The application of intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to examine birthweight inequities in New York City

Christina I Nieves; Luisa N Borrell; Clare R Evans; Heidi E Jones; Mary Huynh

doi:10.1016/j.healthplace.2023.103029

The application of intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to examine birthweight inequities in New York City

Health Place. 2023 May:81:103029. doi: 10.1016/j.healthplace.2023.103029. Epub 2023 Apr 27.

Authors

Christina I Nieves¹, Luisa N Borrell², Clare R Evans³, Heidi E Jones⁴, Mary Huynh⁵

Affiliations

¹ Department of Epidemiology & Biostatistics, Graduate School of Public Health & Health Policy, City University of New York, New York, NY, United States. Electronic address: [email protected].
² Department of Epidemiology & Biostatistics, Graduate School of Public Health & Health Policy, City University of New York, New York, NY, United States.
³ Department of Sociology, University of Oregon, Eugene, OR, United States.
⁴ Department of Epidemiology & Biostatistics, Graduate School of Public Health & Health Policy, City University of New York, New York, NY, United States; Institute for Implementation Science, City University of New York, New York, NY, United States.
⁵ New York City Department of Health and Mental Hygiene, New York, NY, United States.

PMID: 37119694
DOI: 10.1016/j.healthplace.2023.103029

Abstract

Exploring the intersection of dimensions of social identity is critical for understanding drivers of health inequities. We used multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to examine the intersection of age, race/ethnicity, education, and nativity status on infant birthweight among singleton births in New York City from 2012 to 2018 (N = 725,875). We found evidence of intersectional effects of various systems of oppression on birthweight inequities and identified U.S.-born Black women as having infants of lower-than-expected birthweights. The MAIHDA approach should be used to identify intersectional causes of health inequities and individuals affected most to develop policies and interventions redressing inequities.

Keywords: Birthweight; Health inequities; Intersectionality; MAIHDA; Multilevel models.

MeSH terms

Birth Weight*
Educational Status
Female
Health Status Disparities*
Humans
Intersectional Framework
Multilevel Analysis
New York City
Social Determinants of Health