Scherbakov Dmitry, Marrone Michael T, Lenert Leslie A, Alekseyenko Alexander V
Medical University of South Carolina.
Res Sq. 2024 Dec 3:rs.3.rs-5536130. doi: 10.21203/rs.3.rs-5536130/v1.
BACKGROUND/OBJECTIVE: Depression is a complex mental health disorder influenced by various social determinants of health (SDOH) at individual and community levels. Area-level factors and intersectionality framework, which considers overlapping personal identities, are used in this paper to get a nuanced picture of depression disparities.
This cross-sectional study uses electronic health records data from the All of Us research network. Our study cohort includes 20,042 individuals who completed the SDOH surveys in All of Us and had at least one in-patient visit, with 27.3% diagnosed with depression since 2020. We used depression diagnosis as an outcome, while independent variables include US Religious Census and American urvey responses, area-level variables, sociodemographic characteristics: age group, income, gender, sexual orientation, immigration status, marital status, and race/ethnicity - and the interactions of the latter with each other and with other variables. The association between depression diagnosis and the variables is reported by fitting the logistic regression model on the subset of variables identified by LASSO method.
The analysis revealed that area-level indicators, such as religious adherence and childbirth rates, significantly influenced depression outcomes when interacting with personal identity variables: area-level religious adherence was associated with increased depression odds for women (OR 1.33, 95% CI 1.15-1.54) and non-binary individuals (OR 3.70, 95% CI 1.03-13.31). Overlapping identities, such as younger adults unemployed for less than a year and never married Middle Eastern and North African participants showed higher depression odds (OR 2.3, 95% CI 1.06-4.99, and OR 3.35, 95% CI 1.19-9.45, respectively).
DISCUSSION/CONCLUSION: The findings underscore the importance of considering all types of factors: individual, area-level, and intersectional in depression research.
背景/目的：抑郁症是一种复杂的心理健康障碍，受到个体和社区层面各种健康社会决定因素（SDOH）的影响。本文采用区域层面因素和交叉性框架（该框架考虑了重叠的个人身份）来深入了解抑郁症差异情况。
这项横断面研究使用了来自“我们所有人”研究网络的电子健康记录数据。我们的研究队列包括20,042名在“我们所有人”中完成了SDOH调查且至少有一次住院就诊的个体，自2020年以来，其中27.3%被诊断患有抑郁症。我们将抑郁症诊断作为结果变量，而自变量包括美国宗教普查和美国调查的回复、区域层面变量、社会人口学特征（年龄组、收入、性别、性取向、移民身份、婚姻状况以及种族/族裔）以及后者彼此之间以及与其他变量的相互作用。通过对套索（LASSO）方法确定的变量子集拟合逻辑回归模型，报告抑郁症诊断与这些变量之间的关联。
分析表明，宗教信仰程度和出生率等区域层面指标在与个人身份变量相互作用时，对抑郁症结果有显著影响：区域层面的宗教信仰程度与女性患抑郁症几率增加相关（比值比[OR]为1.33，95%置信区间[CI]为1.15 - 1.54），与非二元性别人士患抑郁症几率增加相关（OR为3.70，95% CI为1.03 - 13.31）。重叠身份，如失业不到一年的年轻成年人以及从未结婚的中东和北非参与者，患抑郁症的几率更高（分别为OR 2.3，95% CI为1.06 - 4.99，以及OR 3.35，95% CI为1.19 - 9.45）。
讨论/结论：研究结果强调了在抑郁症研究中考虑所有类型因素（个体因素、区域层面因素和交叉性因素）的重要性。
