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.
View Article and Find Full Text PDFDepression in adolescents and young adults remains a pressing public health concern and there is increasing interest in evaluating population-level inequalities in depression intersectionally. A recent advancement in quantitative methods-multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA)-has many practical and theoretical advantages over conventional models of intercategorical intersectionality, including the ability to more easily evaluate numerous points of intersection between axes of marginalization. This study is the first to apply the MAIHDA approach to investigate mental health outcomes intersectionally in any population.
View Article and Find Full Text PDFBackground: Although meningitis is rare in previously healthy term infants, lumbar puncture is often performed to evaluate for source of illness. This study was performed to determine the time to detection for positive cerebrospinal fluid (CSF) cultures and to provide an update on the current epidemiology of bacterial meningitis in term infants.
Methods: This study was a multicenter, retrospective review of positive CSF cultures in infants ≤90 days of age.