Introduction: Body mass index (BMI) is a composite variable of weight and height, often used as a predictor of health outcomes, including mortality. The main purpose of combining weight and height in one variable is to obtain a measure of obesity independent of height. It is however unclear how accurate BMI is as a predictor of mortality compared with models including both weight and height or a weight x height interaction as predictors.

Methods: The current study used conscription data on weight, height, and BMI of Swedish men (N = 48,904) in 1969/70 as well as linked data on mortality (3442 deaths) between 1969 and 2008. Cox proportional hazard models including combinations of weight, height, and BMI at conscription as predictors of subsequent all-cause and cause-specific mortality were fitted to data.

Results: An increase by one standard deviation on weight and BMI were associated with an increase in hazard for all-cause mortality by 5.4% and 11.5%, respectively, while an increase by one standard deviation on height was associated with a decrease in hazard for all-cause mortality by 9.4%. The best-fitting model indicated lowest predicted all-cause mortality for those who weighed 60.5 kg at conscription, regardless of height. Further analyses of cause-specific mortality suggest that this weight seems to be a compromise between lower optimal weights to avoid cancer and CVD mortality and a higher optimal weight to not die by suicide.

Conclusions: According to the present findings, there are several ways to make better use of measured weight and height than to calculate BMI when predicting mortality.