Background: The emerging cases of childhood scarlet fever (SF) and worsening air pollution problems in Chinese cities suggests a potential linkage between them. However, few studies had explored this association in a large childhood population.
Methods: We conducted a time-series analysis using the daily count of SF and the daily concentrations of particulate matters with an aerodynamic diameter of 2.5 (PM2.5) and 10 (PM10), as well as nitrogen dioxide (NO2) in Hangzhou, China from 2014 to 2018. Distributed lag nonlinear models were used to estimate the lag effects of PM2.5, PM10 and NO2 for a maximum lag of 10 days, which were quantified using relative risk (RR) comparing the adjusted risks at the 2.5th (extremely low effect) and 97.5th (extremely high effect) percentiles of concentration of the three air pollutants to that at the median. Stratified RRs by sex were also reported.
Results: Using the median concentration as reference, for extremely high effect, the RR was the highest on lag days 5, 6, and 3 for PM2.5, PM10, and NO2 respectively. While on lag day 0, the RR of PM2.5, PM10, and NO2 were 1.04 (95%CI: 0.90-1.20), 1.07 (95%CI: 0.92-1.24), and 1.08 (95%CI: 0.92-1.26) respectively, the RRs increased constantly and cumulatively to the maximum values of 1.88 (95%CI: 1.33-2.66), 1.82 (95%CI: 1.29-2.55), and 2.19 (95%CI: 1.47-3.27) for PM2.5, PM10, and NO2 respectively on lag day 10. Subgroup analyses showed that females appeared to be more vulnerable to the three pollutants than males.
Conclusion: Our study provides evidence that PM2.5, PM10, and NO2 exert delayed effects on SF infection.
Keywords: Air pollution; Distributed lag nonlinear models; NO(2); PM(10); PM(2.5); Scarlet fever.
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