Background: High atmospheric temperature has been associated with the occurrence of bacillary dysentery (BD). Recent studies have suggested that hot extremes may influence health outcomes, however, none have examined the association between hot extremes and BD risk, especially at the national level.
Objectives: To assess the effect and attributable burden of hot extremes on BD cases and to identify populations at high risk of BD.
Methods: Daily incident BD data of 31 provincial capital cities from 2010 to 2018 were collected from the Chinese Center for Disease Control and Prevention, weather data was obtained from the fifth generation of the European Re-Analysis Dataset. Three types of hot extremes, including hot day, hot night, and hot day and night, were defined according to single or sequential occurrence of daytime hot and nighttime hot within 24 h. A two-stage analytical strategy combined with distributed lag non-linear models (DLNM) was used to evaluate city-specific associations and national pooled estimates.
Results: Hot extremes were significantly associated with the risk of BD on lagged 1-6 days. The overall cumulative relative risk (RR) was 1.136 [95% confidence interval (CI): 1.022, 1.263] for hot day, 1.181 (95% CI: 1.019, 1.369) for hot night, and 1.154 (95% CI: 1.038, 1.283) for hot day and night. Northern residents, females, and children younger than or equal to 14 years old were vulnerable under hot night, southern residents were vulnerable under hot day, and males were vulnerable under hot day and night. 1.854% (95% CI: 1.294%, 2.205%) of BD cases can be attributable to hot extremes, among which, hot night accounted for a large proportion.
Conclusions: Hot extremes may significantly increase the incidence risk and disease burden of BD. Type-specific protective measures should be taken to reduce the risk of BD, especially in those we found to be particularly vulnerable.
Keywords: Bacillary dysentery; Distributed lag non-linear model; Hot extremes.
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