Body mass index and mortality: understanding the patterns and paradoxes.
Wild SH, Byrne CD.
BMJ. 2016 May 4;353:i2433. doi: 10.1136/bmj.i2433. No abstract available.
PMID: 27146663
http://www.bmj.com/content/353/bmj.i2433People who are lean for life have the lowest mortality
The optimal body mass index (BMI) associated with lowest risk of all cause mortality is not known. As excess adiposity increases risk of conditions such as diabetes that reduce life expectancy, one might expect increasing BMI to be associated with increasing mortality. However, compared with normal weight, underweight is associated with increased mortality and modestly elevated BMI is associated with lower mortality. The former pattern is only partly explained by confounding by smoking or comorbidity, and the second observation has been called the obesity paradox.1 In addition, the influence on mortality of different patterns of weight change throughout the life course is poorly understood. Two linked papers attempt to shed light on these important subjects.2 3
Aune and colleagues (doi:10.1136/bmj.i1256) report a meta-analysis of 230 prospective studies with more than 3.74 million deaths among more than 30.3 million participants, providing further evidence that adiposity (measured by BMI) increases the risk of premature death.2 Some increase in risk was observed in lower weight participants, and in the analysis of all participants the lowest mortality was observed with a BMI of around 25. However, the lowest mortality was observed in the BMI range 23-24 among never smokers, in the BMI range 22-23 among healthy never smokers, and in the BMI range 20-22 among studies of never smokers with longer durations of follow-up (=/>20 and =/>25 years). The findings show the importance of smoking and comorbidity in confounding the association between BMI and mortality and contributing to the apparent paradox of a U shaped association.
The attenuation of the observed J shaped relation in analyses confined to never smokers with longer follow-up and the finding of the lowest mortality in the BMI range 20-22 in this group suggest that any increased mortality among never smokers with low BMI is probably a result of residual confounding from unidentified comorbidity. However, the authors were unable to investigate how changes in weight over time might influence their findings.
In a second paper (doi:10.1136/bmj.i2195), Song and colleagues used an interesting strategy to try to find out how weight trajectories from age 5 to 50 years influence all cause and cause specific mortality among adults over 60 years of age.3 Having validated an approach in an earlier study in which people were asked to identify their body shape from outline drawings of different body shapes (somatotypes),4 the investigators studied associations between changes in somatotypes over time and mortality outcomes, using data from two large US prospective cohort studies.
They identified five common patterns or weight trajectories: lean-stable, lean-moderate increase, lean-marked increase, medium-stable/increase, and heavy stable/increase. Unsurprisingly, the authors found that people who reported remaining lean throughout life had the lowest mortality and that those who reported being heavy as children and who remained heavy or gained further weight had the highest mortality. Gaining weight from childhood to age 50 was associated with increased mortality compared with people who reported remaining lean. Weight gain was more strongly associated with cardiovascular than all cause mortality, and the effect was more pronounced among never smokers than ever smokers.
The association between weight gain and cancer mortality was also stronger among never smokers than ever smokers, presumably owing to the higher proportion of obesity related cancers among non-smokers. The stronger association between weight gain and mortality among people with diabetes suggests that diabetes may act as marker of metabolically unhealthy obesity within strata of BMI with the adverse effects of hypertension, dyslipidaemia, and insulin resistance added to the adverse effects of hyperglycaemia. Such findings are a reminder that BMI by itself is an imperfect measure of adiposity.
Recall of body shape is also an imperfect measure. Correlation coefficients between objective and subjective levels of adiposity varied between r=0.36 and r=0.66 in different age groups of men and women. Misclassification bias seems likely, although what effect this might have on the study’s findings is unclear. Interestingly, the authors did not identify repeated loss and regain of weight (weight cycling) as a separate trajectory. This pattern of weight change is thought to increase risk of diabetes, but limited evidence exists to support an effect on mortality.5 6
In conclusion, the study by Aune and colleagues suggests an optimal BMI for lowest mortality likely to apply to European and North American populations. Optimal BMI can be expected to vary by age, ethnicity, and the proportion of people with comorbidity in different populations, and secular declines in mortality may have been even more marked if the prevalence of obesity had not increased. The study by Song and colleagues is an important step forward in furthering our understanding of how weight gain over the life course, particularly in mid-life, is likely to influence health and mortality. Major challenges remain in finding effective ways to prevent weight gain, support weight loss, and prevent weight re-gain, in both individuals and populations.
BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants.
Aune D, Sen A, Prasad M, Norat T, Janszky I, Tonstad S, Romundstad P, Vatten LJ.
BMJ. 2016 May 4;353:i2156. doi: 10.1136/bmj.i2156.
PMID: 27146380
http://www.bmj.com/content/353/bmj.i2156http://www.bmj.com/content/bmj/353/bmj.i2156.full.pdfAbstract
OBJECTIVE:
To conduct a systematic review and meta-analysis of cohort studies of body mass index (BMI) and the risk of all cause mortality, and to clarify the shape and the nadir of the dose-response curve, and the influence on the results of confounding from smoking, weight loss associated with disease, and preclinical disease.
DATA SOURCES:
PubMed and Embase databases searched up to 23 September 2015.
STUDY SELECTION:
Cohort studies that reported adjusted risk estimates for at least three categories of BMI in relation to all cause mortality.
DATA SYNTHESIS:
Summary relative risks were calculated with random effects models. Non-linear associations were explored with fractional polynomial models.
RESULTS:
230 cohort studies (207 publications) were included. The analysis of never smokers included 53 cohort studies (44 risk estimates) with >738 144 deaths and >9 976 077 participants. The analysis of all participants included 228 cohort studies (198 risk estimates) with >3 744 722 deaths among 30 233 329 participants. The summary relative risk for a 5 unit increment in BMI was 1.18 (95% confidence interval 1.15 to 1.21; I(2)=95%, n=44) among never smokers, 1.21 (1.18 to 1.25; I(2)=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33; I(2)=89%, n=11) among healthy never smokers with exclusion of early follow-up, and 1.05 (1.04 to 1.07; I(2)=97%, n=198) among all participants. There was a J shaped dose-response relation in never smokers (Pnon-linearity <0.001), and the lowest risk was observed at BMI 23-24 in never smokers, 22-23 in healthy never smokers, and 20-22 in studies of never smokers with =/>20 years' follow-up. In contrast there was a U shaped association between BMI and mortality in analyses with a greater potential for bias including all participants, current, former, or ever smokers, and in studies with a short duration of follow-up (<5 years or <10 years), or with moderate study quality scores.
CONCLUSION:
Overweight and obesity is associated with increased risk of all cause mortality and the nadir of the curve was observed at BMI 23-24 among never smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of follow-up. The increased risk of mortality observed in underweight people could at least partly be caused by residual confounding from prediagnostic disease. Lack of exclusion of ever smokers, people with prevalent and preclinical disease, and early follow-up could bias the results towards a more U shaped association.Trajectory of body shape in early and middle life and all cause and cause specific mortality: results from two prospective US cohort studies.
Song M, Hu FB, Wu K, Must A, Chan AT, Willett WC, Giovannucci EL.
BMJ. 2016 May 4;353:i2195. doi: 10.1136/bmj.i2195.
PMID: 27146280
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4856853/http://www.bmj.com/content/bmj/353/bmj.i2195.full.pdfAbstract
OBJECTIVE:
To assess body shape trajectories in early and middle life in relation to risk of mortality.
DESIGN:
Prospective cohort study.
SETTING:
Nurses' Health Study and Health Professionals Follow-up Study.
POPULATION:
80 266 women and 36 622 men who recalled their body shape at ages 5, 10, 20, 30, and 40 years and provided body mass index at age 50, followed from age 60 over a median of 15-16 years for death.
MAIN OUTCOME MEASURES:
All cause and cause specific mortality.
RESULTS:
Using a group based modeling approach, five distinct trajectories of body shape from age 5 to 50 were identified: lean-stable, lean-moderate increase, lean-marked increase, medium-stable/increase, and heavy-stable/increase. The lean-stable group was used as the reference. Among never smokers, the multivariable adjusted hazard ratio for death from any cause was 1.08 (95% confidence interval 1.02 to 1.14) for women and 0.95 (0.88 to 1.03) for men in the lean-moderate increase group, 1.43 (1.33 to 1.54) for women and 1.11 (1.02 to 1.20) for men in the lean-marked increase group, 1.04 (0.97 to 1.12) for women and 1.01 (0.94 to 1.09) for men in the medium-stable/increase group, and 1.64 (1.49 to 1.81) for women and 1.19 (1.08 to 1.32) for men in the heavy-stable/increase group. For cause specific mortality, participants in the heavy-stable/increase group had the highest risk, with a hazard ratio among never smokers of 2.30 (1.88 to 2.81) in women and 1.45 (1.23 to 1.72) in men for cardiovascular disease, 1.37 (1.14 to 1.65) in women and 1.07 (0.89 to 1.30) in men for cancer, and 1.59 (1.38 to 1.82) in women and 1.10 (0.95 to 1.29) in men for other causes. The trajectory-mortality association was generally weaker among ever smokers than among never smokers (for all cause mortality: P for interaction <0.001 in women and 0.06 in men). When participants were classified jointly according to trajectories and history of type 2 diabetes, the increased risk of death associated with heavier body shape trajectories was more pronounced among participants with type 2 diabetes than those without diabetes, and those in the heavy-stable/increase trajectory and with a history of diabetes had the highest risk of death.
CONCLUSIONS:
Using the trajectory approach, we found that heavy body shape from age 5 up to 50, especially the increase in middle life, was associated with higher mortality. In contrast, people who maintained a stably lean body shape had the lowest mortality. These results indicate the importance of weight management across the lifespan.