Objective: To quantify the association between heat and infant mortality and identify factors that influence infant vulnerability to heat.
Methods: We conducted a time-stratified case-crossover analysis of associations between ambient temperature and infant mortality in Philadelphia, Pennsylvania, during the warm months of 2000 through 2015. We used conditional logistic regression models to estimate associations of infant mortality with daily temperatures on the day of death (lag 0) and for averaging periods of 0 to 1 to 0 to 3 days before the day of death. We explored modification of associations by individual and census tract-level characteristics and by amounts of green space.
Results: Risk of infant mortality increased by 22.4% (95% confidence interval [CI] = 5.0%, 42.6%) for every 1°C increase in minimum daily temperature over 23.9°C on the day of death. We observed limited evidence of effect modification across strata of the covariates.
Conclusions: Our results contribute to a growing body of evidence that infants are a subpopulation that is particularly vulnerable to climate change effects. Further research using large data sets is critically needed to elucidate modifiable factors that may protect infants against heat vulnerability.