Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe.

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Abstract

Although overweight and obesity have been studied in relation to individual cardiometabolic diseases, their association with risk of cardiometabolic multimorbidity is poorly understood. Here we aimed to establish the risk of incident cardiometabolic multimorbidity (ie, at least two from: type 2 diabetes, coronary heart disease, and stroke) in adults who are overweight and obese compared with those who are a healthy weight.

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Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.

Salim Yusuf, Steven Hawken, Stephanie Ounpuu … (2004)

Although more than 80% of the global burden of cardiovascular disease occurs in low-income and middle-income countries, knowledge of the importance of risk factors is largely derived from developed countries. Therefore, the effect of such factors on risk of coronary heart disease in most regions of the world is unknown. We established a standardised case-control study of acute myocardial infarction in 52 countries, representing every inhabited continent. 15152 cases and 14820 controls were enrolled. The relation of smoking, history of hypertension or diabetes, waist/hip ratio, dietary patterns, physical activity, consumption of alcohol, blood apolipoproteins (Apo), and psychosocial factors to myocardial infarction are reported here. Odds ratios and their 99% CIs for the association of risk factors to myocardial infarction and their population attributable risks (PAR) were calculated. Smoking (odds ratio 2.87 for current vs never, PAR 35.7% for current and former vs never), raised ApoB/ApoA1 ratio (3.25 for top vs lowest quintile, PAR 49.2% for top four quintiles vs lowest quintile), history of hypertension (1.91, PAR 17.9%), diabetes (2.37, PAR 9.9%), abdominal obesity (1.12 for top vs lowest tertile and 1.62 for middle vs lowest tertile, PAR 20.1% for top two tertiles vs lowest tertile), psychosocial factors (2.67, PAR 32.5%), daily consumption of fruits and vegetables (0.70, PAR 13.7% for lack of daily consumption), regular alcohol consumption (0.91, PAR 6.7%), and regular physical activity (0.86, PAR 12.2%), were all significantly related to acute myocardial infarction (p<0.0001 for all risk factors and p=0.03 for alcohol). These associations were noted in men and women, old and young, and in all regions of the world. Collectively, these nine risk factors accounted for 90% of the PAR in men and 94% in women. Abnormal lipids, smoking, hypertension, diabetes, abdominal obesity, psychosocial factors, consumption of fruits, vegetables, and alcohol, and regular physical activity account for most of the risk of myocardial infarction worldwide in both sexes and at all ages in all regions. This finding suggests that approaches to prevention can be based on similar principles worldwide and have the potential to prevent most premature cases of myocardial infarction.

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Type 2 diabetes.

Melanie Davies, Sudesna Chatterjee, Kamlesh Khunti (2017)

415 million people live with diabetes worldwide, and an estimated 193 million people have undiagnosed diabetes. Type 2 diabetes accounts for more than 90% of patients with diabetes and leads to microvascular and macrovascular complications that cause profound psychological and physical distress to both patients and carers and put a huge burden on health-care systems. Despite increasing knowledge regarding risk factors for type 2 diabetes and evidence for successful prevention programmes, the incidence and prevalence of the disease continues to rise globally. Early detection through screening programmes and the availability of safe and effective therapies reduces morbidity and mortality by preventing or delaying complications. Increased understanding of specific diabetes phenotypes and genotypes might result in more specific and tailored management of patients with type 2 diabetes, as has been shown in patients with maturity onset diabetes of the young. In this Seminar, we describe recent developments in the diagnosis and management of type 2 diabetes, existing controversies, and future directions of care.

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Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents

Neil Murphy, George Davey Smith (2017)

Summary Background Overweight and obesity are increasing worldwide. To help assess their relevance to mortality in different populations we conducted individual-participant data meta-analyses of prospective studies of body-mass index (BMI), limiting confounding and reverse causality by restricting analyses to never-smokers and excluding pre-existing disease and the first 5 years of follow-up. Methods Of 10 625 411 participants in Asia, Australia and New Zealand, Europe, and North America from 239 prospective studies (median follow-up 13·7 years, IQR 11·4–14·7), 3 951 455 people in 189 studies were never-smokers without chronic diseases at recruitment who survived 5 years, of whom 385 879 died. The primary analyses are of these deaths, and study, age, and sex adjusted hazard ratios (HRs), relative to BMI 22·5–<25·0 kg/m2. Findings All-cause mortality was minimal at 20·0–25·0 kg/m2 (HR 1·00, 95% CI 0·98–1·02 for BMI 20·0–<22·5 kg/m2; 1·00, 0·99–1·01 for BMI 22·5–<25·0 kg/m2), and increased significantly both just below this range (1·13, 1·09–1·17 for BMI 18·5–<20·0 kg/m2; 1·51, 1·43–1·59 for BMI 15·0–<18·5) and throughout the overweight range (1·07, 1·07–1·08 for BMI 25·0–<27·5 kg/m2; 1·20, 1·18–1·22 for BMI 27·5–<30·0 kg/m2). The HR for obesity grade 1 (BMI 30·0–<35·0 kg/m2) was 1·45, 95% CI 1·41–1·48; the HR for obesity grade 2 (35·0–<40·0 kg/m2) was 1·94, 1·87–2·01; and the HR for obesity grade 3 (40·0–<60·0 kg/m2) was 2·76, 2·60–2·92. For BMI over 25·0 kg/m2, mortality increased approximately log-linearly with BMI; the HR per 5 kg/m2 units higher BMI was 1·39 (1·34–1·43) in Europe, 1·29 (1·26–1·32) in North America, 1·39 (1·34–1·44) in east Asia, and 1·31 (1·27–1·35) in Australia and New Zealand. This HR per 5 kg/m2 units higher BMI (for BMI over 25 kg/m2) was greater in younger than older people (1·52, 95% CI 1·47–1·56, for BMI measured at 35–49 years vs 1·21, 1·17–1·25, for BMI measured at 70–89 years; pheterogeneity<0·0001), greater in men than women (1·51, 1·46–1·56, vs 1·30, 1·26–1·33; pheterogeneity<0·0001), but similar in studies with self-reported and measured BMI. Interpretation The associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents. This finding supports strategies to combat the entire spectrum of excess adiposity in many populations. Funding UK Medical Research Council, British Heart Foundation, National Institute for Health Research, US National Institutes of Health.

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Journal ID (iso-abbrev): Lancet Public Health

Title: The Lancet. Public health

Publisher: Elsevier BV

ISSN: 2468-2667

Publication date (Electronic): Jun 2017

Volume: 2

Issue: 6

Affiliations

[1 ] Department of Epidemiology and Public Health, University College London, London, UK; Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Finnish Institute of Occupational Health, Helsinki, Finland. Electronic address: m.kivimaki@ucl.ac.uk.

[2 ] Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

[3 ] Department of Epidemiology and Public Health, University College London, London, UK; School of Social and Community Medicine, University of Bristol, Bristol, UK.

[4 ] Centre for Occupational and Environmental Medicine, Stockholm County Council, Sweden; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

[5 ] Department of Epidemiology and Public Health, University College London, London, UK.

[6 ] Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Stress Research Institute, Stockholm University, Stockholm, Sweden; School of Health Sciences, Jönköping University, Jönköping, Sweden.

[7 ] Inserm UMS 011, Population-Based Epidemiological Cohorts Unit, Villejuif, France.

[8 ] Department of Health Sciences, Mid Sweden University, Sundsvall, Sweden.

[9 ] Department of Public Health, University of Helsinki, Helsinki, Finland.

[10 ] Stress Research Institute, Stockholm University, Stockholm, Sweden; Department of Psychology, Umeå University, Umeå, Sweden.

[11 ] Finnish Institute of Occupational Health, Helsinki, Finland.

[12 ] Department of Public Health and Department of Psychology, University of Copenhagen, Copenhagen, Denmark; National Research Centre for the Working Environment, Copenhagen, Denmark.

[13 ] Department of Epidemiology and Public Health, University College London, London, UK; Inserm U1018, Centre for Research in Epidemiology and Population Health, Villejuif, France.

[14 ] Department of Public Health, University of Turku, Turku, Finland; Folkhälsan Research Center, Helsinki, Finland; University of Skövde, Skövde, Sweden.

[15 ] Department of Public Health, University of Turku, Turku, Finland; Turku University Hospital, Turku, Finland.

[16 ] Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

[17 ] Stress Research Institute, Stockholm University, Stockholm, Sweden.

[18 ] Department of Epidemiology and Public Health, University College London, London, UK; National Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, UK.

[19 ] Department of Epidemiology and Public Health, University College London, London, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.

[20 ] Department of Epidemiology and Public Health, University College London, London, UK; 1st Department of Medicine, Semmelweis University Faculty of Medicine, Budapest, Hungary.

[21 ] Institute of Behavioral Sciences, University of Helsinki, Helsinki, Finland.

Article

Publisher Item ID: S2468-2667(17)30074-9

DOI: 10.1016/S2468-2667(17)30074-9

PMC ID: 5463032

PubMed ID: 28626830

SO-VID: 2ac883a9-2032-4135-bdb6-cfc3882b2cb4

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Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe.

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Most cited references 57

Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study.

Type 2 diabetes.

Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents

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Cited by 215