Moderate-intensity exercise sustained for 16 months is effective for weight management in young adults.

This preliminary data suggests that active commuting does not appear to provide sufficient amounts of physical activity to attenuate BMI; however, it may contribute to the attainment of physical activity recommendations. Future research is needed to objectively measure the impact of active commuting on the prevalence of overweight.

EISENMANN, JOEY C., KATE A. HEELAN, AND GREGORY J. WELK. Assessing body composition among 3-to 8-year-old children: anthropometry, BIA, and DXA. Obes Res. 2004;12:1633-1640. Objective: To examine the inter-relationships of body composition variables derived from simple anthropometry [BMI and skinfolds (SFs)], bioelectrical impedance analysis (BIA), and dual energy x-ray (DXA) in young children. Research Methods and Procedures: Seventy-five children (41 girls, 34 boys) 3 to 8 years of age were assessed for body composition by the following methods: BMI, SF thickness, BIA, and DXA. DXA served as the criterion measure. Predicted percentage body fat (%BF), fat-free mass (FFM; kilograms), and fat mass (FM; kilograms) were derived from SF equations [Slaughter (SL)1 and SL2, Deurenberg (D) and Dezenberg] and BIA. Indices of truncal fatness were also determined from anthropometry. Results: Repeated measures ANOVA showed significant differences among the methods for %BF, FFM, and FM. All methods, except the D equation (p ϭ 0.08), significantly underestimated measured %BF (p Ͻ 0.05). In general, correlations between the BMI and estimated %BF were moderate (r ϭ 0.61 to 0.75). Estimated %BF from the SL2 also showed a high correlation with DXA %BF (r ϭ 0.82). In contrast, estimated %BF derived from SFs showed a low correlation with estimated %BF derived from BIA (r ϭ 0.38); likewise, the correlation between DXA %BF and BIA %BF was low (r ϭ 0.30). Correlations among indicators of truncal fatness ranged from 0.43 to 0.98. Discussion: The results suggest that BIA has limited utility in estimating body composition, whereas BMI and SFs seem to be more useful in estimating body composition during the adiposity rebound. However, all methods significantly underestimated body fatness as determined by DXA, and, overall, the various methods and prediction equations are not interchangeable.

BackgroundWhile socio-economic status has been shown to be an important determinant of health and physical activity in adults, results for children and adolescents are less consistent. The purpose of this study, therefore, is to examine whether physical activity and sedentary behavior differs in children by socio-economic status (SES) independent of body mass index.MethodsData were from two cohorts including 271 children (117 males; 154 females) in study 1 and 131 children in study 2 (63 males; 68 females). The average age was 9.6 and 8.8 years respectively. Height and body mass were assessed according to standard procedures and body mass index (BMI, kg/m2) was calculated. Parent-reported household income was used to determine SES. Habitual, free-living physical activity (PA) was assessed by a pedometer (steps/day) in study 1 and accelerometer (time spent in moderate-to-vigorous PA) in study 2. Self-reported time spent watching TV and on the computer was used as measure of sedentary behavior. Differences in PA and sedentary behavior by SES were initially tested using ANOVA. Further analyses used ANCOVA controlling for BMI, as well as leg length in the pedometer cohort.ResultsIn study 1, mean daily steps differed significantly among SES groups with lower SES groups approximating 10,500 steps/day compared to about 12,000 steps/day in the higher SES groups. These differences remained significant (p < 0.05) when controlling for leg length. Lower SES children, however, had higher body mass and BMI compared to higher SES groups (p < 0.05) and PA no longer remained significant when further controlling for BMI. In study 2 results depended on the methodology used to determine time spent in moderate-to-vigorous physical activity (MVPA). Only one equation resulted in significant group differences (p = 0.015), and these differences remained after controlling for BMI. Significant differences between SES groups were shown for sedentary behavior in both cohorts (P < 0.05) with higher SES groups spending less time watching TV than low SES groups.ConclusionsChildren from a low SES show a trend of lower PA levels and spend more time in sedentary behavior than high SES children; however, differences in PA were influenced by BMI. The higher BMI in these children might be another factor contributing to increased health risks among low SES children compared to children from with a higher SES.