Body-Mass Index and Mortality among 1.46 Million White Adults

Obstetrical & Gynecological Survey, 2009

Background The main associations of body-mass index (BMI) with overall and cause-specifi c mortality can best be assessed by long-term prospective follow-up of large numbers of people. The Prospective Studies Collaboration aimed to investigate these associations by sharing data from many studies. Methods Collaborative analyses were undertaken of baseline BMI versus mortality in 57 prospective studies with 894 576 participants, mostly in western Europe and North America (61% [n=541 452] male, mean recruitment age 46 [SD 11] years, median recruitment year 1979 [IQR 1975-85], mean BMI 25 [SD 4] kg/m²). The analyses were adjusted for age, sex, smoking status, and study. To limit reverse causality, the fi rst 5 years of follow-up were excluded, leaving 66 552 deaths of known cause during a mean of 8 (SD 6) further years of follow-up (mean age at death 67 [SD 10] years): 30 416 vascular; 2070 diabetic, renal or hepatic; 22 592 neoplastic; 3770 respiratory; 7704 other. Findings In both sexes, mortality was lowest at about 22•5-25 kg/m². Above this range, positive associations were recorded for several specifi c causes and inverse associations for none, the absolute excess risks for higher BMI and smoking were roughly additive, and each 5 kg/m² higher BMI was on average associated with about 30% higher overall mortality (hazard ratio per 5 kg/m² [HR] 1•29 [95% CI 1•27-1•32]): 40% for vascular mortality (HR 1•41 [1•37-1•45]); 60-120% for diabetic, renal, and hepatic mortality (HRs 2•16 [1•89-2•46], 1•59 [1•27-1•99], and 1•82 [1•59-2•09], respectively); 10% for neoplastic mortality (HR 1•10 [1•06-1•15]); and 20% for respiratory and for all other mortality (HRs 1•20 [1•07-1•34] and 1•20 [1•16-1•25], respectively). Below the range 22•5-25 kg/m², BMI was associated inversely with overall mortality, mainly because of strong inverse associations with respiratory disease and lung cancer. These inverse associations were much stronger for smokers than for non-smokers, despite cigarette consumption per smoker varying little with BMI. Interpretation Although other anthropometric measures (eg, waist circumference, waist-to-hip ratio) could well add extra information to BMI, and BMI to them, BMI is in itself a strong predictor of overall mortality both above and below the apparent optimum of about 22•5-25 kg/m². The progressive excess mortality above this range is due mainly to vascular disease and is probably largely causal. At 30-35 kg/m², median survival is reduced by 2-4 years; at 40-45 kg/m², it is reduced by 8-10 years (which is comparable with the eff ects of smoking). The defi nite excess mortality below 22•5 kg/m² is due mainly to smoking-related diseases, and is not fully explained.

Int. J. Obes., 2009

Objectives: To study total mortality in different categories of BMI values, with adjustments for important covariates in a population-based 26-year mortality follow-up. Special interest will be given to gender differences and low BMI values. Methods: From a stratified sample in 1969 of 32 185 individuals aged 18-64 years from Stockholm County, 2422 underwent a health examination, with complete data obtained for 1020 subjects. BMI was classified as underweight (o20), normal (20-24.9), overweight (25-29.9) or obesity (X30). Participants were followed up in the National Cause of Death Register until the end of 1996. Multivariate analysis was performed by Cox regression for men and women separately, with different models, with step-wise adjustment for age, care need category, heart rate, hypertension, blood glucose, alcohol intake and smoking, with hazard ratios (HR) and 95% confidence interval (CI) and with normal weight as reference. Results: Among men, the age-adjusted HR was 1.68 (95% CI 1.10-2.57) for underweight and 1.62 (95% CI 1.08-2.43) for obesity, and among women it was 0.93 (95% CI 0.58-1.51) for underweight and 1.88 (95% CI 1.26-2.82) for obesity. In men, the significantly increased mortality remained when also adjusting for care need category, but not when adjusting for other factors, whereas the opposite was found regarding obesity. For women, underweight was significantly associated with decreased mortality when adjusting for smoking and for all factors together, whereas obesity was associated with increased mortality when adjusting for the different factors except for all factors together. Conclusions: Underweight was associated with higher mortality among men, but not when adjusting for covariates, whereas underweight was associated with lower mortality among women when adjusting for smoking.

International journal of obesity (2005), 2006

To investigate whether the nature of the relationship between body mass index (BMI (kg/m2)) and all-cause mortality is direct, J- or U-shaped, and whether this relationship changes as people age. Prospective nationwide cohort study of US radiologic technologists (USRT). Sixty-four thousand seven hundred and thirty-three female and 19 011 male certified radiation technologists. We prospectively followed participants from the USRT study who completed a mail survey in 1983-1989 through 2000. During an average of 14.7 years of follow-up or 1.23 million person-years, 2278 women and 1495 men died. Using Cox's proportional-hazards regression analyses, we analyzed the relationship between BMI and all-cause mortality by gender and by age group (<55 years; > or = 55 years). We also examined risk in never-smokers after the first 5 years of follow-up to limit bias owing to the confounding effects of smoking and illness-related weight loss on BMI and mortality. Risks were generally J-s...

Obesity, 2010

PLoS ONE, 2014

Background: High Body-Mass-Index (BMI) is associated with increased all-cause mortality, but little is known about the effect of short-and long-term BMI change on mortality. The aim of the study was to determine how long-term weight change affects mortality.

Journal of Clinical Epidemiology, 1990

The association between body mass index (BMI) and mortaliy was investigated in 2453 black male (aged 30-79 years) and 273 1 black female (aged 40-79 years) members of the Kaiser Foundation Health Plan. During a 15year follow-up 393 male and 283 female deaths were identified. Analyses were conducted separately in a lower and an upper range of BMI (as well as over the entire range), to isolate separate effects of low weight and high weight on mortality. Particular attention was also paid to potential bias from cigarette smoking and antecedent illness.

American Journal of Epidemiology, 1998

In this paper, the authors model the nonmonotonic relation between body mass index (BMI) (weight (kgyheight 2 (m 2 )) and mortality in 13,242 black and white participants in the NHANES I Epidemiologic Follow-up Study in order to estimate the BMI at which minimum mortality occurs. The BMI of minimum mortality was 27.1 for black men (95% confidence interval (Cl) 24.8-29.4), 26.8 for black women (95% Cl 24.7-28.9), 24.8 for white men (95% Cl 23.8-25.9), and 24.3 for white women (95% Cl 23.3-25.4). Each confidence interval included the group average. Analyses conducted by smoking status and after exclusion of persons with baseline illness and persons who died during the first 4 years of follow-up led to virtually identical estimates. The authors determined the range of values over which risk of all-cause mortality would increase no more than 20% in comparison with the minimum. This interval was nine BMI units wide, and it included 70% of the population. These results were confirmed by parallel analyses using quantlles. The model used allowed the estimation of parameters in the BMI-mortaltty relation. The resulting empirical findings from each of four race/sex groups, which are representative of the US population, demonstrate a wide range of BMIs consistent with minimum mortality and do not suggest that the optimal BMI is at the lower end of the distribution for any subgroup. Am J Epidemiol 1998; 147:739-49. body mass index; mortality; obesity Downloaded from * Age-adjusted mortality rates vwre obtained by the direct method, with 10-year strata of the entire saxVracespecrfic cohort used as reference groups.

operated 7 public hospitals and affiliated clinics in Louisiana that provided quality medical care to the residents of Background-Several prospective studies have evaluated the association between body mass index (BMI) and death risk among patients with diabetes mellitus; however, the results have been inconsistent. Methods and Results-We performed a prospective cohort study of 19 478 black and 15 354 white patients with type 2 diabetes mellitus. Cox proportional hazards regression models were used to estimate the association of different levels of BMI stratification with all-cause mortality. During a mean follow-up of 8.7 years, 4042 deaths were identified. The multivariable-adjusted (age, sex, smoking, income, and type of insurance) hazard ratios for all-cause mortality associated with BMI levels (18.5-22.9, 23-24.9, 25-29.9, 30-34.9 [reference group], 35-39.9, and ≥40 kg/m 2 ) at baseline were 2.12 (95% confidence interval [CI], 1.80-2.49), 1.74 (95% CI, 1.46-2.07), 1.23 (95% CI, 1.08-1.41), 1.00, 1.19 (95% CI, 1.03-1.39), and 1.23 (95% CI, 1.05-1.43) for blacks and 1.70 (95% CI, 1.42-2.04), 1.51 (95% CI, 1.27-1.80), 1.07 (95% CI, 0.94-1.21), 1.00, 1.07 (95% CI, 0.93-1.23), and 1.20 (95% CI, 1.05-1.38) for whites, respectively. When stratified by age, smoking status, patient type, or the use of antidiabetic drugs, a U-shaped association was still present. When BMI was included in the Cox model as a time-dependent variable, the U-shaped association of BMI with all-cause mortality risk did not change. Conclusions-The present study indicated a U-shaped association of BMI with all-cause mortality risk among black and white patients with type 2 diabetes mellitus. A significantly increased risk of all-cause mortality was observed among blacks with BMI <30 kg/m 2 and ≥35 kg/m 2 and among whites with BMI <25 kg/m 2 and ≥40 kg/m 2 compared with patients with BMI of 30 to 34.9 kg/m 2 . (Circulation. 2014;130:2143-2151.) ; and LSU Health Baton Rouge, Baton Rouge, LA (J.J.). The online-only Data Supplement is available with this article at http://circ.ahajournals.org/lookup/suppl/

Lancet (London, England), 2016

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. 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-&lt;25·0 kg/m(2). 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-&lt;22·5 kg/m(2); 1·00, 0·99-1·01 for BMI 22·5-&lt;25·0 kg/m(2)), and increased significantly...

Obesity, 2016

Objective: To determine the risk of mortality associated with and quantify the deaths attributable to combinations of body mass index (BMI) and waist circumference (WC). Methods: This study included 41,439 participants. For the hazard ratio (HR) calculation, adiposity categories were defined as: BMI N /WC N , BMI N /WC O , BMI O /WC N , and BMI O /WC O (N 5 non-obese, O 5 obese). For the population attributable fraction analysis, obesity was classified as: (i) obese by BMI and/or WC; (ii) obese by BMI; and (iii) obese by WC. Mortality data was complete to the end of 2012. Results: The prevalence of BMI N /WC N , BMI N /WC O , BMI O /WC N , and BMI O /WC O was 73%, 6%, 6%, and 15%, respectively. There was an increased risk of all-cause and cardiovascular disease (CVD) mortality in those with BMI N /WC O (HR (95% CI) 1.2 (1.2, 1.3) and 1.3 (1.1, 1.6)) and BMI O /WC O (1.3 (1.3, 1.4) and 1.7 (1.5, 1.9)) compared to those with BMI N /WC N. The estimated proportion of all-cause and CVD mortality attributable to obesity defined using WC or using BMI and/or WC was higher compared to obesity defined using BMI. Conclusions: Current population obesity monitoring misses those with BMI N /WC O who are at increased risk of mortality. By targeting reductions in population WC, the potential exists to prevent more deaths in the population than if we continue to target reductions in BMI alone.