Inequality in physical activity, sedentary behaviour, sleep duration and risk of obesity in children: a 12‐country study. (4th May 2018)

• Record Type: Journal Article
• Authors: Chaput, J.‐P.; Barnes, J. D.; Tremblay, M. S.; Fogelholm, M.; Hu, G.; Lambert, E. V.; Maher, C.; Maia, J.; Olds, T.; Onywera, V.; Sarmiento, O. L.; Standage, M.; Tudor‐Locke, C.; Katzmarzyk, P. T.
• Is Part Of: Obesity science and practice. Volume 4:Number 3(2018)
• Page Start: 229
• Page End: 237
• Publication Date: 2018-05-04
• Subjects: Disparity -- Gini coefficient -- movement behaviours -- paediatric population; Obesity -- Periodicals; 616.398005
• DOI: 10.1002/osp4.271
• Languages: English
• ISSNs: 2055-2238

Abstract

Summary: Objective: Studies examining associations between movement behaviours (i.e. physical activity, sedentary behaviour and sleep duration) and obesity focus on average values of these movement behaviours, despite important within‐country and between‐country variability. A better understanding of movement behaviour inequalities is important for developing public health policies and behaviour‐change interventions. The objective of this ecologic analysis at the country level was to determine if inequality in movement behaviours is a better correlate of obesity than average movement behaviour volume in children from all inhabited continents of the world. Methods: This multinational, cross‐sectional study included 6, 128 children 9–11 years of age. Moderate‐to‐vigorous physical activity (MVPA), total sedentary time (SED) and sleep period time were monitored over 7 consecutive days using waist‐worn accelerometry. Screen time was self‐reported. Inequality in movement behaviours was determined using Gini coefficients (ranging from 0 [complete equality] to 1 [complete inequality]). Results: The largest inequality in movement behaviours was observed for screen time (Gini of 0.32; medium inequality), followed by MVPA (Gini of 0.21; low inequality), SED (Gini of 0.07; low inequality) and sleep period time (Gini of 0.05; low inequality). Average MVPA (h d −1 ) was a better correlate of obesity than MVPA inequality ( r = −0.77 vs. r = 0.00, p = 0.03). Average SED (h d −1 ) was also a better correlate of obesity than SED inequality ( r = 0.52 vs. r = −0.32, p = 0.05). Differences in associations for screen time and sleep period time were not statistically significant. MVPA in girls was found to be disproportionally lower in countries with more MVPA inequality. Conclusions: Findings from this study show that average MVPA and SED should continue to be used in population health studies of children as they are better correlates of obesity than inequality in these behaviours. Moreover, the findings suggest that MVPA inequality could be greatly reduced through increases in girls' MVPA alone.