Helena Marti-Soler1, Cédric Gubelmann1, Stefanie Aeschbacher2, Luis Alves3, Martin Bobak4, Vanina Bongard5, Els Clays6, Giovanni de Gaetano7, Augusto Di Castelnuovo7, Roberto Elosua8, Jean Ferrieres5, Idris Guessous9, Jannicke Igland10, Torben Jørgensen11, Yuri Nikitin12, Mark G O'Doherty13, Luigi Palmieri14, Rafel Ramos15, Judith Simons16, Gerhard Sulo10, Diego Vanuzzo17, Joan Vila8, Henrique Barros3, Anders Borglykke18, David Conen2, Dirk De Bacquer6, Chiara Donfrancesco14, Jean-Michel Gaspoz19, Simona Giampaoli14, Graham G Giles20, Licia Iacoviello7, Frank Kee13, Ruzena Kubinova21, Sofia Malyutina22, Jaume Marrugat8, Eva Prescott23, Jean Bernard Ruidavets5, Robert Scragg24, Leon A Simons25, Abdonas Tamosiunas26, Grethe S Tell10, Peter Vollenweider27, Pedro Marques-Vidal1. 1. Institute of Social and Preventive Medicine, University of Lausanne, Lausanne, Switzerland. 2. Department of Medicine, University Hospital Basel, Basel, Switzerland. 3. Department of Clinical Epidemiology, Predictive Medicine and Public Health, University of Porto Medical School, Porto, Portugal Institute of Public Health of the University of Porto, Porto, Portugal. 4. Department of Epidemiology and Public Health, University College London, London, UK. 5. Department of Epidemiology, UMR 1027- INSERM, Toulouse University-CHU Toulouse, Toulouse, France. 6. Department of Public Health, Ghent University, Ghent, Belgium. 7. Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo NEUROMED, Pozzilli (IS), Italy. 8. Cardiovascular and Genetic Epidemiology Research Group (ULEC-EGEC), Inflammatory and Cardiovascular Disease Programme (RICAD), IMIM, Barcelona, Spain. 9. Institute of Social and Preventive Medicine, University of Lausanne, Lausanne, Switzerland Department of Community Medicine, Preventive care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland. 10. Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway. 11. Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark Faculty of Health Science, University of Copenhagen, Denmark. 12. Laboratory of Internal Medicine, Institute of Internal Medicine, Siberian Branch RAMS, Novosibirsk, Russia. 13. UKCRC Centre of Excellence for Public Health, Queens University of Belfast, Belfast, UK. 14. Unit of Epidemiology of Cerebro and Cardiovascular Diseases, National Centre of Epidemiology, Surveillance and Health Promotion, Istituto Superiore di Sanità, Rome, Italy. 15. Research Unit and Docent Unit of Family Medicine Girona, Primary Care Research Institute Jordi Gol, Girona, Spain Departament of Medicine, Universitat de Girona, Girona, Spain. 16. Lipid Research Department, University of New South Wales, St Vincent's Hospital, Sydney, Australia. 17. Centro di Prevenzione Cardiovascolare, ASS 4 'Medio Friuli', Udine, Italy. 18. Research Centre for Prevention and Health, Capital Region of Denmark, Glostrup, Denmark. 19. Department of Community Medicine, Preventive care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland. 20. Cancer Epidemiology Centre, Cancer Council Victoria, Victoria, Australia. 21. Centre for Health Monitoring, National Institute of Public Health, Prague, Czech Republic. 22. Laboratory of Internal Medicine, Institute of Internal Medicine, Siberian Branch RAMS, Novosibirsk, Russia Novosibirsk State Medical University, Novosibirsk, Russia. 23. Department of Cardiology, Bispebjerg University Hospital, Copenhagen, Denmark Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen, Denmark. 24. School of Population Health, University of Auckland, Auckland, New Zealand. 25. Departament of Medicine, Universitat de Girona, Girona, Spain. 26. Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania. 27. Department of Internal Medicine, University Hospital and University of Lausanne, Lausanne, Switzerland.
Abstract
OBJECTIVE: To assess the seasonality of cardiovascular risk factors (CVRF) in a large set of population-based studies. METHODS: Cross-sectional data from 24 population-based studies from 15 countries, with a total sample size of 237 979 subjects. CVRFs included Body Mass Index (BMI) and waist circumference; systolic (SBP) and diastolic (DBP) blood pressure; total, high (HDL) and low (LDL) density lipoprotein cholesterol; triglycerides and glucose levels. Within each study, all data were adjusted for age, gender and current smoking. For blood pressure, lipids and glucose levels, further adjustments on BMI and drug treatment were performed. RESULTS: In the Northern and Southern Hemispheres, CVRFs levels tended to be higher in winter and lower in summer months. These patterns were observed for most studies. In the Northern Hemisphere, the estimated seasonal variations were 0.26 kg/m(2) for BMI, 0.6 cm for waist circumference, 2.9 mm Hg for SBP, 1.4 mm Hg for DBP, 0.02 mmol/L for triglycerides, 0.10 mmol/L for total cholesterol, 0.01 mmol/L for HDL cholesterol, 0.11 mmol/L for LDL cholesterol, and 0.07 mmol/L for glycaemia. Similar results were obtained when the analysis was restricted to studies collecting fasting blood samples. Similar seasonal variations were found for most CVRFs in the Southern Hemisphere, with the exception of waist circumference, HDL, and LDL cholesterol. CONCLUSIONS: CVRFs show a seasonal pattern characterised by higher levels in winter, and lower levels in summer. This pattern could contribute to the seasonality of CV mortality. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
OBJECTIVE: To assess the seasonality of cardiovascular risk factors (CVRF) in a large set of population-based studies. METHODS: Cross-sectional data from 24 population-based studies from 15 countries, with a total sample size of 237 979 subjects. CVRFs included Body Mass Index (BMI) and waist circumference; systolic (SBP) and diastolic (DBP) blood pressure; total, high (HDL) and low (LDL) density lipoprotein cholesterol; triglycerides and glucose levels. Within each study, all data were adjusted for age, gender and current smoking. For blood pressure, lipids and glucose levels, further adjustments on BMI and drug treatment were performed. RESULTS: In the Northern and Southern Hemispheres, CVRFs levels tended to be higher in winter and lower in summer months. These patterns were observed for most studies. In the Northern Hemisphere, the estimated seasonal variations were 0.26 kg/m(2) for BMI, 0.6 cm for waist circumference, 2.9 mm Hg for SBP, 1.4 mm Hg for DBP, 0.02 mmol/L for triglycerides, 0.10 mmol/L for total cholesterol, 0.01 mmol/L for HDL cholesterol, 0.11 mmol/L for LDL cholesterol, and 0.07 mmol/L for glycaemia. Similar results were obtained when the analysis was restricted to studies collecting fasting blood samples. Similar seasonal variations were found for most CVRFs in the Southern Hemisphere, with the exception of waist circumference, HDL, and LDL cholesterol. CONCLUSIONS: CVRFs show a seasonal pattern characterised by higher levels in winter, and lower levels in summer. This pattern could contribute to the seasonality of CV mortality. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.