Montana Greider, MA1 • Chris R. Fernandez, MS1 • Sam Rusk1 • Yoav N. Nygate, MS1 • Dana Richardson2 • Brian Hutchinson2 • Tim Bartholow2 • Nathaniel F. Watson, MD, MS3 • Emerson Wickwire, MD, MS4
Introduction
Area socioeconomic deprivation, as measured by the Area Deprivation Index (ADI), is associated with numerous adverse health and economic outcomes (cardiovascular, readmissions, Alzheimer’s). This composite score is based on 17 health disparities indicators (income, education, employment, housing) used to rank relative disadvantage across communities, and is a widely utilized key social determinant of health and a validated marker of health risk. The purpose of this study was to determine the association between the ADI and OSA testing and diagnosis.
Methods
Our data source was the All-Payer Claims Database (APCD) for the Wisconsin Health Information Organization from 2017-2022 and linked to the publicly available ADI. Sociodemographic variables were extracted from APCD including race, gender, and age. Inclusion criteria included continuous enrollment coverage for a minimum of 12-months prior to the date of OSA diagnosis (defined by ICD code G47.33) and a diagnostic sleep test (defined by CPT codes for PSGs and HSATs). ADI was measured at state and national levels. Rates of OSA testing and diagnosis were compared between individuals with OSA across the entire range of ADI scores using ordinary least squares (OLS) regression analysis.
Results
Of N=6,026,463 participants, n=1,310,286 were linked and included in the final sample: 53% women, Mean age=46.75[SD=22.2], National ADI=52.4[SD=20.2], ethnoracial demographic group affiliation: 22 self-identified categories), n=154,821 underwent OSA diagnostic testing, and n=43,601 were subsequently diagnosed with OSA (45% women, age=56.24[SD=16.2], National ADI=55.95[SD=20.88]). Diagnostic testing for OSA was significantly, positively associated with socioeconomic deprivation based on National ADI (slope: 0.0002, p< 0.005) and State ADI (slope: 0.0003, p< 0.005). The highest rates of OSA testing were observed in areas of socioeconomic disadvantage (>4.5%: ADI-decile 90-10). Conversely, the lowest OSA testing rates were observed in areas of socioeconomic advantage (< 2%: ADI-decile 0-10). Relative to individuals in socioeconomically advantaged areas (low-ADI), individuals in disadvantaged areas (high-ADI) were approximately 3% more likely to be tested for OSA.
Conclusion
Area socioeconomic deprivation measured by ADI is associated with a small but significant increase in OSA testing. Future research should seek to increase access to OSA care in areas of socioeconomic disadvantage to improve sleep health equity and reduce global health disparities.
