Assesses air pollution's effects on respiratory health in Nakhon Ratchasima, suggesting economic benefits from pollution reduction.
Thailand provinces have been experiencing rising air pollution, though few studies have explored their association with respiratory morbidity and mortality. This study aimed to examine the association between respiratory morbidity and mortality and short-term exposure to ambient air pollution in Nakhon Ratchasima Municipality (NRM), Thailand. Data on daily respiratory morbidity and mortality, criterion air pollutants, and meteorological variables were collected for the period 2019–2021. Associations were assessed using Generalized additive models (GAMs) and distributed lag nonlinear models (DLNMs). The results confirmed a significant association between short-term air pollution exposure and respiratory mortality and morbidity in NRM. Multi-pollutant GAMs indicated that a 10 μg/m 3 increase in PM 2.5 , was associated with a 2% increase in respiratory morbidity at lag 0 and lag 0–1. Also, a 10 μg/m 3 increase in PM 10 was associated with 3% and 2% increases in respiratory morbidity at lag5 and lag 0–6, respectively. Both SO 2 and CO exhibited prolonged effects on respiratory morbidity. Results from single-pollutant models incorporating PM 2.5 and PM 10 were consistent with the findings. DLNM analyses further showed that PM 2.5 exerted both immediate and delayed cumulative effects, whereas the effects of PM₁₀ predominantly emerge after a short delay and accumulated over subsequent lag days. The study demonstrated that air pollution control measures could substantially reduce the economic burden of respiratory diseases in NRM, yielding potential economic benefits of up to 222 million THB. • NRM involved the evaluation of short-term effects of air pollution on health with GAM and DLNM models. • The exposure to PM 2.5 and PM 10 caused high respiratory morbidity and mortality. • SO 2 and CO had a delayed lag effect on respiratory health outcomes in NRM. • As much as 222 million THB in economic losses would be saved by reduction in air pollution.
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Dutta et al. (2026) studied this question.
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