Exposure to Ambient Air Pollutions and Upper Respiratory Tract Infection in Zhengzhou City, China: A Approximate Five-Year Surveillance Study
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Abstract Background: Studies indicated that air pollutions were associated with respiratory disease have with a lag exposure–response relationship, but not linear. However, few evidences in Zhengzhou, one of the most polluted cities for China. Method: Upper respiratory tract infection (URTI) outpatient visits in the hospital, meteorological parameters and air pollutions data were obtained from October 28, 2013 to May 1, 2018 and were used for evaluating the risk effects of the air pollutants with a distributed lag non-linear model (DLNM), including the stratified analysis of gender and age. Result: 475013 cases were included, with obvious seasonal fluctuations,higher in cool/cold and lower in warm. Every increase of 10μg/m 3 of PM 2.5 , PM 10 , SO 2 , NO 2 and CO showed similar impacts on URTI outpatient visits in different genders and age sub-groups,within 0 to15 days of lag. PM 10 , SO 2 and NO 2 had the strongest immediately risk at lag 0 [RR PM10 : 1.0011, 95%CI (1.0002-1.0020); RR SO2 : 1.0084, 95%CI (1.0039-1.0130); RR NO2 : 1.0149, 95%CI: (1.0111-1.0188), respectively], while PM 2.5 and CO got highest risk at lag 15 days [RR PM2.5 : 1.0014, 95%CI (1.0003-1.0025); RR CO : 1.0002, 95%CI: (1.0001-1.0003), respectively]. In addition, calculating overall accumulated effects of each 10μg/m3 increase in PM 10 , SO 2 , NO 2 , and CO was greater in females than in males, as well as greater in the adolescents (aged 0-18 years) and elderly (aged ≥ 60 years) than in adults (aged 19-59 years), except CO was greater in the adolescents and adults than in the elderly. No significant cumulative effects were found in PM 2.5 . O 3 levelwasno significant correlation withURTI outpatient visits throughout the lag period. Conclusions: Our results indicated that PM 10 , SO 2 , NO 2 and CO had strong immediate and lag cumulative effects in the females, adolescents, and elderly. PM 2.5 has lag effects but has no significant lag cumulative impact effects on gender and age.Keywords:
Distributed lag
Lag time
Outpatient visits
Respiratory tract
Short-term exposure to air pollution has been associated with ischemic stroke (IS) hospitalizations, but the evidence of its effects on IS in low- and middle-income countries is limited and inconsistent. We aimed to quantitatively estimate the association between air pollution and hospitalizations for IS in Chongqing, China. This time series study included 2,299 inpatients with IS from three hospitals in Chongqing from January 2015 to December 2016. Generalized linear regression models combined with a distributed lag nonlinear model (DLNM) were used to investigate the impact of air pollution on IS hospitalizations. Stratification analysis was further implemented by sex, age, and season. The maximum lag-specific and cumulative percentage changes of IS were 1.2% (95% CI: 0.4–2.1%, lag 3 day) and 3.6% (95% CI: 0.5–6.7%, lag 05 day) for each 10 μg/m 3 increase in PM 2.5 ; 1.0% (95% CI: 0.3–1.7%, lag 3 day) and 2.9% (95% CI: 0.6–5.2%, lag 05 day) for each 10 μg/m 3 increase in PM 10 ; 4.8% (95% CI: 0.1–9.7%, lag 4 day) for each 10 μg/m 3 increase in SO 2 ; 2.5% (95% CI: 0.3–4.7%, lag 3 day) and 8.2% (95% CI: 0.9–16.0%, lag 05 day) for each 10 μg/m3 increase in NO 2 ; 0.7% (95% CI: 0.0–1.5%, lag 6 day) for each 10 μg/m 3 increase in O 3 . No effect modifications were detected for sex, age, and season. Our findings suggest that short-term exposure to PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 contributes to more IS hospitalizations, which warrant the government to take effective actions in addressing air pollution issues.
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Stroke
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Abstract The objective of this study was to investigate the potential association between air pollutants and respiratory diseases (RDs). Generalized additive models were used to analyze the effect of air pollutants on mortalities or outpatient visits. The average concentrations of air pollutants in Hangzhou (HZ) were 1.6–2.8 times higher than those in Zhoushan (ZS), except for O 3 . In a single pollutant model, the increased concentrations of PM 2.5 , NO 2 , and SO 2 were strongly associated with deaths caused by RD in HZ, while PM 2.5 and O 3 were associated with deaths caused by RD in ZS. All air pollutants (PM 2.5 , NO 2 , SO 2 , and O 3 ) were strongly associated with outpatient visits for RD in both HZ and ZS. In multiple pollutant models, a significant association was only observed between PM 2.5 and the mortality rate of RD patients in both HZ and in ZS. Moreover, strong associations between SO 2 , NO 2 , and outpatient visits for RD were observed in HZ and ZS. This study has provided evidence that both the mortality rates and outpatient visits for RD were significantly associated with air pollutants. Furthermore, the results showed that different air pollutant levels lead to regional differences between mortality rates and outpatient visits.
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Few studies on population-specific health effects of extreme temperature on cardiovascular diseases (CVDs) deaths have been conducted in the subtropical and tropical climates of China. We examined the association between extreme temperature and CVD across four cities in China. We performed a two-stage analysis; we generated city-specific estimates using a distributed lag non-linear model (DLNM) and estimated the overall effects by conducting a meta-analysis. Heat thresholds of 29 °C, 29 °C, 29 °C, and 30 °C and cold thresholds of 6 °C, 10 °C, 14 °C, and 15 °C were observed in Hefei, Changsha, Nanning, and Haikou, respectively. The lag periods for heat-related CVD mortality were observed only for 0–2 days, while those of cold-related CVD mortality were observed for 10–15 days. The meta-analysis showed that a 1 °C increase above the city-specific heat threshold was associated with average overall CVD mortality increases of 4.6% (3.0%–6.2%), 6.4% (3.4%–9.4%), and 0.2% (−4.8%–5.2%) for all ages, ≥65 years, and <65 years over a lag period of 0–2 days, respectively. Similarly, a 1 °C decrease below the city-specific cold threshold was associated with average overall CVD mortality increases of 4.2% (3.0%–5.4%), 4.9% (3.5%–6.3%), and 3.1% (1.7%–4.5%), for all ages, ≥65 years, and <65 years over a lag period of 0–15 days, respectively. This work will help to take appropriate measures to reduce temperature-mortality risk in different populations in the subtropical and tropical climates of China.
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This study examined the short-term relationship between ambient air pollutants and children's outpatient visits, and identified the effect of modifications by season. Daily recordings of air pollutants (CO, NO2, O3, SO2, PM10, and PM2.5) and children's outpatient visit data were collected in Guangzhou from 2015 to 2019. A generalized additive model adjusted for potential confounding was introduced to verify the association between ambient air pollution and outpatient visits for children. Subgroup analysis by season was performed to evaluate the potential effects. A total of 5,483,014 children's outpatient visits were recorded. The results showed that a 10 μg/m3 increase in CO, NO2, O3, SO2, PM10, and PM2.5 corresponded with a 0.19% (95% CI: 0.15-0.24%), 2.46% (2.00-2.92%), 0.27% (0.07-0.46%), 7.16% (4.80-9.57%), 1.16% (0.83-1.49%), and 1.35% (0.88-1.82%) increase in children's outpatient visits on the lag0 of exposure, respectively. The relationships were stronger for O3, PM10, and PM2.5 in the warm seasons, and for CO, NO2, and SO2 in the cool seasons. When adjusting for the co-pollutants, the effects of CO, NO2, and PM10 were robust. The results of this study indicate that six air pollutants might increase the risk of children's outpatient visits in Guangzhou, China, especially in the cool season.
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Objectives: This study aimed to investigate the associations between air pollution exposure and pediatric outpatient visits for dry eye disease (DED) in Shenzhen, China. Methods: Generalized additive models were utilized to explore the acute effects of air pollution exposure on pediatric outpatient visits for DED. Results: Single-day lag exposures to NO 2 , O 3 , PM 2.5 , and PM 10 were associated with DED outpatient visits at lag days 0, 6, 4 and 2. Relative risks (RRs) for DED given a 10-μg/m 3 increase in NO 2 , O 3 , PM 2.5 , and PM 10 concentrations were 1.062[95% confidence interval (CI) 1.003, 1.123], 1.015(95% CI 1.001, 1.031), 1.052(95% CI 1.001, 1.115), and 1.038 (95% CI 1.002, 1.076), respectively. RR for DED given a 10-μg/m 3 increase in NO 2 over cumulative lag days 0–1 was 1.075 (95% CI 1.009, 1.147), and RR for DED given a 10-μg/m 3 increase in PM 10 over cumulative lag days 0–4 was 1.051 (95% CI 1.003, 1.102). Conclusion: The observed associations between air pollution and outpatient visits for DED may provide evidence for policy makers to consider implementing measures to reduce the risk of DED owing to air pollution in China.
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To determine the time-lag effect of meteorological factors on the relative risk (RR) of dengue incidence in Coronel Fabriciano city, Brazil, we applied a distributed lag nonlinear model, a modeling framework that can simultaneously represent nonlinear exposure–response dependencies and delayed effects, to establish the association between dengue incidence and weather predictors. The weekly number of notified dengue cases during the period 2004–2010 was used for analysis. When considering the rainfall, the highest RR (1.2) was observed for lag 10. Observing the cumulative effect of the precipitation, the RR for 12th and 13th week was RR = 4. The highest risk, 1.25, was observed at 25 °C, denoting that the risk of dengue transmission increases with temperature. Climate-based models that take into account the time lag between rainfall, temperature, and dengue can be useful in dengue control programs to be applied in tropical countries.
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Background Ambient temperature change is a risk factor for urolithiasis that cannot be ignored. The association between temperature and urolithiasis varies from region to region. Our study aimed to analyze the impact of extremely high and low temperatures on the number of inpatients for urolithiasis and their lag effect in Ganzhou City, China. Methods We collected the daily number of inpatients with urolithiasis in Ganzhou from 2018 to 2019 and the meteorological data for the same period. The exposure-response relationship between the daily mean temperature and the number of inpatients with urolithiasis was studied by the distributed lag non-linear model (DLNM). The effect of extreme temperatures was also analyzed. A stratification analysis was performed for different gender and age groups. Results There were 38,184 hospitalizations for urolithiasis from 2018 to 2019 in Ganzhou. The exposure-response curve between the daily mean temperature and the number of inpatients with urolithiasis in Ganzhou was non-linear and had an observed lag effect. The warm effects (30.4°C) were presented at lag 2 and lag 5–lag 9 days, and the cold effects (2.9°C) were presented at lag 8 and lag 3–lag 4 days. The maximum cumulative warm effects were at lag 0–10 days (cumulative relative risk, CRR = 2.379, 95% CI: 1.771, 3.196), and the maximum cumulative cold effects were at lag 0–5 (CRR = 1.182, 95% CI: 1.054, 1.326). Men and people between the ages of 21 and 40 were more susceptible to the extreme temperatures that cause urolithiasis. Conclusion Extreme temperature was correlated with a high risk of urolithiasis hospitalizations, and the warm effects had a longer duration than the cold effects. Preventing urolithiasis and protecting vulnerable people is critical in extreme temperature environments.
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In this note the supply responses in maize and wheat production are estimated from distributed lag models. The Nerlove model and the Fisher distributed lag model fit Kenyan data but more complicated models, like the polynomial lag model, do not. The calculated price elasticities suggest that Kenyan large‐scale farmers are highly responsive to price changes. Some policy implications are drawn from the analysis.
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Abstract Previous studies have shown that air pollutants have a significant impact on cardiovascular and cerebrovascular diseases (CCD), but these studies have focused more on provincial capitals or large cities. This study was the first time to explore the effects of air pollutants on CCD in Luoyang. In this study, the generalized additive model (GAM) was used to establish a single‐pollutant model, a multi‐pollutant model and stratified modes of age, sex and season to evaluate the effects of PM 2.5 , PM 10 , SO 2 , NO 2 , CO and O 3 on outpatient visits for CCD within a week. The results of the single‐pollutant model showed that PM 2.5 , PM 10 , SO 2 , NO 2 , CO and O 3 all had significant effects on the outpatient visits for CCD with a lag effect. The multi‐pollutant model showed that there might be complex interactions among pollutants. The results of the stratified model showed that there was no significant difference in the effects of different pollutants on different genders and ages, and the results of seasonal stratification showed that PM 2.5 , PM 10 , SO 2 and CO had a greater influence on the outpatient visits for CCD in spring and summer, while NO 2 and O 3 had a greater influence on the outpatient visits for CCD in winter and summer, respectively. The results showed that air pollutants significantly affected outpatient visits for CCD, among which NO 2 had the greatest influence, and seasonal effects and the combined effects of various pollutants should be considered in strategies for the prevention of CCD.
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Little is known about the effects of temperature on healthcare-associated infections (HAIs). A distributed lag non-linear model was used to estimate the association between ambient temperature and HAIs in Hefei, China. In total, 9,592 HAIs were included. The effect of low temperature (-0.1°C, 2.5th percentile) was significant on the current day (RR = 1.108, 95%CI:1.003-1.222), and then appeared on the 4th day (RR = 1.045, 95%CI:1.007-1.084) and the 5th day (RR = 1.033, 95%CI:1.006-1.061). The cumulative lag effects of low temperature lasted from the 5th to 10th days (RR = 1.123-1.143), and a long-term cumulative lag effect was observed on the 14th day (RR = 1.157, 95%CI:1.001-1.338). The lag effect of high temperature (31.0°C, 97.5th percentile) was not statistically significant. However, the effects of temperatures on HAIs were not significant among gender or age subgroups. This study suggests that the low temperatures have acute and lag effects on HAIs in Hefei, China.
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