Intersectional inequities in the birthweight gap between twin and singleton births: A random effects MAIHDA analysis of 2012–2018 New York City birth data

Abstract

Birthweight is a widely-used biomarker of infant health, with inequities patterned intersectionally by maternal age, race/ethnicity, nativity/immigration status, and socioeconomic status in the United States. However, studies of birthweight inequities almost exclusively focus on singleton births, neglecting high-risk twin births. We address this gap using a large sample (N = 753,180) of birth records, obtained from the 2012–2018 New York City (NYC) Department of Health and Mental Hygiene, Bureau of Vital Statistics, representing 99% of all births registered in NYC, and a novel random coefficients intersectional MAIHDA (Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy) model. Our results show evidence of intersectional inequities in birthweight outcomes for both twin and singleton births by maternal age, race/ethnicity, education, and nativity status. Twins have considerably lower predicted birthweights than singletons overall (−930 g on average), and this is especially true for babies born to mothers who are younger (11–19 years), older (40+), racial/ethnic minoritized, foreign-born, and have lower education. However, the magnitude of this birthweight ‘gap’ between twins and singletons varies considerably across social identity strata, ranging between 830.8 g (observed among 40+ year old Black foreign-born mothers with high school degrees) and 1013.7 g (observed among 30–39 year old Hispanic/Latina foreign-born mothers with less than high school degrees). This study underscored the needs of a high-risk population and the need for aggressive social policies to address health inequities and dismantle intersectional systems of marginalization, oppression, and socioeconomic inequality. In addition to our substantive contributions, we add to the growing methods literature on intersectional quantitative analysis by demonstrating how to apply intersectional MAIHDA with random coefficients and random slopes. We conclude with a discussion of the significant potential for this methodological extension in future research on inequities.