Association Between Neighborhood Socioeconomic Deprivation, Comorbidity Burden, and Depression in a Mammography Cohort

Background and Purpose: Extensive literature highlights how neighborhood socioeconomic position (SEP) is associated with mental and physical health outcomes, but research involving clinical populations already facing health risks remains limited. This study examines the macrosocial forces associated with well-being by evaluating the relationship between neighborhood socioeconomic deprivation and clinical depression in a large clinical cohort of MetroHealth Systems patients. A secondary aim was to characterize the health context of depression by examining its association with comorbidity burden.

Methods: Using a retrospective cross-sectional design, we analyzed data from 29,619 patients in a mammography screening cohort. We constructed a composite health-related social needs (HRSN; i.e., social disconnection, housing instability, stress, intimate partner violence, transportation inaccessibility, food insecurity, financial strain risk) score via principal component analysis (PCA) to capture patients’ social needs as reported in the clinical setting. We used multivariable logistic regression to model the association between neighborhood SEP (operationalized by quintile of Area Deprivation Index [ADI]) and clinical depression diagnosis, adjusting for age, race/ethnicity, marital status, insurance type, and the HRSN-PCA composite. In the secondary analysis examining health context, multinomial logistic regression assessed the association between depression and comorbidity burden, categorized as low (0–2 diagnoses), moderate (3–4 diagnoses), or high (≥5 diagnoses), with adjustment for the same covariates.

Results: The mean age of patients in the cohort was 58.9 years (SD 10.8), the mean number of health conditions was 2.6 (SD = 2.13) and 22.47% had a diagnosis of clinical depression. In fully adjusted models, a diagnosis of depression was associated with higher ADI quintile (i.e., lower neighborhood socioeconomic position). Compared to patients in less socioeconomically vulnerable neighborhoods (Quintile 1), those in the most vulnerable areas (Quintile 5) had 1.33 times higher odds of depression (95% CI: 1.19-1.46, p < 0.001). This association persisted after adjustment for composite HRSN, which itself was strongly associated with depression (OR = 1.26, 95% CI: 1.24–1.28, p < 0.001). In the secondary multinomial analysis examining health context, depression was associated with an increase in comorbidity burden: 3.71 times higher odds of moderate comorbidity (95% CI: 3.45–3.99, p < 0.001) and 8.07 times higher odds of high comorbidity (95% CI: 7.41–8.78, p < 0.001) relative to low comorbidity burden.

Conclusion and Implications: In this population of patients undergoing breast cancer screening, neighborhood socioeconomic vulnerability is robustly and independently associated with depression, even after accounting for individual social needs and demographic factors. Additionally, depression is strongly associated with higher comorbidity burden. These findings highlight the importance of structural factors in mental health disparities and suggest that neighborhood-level disadvantage is associated with greater odds of co-occurring depression and higher comorbidity burden, pointing to the need for multi-level interventions addressing structural drivers of health.