中国6～13岁儿童24小时活动水平和相关因素分析

Levels and correlates of 24-hour movement behaviors in Chinese children aged 6-13 years

目的了解中国6~13岁儿童24 h活动指南的达标现状,并探讨其社会人口学影响因素,为中国儿童的健康促进提供依据。方法基于一项全国多中心干预研究,采用分层整群随机抽样方法选取湖南、宁夏、天津、重庆、辽宁、上海和广东7个省市6~13岁儿童共31 362名进行流行病学基线调查。采用问卷调查方式,收集儿童中高强度体力活动(moderate to vigorous physical activity, MVPA)、视屏时间(screen time, ST)和睡眠时长及社会人口学资料。采用广义线性混合模型分析儿童MVPA、ST和睡眠时长达标情况的社会人口学影响因素。结果被试平均每天MVPA时间为(53.36±62.28)min,平均每天ST为(1.48±1.46)h,每天睡眠时间<7,7~<9,9~11,>11 h的分别占8.7%,59.6%,30.1%,1.6%。符合MVPA、ST、睡眠指南推荐的比例分别为32.2%,78.5%,30.1%;总达标条数为0,1,2,3条的比例分别为9.6%,47.7%,35.0%,7.7%。年龄、性别、父母文化水平和家庭月收入对体力活动、ST和睡眠是否达标有影响;父母文化程度低与不健康的活动模式有关,父母文化水平越低,达标条数越少(P值均<0.05)。结论中国6~13岁儿童24 h身体活动达标现状不理想,在设计有针对性的干预措施以促进儿童健康时应考虑社会人口学特征。

Objective To investigate the different patterns of 24-h movement behaviors, and their associations with sociodemographic factors in a nationally representative sample of Chinese children aged 6-13 years. Methods This study was based on a national multi-centered cluster intervention study involving 31 362 children aged 6-13 years from 7 provinces in China. Questionnaires were used to collect moderate to vigorous physical activity(MVPA), screen time(ST) and sleep duration, as well as sociodemographic variables including age, gender, area of residence, parents’ education level and family income. Generalized linear mixed model(GLMM) analyses were conducted for the 24-hour movement behaviors according to sociodemographic variables. Results The proportions of individuals meeting the MVPA, ST, and sleep guidelines were 32.2%, 78.5%, 30.1%, respectively. The proportion that meet 0, 1, 2 and 3 recommended items was 9.6%, 47.7%, 35.0% and 7.7%, respectively. Age, gender, parents’ education levels and family income showed associations with PA, ST and sleep. Compared with low parents’ education group, the risk for unhealthy behavioral patterns was lower in those with high parents’ education level(P<0.05). Conclusion The current status of 24-hour physical activity for children aged 6-13 in China is not ideal, and social demographics should be considered when designing targeted interventions to promote children’s health.