From
Dr. Meera Kotagal
Understanding area-based socioeconomic deprivation indices in health research
With Dr. Meera Kotagal · hosted by Dr. Alan Weil
Chapter 1 of 8
Introduction
Introduction to area-based socioeconomic deprivation indices
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What the experts said
Area-based socioeconomic deprivation indices measure neighborhood context at census tract or zip code level
Complex socioeconomic deprivation indices are better predictors of and have better association with health outcomes than any single measure alone
The systematic scoping review identified over 3000 articles, which narrowed to over 1000 abstracts after excluding duplicates, yielding 44 potential indices
After excluding indices that were too geographically broad or limited to single states, 15 indices remained for review
The Social Vulnerability Index (SVI) was developed to assess vulnerability to disaster and includes race because communities with higher proportions of minority individuals are more vulnerable to disaster due to structural racism
Most deprivation indices include measures of income/poverty, education, and employment
The Social Vulnerability Index used expert consensus to identify which factors should be included
Some indices use statistical factor loading methods that weight variables based on how much variation they explain in the sample
Most indices output results by percentile rank, but some use absolute values
For the Material Community Deprivation Index, the top quintile (top 20% most deprived) contains more variation than the other 80% combined
Four of the 15 reviewed indices include race or ethnicity in their composition
A neighborhood's racial composition is not in itself a marker of socioeconomic deprivation; race is a social construct, not a biological one
When measuring race in deprivation indices, what is actually being measured is structural racism and how racism manifests, not race itself
There are higher rates of vulnerability after disaster in communities with higher percentages of Black residents, even after controlling for socioeconomic status
If trying to assess individual-level racial inequities while controlling for area-level racial makeup in a deprivation index, it impacts the results
Four or five indices include transportation availability as part of their metric
Transportation measures like car ownership are region-dependent; in Manhattan, percentage of car ownership is not reflective of community deprivation as it might be elsewhere in the United States
Non-English primary language creates barriers to healthcare access and health interventions, but not all non-English primary language communities are deprived or lack resources
There is a role for multiple indices because each has advantages and disadvantages; the goal should not be a single index for all studies
MassHealth uses census-tract neighborhood stress index scores to adjust payments according to patient social risk
CMS's Accountable Care Organization REACH model adjusts reimbursement rates based on area deprivation
Policy use of deprivation indices reflects understanding the difference between equality and equity, recognizing that equity requires providing additional resources to reach the same outcome
Deprivation indices focus on deficits within communities, which allows identification of gaps that can be remedied to make positive impact
Deprivation indices do not measure community well-being, social cohesion, or how communities thrive; other tools like social dynamics modeling can demonstrate community strengths
Most indices use census tract level; Area Deprivation Index is available at census block group level; Community Need Index and Distressed Communities Index are only available at zip code level
Zip codes can be variable in size and may include multiple different types of communities, which can cause loss of signal at the zip code level
In Flint lead analysis, using zip codes failed to identify a signal because zip codes extended beyond city boundaries into suburban areas, but census tract level analysis identified the significant problem
Zip codes are sometimes used because data can be more complete, no geocoding is required, and privacy/confidentiality concerns are addressed, but there is significant heterogeneity within zip codes