湖南省城乡中小学生超重与肥胖的分布特征及影响因素
秦李希 , 罗米扬 , 李可欣 , 周阳 , 陈艳华 , 谭雅卿 , 王非
中南大学学报(医学版) ›› 2025, Vol. 50 ›› Issue (04) : 684 -693.
湖南省城乡中小学生超重与肥胖的分布特征及影响因素
Distribution characteristics and influencing factors of overweight and obesity among urban and rural primary and secondary school students in Hunan Province
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目的 儿童青少年超重率与肥胖率持续上升,逐渐成为21世纪全球最严重的公共卫生问题之一。城乡儿童青少年的生长发育环境不同,超重与肥胖相关的危险因素也有所不同。本研究旨在探究湖南省城乡中小学生超重与肥胖的分布特征及影响因素,为采取针对性干预措施提供科学依据。 方法 采用分层随机整群抽样法抽取研究对象,共纳入湖南省14个市(州)197 084名中小学生进行体格检查和问卷调查。分析湖南省城乡中小学生超重与肥胖的人群与空间分布特征,使用ArcGIS绘制超重率与肥胖率空间分布图并进行空间自相关分析。采用多因素Logistic回归分析湖南省城乡中小学生超重与肥胖的影响因素。 结果 湖南省中小学生超重率和肥胖率分别为14.7%和10.9%,城区超重率、肥胖率均高于郊县(分别为16.0% vs 13.9%、12.1% vs 10.2%)。无论城区还是郊县,男生超重率和肥胖率均高于女生,高年级超重率均高于低年级,高年级肥胖率均低于低年级;城区汉族中小学生超重率和肥胖率、郊县汉族学生肥胖率均低于少数民族中小学生(均P<0.05)。湖南省各市(州)城区中小学生超重率和肥胖率分别为14.7%~18.7%和8.4%~20.6%;郊县中小学生超重率和肥胖率分别为10.9%~17.2%和6.6%~13.7%。空间自相关分析显示常德、张家界城区及娄底、怀化、邵阳等地的郊县出现了超重率/肥胖率的高值聚集。多因素Logistic回归分析结果显示:性别、学段、民族、新鲜蔬菜摄入频率、睡眠时间与湖南省城区和郊县中小学生超重和/或肥胖有关;油炸食物及新鲜水果摄入频率、早餐习惯、日常及假期身体活动、用电脑时间与城区中小学生超重和/或肥胖有关;看电视时间和久坐时间与郊县中小学生超重和/或肥胖有关。 结论 湖南省中小学生超重与肥胖情况不容乐观,应重点关注超重率/肥胖率的高值聚集区域,并结合城乡影响因素进行针对性干预。
Objective The prevalence of overweight and obesity among children and adolescents continues to rise, becoming one of the most serious global public health issues of the 21st century. Given the differing growth and development environments between urban and rural children, associated risk factors also vary. This study aims to explore the distribution characteristics and influencing factors of overweight and obesity among urban and rural primary and secondary school students in Hunan Province, providing scientific evidence for targeted interventions. Methods A stratified, randomized cluster sampling method was used to select participants. A total of 197 084 students from primary and secondary schools across 14 prefectures in Hunan Province underwent physical examinations and questionnaire surveys. Population and spatial distribution characteristics of overweight and obesity were analyzed. Spatial distribution maps and spatial autocorrelation analyses were conducted using ArcGIS. Multivariate Logistic regression was used to identify influencing factors for overweight and obesity. Results The overall overweight and obesity rates among students in Hunan Province were 14.7% and 10.9%, respectively. Both rates were higher in urban areas than in rural counties (16.0% vs 13.9% for overweight; 12.1% vs 10.2% for obesity). Among both urban and rural students, boys had higher rates of overweight and obesity than girls. Higher-grade students had a higher overweight rate but a lower obesity rate than lower-grade students. In urban areas, the overweight and obesity rates of Han Chinese primary and secondary school students are lower than those of ethnic minority students (both P<0.05). In rural areas, the obesity rate of Han primary and secondary school students is lower than that of ethnic students (P<0.05). Across cities and prefectures, urban overweight and obesity rates ranged from 14.7% to 18.7% and 8.4% to 20.6% respectively, while rural rates ranged from 10.9% to 17.2% and 6.6% to 13.7% respectively. Spatial autocorrelation analysis revealed high-value clusters of overweight/obesity in urban areas of Changde and Zhangjiajie, and in rural areas of Loudi, Huaihua, and Shaoyang. Multivariate Logistic regression showed that gender, school stage, ethnicity, frequency of fresh vegetable intake, and sleep duration were associated with overweight and/or obesity in both urban and rural students. In urban students, frequency of fried food and fresh fruit intake, breakfast habits, physical activity on weekdays and holidays, and screen time on computers were also significant. In rural students, TV viewing time and sedentary duration were additional relevant factors. Conclusion The situation of overweight and obesity among primary and secondary school students in Hunan Province remains concerning. Greater attention should be paid to regions with high-value clusters of overweight/obesity, and targeted interventions should be developed based on urban-rural differences in influencing factors.
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