1
|
Guo C, Cai K, Chen G, Wang J, Zeng J, Huang X, Deng M. Daily diurnal temperature range associated with emergency ambulance calls: a nine-year time-series study. Front Public Health 2024; 12:1454097. [PMID: 39421822 PMCID: PMC11484036 DOI: 10.3389/fpubh.2024.1454097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 08/27/2024] [Indexed: 10/19/2024] Open
Abstract
Background Diurnal temperature range (DTR) is associated with the increased risk of morbidity and mortality. However, the relationship between DTR and emergency ambulance calls (EACs), which more accurately and immediately reflect the health impacts of temperature changes, remains underexplored in China. Methods We collected daily data on EACs and meteorological factors from 2009 to 2017 in Guangzhou, China. DTR, representing the temperature range within a day, was calculated by subtracting the minimum temperature from the maximum temperature for each day. Generalized additive models were used to estimate the association between DTR and EACs for all-cause, cardiovascular diseases, and respiratory diseases. Additionally, subgroup and sensitivity analyses were conducted in our study. Results We found significant associations between daily DTR and EACs. The excess risks (ERs) were 0.47% (95% CI: 0.14, 0.81%) for all-cause EACs, 0.94% (95% CI: 0.46, 1.43%) for cardiovascular-related EACs, and 1.31% (95% CI: 0.76, 1.86%) for respiratory -related EACs at lag01, respectively. Subgroup analyses indicated that these associations were notably stronger among the older, males, and during the warm season. Specifically, there was an increase of 1.16% (95% CI: 0.59, 1.74%) in cardiovascular-related EACs among the older adult, compared to 0.45% (95% CI: -0.21, 1.12%) among those younger than 65 years. Among males, the increase was 1.39% (95% CI: 0.79, 1.99%), compared to 0.13% (95% CI: -0.53, 0.79%) among females. During the warm season, the increase was 1.53% (95% CI: 0.74, 2.34%), compared to 0.75% (95% CI: 0.14, 1.37%) during the cold season. Conclusion DTR might increase the risk of daily all-cause, cardiovascular-related, and respiratory-related EACs in Guangzhou, China. The associations were particularly strong among older adults, males, and during the warm season. Implementing public health policies is essential to mitigate the adverse health effects of DTR.
Collapse
Affiliation(s)
- Chaohui Guo
- Department of Clinical Psychology, The Third Hospital of Quzhou, Quzhou, China
| | - Keke Cai
- Department of Traditional Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Gao Chen
- Department of Traditional Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jin Wang
- Department of Traditional Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Jie Zeng
- Department of Internet Medical Center, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Xiaoqing Huang
- Department of Traditional Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China
| | - Mengling Deng
- Department of Psychiatry, The Third Hospital of Quzhou, Quzhou, China
| |
Collapse
|
2
|
Chen Y, Zhou L, Zha Y, Wang Y, Wang K, Lu L, Guo P, Zhang Q. Impact of Ambient Temperature on Mortality Burden and Spatial Heterogeneity in 16 Prefecture-Level Cities of a Low-Latitude Plateau Area in Yunnan Province: Time-Series Study. JMIR Public Health Surveill 2024; 10:e51883. [PMID: 39045874 PMCID: PMC11287102 DOI: 10.2196/51883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 05/14/2024] [Accepted: 05/28/2024] [Indexed: 07/25/2024] Open
Abstract
Background The relation between climate change and human health has become one of the major worldwide public health issues. However, the evidence for low-latitude plateau regions is limited, where the climate is unique and diverse with a complex geography and topography. objectives This study aimed to evaluate the effect of ambient temperature on the mortality burden of nonaccidental deaths in Yunnan Province and to further explore its spatial heterogeneity among different regions. Methods We collected mortality and meteorological data from all 129 counties in Yunnan Province from 2014 to 2020, and 16 prefecture-level cities were analyzed as units. A distributed lagged nonlinear model was used to estimate the effect of temperature exposure on years of life lost (YLL) for nonaccidental deaths in each prefecture-level city. The attributable fraction of YLL due to ambient temperature was calculated. A multivariate meta-analysis was used to obtain an overall aggregated estimate of effects, and spatial heterogeneity among 16 prefecture-level cities was evaluated by adjusting the city-specific geographical characteristics, demographic characteristics, economic factors, and health resources factors. Results The temperature-YLL association was nonlinear and followed slide-shaped curves in all regions. The cumulative cold and heat effect estimates along lag 0-21 days on YLL for nonaccidental deaths were 403.16 (95% empirical confidence interval [eCI] 148.14-615.18) and 247.83 (95% eCI 45.73-418.85), respectively. The attributable fraction for nonaccidental mortality due to daily mean temperature was 7.45% (95% eCI 3.73%-10.38%). Cold temperature was responsible for most of the mortality burden (4.61%, 95% eCI 1.70-7.04), whereas the burden due to heat was 2.84% (95% eCI 0.58-4.83). The vulnerable subpopulations include male individuals, people aged <75 years, people with education below junior college level, farmers, nonmarried individuals, and ethnic minorities. In the cause-specific subgroup analysis, the total attributable fraction (%) for mean temperature was 13.97% (95% eCI 6.70-14.02) for heart disease, 11.12% (95% eCI 2.52-16.82) for respiratory disease, 10.85% (95% eCI 6.70-14.02) for cardiovascular disease, and 10.13% (95% eCI 6.03-13.18) for stroke. The attributable risk of cold effect for cardiovascular disease was higher than that for respiratory disease cause of death (9.71% vs 4.54%). Furthermore, we found 48.2% heterogeneity in the effect of mean temperature on YLL after considering the inherent characteristics of the 16 prefecture-level cities, with urbanization rate accounting for the highest proportion of heterogeneity (15.7%) among urban characteristics. Conclusions This study suggests that the cold effect dominated the total effect of temperature on mortality burden in Yunnan Province, and its effect was heterogeneous among different regions, which provides a basis for spatial planning and health policy formulation for disease prevention.
Collapse
Affiliation(s)
- Yang Chen
- School of Public Health, Kunming Medical University, Kunming, China
- Institute for Noncommunicable Disease Prevention and Control, Yunnan Centers for Disease Prevention and Control, Kunming, China
| | - Lidan Zhou
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Yuanyi Zha
- Graduate School, Kunming University of Medical, Kunming, China
| | - Yujin Wang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Kai Wang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Lvliang Lu
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, China
| |
Collapse
|
3
|
Amoatey P, Osborne NJ, Darssan D, Xu Z, Doan QV, Phung D. The effects of diurnal temperature range on mortality and emergency department presentations in Victoria state of Australia: A time-series analysis. ENVIRONMENTAL RESEARCH 2024; 240:117397. [PMID: 37879389 DOI: 10.1016/j.envres.2023.117397] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/30/2023] [Accepted: 10/11/2023] [Indexed: 10/27/2023]
Abstract
State of Victoria, Australia (SVA) has a wide variation of diurnal temperatures (DTR). DTR has been reported to be associated with risk of mortality and morbidity. We examined the association between exposure to DTR and risk of all-cause mortality and emergency department (ED) presentations in the SVA. We obtained data on daily counts of deaths and ED presentations, and weather data from 1 st January 2000─2019. We applied a quasi-Poisson time-series regression analysis to examine the association between daily DTR exposures and risk of mortality and ED presentations. The analyses were queried by age, sex, seasons, ED presentations triages, and departure status. Risk of mortality and ED presentation increased by 0.33% (95% CI: 0.24%-0.43%), and 0.094% (95% CI: 0.077%-0.11%) in relation to one degree increase in the daily DTR. The association between DTR and ED presentations was stronger in children (0-15 years) (0.38% [95% CI: 0.34%-0.42%]) and the elderly (75+ years) (0.34% [95% CI: 0.29%-0.39%]). Resuscitation, which was consistently accounted for the highest vulnerability to DTR variation, increased by 0.79% (95% CI: 0.60%-0.99%). This study suggests that the risk of mortality and ED presentations associates with the increase of DTR. Children, the elderly, and their caregivers need to be made aware of the health risk posed by DTR.
Collapse
Affiliation(s)
- Patrick Amoatey
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia
| | - Nicholas J Osborne
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia; School of Population Health, University of New South Wales, Sydney, NSW 2052, Australia; European Centre for Environment and Human Health (ECEHH), University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Truro TR1 3HD, Cornwall, UK; Queensland Alliance for Environmental Health Sciences, The University of Queensland, Australia
| | - Darsy Darssan
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia
| | - Zhiwei Xu
- School of Medicine and Dentistry, Griffith University, Australia
| | - Quang-Van Doan
- Center for Computational Sciences, University of Tsukuba, Japan
| | - Dung Phung
- School of Public Health, Faculty of Medicine, The University of Queensland, Australia; Queensland Alliance for Environmental Health Sciences, The University of Queensland, Australia.
| |
Collapse
|
4
|
Zhang T, Ni M, Jia J, Deng Y, Sun X, Wang X, Chen Y, Fang L, Zhao H, Xu S, Ma Y, Zhu J, Pan F. Research on the relationship between common metabolic syndrome and meteorological factors in Wuhu, a subtropical humid city of China. BMC Public Health 2023; 23:2363. [PMID: 38031031 PMCID: PMC10685562 DOI: 10.1186/s12889-023-17299-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 11/22/2023] [Indexed: 12/01/2023] Open
Abstract
As climate conditions deteriorate, human health faces a broader range of threats. This study aimed to determine the risk of death from metabolic syndrome (MetS) due to meteorological factors. We collected daily data from 2014 to 2020 in Wuhu City, including meteorological factors, environmental pollutants and death data of common MetS (hypertension, hyperlipidemia and diabetes), as well as a total number of 15,272 MetS deaths. To examine the relationship between meteorological factors, air pollutants, and MetS mortality, we used a generalized additive model (GAM) combined with a distributed delay nonlinear model (DLNM) for time series analysis. The relationship between the above factors and death outcomes was preliminarily evaluated using Spearman analysis and structural equation modeling (SEM). As per out discovery, diurnal temperature range (DTR) and daily mean temperature (T mean) increased the MetS mortality risk notably. The ultra low DTR raised the MetS mortality risk upon the general people, with the highest RR value of 1.033 (95% CI: 1.002, 1.065) at lag day 14. In addition, T mean was also significantly associated with MetS death. The highest risk of ultra low and ultra high T mean occured on the same day (lag 14), RR values were 1.043 (95% CI: 1.010, 1.077) and 1.032 (95% CI: 1.003, 1.061) respectively. Stratified analysis's result showed lower DTR had a more pronounced effect on women and the elderly, and ultra low and high T mean was a risk factor for MetS mortality in women and men. The elderly need to take extra note of temperature changes, and different levels of T mean will increase the risk of death. In warm seasons, ultra high RH and T mean can increase the mortality rate of MetS patients.
Collapse
Affiliation(s)
- Tao Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Man Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Juan Jia
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Yujie Deng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Xiaoya Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Xinqi Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Yuting Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Lanlan Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Hui Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- Department of Hospital Management Research, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230032, China
| | - Shanshan Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Yubo Ma
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China
| | - Jiansheng Zhu
- Wuhu center for disease control and prevention, Wuhu, Anhui, China
| | - Faming Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
- The Key Laboratory of Major Autoimmune Diseases, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
- Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| |
Collapse
|
5
|
Wang L, Cheng J, Yu G, Zong Q, Zhai C, Hu W, Wang Y, Yan Z, Zhang T, Wang J, Zhang C, Su H, Zou Y. Impact of diurnal temperature range on other infectious diarrhea in Tongcheng, China, 2010-2019: a distributed lag non-linear analysis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:51089-51098. [PMID: 36808040 DOI: 10.1007/s11356-023-25992-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 02/14/2023] [Indexed: 04/16/2023]
Abstract
Our study aimed to quantify the exposure-lag-response effects of the diurnal temperature range (DTR) on other infectious diarrhea (OID) in Tongcheng city and examine the vulnerable populations. Distributed lag non-linear model (DLNM) and generalized additive model (GAM) were applied jointly to quantify the association between DTR and the daily number of OID cases compared with the median DTR. Stratified analysis was performed by gender, age, and seasons of onset. There are a total of 8231 cases during this decade. We observed a j-shaped relationship between DTR and OID, with a peak point at the maximum DTR (RR: 2.651, 95% CI: 1.320-5.323) compared to the median DTR. As DTR increased from 8.2 to 10.9 °C, we found the RRs started to decrease and then rise from day 0, and the minimum value occurred on day 7 (RR:1.003, 95% CI: 0.996-1.010). From stratified analysis, we observed that females and adults are more likely to be affected by high DTR significantly. In addition, the influence of DTR was different in cold and warm seasons. High DTR in warm seasons affects the number of OID daily cases, but no statistical significance was identified in cold seasons. This study suggests a significant relationship between high DTR and the incidence risk of OID.
Collapse
Affiliation(s)
- Linlin Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Guanghui Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Qiqun Zong
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Chunxia Zhai
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Wanqin Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Yuhua Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Ziye Yan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Tingyu Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Junwu Wang
- Tongcheng Center for Disease Control and Prevention, Tongcheng, China
| | - Chengye Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Hong Su
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China
| | - Yanfeng Zou
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81, Meishan Road, Hefei, 230032, Anhui, China.
| |
Collapse
|
6
|
Jin X, Xu Z, Liang Y, Sun X, Yan S, Wu Y, Li Y, Mei L, Cheng J, Wang X, Song J, Pan R, Yi W, Yang Z, Su H. The modification of air particulate matter on the relationship between temperature and childhood asthma hospitalization: An exploration based on different interaction strategies. ENVIRONMENTAL RESEARCH 2022; 214:113848. [PMID: 35817164 DOI: 10.1016/j.envres.2022.113848] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/28/2022] [Accepted: 07/05/2022] [Indexed: 06/15/2023]
Abstract
The influence of temperature on childhood asthma was self-evident, yet the issue of whether the relationship will be synergized by air pollution remains unclear. The study aimed to investigate whether the relationship between short-term temperature exposure and childhood asthma hospitalization was modified by particulate matter (PM). Data on childhood asthma hospitalization, meteorological factors, and air pollutants during 2013-2016 in Hefei, China, were collected. First, a basic Poisson regression model combined with a distributed lag nonlinear model was used to assess the temperature-childhood asthma hospitalization relationship. Then, two interactive strategies were applied to explore the modification effect of PM on the temperature-childhood asthma hospitalization association. We found a greater effect of cold (5th percentile of temperature) on asthma during days with higher PM2.5 (RR: 2.16, 95% CI: 1.38, 3.38) or PM10 (RR: 1.87, 95% CI:1.20, 2.91) than that during days with lower PM2.5 (RR: 1.64, 95% CI: 1.06, 2.54) or PM10 (RR: 1.52, 95% CI: 0.98, 2.36). In addition, we observed a greater modification effect of PM2.5 on the cold-asthma association than did PM10, with a per 10 μg/m3 increase in PM2.5 and PM10 associated with increases of 0.065 and 0.025 for the RR corresponding to the 5th temperature percentile, respectively. For the temperature-related AF, moderate cold showed the largest change magnitude with the PM levels rising compared with other temperature ranges. For the subgroup, Females and those aged 6-18 years were more sensitive to the modification effect of PM2.5 or PM10 on the cold-asthma association. Our findings demonstrated that particulate matter could modify the associations between temperature and childhood asthma hospitalization.
Collapse
Affiliation(s)
- Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xu Wang
- Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zeyu Yang
- Anhui Provincial Children's Hospital, Hefei, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
| |
Collapse
|
7
|
Zhang Z, Xu D, Chen J, Meng Q, Liang Z, Zhang X. Daily diurnal temperature range associated with outpatient visits of acute lower respiratory infection in children: A time-series study in Guangzhou, China. Front Public Health 2022; 10:951590. [PMID: 36339182 PMCID: PMC9632279 DOI: 10.3389/fpubh.2022.951590] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/23/2022] [Indexed: 01/24/2023] Open
Abstract
Background Diurnal 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. Methods A 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. Results Diurnal 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. Conclusion Diurnal 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.
Collapse
Affiliation(s)
| | | | | | | | - Zhenyu Liang
- Department of Pediatrics, Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Xiao Zhang
- Department of Pediatrics, Guangdong Second Provincial General Hospital, Guangzhou, China
| |
Collapse
|
8
|
Zhang F, Wu C, Zhang M, Zhang H, Feng H, Zhu W. The association between diurnal temperature range and clinic visits for upper respiratory tract infection among college students in Wuhan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:2287-2297. [PMID: 34363175 DOI: 10.1007/s11356-021-15777-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/29/2021] [Indexed: 06/13/2023]
Abstract
The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.
Collapse
Affiliation(s)
- Faxue Zhang
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Chuangxin Wu
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Miaoxuan Zhang
- Hospital of Wuhan University, Wuhan, 430072, Hubei, China
| | - Han Zhang
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Huan Feng
- Department of Epidemiology and Biostatistics, School of Health Sciences, Wuhan University, Wuhan, 430071, China
| | - Wei Zhu
- Department of Occupational and Environmental Health, School of Health Sciences, Wuhan University, Wuhan, 430071, China.
| |
Collapse
|
9
|
Wang Y, Chen Y, Chen J, Wu R, Guo P, Zha S, Zhang Q. Mortality risk attributable to diurnal temperature range: a multicity study in Yunnan of southwest China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:60597-60608. [PMID: 34160766 DOI: 10.1007/s11356-021-14981-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/11/2021] [Indexed: 02/05/2023]
Abstract
We aimed to estimate the non-accidental and cause-specific mortality burden attributed to diurnal temperature range (DTR) and the relative contributions of low, high, and extremely low and extremely high DTR in Yunnan, southwest China. Furthermore, we explored the possible effect modification of the DTR-mortality association by season, sex, age, ethnicity, marital status, and occupation. A standard time-series quasi-Poisson regression model combined with a distributed lag nonlinear model was used to derive estimates of city-specific DTR-mortality associations, then random effects meta-analysis was used to pool the estimated city-specific overall cumulative DTR-mortality association, estimating empirical confidence intervals (eCIs). The overall fraction of non-accidental mortality caused by DTR was 11.00% (95% eCI 3.40-17.28): high DTR accounted for most of burden (total estimate 10.03%, 95% eCI 2.59-16.32). The estimated mortality risk attributable to DTR was significantly associated with cardiovascular and respiratory mortality, with attributable fractions of 13.61% (95% eCI 3.91-21.13) and 14.32% (95% eCI 0.47-21.44), respectively. The estimated risk attributable to DTR was slightly greater for males, people ≥75 years old, married people, and non-farmers than their corresponding categories. Most of the DTR-related mortality burden was attributable to high DTR, and the mortality risk attributable to DTR might be modified by specific causes, sex, age, marital status, and occupation.
Collapse
Affiliation(s)
- Yujin Wang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Yang Chen
- Yunnan Center for Disease Control and Prevention, Kunming, 650022, Yunnan, China
| | - Jiaqi Chen
- Department of Preventive Medicine, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Rong Wu
- Department of Preventive Medicine, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Shun Zha
- Yunnan Center for Disease Control and Prevention, Kunming, 650022, Yunnan, China.
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, Shantou, 515041, Guangdong, China.
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Cancer Hospital of Shantou University Medical College, Shantou, 515041, China.
| |
Collapse
|
10
|
Xiao Y, Meng C, Huang S, Duan Y, Liu G, Yu S, Peng J, Cheng J, Yin P. Short-Term Effect of Temperature Change on Non-Accidental Mortality in Shenzhen, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18168760. [PMID: 34444520 PMCID: PMC8392083 DOI: 10.3390/ijerph18168760] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/14/2021] [Accepted: 08/16/2021] [Indexed: 11/16/2022]
Abstract
Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.
Collapse
Affiliation(s)
- Yao Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan 430030, China; (Y.X.); (C.M.); (Y.D.)
| | - Chengzhen Meng
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan 430030, China; (Y.X.); (C.M.); (Y.D.)
| | - Suli Huang
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen 518055, China; (S.H.); (G.L.); (S.Y.)
| | - Yanran Duan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan 430030, China; (Y.X.); (C.M.); (Y.D.)
| | - Gang Liu
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen 518055, China; (S.H.); (G.L.); (S.Y.)
| | - Shuyuan Yu
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen 518055, China; (S.H.); (G.L.); (S.Y.)
| | - Ji Peng
- Shenzhen Center for Chronic Disease Control, 2021 Buxin Rd, Shenzhen 518020, China
- Correspondence: (J.P.); (J.C.); (P.Y.)
| | - Jinquan Cheng
- Shenzhen Center for Disease Control and Prevention, 8 Longyuan Rd, Shenzhen 518055, China; (S.H.); (G.L.); (S.Y.)
- Correspondence: (J.P.); (J.C.); (P.Y.)
| | - Ping Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan 430030, China; (Y.X.); (C.M.); (Y.D.)
- Correspondence: (J.P.); (J.C.); (P.Y.)
| |
Collapse
|
11
|
He Y, Tang C, Liu X, Yu F, Wei Q, Pan R, Yi W, Gao J, Xu Z, Duan J, Su H. Effect modification of the association between diurnal temperature range and hospitalisations for ischaemic stroke by temperature in Hefei, China. Public Health 2021; 194:208-215. [PMID: 33962098 DOI: 10.1016/j.puhe.2020.12.019] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 10/17/2020] [Accepted: 12/30/2020] [Indexed: 01/21/2023]
Abstract
OBJECTIVES Diurnal temperature range (DTR) is an important indicator of global climate change. Many epidemiological studies have reported the associations between high DTR and human health. This study investigated the association between DTR and hospitalisations for ischaemic stroke in Hefei, China. STUDY DESIGN This is an ecological study. METHODS Data of daily hospital admissions for ischaemic stroke and meteorological variables from 1 January 2009 to 31 December 2017 were collected in Hefei, China. A generalised additive model combined with distributed lag non-linear model was used to quantify the effects of DTR on ischaemic stroke. The interactive effect between DTR and temperature was explored with a non-parametric bivariate response surface model. RESULTS High DTR was associated with hospitalisations for ischaemic stroke. The adverse effect of extremely high DTR (99th percentile [17.1 °C]) occurred after 8 days (relative risk [RR] = 1.021, 95% confidence interval [CI] = 1.002, 1.041) and the maximum effect appeared after 12 days (RR = 1.029, 95% CI = 1.011, 1.046). The overall trend of the effect of DTR on ischaemic stroke was decreasing. In addition, there was a significant interactive effect of high DTR and low temperature on ischaemic stroke. CONCLUSIONS This study suggests that the impact of high DTR should be considered when formulating targeted measures to prevent ischaemic stroke, especially for those days with high DTR and low mean temperature.
Collapse
Affiliation(s)
- Y He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - C Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - X Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - F Yu
- Anhui Provincial Hospital, China
| | - Q Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - R Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - W Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - J Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Z Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - J Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - H Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
| |
Collapse
|
12
|
Lee W, Kim Y, Sera F, Gasparrini A, Park R, Michelle Choi H, Prifti K, Bell ML, Abrutzky R, Guo Y, Tong S, de Sousa Zanotti Stagliorio Coelho M, Nascimento Saldiva PH, Lavigne E, Orru H, Indermitte E, Jaakkola JJK, Ryti NRI, Pascal M, Goodman P, Zeka A, Hashizume M, Honda Y, Hurtado Diaz M, César Cruz J, Overcenco A, Nunes B, Madureira J, Scovronick N, Acquaotta F, Tobias A, Vicedo-Cabrera AM, Ragettli MS, Guo YLL, Chen BY, Li S, Armstrong B, Zanobetti A, Schwartz J, Kim H. Projections of excess mortality related to diurnal temperature range under climate change scenarios: a multi-country modelling study. Lancet Planet Health 2020; 4:e512-e521. [PMID: 33159878 PMCID: PMC7869581 DOI: 10.1016/s2542-5196(20)30222-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 08/27/2020] [Accepted: 08/27/2020] [Indexed: 05/24/2023]
Abstract
BACKGROUND Various retrospective studies have reported on the increase of mortality risk due to higher diurnal temperature range (DTR). This study projects the effect of DTR on future mortality across 445 communities in 20 countries and regions. METHODS DTR-related mortality risk was estimated on the basis of the historical daily time-series of mortality and weather factors from Jan 1, 1985, to Dec 31, 2015, with data for 445 communities across 20 countries and regions, from the Multi-Country Multi-City Collaborative Research Network. We obtained daily projected temperature series associated with four climate change scenarios, using the four representative concentration pathways (RCPs) described by the Intergovernmental Panel on Climate Change, from the lowest to the highest emission scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5). Excess deaths attributable to the DTR during the current (1985-2015) and future (2020-99) periods were projected using daily DTR series under the four scenarios. Future excess deaths were calculated on the basis of assumptions that warmer long-term average temperatures affect or do not affect the DTR-related mortality risk. FINDINGS The time-series analyses results showed that DTR was associated with excess mortality. Under the unmitigated climate change scenario (RCP 8.5), the future average DTR is projected to increase in most countries and regions (by -0·4 to 1·6°C), particularly in the USA, south-central Europe, Mexico, and South Africa. The excess deaths currently attributable to DTR were estimated to be 0·2-7·4%. Furthermore, the DTR-related mortality risk increased as the long-term average temperature increased; in the linear mixed model with the assumption of an interactive effect with long-term average temperature, we estimated 0·05% additional DTR mortality risk per 1°C increase in average temperature. Based on the interaction with long-term average temperature, the DTR-related excess deaths are projected to increase in all countries or regions by 1·4-10·3% in 2090-99. INTERPRETATION This study suggests that globally, DTR-related excess mortality might increase under climate change, and this increasing pattern is likely to vary between countries and regions. Considering climatic changes, our findings could contribute to public health interventions aimed at reducing the impact of DTR on human health. FUNDING Korea Ministry of Environment.
Collapse
Affiliation(s)
- Whanhee Lee
- Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | - Yoonhee Kim
- Department of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Francesco Sera
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Antonio Gasparrini
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Methodology, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Rokjin Park
- School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
| | | | - Kristi Prifti
- Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, South Korea
| | - Michelle L Bell
- School of the Environment, Yale University, New Haven, CT, USA
| | - Rosana Abrutzky
- Faculty of Social Sciences, Research Institute Gino Germani, University of Buenos Aires, Buenos Aries, Argentina
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Shilu Tong
- Shanghai Children's Medical Centre, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | | | | | - Eric Lavigne
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Air Health Science Division, Health Canada, Ottawa, ON, Canada
| | - Hans Orru
- Department of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Ene Indermitte
- Department of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Jouni J K Jaakkola
- Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland
| | - Niilo R I Ryti
- Center for Environmental and Respiratory Health Research, University of Oulu, Oulu, Finland
| | - Mathilde Pascal
- Department of Environmental Health, French National Public Health Agency, Public Health France, Saint Maurice, France
| | - Patrick Goodman
- School of Physics, Technological University Dublin, Dublin, Ireland
| | - Ariana Zeka
- Institute of Environment, Health and Societies, Brunel University London, London, UK
| | - Masahiro Hashizume
- Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yasushi Honda
- Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba, Japan
| | - Magali Hurtado Diaz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Julio César Cruz
- Department of Environmental Health, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - Ala Overcenco
- Laboratory of Management in Science and Public Health, National Agency for Public Health of the Ministry of Health, Chisinau, Republic of Moldova
| | - Baltazar Nunes
- Department of Epidemiology, National Institute of Health Dr Ricardo Jorge, Lisbon, Portugal
| | - Joana Madureira
- Department of Environmental Health, National Institute of Health Dr Ricardo Jorge, Lisbon, Portugal; EPIUnit, Institute of Public Health, University of Porto, Lisbon, Portugal
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | | | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research, IDAEA, Spanish Council for Scientific Research, CSIC, Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | | | - Martina S Ragettli
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Yue-Liang Leon Guo
- Environmental and Occupational Medicine, and Institute of Environmental and Occupational Health Sciences, National Taiwan University and National Taiwan University Hospital, Taipei, Taiwan; National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan
| | - Bing-Yu Chen
- National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan; National Institute of Environmental Health Science, National Health Research Institutes, Zhunan, Taiwan
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Ben Armstrong
- Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK
| | - Antonella Zanobetti
- Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Joel Schwartz
- Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Ho Kim
- Department of Public Health Science, Graduate School of Public Health, Seoul National University, Seoul, South Korea.
| |
Collapse
|
13
|
Wang Z, Zhou Y, Luo M, Yang H, Xiao S, Huang X, Ou Y, Zhang Y, Duan X, Hu W, Liao C, Zheng Y, Wang L, Xie M, Tang L, Zheng J, Liu S, Wu F, Deng Z, Tian H, Peng J, Wang X, Zhong N, Ran P. Association of diurnal temperature range with daily hospitalization for exacerbation of chronic respiratory diseases in 21 cities, China. Respir Res 2020; 21:251. [PMID: 32993679 PMCID: PMC7526384 DOI: 10.1186/s12931-020-01517-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 09/21/2020] [Indexed: 12/18/2022] Open
Abstract
Background The association between diurnal temperature range (DTR) and hospitalization for exacerbation of chronic respiratory diseases (CRD) was rarely reported. Objectives To examine the association between DTR and daily hospital admissions for exacerbation of CRD and find out the potential effect of modifications on this association. Method Data on daily hospitalization for exacerbation of chronic obstructive pulmonary disease (COPD), asthma and bronchiectasis and meteorology measures from 2013 through 2017 were obtained from 21 cities in South China. After controlling the effects of daily mean temperature, relative humidity (RH), particulate matter < 2.5 μm diameter (PM2.5) and other confounding factors, a standard generalized additive model (GAM) with a quasi-Poisson distribution was performed to evaluate the relationships between DTR and daily hospital admissions of CRD in a two-stage strategy. Subgroup analysis was performed to find potential modifications, including seasonality and population characteristics. Result Elevated risk of hospitalization for exacerbation of CRD (RR = 1.09 [95%CI: 1.08 to 1.11]) was associated with the increase in DTR (the 75th percentile versus the 25th percentile of DTR at lag0–6). The effects of DTR on hospital admissions for CRD were strong at low DTR in the hot season and high DTR in the cold season. The RR (the 75th percentile versus the 25th percentile of DTR at lag0–6) of hospitalization was 1.11 (95%CI: 1.08 to 1.12) for exacerbations of COPD and 1.09 (95%CI: 1.05 to 1.13) for asthma. The adverse effect of DTR on hospitalization for bronchiectasis was only observed in female patients (RR = 1.06 [95%CI: 1.03 to 1.10]). Conclusion Our study provided additional evidence for the association between DTR and daily hospitalization for exacerbation of CRD, and these associations are especially stronger in COPD patients and in the cold season than the hot season. Preventive measures to reduce the adverse impacts of DTR were needed for CRD patients.
Collapse
Affiliation(s)
- Zihui Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Yumin Zhou
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Ming Luo
- School of Geography and Planning, Sun Yat Sen University, Guangzhou, China
| | - Huajing Yang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Shan Xiao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Xiaoliang Huang
- Government Affairs Service Center of Health Commission of Guangdong Province, Guangzhou, China
| | - Yubo Ou
- Guangdong Environmental Monitoring Center, Guangzhou, China
| | - Yongbo Zhang
- Guangdong Provincial Academy of Environmental Science, Guangzhou, China
| | - Xianzhong Duan
- Department of Ecology and Environment of Guangdong Province, Guangzhou, China
| | - Wei Hu
- Government Affairs Service Center of Health Commission of Guangdong Province, Guangzhou, China
| | - Chenghao Liao
- Guangdong Provincial Academy of Environmental Science, Guangzhou, China
| | - Yijia Zheng
- Guangdong Provincial Academy of Environmental Science, Guangzhou, China
| | - Long Wang
- Guangdong Provincial Academy of Environmental Science, Guangzhou, China
| | - Min Xie
- Guangdong Environmental Monitoring Center, Guangzhou, China
| | - Longhui Tang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Jinzhen Zheng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Sha Liu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Fan Wu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Zhishan Deng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Heshen Tian
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Jieqi Peng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Xinwang Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Nanshan Zhong
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Pixin Ran
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China.
| |
Collapse
|
14
|
Wei Q, Zhong L, Gao J, Yi W, Pan R, Gao J, Duan J, Xu Z, He Y, Liu X, Tang C, Su H. Diurnal temperature range and childhood asthma in Hefei, China: Does temperature modify the association? THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 724:138206. [PMID: 32247134 DOI: 10.1016/j.scitotenv.2020.138206] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 03/23/2020] [Accepted: 03/23/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND The present study aimed to understand the effect of diurnal temperature range (DTR) on childhood asthma in Hefei, China, and to explore the effect of temperature on the DTR-asthma association. MATERIALS AND METHODS Daily data on hospital admissions for childhood asthma, air pollutants, and weather variables in Hefei, China, from 1st January 2014 to 31st December 2015, were collected. A generalized additive model combined with a distributed lag non-linear model was used to quantify the effects of DTR on the total, age- and gender-specific hospital admissions for childhood asthma. A non-parametric bivariate response surface model, and a generalized additive model combined with a stratified parametric model were used to explore the interaction between DTR and temperature. RESULTS We observed that high DTR was associated with an increase in hospital admissions for childhood asthma. When DTR increased from 6.7 °C to 16.8 °C (99% percentile), hospital admissions for childhood asthma increased by 13% (relative risk: 1.13, 95% confidence interval: 1.07, 1.12). The analysis stratified, by mean temperature level, suggested that when DTR increased by 1 °C at low temperatures, asthma hospitalizations in total children, girls, boys and school-age children increased by 5.0% (95% CI: 2.6%, 7.5%), 3.7% (95% CI: 0.4%, 5.7%), 2.9% (95% CI: 0.8%, 4.4%) and 5.0% (95% CI: 2.6%, 7.5%), respectively. CONCLUSIONS This study suggests that the impact of high DTR should be considered among public health advice for children with existing asthma. Those days with high DTR and low mean temperature need extra attention.
Collapse
Affiliation(s)
- Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Liqin Zhong
- The Second People's Hospital of Hefei, Hefei, Anhui 230011, China
| | - Jiaqi Gao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China.; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui 230032, China.
| |
Collapse
|