Evidence Sharing: 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

Introduction:

- The association between overweight and obesity and increased risk of a wide range of chronic diseases, including cardiovascular diseases, type 2 diabetes, several types of cancer, gallbladder disease, gout, osteoarthritis, and several other conditions, as well as all cause mortality.

- Though many studies have shown an increased risk of all cause mortality with greater adiposity as measured by body mass index (BMI), questions remain about the shape of the dose-response relation

- It is well known that smoking strongly increases risk of mortality and many specific causes of death, and there is therefore a great potential for residual confounding by smoking as it is typically also associated with lower weight.

- Weight loss can precede a diagnosis of disease by many years and because of such preclinical weight loss the associations between low BMI and increased mortality might at least partly be caused by confounding by preclinical disease.

Objective:

- To demonstrate the association of BMI and all cause mortality

- To clarify the shape and the nadir of the dose-response curve

- To study the influence of confounding from smoking, weight loss associated with disease and preclinical diseases

Methods:

- Search Period: until 23 September 2015

- Database: PubMed and Embase

- Language: English

- Study quality assessment: Newcastle-Ottawa scale

- Inclusion criteria: Cohort studies reported adjusted risk estimates for at least 3 BMI categories in relation to all cause mortality; populations living in the community

- Exclusion criteria: studies included only patients, nursing home residents, and disabled people; only reported continuous linear risk estimate (because there is evidence that the association between BMI and mortality is non-linear)

- Other consideration: we did not include data from studies that combined never smokers and former smokers who had quit for a long duration

Statistics:

- Primary analysis: Never smokers
- Relative risk calculated with random effects models

- Non-linear associations were explored with fractional polynomial models.

- The analyses were re-scaled so the reference category was a BMI of 23, which seemed to be the nadir of the curve among never smokers, so there was no loss of statistical power from these re-calculations

Results:

- Total number of included studies: 230 cohort studies (207 publications)

- Total number of subjects: 30 233 329 participants (>3 744 722 deaths)\

- Study Location: Europe (n=96), North America, (n=71) Latin or South America (n=3)

Asia (n=49), Australia and New Zealand (n=10), Pacific region (n=1)

Among Never Smokers,

- Number of included studies: 53 cohort studies (with 44 risk estimates)

- Number of subjects: > 9 976 077 participants (>738 144 deaths)

Main findings:

For every 5 unit increment in BMI, the relative risk (RR) for all cause mortality among:

- Never smokers (primary analysis): RR 1.18 (95% CI 1.15-1.21; I²=95%; n=44)

- Among healthy* Never smokers: RR 1.21 (95% CI 1.18-1.25; I²=93%; n=25)

- Among healthy Never smokers with exclusion of early follow-up# : RR 1.27 (95% CI 1.21-1.33; I²=89%; n=11)

- All participants: RR 1.05 (95% CI 1.04-1.07; I²=97%; n=198)

There was a J shaped dose-response relation in never smokers and lowest risk was observed at (reference at BMI 23):

- BMI 23-24 in never smokers

- BMI 22-23 in healthy never smokers

- BMI 20-22 in studies of never smokers with ≥20 years of follow-up

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

- In studies with short duration of follow-up (<5 years or <10 years)

- Moderate study quality scores

Publication bias: Absent (never smoker analysis), Present (All participants analysis)

Subgroup analysis:

- Stratified by sex, geographical region, study quality scores, number of deaths: Never smokers (absence of heterogeneity); all participants (presence of heterogeneity)

- The positive association between BMI and all cause mortality among never smokers persisted in subgroup analyses defined by sex, assessment of anthropometric measures, geographical location, number of deaths, and adjustment for confounding factors including age, education, alcohol, physical activity, height, dietary pattern, and intake of fat, fruit, and vegetables. There was little evidence of heterogeneity between any of these subgroups with meta-regression analyses

- In the analysis of all participants, heterogeneity is presence among studies stratified by adjustment for number of cigarettes smoked a day (P<0.001), with a stronger association among studies with such adjustment compared with studies without such adjustment

- The association between BMI and mortality was stronger among studies that had adjusted for the most important confounding factors (age, smoking, alcohol, physical activity) but that did not adjust for intermediate factors or prevalent disease. These associations were further strengthened among studies with longer duration of follow-up

- Among Never smokers: the association between BMI and all cause mortality was considerably stronger among people aged <65 than among people aged ≥65 (sig heterogeneity)

Discussion:

- Among never smokers: relative risks of 1.11, 1.24, 1.42, 1.98 and 3.54 for BMI values of 27.5, 30, 32.5, 37.5, and 45 compared with a BMI of 23 (Table)
- The analysis of all participants needs to be interpreted carefully as there is a greater possibility of confounding by smoking and confounding from prediagnostic weight loss associated with disease.

- The increased risk observed with a BMI of 20 in the analysis of all participants and never smokers and the lower risk in overweight people in the analysis of all participants is likely to be caused by confounding by smoking and prediagnostic weight loss.

- The lowest risk was observed in the overweight range at a BMI of 27.5 in the studies with medium quality scores, while the lowest risk was observed at a BMI of 24-25 in the studies with the highest quality scores.

Limitations:

- Meta-analysis of observational studies: confounding by unmeasured or imperfectly measured risk factors could have influenced the results

- Not able to investigate the potential interactions between BMI and physical activity or dietary factors in relation to all cause mortality as few studies reported such results

- Although BMI is an imperfect measure of body fatness but in most people it is highly correlated with measures of body fat; incorporating waist measures might have additional clinical relevance for risk assessment

- Measurement errors in the assessment of height and weight could have influenced the results.

- Only English language publication

Conclusion:

- Overweight and obesity is associated with increased risk of all cause mortality and the nadir (lowest point=lowest mortality) 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 pre-diagnostic disease.

- Lack of exclusion of ever smokers, people with prevalent disease, and early follow-up and inclusion of studies with lower study quality could bias the associations between BMI and mortality towards a more U shaped association

Note:

- For relative risk or odds ratio, the result is significant if the 95% confidence interval does not include 1, because 1 means null effect.
(Some study will only report 95% CI without p-value, it is beneficial to learn how to determine significant without relying on p-value. Try to look at the results for this study and determine whether the result is significant.)

- Heterogeneity (I²≥50% or p-value for I² <0.05) may weaken the result of a meta-analysis. They are usually addressed in subgroup/sensitivity analysis.

* Healthy: Excluded people with prevalent cancer, cardiovascular disease, and in some cases diabetes, and/or people with recent weight loss)

# Excluded early follow-up: (from first year up to six years of follow-up)