Environmental factors have been associated with adverse health effects in epidemiological studies. The main exposure variable is usually determined via prior knowledge or statistical methods. It may be challenging when evidence is scarce to support prior knowledge, or to address collinearity issues using statistical methods. This study aimed to investigate the importance level of environmental variables for the under-five mortality in Malaysia via random forest approach. We applied a conditional permutation importance via a random forest (CPI-RF) approach to evaluate the relative importance of the weather- and air pollution-related environmental factors on daily under-five mortality in Malaysia. This study spanned from January 1, 2014 to December 31, 2016. In data preparation, deviation mortality counts were derived through a generalized additive model, adjusting for long-term trend and seasonality. Analyses were conducted considering mortality causes (all-cause, natural-cause, or external-cause) and data structures (continuous, categorical, or all types [i.e., include all variables of continuous type and all variables of categorical type]). The main analysis comprised of two stages. In Stage 1, Boruta selection was applied for preliminary screening to remove highly unimportant variables. In Stage 2, the retained variables from Boruta were used in the CPI-RF analysis. The final importance value was obtained as an average value from a 10-fold cross-validation. Some heat-related variables (maximum temperature, heat wave), temperature variability, and haze-related variables (PM10, PM10-derived haze index, PM10- and fire-derived haze index, fire hotspot) were among the prominent variables associated with under-five mortality in Malaysia. The important variables were consistent for all- and natural-cause mortality and sensitivity analyses. However, different most important variables were observed between natural- and external-cause under-five mortality. Heat-related variables, temperature variability, and haze-related variables were consistently prominent for all- and natural-cause under-five mortalities, but not for external-cause.

Fire emits hazardous air pollutants, the most dominant of which is fine particulate matter of diameter ⩽2.5 μm (PM_2.5). PM_2.5 is a great concern due to its adverse effects on public health. Previous studies have examined the health burden from fire-related PM_2.5 for the historical period; however, future global mortality associated with fire-PM_2.5, particularly under the coexisting impacts of climate and socioeconomic changes, is yet to be projected. Here, we estimated the mortality associated to fire-PM_2.5 (fire-PM_2.5 mortality) for the present period (2010s) and then projected the mortality for the 2050s and 2090s under 10 scenarios created by combining two Representative Concentration Pathways (RCP2.6 or 6.0) with five Shared Socioeconomic Pathways (SSP1–5). We used the Li-Park fire model in combination with a chemical transport model and health risk assessment to calculate fire-PM_2.5 mortality. For the present period, the estimated fire-PM_2.5 mortality was 135 180 (105 403–163 738), which is 1.7 deaths per 100 000 population globally. When countries were grouped by income, the fire-PM_2.5 mortality rate was the highest in the high-income country group and lowest in the lowest-income country group. For the 2050s and 2090s, the fire-PM_2.5 mortality rate was projected to decrease under most scenarios because of decreases in fire emissions and baseline mortality rate. However, a scenario of high population growth and low technical development (SSP3) together with severe global warming (RCP6.0) would lead to an increase in the fire-PM_2.5 mortality rate in the 2090s, particularly in the highest-income countries, due to increased fire under drier and warmer weather conditions. Stratification of countries by gross domestic product indicated the need for adaptation efforts in the highest-income countries to avoid future increases of mortality associated with fire-PM_2.5.

Short-term health effects of ambient PM_2.5 have been established with numerous studies, but evidence in Asian countries is limited. This study aimed to investigate the short-term effects of PM_2.5 on acute health outcomes, particularly all-cause, cardiovascular, respiratory, cerebrovascular and neuropsychological outcomes. We utilized daily emergency ambulance dispatches (EAD) data from eight Japanese cities (2007–2011). Statistical analyses included two stages: (1) City-level generalized linear model with Poisson distribution; (2) Random-effects meta-analysis in pooling city-specific effect estimates. Lag patterns were explored using (1) unconstrained-distributed lags (lag 0 to lag 7) and (2) average lags (lag: 0–1, 0–3, 0–5, 0–7). In all-cause EAD, significant increases were observed in both shorter lag (lag 0: 1.24% (95% CI: 0.92, 1.56)) and average lag 0–1 (0.64% (95% CI: 0.23, 1.06)). Increases of 1.88% and 1.48% in respiratory and neuropsychological EAD outcomes, respectively, were observed at lag 0 per 10 µg/m³ increase in PM_2.5. While respiratory outcomes demonstrated significant average effects, no significant effect was observed for cardiovascular outcomes. Meanwhile, an inverse association was observed in cerebrovascular outcomes. In this study, we observed that effects of PM_2.5 on all-cause, respiratory and neuropsychological EAD were acute, with average effects not exceeding 3 days prior to EAD onset.