1218-P: Immigrant Density and Prevalence of Diabetes in American Neighborhoods

Abstract

Background: The “healthy immigrant effect” suggests that despite immigrants generally demonstrating lower socioeconomic status than non-immigrants, they have lower age-related disease prevalence and mortality compared to non-immigrants. Recent evidence suggests immigrants may have higher levels of physical activity and may also influence their neighbors to decrease sedentary behavior. Drawing from the literature, we investigated the association between immigrant density with the prevalence of diabetes in neighborhoods and of both foreign-born and U.S.-born populations by ZIP code level. Methods: In this retrospective, cross-sectional ecological study, we used data from the American Community Survey (ACS) and the CDC Behavioral Risk Factor Surveillance System (BRFSS) for 2018. We performed multiple regression to test our predictive model that appointed obesity and physical activity as possible mediators between immigrant density and diabetes. Participants: ZIP codes with more than 16 foreign-born individuals (324out of 41692 total ZCTAs) Results: Higher immigrant density in a neighborhood is associated with lower prevalence of diabetes (beta estimate = −0.056657; r-squared = 0.02709) ; this remains true even after adjusting for prevalence of obesity (0.038646; 0.5356) , physical activity (-0.014093; 0.7097) , and both (−0.001015; 0.7168) , with all p-values < 0.001. We concluded that immigrant density is a potential protective factor of diabetes, and the relationship is mediated by the prevalence of obesity and physical activity. Discussion: The effects may differ depending on the racial/ethnic composition of the neighborhood. A previous study has shown that living in communities with a high Hispanic concentration (>=25%) was associated with an increase in body mass index (BMI) and higher odds for obesity in non-Hispanic Whites, respectively; meanwhile, the opposite effect is observed for communities with high Asian concentration. As a next step, we will disaggregate our results by race.