Association of Unhealthy Behaviors with Self-Harm in Chinese Adolescents: A Study Using Latent Class Analysis

Rong Yang, Dan-lin Li, R. Tian, Jie Hu, Yanni Xue, Xuexue Huang, Y. Wan, Jun Fang, Shi-chen Zhang
{"title":"Association of Unhealthy Behaviors with Self-Harm in Chinese Adolescents: A Study Using Latent Class Analysis","authors":"Rong Yang, Dan-lin Li, R. Tian, Jie Hu, Yanni Xue, Xuexue Huang, Y. Wan, Jun Fang, Shi-chen Zhang","doi":"10.3390/traumacare1020008","DOIUrl":null,"url":null,"abstract":"Previous studies have demonstrated the link between individual unhealthy behaviors and self-harm, but little is known about the influence of multiple unhealthy behaviors on self-harm among adolescents. This study aims to identify the potential patterns of unhealthy behaviors and to examine their associations with self-harm, which may become a useful tool for the screening of self-harm in adolescents. A total of 22,628 middle school students (10,990 males and 11,638 females) in six cities was enrolled in this study by multistage stratified cluster sampling from November 2015 to January 2016. Latent class analysis (LCA) was performed based on five kinds of unhealthy behaviors (unhealthy losing weight (ULW), tobacco use (TU), alcohol use (AU), screen time (ST), and mobile phone dependence (MPD)). Multivariate logistic regressions were used to examine associations between identified subgroups and self-harm. Four subgroups of unhealthy behaviors were identified. Class 1 (71.2%) had the lowest engagement in unhealthy behaviors. Class 2 ((ULW/MPD), 22.3%) had a relatively high prevalence of ULW and MPD. Class 3 ((TU/AU/ST), 3.2%) had a relatively high prevalence of TU, AU, and ST. Class 4 (3.3%) consistently engaged in unhealthy behaviors. Compared to class 1, class 2 (ULW/MPD), class 3 (TU/AU/ST), and class 4 showed OR (95%CI) values of 2.101 (1.964–2.248), 2.153 (1.839–2.520), and 3.979 (3.407–4.645) (p < 0.001 for each), respectively. Class 1, class 2 (ULW/MPD), and class 3 (TU/AU/ST) engagement in unhealthy behaviors was associated with increased self-harm. These findings strongly suggested that self-harm prevention efforts focusing on multiple unhealthy behaviors should be seriously considered for early detection of self-harm.","PeriodicalId":75251,"journal":{"name":"Trauma care (Basel, Switzerland)","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3390/traumacare1020008","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trauma care (Basel, Switzerland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/traumacare1020008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Previous studies have demonstrated the link between individual unhealthy behaviors and self-harm, but little is known about the influence of multiple unhealthy behaviors on self-harm among adolescents. This study aims to identify the potential patterns of unhealthy behaviors and to examine their associations with self-harm, which may become a useful tool for the screening of self-harm in adolescents. A total of 22,628 middle school students (10,990 males and 11,638 females) in six cities was enrolled in this study by multistage stratified cluster sampling from November 2015 to January 2016. Latent class analysis (LCA) was performed based on five kinds of unhealthy behaviors (unhealthy losing weight (ULW), tobacco use (TU), alcohol use (AU), screen time (ST), and mobile phone dependence (MPD)). Multivariate logistic regressions were used to examine associations between identified subgroups and self-harm. Four subgroups of unhealthy behaviors were identified. Class 1 (71.2%) had the lowest engagement in unhealthy behaviors. Class 2 ((ULW/MPD), 22.3%) had a relatively high prevalence of ULW and MPD. Class 3 ((TU/AU/ST), 3.2%) had a relatively high prevalence of TU, AU, and ST. Class 4 (3.3%) consistently engaged in unhealthy behaviors. Compared to class 1, class 2 (ULW/MPD), class 3 (TU/AU/ST), and class 4 showed OR (95%CI) values of 2.101 (1.964–2.248), 2.153 (1.839–2.520), and 3.979 (3.407–4.645) (p < 0.001 for each), respectively. Class 1, class 2 (ULW/MPD), and class 3 (TU/AU/ST) engagement in unhealthy behaviors was associated with increased self-harm. These findings strongly suggested that self-harm prevention efforts focusing on multiple unhealthy behaviors should be seriously considered for early detection of self-harm.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
中国青少年不健康行为与自残的关系:一项基于潜类分析的研究
先前的研究已经证明了个体不健康行为与自残之间的联系,但对多种不健康行为对青少年自残的影响知之甚少。本研究旨在探讨青少年不健康行为的潜在模式及其与自我伤害的关系,为青少年自我伤害的筛查提供有益的工具。本研究采用多阶段分层整群抽样方法,于2015年11月至2016年1月对6个城市的22,628名中学生(男生10,990人,女生11,638人)进行研究。潜在类分析(LCA)基于五种不健康行为(不健康减肥(ULW),烟草使用(TU),酒精使用(AU),屏幕时间(ST)和手机依赖(MPD))。使用多变量逻辑回归来检验确定的亚组与自我伤害之间的关系。确定了四个不健康行为亚组。1班(71.2%)的不健康行为参与度最低。2级((ULW/MPD), 22.3%)的ULW和MPD患病率相对较高。3级((TU/AU/ST), 3.2%)有较高的TU、AU和ST患病率,4级(3.3%)持续从事不健康行为。与1类相比,2类(ULW/MPD)、3类(TU/AU/ST)和4类的OR (95%CI)值分别为2.101(1.964 ~ 2.248)、2.153(1.839 ~ 2.520)和3.979 (3.407 ~ 4.645)(p < 0.001)。1类、2类(ULW/MPD)和3类(TU/AU/ST)参与不健康行为与自残增加相关。这些发现强烈表明,应该认真考虑针对多种不健康行为的自我伤害预防工作,以便及早发现自我伤害。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Influence of COVID-19 on Patient Mobilization and Injury Attributes in the ICU: A Retrospective Analysis of a Level II Trauma Center. Assessing Risk Factors for Victims of Violence in a Hospital-Based Violence Intervention Program Does a Preoperative Carbohydrate Drink Reduce Postoperative Inflammation? A Systematic Review and Meta-Analysis Addressing Attrition from Psychotherapy for PTSD in the U.S. Department of Veterans Affairs Are There Sex Differences in the Prevalence and Severity of Early-Stage Trauma-Related Stress in Mildly Impaired Autistic Children and Adolescents?
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1