Predicted lean body mass, fat mass, and all cause and cause specific mortality in men: prospective US cohort study

Abstract

ObjectiveTo investigate the association of predicted lean body mass, fat mass, and body mass index (BMI) with all cause and cause specific mortality in men.DesignProspective cohort study.SettingHealth professionals in the United StatesParticipants38 006 men (aged 40-75 years) from the Health Professionals Follow-up Study, followed up for death (1987-2012).Main outcome measuresAll cause and cause specific mortality.ResultsUsing validated anthropometric prediction equations previously developed from the National Health and Nutrition Examination Survey, lean body mass and fat mass were estimated for all participants. During a mean of 21.4 years of follow-up, 12 356 deaths were identified. A J shaped association was consistently observed between BMI and all cause mortality. Multivariable adjusted Cox models including predicted fat mass and lean body mass showed a strong positive monotonic association between predicted fat mass and all cause mortality. Compared with those in the lowest fifth of predicted fat mass, men in the highest fifth had a hazard ratio of 1.35 (95% confidence interval 1.26 to 1.46) for mortality from all causes. In contrast, a U shaped association was found between predicted lean body mass and all cause mortality. Compared with those in the lowest fifth of predicted lean body mass, men in the second to fourth fifths had 8-10% lower risk of mortality from all causes. In the restricted cubic spline models, the risk of all cause mortality was relatively flat until 21 kg of predicted fat mass and increased rapidly afterwards, with a hazard ratio of 1.22 (1.18 to 1.26) per standard deviation. For predicted lean body mass, a large reduction of the risk was seen within the lower range until 56 kg, with a hazard ratio of 0.87 (0.82 to 0.92) per standard deviation, which increased thereafter (P for non-linearity <0.001). For cause specific mortality, men in the highest fifth of predicted fat mass had hazard ratios of 1.67 (1.47 to 1.89) for cardiovascular disease, 1.24 (1.09 to 1.43) for cancer, and 1.26 (0.97 to 1.64) for respiratory disease. On the other hand, a U shaped association was found between predicted lean body mass and mortality from cardiovascular disease and cancer. However, a strong inverse association existed between predicted lean body mass and mortality from respiratory disease (P for trend <0.001).ConclusionsThe shape of the association between BMI and mortality was determined by the relation between two body components (lean body mass and fat mass) and mortality. This finding suggests that the “obesity paradox” controversy may be largely explained by low lean body mass, rather than low fat mass, in the lower range of BMI.

Long‐term status of predicted body fat percentage, body mass index and other anthropometric factors with risk of colorectal carcinoma: Two large prospective cohort studies in the US

“…This explains why we observed a positive association between predicted lean body mass and CRC risk. In contrast, we recently reported that an inverse relationship between BMI and mortality associated with respiratory disease was largely due to lean body mass . Our current findings suggest that BMI can be a good measure of obesity at least for estimating the risk of CRC regardless of age.…”

“…In contrast, we recently reported that an inverse relationship between BMI and mortality associated with respiratory disease was largely due to lean body mass. 22 Our current findings suggest that BMI can be a good measure of obesity at least for estimating the risk of CRC regardless of age. Observed heterogenous susceptibilities of obesity with the risk of CRC were consistent with a large body of previous literature.…”

“…Considering the variation in body size, we further adjusted for height for predicted fat mass as seen in our previous literature. 17,21,22 To capture the long-term influence of anthropometric measurements, cumulative average of repeated measures over the follow-up was used.…”

“…Confounders were updated over the follow‐up periods and the cumulative average of each relevant variable was used to reduce within‐individual variation and to estimate the long‐term influence. Considering the variation in body size, we further adjusted for height for predicted fat mass as seen in our previous literature . To capture the long‐term influence of anthropometric measurements, cumulative average of repeated measures over the follow‐up was used.…”

Nonalcoholic Fatty Liver Disease in The Rotterdam Study: About Muscle Mass, Sarcopenia, Fat Mass, and Fat Distribution

“…This gives room for thought whether it is a true shortage of muscle mass, or a relative excess of fat mass, or both that is associated with NAFLD. Interestingly, a recent population‐based study found that the two body components, lean body mass and fat mass, both explained the relation between BMI and mortality . To the best of our knowledge, there are no studies that have examined the role of both components, independent of each other, in relation to NAFLD.…”