Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Apr;13(2):1064-1075.
doi: 10.1002/jcsm.12921. Epub 2022 Jan 23.

Predicted fat mass and lean mass in relation to all-cause and cause-specific mortality

Affiliations

Predicted fat mass and lean mass in relation to all-cause and cause-specific mortality

Mengyi Liu et al. J Cachexia Sarcopenia Muscle. 2022 Apr.

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.

Keywords: Abdominal obesity; Age; Mortality; Predicted fat mass; Predicted lean mass.

PubMed Disclaimer

Conflict of interest statement

No disclosures were reported.

Figures

Figure 1
Figure 1
The association between predicted fat mass and risk of all‐cause mortality in various subgroups *Adjusted for age, sex, height, race/ethnicity, education level, marital status, smoking status, history of hypertension and diabetes, leisure physical activity level, high‐density lipoprotein cholesterol, total cholesterol, and predicted lean mass, if not already stratified; mortality rate is presented as per 1000 person‐years; sex‐specific quintiles of predicted fat mass (kg): female participants: Q1: <21.0; Q2: 21.0–<26.2; Q3: 26.2–<31.7; Q4: 31.7–<39.6; Q5: ≥39.6; Q5: ≥39.8; male participants: Q1: <16.2; Q2: 16.2–<20.9; Q3: 20.9–<25.3; Q4: 25.3–<31.0.
Figure 2
Figure 2
The association between predicted lean mass and risk of all‐cause mortality in various subgroups *Adjusted for age, sex, height, race/ethnicity, education level, marital status, smoking status, history of hypertension and diabetes, leisure physical activity level, high‐density lipoprotein cholesterol, total cholesterol, and predicted fat mass, if not already stratified; mortality rate is presented as per 1000 person‐years; sex‐ specific quintiles of predicted lean mass (kg): Female participants: Q1: <35.7; Q2: 35.7–<39.0; Q3: 39.0–<42.4; Q4: 42.4–<47.2; Q5: ≥47.2; male participants: Q1: Q1: <50.3; Q2: 50.3–<54.8; Q3: 54.8–<59.2; Q4: 59.2–<65.4; Q5: ≥65.4.

Similar articles

Cited by

References

    1. Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, 2007–2008 to 2015–2016. JAMA 2018;319:1723–1725. - PMC - PubMed
    1. Dai H, Alsalhe TA, Chalghaf N, Riccò M, Bragazzi NL, Wu J. The global burden of disease attributable to high body mass index in 195 countries and territories, 1990–2017: an analysis of the Global Burden of Disease Study. PLoS Med 2020;17:e1003198. - PMC - PubMed
    1. Bhaskaran K, Dos‐Santos‐Silva I, Leon DA, Douglas IJ, Smeeth L. Association of BMI with overall and cause‐specific mortality: a population‐based cohort study of 3.6 million adults in the UK. Lancet Diabetes Endocrinol 2018;6:944–953. - PMC - PubMed
    1. Rothman KJ. BMI‐related errors in the measurement of obesity. Int J Obes (Lond) 2008;32:S56–S59. - PubMed
    1. Wannamethee SG, Atkins JL. Muscle loss and obesity: the health implications of sarcopenia and sarcopenic obesity. Proc Nutr Soc 2015;74:405–412. - PubMed

Publication types