Latent Class Analysis of Depressive Symptom Phenotypes Among Black/African American Mothers

Author:

Perez Nicole BeaulieuORCID,D'Eramo Melkus GailORCID,Wright FayORCID,Yu GaryORCID,Vorderstrasse Allison A.ORCID,Sun Yan V.ORCID,Crusto Cindy A.ORCID,Taylor Jacquelyn Y.ORCID

Abstract

Background Depression is a growing global problem with significant individual and societal costs. Despite their consequences, depressive symptoms are poorly recognized and undertreated because wide variation in symptom presentation limits clinical identification—particularly among African American (AA) women—an understudied population at an increased risk of health inequity. Objectives The aims of this study were to explore depressive symptom phenotypes among AA women and examine associations with epigenetic, cardiometabolic, and psychosocial factors. Methods This cross-sectional, retrospective analysis included self-reported Black/AA mothers from the Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure study (data collected in 2015–2020). Clinical phenotypes were identified using latent class analysis. Bivariate logistic regression examined epigenetic age, cardiometabolic traits (i.e., body mass index ≥ 30 kg/m2, hypertension, or diabetes), and psychosocial variables as predictors of class membership. Results All participants were Black/AA and predominantly non-Hispanic. Over half of the sample had one or more cardiometabolic traits. Two latent classes were identified (low vs. moderate depressive symptoms). Somatic and self-critical symptoms characterized the moderate symptom class. Higher stress overload scores significantly predicted moderate-symptom class membership. Discussion In this sample of AA women with increased cardiometabolic burden, increased stress was associated with depressive symptoms that standard screening tools may not capture. Research examining the effect of specific stressors and the efficacy of tools to identify at-risk AA women are urgently needed to address disparities and mental health burdens.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Nursing

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3