Research on the influence of meteorological factors on the incidence of foodborne diseases / 公共卫生与预防医学

Objective To explore the correlation between the incidence of foodborne diseases and meteorological factors in Jinan, and to provide targeted measures for the prevention and control of foodborne diseases. Methods Data from the reporting systems of two sentinel hospitals for active surveillance of foodborne diseases from 2013 to 2021 in Jinan were collected. The meteorological data in the same period in Jinan were also collected. The generalized additive model was used to explore the nonlinear relationship between meteorological factors and the incidence of foodborne diseases, and threshold function analysis was use to perform subsection regression. Results The incidence of foodborne diseases was positively correlated with daily average temperature (rs=0.23), relative humidity (rs=0.05), and daily average wind speed (rs=0.01), and negatively correlated with daily average air pressure (rs=-0.19). Based on the GAM results and segmented regression analysis of meteorological factors, it was found that when the daily average temperature was below or above the threshold of 24.63°C, for every 1°C increase in daily average temperature, the incidence of foodborne diseases correspondingly increased by 0.04% and 0.18%. When the daily average wind speed was above the threshold of 2.26 m/s, the incidence of foodborne diseases decreased by 0.36% for every 1 m/s increase in the daily average wind speed. Conclusion Nine years of observation and data analysis have shown that meteorological factors such as daily average temperature, relative humidity, air pressure, and wind speed are related to the incidence of foodborne diseases. These findings suggest that meteorological factors may be important factors leading to foodborne diseases, which provides an important scientific basis for formulating effective prevention and control measures.

Association between ozone pollution and daily outpatient visits for respiratory system in a district of Shanghai / 上海预防医学

ObjectiveTo analyze the effect of O3 pollution on outpatient visits for respiratory diseases in a district of Shanghai. MethodsWe collected the respiratory disease outpatient data， and atmospheric and meteorological data of from a suburban general hospital in Shanghai from 2015 to 2017. A time-series analysis by generalized additive model was conducted to examine the relationship between O3 pollution and daily outpatient visits. ResultsThe daily outpatient volume for respiratory diseases was 831. The daily 8 h median concentration of O3 was 101.04 μg·m-3. The excess relative risk was 0.461% （95%CI： 0.240%‒0.682%） at lag3. Stratified by gender and age， females， child and the aged had higher risk of respiratory diseases. In the double-pollutant model， PM2.5 and PM10 increased health effects， while CO reduced health effects. ConclusionThe increase of O3 concentration can increase the daily outpatient volume of respiratory diseases.

Association between atmospheric particulate matters and outpatient visits for respiratory disorders in Jiaxing City of Zhejiang Province from 2019 to 2021： a time series analysis / 上海预防医学

ObjectiveTo explore the effect of exposure to atmospheric particulate matters on the outpatient visits of respiratory disorders in Jiaxing City，Zhejiang Province. MethodsDaily air pollutant monitoring data，meteorological data and outpatient visits of respiratory disorders in Jiaxing City from 2019 to 2021 were collected．A generalized additive model was applied to evaluate the effect and laggeel effect of the concentrations of atmospheric particulates for outpatient visits of respiratory disorders after adjusting for secular trend， day-of-the-week effect， holiday effect， and meteorological variables. ResultsThe daily average concentrations of PM2.5， PM10， O3 and NO2 exceeded the standard， and the proportion of days exceeding the standard was 3.4%， 1.3%， 11.0% and 0.8%， respectively. Every 10 μg·m-3 increase in PM2.5 concentration showed the strongest effects on the daily outpatient visits of respiratory disorders， adult and childhood respiratory disorders all on lag07 with ER（95%CI） being 2.29%（1.35%‒3.24%）， 2.31% （1.39%‒3.23%） and 2.65 % （1.36%‒3.96%）， respectively. The maximum ER of outpatient visits for respiratory disorders in children was higher than that in adults. Every 10 μg·m-3 increase in PM10 concentration showed the strongest effects on the daily outpatient visits of respiratory disorders on lag07， adult respiratory disorders on lag06 and childhood respiratory disorders on lag07 with ER（95%CI） being 1.42% （0.87%‒1.96%）， 1.49%（0.99%‒1.99%） and 1.61% （0.87%‒2.36%）， respectively. The results of double-pollutant model showed that the effect of atmospheric particulate reduced after O3 was introduced into the model. ConclusionThere are a short-term effect and a laggeel effect of atmospheric particulate on the outpatient visits of respiratory disorders. It is necessary to strengthen the health protection of the respiratory system of the population， especially the children.

Comparison of the application effects of SARIMA, GAM and LSTM in prediction of hemorrhagic fever with renal syndrome / 中华地方病学杂志

Objective:To analyze the effects of seasonal autoregressive integrated moving average model (SARIMA), generalized additive model (GAM), and long-short term memory model (LSTM) in fitting and predicting the incidence of hemorrhagic fever with renal syndrome (HFRS), so as to provide references for optimizing the HFRS prediction model.Methods:The monthly incidence data of HFRS from 2004 to 2017 of the whole country and the top 9 provinces with the highest incidence of HFRS (Heilongjiang, Shaanxi, Jilin, Liaoning, Shandong, Hebei, Jiangxi, Zhejiang and Hunan) were collected in the Public Health Science Data Center (https://www.phsciencedata.cn/), of which the data from 2004 to 2016 were used as training data, and the data from January to December 2017 were used as test data. The SARIMA, GAM, and LSTM of HFRS incidence in the whole country and 9 provinces were fitted with the training data; the fitted model was used to predict the incidence of HFRS from January to December 2017, and compared with the test data. The mean absolute percentage error ( MAPE) was used to evaluate the model fitting and prediction accuracy. When MAPE < 20%, the model fitting or prediction effect was good, 20%-50% was acceptable, and > 50% was poor. Results:From the perspective of overall fitting and prediction effect, the optimal model for the whole country and Heilongjiang, Shaanxi, Jilin, Liaoning and Jiangxi was SARIMA ( MAPE was 19.68%, 20.48%, 44.25%, 19.59%, 23.82% and 35.29%, respectively), among which the fitting and prediction effects of the whole country and Jilin were good, and the rest were acceptable. The optimal model for Shandong and Zhejiang was GAM ( MAPE was 18.29% and 21.25%, respectively), the fitting and prediction effect of Shandong was good, and Zhejiang was acceptable. The optimal model for Hebei and Hunan was LSTM ( MAPE was 26.52% and 22.69%, respectively), and the fitting and prediction effects were acceptable. From the perspective of fitting effect, GAM had the highest fitting accuracy in the whole country data, with MAPE = 10.44%. From the perspective of prediction effect, LSTM had the highest prediction accuracy in the whole country data, with MAPE = 12.23%. Conclusions:SARIMA, GAM, and LSTM can all be used as the optimal models for fitting the incidence of HFRS, but the optimal models fitted in different regions show great differences. In the future, in the establishment of HFRS prediction models, as many alternative models as possible should be included for screening to ensure higher fitting and prediction accuracy.

Effects of ambient temperature on metabolic syndrome and pathway analysis / 环境与职业医学

Background In recent years, the incidence of metabolic syndrome (MS) is increasing significantly in China. Some studies have found that temperature is related to single metabolic index, but there is a lack of research on associated mechanism and identifying path of the influence of temperature on MS. Objective Based on the data of Guangdong Province, to investigate the effect of temperature on MS and its pathway. Methods A total of 8524 residents were enrolled by multi-stage random sampling from October 2015 to January 2016 in Guangdong. Basic characteristics, behavioral characteristics, health status, and physical activity level were obtained through questionnaires and physical examinations, and meteorological data were obtained from meteorological monitoring sites. We matched individual data both with the temperature data of the physical examination day and of a lag of 14 d. A generalized additive model was used to explore the exposure-effect relationship between temperature and MS and its indexes, calculate effect values, and explore the effects of single-day lag temperature. Based on the literature and the results of generalized additive model analysis, a path analysis was conducted to explore the pathways of temperature influencing MS. Results The association between daily average temperature on the current day or lag 14 day and MS risk was not statistically significant. When daily average temperature increased by 1 ℃, the change values of fasting blood-glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), and high density lipoprotein cholesterol (HDL-C) were −0.033 (95%CI: −0.040-−0.026) mmol·L−1, −0.662 (95%CI: −0.741-−0.583) mmHg, −0.277 (95%CI: −0.323-−0.230) mmHg, and −0.005 (95%CI: −0.007-−0.004) mmol·L−1 respectively. The effects of average daily temperature on FBG, blood pressure, HDL-C, and waist circumference lasted until lag 14 day. The effects of daily average temperature on SBP and DBP were the largest on the current day. Daily average temperature of current day had direct and indirect effects on FBG and SBP. Temperature had an indirect effect on TG, and the intermediate variables were waist circumference and FBG, with an indirect effect value of −0.011 (95%CI: −0.020-−0.002). The indirect effects of daily average temperature on SBP, FBG, and TG were weak. Conclusion There is no significant correlation between temperature and risk of MS, and daily average temperature of current day could significantly affected blood pressure and FBG with a lag effect. Daily average temperature of current day has indirect effects on FBG and TG.

Association between air pollution and death from respiratory diseases in Wuhan from 2014 to 2019 / 上海预防医学

ObjectiveTo determine the association between air pollutants （PM2.5， PM10， SO2， NO2） and death from respiratory diseases in Wuhan. MethodsDaily air pollutants， meteorological data and mortality from respiratory disease between 2014 and 2019 were collected for a descriptive analysis. A time series semi-parametric generalized additive model （GAM） was used to determine the exposure-effect relationship between atmospheric pollutants and daily mortality from respiratory diseases，and the excess risk （ER） was used to quantify the effects of air pollutants on death from respiratory diseases. ResultsThere was significant effect of PM2.5， PM10， SO2 and NO2 on respiratory diseases mortality. In the period with strongest effect， the ER of death from respiratory diseases were 2.803%（95%CI：2.151%‒3.460%）， 1.878%（95%CI：1.477%‒2.281%）， 10.210%（95%CI：7.922%‒12.549%）， 4.564%（95%CI：3.530%‒5.608%）， along with an incremental 10 μg·m-3 of PM2.5，PM10，SO2 and NO2， respectively. Furthermore， females were more sensitive to PM2.5， SO2 and NO2， while males were more sensitive to PM10. Residents aged less than 65 years were more sensitive to PM2.5 and NO2， and those older than 65 years were more sensitive to PM10 and SO2. ConclusionAir pollutants （PM2.5， PM10， SO2， and NO2） in Wuhan are associated with the death from respiratory diseases. Therefore， at-risk groups should be considered for formulating local policies against air pollution.

Study on the relationship between habitat factors and the distribution / 公共卫生与预防医学

Objective To explore the relationship between the distribution characteristics and the habitat factors of the invasive B. straminea in South China. Methods From October 2016 to August 2017, the breeding condition and habitat factors of B. straminea were investigated in the rivers of Shenzhen and its adjacent areas in the dry season, normal season and wet reason. The generalized additive model (GAM) was used to study the main habitat factors affecting the distribution density of B. straminea. Results The distribution characteristics of B. straminea showed obvious aggregation and unevenness in space. In terms of time, the density of snails was the highest in the dry season, followed by the normal water season and the least in the wet season. The GAM model analysis showed that the main habitat factors affecting the distribution density of B. straminea were water depth, water temperature, flow velocity, dissolved oxygen, and total phosphorus. When the flow velocity and water temperature were 0.25 m / s and 26 °C, respectively, the largest distribution density of snails might appear. The distribution density of B. straminea was positively correlated with dissolved oxygen and total phosphorus. Conclusion B. straminea is suitable to live in the water environment with poor water quality. In the future, the monitoring should be strengthened to provide reference for the prevention and control of the spread of the snails.

Effects of daily mean temperature and other meteorological variables on bacillary dysentery in Beijing-Tianjin-Hebei region, China

BACKGROUND@#Although previous studies have shown that meteorological factors such as temperature are related to the incidence of bacillary dysentery (BD), researches about the non-linear and interaction effect among meteorological variables remain limited. The objective of this study was to analyze the effects of temperature and other meteorological variables on BD in Beijing-Tianjin-Hebei region, which is a high-risk area for BD distribution.@*METHODS@#Our study was based on the daily-scale data of BD cases and meteorological variables from 2014 to 2019, using generalized additive model (GAM) to explore the relationship between meteorological variables and BD cases and distributed lag non-linear model (DLNM) to analyze the lag and cumulative effects. The interaction effects and stratified analysis were developed by the GAM.@*RESULTS@#A total of 147,001 cases were reported from 2014 to 2019. The relationship between temperature and BD was approximately liner above 0 °C, but the turning point of total temperature effect was 10 °C. Results of DLNM indicated that the effect of high temperature was significant on lag 5d and lag 6d, and the lag effect showed that each 5 °C rise caused a 3% [Relative risk (RR) = 1.03, 95% Confidence interval (CI): 1.02-1.05] increase in BD cases. The cumulative BD cases delayed by 7 days increased by 31% for each 5 °C rise in temperature above 10 °C (RR = 1.31, 95% CI: 1.30-1.33). The interaction effects and stratified analysis manifested that the incidence of BD was highest in hot and humid climates.@*CONCLUSIONS@#This study suggests that temperature can significantly affect the incidence of BD, and its effect can be enhanced by humidity and precipitation, which means that the hot and humid environment positively increases the incidence of BD.

Research on prediction of daily admissions of respiratory diseases with comorbid diabetes in Beijing based on long short-term memory recurrent neural network / 浙江大学学报·医学版

To compare the performance of generalized additive model (GAM) and long short-term memory recurrent neural network (LSTM-RNN) on the prediction of daily admissions of respiratory diseases with comorbid diabetes. Daily data on air pollutants, meteorological factors and hospital admissions for respiratory diseases from Jan 1st, 2014 to Dec 31st, 2019 in Beijing were collected. LSTM-RNN was used to predict the daily admissions of respiratory diseases with comorbid diabetes, and the results were compared with those of GAM. The evaluation indexes were calculated by five-fold cross validation. Compared with the GAM, the prediction errors of LSTM-RNN were significantly lower [root mean squared error (RMSE): 21.21±3.30 vs. 46.13±7.60, <0.01; mean absolute error (MAE): 14.64±1.99 vs. 36.08±6.20, <0.01], and the value was significantly higher (0.79±0.06 vs. 0.57±0.12, <0.01). In gender stratification, RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting female admission (all <0.05), but there were no significant difference in predicting male admission between two models (all >0.05). In seasonal stratification, RMSE and MAE of LSTM-RNN were lower than those of GAM in predicting warm season admission (all <0.05), but there was no significant difference in value (>0.05). There were no significant difference in RMSE, MAE and between the two models in predicting cold season admission (all >0.05). In the stratification of functional areas, the RMSE, MAE and values of LSTM-RNN were better than those of GAM in predicting core area admission (all <0.05). has lower prediction errors and better fitting than the GAM, which can provide scientific basis for precise allocation of medical resources in polluted weather in advance.

Time series analysis of air pollution and asthma outpatient visits in Hefei / 公共卫生与预防医学

Objective To explore the relationship between the outpatient visits for adult asthma and air pollution in a tertiary hospital in Hefei. Methods The number of outpatient visits for asthma in a tertiary hospital in Hefei from 2014 to 2020 was collected. The air pollutant data was obtained through the Hefei Air Monitoring Station, and the meteorological indicators of the same period were collected through the China Meteorological Network. The R statistical software was used to establish a generalized additive model to analyze the lag effect of air pollution on the number of outpatient visits for asthma. Results From 2014 to 2020, there were 7 220 asthma outpatients in the tertiary hospital in Hefei, including 3104 males and 4 116 females, 3 798 patients in warm season, and 3 422 patients in cold season. During the period, the average concentrations of SO2, NO2, CO, O3, PM10, and PM2.5 were 11.9μg/m3, 40.1μg/m3, 0.9 mg/m3, 87.3μg/m3, 81.3μg/m3, and 55.7μg/m3, respectively. The results of the single-pollutant model showed that every 10μg/m3 increase in SO2 concentration increased the risk of asthma by 0.74% (95%CI: 0.22%-1.29%), and the effect was the greatest on Lag2 day. NO2 increased the risk of asthma by 0.31% (95%CI: 0.13%-0.49%), with the greatest effect on Lag0 day. The analysis of the dual pollutant model found that whereas the effect of SO2 decreased after the incorporation of NO2, the effect increased after the incorporation of CO, O3, PM10, or PM2.5, respectively. The effect of NO2 on asthma decreased after the incorporation of SO2, whereas the effect on asthma increased after the inclusion of CO, PM10, or PM2.5. Stratified analysis of cold and warm seasons showed that the effect of NO2 on asthma was the greatest in lag0 in cold season. The effect of SO2 was higher in cold season than in warm season, and it was the highest in lag2. The gender stratification analysis showed that the effects of SO2 and NO2 on male asthma were higher than those on females. Conclusion From 2014 to 2020, the increase of SO2 and NO2 concentrations in Hefei is positively correlated with the risk of asthma in the outpatient department of a tertiary hospital. The effect has a certain lag. It is of great significance to formulate relevant preventive measures for the occurrence and attack of asthma.

Time-series analysis of air pollution effects on diabetes related mortality / 环境与职业医学

Background Diabetes mellitus is a major public health issue at present. Previous studies have shown that ambient air pollution is a risk factor for diabetes. Objective This study aims to explore the acute effects of ambient air pollution on diabetes related death in Shanghai Jing’an District. Methods Daily air pollution data, meteorological data, and diabetes related mortality data in 2013−2019 in Shanghai Jing’an District were collected. A generalized additive model (GAM) was established to conduct time-series analysis on the short-term effect of ambient air pollution on diabetes related mortality, and gender- and age-stratified analysis on susceptibility of various groups to ambient air pollution exposures. Results For every 10 μg·m−3 increase of the concentrations of PM2.5, PM10, SO2, and NO2, the diabetes related mortality increased by 2.47% (95%CI: 1.56%−3.38%), 2.02% (95%CI: 1.29%−2.75%), 5.75% (95%CI: 2.99%−8.58%), and 3.93% (95%CI: 2.49%−5.39%) at lag05 respectively (P<0.05). In the stratified analysis, exposures to increased concentrations of PM2.5, PM10, SO2, and NO2 raised the mortality risks from diabetes in male, female, and ≥65 years oldgroups (P<0.05). However, the differences in mortality risks from diabetes due to air pollution within gender and age groups were statistically insignificant. Conclusion In Shanghai Jing'an District, the elevated levels of ambient air pollutants, including PM2.5, PM10, SO2, and NO2, are significantly associated with the increase of diabetes related mortality, and there are lag effects and cumulative effects. The ≥65 years olds are more susceptible to the impact of air pollution on diabetes related deaths.

Time series study on the correlation between atmospheric particulate matter and confirmed cases of influenza in Pudong New Area, Shanghai / 公共卫生与预防医学

Objective To understand the correlation between atmospheric particulate matter and confirmed cases of influenza in Pudong New Area, Shanghai, and to provide a basis for formulating relevant control measures. Methods The meteorological factors (average temperature, relative humidity, and atmospheric pressure), atmospheric pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) and confirmed cases of influenza of different ages and genders from January 1, 2014 to December 31, 2018 were collected. Data was fitted to a generalized additive model of Poisson distribution to assess the correlation between atmospheric particulate matter (PM2.5, PM10) and the number of confirmed cases of influenza. Results There was a correlation between atmospheric particulate matter and the number of confirmed cases of influenza in Pudong New Area. For each increase of 10 μg/m3 in the concentration of the two types of particulate matter, the confirmed cases increased by 0.638% (95%CI: 0.413%~0.864%), and 0.520% (95%CI: 0.324%~0.715%), respectively, when the lag was 0-7d (lag07). People of different ages and genders were affected by atmospheric particulate matter differently. After incorporating the effects of SO2, NO2, CO, and O3 in the multi-pollutant model, the effect of atmospheric particulate matter on the number of influenza cases had changed. Conclusion The increase of atmospheric particulate matter (PM2.5, PM10) concentration increased the number of confirmed cases of influenza in Pudong New Area.

Effects of Air Pollutants on Outpatient Visits for Atopic Dermatitis in Lanzhou / 中国医学科学院学报

Objective To quantitatively evaluate the associations of PM

Effect of Air Pollution on Emergency Room Visits for Respiratory Diseases in Lanzhou / 中国医学科学院学报

Objective To explore the effect of air pollution on the number of emergency room visits for respiratory diseases in residents at different ages and its seasonal changes in Lanzhou,so as to provide a scientific basis for the early prevention of respiratory diseases in Lanzhou. Methods The daily number of emergency room visits for respiratory diseases in three class A hospitals in Lanzhou from January 1,2013 to December 31,2017,as well as the air pollutants and meteorological data of Lanzhou in the same period,was collected.After controlling the confounding factors including long-term trend of time,meteorological factors and day-of-week effect using a generalized additive model,we analyzed the relationships between air pollutants and the daily number of emergency room visits for respiratory diseases,and explored whether there was a lag effect of air pollutants.Results From 2013 to 2017,the emergency room visits for respiratory diseases in Lanzhou had a total number of 124 871,with an average of 69(1-367)visits per day.The single pollutant model showed that among the six conventional air pollutants monitored in Lanzhou,PM

The relationship between air pollutants and mortality in Huairou District / 预防医学

Objective@#To evaluate the relationship between air pollutants and mortality of residents in Huairou District, Beijing, providing a basis for the formulation of air pollution control measures. @*Methods @#The data of daily deaths, meteorological factors and air pollutants in Huairou District from 2014 to 2018 were collected from Beijing Disease Prevention Monitoring Information Integration and Analysis System, Huairou Meteorological Bureau and Environmental Monitoring Station. The generalized additive models were used to analyze the relationship between the average daily concentration of air pollutants and the daily deaths.@*Results@#The medians of daily average concentrations of SO2, NO2, CO, O3, PM10 and PM2.5 were 5.00 μg/m3, 24.00 μg/m3, 0.71 mg/m3, 77.27 μg/m3, 64.25 μg/m3 and 44.13 μg/m3, respectively. Except for O3, the daily average concentrations of SO2, NO2, CO, PM10 and PM2.5 showed decreasing trends from 2014 to 2018. An increase of 10 μg/m3 of NO2 resulted in an elevation of 1.69% ( 95%CI: 0.31%-3.08% ) , 3.31% ( 95%CI: 1.24%-5.42% ) and 3.31% ( 95%CI: 0.51%-6.19% ) for non-accidental death in the whole population, females and people under 65 years old, respectively, with a delay of 2 days (lag2). For every 10 μg/m3 increase in the daily average concentrations of CO and PM2.5, the risk of non-accidental death among people under 65 years old at lag2 increased by 0.08% ( 95%CI: 0.01%-0.14% ) and 0.88% ( 95%CI: 0.12%-1.64% ) , respectively. For every 10 μg/m3 increase in daily average concentration of O3, there was 0.69% ( 95%CI: 0.02%-1.36% ) increase in daily male non-accidental death risk at lag4. The results of the multi-pollutant model showed that after adjusting the effects of the other two air pollutants, NO2, CO and PM2.5 had no statistically significant effects on the daily non-accidental deaths of people under 65 years old at lag2 ( P>0.05 ) . @*Conclusion@# The ambient NO2, CO, O3 and PM2.5 pollution increase daily non-accidental deaths, which shows a lag effect．

Short-term effects of ambient air pollution and cause-specific emergency department visits in Guangzhou / 中华疾病控制杂志

Objective To understand the relationship between the concentration of air pollutants and daily emergency department visits for different diseases (circulatory system disease, digestive system disease, nervous system disease and respiratory system disease) in Guangzhou, Guangdong Province. Methods The daily average concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2, carbon monoxide (CO) and PM2.5 and the daily maximum 8-hour concentrations of O3, the daily average temperature, the relative humidity and cause -specific emergency department visits of the four major diseases from 2015 to 2017 were collected in Guangzhou. Semi-parametric generalized additive model was used to analyze the relationship between the concentration of pollutants and daily cause-specific emergency department visits. Results The daily average concentrations of SO2, NO2, CO, O3 and PM2.5 during the study period were 13.24 μg /m3, 45.96 μg /m3, 0.97 mg /m3, 123.77 μg /m3 and 36.22 μg /m3, respectively. For circulatory system disease，the independently significant associations of SO2 with emergency department visits in single-pollutant models (2.91%, 95% CI: 1.00%-4.85%), and multipollutant models (4.39%, 95% CI: 1.22%-7.67%) were observed. Conclusion The ambient SO2 increases the risk of emergency department visits due to circulatory diseases in Guangzhou. Comprehensive prevention and control measures should be taken to reduce the emission of SO2.

‘Pneumonia Weather’: Short-term Effects of Meteorological Factors on Emergency Room Visits Due to Pneumonia in Seoul, Korea / 예방의학회지

OBJECTIVES: Many studies have explored the relationship between short-term weather and its health effects (including pneumonia) based on mortality, although both morbidity and mortality pose a substantial burden. In this study, the authors aimed to describe the influence of meteorological factors on the number of emergency room (ER) visits due to pneumonia in Seoul, Korea. METHODS: Daily records of ER visits for pneumonia over a 6-year period (2009-2014) were collected from the National Emergency Department Information System. Corresponding meteorological data were obtained from the National Climate Data Service System. A generalized additive model was used to analyze the effects. The percent change in the relative risk of certain meteorological variables, including pneumonia temperature (defined as the change in average temperature from one day to the next), were estimated for specific age groups. RESULTS: A total of 217 776 ER visits for pneumonia were identified. The additional risk associated with a 1°C increase in pneumonia temperature above the threshold of 6°C was 1.89 (95% confidence interval [CI], 1.37 to 2.61). Average temperature and diurnal temperature range, representing within-day temperature variance, showed protective effects of 0.07 (95% CI, 0.92 to 0.93) and 0.04 (95% CI, 0.94 to 0.98), respectively. However, in the elderly (65+ years), the effect of pneumonia temperature was inconclusive, and the directionality of the effects of average temperature and diurnal temperature range differed. CONCLUSIONS: The term ‘pneumonia temperature’ is valid. Pneumonia temperature was associated with an increased risk of ER visits for pneumonia, while warm average temperatures and large diurnal temperature ranges showed protective effects.

Series study on the relationship between air quality index and tuberculosis incidence in Beijing / 中华流行病学杂志

Objective To analyze the effect of air quality index (AQI) on the incidence of tuberculosis (TB) in Beijing,and to provide evidence for setting up a better program regarding prevention and control of tuberculosis.Methods Generalized additive model (GAM) was used to analyze the association between AQI and the incidence of tuberculosis in Beijing,from January 1,2014 to November 9,2016.Confounding factors as meteorological conditions and time trends were under control.Results In Beijing,a total of 14 533 TB cases with definite dates of onset were collected during the study period,with 36 children excluded from the study.Finally,14 497 cases were included in the study,including 9 513 men and 4 984 women,with 11 290 adults (15-59 years old) and 3 207 elderly (≥60 years old).Data from the optimal single-day lag effect of GAM showed that,with every 1 0 increase of AQI,the percent of increase on the onsets of overall,male,female and adult;tuberculosis cases were 0.85％ (95％CI:0.26％-1.44％),0.83％ (95％CI:0.24％-1.42％),0.93％ (95％CI:0.24％-1.62％) and 0.88％ (95％CI:0.29％-1.46％),respectively.The optimal lag time of the single-day effects were 15 days (lagl5),but 16 days (lag16) for male.The optimal cumulative lag effect showed that with every 10 AQI increase,the percent of increase on the onsets of overall,male,female and adult tuberculosis cases were 1.92％ (95％CI:0.23％-3.16％),1.94％ (95％CI:0.15％-3.72％),2.04％ (95％CI:0.10％-3.97％) and 2.00％ (95％CI:0.30％-3.69％),respectively,with the optimal lag time of cumulative delayed effects as 17 days (lag0_17),18 days (lag0_18),16 days (lag0_16) and 17 days (lag0_17),respectively.However,there were no statistical significances noticed in the elderly cases.Conclusion There was a positive correlation between AQI and the number of TB cases in Beijing,and the effects of AQI on the number of TB cases in different genders and age groups were different.

Series study on the relationship between air quality index and tuberculosis incidence in Beijing / 中华流行病学杂志

Objective To analyze the effect of air quality index (AQI) on the incidence of tuberculosis (TB) in Beijing,and to provide evidence for setting up a better program regarding prevention and control of tuberculosis.Methods Generalized additive model (GAM) was used to analyze the association between AQI and the incidence of tuberculosis in Beijing,from January 1,2014 to November 9,2016.Confounding factors as meteorological conditions and time trends were under control.Results In Beijing,a total of 14 533 TB cases with definite dates of onset were collected during the study period,with 36 children excluded from the study.Finally,14 497 cases were included in the study,including 9 513 men and 4 984 women,with 11 290 adults (15-59 years old) and 3 207 elderly (≥60 years old).Data from the optimal single-day lag effect of GAM showed that,with every 1 0 increase of AQI,the percent of increase on the onsets of overall,male,female and adult;tuberculosis cases were 0.85％ (95％CI:0.26％-1.44％),0.83％ (95％CI:0.24％-1.42％),0.93％ (95％CI:0.24％-1.62％) and 0.88％ (95％CI:0.29％-1.46％),respectively.The optimal lag time of the single-day effects were 15 days (lagl5),but 16 days (lag16) for male.The optimal cumulative lag effect showed that with every 10 AQI increase,the percent of increase on the onsets of overall,male,female and adult tuberculosis cases were 1.92％ (95％CI:0.23％-3.16％),1.94％ (95％CI:0.15％-3.72％),2.04％ (95％CI:0.10％-3.97％) and 2.00％ (95％CI:0.30％-3.69％),respectively,with the optimal lag time of cumulative delayed effects as 17 days (lag0_17),18 days (lag0_18),16 days (lag0_16) and 17 days (lag0_17),respectively.However,there were no statistical significances noticed in the elderly cases.Conclusion There was a positive correlation between AQI and the number of TB cases in Beijing,and the effects of AQI on the number of TB cases in different genders and age groups were different.

Male external genitalia growth curves and charts for children and adolescents aged 0 to 17 years in Chongqing, China / 亚洲男科学杂志(英文版)

Genital size is a crucial index for the assessment of male sexual development, as abnormal penile or testicular size may be the earliest visible clinical manifestation of some diseases. However, there is a lack of data regarding penile and testicular size measurements for Chinese boys at all stages of childhood and puberty. This cross-sectional study aimed to develop appropriate growth curves and charts for male external genitalia among children and adolescents aged 0-17 years in Chongqing, China. A total of 2974 boys were enrolled in the present study. Penile length was measured using a rigid ruler, penile diameter was measured using a pachymeter, and testicular volume was determined using a Prader orchidometer. Age-specific percentile curves for penile length, penile diameter, and testicular volume were drawn using the generalized additive models for location, scale, and shape. Very similar growth curves were found for both penile length and penile diameter. Both of them gradually rose to 10 years of age and then sharply increased from 11 to 15 years of age. However, testicular volume changed little before the age of 10 years. This study contributes to the literature covering age-specific growth curve and charts about male external genitalia in Chinese children and adolescents. These age-related values are valuable in evaluating the growth and development status of male external genitalia and could be helpful in diagnosing genital disorders.