1 Purpose of Study
This project aims to compare commonly used Social Determinants of Health (SDOH) indices and explore their association with health outcomes in Ohio’s counties and census tracts.
2 Methods
The indices used include (1) the 2022 Neighborhood Atlas Area Deprivation Index (ADI), (2) the 2020 CDC/ATSDR Social Vulnerability Index (SVI), and (3) the 2018 Ohio Opportunity Index (OOI). Selected health outcome indicators come from (1) the 2021 CDC PLACES data and (2) the 2021 OMAS Small Area Estimate Series.
All data visualizations and statistics referenced in this poster and document were created using the statistical package R and RStudio.
3 Discussion
Given the well known challenges Appalachia and Appalachians have faced for decades, of course the default expectation was that both social determinants of health, as measured by ADI and other indices, would paint Appalachia as most resource deprived, and because SDOH drive health, that health outcomes would be the worst for Appalachians too. There is a lot to unpack here but these are some things that struck me …
- Ohio’s most deprived census tracts (measured by the ADI) are not located in the most deprived counties. In particular, the most deprived counties in Ohio are located Appalachia while the most deprived census tracts are in cities and large metropolitan areas.
- The SDOHs measured by the ADI are highly correlated with adult health outcomes, but not as as much for child health outcomes.
- Even within health outcomes, there is a good bit of variation. For example, the SDOHs measured by the ADI are more correlated with diabetes rates than with the prevalence of obesity. Ths is surprising to me since I expected a greater overlap between obesity and diabetes.
- It is also clear to me that because of significant within-county variation in deprivation, county-level estimates tend to wash out these nuances. Think about Franklin county … how varied are the census tracts? However, tract-level data are hard to come by on the health outcome side, and that forces analysts to use county-level data. I am convinced more than ever that we need to do a better job of getting at tract-level data if we really want to unpack how SDOH are linked to health.
4 Limitations
- Variation in census tract boundaries, when joining indices and health outcomes, resulted in roughly 18% data loss of tracts.
- Limited adult health outcomes data are available at the county- and tract-level in CDC PLACES. Tract-level data also suffer from substantial missingness. No child health outcome data are available in PLACES.
- County-level analyses attenuate variation that exists across tracts both in terms of SDOH and adult/child outcomes.
- Census tracts are not all equal, therefore even tract-level analysis isn’t taking into account the fact that some tracts will be more populous than others.
- More tract-level health outcomes data for adults and children would lead to more accurate analyses and hence, policies and programs.
5 Index Measures
5.1 Area Deprivation Index (ADI)
The Area Deprivation Index is based on a measure created by the Health Resources & Services Administration (HRSA) over three decades ago, and was refined, adapted, and validated to the Census block group neighborhood level by Amy Kind, MD, PhD and her research team at the University of Wisconsin-Madison. It allows for rankings of neighborhoods by socioeconomic disadvantage in a region of interest (e.g., at the state or national level).
The ADI is a composite measure of 17 census variables designed to describe socioeconomic disadvantage based on the four domains of income, education, household characteristics, and housing. It can be used to inform health delivery and policy, especially for the most disadvantaged neighborhood groups.
| Domain | Census Variables |
|---|---|
| Education |
|
| Income/Employment |
|
| Housing |
|
| Household Characteristics |
|