Project description:This study sought to investigate the relationship between meteorological factors and outpatient visits for herpes zoster. In this time-series analysis, we used data from two major hospitals in Hefei, collected between 2015 and 2019, to evaluate the impact of meteorological factors on the risk of herpes zoster. After controlling for confounders, we adopted a distributed lag nonlinear model to probe the relationship between meteorological factors and outpatient visits for herpes zoster. The analysis was stratified according to age (<40 years, ≥40 years) and sex (male, female). A total of 43,547 cases of herpes zoster were reported, and compared with the median value, a high temperature and high relative humidity had a significant risk effect on the incidence of herpes zoster. The maximum harmful effect of high temperature on herpes zoster occurred on the lag0 (RR: 1.027, 95% CI: 1.002-1.053) and further declined over the following days. The cumulative effect increased with the extension of lag days, and the cumulative RR was the largest on the sixth day of lag (RR1.031, 95% CI: 1.006-1.056) when the relative humidity was 85.7% (77.0% as the reference). The stratified analysis results reveal that females and the elderly (≥40 years) were more susceptible to temperature and relative humidity. This study shows that high-temperatures may lead to herpes zoster, indicating that those infected with varicella zoster virus need to take measures over the course of several days when not exposed to the best appropriate temperature conditions.
Project description:Conjunctivitis is a common multifactorial inflammatory ocular surface disease characterized by symptoms such as congestion, edema, and increased secretion of conjunctival tissue, and the potential effects of meteorological factors as well as extreme meteorological factors on conjunctivitis and their lagging effects have not been fully evaluated. We obtained the electronic case information of 59,731 outpatients with conjunctivitis from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China) for the period from January 1, 2013, to December 31, 2020. Meteorological data for daily mean temperature (°C), daily relative humidity (%), daily average wind speed (m/s), and atmospheric pressure (hPa) were obtained from the China Meteorological Data Sharing Service. The air pollutant data were obtained from 11 standard urban background fixed air quality monitors. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effects of exposure to different meteorological factors and extreme weather on conjunctivitis outpatient visits. Subgroup analyses were performed on gender, age and season, and type of conjunctivitis. Univariate and multifactorial model results indicated that each 10-unit increase in mean temperature and relative humidity was associated with an increased risk of conjunctivitis outpatient visits, while each 10-unit increase in atmospheric pressure was associated with a decreased risk. The results of the extreme weather analysis suggested that extremely low levels of atmospheric pressure and relative humidity as well as extreme levels of temperature were associated with an increased risk of outpatient conjunctivitis visits, and extreme wind speeds were associated with a decreased risk. The results of the subgroup analysis suggested gender, age, and seasonal differences. We conducted the first large sample size time-series analysis in the large city furthest from the ocean in the world and confirmed for the first time that elevated mean temperature and extreme low levels of relative humidity in Urumqi were risk factors for local conjunctivitis outpatient visits, while elevated atmospheric pressure and extreme low levels of wind speed were protective factors, and there were lagged effects of temperature and atmospheric pressure. Multicenter studies with larger sample sizes are needed.
Project description:Previous epidemiological studies have linked short-term exposure to particulate matter with outpatient visits for respiratory diseases. However, evidence on ultrafine particle (UFP) is still scarce in China. To investigate the association between short-term UFP exposure and outpatient visits for respiratory diseases as well as the corresponding lag patterns, information on outpatient visits for main respiratory diseases during January 1, 2017, to December 31, 2019 was collected from electronic medical records of two large tertiary hospitals in Shanghai, China. Generalized additive models employing a Quasi-Poisson distribution were employed to investigate the relationships between UFP and respiratory diseases. We computed the percentage change and its corresponding 95% confidence interval (CI) for outpatient visits related to respiratory diseases per interquartile range (IQR) increase in UFP concentrations. Based on a total of 1,034,394 hospital visits for respiratory diseases in Shanghai, China, we found that the strongest associations of total UFP with acute upper respiratory tract infection (AURTI), bronchitis, chronic obstructive pulmonary disease (COPD), and pneumonia occurred at lag 03, 03, 0, and 03 days, respectively. Each IQR increase in the total UFP concentrations was associated with increments of 9.02% (95% CI: 8.64-9.40%), 3.94% (95% CI: 2.84-5.06%), 4.10% (95% CI: 3.01-5.20%), and 10.15% (95% CI: 9.32-10.99%) for AURTI, bronchitis, COPD, and pneumonia, respectively. Almost linear concentration-response relationship curves without apparent thresholds were observed between total UFP and outpatient-department visits for four respiratory diseases. Stratified analyses illustrated significantly stronger associations of total UFP with AURTI, bronchitis, and pneumonia among female patients, while that with COPD was stronger among male patients. After adjustment of criteria air pollutants, these associations all remained robust. This time-series study indicates that short-term exposure to UFP was associated with increased risk of hospital visits for respiratory diseases, underscoring the importance of reducing ambient UFP concentrations for respiratory diseases control and prevention.
Project description:BackgroundPrevious studies showed inconsistent results on risk of increased outpatient visits for cause-specific diseases associated with ambient carbon monoxide (CO).MethodsDaily data for CO exposure and outpatient visits for all-causes and five specific diseases in Yichang, China from 1st January 2016 to 31st December 2017 were collected. Generalised additive models with different lag structures were used to examine the short-term effects of ambient CO on outpatient visits. Potential effect modifications by age, sex and season were examined.ResultsA total of 5,408,021 outpatient visits were recorded. We found positive and statistically significant associations between CO and outpatient visits for multiple outcomes and all the estimated risks increased with longer moving average lags. An increase of 1 mg/m3 of CO at lag06 (a moving average of lag0 to lag6), was associated with 24.67% (95%CI: 14.48, 34.85%), 21.79% (95%CI: 12.24, 31.35%), 39.30% (95%CI: 25.67, 52.92%), 25.83% (95%CI: 13.91, 37.74%) and 19.04% (95%CI: 8.39, 29.68%) increase in daily outpatient visits for all-cause, respiratory, cardiovascular, genitourinary and gastrointestinal diseases respectively. The associations for all disease categories except for genitourinary diseases were statistically significant and stronger in warm seasons than cool seasons.ConclusionOur analyses provide evidences that the CO increased the total and cause-specific outpatient visits and strengthen the rationale for further reduction of CO pollution levels in Yichang. Ambient CO exerted adverse effect on respiratory, cardiovascular, genitourinary, gastrointestinal and neuropsychiatric diseases especially in the warm seasons.
Project description:BackgroundDiurnal temperature range (DTR) has been increasingly recognized as a risk factor for mortality and morbidity, but the association between DTR and acute lower respiratory infection (ALRI) outpatient visits has not been examined among children in China.MethodsA total of 79,416 ALRI outpatient visits among children were obtained from the Guangdong Second Provincial General Hospital between 2013 and 2019. DTR was calculated by taking the difference between the maximum and the minimum temperatures. Generalized additive models using a quasi-Poisson distribution were used to model the relationship between DTR and ALRI outpatient visits.ResultsDiurnal temperature range was significantly associated with elevated risks of ALRI outpatient visits: the excess risks (ERs) and 95% confidence intervals (CIs) were 2.31% (1.26, 3.36%) for ALRI, 3.19% (1.86, 4.54%) for pneumonia, and 1.79% (0.59, 3.01%) for bronchiolitis, respectively. Subgroup analyses suggested that the associations were significantly stronger during rainy seasons (ER for ALRI: 3.02%, 95% CI: 1.43, 4.64%) than those in dry seasons (ER for ALRI: 2.21%, 95% CI: 0.65, 3.81%), while no significant effect modifications were found in sex and age groups.ConclusionDiurnal temperature range may elevate the risk of ALRI outpatient visits among children in China, especially during rainy seasons. Public health policies are needed to mitigate the adverse health impacts of DTR on children.
Project description:ObjectivesAs the largest organ of the human body, the skin is the major exposure route of NO2. However, the evidence for a relationship between NO2 exposure and dermatologic diseases (DMs) is limited. This time-series study was conducted to assess the short-term effect of nitrogen dioxide (NO2) exposure on DMs outpatient visits in Xinxiang, China.MethodsDaily recordings of NO2 concentrations, meteorological data, and the outpatient visits data for DMs were collected in Xinxiang from January 1st, 2015, to December 31st, 2018. The analysis method used was based on the generalized additive model (GAM) with quasi-Poisson regression to investigate the relationship between NO2 exposure and DMs outpatient visits. Several covariates, such as long-term trends, seasonality, and weather conditions were controlled.ResultsA total of 164,270 DMs outpatients were recorded. A 10 μg/m3 increase in NO2 concentrations during the period was associated with a 1.86% increase in DMs outpatient visits (95% confidence intervals [Cl]: 1.06-2.66%). The effect was stronger (around 6 times) in the cool seasons than in warmer seasons and younger patients (< 15 years of age) appeared to be more vulnerable.ConclusionsThe findings of this study indicate that short-term exposure to NO2 increases the risk of DMs in Xinxiang, China, especially in the cool seasons. Policymakers should implement more stringent air quality standards to improve air quality.
Project description:BackgroundOver the past decades there have been outbreaks of mumps in many countries, even in populations that were vaccinated. Some studies suggest that the incidence of mumps is related to meteorological changes, but the results of these studies vary in different regions. To date there is no reported study on correlations between mumps incidence and meteorological parameters in Beijing, China.MethodsA time series analysis incorporating selected weather factors and the number of mumps cases from 1990 to 2012 in Beijing was performed. First, correlations between meteorological variables and the number of mumps cases were assessed. A seasonal autoregressive integrated moving average model with explanatory variables (SARIMAX) was then constructed to predict mumps cases.ResultsMean temperature, rainfall, relative humidity, vapor pressure, and wind speed were significantly associated with mumps incidence. After constructing the SARIMAX model, mean temperature at lag 0 (β = 0.016, p < 0.05, 95% confidence interval 0.001 to 0.032) was positively associated with mumps incidence, while vapor pressure at lag 2 (β = -0.018, p < 0.05, 95% confidence interval -0.038 to -0.002) was negatively associated. SARIMAX (1, 1, 1) (0, 1, 1)12 with temperature at lag 0 was the best predictive construct.ConclusionsThe incidence of mumps in Beijing from 1990 to 2012 was significantly correlated with meteorological variables. Combining meteorological variables, a predictive SARIMAX model that could be used to preemptively estimate the incidence of mumps in Beijing was established.
Project description:Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration-response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29), and 1.26 (1.24-1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.