Measuring early childhood health and health disparities: A new approach

Efforts to improve the health of U.S. children and reduce disparities have been hampered by lack of a rigorous way to summarize the multi-dimensional nature of children's health. This research employed a novel statistical approach to measurement to provide an integrated, comprehensive perspective on early childhood health and disparities. Nationally-representative data (n = 8,800) came from the Early Childhood Longitudinal Study, Birth Cohort. Latent class analysis was used to classify health at 48 months, incorporating health conditions, functioning, and aspects of physical, cognitive, and emotional development. Health disparities by gender, poverty, race/ethnicity, and birthweight were examined. Over half of all children were classified as healthy using multidimensional latent class methodology; others fell into one of seven less optimal health statuses. The analyses highlighted pervasive disparities in health, with poor children at increased risk of being classified into the most disadvantaged health status consisting of chronic conditions and a cluster of developmental problems including low cognitive achievement, poor social skills, and behavior problems. Children with very low birthweight had the highest rate of being in the most disadvantaged health status (25.2 %), but moderately low birthweight children were also at elevated risk (7.9 vs. 3.4 % among non-low birthweight children). Latent class analysis provides a uniquely comprehensive picture of child health and health disparities that identifies clusters of problems experienced by some groups. The findings underscore the importance of continued efforts to reduce preterm birth, and to ameliorate poverty's effects on children's health through access to high-quality healthcare and other services.