Influence of calendar period on the association between BMI and coronary heart disease: A meta-analysis of 31 cohorts§


  • BMI-CHD collaboration investigators and study sites: Australian National Heart Foundation Risk Factor Prevalence Study: T Welborn; Busselton Health Study: M Knuiman, School of Population Health, The University of Western Australia, Nedlands, Australia; Caerphilly Prospective Study: JWG Yarnell and Y Ben-Shlomo, Dept of Epidemiology and Public Health, The Queen's University of Belfast, Institute of Clinical Science, Royal Victoria Hospital, N Ireland, United Kingdom; Dubbo Study of Australian Elderly: LA Simons MD FRACP, University of New South Wales Lipid Research Department, St Vincent's Hospital, Sydney, Australia; Finnish Mobile Clinic Health Examination Survey: P Knekt, Department of Health and Functional Capacity, National Public Health Institute, Helsinki, Finland; Finnish Twin Cohort Study: J Kaprio, Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Fletcher Challenge: S MacMahon, R Norton, M Woodward, The George Institute, University of Sydney, Australia; R Jackson, University of Auckland, New Zealand; Iowa Women's Health Study: AR Folsom and CP Hong, Division of Epidemiology, University of Minnesota, School of Public Health, Minneapolis, MN, USA; Kuopio Ischaemic Heart Disease Risk Factor Study: HM Lakka, Department of Public Health and Clinical Nutrition, University of Kuopio, Kuopio, Finland; Malmö Preventive Project: S Calling and B Hedblad, Dept of Clinical Sciences in Malmö, Epidemiological Research Group, Lund University, Malmö University Hospital, Malmö, Sweden; Manresa Catalonia Study: L Tomas-Abadal, Departamento de Cardiología, Hospital de Sant Pau, Barcelona; Melbourne Collaborative Cohort Study: GG Giles, Cancer Epidemiology Center, The Cancer Council Victoria, Melbourne, Australia; Multifactor Primary Prevention Study (MPPS) Göteborg: A Rosengren, Department of Medicine, Sahlgrenska University Hospital/Östra, Göteborg, Sweden; NHANES I Epidemiologic Follow-up Study: RJ Thorpe, Jr, The Johns Hopkins Medical Institutions, Baltimore, MD, USA; Nijmegen Cohort Study: JC Bakx, Department of General Practice, University Medical Center St Radboud Nijmegen, Nijmegen, The Netherlands; Norwegian Counties: B H Strand, Norwegian Institute of Public Health, Division of Epidemiology, Oslo, Norway; Nurses' Health Study: FB Hu, RM van Dam, Department of Nutrition, Harvard School of Public Health, Boston MA, USA; Perth Cohort: K Jamrozik, School of Population Health, The University of Queensland, Herston, Australia; MS Hobbs, School of Population Health, University of Western Australia, Australia; PRIME Study: P Ducimetiere, INSERM Unit 258: Cardiovascular and Metabolic Epidemiology, Villejuif Cedex, France; Scottish Heart Health Study: H Tunstall-Pedoe, M Woodward, Cardiovascular Epidemiology Unit, Ninewells Hospital & Medical School, Dundee, Scotland, UK; SENECA: CPGM de Groot, WA van Staveren, Division of Human Nutrition, Wageningen University, The Netherlands; Swedish Annual Level-of-Living Survey (SALLS): S-E Johansson, Centrum för Allmänmedicin (Center for Family Medicine), Karolinska Institutet, Huddinge, Sweden; US Railroad Cohort, Rome Railroad Cohort, and Italian Rural Areas of the Seven Countries Study; Gubbio Population Study; ECCIS Study: A Menotti, Associazione per la Ricerca Cardiologica (Association for Cardiac Research), Rome, Italy; Ventimiglia di Sicilia Heart Study (VHS): Carlo M. Barbagallo, Dipartimento di Medicina Clinica e Patologie Emergenti, Università degli Studi di Palermo, Palermo, Italy; Western Australian Abdominal Aortic Aneurysm Study: PE Norman, School of Surgery and Pathology, University of Western Australia, Australia; K Jamrozik, University of Queensland, Australia; Whitehall Study: MJ Shipley, Dept of Epidemiology and Public Health, University College London, London, UK; Zutphen Elderly Study: D Kromhout, Department of Human Nutrition, University of Wageningen, Wageningen, the Netherlands, IEJ Milder, Center for Prevention and Health Services Research, National Institute of Public Health and the Environment, Bilthoven, The Netherlands.

  • Disclosures: The funders did not have any say in any aspects of the study, and the responsible scientist had full scientific independence. No conflicts of interest were declared.

  • §

    Funding agencies: Analysis of the Finnish Twin Cohort data was part of the GENOMEUTWIN project which is supported by the European Union Contract No. QLG2-CT-2002-01254. M.J.S. is supported by the British Heart Foundation.



The association between obesity and coronary heart disease (CHD) may have changed over time, for example due to improved pharmacological treatment of CHD risk factors. This meta-analysis of 31 prospective cohort studies explores the influence of calendar period on CHD risk associated with body mass index (BMI).

Design and Methods:

The relative risks (RRs) of CHD for a five-BMI-unit increment and BMI categories were pooled by means of random effects models. Meta-regression analysis was used to examine the influence of calendar period (>1985 v ≤1985) in univariate and multivariate analyses (including mean population age as a covariate).


The age, sex, and smoking adjusted RR (95% confidence intervals) of CHD for a five-BMI-unit increment was 1.28(1.22:1.34). For underweight, overweight and obesity, the RRs (compared to normal weight) were 1.11(0.91:1.36), 1.31(1.22:1.41), and 1.78(1.55:2.04), respectively. The univariate analysis indicated 31% (95%CI: −56:0) lower RR of CHD associated with a five-BMI-unit increment and a 51% (95%CI: −78: −14)) lower RR associated with obesity in studies starting after 1985 (n = 15 and 10, respectively) compared to studies starting in or before 1985 (n = 16 and 10). However, in the multivariate analysis, only mean population age was independently associated with the RRs for a five-BMI-unit increment and obesity (−29(95%CI: −55: −5)) and −31(95%CI: −66:3), respectively) per 10-year increment in mean age).


This study provides no consistent evidence for a difference in the association between BMI and CHD by calendar period. The mean population age seems to be the most important factor that modifies the association between the risk of CHD and BMI, in which the RR decreases with increasing age.