five

S2 Data -

收藏
NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://figshare.com/articles/dataset/S2_Data_-/23872525
下载链接
链接失效反馈
官方服务:
资源简介:
Objective This study aimed to analyze the prevalence of overweight/obesity and the factors influencing these conditions among 9- to 18-year-old adolescents in Keerqin District of Tongliao City. We explored whether overweight/obesity is accompanied by differences in eating habits, lifestyle, and mental health. Methods A cross-sectional survey was administered to 1,736 adolescents in November 2020. A physical examination was performed for each participant, and an online questionnaire was adopted to collect information. The association of several risk factors with overweight/obesity was explored using a logistic regression model. Results The prevalence of overweight/obesity in the study population was 43.32%. The risk of overweight/obesity was higher among nonresident students (odds ratio [OR] = 1.564, 95% CI = 1.182–2.069) who had an average of 3–4 (OR = 2.164, 95% CI = 1.087–4.308) or 5 or more (OR = 2.114, 95% CI = 1.376–3.248) PE classes per week. The risk of overweight/obesity was lower among girls (OR = 0.485, 95% CI = 0.396–0.593), students aged 15–16 years (OR = 0.288, 95% CI = 0.135–0.617) and those aged 17–18 years (OR = 0.282, 95% CI = 0.124–0.639), students who ate sweets more than once a week (OR = 0.570, 95% CI = 0.366–0.887), students who spent less than 1 hour per day on the computer each week (OR = 0.776, 95% CI = 0.620–0.971), students with depressive symptoms (Center for Epidemiologic Studies Depression Scale [CES-D] score ≥ 16) (Model 2: OR = 0.618, 95% CI = 0.385–0.990; Model 3: OR = 0.623, 95% CI = 0.388–1.000), and students with depressed affect (Model 2: OR = 0.921, 95% CI = 0.877–0.967; Model 3: OR = 0.929, 95% CI = 0.885–0.976). Conclusion Overweight/obesity was influenced by eating habits and lifestyle factors. In addition, overweight/obesity adolescents had a lower risk of depressed than those with normal weight.
创建时间:
2023-08-04
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作