Triaging Factors of Caregiver Depression through Chi-Square Automatic Interaction Detection (CHAID) Analysis.

Abstract

Over one in four caregivers in the United States report having received a diagnosis of depression, compared with less than 10% of the general adult population. We conducted a cross-sectional analysis of the 2022-2023 Behavioral Risk Factor Surveillance Survey using 23 demographic, comorbidity, or caregiving variables for 30,961 surveyed caregivers. The rate of caregivers reporting a diagnosis of depression was compared between these variables. We then conducted a chi-square automatic interaction detection analysis to determine the order of significance among these variables in predicting depression rates. The greatest differential in depression rates is based on the age of the caregiver (35.3% younger than 55 versus 21.6% 55 and older; p < .001). Among both age groups, income was the second greatest factor in predicting caregiver depression (35.4% with less than $50,000 and 21.6% with $50,000 or more; p < .001). Analysis of the factors associated with the greatest caregiver depression rates informs strategies to triage community funds and resources.