The Influence of Lifestyle Factors on Resting Energy Expenditure and Its Role in Cardiometabolic Risk: A Cross-Sectional Study

TL;DR

This study shows that moderate physical activity and higher HDL cholesterol are linked to increased resting energy expenditure, which may help prevent cardiometabolic diseases.

Contribution

The study identifies moderate physical activity and HDL-C as independent contributors to resting energy expenditure beyond body composition and sex.

Findings

Fat-free mass is the strongest predictor of resting energy expenditure.

Moderate physical activity and HDL-C independently contribute to resting energy expenditure.

Sleep duration did not significantly affect resting energy expenditure in this cohort.

Abstract

Objectives: This cross-sectional study aimed to examine the associations between lifestyle factors (diet, physical activity, and sleep) and resting energy expenditure (REE) in a group of 75 healthy adults aged 30–45 years without obesity, and to explore its relationship with body composition parameters and selected biochemical markers that could positively influence cardiometabolic disease prevention. Methods: For this purpose, indirect calorimetry, accelerometers, and bioelectrical impedance analysis (BIA) were used. Results: We found that fat-free mass (FFM) showed the strongest association with REE, along with related metrics such as total body water, body cell mass, and muscle mass (p < 0.0001, adj. R2 > 0.5). In univariable models, all physical activity intensities were significantly associated with REE, but only moderate physical activity (MPA) remained significant after adjusting for sex and FFM (β = 2.1 ± 1.0, p < 0.05, adj. R2 = 0.589). Similarly, a positive association between HDL-C and REE persisted after adjustments (β = 4.8 ± 2.3 kcal/d, p < 0.05, adj. R2 = 0.590). Further analyses confirmed that MPA and HDL-C independently contributed to REE (ΔR2 = 0.02, p < 0.05; Partial r = 0.233 and 0.236, respectively, both p < 0.05), highlighting their role beyond the effects of FFM and sex. Other biochemical and lifestyle factors, including HOMA-IR, insulin levels, triglycerides, and total energy intake, showed positive associations with REE in the crude model. However, these relationships diminished after adjustment, suggesting that their influence is likely mediated by factors such as body composition, body size, and sex. Finally, no significant relationship between sleep and REE was observed in our cohort under naturalistic conditions, possibly due to the alignment of participants’ sleep durations with recommended guidelines. Conclusions: These potential direct links between MPA–REE and REE-HDL may be partially explained by habitual, spontaneous physical activity, which contributes to post-exercise metabolic elevation and may promote adipose tissue browning, potentially resulting in favorable metabolic effects, that support cardiometabolic disease prevention.