Evaluation of heat warning thresholds with multiple lagged and cumulative health impacts based on a 20-year population database.

Heat warning systems represent a critical health adaptation strategy under global boiling. This study evaluates the appropriateness of the existing criteria of heat warning categories, which were established based on climatology. The objectives were (1) to evaluate the association of the daily maximum temperature (Tmax) and multiple health outcomes (including emergency visits, hospitalization cases, and mortality of heat-related illness (HRI), cardiovascular, respiratory, diabetes, and renal diseases) considering both the lag and cumulative effects, and (2) to identify vulnerable groups (considering their demographic, occupation, geographic, and health status) and areas of heat-health impacts. Weather and health records in Taiwan from May to October from 2000 to 2019 were analyzed using generalized additive models. The results show that HRI was the most sensitive health outcome, and the relative risk (RR) was 1.81 (confidence interval (CI): 1.51 - 2.18) and 2.99 (CI: 1.99 - 4.49) for emergency visits and hospitalizations, respectively, when Tmax was ≥ 34 °C. The corresponding RRs were 2.00 (CI: 1.67 - 2.39) and 2.39 (CI: 1.44 - 3.95) when Tmax was ≥ 32 and ≥ 31 °C for three consecutive days, respectively. The morbidity risks of cardiovascular, respiratory, diabetes, and renal diseases all increased at different temperature thresholds. Significant associations between Tmax and health outcomes occurred at thresholds lower than the current warning thresholds, indicating the need for revision. Both lag and cumulative effects need to be considered in heat-health warning systems. People with hypertension, hyperglycemia, or hyperlipidemia were found to be more vulnerable, as they had higher RRs for pneumonia, COPD, and stroke than the general population. Among different occupations, farmers were found to be most vulnerable. This study demonstrates a methodology considering both lag and cumulative effects that can be applied in other countries to assist in the establishment of evidence-based heat-health warning systems.