The Role of Social Determinants of Health and Social Position in Mental Health: An Examination of the Moderating Effects of Race, Ethnicity, and Gender on Depression through the All of Us Dataset

Matt Kammer-Kerwick, Kyle Cox, Ishani Purohit,S. Craig Watkins

medRxiv (Cold Spring Harbor Laboratory)(2023)

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摘要
Background. Extant research has examined the roles of social position (SP) and social determinants of health (SDoH) on mental health outcomes. We add to this literature by focusing on major depressive disorder, investigating how race, ethnicity, gender, and sexual identity moderate the role of several social determinant domains on this common mental health condition. Methods. Our analysis is based on the All of Us (AoU) dataset. We use a staged multiple logistic regression design. In the first stage, we consider how SP factors independently predict risk for diagnosis of MDD. In the second stage, we consider how SDoH add information to predict diagnosis of MDD. In the third stage, we consider how select SP factors moderate the role of SDoH in assessing risk for MDD diagnosis. We choose to focus on race/ethnicity and gender/sexual identity as SP moderators. We examine those moderating effects on food insecurity, discrimination, neighborhood social cohesion, and loneliness. Results. Our findings further illustrate the complexity and nuance associated with how the context of where and how people live their lives has significant differential impact on health outcomes. Some of our results confirm long-standing relationships while elucidating detail about the effect on health. For example, independent of discrimination, Black community members have the same likelihood of an MDD diagnosis as Whites (AOR = 1.00, p = 0.982). However, discrimination experienced by Black community members increases their likelihood of a diagnosis of MDD (AOR = 1.47, p = 0.053) whereas among Whites experiencing discrimination does not increase the likelihood of an MDD diagnosis (AOR = 1.25, p = 0.122). Our analysis indicates that increases to loneliness for cisgender heterosexual female community members and gender and sexually minoritized community members are associated with lesser increases in risk of MDD diagnosis than similar increases in loneliness for cisgender heterosexual males (AOR = 0.44 and 0.22, p < 0.001, respectively), suggesting that this specific SDoH may have differential impacts across population segments. Other results shed new light on less well-established moderation effects. For example, gender and sexually minoritized community members are much more likely to experience depression compared to cisgender heterosexual men (AOR = 2.66, p < 0.001). Increasing neighborhood social cohesion does not alter the likelihood of depression, holding all other factors constant (AOR = 0.84, p = 0.181). But there is a weak moderation effect (AOR = 1.41, p = 0.090). Conclusions. We use these analyses to outline future research to delve deeper into these findings. The current study demonstrates the value of the AoU data in the study of how various SDoH factors differentially drive health outcomes. It also provides a reminder that even larger datasets designed to represent the general population face substantial challenges for research focused on marginalized community segments and is a timely reminder that sampling plans are needed to ensure sufficient statistical power to examine those most marginalized and underserved. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was supported by institutional funding at The University of Texas at Austin under the Good Systems project AI and the Future of Racial Justice and the IC2 Institute's project Delivering Equitable Healthcare. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study uses the NIH All of Us Research Project as its source of data. These data and the computational notebooks we used are available through that public resource. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The study uses the NIH All of Us Research Project as its source of data. These data and the computational notebooks we used are available through that public resource.
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