BackgroundAlthough the association between short-term air pollution exposure and certain hospitalizations has been well documented, evidence on the effect of longer-term (e. g., monthly) air pollution on a comprehensive set of outcomes is still limited.MethodA total of 68,416 people in South China were enrolled and followed up during 2019–2020. Monthly air pollution level was estimated using a validated ordinary Kriging method and assigned to individuals. Time-dependent Cox models were developed to estimate the relationship between monthly PM10 and O3 exposures and the all-cause and cause-specific hospitalizations after adjusting for confounders. The interaction between air pollution and individual factors was also investigated.ResultsOverall, each 10 μg/m3 increase in PM10 concentration was associated with a 3.1% (95%CI: 1.3%−4.9%) increment in the risk of all-cause hospitalization. The estimate was even greater following O3 exposure (6.8%, 5.5%−8.2%). Furthermore, each 10 μg/m3 increase in PM10 was associated with a 2.3%-9.1% elevation in all the cause-specific hospitalizations except for those related to respiratory and digestive diseases. The same increment in O3 was relevant to a 4.7%−22.8% elevation in the risk except for respiratory diseases. Additionally, the older individuals tended to be more vulnerable to PM10 exposure (Pinteraction: 0.002), while the alcohol abused and those with an abnormal BMI were more vulnerable to the impact of O3 (Pinteraction: 0.052 and 0.011). However, the heavy smokers were less vulnerable to O3 exposure (Pinteraction: 0.032).ConclusionWe provide comprehensive evidence on the hospitalization hazard of monthly PM10 and O3 exposure and their interaction with individual factors.

Background: Meteorological exposures are well-documented factors underlying the dengue pandemics, and air pollution was reported to have the potential to change the behaviors and health conditions of mosquitos. However, it remains unclear whether air pollution could modify the association of meteorological exposures and the incidence of dengue fever. Method: We matched the dengue surveillance data with the meteorological and air pollution data collected from monitoring sites from 2015 through 2019 in Guangzhou area. We developed generalized additive models with Poisson distribution to regress the daily counts of dengue against four meteorological exposures, while controlling for pollution and NDVI to evaluate the risk ratio (RR) of dengue for each unit increase in different exposures. The interaction terms of meteorological exposures and air pollution were then included to assess the modification effect of different pollution on the associations. Results: Daily dengue cases were nonlinearly associated with one-week cumulative temperature and precipitation, while not associated with humidity and wind speed. RRs were 1.07 (1.04, 1.11) and 0.95 (0.88, 1.03) for temperature below and above 27.1℃, 0.97 (0.96, 0.98) and 1.05 (1.01, 1.08) for precipitation below and above 20.3mm, respectively. For the modification effect, the RRs of low-temperature, wind speed on higher SO2 days and low-precipitation on both higher PM2.5 and SO2 days were greater compared to the low-pollution days with Pinteraction being 0.037, 0.030, 0.022 and 0.018. But the RRs of both high-temperature on higher SO2 days and high-precipitation on higher PM2.5 days were smaller with Pinteraction being 0.001 and 0.043. Conclusion: Air pollution could alter the meteorology-dengue associations. The impact of low-temperature, low-precipitation and wind speed on dengue occurrence tended to increase on days with high SO2 levels while the impact of high-temperature decreased. The impact of low-precipitation increased on high-PM2.5 days while the impact of high-precipitation decreased.