We examined the association between sleep duration and BMI in young adults, and, specifically, in possible gender differences. The population-based sample included 955 young men and 1051 young women (mean age = 25.3 years, s.d. = 1.7) who participated in Project EAT-III (Eating and Activity in Teens and Young Adults)-III. In 2008-2009, study participants completed a survey, on which they reported their weight, height, and typical bed and awakening times. Gender-specific regression models estimated cross-sectional associations between sleep duration and weight status, adjusting for age, race, SES, family structure, depressive symptoms, physical activity, and sedentary and dietary behaviors. In multivariable-adjusted linear regression models, an hour increase in sleep was associated with a -0.38 (-0.70, -0.048) BMI in men. Men who slept <7 h had a 1.4 unit higher mean BMI (27.9; 95% confidence interval (CI): 26.9, 28.9) than men who slept 7-9 h/day (26.5; 95% CI: 26.1, 27.0). Prevalence estimates of overweight (BMI ≥25) and obesity (BMI ≥30) were also inversely associated with sleep duration among men. Sleep duration was not associated with BMI, overweight, or obesity in women. Among women, but not men, there was a statistically significant positive association between trouble falling or staying asleep and mean BMI. Sleep may be an important modifiable risk factor for obesity, particularly in young adult men.

OBJECTIVE: Media images of men and women have become increasingly muscular, and muscle-enhancing techniques are available to youth. Identifying populations at risk for unhealthy muscle-enhancingbehaviors is of considerable public health importance. The current study uses a large and diverse population-based sample of adolescents to examine the prevalence of muscle-enhancing behaviors and differences across demographic characteristics, weight status, and sports team involvement. METHODS: Survey data from 2793 diverse adolescents (mean age = 14.4) were collected at 20 urban middle and high schools. Use of 5 muscle-enhancing behaviors was assessed (changing eating, exercising, protein powders, steroids and other muscle-enhancing substances), and a summary score reflecting use of 3 or more behaviors was created. Logistic regression was used to test for differences in each behavior across age group, race/ethnicity, socioeconomic status, BMI category, and sports team participation. RESULTS: Muscle-enhancing behaviors were common in this sample for both boys and girls. For example, 34.7% used protein powders or shakes and 5.9% reported steroid use. Most behaviors were significantly more common among boys. In models mutually adjusted for all covariates, grade level, Asian race, BMI category, and sports team participation were significantly associated with the use of muscle-enhancing behaviors. For example, overweight (odds ratio = 1.45) and obese (odds ratio = 1.90) girls had significantly greater odds of using protein powders or shakes than girls of average BMI. CONCLUSIONS: The use of muscle-enhancing behaviors is substantially higher than has been previously reported and is cause for concern. Pediatricians and other health care providers should ask their adolescent patients about muscle-enhancing behaviors.