8.6 among all subjects, 26.4 ± 8.0 among men, and 27.4 ± 8.9 among women, with no significant difference between the sexes. The %TWL showed a significant inverse correlation with serum cortisol level in men and with age and the visceral/subcutaneous fat area ratio in women. Multivariable regression analysis revealed the presence of type 2 diabetes and the serum cortisol concentration to be negatively associated with %TWL among all subjects and men, respectively. Receiver operating characteristic curve analysis identified an optimal cutoff of 10 µg/dL for prediction of a %TWL of ≥ 25 in men by serum cortisol level. CONCLUSIONS Serum cortisol concentration was identified as a predictor for postoperative weight loss in men. Our results may thus help inform the decision to perform LSG or more effective surgical procedures in men with severe obesity.
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Hamilton F, Mitchell R, Ahmed H, Ghazal P, Timpson NJ. An observational and Mendelian randomisation study on iron status and sepsis. Sci Rep 2023; 13:2867. [PMID: 36808173 PMCID: PMC9938246 DOI: 10.1038/s41598-023-29641-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 02/08/2023] [Indexed: 02/19/2023] Open
Abstract
Iron deficiency is associated with a substantial burden of morbidity. However, supplementation of iron has been linked to increased rates of serious infection in randomised trials of children in sub-Saharan Africa. Randomised trials in other settings have been inconclusive and it is unknown if changes in levels of iron biomarkers are linked to sepsis in these other settings. We used genetic variants associated with levels of iron biomarkers as instrumental variables in a Mendelian randomisation (MR) analysis to test the hypothesis that increasing levels of iron biomarkers increase the risk of sepsis. In observational and MR analyses we found that increases in iron biomarkers increase the odds of sepsis. In stratified analyses, we show that this risk may be larger in those with iron deficiency and/or anaemia. Taken together, results here suggest a required caution in supplementation of iron and underline the role of iron homeostasis in severe infection.
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Affiliation(s)
- Fergus Hamilton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Infection Sciences, North Bristol NHS Trust, Bristol, UK.
| | - Ruth Mitchell
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Haroon Ahmed
- Division of Population Medicine, Cardiff University Medical School, Cardiff, UK
| | - Peter Ghazal
- System Immunity Research Institute, Division of Infection and Immunity, Cardiff University, Cardiff, UK
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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Zhou A, Hyppönen E. Vitamin D deficiency and C-reactive protein: a bidirectional Mendelian randomization study. Int J Epidemiol 2023; 52:260-271. [PMID: 35579027 PMCID: PMC9908047 DOI: 10.1093/ije/dyac087] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 04/08/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Low vitamin D status is often associated with systemic low-grade inflammation as reflected by elevated C-reactive protein (CRP) levels. We investigated the causality and direction of the association between vitamin D status and CRP using linear and non-linear Mendelian randomization (MR) analyses. METHODS MR analyses were conducted using data from 294 970 unrelated participants of White-British ancestry from the UK Biobank. Serum 25-hydroxyvitamin D [25(OH)D] and CRP concentrations were instrumented using 35 and 46 genome-wide significant variants, respectively. RESULTS In non-linear MR analysis, genetically predicted serum 25(OH)D had an L-shaped association with serum CRP, where CRP levels decreased sharply with increasing 25(OH)D concentration for participants within the deficiency range (<25 nmol/L) and levelled off at ∼50 nmol/L of 25(OH)D (Pnon-linear = 1.49E-4). Analyses using several pleiotropy-robust methods provided consistent results in stratified MR analyses, confirming the inverse association between 25(OH)D and CRP in the deficiency range (P = 1.10E-05) but not with higher concentrations. Neither linear or non-linear MR analysis supported a causal effect of serum CRP level on 25(OH)D concentration (Plinear = 0.32 and Pnon-linear = 0.76). CONCLUSION The observed association between 25(OH)D and CRP is likely to be caused by vitamin D deficiency. Correction of low vitamin D status may reduce chronic inflammation.
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Affiliation(s)
- Ang Zhou
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Elina Hyppönen
- Corresponding author. Australian Center for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, SA 5001, Australia. E-mail:
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27
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Ala-Korpela M. The epidemiological quest for the role of vitamin D turned non-linear-and simply made sense. Int J Epidemiol 2023; 52:1-4. [PMID: 36416418 DOI: 10.1093/ije/dyac218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 11/03/2022] [Indexed: 11/24/2022] Open
Affiliation(s)
- Mika Ala-Korpela
- Systems Epidemiology, Research Unit of Population Health, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland and NMR Metabolomics Laboratory, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
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Mutie PM, Pomares-Milan H, Atabaki-Pasdar N, Coral D, Fitipaldi H, Tsereteli N, Tajes JF, Franks PW, Giordano GN. Investigating the causal relationships between excess adiposity and cardiometabolic health in men and women. Diabetologia 2023; 66:321-335. [PMID: 36221008 PMCID: PMC9807546 DOI: 10.1007/s00125-022-05811-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 08/23/2022] [Indexed: 01/07/2023]
Abstract
AIMS/HYPOTHESIS Excess adiposity is differentially associated with increased risk of cardiometabolic disease in men and women, according to observational studies. Causal inference studies largely assume a linear relationship between BMI and cardiometabolic outcomes, which may not be the case. In this study, we investigated the shapes of the causal relationships between BMI and cardiometabolic diseases and risk factors. We further investigated sex differences within the causal framework. METHODS To assess causal relationships between BMI and the outcomes, we used two-stage least-squares Mendelian randomisation (MR), with a polygenic risk score for BMI as the instrumental variable. To elucidate the shapes of the causal relationships, we used a non-linear MR fractional polynomial method, and used piecewise MR to investigate threshold relationships and confirm the shapes. RESULTS BMI was associated with type 2 diabetes (OR 3.10; 95% CI 2.73, 3.53), hypertension (OR 1.53; 95% CI 1.44, 1.62) and coronary artery disease (OR 1.20; 95% CI 1.08, 1.33), but not chronic kidney disease (OR 1.08; 95% CI 0.67, 1.72) or stroke (OR 1.08; 95% CI 0.92, 1.28). The data suggest that these relationships are non-linear. For cardiometabolic risk factors, BMI was positively associated with glucose, HbA1c, triacylglycerol levels and both systolic and diastolic BP. BMI had an inverse causal relationship with total cholesterol, LDL-cholesterol and HDL-cholesterol. The data suggest a non-linear causal relationship between BMI and BP and other biomarkers (p<0.001) except lipoprotein A. The piecewise MR results were consistent with the fractional polynomial results. The causal effect of BMI on coronary artery disease, total cholesterol and LDL-cholesterol was different in men and women, but this sex difference was only significant for LDL-cholesterol after controlling for multiple testing (p<0.001). Further, the causal effect of BMI on coronary artery disease varied by menopause status in women. CONCLUSIONS/INTERPRETATION We describe the shapes of causal effects of BMI on cardiometabolic diseases and risk factors, and report sex differences in the causal effects of BMI on LDL-cholesterol. We found evidence of non-linearity in the causal effect of BMI on diseases and risk factor biomarkers. Reducing excess adiposity is highly beneficial for health, but there is greater need to consider biological sex in the management of adiposity.
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Affiliation(s)
- Pascal M Mutie
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Hugo Pomares-Milan
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Naeimeh Atabaki-Pasdar
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Daniel Coral
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Hugo Fitipaldi
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Neli Tsereteli
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Juan Fernandez Tajes
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
| | - Paul W Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden.
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Giuseppe N Giordano
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre, Lund University, Lund, Sweden
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29
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Schooling CM, Zhao JV. Insights into Causal Cardiovascular Risk Factors from Mendelian Randomization. Curr Cardiol Rep 2023; 25:67-76. [PMID: 36640254 DOI: 10.1007/s11886-022-01829-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/07/2022] [Indexed: 01/15/2023]
Abstract
PURPOSE OF THE REVIEW This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses. RECENT FINDINGS MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.
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Affiliation(s)
- C M Schooling
- School of Public Health and Health Policy, City University of New York, 55 West 125th St, NY, 10027, New York, USA. .,School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
| | - J V Zhao
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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30
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Baseline and longitudinal trajectories of body-mass index and all-cause mortality among patients with type 2 diabetes. DIABETES & METABOLISM 2023; 49:101426. [PMID: 36669681 DOI: 10.1016/j.diabet.2023.101426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 01/03/2023] [Accepted: 01/05/2023] [Indexed: 01/18/2023]
Abstract
AIM To investigate the associations of baseline body mass index (BMI) and longitudinal BMI trajectories with all-cause mortality among patients with type 2 diabetes mellitus (T2DM). METHODS, We used data from the diabetes surveillance system of Yinzhou Health Information System with T2DM patients registered from 2010 to 2015. Participants aged ≥ 40 years were included and were followed up until September 30, 2021. The latent class growth mixture model was used to identify different changing patterns in BMI for 5 years from registration. Cox proportional hazards models were used to examine the associations of baseline BMI and 5-year BMI trajectories with all-cause mortality. RESULTS We observed a nonlinear association between baseline BMI and all-cause mortality (P for nonlinearity < 0.001), with an increased risk of death for low but not high BMI. However, compared with participants with medium-stable BMI for 5 years from baseline, individuals with increasing BMI had higher mortality, with adjusted hazard ratios (95% confidence intervals) 1.21 (1.02;1.43) for early-increasing and 1.47 (1.19;1.80) for late-sharp increasing groups. CONCLUSION These findings suggest that while obesity itself may not be associated with an increased risk for mortality, weight gain, and in particular rapid weight gain, is a risk factor for mortality among patients with T2DM.
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31
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Lopez-Jimenez F, Almahmeed W, Bays H, Cuevas A, Di Angelantonio E, le Roux CW, Sattar N, Sun MC, Wittert G, Pinto FJ, Wilding JPH. Obesity and cardiovascular disease: mechanistic insights and management strategies. A joint position paper by the World Heart Federation and World Obesity Federation. Eur J Prev Cardiol 2022; 29:2218-2237. [PMID: 36007112 DOI: 10.1093/eurjpc/zwac187] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 08/19/2022] [Accepted: 08/23/2022] [Indexed: 01/11/2023]
Abstract
The ongoing obesity epidemic represents a global public health crisis that contributes to poor health outcomes, reduced quality of life, and >2.8 million deaths each year. Obesity is relapsing, progressive, and heterogeneous. It is considered a chronic disease by the World Obesity Federation (WOF) and a chronic condition by the World Heart Federation (WHF). People living with overweight/obesity are at greater risk for cardiovascular (CV) morbidity and mortality. Increased adiposity (body fat), particularly visceral/abdominal fat, is linked to CV risk and CV disease (CVD) via multiple direct and indirect pathophysiological mechanisms. The development of CVD is driven, in part, by obesity-related metabolic, endocrinologic, immunologic, structural, humoral, haemodynamic, and functional alterations. The complex multifaceted nature of these mechanisms can be challenging to understand and address in clinical practice. People living with obesity and CVD often have concurrent chronic physical or psychological disorders (multimorbidity) requiring multidisciplinary care pathways and polypharmacy. Evidence indicates that intentional weight loss (particularly when substantial) lowers CVD risk among people with overweight/obesity. Long-term weight loss and maintenance require ongoing commitment from both the individual and those responsible for their care. This position paper, developed by the WOF and the WHF, aims to improve understanding of the direct and indirect links between overweight/obesity and CVD, the key controversies in this area and evidence relating to cardiometabolic outcomes with available weight management options. Finally, an action plan for clinicians provides recommendations to help in identifying and addressing the risks of obesity-related CVD (recognizing resource and support variances between countries).
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Affiliation(s)
| | - Wael Almahmeed
- Department of Cardiology, Heart and Vascular Institute, Cleveland Clinic Abu Dhabi, United Arab Emirates
| | - Harold Bays
- Louisville Metabolic and Atherosclerosis Research Center, Louisville, KY, USA
| | - Ada Cuevas
- Center for Advanced Metabolic Medicine and Nutrition (CAMMYN), School of Medicine University Finis Terrae, Santiago, Chile
| | - Emanuele Di Angelantonio
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Health Data Science Centre, Human Technopole, Milan, Italy
| | - Carel W le Roux
- Diabetes Complications Research Centre, University College Dublin, Dublin, Ireland
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Marie Chan Sun
- Department of Medicine, Faculty of Medicine and Health Sciences, University of Mauritius, Mauritius
| | - Gary Wittert
- Freemasons Centre for Male Health and Wellbeing, School of Medicine, University of Adelaide, Adelaide, Australia
| | - Fausto J Pinto
- Cardiology Department, Centro Hospitalar Universitário Lisboa Norte, CAML, CCUL, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Office of the President, World Heart Federation, Geneva, Switzerland
| | - John P H Wilding
- Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, Clinical Sciences Centre, Aintree University Hospital, Liverpool, UK
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Iwagami M, Goto A, Katagiri R, Sutoh Y, Koyanagi YN, Nakatochi M, Nakano S, Hanyuda A, Narita A, Shimizu A, Tanno K, Hozawa A, Kinoshita K, Oze I, Ito H, Yamaji T, Sawada N, Nakamura Y, Nakamura S, Kuriki K, Suzuki S, Hishida A, Kasugai Y, Imoto I, Suzuki M, Momozawa Y, Takeuchi K, Yamamoto M, Sasaki M, Matsuo K, Tsugane S, Wakai K, Iwasaki M. Blood Lipids and the Risk of Colorectal Cancer: Mendelian Randomization Analyses in the Japanese Consortium of Genetic Epidemiology Studies. Cancer Prev Res (Phila) 2022; 15:827-836. [PMID: 36040498 DOI: 10.1158/1940-6207.capr-22-0146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 07/07/2022] [Accepted: 08/25/2022] [Indexed: 01/31/2023]
Abstract
The associations between blood lipids, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), triglycerides, and low-density lipoprotein cholesterol (LDL-C), and colorectal cancer risk are controversial. We evaluated potential causal relationships between blood lipids and colorectal cancer risk. Using the baseline data from the Japanese Consortium of Genetic Epidemiology studies, we estimated the single-nucleotide polymorphism (SNP)-exposure associations (n = 34,546 for TC, n = 50,290 for HDL-C, n = 51,307 for triglycerides, and n = 30,305 for LDL-C). We also estimated the SNP-outcome associations in another Japanese dataset (n = 7,936 colorectal cancer cases and n = 38,042 controls). We conducted Mendelian randomization (MR) analyses for the association between each blood lipid type and the risk of colorectal cancer using an inverse variance-weighted method. The total variances explained by the selected SNPs in TC (68 SNPs), HDL-C (50 SNPs), log-transformed triglycerides (26 SNPs), and LDL-C (35 SNPs) were 7.0%, 10.0%, 6.2%, and 5.7%, respectively. The odds ratios for colorectal cancer were 1.15 [95% confidence interval (CI), 1.01-1.32] per 1 standard deviation (SD; 33.3 mg/dL) increase in TC, 1.11 (95% CI, 0.98-1.26) per 1 SD (15.4 mg/dL) increase in HDL-C, 1.06 (95% CI, 0.90-1.26) per 1 SD (0.5 log-mg/dL) increase in log-transformed triglycerides, and 1.17 (95% CI, 0.91-1.50) per 1 SD (29.6 mg/dL) increase in LDL-C. Sensitivity analyses consistently suggested the positive association between TC and colorectal cancer, whereas results of each lipid component were inconsistent. In conclusion, this large MR study of a Japanese population showed a potentially causal association between high TC and colorectal cancer risk, although the association between each lipid component and colorectal cancer remained inconclusive. PREVENTION RELEVANCE In this large MR analysis of a Japanese population, a positive association was found between genetically predicted high total cholesterol (TC) levels and an increased risk of colorectal cancer. Therefore, lowering TC levels by lifestyle modifications or medications may be justified for the purpose of preventing colorectal cancer.
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Affiliation(s)
- Masao Iwagami
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan.,Department of Health Services Research, Faculty of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Atsushi Goto
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan.,Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Kanagawa, Japan
| | - Ryoko Katagiri
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank, Iwate, Japan
| | - Yuriko N Koyanagi
- Division of Cancer Information and Control, Aichi Cancer Center, Aichi, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Shiori Nakano
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Akiko Hanyuda
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan.,Department of Ophthalmology, Keio University School of Medicine, Tokyo, Japan
| | - Akira Narita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank, Iwate, Japan
| | - Kozo Tanno
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Isao Oze
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center, Aichi, Japan
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center, Aichi, Japan.,Division of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Yohko Nakamura
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
| | - Sho Nakamura
- Graduate School of Health Innovation, Kanagawa University of Human Services, Kanagawa, Japan.,Cancer Prevention and Control Division, Kanagawa Cancer Center Research Institute, Kanagawa, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Aichi, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Yumiko Kasugai
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center, Aichi, Japan
| | - Issei Imoto
- Aichi Cancer Center Research Institute, Aichi, Japan
| | - Midori Suzuki
- Core Facilities, Aichi Cancer Center Research Institute, Aichi, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Kenji Takeuchi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Miyagi, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center, Aichi, Japan.,Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan.,National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan.,Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
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Popiolek-Kalisz J. The Impact of Dietary Flavonols on Central Obesity Parameters in Polish Adults. Nutrients 2022; 14:nu14235051. [PMID: 36501081 PMCID: PMC9739955 DOI: 10.3390/nu14235051] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 11/22/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022] Open
Abstract
Background: Central obesity is defined as the excessive fat tissue located in abdominal region accompanied by systemic inflammation, which drives to cardiovascular disease. Flavonols are antioxidative agents present in food. The aim of this study was investigating the relationship between dietary flavonols intake and central obesity. Methods and results: 80 participants (40 central obese and 40 healthy controls) were administered a food frequency questionnaire dedicated to flavonols intake assessment. Body composition was measured with bioelectrical impedance analysis. The analysis showed significant differences between central obese participants and healthy controls in total flavonol (p = 0.005), quercetin (p = 0.003), kaempferol (p = 0.04) and isorhamnetin (p < 0.001) habitual intake. Among central obese participants, there was a moderate inverse correlation between fat mass (FM) and total flavonol (R = −0.378; 95% CI: −0.620 to −0.071; p = 0.02), quercetin (R = −0.352; 95% CI: −0.601 to −0.041; p = 0.03), kaempferol (R = −0.425; 95% CI: −0.653 to −0.127; p = 0.01) and myricetin intake (R = −0.352; 95% CI: −0.601 to −0.041; p = 0.03). BMI was inversely correlated with total flavonol (R = −0.330; 95% CI: −0.584 to −0.016; p = 0.04) and quercetin intake (R = −0.336; 95% CI: −0.589 to −0.023; p = 0.04). Waist circumference was inversely correlated with total flavonol (R = −0.328; 95% CI: −0.586 to −0.009; p = 0.04), quercetin (R = −0.322; 95% CI: −0.582 to −0.002; p = 0.048) and myricetin intake (R = −0.367; 95% CI: −0.615 to −0.054; p = 0.02). Among flavonols’ dietary sources, there was an inverse correlation between black tea consumption and FM (R: −0.511; 95% CI: −0.712 to −0.233; p < 0.001) and between coffee and waist circumference (R: −0.352; 95% CI: −0.604 to −0.036; p = 0.03) in central obese participants. Conclusions: The higher flavonol intake could play a protective role in abdominal obesity development. What is more, total and selected flavonol dietary intakes are inversely correlated with the parameters used for obesity assessment in central obese participants. The habitual consumption of products rich in flavonols, mainly tea and coffee, could possibly have a preventive role in abdominal obesity development.
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Affiliation(s)
- Joanna Popiolek-Kalisz
- Clinical Dietetics Unit, Department of Bioanalytics, Medical University of Lublin, ul. Chodzki 7, 20-093 Lublin, Poland;
- Department of Cardiology, Cardinal Wyszynski Hospital in Lublin, al. Krasnicka 100, 20-718 Lublin, Poland
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Li R, Cai M, Qian ZM, Wang X, Zhang Z, Wang C, Wang Y, Arnold LD, Howard SW, Li H, Lin H. Ambient air pollution, lifestyle, and genetic predisposition associated with type 2 diabetes: findings from a national prospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 849:157838. [PMID: 35934032 DOI: 10.1016/j.scitotenv.2022.157838] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/26/2022] [Accepted: 08/01/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The combined effects of ambient air pollution, lifestyle, and genetic predisposition on incident Type 2 Diabetes (T2D) have not been well documented. METHODS A total of 263,733 participants without T2D at baseline were identified from the UK Biobank. Annual concentrations of five air pollutants were estimated using Land Use Regression, while a healthy lifestyle score (HLS) was constructed using 7 major lifestyle factors, and polygenic risk score (PRS) was generated using 73 genetic variants. Cox regression was used to determine the association between air pollution and incident T2D for different HLS/PRS categories. Potential HLS/PRS interactions and population attributable fraction (PAF) were also examined. RESULTS During a median follow-up of 11.94 years, 7827 (2.97 %) incident T2D cases were identified. Association between air pollution and incident T2D was stronger among those with higher HLS/PRS in a dose-response fashion. In addition, synergistic interactions between lifestyles and air pollution were observed. Lifestyle was the leading risk factor of T2D with a weighted PAF of 25.54 % (95 % CI: 19.22 %, 27.77 %) for intermediate HLS and 24.24 % (18.24 %, 26.36 %) due to unhealthy HLS. Overall, we estimated that about 25 % of T2D cases could be attributable to air pollution and associated interactions. CONCLUSIONS Associations between air pollution and T2D were stronger among individuals with unhealthier lifestyle on an additive interaction scale. Public health interventions that address both reduction of exposure to high levels of air pollution in addition to lifestyle changes may have more benefit on reducing T2D risk than focusing on lifestyle changes alone.
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Affiliation(s)
- Rui Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Miao Cai
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States.
| | - Xiaojie Wang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
| | - Yuqin Wang
- Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou 510180, China.
| | - Lauren D Arnold
- Department of Epidemiology and Biostatistics, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States.
| | - Steven W Howard
- Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, United States.
| | - Haitao Li
- Department of Social Medicine and Health Service Management, Health Science Center, Shenzhen University, Shenzhen, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
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Gaziano L, Sun L, Arnold M, Bell S, Cho K, Kaptoge SK, Song RJ, Burgess S, Posner DC, Mosconi K, Robinson-Cohen C, Mason AM, Bolton TR, Tao R, Allara E, Schubert P, Chen L, Staley JR, Staplin N, Altay S, Amiano P, Arndt V, Ärnlöv J, Barr EL, Björkelund C, Boer JM, Brenner H, Casiglia E, Chiodini P, Cooper JA, Coresh J, Cushman M, Dankner R, Davidson KW, de Jongh RT, Donfrancesco C, Engström G, Freisling H, de la Cámara AG, Gudnason V, Hankey GJ, Hansson PO, Heath AK, Hoorn EJ, Imano H, Jassal SK, Kaaks R, Katzke V, Kauhanen J, Kiechl S, Koenig W, Kronmal RA, Kyrø C, Lawlor DA, Ljungberg B, MacDonald C, Masala G, Meisinger C, Melander O, Moreno Iribas C, Ninomiya T, Nitsch D, Nordestgaard BG, Onland-Moret C, Palmieri L, Petrova D, Garcia JRQ, Rosengren A, Sacerdote C, Sakurai M, Santiuste C, Schulze MB, Sieri S, Sundström J, Tikhonoff V, Tjønneland A, Tong T, Tumino R, Tzoulaki I, van der Schouw YT, Monique Verschuren W, Völzke H, Wallace RB, Wannamethee SG, Weiderpass E, Willeit P, Woodward M, Yamagishi K, Zamora-Ros R, Akwo EA, Pyarajan S, Gagnon DR, Tsao PS, Muralidhar S, Edwards TL, Damrauer SM, Joseph J, Pennells L, Wilson PW, Harrison S, Gaziano TA, Inouye M, Baigent C, Casas JP, Langenberg C, Wareham N, Riboli E, Gaziano J, Danesh J, Hung AM, Butterworth AS, Wood AM, Di Angelantonio E. Mild-to-Moderate Kidney Dysfunction and Cardiovascular Disease: Observational and Mendelian Randomization Analyses. Circulation 2022; 146:1507-1517. [PMID: 36314129 PMCID: PMC9662821 DOI: 10.1161/circulationaha.122.060700] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 08/18/2022] [Indexed: 01/28/2023]
Abstract
BACKGROUND End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. METHODS Observational analyses were conducted using individual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition-Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. RESULTS There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values <60 or >105 mL·min-1·1.73 m-2, compared with those with eGFR between 60 and 105 mL·min-1·1.73 m-2. Mendelian randomization analyses for CHD showed an association among participants with eGFR <60 mL·min-1·1.73 m-2, with a 14% (95% CI, 3%-27%) higher CHD risk per 5 mL·min-1·1.73 m-2 lower genetically predicted eGFR, but not for those with eGFR >105 mL·min-1·1.73 m-2. Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. CONCLUSIONS In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.
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Affiliation(s)
- Liam Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Luanluan Sun
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | | | - Steven Bell
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Stroke Research Group, Department of Clinical Neurosciences (S. Bell), University of Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
| | - Kelly Cho
- Division of Aging (K.C., S.P., J.P.C. J.M.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Stephen K. Kaptoge
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Rebecca J. Song
- Department of Epidemiology, Boston University School of Public Health, MA (R.J.S.)
| | - Stephen Burgess
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Medical Research Council Biostatistics Unit (A.M.M., S. Burgess), University of Cambridge, UK
| | - Daniel C. Posner
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
| | - Katja Mosconi
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Cassianne Robinson-Cohen
- Division of Nephrology, Department of Medicine (C.R.-C., E.A.A.), Vanderbilt University Medical Center, Nashville, TN
| | - Amy M. Mason
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Medical Research Council Biostatistics Unit (A.M.M., S. Burgess), University of Cambridge, UK
| | - Thomas R. Bolton
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
| | - Ran Tao
- Department of Biostatistics (R. Tao), Vanderbilt University Medical Center, Nashville, TN
| | - Elias Allara
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
| | - Petra Schubert
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
| | - Lingyan Chen
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - James R. Staley
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Natalie Staplin
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit (N.S., C.B.), Nuffield Department of Population Health, University of Oxford, UK
| | - Servet Altay
- Department of Cardiology, Trakya University School of Medicine, Edirne, Turkey (S.A.)
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain (P.A.)
- Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain (P.A.)
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain (P.A., A.G.d.l.C., D.P., C. Santiuste)
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research (V.A.), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Johan Ärnlöv
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Medical Research Council Biostatistics Unit (A.M.M., S. Burgess), University of Cambridge, UK
- Stroke Research Group, Department of Clinical Neurosciences (S. Bell), University of Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
- MRC Epidemiology Unit, School of Clinical Medicine (C.L., N.W.), University of Cambridge, UK
- Division of Aging (K.C., S.P., J.P.C. J.M.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Division of Cardiovascular Medicine (J.J., T.A.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Department of Epidemiology, Boston University School of Public Health, MA (R.J.S.)
- Division of Nephrology, Department of Medicine (C.R.-C., E.A.A.), Vanderbilt University Medical Center, Nashville, TN
- Department of Biostatistics (R. Tao), Vanderbilt University Medical Center, Nashville, TN
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit (N.S., C.B.), Nuffield Department of Population Health, University of Oxford, UK
- Cancer Epidemiology Unit (T.T.), Nuffield Department of Population Health, University of Oxford, UK
- Department of Cardiology, Trakya University School of Medicine, Edirne, Turkey (S.A.)
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain (P.A.)
- Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain (P.A.)
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain (P.A., A.G.d.l.C., D.P., C. Santiuste)
- Division of Clinical Epidemiology and Aging Research (V.A.), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Cancer Epidemiology (S.K.J., R.K., V.K.), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden (J.A., H.B.)
- School of Health and Social Studies, Dalarna University, Falun, Sweden (J.A.)
- Wellbeing & Preventable Chronic Diseases (WPCD) Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia (E.L.M.B.)
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (E.L.M.B., M.I.)
- Institute of Medicine, School of Public Health and Community Medicine (C.B.), Sahlgrenska Academy, University of Gothenburg, Sweden
- Institute of Medicine, Department of Molecular and Clinical Medicine (P.-O.H., A.R.), Sahlgrenska Academy, University of Gothenburg, Sweden
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands (J.M.A.B., W.M.M.V.)
- Network Aging Research (NAR), Heidelberg University, Germany (H.B.)
- Studium Patavinum (E.C.), University of Padua, Italy
- Department of Medicine (V.T.), University of Padua, Italy
- Dipartimento di Salute Mentale e Fisica e Medicina Preventiva, Università degli Studi della Campania ‘Luigi Vanvitelli’, Caserta, Italy (P.C.)
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, UK (J.A.C.)
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (J.C.)
- Larner College of Medicine, The University of Vermont, Burlington (M.C.)
- The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Israel (R.D.)
- School of Public Health, Department of Epidemiology and Preventive Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel (R.D.)
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, NY (R.D., K.W.D.)
- Amsterdam University Medical Centers, VUMC, the Netherlands (R.T.d.J.)
- Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy (C.D., L. Palmer)
- Department of Clinical Sciences, Malmö, Lund University, Sweden (G.E., O.M.)
- International Agency for Research on Cancer (IARC), World Health Organization, Lyon, France (H.F., E.W.)
- 12 Octubre Hospital Research Institute, Madrid, Spain (A.G.d,l,C.)
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland and Icelandic Heart Association, Kopavogur, Iceland (V.G.)
- Medical School Faculty of Health & Medical Sciences, The University of Western Australia, Perth, WA, Australia (G.J.H.)
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Medicine Geriatrics and Emergency Medicine/Östra, Gothenburg, Sweden (P.-O.H., A.R.)
- School of Public Health (A.K.H., I.T., E.R.), Imperial College London, UK
- The George Institute for Global Health (M.W.), Imperial College London, UK
- Department of Internal Medicine, Division of Nephrology and Transplantation, Erasmus MC, University Medical Center Rotterdam, the Netherlands (E.J.H.)
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita, Japan (H.I.)
- University of Eastern Finland (UEF), Kuopio, Finland (J.K.)
- Department of Neurology & Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria (S.K.)
- Clinical Epidemiology Team, Institute of Health Economics, Medical University of Innsbruck, Innsbruck, Austria (S.K., P.W.)
- Institute of Epidemiology and Medical Biometry, University of Ulm, Germany (W.K.)
- Deutsches Herzzentrum München, Technische Universität München, Germany (W.K.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance (W.K.)
- School of Public Health, University of Washington, Seattle (R.A.K.)
- Danish Cancer Society Research Center, Copenhagen, Denmark (C.K., A.T.)
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, UK (D.A.L.)
- Population Health Science, Bristol Medical School, UK (D.A.L.)
- Department of Surgical and Perioperative sciences, Urology and Andrology, Umeå University, Sweden (B.L.)
- University Paris-Saclay, UVSQ, Inserm, Villejuif, France (C. MacDonald)
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy (G.M.)
- Helmholtz Zentrum München, Munich, Germany (C. Meisinger)
- Navarra Public Health Institute, IdiSNA, Pamplona, Spain (C.M.I.)
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Pamplona, Spain (C.M.I.)
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan (T.N.)
- London School of Hygiene & Tropical Medicine, UK (D.N.)
- Herlev and Gentofte Hospital (B.G.N.), Copenhagen University Hospital, Copenhagen, Denmark
- Frederiksberg Hospital B.G.N.), Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences (B.G.N.), University of Copenhagen, Denmark
- Department of Public Health (A.T.), University of Copenhagen, Denmark
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands (C.O.-M., Y.T.v.d.S., W.M.M.V.)
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain (D.P.)
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain (D.P.)
- Consejería de Sanidad del Principado de Asturias Oviedo, Asturias, Spain (J.R.Q.G.)
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital, Turin, Italy (C. Sacerdote)
- Department of Social and Environmental Medicine, Kanazawa Medical University, Uchinada, Japan (M.S.)
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Spain (C. Santiuste)
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany (M.B.S.)
- German Center for Diabetes Research (DZD), Neuherberg, Germany (M.B.S.)
- Institute of Nutritional Science, University of Potsdam, Germany (M.B.S.)
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy (S.S.)
- Department of Medical Sciences, Uppsala University, Sweden (J.S.)
- Hyblean Association for Epidemiological Reserach AIRE - ONLUS, Ragusa, Italy (R.T.)
- Universitätsmedizin Greifswald, Institut für Community Medicine, Abteilung SHIP/ Klinisch-Epidemiologische Forschung, Germany (H.V.)
- College of Public Health, University of Iowa (R.B.W.)
- University College London, UK (S.G.W.)
- The George Institute for Global Health, Camperdown, NSW, Australia (M.W.)
- Department of Public Health Medicine, Faculty of Medicine, and Health Services Research and Development Center, University of Tsukuba, Japan (K.Y.)
- Unit of Nutrition and Cancer, Epidemiology Research Program, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat (Barcelona), Spain (R.Z.-R.)
- Center for Data and Computational Sciences, VA Boston Healthcare System, Boston, MA (S.P.)
- Department of Biostatistics, Boston University School of Public Health, MA (D.R.G.)
- VA Pal Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, CA (P.S.T.)
- Medicine (Cardiovascular Medicine), Stanford University of School of Medicine, CA (P.S.T.)
- Office of Research and Development, Veterans Health Administration, Washington, DC (S.M.)
- Department of Veterans Affairs, Tennessee Valley Health Care System, Vanderbilt University, Nashville (T.L.E.)
- Medicine/Epidemiology, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN (T.L.E.)
- Department of Surgery, Corporal Michael Crescenz VA Medical Center and Perelman School of Medicine, University of Pennsylvania, Philadelphia (S.M.D.)
- Internal Medicine, VA Atlanta Healthcare System, Decatur, GA (P.W.F.W.)
- Emory University School of Medicine (Cardiology), Emory University, Atlanta, GA (P.W.F.W.)
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA (T.A.G.)
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
- The Alan Turing Institute, London, UK (M.I.)
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Germany (C.L.)
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK (J.D.)
- Division of Nephrology & Hypertension, Department of Medicine, Tennessee Valley Health Care System and Vanderbilt University Medical Center, Nashville (A.M.H.)
- Cambridge Centre for AI in Medicine, UK (A.M.W.)
- Health Data Science Centre, Human Technopole, Milan, Italy (E.D.A.)
| | - Elizabeth L.M. Barr
- Wellbeing & Preventable Chronic Diseases (WPCD) Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia (E.L.M.B.)
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (E.L.M.B., M.I.)
| | - Cecilia Björkelund
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit (N.S., C.B.), Nuffield Department of Population Health, University of Oxford, UK
| | - Jolanda M.A. Boer
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands (J.M.A.B., W.M.M.V.)
| | - Hermann Brenner
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden (J.A., H.B.)
- Network Aging Research (NAR), Heidelberg University, Germany (H.B.)
| | | | - Paolo Chiodini
- Dipartimento di Salute Mentale e Fisica e Medicina Preventiva, Università degli Studi della Campania ‘Luigi Vanvitelli’, Caserta, Italy (P.C.)
| | - Jackie A. Cooper
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, UK (J.A.C.)
| | - Josef Coresh
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (J.C.)
| | - Mary Cushman
- Larner College of Medicine, The University of Vermont, Burlington (M.C.)
| | - Rachel Dankner
- The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Israel (R.D.)
- School of Public Health, Department of Epidemiology and Preventive Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel (R.D.)
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, NY (R.D., K.W.D.)
| | - Karina W. Davidson
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, NY (R.D., K.W.D.)
| | | | - Chiara Donfrancesco
- Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy (C.D., L. Palmer)
| | - Gunnar Engström
- Department of Clinical Sciences, Malmö, Lund University, Sweden (G.E., O.M.)
| | - Heinz Freisling
- International Agency for Research on Cancer (IARC), World Health Organization, Lyon, France (H.F., E.W.)
| | - Agustín Gómez de la Cámara
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain (P.A., A.G.d.l.C., D.P., C. Santiuste)
- 12 Octubre Hospital Research Institute, Madrid, Spain (A.G.d,l,C.)
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland and Icelandic Heart Association, Kopavogur, Iceland (V.G.)
| | - Graeme J. Hankey
- Medical School Faculty of Health & Medical Sciences, The University of Western Australia, Perth, WA, Australia (G.J.H.)
| | - Per-Olof Hansson
- Institute of Medicine, Department of Molecular and Clinical Medicine (P.-O.H., A.R.), Sahlgrenska Academy, University of Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Medicine Geriatrics and Emergency Medicine/Östra, Gothenburg, Sweden (P.-O.H., A.R.)
| | - Alicia K. Heath
- School of Public Health (A.K.H., I.T., E.R.), Imperial College London, UK
| | - Ewout J. Hoorn
- Department of Internal Medicine, Division of Nephrology and Transplantation, Erasmus MC, University Medical Center Rotterdam, the Netherlands (E.J.H.)
| | - Hironori Imano
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita, Japan (H.I.)
| | - Simerjot K. Jassal
- Department of Cancer Epidemiology (S.K.J., R.K., V.K.), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Department of Cancer Epidemiology (S.K.J., R.K., V.K.), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology (S.K.J., R.K., V.K.), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jussi Kauhanen
- University of Eastern Finland (UEF), Kuopio, Finland (J.K.)
| | - Stefan Kiechl
- Department of Neurology & Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria (S.K.)
- Clinical Epidemiology Team, Institute of Health Economics, Medical University of Innsbruck, Innsbruck, Austria (S.K., P.W.)
| | - Wolfgang Koenig
- Institute of Epidemiology and Medical Biometry, University of Ulm, Germany (W.K.)
- Deutsches Herzzentrum München, Technische Universität München, Germany (W.K.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance (W.K.)
| | | | - Cecilie Kyrø
- Danish Cancer Society Research Center, Copenhagen, Denmark (C.K., A.T.)
| | - Deborah A. Lawlor
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, UK (D.A.L.)
- Population Health Science, Bristol Medical School, UK (D.A.L.)
| | - Börje Ljungberg
- Department of Surgical and Perioperative sciences, Urology and Andrology, Umeå University, Sweden (B.L.)
| | - Conor MacDonald
- University Paris-Saclay, UVSQ, Inserm, Villejuif, France (C. MacDonald)
| | - Giovanna Masala
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy (G.M.)
| | | | - Olle Melander
- Department of Clinical Sciences, Malmö, Lund University, Sweden (G.E., O.M.)
| | - Conchi Moreno Iribas
- Navarra Public Health Institute, IdiSNA, Pamplona, Spain (C.M.I.)
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Pamplona, Spain (C.M.I.)
| | - Toshiharu Ninomiya
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan (T.N.)
| | | | - Børge G. Nordestgaard
- Herlev and Gentofte Hospital (B.G.N.), Copenhagen University Hospital, Copenhagen, Denmark
- Frederiksberg Hospital B.G.N.), Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences (B.G.N.), University of Copenhagen, Denmark
| | - Charlotte Onland-Moret
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands (C.O.-M., Y.T.v.d.S., W.M.M.V.)
| | - Luigi Palmieri
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Medical Research Council Biostatistics Unit (A.M.M., S. Burgess), University of Cambridge, UK
- Stroke Research Group, Department of Clinical Neurosciences (S. Bell), University of Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
- MRC Epidemiology Unit, School of Clinical Medicine (C.L., N.W.), University of Cambridge, UK
- Division of Aging (K.C., S.P., J.P.C. J.M.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Division of Cardiovascular Medicine (J.J., T.A.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Department of Epidemiology, Boston University School of Public Health, MA (R.J.S.)
- Division of Nephrology, Department of Medicine (C.R.-C., E.A.A.), Vanderbilt University Medical Center, Nashville, TN
- Department of Biostatistics (R. Tao), Vanderbilt University Medical Center, Nashville, TN
- Medical Research Council Population Health Research Unit, Clinical Trial Service Unit and Epidemiological Studies Unit (N.S., C.B.), Nuffield Department of Population Health, University of Oxford, UK
- Cancer Epidemiology Unit (T.T.), Nuffield Department of Population Health, University of Oxford, UK
- Department of Cardiology, Trakya University School of Medicine, Edirne, Turkey (S.A.)
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain (P.A.)
- Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain (P.A.)
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain (P.A., A.G.d.l.C., D.P., C. Santiuste)
- Division of Clinical Epidemiology and Aging Research (V.A.), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Cancer Epidemiology (S.K.J., R.K., V.K.), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, Stockholm, Sweden (J.A., H.B.)
- School of Health and Social Studies, Dalarna University, Falun, Sweden (J.A.)
- Wellbeing & Preventable Chronic Diseases (WPCD) Division, Menzies School of Health Research, Charles Darwin University, Darwin, NT, Australia (E.L.M.B.)
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (E.L.M.B., M.I.)
- Institute of Medicine, School of Public Health and Community Medicine (C.B.), Sahlgrenska Academy, University of Gothenburg, Sweden
- Institute of Medicine, Department of Molecular and Clinical Medicine (P.-O.H., A.R.), Sahlgrenska Academy, University of Gothenburg, Sweden
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands (J.M.A.B., W.M.M.V.)
- Network Aging Research (NAR), Heidelberg University, Germany (H.B.)
- Studium Patavinum (E.C.), University of Padua, Italy
- Department of Medicine (V.T.), University of Padua, Italy
- Dipartimento di Salute Mentale e Fisica e Medicina Preventiva, Università degli Studi della Campania ‘Luigi Vanvitelli’, Caserta, Italy (P.C.)
- William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, UK (J.A.C.)
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (J.C.)
- Larner College of Medicine, The University of Vermont, Burlington (M.C.)
- The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, Israel (R.D.)
- School of Public Health, Department of Epidemiology and Preventive Medicine, Tel Aviv University, Ramat Aviv, Tel Aviv, Israel (R.D.)
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York, NY (R.D., K.W.D.)
- Amsterdam University Medical Centers, VUMC, the Netherlands (R.T.d.J.)
- Department of Cardiovascular, Endocrine-metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy (C.D., L. Palmer)
- Department of Clinical Sciences, Malmö, Lund University, Sweden (G.E., O.M.)
- International Agency for Research on Cancer (IARC), World Health Organization, Lyon, France (H.F., E.W.)
- 12 Octubre Hospital Research Institute, Madrid, Spain (A.G.d,l,C.)
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland and Icelandic Heart Association, Kopavogur, Iceland (V.G.)
- Medical School Faculty of Health & Medical Sciences, The University of Western Australia, Perth, WA, Australia (G.J.H.)
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Medicine Geriatrics and Emergency Medicine/Östra, Gothenburg, Sweden (P.-O.H., A.R.)
- School of Public Health (A.K.H., I.T., E.R.), Imperial College London, UK
- The George Institute for Global Health (M.W.), Imperial College London, UK
- Department of Internal Medicine, Division of Nephrology and Transplantation, Erasmus MC, University Medical Center Rotterdam, the Netherlands (E.J.H.)
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita, Japan (H.I.)
- University of Eastern Finland (UEF), Kuopio, Finland (J.K.)
- Department of Neurology & Neurosurgery, Medical University of Innsbruck, Innsbruck, Austria (S.K.)
- Clinical Epidemiology Team, Institute of Health Economics, Medical University of Innsbruck, Innsbruck, Austria (S.K., P.W.)
- Institute of Epidemiology and Medical Biometry, University of Ulm, Germany (W.K.)
- Deutsches Herzzentrum München, Technische Universität München, Germany (W.K.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance (W.K.)
- School of Public Health, University of Washington, Seattle (R.A.K.)
- Danish Cancer Society Research Center, Copenhagen, Denmark (C.K., A.T.)
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, UK (D.A.L.)
- Population Health Science, Bristol Medical School, UK (D.A.L.)
- Department of Surgical and Perioperative sciences, Urology and Andrology, Umeå University, Sweden (B.L.)
- University Paris-Saclay, UVSQ, Inserm, Villejuif, France (C. MacDonald)
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy (G.M.)
- Helmholtz Zentrum München, Munich, Germany (C. Meisinger)
- Navarra Public Health Institute, IdiSNA, Pamplona, Spain (C.M.I.)
- Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Pamplona, Spain (C.M.I.)
- Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan (T.N.)
- London School of Hygiene & Tropical Medicine, UK (D.N.)
- Herlev and Gentofte Hospital (B.G.N.), Copenhagen University Hospital, Copenhagen, Denmark
- Frederiksberg Hospital B.G.N.), Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences (B.G.N.), University of Copenhagen, Denmark
- Department of Public Health (A.T.), University of Copenhagen, Denmark
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands (C.O.-M., Y.T.v.d.S., W.M.M.V.)
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain (D.P.)
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain (D.P.)
- Consejería de Sanidad del Principado de Asturias Oviedo, Asturias, Spain (J.R.Q.G.)
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital, Turin, Italy (C. Sacerdote)
- Department of Social and Environmental Medicine, Kanazawa Medical University, Uchinada, Japan (M.S.)
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Spain (C. Santiuste)
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany (M.B.S.)
- German Center for Diabetes Research (DZD), Neuherberg, Germany (M.B.S.)
- Institute of Nutritional Science, University of Potsdam, Germany (M.B.S.)
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy (S.S.)
- Department of Medical Sciences, Uppsala University, Sweden (J.S.)
- Hyblean Association for Epidemiological Reserach AIRE - ONLUS, Ragusa, Italy (R.T.)
- Universitätsmedizin Greifswald, Institut für Community Medicine, Abteilung SHIP/ Klinisch-Epidemiologische Forschung, Germany (H.V.)
- College of Public Health, University of Iowa (R.B.W.)
- University College London, UK (S.G.W.)
- The George Institute for Global Health, Camperdown, NSW, Australia (M.W.)
- Department of Public Health Medicine, Faculty of Medicine, and Health Services Research and Development Center, University of Tsukuba, Japan (K.Y.)
- Unit of Nutrition and Cancer, Epidemiology Research Program, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat (Barcelona), Spain (R.Z.-R.)
- Center for Data and Computational Sciences, VA Boston Healthcare System, Boston, MA (S.P.)
- Department of Biostatistics, Boston University School of Public Health, MA (D.R.G.)
- VA Pal Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, CA (P.S.T.)
- Medicine (Cardiovascular Medicine), Stanford University of School of Medicine, CA (P.S.T.)
- Office of Research and Development, Veterans Health Administration, Washington, DC (S.M.)
- Department of Veterans Affairs, Tennessee Valley Health Care System, Vanderbilt University, Nashville (T.L.E.)
- Medicine/Epidemiology, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN (T.L.E.)
- Department of Surgery, Corporal Michael Crescenz VA Medical Center and Perelman School of Medicine, University of Pennsylvania, Philadelphia (S.M.D.)
- Internal Medicine, VA Atlanta Healthcare System, Decatur, GA (P.W.F.W.)
- Emory University School of Medicine (Cardiology), Emory University, Atlanta, GA (P.W.F.W.)
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA (T.A.G.)
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
- The Alan Turing Institute, London, UK (M.I.)
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Germany (C.L.)
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK (J.D.)
- Division of Nephrology & Hypertension, Department of Medicine, Tennessee Valley Health Care System and Vanderbilt University Medical Center, Nashville (A.M.H.)
- Cambridge Centre for AI in Medicine, UK (A.M.W.)
- Health Data Science Centre, Human Technopole, Milan, Italy (E.D.A.)
| | - Dafina Petrova
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain (P.A., A.G.d.l.C., D.P., C. Santiuste)
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain (D.P.)
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain (D.P.)
| | | | - Annika Rosengren
- Institute of Medicine, Department of Molecular and Clinical Medicine (P.-O.H., A.R.), Sahlgrenska Academy, University of Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Medicine Geriatrics and Emergency Medicine/Östra, Gothenburg, Sweden (P.-O.H., A.R.)
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital, Turin, Italy (C. Sacerdote)
| | - Masaru Sakurai
- Department of Social and Environmental Medicine, Kanazawa Medical University, Uchinada, Japan (M.S.)
| | - Carmen Santiuste
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain (P.A., A.G.d.l.C., D.P., C. Santiuste)
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Spain (C. Santiuste)
| | - Matthias B. Schulze
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany (M.B.S.)
- German Center for Diabetes Research (DZD), Neuherberg, Germany (M.B.S.)
- Institute of Nutritional Science, University of Potsdam, Germany (M.B.S.)
| | - Sabina Sieri
- Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy (S.S.)
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Sweden (J.S.)
| | | | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark (C.K., A.T.)
- Department of Public Health (A.T.), University of Copenhagen, Denmark
| | - Tammy Tong
- Cancer Epidemiology Unit (T.T.), Nuffield Department of Population Health, University of Oxford, UK
| | - Rosario Tumino
- Hyblean Association for Epidemiological Reserach AIRE - ONLUS, Ragusa, Italy (R.T.)
| | - Ioanna Tzoulaki
- School of Public Health (A.K.H., I.T., E.R.), Imperial College London, UK
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands (C.O.-M., Y.T.v.d.S., W.M.M.V.)
| | - W.M. Monique Verschuren
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands (J.M.A.B., W.M.M.V.)
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, the Netherlands (C.O.-M., Y.T.v.d.S., W.M.M.V.)
| | - Henry Völzke
- Universitätsmedizin Greifswald, Institut für Community Medicine, Abteilung SHIP/ Klinisch-Epidemiologische Forschung, Germany (H.V.)
| | | | | | - Elisabete Weiderpass
- International Agency for Research on Cancer (IARC), World Health Organization, Lyon, France (H.F., E.W.)
| | - Peter Willeit
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Clinical Epidemiology Team, Institute of Health Economics, Medical University of Innsbruck, Innsbruck, Austria (S.K., P.W.)
| | - Mark Woodward
- The George Institute for Global Health, Camperdown, NSW, Australia (M.W.)
| | - Kazumasa Yamagishi
- Department of Public Health Medicine, Faculty of Medicine, and Health Services Research and Development Center, University of Tsukuba, Japan (K.Y.)
| | - Raul Zamora-Ros
- Unit of Nutrition and Cancer, Epidemiology Research Program, Catalan Institute of Oncology, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat (Barcelona), Spain (R.Z.-R.)
| | - Elvis A. Akwo
- Division of Nephrology, Department of Medicine (C.R.-C., E.A.A.), Vanderbilt University Medical Center, Nashville, TN
| | - Saiju Pyarajan
- Division of Aging (K.C., S.P., J.P.C. J.M.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Center for Data and Computational Sciences, VA Boston Healthcare System, Boston, MA (S.P.)
| | - David R. Gagnon
- Department of Biostatistics, Boston University School of Public Health, MA (D.R.G.)
| | - Philip S. Tsao
- VA Pal Alto Epidemiology Research and Information Center for Genomics, VA Palo Alto Health Care System, CA (P.S.T.)
- Medicine (Cardiovascular Medicine), Stanford University of School of Medicine, CA (P.S.T.)
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC (S.M.)
| | - Todd L. Edwards
- Department of Veterans Affairs, Tennessee Valley Health Care System, Vanderbilt University, Nashville (T.L.E.)
- Medicine/Epidemiology, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN (T.L.E.)
| | - Scott M. Damrauer
- Department of Surgery, Corporal Michael Crescenz VA Medical Center and Perelman School of Medicine, University of Pennsylvania, Philadelphia (S.M.D.)
| | - Jacob Joseph
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- Division of Cardiovascular Medicine (J.J., T.A.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Lisa Pennells
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Peter W.F. Wilson
- Internal Medicine, VA Atlanta Healthcare System, Decatur, GA (P.W.F.W.)
- Emory University School of Medicine (Cardiology), Emory University, Atlanta, GA (P.W.F.W.)
| | - Seamus Harrison
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Thomas A. Gaziano
- Division of Cardiovascular Medicine (J.J., T.A.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA (T.A.G.)
| | - Michael Inouye
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia (E.L.M.B., M.I.)
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
- The Alan Turing Institute, London, UK (M.I.)
| | - Colin Baigent
- Institute of Medicine, School of Public Health and Community Medicine (C.B.), Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Juan P. Casas
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- Division of Aging (K.C., S.P., J.P.C. J.M.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Claudia Langenberg
- MRC Epidemiology Unit, School of Clinical Medicine (C.L., N.W.), University of Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Germany (C.L.)
| | - Nick Wareham
- MRC Epidemiology Unit, School of Clinical Medicine (C.L., N.W.), University of Cambridge, UK
| | - Elio Riboli
- The George Institute for Global Health (M.W.), Imperial College London, UK
| | - J.Michael Gaziano
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA (L.G., K.C., R.J.S., D.C.P., P.S., J.J., J.P.C., J.M.G.)
- Division of Aging (K.C., S.P., J.P.C. J.M.G.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - John Danesh
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK (J.D.)
| | - Adriana M. Hung
- Division of Nephrology & Hypertension, Department of Medicine, Tennessee Valley Health Care System and Vanderbilt University Medical Center, Nashville (A.M.H.)
| | - Adam S. Butterworth
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
| | - Angela M. Wood
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Cambridge Centre for AI in Medicine, UK (A.M.W.)
| | - Emanuele Di Angelantonio
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care (L.G., L.S., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., T.R.B., E.A., L.C., J.R.S., P.W., L. Pennells, S.H., M.I., J.D., A.S.B., A.M.W., E.D.A.)
- BHF Centre of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital (A.M.M., S. Burgess, J.D., A.M.W., A.S.B., E.D.A.)
- Heart and Lung Research Institute, University of Cambridge, Cambridge UK (L.G., S. Bell, S.K.K., S. Burgess, K.M., A.M.M., E.A., L. Pennells, M.I., J.D., A.S.B., A.M.W., E.D.A.)
- NIHR Blood and Transplant Research Unit in Donor Health and Behaviour (S. Bell, T.R.B., E.A., J.D., A.S.B., A.M.W., E.D.A.), University of Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, UK (M.I., J.D., A.S.B., A.M.W., E.D.A.)
- Health Data Science Centre, Human Technopole, Milan, Italy (E.D.A.)
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Chen L, Fan Z, Lv G. Associations of muscle mass and grip strength with severe NAFLD: A prospective study of 333,295 UK Biobank participants. J Hepatol 2022; 77:1453-1454. [PMID: 35605742 DOI: 10.1016/j.jhep.2022.05.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 05/06/2022] [Indexed: 12/11/2022]
Affiliation(s)
- Lanlan Chen
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, 71 Xinmin Street, Changchun, 130021, Jilin, China
| | - Zhongqi Fan
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, 71 Xinmin Street, Changchun, 130021, Jilin, China
| | - Guoyue Lv
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, 71 Xinmin Street, Changchun, 130021, Jilin, China.
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Liu Z, Song C, Suo C, Fan H, Zhang T, Jin L, Chen X. Alcohol consumption and hepatocellular carcinoma: novel insights from a prospective cohort study and nonlinear Mendelian randomization analysis. BMC Med 2022; 20:413. [PMID: 36303185 PMCID: PMC9615332 DOI: 10.1186/s12916-022-02622-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/21/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Heavy drinking was well associated with an increased risk of hepatocellular carcinoma (HCC), whereas the effect of low-to-moderate drinking on HCC remains under debate. METHODS Participants from the UK Biobank with detailed information on alcohol use and free of common diseases were included. Daily pure alcohol intake (g/day) was calculated, and the predominant alcoholic beverage type was assigned for each participant. Additive Cox regression model and nonlinear Mendelian randomization (NLMR) analyses were performed to evaluate the association of alcohol intake with HCC. RESULTS Of 329,164 participants (52.3% females, mean [SD] age = 56.7 [8.0] years), 201 incident HCC cases were recorded during the median follow-up of 12.6 years. The best-fitted Cox regression model suggested a J-shaped relationship between daily alcohol intake level and HCC risk. However, NLMR analysis did not detect a nonlinear correlation between alcohol use and HCC (nonlinearity P-value: 0.386). The J-shaped correlation pattern was detected only in subjects who mainly drank wine but not in those who mainly drank beer, spirits, or fortified wine. Moderate wine drinking showed a significant alanine transaminase (ALT)- and aspartate aminotransferase-lowering effect compared to that of the nondrinkers. In low-risk populations of HCC including women, people aged < 60 years, subjects with normal ALT levels, and those carrying non-risk genotypes of PNPLA3 rs738409 and TM6SF2 rs58542926, we observed a J-shaped correlation between alcohol use and HCC; however, a positive dose-response correlation was found in their respective counterparts, even in those predominantly drinking wine. CONCLUSIONS Low-to-moderate drinking may be inversely associated with the risk of HCC in low-risk populations, which may be largely driven by wine drinking. However, those in high-risk populations of HCC, such as men and older people, and those with abnormal ALT levels and carry genetic risk variants, should abstain from drinking alcohol. Given the small HCC case number, further validations with larger case numbers are warranted in future works.
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Affiliation(s)
- Zhenqiu Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai, 200438, China.,Fudan University Taizhou Institute of Health Sciences, Taizhou, 225316, China
| | - Ci Song
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Chen Suo
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, 200032, China.,Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Hong Fan
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, 200032, China.,Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Tiejun Zhang
- Key Laboratory of Public Health Safety, Fudan University, Ministry of Education, Shanghai, 200032, China. .,Department of Epidemiology, School of Public Health, Fudan University, Shanghai, 200032, China.
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai, 200438, China.,Fudan University Taizhou Institute of Health Sciences, Taizhou, 225316, China
| | - Xingdong Chen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai, 200438, China. .,Fudan University Taizhou Institute of Health Sciences, Taizhou, 225316, China. .,National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, 200040, China.
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38
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Lundgren S, Kuitunen S, Pietiläinen KH, Hurme M, Kähönen M, Männistö S, Perola M, Lehtimäki T, Raitakari O, Kaprio J, Ollikainen M. BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index. J Intern Med 2022; 292:627-640. [PMID: 35699258 PMCID: PMC9540898 DOI: 10.1111/joim.13528] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND Obesity is a heritable complex phenotype that can increase the risk of age-related outcomes. Biological age can be estimated from DNA methylation (DNAm) using various "epigenetic clocks." Previous work suggests individuals with elevated weight also display accelerated aging, but results vary by epigenetic clock and population. Here, we utilize the new epigenetic clock GrimAge, which closely correlates with mortality. OBJECTIVES We aimed to assess the cross-sectional association of body mass index (BMI) with age acceleration in twins to limit confounding by genetics and shared environment. METHODS AND RESULTS Participants were from the Finnish Twin Cohort (FTC; n = 1424), including monozygotic (MZ) and dizygotic (DZ) twin pairs, and DNAm was measured using the Illumina 450K array. Multivariate linear mixed effects models including MZ and DZ twins showed an accelerated epigenetic age of 1.02 months (p-value = 6.1 × 10-12 ) per one-unit BMI increase. Additionally, heavier twins in a BMI-discordant MZ twin pair (ΔBMI >3 kg/m2 ) had an epigenetic age 5.2 months older than their lighter cotwin (p-value = 0.0074). We also found a positive association between log (homeostatic model assessment of insulin resistance) and age acceleration, confirmed by a meta-analysis of the FTC and two other Finnish cohorts (overall effect = 0.45 years, p-value = 4.1 × 10-25 ) from adjusted models. CONCLUSION We identified significant associations of BMI and insulin resistance with age acceleration based on GrimAge, which were not due to genetic effects on BMI and aging. Overall, these results support a role of BMI in aging, potentially in part due to the effects of insulin resistance.
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Affiliation(s)
- Sara Lundgren
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sara Kuitunen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland.,Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Satu Männistö
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland.,Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.,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
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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Zheng J, Xu M, Walker V, Yuan J, Korologou-Linden R, Robinson J, Huang P, Burgess S, Au Yeung SL, Luo S, Holmes MV, Davey Smith G, Ning G, Wang W, Gaunt TR, Bi Y. Evaluating the efficacy and mechanism of metformin targets on reducing Alzheimer's disease risk in the general population: a Mendelian randomisation study. Diabetologia 2022; 65:1664-1675. [PMID: 35902387 PMCID: PMC9477943 DOI: 10.1007/s00125-022-05743-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 04/08/2022] [Indexed: 02/05/2023]
Abstract
AIMS/HYPOTHESIS Metformin use has been associated with reduced incidence of dementia in diabetic individuals in observational studies. However, the causality between the two in the general population is unclear. This study uses Mendelian randomisation (MR) to investigate the causal effect of metformin targets on Alzheimer's disease and potential causal mechanisms in the brain linking the two. METHODS Genetic proxies for the effects of metformin drug targets were identified as variants in the gene for the corresponding target that associated with HbA1c level (N=344,182) and expression level of the corresponding gene (N≤31,684). The cognitive outcomes were derived from genome-wide association studies comprising 527,138 middle-aged Europeans, including 71,880 with Alzheimer's disease or Alzheimer's disease-by-proxy. MR estimates representing lifelong metformin use on Alzheimer's disease and cognitive function in the general population were generated. Effect of expression level of 22 metformin-related genes in brain cortex (N=6601 donors) on Alzheimer's disease was further estimated. RESULTS Genetically proxied metformin use, equivalent to a 6.75 mmol/mol (1.09%) reduction on HbA1c, was associated with 4% lower odds of Alzheimer's disease (OR 0.96 [95% CI 0.95, 0.98], p=1.06×10-4) in non-diabetic individuals. One metformin target, mitochondrial complex 1 (MCI), showed a robust effect on Alzheimer's disease (OR 0.88, p=4.73×10-4) that was independent of AMP-activated protein kinase. MR of expression in brain cortex tissue showed that decreased MCI-related gene (NDUFA2) expression was associated with lower Alzheimer's disease risk (OR 0.95, p=4.64×10-4) and favourable cognitive function. CONCLUSIONS/INTERPRETATION Metformin use may cause reduced Alzheimer's disease risk in the general population. Mitochondrial function and the NDUFA2 gene are plausible mechanisms of action in dementia protection.
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Affiliation(s)
- Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Venexia Walker
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Jinqiu Yuan
- Clinical Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
- Center for Digestive Disease, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China
- Guangzhou Women and Children Medical Center, Guangzhou, Guangdong, China
- Division of Epidemiology, the JC School of Public Health & Primary Care, the Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Roxanna Korologou-Linden
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Jamie Robinson
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Peiyuan Huang
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Shiu Lun Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, SAR, China
| | - Shan Luo
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong, SAR, China
| | - Michael V Holmes
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Oxford, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK.
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK.
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Yang Q, Magnus MC, Kilpi F, Santorelli G, Soares AG, West J, Magnus P, Wright J, Håberg SE, Sanderson E, Lawlor DA, Tilling K, Borges MC. Investigating causal relations between sleep duration and risks of adverse pregnancy and perinatal outcomes: linear and nonlinear Mendelian randomization analyses. BMC Med 2022; 20:295. [PMID: 36089592 PMCID: PMC9465870 DOI: 10.1186/s12916-022-02494-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 07/25/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Observational studies have reported maternal short/long sleep duration to be associated with adverse pregnancy and perinatal outcomes. However, it remains unclear whether there are nonlinear causal effects. Our aim was to use Mendelian randomization (MR) and multivariable regression to examine nonlinear effects of sleep duration on stillbirth (MR only), miscarriage (MR only), gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, preterm birth and low/high offspring birthweight. METHODS We used data from European women in UK Biobank (N=176,897), FinnGen (N=~123,579), Avon Longitudinal Study of Parents and Children (N=6826), Born in Bradford (N=2940) and Norwegian Mother, Father and Child Cohort Study (MoBa, N=14,584). We used 78 previously identified genetic variants as instruments for sleep duration and investigated its effects using two-sample, and one-sample nonlinear (UK Biobank only), MR. We compared MR findings with multivariable regression in MoBa (N=76,669), where maternal sleep duration was measured at 30 weeks. RESULTS In UK Biobank, MR provided evidence of nonlinear effects of sleep duration on stillbirth, perinatal depression and low offspring birthweight. Shorter and longer duration increased stillbirth and low offspring birthweight; shorter duration increased perinatal depression. For example, longer sleep duration was related to lower risk of low offspring birthweight (odds ratio 0.79 per 1 h/day (95% confidence interval: 0.67, 0.93)) in the shortest duration group and higher risk (odds ratio 1.40 (95% confidence interval: 1.06, 1.84)) in the longest duration group, suggesting shorter and longer duration increased the risk. These were supported by the lack of evidence of a linear effect of sleep duration on any outcome using two-sample MR. In multivariable regression, risks of all outcomes were higher in the women reporting <5 and ≥10 h/day sleep compared with the reference category of 8-9 h/day, despite some wide confidence intervals. Nonlinear models fitted the data better than linear models for most outcomes (likelihood ratio P-value=0.02 to 3.2×10-52), except for gestational diabetes. CONCLUSIONS Our results show shorter and longer sleep duration potentially causing higher risks of stillbirth, perinatal depression and low offspring birthweight. Larger studies with more cases are needed to detect potential nonlinear effects on hypertensive disorders of pregnancy, preterm birth and high offspring birthweight.
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Affiliation(s)
- Qian Yang
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Maria C Magnus
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Fanny Kilpi
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gillian Santorelli
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Ana Gonçalves Soares
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jane West
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Siri Eldevik Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Eleanor Sanderson
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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41
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Mason AM, Burgess S. Software Application Profile: SUMnlmr, an R package that facilitates flexible and reproducible non-linear Mendelian randomization analyses. Int J Epidemiol 2022; 51:2014-2019. [PMCID: PMC9749704 DOI: 10.1093/ije/dyac150] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 08/05/2022] [Indexed: 11/06/2023] Open
Abstract
Motivation Mendelian randomization methods that estimate non-linear exposure-outcome relationships typically require individual-level data. This package implements non-linear Mendelian randomization methods using stratified summarized data, facilitating analyses where individual-level data cannot easily be shared, and additionally increasing reproducibility as summarized data can be reported. Dependence on summarized data means the methods are independent of the form of the individual-level data, increasing flexibility to different outcome types (such as continuous, binary or time-to-event outcomes). Implementation SUMnlmr is available as an R package (version 3.1.0 or higher). General features The package implements the previously proposed fractional polynomial and piecewise linear methods on stratified summarized data that can either be estimated from individual-level data using the package or supplied by a collaborator. It constructs plots to visualize the estimated exposure-outcome relationship, and provides statistics to assess preference for a non-linear model over a linear model. Availability The package is freely available from GitHub [https://github.com/amymariemason/SUMnlmr ].
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Affiliation(s)
- Amy M Mason
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
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Camm CF, Virdone S, Goto S, Bassand JP, van Eickels M, Haas S, Gersh BJ, Pieper K, Fox KAA, Misselwitz F, Turpie AGG, Goldhaber SZ, Verheugt F, Camm J, Kayani G, Panchenko E, Oh S, Luciardi HL, Sawhney JPS, Connolly SJ, Angchaisuksiri P, ten Cate H, Eikelboom JW, Kakkar AK. Association of body mass index with outcomes in patients with newly diagnosed atrial fibrillation: GARFIELD-AF. Open Heart 2022. [PMCID: PMC9362832 DOI: 10.1136/openhrt-2022-002038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Objective While greater body mass index (BMI) is associated with increased risk of developing atrial fibrillation (AF), the impact of BMI on outcomes in newly diagnosed AF is unclear. We examine the influence of BMI on outcomes and whether this is modified by sex and evaluate the effect of non-vitamin K oral anticoagulants (NOACs) in patients with high BMI. Methods GARFIELD-AF is a prospective registry of 52 057 newly diagnosed AF patients. The study population comprised 40 482 participants: 703 underweight (BMI <18.5 kg/m2), 13 095 normal (BMI=18.5–24.9 kg/m2), 15 043 overweight (BMI=25.0–29.9 kg/m2), 7560 obese (BMI=30.0–34.9 kg/m2) and 4081 extremely obese (BMI ≥35.0 kg/m2). Restricted cubic splines quantified the association of BMI with outcomes. Comparative effectiveness of NOACs and vitamin K antagonists (VKAs) by BMI was performed using propensity score overlap-weighted Cox models. Results The median age of participants was 71.0 years (Q1; Q3 62.0; 78.0), and 55.6% were male. Those with high BMI were younger, more often had vascular disease, hypertension and diabetes. Within 2-year follow-up, a U-shaped relationship between BMI and all-cause mortality was observed, with BMI of ~30 kg/m2 associated with the lowest risk. The association with new/worsening heart failure was similar. Only low BMI was associated with major bleeding and no association emerged for non-haemorrhagic stroke. BMI was similarly associated with outcomes in men and women. BMI did not impact the lower rate of all-cause mortality of NOACs compared with VKAs. Conclusions In the GARFIELD-AF registry, underweight and extremely obese AF patients have increased risk of mortality and new/worsening heart failure compared with normal or obese patients.
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Abstract
Obesity is in theory defined on the basis of the excess health risk caused by adiposity exceeding the size normally found in the population, but for practical reasons, the World Health Organization (WHO) has defined obesity as a body mass index (weight (kg)/height (m)2) of 30 or above for adults. WHO considers the steep increases in prevalence of obesity in all age groups, especially since the 1970s as a global obesity epidemic. Today, approximately 650 million adult people and approximately 340 million children and adolescence (5-19 years) suffer from obesity. It is generally more prevalent among women and older age groups than among men and younger age groups. Beyond the necessity of availability of food, evidence about causes of obesity is still very limited. However, studies have shown that obesity 'runs in families', where both genetics and environmental, and especially social, factors play important roles. Obesity is associated with an increased risk of many adverse medical, mental and social consequences, including a strong relation to type 2 diabetes. Type 2 diabetes and related metabolic syndrome and diseases are major contributors to the excess morbidity and mortality associated with obesity.
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Tarp J, Fagerland MW, Dalene KE, Johannessen JS, Hansen BH, Jefferis BJ, Whincup PH, Diaz KM, Hooker S, Howard VJ, Chernofsky A, Larson MG, Spartano NL, Vasan RS, Dohrn IM, Hagströmer M, Edwardson C, Yates T, Shiroma EJ, Dempsey PC, Wijndaele K, Anderssen SA, Lee IM, Ekelund U. Device-measured physical activity, adiposity and mortality: a harmonised meta-analysis of eight prospective cohort studies. Br J Sports Med 2022; 56:725-732. [PMID: 34876405 PMCID: PMC9209690 DOI: 10.1136/bjsports-2021-104827] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 12/27/2022]
Abstract
BACKGROUND The joint associations of total and intensity-specific physical activity with obesity in relation to all-cause mortality risk are unclear. METHODS We included 34 492 adults (72% women, median age 62.1 years, 2034 deaths during follow-up) in a harmonised meta-analysis of eight population-based prospective cohort studies with mean follow-up ranging from 6.0 to 14.5 years. Standard body mass index categories were cross-classified with sample tertiles of device-measured total, light-to-vigorous and moderate-to-vigorous physical activity and sedentary time. In five cohorts with waist circumference available, high and low waist circumference was combined with tertiles of moderate-to-vigorous physical activity. RESULTS There was an inverse dose-response relationship between higher levels of total and intensity-specific physical activity and mortality risk in those who were normal weight and overweight. In individuals with obesity, the inverse dose-response relationship was only observed for total physical activity. Similarly, lower levels of sedentary time were associated with lower mortality risk in normal weight and overweight individuals but there was no association between sedentary time and risk of mortality in those who were obese. Compared with the obese-low total physical activity reference, the HRs were 0.59 (95% CI 0.44 to 0.79) for normal weight-high total activity and 0.67 (95% CI 0.48 to 0.94) for obese-high total activity. In contrast, normal weight-low total physical activity was associated with a higher risk of mortality compared with the obese-low total physical activity reference (1.28; 95% CI 0.99 to 1.67). CONCLUSIONS Higher levels of physical activity were associated with lower risk of mortality irrespective of weight status. Compared with obesity-low physical activity, there was no survival benefit of being normal weight if physical activity levels were low.
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Affiliation(s)
- Jakob Tarp
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | - Morten W Fagerland
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | - Knut Eirik Dalene
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | | | - Bjørge H Hansen
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
- Department of Sport Science and Physical Education, University of Agder, Kristiansand, Norway
| | - Barbara J Jefferis
- Primary Care and Population Health, University College London, London, UK
| | - Peter H Whincup
- Population Health Research Institute, St George's University of London, London, UK
| | - Keith M Diaz
- Department of Medicine, Center for Behavioral Cardiovascular Health, Columbia University Medical Center, New York, New York, USA
| | - Steven Hooker
- College of Health and Human Services, San Diego State University, San Diego, California, USA
| | - Virginia J Howard
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Ariel Chernofsky
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Nicole L Spartano
- Department of Endocrinology, Diabetes, Nutrition and Weight Management, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Ramachandran S Vasan
- Departments of Medicine and Epidemiology, Boston University School of Medicine and Boston University School of Public Health, Boston, Massachusetts, USA
| | - Ing-Mari Dohrn
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Maria Hagströmer
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden
| | - Charlotte Edwardson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Thomas Yates
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust, Leicester, UK
| | - Eric J Shiroma
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, Maryland, USA
| | - Paddy C Dempsey
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Physical Activity and Behavioural Epidemiology Laboratories, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | | | - Sigmund A Anderssen
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
| | - I-Min Lee
- Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo, Norway
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
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Hasebe T, Hasebe N. Impact of risk factors related to metabolic syndrome on acute myocardial infarction in younger patients. Hypertens Res 2022; 45:1447-1458. [PMID: 35681042 DOI: 10.1038/s41440-022-00951-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/23/2022] [Accepted: 05/03/2022] [Indexed: 01/09/2023]
Abstract
Despite diagnostic and therapeutic advancements in cardiovascular medicine, myocardial infarction (MI) remains a major cause of adverse outcomes in younger MI patients, i.e., those who are aged 55 years or younger. Traditional cardiovascular risk factors have not often been emphasized in the management of younger MI patients. However, plaque rupture or erosion, which is deeply related to cardiovascular risk factors, remains the most common etiology of MI even in younger patients. The global increase in the prevalence of obesity underscores the clinical importance of metabolic syndrome (MetS), i.e., obesity-associated cardiovascular risk factors, dyslipidemia, diabetes mellitus and particularly hypertension, in younger people. The concept of "lifetime risk" of cardiovascular disease reinforces the need for prevention or treatment of MetS. This review focuses on the risk factors related to MetS and an overall understanding of recent profiles of younger MI patients. We hope that this review will aid in the primary prevention of MetS-related risk factors and the prevention of cardiovascular disease, particularly MI, in younger patients.
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Affiliation(s)
- Tomomi Hasebe
- Department of Cardiovascular Medicine, Asahikawa Rehabilitation Hospital, Asahikawa, Japan
| | - Naoyuki Hasebe
- Department of Cardiovascular Regeneration and Innovation, Asahikawa Medical University, Asahikawa, Japan.
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Zhou A, Selvanayagam JB, Hyppönen E. Non-linear Mendelian randomization analyses support a role for vitamin D deficiency in cardiovascular disease risk. Eur Heart J 2022; 43:1731-1739. [PMID: 34891159 DOI: 10.1093/eurheartj/ehab809] [Citation(s) in RCA: 93] [Impact Index Per Article: 46.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/28/2021] [Accepted: 11/12/2021] [Indexed: 11/14/2022] Open
Abstract
AIMS Low vitamin D status is associated with a higher risk for cardiovascular diseases (CVDs). Although most existing linear Mendelian randomization (MR) studies reported a null effect of vitamin D on CVD risk, a non-linear effect cannot be excluded. Our aim was to apply the non-linear MR design to investigate the association of serum 25-hydroxyvitamin D [25(OH)D] concentration with CVD risk. METHODS AND RESULTS The non-linear MR analysis was conducted in the UK Biobank with 44 519 CVD cases and 251 269 controls. Blood pressure (BP) and cardiac-imaging-derived phenotypes were included as secondary outcomes. Serum 25(OH)D concentration was instrumented using 35 confirmed genome-wide significant variants.We also estimated the potential reduction in CVD incidence attributable to correction of low vitamin D status. There was a L-shaped association between genetically predicted serum 25(OH)D and CVD risk (Pnon-linear = 0.007), where CVD risk initially decreased steeply with increasing concentrations and levelled off at around 50 nmol/L. A similar association was seen for systolic (Pnon-linear = 0.03) and diastolic (Pnon-linear = 0.07) BP. No evidence of association was seen for cardiac-imaging phenotypes (P = 0.05 for all). Correction of serum 25(OH)D level below 50 nmol/L was predicted to result in a 4.4% reduction in CVD incidence (95% confidence interval: 1.8- 7.3%). CONCLUSION Vitamin D deficiency can increase the risk of CVD. Burden of CVD could be reduced by population-wide correction of low vitamin D status.
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Affiliation(s)
- Ang Zhou
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia
| | - Joseph B Selvanayagam
- South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia
- Department of Cardiovascular Medicine, Flinders Medical Centre, Bedford Park, Adelaide, SA 5042, Australia
| | - Elina Hyppönen
- Australian Center for Precision Health, University of South Australia Cancer Research Institute, GPO Box 2471, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London, UK
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Wade KH, Yarmolinsky J, Giovannucci E, Lewis SJ, Millwood IY, Munafò MR, Meddens F, Burrows K, Bell JA, Davies NM, Mariosa D, Kanerva N, Vincent EE, Smith-Byrne K, Guida F, Gunter MJ, Sanderson E, Dudbridge F, Burgess S, Cornelis MC, Richardson TG, Borges MC, Bowden J, Hemani G, Cho Y, Spiller W, Richmond RC, Carter AR, Langdon R, Lawlor DA, Walters RG, Vimaleswaran KS, Anderson A, Sandu MR, Tilling K, Davey Smith G, Martin RM, Relton CL. Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer. Cancer Causes Control 2022; 33:631-652. [PMID: 35274198 PMCID: PMC9010389 DOI: 10.1007/s10552-022-01562-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 02/10/2022] [Indexed: 02/08/2023]
Abstract
Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner. Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when using MR, and methodological developments aimed at investigating and potentially overcoming these biases when present. Lastly, we consider the use of MR in identifying causally relevant nutritional risk factors for various cancers in different regions across the world, given notable geographical differences in some cancers. We also discuss how MR results could be translated into further research and policy. We conclude that findings from MR studies, which corroborate those from other well-conducted studies with different and orthogonal biases, are poised to substantially improve our understanding of nutritional influences on cancer. For such corroboration, there is a requirement for an interdisciplinary and collaborative approach to investigate risk factors for cancer incidence and progression.
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Affiliation(s)
- Kaitlin H Wade
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.
| | - James Yarmolinsky
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Edward Giovannucci
- Departments of Nutrition and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Sarah J Lewis
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) and the Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marcus R Munafò
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Fleur Meddens
- Department of Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Kimberley Burrows
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Joshua A Bell
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Neil M Davies
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Daniela Mariosa
- International Agency for Research On Cancer (IARC), Lyon, France
| | | | - Emma E Vincent
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Cellular and Molecular Medicine, Faculty of Life Sciences, University of Bristol, Bristol, UK
| | - Karl Smith-Byrne
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Florence Guida
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Marc J Gunter
- International Agency for Research On Cancer (IARC), Lyon, France
| | - Eleanor Sanderson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Tom G Richardson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Jack Bowden
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Research Innovation Learning and Development (RILD) Building, University of Exeter Medical School, Exeter, UK
| | - Gibran Hemani
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Yoonsu Cho
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Wes Spiller
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Alice R Carter
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Ryan Langdon
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) and the Medical Research Council Population Health Research Unit (MRC PHRU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Annie Anderson
- Population Health and Genomics, School of Medicine, University of Dundee, Dundee, Scotland, UK
| | - Meda R Sandu
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre, Bristol, UK
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
| | - Richard M Martin
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
| | - Caroline L Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK
- Bristol National Institute for Health Research (NIHR) Biomedical Research Centre, Bristol, UK
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Trends of overweight, obesity and anthropometric measurements among the adult population in Italy: The CUORE Project health examination surveys 1998, 2008, and 2018. PLoS One 2022; 17:e0264778. [PMID: 35231070 PMCID: PMC8887738 DOI: 10.1371/journal.pone.0264778] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 02/16/2022] [Indexed: 12/23/2022] Open
Abstract
Background/Objectives Obesity is associated with an increased risk of noncommunicable diseases, such as diabetes, coronary heart disease, stroke, cancers, and conditions, including obstructive sleep apnea and osteoarthritis. Obesity is largely preventable, and halting its rise is one of the World Health Organization Global Action Plan for the Prevention of Noncommunicable Diseases targets. This study aimed to assess trends of anthropometric measurements in Italy using the data collected within the CUORE Project health examination surveys (HESs) 1998, 2008, and 2018. Subjects/Methods Within the HESs 1998–2002, 2008–2012, and 2018–2019, anthropometric measurements were collected in random samples of the resident population aged 35–74 years, stratified by age and sex, from 10 Italian Regions in Northern, Central, and Southern Italy (2984 men and 2944 women, 2224 men and 2188 women, 1035 men and 1065 women, respectively). Weight, height, and waist and hip circumferences were measured using standardized methodologies. A standardized questionnaire was used to collect data on education. Indicators were age standardized. Results For both men and women, mean body mass index in 2018 was comparable with those in 1998 and 2008 (in 1998, 2008, and 2018—men: 26.7, 27.5, and 27.0 kg/m2; women: 26.2, 26.6, and 26.3 kg/m2). In 1998, 2008, 2018 prevalence of overweight resulted 49%, 47%, 46% in men and 33%, 32%, 28% in women respectively; prevalence of obesity resulted 17%, 24% 20% in men and 19%, 23%, 23% in women respectively. All indicators of excess weight worsen with increasing age and are more severe in persons with a lower educational level. Conclusions Although the overall trend of excess weight over the past two decades appeared to be substantially stable in the Italian adult population, the continuous strengthening of undertaken initiatives should continue since there remains a high proportion of overweight or obesity and a gap between educational levels.
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Drapkina OM, Kontsevaya AV, Kalinina AM, Avdeev SM, Agaltsov MV, Alexandrova LM, Antsiferova AA, Aronov DM, Akhmedzhanov NM, Balanova YA, Balakhonova TV, Berns SA, Bochkarev MV, Bochkareva EV, Bubnova MV, Budnevsky AV, Gambaryan MG, Gorbunov VM, Gorny BE, Gorshkov AY, Gumanova NG, Dadaeva VA, Drozdova LY, Egorov VA, Eliashevich SO, Ershova AI, Ivanova ES, Imaeva AE, Ipatov PV, Kaprin AD, Karamnova NS, Kobalava ZD, Konradi AO, Kopylova OV, Korostovtseva LS, Kotova MB, Kulikova MS, Lavrenova EA, Lischenko OV, Lopatina MV, Lukina YV, Lukyanov MM, Mayev IV, Mamedov MN, Markelova SV, Martsevich SY, Metelskaya VA, Meshkov AN, Milushkina OY, Mukaneeva DK, Myrzamatova AO, Nebieridze DV, Orlov DO, Poddubskaya EA, Popovich MV, Popovkina OE, Potievskaya VI, Prozorova GG, Rakovskaya YS, Rotar OP, Rybakov IA, Sviryaev YV, Skripnikova IA, Skoblina NA, Smirnova MI, Starinsky VV, Tolpygina SN, Usova EV, Khailova ZV, Shalnova SA, Shepel RN, Shishkova VN, Yavelov IS. 2022 Prevention of chronic non-communicable diseases in Of the Russian Federation. National guidelines. КАРДИОВАСКУЛЯРНАЯ ТЕРАПИЯ И ПРОФИЛАКТИКА 2022. [DOI: 10.15829/1728-8800-2022-3235] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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Abusharha A, El-Hiti GA, Alharbi A, Fagehi R, Alanazi MA, Alsaqar A, Masmali AM, Almubrad T. Evaluation of Tear Evaporation Rate in Subjects with a High Body Mass Index. Klin Monbl Augenheilkd 2022; 240:283-287. [PMID: 35426102 DOI: 10.1055/a-1778-4435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Abstract
Aim This study evaluated the tear evaporation rate (TER) in subjects with a high body mass index (BMI) and tested the correlation between BMI and dry eye.
Methods Thirty male subjects aged 18 – 38 years (26.4 ± 4.0 years) with a high BMI (26.4 – 47.0 kg/m2) were enrolled in the study. In addition, a control group of 30 males
aged 20 – 36 years (24.0 ± 3.6 years) with a normal BMI (< 25 kg/m2) participated in the study for comparison. Each subject completed the ocular surface disease index (OSDI),
followed by the TER measurement using a handheld VapoMeter.
Results Significant differences (Wilcoxon test; p = 0.002 and 0.001) were found between the median scores of the OSDI (10.3 [3.7] vs. 5.9 [7.2]) and TER (35.5 [13.1] vs. 15.5 [12.8]
g/m2 h) in the study and control groups, respectively. The OSDI indicated dry eye in 60.0% of subjects in the study group (n = 18). The TER measurements showed that 76.7% of
subjects in the study group (n = 23) had dry eyes. A medium correlation (r = 0.569; p = 0.001) was found between the OSDI scores and TER measurements.
Conclusions The means of the tear evaporation rate and the ocular surface disease index scores are significantly higher in subjects with a high BMI compared with the control group.
Therefore, a high BMI is considered a risk factor for dry eye. The measurement of the tear evaporation rate using a handheld VapoMeter is a simple and rapid method to detect dry eyes in
combination with other tools.
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Affiliation(s)
- Ali Abusharha
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Gamal A. El-Hiti
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Abdulhadi Alharbi
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Raied Fagehi
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Mana A. Alanazi
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Ali Alsaqar
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Ali M. Masmali
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
| | - Turki Almubrad
- Department of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia
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