The impact of adverse childhood experiences on adult physical, mental health, and abuse behaviors: A sex-stratified nationwide latent class analysis in Japan

潜在类模型 童年不良经历 心理健康 精神科 身体虐待 儿童期虐待 心理学 医学 临床心理学 性虐待 环境卫生 自杀预防 毒物控制 数学 统计
作者
Tomoya Hirai,Kosuke Hagiwara,Chong Chen,Ryo Okubo,Fumihiro Higuchi,Toshio Matsubara,Masahito Takahashi,Shin Nakagawa,Takahiro Tabuchi
出处
期刊:Journal of Affective Disorders [Elsevier BV]
标识
DOI:10.1016/j.jad.2024.10.074
摘要

Adverse childhood experiences (ACEs) have been reported to detrimentally impact physical and mental health. While experiencing multiple ACEs is common, previous research primarily assessed ACEs by their total count, neglecting the impacts of different experience types. Furthermore, sex-based differences in ACEs and their influences remain unclear. This study employed Latent Class Analysis (LCA) to uncover patterns of ACEs with consideration for sex differences, aiming to elucidate their effects on adult physical and mental health. A geographically nationally representative dataset from the "Japan COVID-19 and Society Internet Study (JACSIS)" conducted in 2022 was used. 13,715 men and 14,327 women retrospectively reported their experiences across fifteen ACEs. The analysis revealed four distinct ACE patterns for both sexes: a Multiple Adversities class with a wide range of severe ACEs, a Psychological Abuse class experiencing emotional abuse at home and bullying at school, a Poverty class facing economic hardships, and a Low Adversities class with the fewest ACEs. Multinomial logistic regression analysis indicated that more severe patterns of exposure correlated with heightened adverse adult outcomes. However, the extent of these impacts varied by sex and ACE pattern. For instance, men in Multiple Adversities and Psychological Abuse classes exhibited higher tendencies towards conducting physical and psychological abuse behaviors. While ACEs in men were linked to both underweight (in cases of psychological abuse) and obesity (across all classes), women with ACEs generally leaned towards higher body weight. These findings highlight the importance of developing support strategies sensitive to sex differences and the specific content of ACEs.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wicjy完成签到,获得积分20
刚刚
nihaoaaaa发布了新的文献求助10
刚刚
1秒前
兮日完成签到,获得积分10
1秒前
geyal发布了新的文献求助20
1秒前
1秒前
2秒前
tzy完成签到,获得积分10
2秒前
霸气的念云完成签到,获得积分10
3秒前
PJoooi发布了新的文献求助10
3秒前
怕孤单的龙猫完成签到,获得积分10
4秒前
兮日发布了新的文献求助10
4秒前
沉柒完成签到,获得积分10
4秒前
七昂完成签到,获得积分10
5秒前
eleven完成签到 ,获得积分10
5秒前
Liu完成签到,获得积分10
5秒前
masirui应助小刀采纳,获得10
6秒前
6秒前
7秒前
8秒前
脑洞疼应助淡定的依丝采纳,获得10
8秒前
碎觉觉发布了新的文献求助10
8秒前
小绵羊发布了新的文献求助10
8秒前
科研通AI6.2应助贪玩的誉采纳,获得10
9秒前
10秒前
10秒前
aaaa应助爱撒娇的怜珊采纳,获得100
10秒前
Alan完成签到,获得积分10
11秒前
wzh1745发布了新的文献求助10
11秒前
伊洛完成签到 ,获得积分10
11秒前
12秒前
wangDx发布了新的文献求助10
12秒前
wkkk完成签到,获得积分10
12秒前
斯文败类应助霸气的念云采纳,获得10
13秒前
13秒前
twilight完成签到,获得积分10
13秒前
悦悦发布了新的文献求助10
15秒前
cdercder应助糕糕采纳,获得20
15秒前
爱吃螺蛳粉完成签到,获得积分10
16秒前
炙热谷雪完成签到,获得积分10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
Digital Displacement Hydrostatic Transmission for Rotorcraft and Distributed Propulsion 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7707357
求助须知:如何正确求助?哪些是违规求助? 9264929
关于积分的说明 20052337
捐赠科研通 7283819
什么是DOI,文献DOI怎么找? 3296055
关于科研通互助平台的介绍 2450935
邀请新用户注册赠送积分活动 2303010