Predicted fat mass and lean mass in relation to all‐cause and cause‐specific mortality. Issue 2 (23rd January 2022) - Liu, Mengyi; Zhang, Zhuxian; Zhou, Chun; Ye, Ziliang; He, Panpan; Zhang, Yuanyuan; Li, Huan; Liu, Chengzhang; Qin, Xianhui
Abstract: Background: Studies on the prospective association of body composition with mortality in US general populations are limited. We aimed to examine this association by utilizing data from the National Health and Nutrition Examination Survey (NHANES), a representative sample of US adults, linked with data from the National Death Index. Methods: We analysed data of NHANES 1988–1994 and 1999–2014, with 55 818 participants [50.6% female, baseline mean age: 45.0 years (SE, 0.2)]. Predicted fat mass and lean mass were calculated using the validated sex‐specific anthropometric prediction equations developed by the NHANES based on individual age, race, height, weight, and waist circumference. Body composition and other covariates were measured at only one time point. Multivariable Cox regression was used to investigate the associations of predicted fat mass and lean mass with overall and cause‐specific mortality, adjusting for potential confounders. Interactions between age and body composition on mortality were examined with likelihood ratio testing. Results: Mean predicted fat mass was 24.1 kg [95% confidence interval (CI): 23.9–24.3) for male participants and 29.9 kg (95% CI: 29.6–30.1) for female participants, while mean predicted lean mass was 59.3 kg (95% CI: 59.1–59.5) for male participants and 41.7 kg (95% CI: 41.5–41.8) for female participants. During a median period of 9.7 years from the survey, 10 408 deaths occurred. When predicted fat and lean mass were both included in the model, predicted fat mass showed a U‐shaped association with all‐cause mortality, with significantly higher risk at two ends: Quintile 1 (HR, 1.17; 95% CI: 1.05–1.31), Quintile 2 (HR, 1.14; 95% CI: 1.04–1.26) and Quintile 5 (HR, 1.37; 95% CI: 1.12–1.68) compared with Quintile 3. In contrast, predicted lean mass showed a L‐shaped association with all‐cause mortality, with higher mortality in those with lower lean mass: Quintile 1 (HR, 1.64; 95% CI: 1.46–1.83) and Quintile 2 (HR, 1.29; 95% CI: 1.18–1.42) compared with Quintile 3. Similar results were found for cardiovascular, cancer, and respiratory cause‐specific mortality. Age was a significant modifier: There was a monotonic positive association of predicted fat mass with mortality in younger participants (<60 years), but an approximate J‐shaped association in older participants (≥60 years) ( P interaction <0.001); there was a stronger inverse association between predicted lean mass and mortality in older participants (≥60) compared with those <60 years ( P interaction <0.001). Conclusions: In this US general population, predicted fat mass and lean mass were independent predictors for overall and cause‐specific mortality. Age was a significant modifier on the associations.