Statistical methods
The data were analyzed using R version 4.0.2. No overall prospective analysis plan was used. Demographic characteristics were derived for the cohort and each Apgar score group (low, intermediate, normal), with frequencies and percentages reported for categorical variables and means and standard deviations reported for continuous variables.
Univariate logistic regression models were used to quantify the association between each racial group and odds of being assigned a low Apgar score (low versus not low), being assigned an intermediate Apgar score (intermediate versus not intermediate) and to quantify the association between race group and each mortality outcome (early neonatal mortality, neonatal mortality, and infant mortality). Univariate logistic regression models were also used to assess the crude association between each covariate and the mortality outcomes, stratified by race group.
Multivariable logistic regression models were conducted to determine the association between Apgar score and each mortality outcome in the total population and stratified by race group. We formally assessed whether there was evidence that the association between Apgar score and mortality varied by race group by including an interaction term in the adjusted model in the total population. Additionally, we conducted a chi-squared test to determine whether there were trends between Apgar score category and early neonatal, overall neonatal, and infant mortality rates among each race group.
Citation: Gillette E, Boardman JP, Calvert C, John J, Stock SJ (2022) Associations between low Apgar scores and mortality by race in the United States: A cohort study of 6,809,653 infants. PLoS Med 19(7): e1004040. https://doi.org/10.1371/journal.pmed.1004040
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