The relationship between resting metabolic rate and quality of life is moderated by age and body composition in women: a cross-sectional study

Author:

Benton Melissa J.ORCID,Hutchins Andrea M.ORCID

Abstract

Abstract Background Health-related quality of life (HRQOL) is related to body composition, which is also related to resting metabolic rate (RMR). RMR can be increased by exercise and diet interventions that are not dependent on changes in body composition, so a link between RMR and HRQOL may provide interventions that directly improve HRQOL in women. Methods One hundred twenty women (median age 63.5 [IQR: 53.0–71.0] years) completed one-time measurement of body composition (multi-frequency bioelectrical impedance), RMR (handheld calorimetry), and HRQOL (RAND-36). Physical (PCS) and mental (MCS) composite scores were calculated for the RAND-36. Pearson correlations were used to identify relationships between RMR, body composition, and HRQOL. Variables at the p < .01 level were entered into multiple regression models. Results Median body mass index was 26.1 [IQR: 23.2–30.9] kg/m2 and median lean mass index was 16.1 [IQR: 14.6–17.3] kg/m2. Body composition consisted of fat mass (median 27.2 [IQR: 20.3–34.7] kg) and lean mass (median 42.7 [IQR: 38.2–46.9] kg). Median RMR was 1165.0 [IQR: 1022.5–1380.0] kcal/day. Median HRQOL scores were PCS (84.0 [IQR: 74.0–93.0]) and MCS (85.0 [IQR: 74.3–90.0]). RMR was not directly related to PCS, but was directly and negatively related to MCS (p = .002). RMR was significantly and positively related to body composition (lean mass: p < .001; fat mass: p < .001), body mass index (p = .005), and lean mass index (p < .001); but only fat mass (PCS: p < .001; MCS: p < .001) and body mass index (PCS: p < .001; MCS: p < .001) were related to HRQOL, although the relationship was negative. In addition, age was found to be significantly negatively related to RMR (p < .001) and PCS (p = .003). Regression models confirmed the moderating influence of age and body composition on the relationship between RMR and HRQOL. RMR, age, fat mass, and body mass index explained 24% (p < .001) of variance in PCS; and RMR, fat mass, and body mass index explained 15% (p < .001) of variance in MCS. Conclusion In women, the relationship between RMR and HRQOL is moderated by age and body composition. Understanding these pathways will allow clinicians and researchers to direct interventions more effectively.

Funder

University of Colorado Colorado Springs Office of Research Committee on Research and Creative Works and the Faculty Assembly Women’s Committee

Publisher

Springer Science and Business Media LLC

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