Warm Season and Emergency Department Visits to U.S. Children's Hospitals

Abstract

Background: Extreme heat exposures are increasing with climate change. Health effects are well documented in adults, but the risks to children are not well characterized.

Objectives: We estimated the association between warm season (May to September) temperatures and cause-specific emergency department (ED) visits among U.S. children and adolescents.

Methods: This multicenter time-series study leveraged administrative data on $3.8\text{million}$ ED visits by children and adolescents $\le 18\text{years}$ of age to the EDs of 47 U.S. children's hospitals from May to September from 2016 to 2018. Daily maximum ambient temperature was estimated in the county of the hospital using a spatiotemporal model. We used distributed-lag nonlinear models with a quasi-Poisson distribution to estimate the association between daily maximum temperature and the relative risk (RR) of ED visits, adjusting for temporal trends. We then used a random-effects meta-analytic model to estimate the overall cumulative association.

Results: Extreme heat was associated with an RR of all-cause ED visits of 1.17 (95% CI: 1.12, 1.21) relative to hospital-specific minimum morbidity temperature. Associations were more pronounced for ED visits due to heat-related illness including dehydration and electrolyte disorders ($\text{RR}=$ 1.83; 95% CI: 1.31, 2.57), bacterial enteritis (1.35; 95% CI: 1.02, 1.79), and otitis media and externa (1.30; 95% CI: 1.11, 1.52). Taken together, temperatures above the minimum morbidity temperature accounted for an estimated 11.8% [95% empirical 95% confidence interval (eCI): 9.9%, 13.3%] of warm season ED visits for any cause and 31.0% (95% eCI: 17.9%, 36.5%) of ED visits for heat-related illnesses.

Conclusion: During the warm season, days with higher temperatures were associated with higher rates of visits to children's hospital EDs. Higher ambient temperatures may contribute to a significant proportion of ED visits among U.S. children and adolescents. https://doi.org/10.1289/EHP8083.

Figure 1.

Map showing the locations of participating children’s hospitals ($n=47$), median numbers of ED visits among children and adolescents $\le 18\text{\hspace{0.17em}years}$ of age, and mean daily maximum temperatures during May to September from 2016 to 2018. Note: ED, emergency department; $T_{\max }$; mean daily maximum temperature.

Figure 2.

RRs and 95% CIs of the association of specific causes of emergency department visits with $T_{\max }$. RRs contrast the 95th percentile of the hospital-specific warm season (May to September) $T_{\max }$ distribution to the hospital-specific minimum morbidity temperature (MMT) over lag 0–7 d among 47 participating children’s hospitals from May to September from 2016 to 2018. The temperature–ED visit association was modeled with a quasi-Poisson regression with distributed-lag nonlinear model for each hospital, controlling for temporal trends, seasonality, relative humidity, federal holidays, and day of the week. RRs are then pooled across the 47 participating hospitals using multivariate random-effect meta-analyses with hospital-specific mean and range of temperatures as the predictors. Note: CI, confidence interval; RR, relative risk; $T_{\max }$, mean daily maximum temperature.

Figure 3.

Pooled RRs and 95% CIs of ED visits for all causes and heat-related illness overall and stratified by patient demographics. RRs contrast the 95th percentile of the hospital-specific warm season (May to September) $T_{\max }$ distribution to the hospital-specific minimum morbidity temperature (MMT), over lag 0–7 d, 2016–2018. The temperature–ED visit association was modeled with a quasi-Poisson distribution with a distributed-lag nonlinear model for each hospital, controlling for temporal trends, seasonality, humidity, and day of the week. RRs were then pooled across the 47 participating hospitals using random-effect meta-analyses. We calculated ${\mathbf{\chi }}_2^{\text{Wald}}$ based on stratum-specific RRs and the pooled RR. We obtained the $p$-value for the heterogeneity based on the statistic in a ${\mathrm{\chi }}^2$ table. A Wald test with $p<0.05$ was considered as indicative of heterogeneity across strata. See Tables S3 and S4 for results for other specific causes. Note: CI, confidence interval; ED, emergency department; RR, relative risk; $T_{\max }$, mean daily maximum temperature; N.A., not available.