Propensity Scores: Method for Matching on Multiple Variables in Down Syndrome Research

Confounding variables can affect the results from studies of children with Down-syndrome and their families. Traditional methods for addressing confounders are often limited, providing control for only a few confounding variables. This study introduces propensity score matching to control for multiple confounding variables. Using Tennessee birth data as an example, newborns with Down syndrome were compared with a group of typically developing infants on birthweight. Three approaches to matching on confounders-nonmatched, covariate matched, and propensity matched-were compared using 8 potential confounders. Fewer than half of the newborns with Down syndrome were marched using covariate matching, and the matched group was differed from the unmatched newborns. Using propensity scores, 100% of newborns with Down syndrome could be matched to a group of comparison newborns, a decreased effect size was found on newborn birthweight, and group differences were not statistically significant.