Association between ambient air pollution and daily hospital visits for cardiovascular diseases in Wuhan, China: a time-series analysis based on medical insurance data.

Although evidence showed the adverse effects of air pollution on cardiovascular disease (CVDs), few studies were based on medically insured populations. We applied a generalized additive Poisson model (GAM) to estimate the short-term effects of ambient air pollution on a group of medically insured population in Wuhan, China. We extracted daily air pollution data, meteorological data, and daily hospital visits for CVDs. We found that the ambient air pollutants sulfur dioxide (SO2), nitrogen dioxide (NO2), ground-level ozone (O3) particulate matter (PM) with an aerodynamic diameter ≤10 µm (PM10), and those ≤2.5 µm (PM2.5) all increased the risk of daily hospital visits for CVDs. We also found that the effect of air pollution on daily hospital visits for CVDs is greater in the cold season than in the warm season. Our findings can be used as evidence that supports the formulation of policies for air pollution and CVDs.

Short-term effects of ambient air pollution on the incidence of influenza in Wuhan, China: A time-series analysis.

BACKGROUND: Evidence suggests that air pollution is associated with many adverse health outcomes such as cardiovascular diseases (CVD), respiratory diseases, cancer, and birth defects. Yet few studies dig into the relationship between air pollution and airborne infectious diseases. METHODS: Daily data on influenza incidence were obtained from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC). Data on air pollutants including nitrogen dioxide (NO2), sulfur dioxide (SO2), ground-level ozone (O3), particulate matter (PM) with aerodynamic diameter ≤ 2.5 µm (PM2.5), and PM with aerodynamic diameter ≤ 10 µm (PM10) were retrieved from ten national air sampling stations located at Wuhan. We applied generalized additive model (GAM) to estimate the associations between air pollution and the risk of influenza in Wuhan, China during 2015-2017. RESULTS: In the single-day lag model, the largest effect estimates were observed at lag 0. An increased relative risk (RR) of influenza was significantly associated with a 10 µg/m3 increase in SO2 (RR: 1.099; 95% confidence interval [CI]: 1.011-1.195), NO2 (RR: 1.039; 95% CI: 1.013-1.065), and O3 (RR: 1.005; 95% CI: 0.994-1.016), respectively. In the multi-day lag model, concentrations of SO2, NO2, and O3 were statistically significantly associated with the risk of influenza at lag 0-1. The seasonal analysis suggests that the influence of air pollution on influenza is greater in the cold season as compared in the warm season in the early lag days. The multi-pollutant model indicates that NO2 may be a potential confounder for co-pollutants. CONCLUSIONS: Our study shows that air pollution may be associated with the risk of influenza in a broad sense. Therefore, when formulating policies to deal with influenza outbreaks in the future, factors regarding air pollution should be taken into consideration.

Association of Short-Term Exposure to Meteorological Factors and Risk of Hand, Foot, and Mouth Disease: A Systematic Review and Meta-Analysis.

(1) Background: Inconsistencies were observed in studies on the relationship between short-term exposure to meteorological factors and the risk of hand, foot, and mouth disease (HFMD). This systematic review and meta-analysis was aimed to assess the overall effects of meteorological factors on the incidence of HFMD to help clarify these inconsistencies and serve as a piece of evidence for policy makers to determine relevant risk factors. (2) Methods: Articles published as of 24 October 2020, were searched in the four databases, namely, PubMed, Web of Science, Embase, and MEDLINE. We applied a meta-analysis to assess the impact of ambient temperature, relative humidity, rainfall, wind speed, and sunshine duration on the incidence of HFMD. We conducted subgroup analyses by exposure metrics, exposure time resolution, regional climate, national income level, gender, and age as a way to seek the source of heterogeneity. (3) Results: Screening by the given inclusion and exclusion criteria, a total of 28 studies were included in the analysis. We observed that the incidence of HFMD based on the single-day lag model is significantly associated with ambient temperature, relative humidity, rainfall, and wind speed. In the cumulative lag model, ambient temperature and relative humidity significantly increased the incidence of HFMD as well. Subgroup analysis showed that extremely high temperature and relative humidity significantly increased the risk of HFMD. Temperate regions, high-income countries, and children under five years old are major risk factors for HFMD. (4) Conclusions: Our results suggest that various meteorological factors can increase the incidence of HFMD. Therefore, the general public, especially susceptible populations, should pay close attention to weather changes and take protective measures in advance.