Genxin Song
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Genxin Song has a total of 24 co-authors. Here are the top co-authors by number of shared publications:
- Hongquan Song
State Key Laboratory of Spatial Datum, Henan Key Laboratory of Air Pollution Control and Ecological Security, Faculty of Geographical Science and Engineering, Henan University, Zhengzhou, China
3 shared publications - Lizhong Liang
The Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
3 shared publications - Shiyan Zhai
Faculty of Geographical Science and Engineering, College of Geographical Sciences, Henan University, Zhengzhou 450046, China
3 shared publications - Xiaoxiao Liu
Department of Community Health Science, Cumming School of Medicine, University of Calgary, Calgary, Canada
3 shared publications - Yunfeng Kong
College of Geography and Environmental Science, Henan University, Kaifeng, China
3 shared publications - Alfred Stein
University of Twente
1 shared publication
Latest Publications
- 9 May 2022
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (45) , 68103-68117
Interactive short-term effects of meteorological factors and air pollution on hospital admissions for cardiovascular diseases
A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution (\(\mathrm{SO}_{2}\), \(\mathrm{NO}_{2}\), \({\mathrm{PM}}_{2.5}\), and \({\mathrm{O}}_{3}\)) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of \(10\mathrm{\mu g}/{\mathrm{m}}^{3}\) in \(\mathrm{SO}_{2}\), \(\mathrm{NO}_{2}\), and \({\mathrm{O}}_{3}\) was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0–2; and 0.13% (0.02%, 0.23%) at lag 0–3 in CVD hospitalizations, respectively. During low relative humidity days, a \(10\mathrm{\mu g}/{\mathrm{m}}^{3}\) increment of lag 0–3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for \(\mathrm{NO}_{2}\) and \({\mathrm{PM}}_{2.5}\), respectively. On high relative humidity days, an increase of \(10\mathrm{\mu g}/{\mathrm{m}}^{3}\) in \(\mathrm{SO}_{2}\) was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0–2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that \(\mathrm{SO}_{2}\), \(\mathrm{NO}_{2}\), and \({\mathrm{O}}_{3}\) posed to CVD hospitalizations could be significantly enhanced by low temperatures. For \(\mathrm{NO}_{2}\) and \({\mathrm{PM}}_{2.5}\), CVD hospitalization risk increased in low relative humidity. The effects of \(\mathrm{SO}_{2}\) were enhanced at high relative humidity.- 9 May 2022
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (45) , 68103-68117
Interactive short-term effects of meteorological factors and air pollution on hospital admissions for cardiovascular diseases
A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution (\(\mathrm{SO}_{2}\), \(\mathrm{NO}_{2}\), \({\mathrm{PM}}_{2.5}\), and \({\mathrm{O}}_{3}\)) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of \(10\mathrm{\mu g}/{\mathrm{m}}^{3}\) in \(\mathrm{SO}_{2}\), \(\mathrm{NO}_{2}\), and \({\mathrm{O}}_{3}\) was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0–2; and 0.13% (0.02%, 0.23%) at lag 0–3 in CVD hospitalizations, respectively. During low relative humidity days, a \(10\mathrm{\mu g}/{\mathrm{m}}^{3}\) increment of lag 0–3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for \(\mathrm{NO}_{2}\) and \({\mathrm{PM}}_{2.5}\), respectively. On high relative humidity days, an increase of \(10\mathrm{\mu g}/{\mathrm{m}}^{3}\) in \(\mathrm{SO}_{2}\) was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0–2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that \(\mathrm{SO}_{2}\), \(\mathrm{NO}_{2}\), and \({\mathrm{O}}_{3}\) posed to CVD hospitalizations could be significantly enhanced by low temperatures. For \(\mathrm{NO}_{2}\) and \({\mathrm{PM}}_{2.5}\), CVD hospitalization risk increased in low relative humidity. The effects of \(\mathrm{SO}_{2}\) were enhanced at high relative humidity.- 27 January 2022
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (27) , 40711-40723
Rural-urban differences in associations between air pollution and cardiovascular hospital admissions in Guangxi, southwest China
Epidemiological studies found that exposure to air pollution increases cardiovascular hospitalizations. However, studies on rural-urban differences in associations between hospitalizations for cardiovascular diseases and air pollution are limited. The generalized linear model (GLM) was applied to investigate the associations between cardiovascular hospitalizations and air pollution (SO2, NO2, PM2.5, PM10, CO, and O3) in Guangxi, southwest China, in 2015 (January 1–December 31). The relative risk of pollutants (SO2, NO2) on cardiovascular hospital admissions was significantly different between urban and rural areas. The effect of SO2 on cardiovascular hospitalizations was higher in urban areas than in rural areas at lag0 to lag3 and cumulative lag01 to lag03. In urban areas, there were positive associations between NO2 and cardiovascular hospitalizations at lag0, lag1 and cumulative lag01, lag02. In contrast, the effect of NO2 on cardiovascular hospitalizations was not significant in rural areas. Urban residents were more sensitive than rural residents to SO2 and NO2. Subgroup analyses showed statistically significant differences between rural and urban areas in the association between SO2 and NO2 and cardiovascular hospitalizations for males. For age groups, people aged ≥ 65 years appeared to be more vulnerable to SO2 and NO2 in urban areas. The effects of PM2.5 PM10, CO, and O3 on cardiovascular hospitalizations were consistently negative for all groups. Our findings indicated that there were rural-urban differences in associations between cardiovascular hospitalizations and air pollutants. In rural areas, the risk of cardiovascular hospitalizations was mainly influenced by SO2. Therefore, we expect to pay attention to protecting people from air pollution, particularly for those aged ≥ 65 years in urban areas.
- 27 January 2022
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (27) , 40711-40723
Rural-urban differences in associations between air pollution and cardiovascular hospital admissions in Guangxi, southwest China
Epidemiological studies found that exposure to air pollution increases cardiovascular hospitalizations. However, studies on rural-urban differences in associations between hospitalizations for cardiovascular diseases and air pollution are limited. The generalized linear model (GLM) was applied to investigate the associations between cardiovascular hospitalizations and air pollution (SO2, NO2, PM2.5, PM10, CO, and O3) in Guangxi, southwest China, in 2015 (January 1–December 31). The relative risk of pollutants (SO2, NO2) on cardiovascular hospital admissions was significantly different between urban and rural areas. The effect of SO2 on cardiovascular hospitalizations was higher in urban areas than in rural areas at lag0 to lag3 and cumulative lag01 to lag03. In urban areas, there were positive associations between NO2 and cardiovascular hospitalizations at lag0, lag1 and cumulative lag01, lag02. In contrast, the effect of NO2 on cardiovascular hospitalizations was not significant in rural areas. Urban residents were more sensitive than rural residents to SO2 and NO2. Subgroup analyses showed statistically significant differences between rural and urban areas in the association between SO2 and NO2 and cardiovascular hospitalizations for males. For age groups, people aged ≥ 65 years appeared to be more vulnerable to SO2 and NO2 in urban areas. The effects of PM2.5 PM10, CO, and O3 on cardiovascular hospitalizations were consistently negative for all groups. Our findings indicated that there were rural-urban differences in associations between cardiovascular hospitalizations and air pollutants. In rural areas, the risk of cardiovascular hospitalizations was mainly influenced by SO2. Therefore, we expect to pay attention to protecting people from air pollution, particularly for those aged ≥ 65 years in urban areas.
- 10 September 2021
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (7) , 9841-9851
Synergistic effects of gaseous pollutants on hospital admissions for cardiovascular disease in Liuzhou, China
Previous studies demonstrated that short-term exposure to gaseous pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3)) had a greater adverse effect on cardiovascular disease. However, little evidence exists regarding the synergy between gaseous pollutants and cardiovascular disease (CVD). Therefore, we aimed to estimate the effect of individual gaseous pollutants on hospital admissions for CVD and to explore the possible synergistic effects between gaseous pollutants. Daily hospitalization counts for CVD were collected from January 1, 2014, to December 31, 2015. We also collected daily time series on gaseous pollutants from the Environment of the People’s Republic of China, including NO2, SO2, and O3. We used distributed lag nonlinear models (DLNMs) to assess the association of individual gaseous pollutants on CVD hospitalization, after controlling for seasonality, day of the week, public holidays, and weather variables. Then, we explored the variability across age and sex groups. In addition, we analyzed the synergistic effects between gaseous pollutants on CVD. Extremely low NO2 and SO2 increase the risk of CVD in all subgroup at lag 7 days. The greatest effect of high concentration of SO2 was observed in male and the elderly (≥ 65 years) at lag 3 days. Greater effects of high concentration of O3 were more pronounced in the young (< 65 years) and female at lag 3 days, while the effect of low concentration of O3 was greater in male and the young (< 65 years) at lag 0 day. We found a synergistic effect between NO2 and SO2 for CVD, as well as between SO2 and O3. The synergistic effects of NO2 and SO2 on CVD were stronger in the elderly (≥ 65) and female. The female was sensitive to synergistic effects of SO2-O3 and NO2-O3. Interestingly, we found that there was a risk of CVD in the susceptible population even for gaseous pollutant concentrations below the National Environmental Quality Standard. The synergy between NO2 and SO2 was significantly associated with cardiovascular disease hospitalization in the elderly (≥ 65). This study provides evidence for the synergistic effect of gaseous pollutants on hospital admissions for cardiovascular disease.
- 10 September 2021
- Published by Springer Nature in Environmental Science and Pollution Research
- Vol. 29 (7) , 9841-9851
Synergistic effects of gaseous pollutants on hospital admissions for cardiovascular disease in Liuzhou, China
Previous studies demonstrated that short-term exposure to gaseous pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3)) had a greater adverse effect on cardiovascular disease. However, little evidence exists regarding the synergy between gaseous pollutants and cardiovascular disease (CVD). Therefore, we aimed to estimate the effect of individual gaseous pollutants on hospital admissions for CVD and to explore the possible synergistic effects between gaseous pollutants. Daily hospitalization counts for CVD were collected from January 1, 2014, to December 31, 2015. We also collected daily time series on gaseous pollutants from the Environment of the People’s Republic of China, including NO2, SO2, and O3. We used distributed lag nonlinear models (DLNMs) to assess the association of individual gaseous pollutants on CVD hospitalization, after controlling for seasonality, day of the week, public holidays, and weather variables. Then, we explored the variability across age and sex groups. In addition, we analyzed the synergistic effects between gaseous pollutants on CVD. Extremely low NO2 and SO2 increase the risk of CVD in all subgroup at lag 7 days. The greatest effect of high concentration of SO2 was observed in male and the elderly (≥ 65 years) at lag 3 days. Greater effects of high concentration of O3 were more pronounced in the young (< 65 years) and female at lag 3 days, while the effect of low concentration of O3 was greater in male and the young (< 65 years) at lag 0 day. We found a synergistic effect between NO2 and SO2 for CVD, as well as between SO2 and O3. The synergistic effects of NO2 and SO2 on CVD were stronger in the elderly (≥ 65) and female. The female was sensitive to synergistic effects of SO2-O3 and NO2-O3. Interestingly, we found that there was a risk of CVD in the susceptible population even for gaseous pollutant concentrations below the National Environmental Quality Standard. The synergy between NO2 and SO2 was significantly associated with cardiovascular disease hospitalization in the elderly (≥ 65). This study provides evidence for the synergistic effect of gaseous pollutants on hospital admissions for cardiovascular disease.
- Open Access
- 30 September 2017
- Published by MDPI AG in Remote Sensing
- Vol. 9 (10) , 1018
A Remote Sensing Data Based Artificial Neural Network Approach for Predicting Climate-Sensitive Infectious Disease Outbreaks: A Case Study of Human Brucellosis
Remote sensing technologies can accurately capture environmental characteristics, and together with environmental modeling approaches, help to predict climate-sensitive infectious disease outbreaks. Brucellosis remains rampant worldwide in both domesticated animals and humans. This study used human brucellosis (HB) as a test case to identify important environmental determinants of the disease and predict its outbreaks. A novel artificial neural network (ANN) model was developed, using annual county-level numbers of HB cases and data on 37 environmental variables, potentially associated with HB in Inner Mongolia, China. Data from 2006 to 2008 were used to train, validate and test the model, while data for 2009–2010 were used to assess the model’s performance. The Enhanced Vegetation Index was identified as the most important predictor of HB incidence, followed by land surface temperature and other temperature- and precipitation-related variables. The suitable ecological niche of HB was modeled based on these predictors. Model estimates were found to be in good agreement with reported numbers of HB cases in both the model development and assessment phases. The study suggests that HB outbreaks may be predicted, with a reasonable degree of accuracy, using the ANN model and environmental variables obtained from satellite data. The study deepened the understanding of environmental determinants of HB and advanced the methodology for prediction of climate-sensitive infectious disease outbreaks.
- 30 September 2017
- Published by MDPI AG in Remote Sensing
- Vol. 9 (10) , 1018
Open AccessA Remote Sensing Data Based Artificial Neural Network Approach for Predicting Climate-Sensitive Infectious Disease Outbreaks: A Case Study of Human Brucellosis
Remote sensing technologies can accurately capture environmental characteristics, and together with environmental modeling approaches, help to predict climate-sensitive infectious disease outbreaks. Brucellosis remains rampant worldwide in both domesticated animals and humans. This study used human brucellosis (HB) as a test case to identify important environmental determinants of the disease and predict its outbreaks. A novel artificial neural network (ANN) model was developed, using annual county-level numbers of HB cases and data on 37 environmental variables, potentially associated with HB in Inner Mongolia, China. Data from 2006 to 2008 were used to train, validate and test the model, while data for 2009–2010 were used to assess the model’s performance. The Enhanced Vegetation Index was identified as the most important predictor of HB incidence, followed by land surface temperature and other temperature- and precipitation-related variables. The suitable ecological niche of HB was modeled based on these predictors. Model estimates were found to be in good agreement with reported numbers of HB cases in both the model development and assessment phases. The study suggests that HB outbreaks may be predicted, with a reasonable degree of accuracy, using the ANN model and environmental variables obtained from satellite data. The study deepened the understanding of environmental determinants of HB and advanced the methodology for prediction of climate-sensitive infectious disease outbreaks.