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

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

Men across a range of ethnicities have a higher prevalence of diabetes: findings from a cross-sectional study of 500000 UK Biobank participants

Aims: Studies show that white men have a higher prevalence of Type 2 diabetes mellitus than women at a given age and BMI, but equivalent standardized data for other ethnic groups in the UK are sparse. Methods: This cross-sectional study analysed UK Biobank data from 489 079 participants to compare the prevalence of diabetes mellitus across four major ethnic groups including: 471 700 (96.4%) white, 7871 (1.6%) South Asian, 7974 (1.6%) black and 1534 (0.3%) Chinese participants, before and after standardizing for age, socio-economic status (SES), BMI and lifestyle factors including physical activity, TV viewing, fruit and vegetable intake, processed meat, red meat, oily fish, alcohol intake and smoking. A subgroup analysis of South Asians was also undertaken. Results: Crude diabetes prevalence was higher in men across all four ethnicities. After standardizing for age, SES, BMI and lifestyle factors, a significant sex difference in diabetes prevalence persisted in white (men 6.0% vs. women 3.6%), South Asian (21.0% vs. 13.8%) and black individuals (13.3% vs. 9.7%) (P &#60; 0.0001); there was a non-significant difference between Chinese men and women (7.1% vs. 5.5%) (P = 0.211). Sex differences persisted across South Asian subgroups. Conclusions: Men across a range of major ethnic groups including white, South Asian and black, have a higher prevalence of diabetes compared with women of similar age, BMI, SES and lifestyle in the UK

Body mass index and use and costs of primary care services among women aged 55-79 years in England: a cohort and linked data study.

BACKGROUND: Excess weight is associated with poor health and increased healthcare costs. There are no reliable data describing the association between BMI and the use and costs of primary care services in the United Kingdom. METHODS: Among 69,440 participants in the Million Women Study with primary care records in the Clinical Practice Research Datalink between April 2006 (mean age 64 years) and March 2014, the annual rates and costs of their primary care consultations, prescription medications, and diagnostic and monitoring tests were estimated in relation to their self-reported body mass index (BMI) at recruitment in 1996-2001 (mean age 56 years). Associations of BMI with annual costs were projected to all women in England aged 55-79 years in 2013. RESULTS: Over an average follow-up of 6.0 years, annual rates and mean costs were lowest for women with a BMI of 20 to <22.5 kg/m2 for consultations (7.0 consultations, 99% CI 6.8-7.1; £288, £280-£295) and prescription medications (27.0 prescribed items, 26.0-27.9; £227, £216-£237). Above 20 kg/m2, a 2 kg/m2 higher BMI (a 5 kg change in weight for a woman of average height) was associated with 5.2% (4.8-5.6) and 9.9% (9.2-10.6) higher mean annual consultation and prescription medication costs, respectively. Annual rates and mean costs of diagnostic and monitoring tests were similar for women with different BMIs. Among all women aged 55-79 years in England, excess weight accounted for an estimated 11% (£229 million/£2.2 billion) of all consultation costs and 20% (£384 million/£1.9 billion) of all prescription medication costs, of which 27% were for diabetes drugs, 19% for circulatory system drugs, and 13% for analgesics. CONCLUSIONS: Excess body weight is associated with higher use and costs of primary care services among women in England. Reducing the prevalence of excess weight could improve the health of women and reduce pressures on primary care.Cancer Research UK (grant C570/A16491); Medical Research Council (grant MR/K02700X/1)

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

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/m(2). FINDINGS: All-cause mortality was minimal at 20·0-25·0 kg/m(2) (HR 1·00, 95% CI 0·98-1·02 for BMI 20·0-<22·5 kg/m(2); 1·00, 0·99-1·01 for BMI 22·5-<25·0 kg/m(2)), and increased significantly both just below this range (1·13, 1·09-1·17 for BMI 18·5-<20·0 kg/m(2); 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/m(2); 1·20, 1·18-1·22 for BMI 27·5-<30·0 kg/m(2)). The HR for obesity grade 1 (BMI 30·0-<35·0 kg/m(2)) was 1·45, 95% CI 1·41-1·48; the HR for obesity grade 2 (35·0-<40·0 kg/m(2)) was 1·94, 1·87-2·01; and the HR for obesity grade 3 (40·0-<60·0 kg/m(2)) was 2·76, 2·60-2·92. For BMI over 25·0 kg/m(2), mortality increased approximately log-linearly with BMI; the HR per 5 kg/m(2) 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/m(2) units higher BMI (for BMI over 25 kg/m(2)) 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.UK MRC, BHF, NIHR; US NIHThis is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/S0140-6736(16)30175-

European Society of Cardiology: Cardiovascular Disease Statistics 2017

Background: The European Society of Cardiology (ESC) Atlas has been compiled by the European Heart Agency to document cardiovascular disease (CVD) statistics of the 56 ESC member countries. A major aim of this 2017 data presentation has been to compare high income and middle income ESC member countries, in order to identify inequalities in disease burden, outcomes and service provision. Methods: The Atlas utilizes a variety of data sources, including the World Health Organization, the Institute for Health Metrics and Evaluation, and the World Bank to document risk factors, prevalence and mortality of cardiovascular disease and national economic indicators. It also includes novel ESC sponsored survey data of health infrastructure and cardiovascular service provision provided by the national societies of the ESC member countries. Data presentation is descriptive with no attempt to attach statistical significance to differences observed in stratified analyses. Results: Important differences were identified between the high income and middle income member countries of the ESC with regard to CVD risk factors, disease incidence and mortality. For both women and men, the age-standardised prevalence of hypertension was lower in high income countries (18.3% and 27.3%) compared with middle income countries (23.5% and 30.3%). Smoking prevalence in men (not women) was also lower (26% vs 41.3%), and together these inequalities are likely to have contributed to the higher CVD mortality in middle income countries. Declines in CVD mortality have seen cancer becoming a more common cause of death in a number of high income member countries, but in middle income countries declines in CVD mortality have been less consistent where CVD remains the leading cause of death. Inequalities in CVD mortality are emphasised by the smaller contribution they make to potential years of life lost in high income compared with middle income countries both for women (13% vs. 23%) and men (20% vs. 27%). The downward mortality trends for CVD may, however, be threatened by the emerging obesity epidemic that is seeing rates of diabetes increasing across all ESC member countries. Survey data from the National Cardiac Societies (n=41) showed that rates of cardiac catheterization and coronary artery bypass surgery, as well as the number of specialist centres required to deliver them, were greatest in the high income member countries of the ESC. The Atlas confirmed that these ESC member countries, where the facilities for the contemporary treatment of coronary disease were best developed, were often those in which declines in coronary mortality have been most pronounced. Economic resources were not the only driver for delivery of equitable cardiovascular healthcare, as some middle income ESC member countries reported rates for interventional procedures and device implantations that matched or exceeded the rates in wealthier member countries. Conclusion: In documenting national CVD statistics, the Atlas provides valuable insights into the inequalities in risk factors, healthcare delivery and outcomes of CVD across ESC member countries. The availability of these data will underpin the ESC’s ambitious mission “to reduce the burden of cardiovascular disease” not only in its member countries, but also in nation states around the world

Metabolic phenotyping of diet and dietary Intake

Nutrition provides the building blocks for growth, repair, and maintenance of the body and is key to maintaining health. Exposure to fast foods, mass production of dietary components, and wider importation of goods have challenged the balance between diet and health in recent decades, and both scientists and clinicians struggle to characterize the relationship between this changing dietary landscape and human metabolism with its consequent impact on health. Metabolic phenotyping of foods, using high-density data-generating technologies to profile the biochemical composition of foods, meals, and human samples (pre- and postfood intake), can be used to map the complex interaction between the diet and human metabolism and also to assess food quality and safety. Here, we outline some of the techniques currently used for metabolic phenotyping and describe key applications in the food sciences, ending with a broad outlook at some of the newer technologies in the field with a view to exploring their potential to address some of the critical challenges in nutritional science