Since females have a greater prevalence of obesity compared with males, the question arises whether females have lower metabolic rate than males after adjusting for differences in body weight and composition. 24-h energy expenditure (24EE), basal metabolic rate (BMR), and sleeping metabolic rate (SMR) were measured in a respiratory chamber in 235 healthy, nondiabetic Caucasian subjects (114 males, 121 females). Body composition was determined by hydrodensitometry. 24EE was 124 +/- 38 kcal/d (P less than 0.002) higher in males than females after adjusting for differences in fat-free mass, fat mass, and age. Spontaneous physical activity was not significantly different between males and females. Since adjusted 24EE was 106 +/- 39 kcal/d (P less than 0.01) higher in females during the luteal phase of the menstrual cycle compared with females during the follicular phase, energy expenditure was analyzed in a subset (greater than 50 yr) to minimize the confounding effect of menstrual status. 24EE (160 +/- 66 kcal/d; P less than 0.03), BMR (116 +/- 45; P less than 0.02), and SMR (208 +/- 68 kcal/d; P less than 0.005) were higher in males compared with females of the older subset after adjusting for differences in body composition, age, and activity. In summary, sedentary 24EE is approximately 5-10% lower in females compared with males after adjusting for differences in body composition, age, and activity.
R Ferraro, S Lillioja, A M Fontvieille, R Rising, C Bogardus, E Ravussin
Usage data is cumulative from January 2024 through January 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 488 | 74 |
84 | 199 | |
Scanned page | 240 | 82 |
Citation downloads | 80 | 0 |
Totals | 892 | 355 |
Total Views | 1,247 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.