Revealing the variations in impact of economic segregation on preterm birth among disaggregated Asian ethnicities across MSAs in the United States: 2015-2017.

BACKGROUND

Preterm birth (PTB) accounts for the majority of perinatal morbidity and mortality in developed nations, accounting for 9.9% of all births in the U.S. in 2016. Prior research has primarily focused on disparities between Black and white mothers' rates of PTB due to racial segregation. However, population health scholarship has been limited on the fastest growing population in the U.S., Asian and Pacific Islanders (API). Racial residential segregation has been well studied, but relatively little research examines the effects of economic segregation on perinatal health. This cross-sectional analysis examines how economic segregation modifies risk for PTB among various API ethnic groups.

METHODS

U.S. natality data were used to identify 134 Metropolitan Statistical Areas (MSA) with >500 API births from 2015 to 2017 (n = 766,711). Economic segregation was calculated for each MSA using 2017 income data using the Rank-Order Information Theory Index (H Index). Generalized Estimating Equations estimated the log-odds of PTB, allowing for modification by ethnicity.

RESULTS

There is heterogeneity in PTB prevalence by ethnicity and the association of economic segregation is non-linear. The risk for PTB is higher in MSAs with both high and low H Index for Chinese, Filipino, Japanese, Korean, Vietnamese, and Other Pacific Islander mothers. The risk for PTB follows highest in MSAs with mid-range values of standardized H Index for Indian, Hawaiian, Guamanian, and Samoan mothers. Filipino, Hawaiian, Guamanian, and Other Pacific Islander mothers had the highest predicted risk for PTB at mean levels of economic segregation while Chinese mothers had the lowest.

CONCLUSION

These findings are examined through the lens of immigration histories related to European colonialism, U.S. imperialism, and globalization. Importantly, the results suggest that current practices of aggregating API health data mask disparities in health and how socially stratifying processes like economic segregation may differ by ethnic group.