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Wicki B, Vienneau D, Schwendinger F, Schmidt-Trucksäss A, Wunderli JM, Schalcher S, Röösli M. Associations of exposure to transportation noise with sleep and cardiometabolic health: exploration of pathways. ENVIRONMENTAL RESEARCH 2025; 279:121805. [PMID: 40345417 DOI: 10.1016/j.envres.2025.121805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2024] [Revised: 05/05/2025] [Accepted: 05/07/2025] [Indexed: 05/11/2025]
Abstract
Transportation noise is known to increase the risk for multiple cardiometabolic diseases. However, the complex relationship between different noise sources, sleep, metabolic and cardiovascular risk factors is still not well understood. To study how chronic noise exposure contributes to the development of cardiometabolic disease, data from the cross-sectional COmPLETE-Health Study were used, which includes a comprehensive cardiometabolic assessment and accelerometer-based behavioral monitoring from 527 healthy Swiss adults aged 20-89 years. Road traffic, aircraft and railway noise were modelled at the participants' home addresses, followed by a measurement based model validation. For each noise source, the following conceptual model was tested using Structural Equation Modelling (SEM): Noise was assumed to affect the two latent constructs metabolic risk (defined by waist-to-hip ratio and HDL-cholesterol) and cardiovascular risk (defined by systolic blood pressure and pulse wave velocity) directly, as well as indirectly via sleep efficiency. The SEM showed very good fit of the conceptual models. Road traffic noise had a significant, small-medium sized direct link with cardiovascular risk (β = 0.16, 95 %CI: 0.01, 0.31), while negligible associations with sleep efficiency or metabolic risk were observed. Conversely, railway noise was mainly associated with lower sleep efficiency (β = -0.15, 95 %CI: -0.23, -0.06) and increased metabolic risk (β = 0.14, 95 %CI: -0.05, 0.32), with only a negligible association with cardiovascular risk. The inclusion of physical activity did not change results, suggesting that associations of noise with cardiometabolic health are robust to the additional consideration of physical activity. These insights are important to inform effective measures to protect populations from harmful transportation noise exposure.
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Affiliation(s)
- Benedikt Wicki
- Swiss TPH (Swiss Tropical and Public Health Institute), Allschwil, Switzerland; University of Basel, Basel, Switzerland.
| | - Danielle Vienneau
- Swiss TPH (Swiss Tropical and Public Health Institute), Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Fabian Schwendinger
- Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | | | - Jean-Marc Wunderli
- EMPA, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
| | - Stefan Schalcher
- EMPA, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland
| | - Martin Röösli
- Swiss TPH (Swiss Tropical and Public Health Institute), Allschwil, Switzerland; University of Basel, Basel, Switzerland
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Mozun R, Belle FN, Agostini A, Baumgartner MR, Fellay J, Forrest CB, Froese DS, Giannoni E, Goetze S, Hofmann K, Latzin P, Lauener R, Martin Necker A, Ormond K, Pachlopnik Schmid J, Pedrioli PGA, Posfay-Barbe KM, Rauch A, M Schulzke S, Stocker M, Spycher BD, Vayena E, Welzel T, Zamboni N, Vogt JE, Schlapbach LJ, Bielicki JA, Kuehni CE. Paediatric Personalized Research Network Switzerland (SwissPedHealth): a joint paediatric national data stream. BMJ Open 2024; 14:e091884. [PMID: 39725440 PMCID: PMC11683899 DOI: 10.1136/bmjopen-2024-091884] [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: 07/31/2024] [Accepted: 11/29/2024] [Indexed: 12/28/2024] Open
Abstract
INTRODUCTION Children represent a large and vulnerable patient group. However, the evidence base for most paediatric diagnostic and therapeutic procedures remains limited or is often inferred from adults. There is an urgency to improve paediatric healthcare provision based on real-world evidence generation. Digital transformation is a unique opportunity to shape a data-driven, agile, learning healthcare system and deliver more efficient and personalised care to children and their families. The goal of Paediatric Personalized Research Network Switzerland (SwissPedHealth) is to build a sustainable and scalable infrastructure to make routine clinical data from paediatric hospitals in Switzerland interoperable, standardised, quality-controlled, and ready for observational research, quality assurance, trials and health-policy creation. This study describes the design, aims and current achievements of SwissPedHealth. METHODS AND ANALYSIS SwissPedHealth was started in September 2022 as one of four national data streams co-funded by the Swiss Personalized Health Network (SPHN) and the Personalized Health and Related Technologies (PHRT). SwissPedHealth develops modular governance and regulatory strategies and harnesses SPHN automatisation procedures in collaboration with clinical data warehouses, the Data Coordination Center, Biomedical Information Technology Network, and other SPHN institutions and funded projects. The SwissPedHealth consortium is led by a multisite, multidisciplinary Steering Committee, incorporating patient and family representatives. The data stream contains work packages focusing on (1) governance and implementation of standardised data collection, (2) nested projects to test the feasibility of the data stream, (3) a lighthouse project that enriches the data stream by integrating multi-omics data, aiming to improve diagnoses of rare diseases and 4) engagement with families through patient and public involvement activities and bioethics interviews. ETHICS AND DISSEMINATION The health database regulation of SwissPedHealth was approved by the ethics committee (AO_2022-00018). Research findings will be disseminated through national and international conferences and publications in peer-reviewed journals, and in lay language via online media and podcasts.
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Affiliation(s)
- Rebeca Mozun
- Department of Intensive Care and Neonatology and Children's Research Center, University Children's Hospital Zürich, Zurich, Switzerland
| | - Fabiën N Belle
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
| | - Andrea Agostini
- Department of Computer Science, Institute for Machine Learning, ETH Zurich, Zurich, Switzerland
| | - Matthias R Baumgartner
- Division of Metabolism and Children’s Research Center, University of Zurich, University Children's Hospital Zürich, Zurich, Switzerland
| | - Jacques Fellay
- School of Life Sciences, EPFL, Lausanne, Switzerland
- Biomedical Data Science Center, University of Lausanne, University Hospital of Lausanne, Lausanne, Switzerland
| | - Christopher B Forrest
- Centre for Applied Clinical Research, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - D Sean Froese
- Division of Metabolism and Children’s Research Center, University of Zurich, University Children's Hospital Zürich, Zurich, Switzerland
| | - Eric Giannoni
- Clinic of Neonatology, University of Lausanne, University Hospital of Lausanne, Lausanne, Switzerland
| | - Sandra Goetze
- PHRT Swiss Multi-Omics Centre (SMOC), ETH Zurich, Zurich, Switzerland
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland
| | - Kathrin Hofmann
- Patient and Family Advisory Committee, SwissPedHealth, Zurich, Switzerland
| | - Philipp Latzin
- Division of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, University of Bern, Inselspital University Hospital Bern, Bern, Switzerland
| | | | | | - Kelly Ormond
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Jana Pachlopnik Schmid
- Division of Immunology and Children’s Research Centre, University Children's Hospital Zürich, Zurich, Switzerland
- Faculty of Medicine, University of Zurich, Zurich, Switzerland
| | - Patrick G A Pedrioli
- PHRT Swiss Multi-Omics Centre (SMOC), ETH Zurich, Zurich, Switzerland
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - Anita Rauch
- Institute of Medical Genetics, University of Zurich, Zurich, Switzerland
| | | | | | - Ben D Spycher
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
| | - Effy Vayena
- Institute of Translational Medicine (ITM), Department of Health Sciences and Technology (D-HEST), ETH Zurich, Zurich, Switzerland
| | | | - Nicola Zamboni
- PHRT Swiss Multi-Omics Centre (SMOC), ETH Zurich, Zurich, Switzerland
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Julia E Vogt
- Department of Computer Science, Institute for Machine Learning, ETH Zurich, Zurich, Switzerland
| | - Luregn J Schlapbach
- Department of Intensive Care and Neonatology and Children's Research Center, University Children's Hospital Zürich, Zurich, Switzerland
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Julia A Bielicki
- Paediatric Research Center, UKBB, Basel, Switzerland
- Centre for Neonatal and Paediatric Infection, St George's University of London, London, UK
| | - Claudia E Kuehni
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
- Division of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, University of Bern, Inselspital University Hospital Bern, Bern, Switzerland
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Skrivankova VW, Schreck LD, Berlin C, Panczak R, Staub K, Zwahlen M, Schulzke SM, Egger M, Kuehni CE. Sociodemographic and regional differences in neonatal and infant mortality in Switzerland in 2011-2018: the Swiss National Cohort. Swiss Med Wkly 2024; 154:3682. [PMID: 39835837 DOI: 10.57187/s.3682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2025] Open
Abstract
BACKGROUND AND AIMS Despite a well-funded healthcare system with universal insurance coverage, Switzerland has one of the highest neonatal and infant mortality rates among high-income countries. Identifying avoidable risk factors targeted by evidence-based policies is a public health priority. We describe neonatal and infant mortality in Switzerland from 2011 to 2018 and explore associations with neonatal- and pregnancy-related variables, parental sociodemographic information, regional factors and socioeconomic position (SEP) using data from a long-term nationwide cohort study. METHODS We included 680,077 live births, representing 99.3% of all infants born in Switzerland between January 2011 and December 2018. We deterministically linked the national live birth register with the mortality register and with census and survey data to create a longitudinal dataset of neonatal- and pregnancy-related variables; parental sociodemographic information, such as civil status, age, religion, education, nationality; regional factors, such as urbanity, language region; and the Swiss neighbourhood index of socioeconomic position (Swiss-SEP index). Information on maternal education was available for a random subset of 242,949 infants. We investigated associations with neonatal and infant mortality by fitting multivariable Poisson regression models with robust standard errors. Several sensitivity analyses assessed the robustness of our findings. RESULTS Overall, neonatal mortality rates between 2011 and 2018 were 3.0 per 1000 live births, with regional variations: 3.2 in German-speaking, 2.4 in French-speaking and 2.1 in Italian-speaking Switzerland. For infant mortality, the rates were 3.7 per 1000 live births overall, and 3.9 in the German-speaking, 3.3 in the French-speaking and 2.9 in the Italian-speaking region. After adjusting for sex, maternal age, multiple birth and birth rank, neonatal mortality remained significantly associated with language region (adjusted rate ratio [aRR] 0.72, 95% confidence interval [CI]: 0.64-0.80 for the French-speaking region and aRR 0.66, 95% CI: 0.51-0.87 for the Italian-speaking region vs German-speaking region), with marital status (aRR 1.55, 95% CI: 1.40-1.71 for unmarried vs married), nationality (aRR 1.40, 95% CI: 1.21-1.62 for non-European Economic Area vs Swiss) and the Swiss-SEP index (aRR 1.17, 95% CI: 1.00-1.36 for lowest vs highest SEP quintile). In the subset, we showed a possible association of neonatal mortality with maternal education (aRR 1.24, 95% CI: 0.95-1.61 for compulsory vs tertiary education). CONCLUSION We provide detailed evidence about the social patterning of neonatal and infant mortality in Switzerland and reveal important regional differences with about 30% lower risks in French- and Italian-speaking compared with German-speaking regions. Underlying causes for such regional differences, such as cultural, lifestyle or healthcare-related factors, warrant further exploration to inform and provide an evidence base for public health policies.
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Affiliation(s)
| | - Leonie D Schreck
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Graduate School for Health Sciences, University of Bern, Bern, Switzerland
| | - Claudia Berlin
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Radoslaw Panczak
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Kaspar Staub
- Institute for Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Marcel Zwahlen
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Sven M Schulzke
- University Children's Hospital Basel, University of Basel, Basel, Switzerland
| | - Matthias Egger
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Claudia E Kuehni
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Division of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, University Hospital Bern, Bern, Switzerland
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Sprüngli-Toffel E, Studerus E, Curtis L, Conchon C, Alameda L, Bailey B, Caron C, Haase C, Gros J, Herbrecht E, Huber CG, Riecher-Rössler A, Conus P, Solida A, Armando M, Kapsaridi A, Ducommun MM, Klauser P, Plessen KJ, Urben S, Edan A, Nanzer N, Navarro AL, Schneider M, Genoud D, Michel C, Kindler J, Kaess M, Oliver D, Fusar-Poli P, Borgwardt S, Andreou C. Individualized pretest risk estimates to guide treatment decisions in patients with clinical high risk for psychotic disorders. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2024:S2950-2853(24)00052-8. [PMID: 39303874 DOI: 10.1016/j.sjpmh.2024.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/30/2024] [Accepted: 09/12/2024] [Indexed: 09/22/2024]
Abstract
INTRODUCTION Clinical high risk for psychosis (CHR) states are associated with an increased risk of transition to psychosis. However, the predictive value of CHR screening interviews is dependent on pretest risk enrichment in referred patients. This poses a major obstacle to CHR outreach campaigns since they invariably lead to risk dilution through enhanced awareness. A potential compensatory strategy is to use estimates of individual pretest risk as a 'gatekeeper' for specialized assessment. We aimed to test a risk stratification model previously developed in London, UK (OASIS) and to train a new predictive model for the Swiss population. METHOD The sample was composed of 513 individuals referred for CHR assessment from six Swiss early psychosis detection services. Sociodemographic variables available at referral were used as predictors whereas the outcome variable was transition to psychosis. RESULTS Replication of the risk stratification model developed in OASIS resulted in poor performance (Harrel's c=0.51). Retraining resulted in moderate discrimination (Harrel's c=0.67) which significantly differentiated between different risk groups. The lowest risk group had a cumulative transition incidence of 6.4% (CI: 0-23.1%) over two years. CONCLUSION Failure to replicate the OASIS risk stratification model might reflect differences in the public health care systems and referral structures between Switzerland and London. Retraining resulted in a model with adequate discrimination performance. The developed model in combination with CHR assessment result, might be useful for identifying individuals with high pretest risk, who might benefit most from specialized intervention.
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Affiliation(s)
- Elodie Sprüngli-Toffel
- General Psychiatry Service, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland; Department of Psychiatry, University of Geneva, Geneva, Switzerland.
| | - Erich Studerus
- Institute for Information Systems, University of Applied Sciences and Arts Northwestern Switzerland, Basel, Switzerland
| | - Logos Curtis
- Department of Psychiatry, University of Geneva, Geneva, Switzerland; Department of Adult Psychiatry, Department of Psychiatry, Geneva University Hospital, University of Geneva, Geneva, Switzerland
| | - Caroline Conchon
- General Psychiatry Service, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Luis Alameda
- General Psychiatry Service, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland; King's College of London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom; Centro Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Instituto de Biomedicina de Sevilla (IBIS), Hospital Universitario Virgen del Rocio, Departamento de Psiquiatria, Universidad de Sevilla, Sevilla, Spain
| | - Barbara Bailey
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | - Camille Caron
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | - Carmina Haase
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | - Julia Gros
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | - Evelyn Herbrecht
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | - Christian G Huber
- University Psychiatric Clinics (UPK) Basel, University of Basel, Basel, Switzerland
| | | | - Philippe Conus
- General Psychiatry Service, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland
| | - Alessandra Solida
- General Psychiatry Service, Lausanne University Hospital (CHUV), University of Lausanne, Lausanne, Switzerland; Center of Psychiatry of Neuchâtel (CNP), Neuchâtel, Switzerland
| | - Marco Armando
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Afroditi Kapsaridi
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Mathieu Mercapide Ducommun
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Paul Klauser
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland; Center for Psychiatric Neuroscience, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Kerstin Jessica Plessen
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Sébastien Urben
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Anne Edan
- Child and Adolescent Psychiatric Service, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | - Nathalie Nanzer
- Child and Adolescent Psychiatric Service, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | | | - Maude Schneider
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Davina Genoud
- Division of Child and Adolescent Psychiatry, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Dominic Oliver
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Paolo Fusar-Poli
- King's College of London, Institute of Psychiatry, Psychology and Neuroscience, London, United Kingdom; OASIS Service, South London and the Maudsley NHS Foundation Trust, London, United Kingdom; Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy; Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University Munich, Munich, Germany
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, Translational Psychiatry Unit, University of Lübeck, Lübeck, Germany
| | - Christina Andreou
- Department of Psychiatry and Psychotherapy, Translational Psychiatry Unit, University of Lübeck, Lübeck, Germany
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Auderset D, Amiguet M, Clair C, Riou J, Pittet V, Schwarz J, Mueller Y. Gender/Sex Disparities in the COVID-19 Cascade From Testing to Mortality: An Intersectional Analysis of Swiss Surveillance Data. Int J Public Health 2024; 69:1607063. [PMID: 38835806 PMCID: PMC11148283 DOI: 10.3389/ijph.2024.1607063] [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: 01/08/2024] [Accepted: 05/10/2024] [Indexed: 06/06/2024] Open
Abstract
Objectives This study investigates gender and sex disparities in COVID-19 epidemiology in the Canton of Vaud, Switzerland, focusing on the interplay with socioeconomic position (SEP) and age. Methods We analyzed COVID-19 surveillance data from March 2020 to June 2021, using an intersectional approach. Negative binomial regression models assessed disparities between women and men, across SEP quintiles and age groups, in testing, positivity, hospitalizations, ICU admissions, and mortality (Incidence Rate Ratios [IRR], with 95% Confidence Intervals [CI]). Results Women had higher testing and positivity rates than men, while men experienced more hospitalizations, ICU admissions, and deaths. The higher positivity in women under 50 was mitigated when accounting for their higher testing rates. Within SEP quintiles, gender/sex differences in testing and positivity were not significant. In the lowest quintile, women's mortality risk was 68% lower (Q1: IRR 0.32, CI 0.20-0.52), with decreasing disparities with increasing SEP quintiles (Q5: IRR 0.66, CI 0.41-1.06). Conclusion Our findings underscore the complex epidemiological patterns of COVID-19, shaped by the interactions of gender/sex, SEP, and age, highlighting the need for intersectional perspectives in both epidemiological research and public health strategy development.
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Affiliation(s)
- Diane Auderset
- Department of Family Medicine, University Center of General Medicine and Public Health, Lausanne, Switzerland
| | - Michaël Amiguet
- Department of Epidemiology and Health Systems, University Center of General Medicine and Public Health, Lausanne, Switzerland
| | - Carole Clair
- Department of Ambulatory Care, University Center of General Medicine and Public Health, Lausanne, Switzerland
| | - Julien Riou
- Department of Epidemiology and Health Systems, University Center of General Medicine and Public Health, Lausanne, Switzerland
| | - Valérie Pittet
- Department of Epidemiology and Health Systems, University Center of General Medicine and Public Health, Lausanne, Switzerland
| | - Joelle Schwarz
- Department of Ambulatory Care, University Center of General Medicine and Public Health, Lausanne, Switzerland
| | - Yolanda Mueller
- Department of Family Medicine, University Center of General Medicine and Public Health, Lausanne, Switzerland
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Riou J, Panczak R, Konstantinoudis G, Egger M. Area-level excess mortality in times of COVID-19 in Switzerland: geographical, socioeconomic and political determinants. Eur J Public Health 2024; 34:415-417. [PMID: 38268201 PMCID: PMC10990508 DOI: 10.1093/eurpub/ckad230] [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] [Indexed: 01/26/2024] Open
Abstract
The coronavirus disease 2019 (COVID-19)-related excess mortality in Switzerland is well documented, but no study examined mortality at the small-area level. We analysed excess mortality in 2020 for 2141 Swiss municipalities using a Bayesian spatiotemporal model fitted to 2011-19 data. Areas most affected included the Ticino, the Romandie and the Northeast. Rural areas, municipalities within cross-border labour markets, of lower socioeconomic position and with less support for control measures in the popular vote on the COVID-19 Act had greater excess mortality. Particularly vulnerable municipalities require special efforts to mitigate the impact of pandemics.
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Affiliation(s)
- Julien Riou
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Radoslaw Panczak
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Garyfallos Konstantinoudis
- Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Matthias Egger
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
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7
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Le Vu M, Matthes KL, Brabec M, Riou J, Skrivankova VW, Hösli I, Rohrmann S, Staub K. Health of singleton neonates in Switzerland through time and crises: a cross-sectional study at the population level, 2007-2022. BMC Pregnancy Childbirth 2024; 24:218. [PMID: 38528502 DOI: 10.1186/s12884-024-06414-1] [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: 12/21/2023] [Accepted: 03/12/2024] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND Being exposed to crises during pregnancy can affect maternal health through stress exposure, which can in return impact neonatal health. We investigated temporal trends in neonatal outcomes in Switzerland between 2007 and 2022 and their variations depending on exposure to the economic crisis of 2008, the flu pandemic of 2009, heatwaves (2015 and 2018) and the COVID-19 pandemic. METHODS Using individual cross-sectional data encompassing all births occurring in Switzerland at the monthly level (2007-2022), we analysed changes in birth weight and in the rates of preterm birth (PTB) and stillbirth through time with generalized additive models. We assessed whether the intensity or length of crisis exposure was associated with variations in these outcomes. Furthermore, we explored effects of exposure depending on trimesters of pregnancy. RESULTS Over 1.2 million singleton births were included in our analyses. While birth weight and the rate of stillbirth have remained stable since 2007, the rate of PTB has declined by one percentage point. Exposure to the crises led to different results, but effect sizes were overall small. Exposure to COVID-19, irrespective of the pregnancy trimester, was associated with a higher birth weight (+12 grams [95% confidence interval (CI) 5.5 to 17.9 grams]). Being exposed to COVID-19 during the last trimester was associated with an increased risk of stillbirth (odds ratio 1.24 [95%CI 1.02 to 1.50]). Exposure to the 2008 economic crisis during pregnancy was not associated with any changes in neonatal health outcomes, while heatwave effect was difficult to interpret. CONCLUSION Overall, maternal and neonatal health demonstrated resilience to the economic crisis and to the COVID-19 pandemic in a high-income country like Switzerland. However, the effect of exposure to the COVID-19 pandemic is dual, and the negative impact of maternal infection on pregnancy is well-documented. Stress exposure and economic constraint may also have had adverse effects among the most vulnerable subgroups of Switzerland. To investigate better the impact of heatwave exposure on neonatal health, weekly or daily-level data is needed, instead of monthly-level data.
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Affiliation(s)
- Mathilde Le Vu
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Katarina L Matthes
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Marek Brabec
- Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
| | - Julien Riou
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Veronika W Skrivankova
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland
| | - Irene Hösli
- Department of Obstetrics and Gynaecology, University Hospital of Basel, Basel, Switzerland
| | - Sabine Rohrmann
- Epidemiology, Biostatistics, and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Kaspar Staub
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland.
- Swiss School of Public Health (SSPH+), Zurich, Switzerland.
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Held U, Forzy T, Signorell A, Deforth M, Burgstaller JM, Wertli MM. Development and internal validation of a prediction model for long-term opioid use-an analysis of insurance claims data. Pain 2024; 165:44-53. [PMID: 37782553 PMCID: PMC10723645 DOI: 10.1097/j.pain.0000000000003023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 10/04/2023]
Abstract
ABSTRACT In the United States, a public-health crisis of opioid overuse has been observed, and in Europe, prescriptions of opioids are strongly increasing over time. The objective was to develop and validate a multivariable prognostic model to be used at the beginning of an opioid prescription episode, aiming to identify individual patients at high risk for long-term opioid use based on routinely collected data. Predictors including demographics, comorbid diseases, comedication, morphine dose at episode initiation, and prescription practice were collected. The primary outcome was long-term opioid use, defined as opioid use of either >90 days duration and ≥10 claims or >120 days, independent of the number of claims. Traditional generalized linear statistical regression models and machine learning approaches were applied. The area under the curve, calibration plots, and the scaled Brier score assessed model performance. More than four hundred thousand opioid episodes were included. The final risk prediction model had an area under the curve of 0.927 (95% confidence interval 0.924-0.931) in the validation set, and this model had a scaled Brier score of 48.5%. Using a threshold of 10% predicted probability to identify patients at high risk, the overall accuracy of this risk prediction model was 81.6% (95% confidence interval 81.2% to 82.0%). Our study demonstrated that long-term opioid use can be predicted at the initiation of an opioid prescription episode, with satisfactory accuracy using data routinely collected at a large health insurance company. Traditional statistical methods resulted in higher discriminative ability and similarly good calibration as compared with machine learning approaches.
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Affiliation(s)
- Ulrike Held
- Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Tom Forzy
- Master Program Statistics, ETH Zurich, Zurich, Switzerland
| | - Andri Signorell
- Department of Health Sciences, Helsana, Dübendorf, Switzerland
| | - Manja Deforth
- Department of Biostatistics at Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Jakob M. Burgstaller
- Institute of Primary Care, University and University Hospital Zurich, Zurich, Switzerland
| | - Maria M. Wertli
- Department of Internal Medicine, Cantonal Hospital Baden KSB, Baden, Switzerland
- Department of General Internal Medicine University Hospital Bern, University of Bern, Switzerland
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