Association between non-optimal temperature and hospitalizations for gout in Anqing, China: a time-series analysis
Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily dat...
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Published in | Environmental science and pollution research international Vol. 29; no. 10; pp. 13797 - 13804 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.02.2022
Springer Nature B.V |
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Online Access | Get full text |
ISSN | 0944-1344 1614-7499 1614-7499 |
DOI | 10.1007/s11356-021-16580-w |
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Abstract | Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily data on air pollutants, meteorological factors, and hospitalizations for gout between 1January 2016 and 31 December 2020 in Anqing City, China. We used Poisson generalized linear regression model and a distributed lag non-linear model (DLNM) to explore the relationship of high temperature, diurnal temperature range (DTR), and temperature change between neighboring days (TCN) with hospitalizations for gout. Stratified analysis by gender (male, female) and age (<65 years, ≥65 years) was conducted. Hospitalizations for gout attributed to high temperature, high DTR, and high TCN were also quantified. A total of 8675 hospitalized patients with gout were reported during the study period. We observed that exposure to high temperature was linked with an increased risk of hospitalizations for gout (lag 0, RR: 1.081, 95% confidence interval (CI): 1.011, 1.155). Exposure to high DTR was also associated with increased risk of hospitalizations for gout (lag9, RR: 1.017, 95% CI: 1.001,1.035). A large drop in temperature between neighboring days was associated an increased risk of hospitalizations for gout (lag 0–2 days, RR: 1.234, 95% CI: 1.017, 1.493). Stratified analysis results revealed that older adults and men were more sensitive to high-level DTR exposure than their counterparts. Nearly 15% of hospitalizations for gout could be attributable to high temperature (attributable fraction: 14.93%, 95% CI: 5.99%, 22.11%). This study suggests that high temperature and high temperature variation may trigger hospitalizations for gout, indicating that patients with gout need to take proactive actions in the face of days with non-optimal temperature. |
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AbstractList | Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily data on air pollutants, meteorological factors, and hospitalizations for gout between 1January 2016 and 31 December 2020 in Anqing City, China. We used Poisson generalized linear regression model and a distributed lag non-linear model (DLNM) to explore the relationship of high temperature, diurnal temperature range (DTR), and temperature change between neighboring days (TCN) with hospitalizations for gout. Stratified analysis by gender (male, female) and age (<65 years, ≥65 years) was conducted. Hospitalizations for gout attributed to high temperature, high DTR, and high TCN were also quantified. A total of 8675 hospitalized patients with gout were reported during the study period. We observed that exposure to high temperature was linked with an increased risk of hospitalizations for gout (lag 0, RR: 1.081, 95% confidence interval (CI): 1.011, 1.155). Exposure to high DTR was also associated with increased risk of hospitalizations for gout (lag9, RR: 1.017, 95% CI: 1.001,1.035). A large drop in temperature between neighboring days was associated an increased risk of hospitalizations for gout (lag 0–2 days, RR: 1.234, 95% CI: 1.017, 1.493). Stratified analysis results revealed that older adults and men were more sensitive to high-level DTR exposure than their counterparts. Nearly 15% of hospitalizations for gout could be attributable to high temperature (attributable fraction: 14.93%, 95% CI: 5.99%, 22.11%). This study suggests that high temperature and high temperature variation may trigger hospitalizations for gout, indicating that patients with gout need to take proactive actions in the face of days with non-optimal temperature. Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily data on air pollutants, meteorological factors, and hospitalizations for gout between 1January 2016 and 31 December 2020 in Anqing City, China. We used Poisson generalized linear regression model and a distributed lag non-linear model (DLNM) to explore the relationship of high temperature, diurnal temperature range (DTR), and temperature change between neighboring days (TCN) with hospitalizations for gout. Stratified analysis by gender (male, female) and age (<65 years, ≥65 years) was conducted. Hospitalizations for gout attributed to high temperature, high DTR, and high TCN were also quantified. A total of 8675 hospitalized patients with gout were reported during the study period. We observed that exposure to high temperature was linked with an increased risk of hospitalizations for gout (lag 0, RR: 1.081, 95% confidence interval (CI): 1.011, 1.155). Exposure to high DTR was also associated with increased risk of hospitalizations for gout (lag9, RR: 1.017, 95% CI: 1.001,1.035). A large drop in temperature between neighboring days was associated an increased risk of hospitalizations for gout (lag 0-2 days, RR: 1.234, 95% CI: 1.017, 1.493). Stratified analysis results revealed that older adults and men were more sensitive to high-level DTR exposure than their counterparts. Nearly 15% of hospitalizations for gout could be attributable to high temperature (attributable fraction: 14.93%, 95% CI: 5.99%, 22.11%). This study suggests that high temperature and high temperature variation may trigger hospitalizations for gout, indicating that patients with gout need to take proactive actions in the face of days with non-optimal temperature.Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily data on air pollutants, meteorological factors, and hospitalizations for gout between 1January 2016 and 31 December 2020 in Anqing City, China. We used Poisson generalized linear regression model and a distributed lag non-linear model (DLNM) to explore the relationship of high temperature, diurnal temperature range (DTR), and temperature change between neighboring days (TCN) with hospitalizations for gout. Stratified analysis by gender (male, female) and age (<65 years, ≥65 years) was conducted. Hospitalizations for gout attributed to high temperature, high DTR, and high TCN were also quantified. A total of 8675 hospitalized patients with gout were reported during the study period. We observed that exposure to high temperature was linked with an increased risk of hospitalizations for gout (lag 0, RR: 1.081, 95% confidence interval (CI): 1.011, 1.155). Exposure to high DTR was also associated with increased risk of hospitalizations for gout (lag9, RR: 1.017, 95% CI: 1.001,1.035). A large drop in temperature between neighboring days was associated an increased risk of hospitalizations for gout (lag 0-2 days, RR: 1.234, 95% CI: 1.017, 1.493). Stratified analysis results revealed that older adults and men were more sensitive to high-level DTR exposure than their counterparts. Nearly 15% of hospitalizations for gout could be attributable to high temperature (attributable fraction: 14.93%, 95% CI: 5.99%, 22.11%). This study suggests that high temperature and high temperature variation may trigger hospitalizations for gout, indicating that patients with gout need to take proactive actions in the face of days with non-optimal temperature. |
Author | Wu, Zheng-Dong Fang, Xin-Yu Wang, Gui-Hong Tao, Jin-Hui Sam, Napoleon Bellua Pan, Hai-Feng He, Yi-Sheng Chen, Yue Xu, Zhiwei |
Author_xml | – sequence: 1 givenname: Yi-Sheng surname: He fullname: He, Yi-Sheng organization: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Inflammation and Immune Mediated Diseases Laboratory of Anhui Province – sequence: 2 givenname: Gui-Hong surname: Wang fullname: Wang, Gui-Hong organization: Department of Rheumatology, Anqing Hospital Affiliated to Anhui Medical University – sequence: 3 givenname: Zheng-Dong surname: Wu fullname: Wu, Zheng-Dong organization: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Inflammation and Immune Mediated Diseases Laboratory of Anhui Province – sequence: 4 givenname: Napoleon Bellua surname: Sam fullname: Sam, Napoleon Bellua organization: Department of Medical Research and Innovation, School of Medicine, University for Development Studies – sequence: 5 givenname: Yue surname: Chen fullname: Chen, Yue organization: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Inflammation and Immune Mediated Diseases Laboratory of Anhui Province – sequence: 6 givenname: Jin-Hui surname: Tao fullname: Tao, Jin-Hui organization: Department of Rheumatology and Immunology, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China – sequence: 7 givenname: Xin-Yu surname: Fang fullname: Fang, Xin-Yu organization: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Inflammation and Immune Mediated Diseases Laboratory of Anhui Province – sequence: 8 givenname: Zhiwei surname: Xu fullname: Xu, Zhiwei email: xzw1011@gmail.com organization: School of Public Health, Faculty of Medicine, University of Queensland – sequence: 9 givenname: Hai-Feng orcidid: 0000-0001-8218-5747 surname: Pan fullname: Pan, Hai-Feng email: panhaifeng1982@sina.com organization: Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Inflammation and Immune Mediated Diseases Laboratory of Anhui Province |
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Keywords | Diurnal temperature range Temperature change between neighboring days High temperature Gout |
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SubjectTerms | Aged air Air pollution Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution China China - epidemiology confidence interval Confidence intervals Earth and Environmental Science Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental science Exposure Female females Gout Gout - epidemiology High temperature High temperature effects Hospitalization Hot Temperature Humans Male males Men nonlinear models Older people Pollutants regression analysis Regression models Research Article Risk Statistical analysis Temperature Time series time series analysis Waste Water Technology Water Management Water Pollution Control |
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Title | Association between non-optimal temperature and hospitalizations for gout in Anqing, China: a time-series analysis |
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