1
|
Niu YL, Lu F, Liu XJ, Wang J, Liu DL, Liu QY, Yang J. Global climate change: Effects of future temperatures on emergency department visits for mental disorders in Beijing, China. ENVIRONMENTAL RESEARCH 2024; 252:119044. [PMID: 38697599 DOI: 10.1016/j.envres.2024.119044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 04/08/2024] [Accepted: 04/27/2024] [Indexed: 05/05/2024]
Abstract
Rising temperatures can increase the risk of mental disorders. As climate change intensifies, the future disease burden due to mental disorders may be underestimated. Using data on the number of daily emergency department visits for mental disorders at 30 hospitals in Beijing, China during 2016-2018, the relationship between daily mean temperature and such visits was assessed using a quasi-Poisson model integrated with a distributed lag nonlinear model. Emergency department visits for mental disorders attributed to temperature changes were projected using 26 general circulation models under four climate change scenarios. Stratification analyses were then conducted by disease subtype, sex, and age. The results indicate that the temperature-related health burden from mental disorders was projected to increase consistently throughout the 21st century, mainly driven by high temperatures. The future temperature-related health burden was higher for patients with mental disorders due to the use of psychoactive substances and schizophrenia as well as for women and those aged <65 years. These findings enhance our knowledge of how climate change could affect mental well-being and can be used to advance and refine targeted approaches to mitigating and adapting to climate change with a view on addressing mental disorders.
Collapse
Affiliation(s)
- Yan-Lin Niu
- Institute for Nutrition and Food Hygiene, Beijing Center for Disease Prevention and Control, 100013 Beijing, China
| | - Feng Lu
- Beijing Municipal Health Big Data and Policy Research Center, 100034 Beijing, China
| | - Xue-Jiao Liu
- Department of Medical Record Management and Statistics, Beijing Jishuitan Hospital, Capital Medical University, Beijing 100035, China
| | - Jun Wang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - De Li Liu
- NSW Department of Primary Industries, Wagga Wagga Agricultural Institute, NSW 2650, Australia; Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
| | - Qi-Yong Liu
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Jun Yang
- School of Public Health, Guangzhou Medical University, 511436 Guangzhou, China.
| |
Collapse
|
2
|
Yin Z, Jingesi M, Yin Z, Chen S, Huang S, Cheng J, Li X, Liu N, Wang P, Yin P, Jiang H. Short-term effects of temperature-related indices on emergency ambulance dispatches due to mental and behavioral disorders in Shenzhen, China. Front Public Health 2024; 12:1343550. [PMID: 38883192 PMCID: PMC11177611 DOI: 10.3389/fpubh.2024.1343550] [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: 11/23/2023] [Accepted: 05/03/2024] [Indexed: 06/18/2024] Open
Abstract
Introduction The precise associations between temperature-related indices and mental and behavioral disorders (MBDs) have yet to be fully elucidated. Our study aims to ascertain the most effective temperature-related index and assess its immediate impact on emergency ambulance dispatches (EADs) due to MBDs in Shenzhen, China. Methods EADs data and meteorological data from January 1, 2013, to December 31, 2020, in Shenzhen were collected. Distributed lag non-linear models (DLNMs) were utilized to examine the non-linear and lagged effects of temperature-related indices on EADs due to MBDs. The Quasi Akaike Information criterion (QAIC) was used to determine the optimal index after standardizing temperature-related indices. After adjusting for confounding factors in the model, we estimated the immediate and cumulative effects of temperature on EADs due to MBDs. Results The analysis of short-term temperature effects on EADs due to MBDs revealed Humidex as the most suitable index. Referring to the optimal Humidex (3.2th percentile, 12.00°C), we observed a significant effect of Humidex over the threshold (34.6th percentile, 26.80°C) on EADs due to MBDs at lag 0-5. The cumulative relative risks for high temperature (90th percentile, 41.90°C) and extreme high temperature (99th percentile, 44.20°C) at lag 0-5 were 1.318 (95% CI: 1.159-1.499) and 1.338 (95% CI: 1.153-1.553), respectively. No significant cold effect was observed on EADs due to MBDs. Conclusion High Humidex was associated with more EADs due to MBDs in subtropical regions. Health authorities should implement effective measures to raise public awareness of risks related to high temperature and protect vulnerable populations.
Collapse
Affiliation(s)
- Ziming Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Maidina Jingesi
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao Yin
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Siyi Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Suli Huang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Jinquan Cheng
- Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Xiaoheng Li
- Department of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Ning Liu
- Department of Environment and Health, Shenzhen Center for Disease Control and Prevention, Shenzhen, China
| | - Peng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ping Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongwei Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
3
|
Bai X, Ming X, Zhao M, Zhou L. Explore the effect of apparent temperature and air pollutants on the admission rate of acute myocardial infarction in Chongqing, China: a time-series study. BMJ Open 2024; 14:e084376. [PMID: 38658006 PMCID: PMC11043748 DOI: 10.1136/bmjopen-2024-084376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/02/2024] [Indexed: 04/26/2024] Open
Abstract
OBJECTIVE Limited research has been conducted on the correlation between apparent temperature and acute myocardial infarction (AMI), as well as the potential impact of air pollutants in modifying this relationship. The objective of this study is to investigate the lagged effect of apparent temperature on AMI and assess the effect modification of environmental pollutants on this association. DESIGN A time-series study. SETTING AND PARTICIPANTS The data for this study were obtained from the Academy of Medical Data Science at Chongqing Medical University, covering daily hospitalisations for AMI between 1 January 2015 and 31 December 2016. Meteorological and air pollutant data were provided by China's National Meteorological Information Centre. OUTCOME MEASURES We used a combined approach of quasi-Poisson generalised linear model and distributed lag non-linear model to thoroughly analyse the relationships. Additionally, we employed a generalised additive model to investigate the interaction between air pollutants and apparent temperature on the effect of AMI. RESULT A total of 872 patients admitted to hospital with AMI were studied based on the median apparent temperature (20.43°C) in Chongqing. Low apparent temperature (10th, 7.19℃) has obvious lagged effect on acute myocardial infarction, first appearing on the 8th day (risk ratio (RR) 1.081, 95% CI 1.010 to 1.158) and the greatest risk on the 11th day (RR 1.094, 95% CI 1.037 to 1.153). No lagged effect was observed at high apparent temperature. In subgroup analysis, women and individuals aged 75 and above were at high risk. The interaction analysis indicates that there exist significant interactions between PM2.5 and high apparent temperature, as well as nitrogen dioxide (NO2) and low apparent temperature. CONCLUSION The occurrence of decreased apparent temperature levels was discovered to be linked with a heightened relative risk of hospitalisations for AMI. PM2.5 and NO2 have an effect modification on the association between apparent temperature and admission rate of AMI.
Collapse
Affiliation(s)
- Xiuyuan Bai
- School of Public Health, Chongqing Medical University, Chongqing, China
| | - Xin Ming
- Chongqing Health Center for Women and Children, Chongqing, China
- Department of quality management section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Epidemiology, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Mingming Zhao
- Department of Epidemiology, School of Public Health, Chongqing Medical University, Chongqing, China
| | - Li Zhou
- Department of Epidemiology, School of Public Health, Chongqing Medical University, Chongqing, China
| |
Collapse
|
4
|
Tupinier Martin F, Boudreault J, Campagna C, Lavigne É, Gamache P, Tandonnet M, Généreux M, Trottier S, Goupil-Sormany I. The relationship between hot temperatures and hospital admissions for psychosis in adults diagnosed with schizophrenia: A case-crossover study in Quebec, Canada. ENVIRONMENTAL RESEARCH 2024; 246:118225. [PMID: 38253191 DOI: 10.1016/j.envres.2024.118225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 01/24/2024]
Abstract
INTRODUCTION Some studies have found hot temperatures to be associated with exacerbations of schizophrenia, namely psychoses. As climate changes faster in Northern countries, our understanding of the association between temperature and hospital admissions (HA) for psychosis needs to be deepened. OBJECTIVES 1) Among adults diagnosed with schizophrenia, measure the relationship between mean temperatures and HAs for psychosis during summer. 2) Determine the influence of individual and ecological characteristics on this relationship. METHODS A cohort of adults diagnosed with schizophrenia (n = 30,649) was assembled using Quebec's Integrated Chronic Disease Surveillance System (QICDSS). The follow-up spanned summers from 2001 to 2019, using hospital data from the QICDSS and meteorological data from the National Aeronautics and Space Administration's (NASA) Daymet database. In four geographic regions of the province of Quebec, a conditional logistic regression was used for the case-crossover analysis of the relationship between mean temperatures (at lags up to 6 days) and HAs for psychosis using a distributed lag non-linear model (DLNM). The analyses were adjusted for relative humidity, stratified according to individual (age, sex, and comorbidities) and ecological (material and social deprivation index and exposure to green space) factors, and then pooled through a meta-regression. RESULTS The statistical analyses revealed a statistically significant increase in HAs three days (lag 3) after elevated mean temperatures corresponding to the 90th percentile relative to a minimum morbidity temperature (MMT) (OR 1.040; 95% CI 1.008-1.074), while the cumulative effect over six days was not statistically significant (OR 1.052; 95% IC 0.993-1.114). Stratified analyses revealed non statistically significant gradients of increasing HAs relative to increasing material deprivation and decreasing green space levels. CONCLUSIONS The statistical analyses conducted in this project showed the pattern of admissions for psychosis after hot days. This finding could be useful to better plan health services in a rapidly changing climate.
Collapse
Affiliation(s)
- Frédéric Tupinier Martin
- Centre intégré universitaire de santé et de services sociaux de la Capitale-Nationale, Quebec City (Quebec), Canada; Department of social and preventive medicine, Laval University, Quebec City (Quebec), Canada; Environmental and occupational health and toxicology unit, Quebec National Institute of Public Health, Quebec City (Quebec), Canada.
| | - Jérémie Boudreault
- Environmental and occupational health and toxicology unit, Quebec National Institute of Public Health, Quebec City (Quebec), Canada; Water Earth and Environment Research Center, National institute of scientific research (INRS), Quebec City (Quebec), Canada.
| | - Céline Campagna
- Department of social and preventive medicine, Laval University, Quebec City (Quebec), Canada; Environmental and occupational health and toxicology unit, Quebec National Institute of Public Health, Quebec City (Quebec), Canada; Water Earth and Environment Research Center, National institute of scientific research (INRS), Quebec City (Quebec), Canada.
| | - Éric Lavigne
- Environmental Health Science and Research Bureau, Health Canada, Ottawa (Ontario), Canada; School of Epidemiology & Public Health, University of Ottawa, Ottawa (Ontario), Canada.
| | - Philippe Gamache
- Bureau d'information et d'études en santé des populations (BIESP), Quebec National Institute of Public Health, Quebec City (Quebec), Canada.
| | - Matthieu Tandonnet
- Bureau d'information et d'études en santé des populations (BIESP), Quebec National Institute of Public Health, Quebec City (Quebec), Canada.
| | - Mélissa Généreux
- Department of Community health sciences, Faculty of medicine and health sciences, Sherbrooke University, Sherbrooke (Quebec), Canada; Estrie's Public Health Department, Sherbrooke (Quebec), Canada.
| | - Simon Trottier
- Service des bibliothèques et archives, Université de Sherbrooke, Sherbrooke (Quebec), Canada.
| | - Isabelle Goupil-Sormany
- Department of social and preventive medicine, Laval University, Quebec City (Quebec), Canada; Environmental and occupational health and toxicology unit, Quebec National Institute of Public Health, Quebec City (Quebec), Canada; Axe Santé des populations et pratiques optimales en santé, Centre de recherche du CHU de Québec - Laval University, Quebec City (Quebec), Canada.
| |
Collapse
|
5
|
Zhan ZY, Xu XY, Wei J, Fang HY, Zhong X, Liu ML, Chen ZS, Ye WM, He F. Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 271:115931. [PMID: 38215667 DOI: 10.1016/j.ecoenv.2024.115931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 12/30/2023] [Accepted: 01/02/2024] [Indexed: 01/14/2024]
Abstract
Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 μg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.
Collapse
Affiliation(s)
- Zhi-Ying Zhan
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China
| | - Xin-Ying Xu
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Hai-Yin Fang
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China; Fuzhou Center for Disease Control and Prevention, Fuzhou 350209, Fujian Province, China
| | - Xue Zhong
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China
| | - Mao-Lin Liu
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China
| | - Zi-Shan Chen
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China
| | - Wei-Min Ye
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China.
| | - Fei He
- Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou 350122, Fujian Province, China.
| |
Collapse
|
6
|
Li Y, Varghese BM, Liu J, Bi P, Tong M. Association between High Ambient Temperatures and Road Crashes in an Australian City with Temperate Climate: A Time-Series Study, 2012-2021. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6000. [PMID: 37297604 PMCID: PMC10252869 DOI: 10.3390/ijerph20116000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 05/20/2023] [Accepted: 05/24/2023] [Indexed: 06/12/2023]
Abstract
(1) Background: High ambient temperatures are associated with increased morbidity and mortality rates, and some evidence suggests that high temperatures increase the risk of road crashes. However, little is known regarding the burden of road crashes attributable to no-optimal high temperatures in Australia. Therefore, this study examined the effects of high temperatures on road crashes using Adelaide in South Australia as a case study. (2) Methods: Ten-year daily time-series data on road crashes (n = 64,597) and weather during the warm season (October-March) were obtained between 2012 and 2021. A quasi-Poisson distributed lag nonlinear model (DLNM) was used to quantify the cumulative effect of high temperatures over the previous five days. The associations and attributable burden at moderate and extreme temperature ranges were computed as relative risk (RR) and attributable fraction. (3) Results: There was a J-shaped association between high ambient temperature and the risk of road crashes during the warm season in Adelaide, and pronounced effects were observed for minimum temperatures. The highest risk was observed at a 1 day lag and lasting for 5 days. High temperatures were responsible for 0.79% (95% CI: 0.15-1.33%) of road crashes, with moderately high temperatures accounting for most of the burden compared with extreme temperatures (0.55% vs. 0.32%). (4) Conclusions: In the face of a warming climate, the finding draws the attention of road transport, policy, and public health planners to design preventive plans to reduce the risk of road crashes attributable to high temperatures.
Collapse
Affiliation(s)
- Yannan Li
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | | | - Jingwen Liu
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
| | - Michael Tong
- School of Public Health, The University of Adelaide, Adelaide, SA 5005, Australia
- National Centre for Epidemiology and Population Health, ANU College of Health and Medicine, The Australian National University, Canberra, ACT 2601, Australia
| |
Collapse
|
7
|
Hong J, Kang JM, Cho SE, Jung J, Kang SG. Significant association between increased risk of emergency department visits for psychiatric disorders and air pollutants in South Korea. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2023; 33:490-499. [PMID: 36496456 DOI: 10.1038/s41370-022-00504-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 11/20/2022] [Accepted: 11/23/2022] [Indexed: 06/03/2023]
Abstract
BACKGROUND The association between air pollutants and psychiatric disorders has been investigated in many countries. However, results for the association between air pollutants and emergency room (ER) visits for psychiatric disorders are inconsistent. Further, systematic large-scale studies relating to the same are lacking, especially in South Korea. OBJECTIVE We aimed to investigate the acute and short-term cumulative effect of air pollutants on ER visits for psychiatric disorders in South Korea. METHODS The data on nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) and ER visits due to nine representative psychiatric disorders were collected from eight major cities in South Korea for three years. We estimated the relative risk (RR) at lag 0 and a cumulative 11-day RR by increasing a 10-unit for PM and 0.01-unit for NO2 using the Distributed Lag Nonlinear Model. RESULTS During the study period, a total of 79,092 ER visits for psychiatric disorders were identified and tested for association with NO2, PM2.5, and PM10. The RR at lag 0 of depression per 0.01-unit increase in NO2 was the highest (3.127; 95% confidence interval [CI] 2.933 to 3.332) among the psychiatric disorders. The RRs at lag 0 of anxiety disorders per 10-unit increase in PM2.5 (1.709; 95% CI 1.424 to 2.053) and PM10 (2.168; 95% CI 1.957 to 2.403) were the highest among the psychiatric disorders. SIGNIFICANCE Air pollutants increased ER visits for psychiatric disorders with the highest RR of depression due to NO2 and anxiety disorder due to PM2.5 and PM10. These results contribute evidence to the positive association between ambient exposure to air pollution and aggravation of psychiatric disorders, indicating air pollution may be a modifiable risk factor in mental health management. IMPACT STATEMENT We investigated the effect of air pollution on emergency room visits caused by major psychiatric disorders in prominent cities in South Korea. Using the Distributed Lag Nonlinear Model, an advanced analysis method, we calculated the acute effect and short-term cumulative effect. Air pollutants increased ER visits for psychiatric disorders with the highest relative risk of depression due to NO2 and anxiety disorder due to PM2.5 and PM10. These results reveal an association between ambient exposure to air pollution and aggravation of psychiatric disorders and suggest that air pollution may be a modifiable risk factor in mental health management.
Collapse
Affiliation(s)
- Jinwook Hong
- Department of Preventive Medicine, Gachon University College of Medicine, Incheon, Republic of Korea
- Artificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea
| | - Jae Myeong Kang
- Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea
| | - Seo-Eun Cho
- Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea
| | - Jaehun Jung
- Department of Preventive Medicine, Gachon University College of Medicine, Incheon, Republic of Korea.
- Artificial Intelligence and Big-Data Convergence Center, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea.
| | - Seung-Gul Kang
- Department of Psychiatry, Gil Medical Center, Gachon University College of Medicine, Incheon, Republic of Korea.
| |
Collapse
|
8
|
Niu L, Girma B, Liu B, Schinasi LH, Clougherty JE, Sheffield P. Temperature and mental health-related emergency department and hospital encounters among children, adolescents and young adults. Epidemiol Psychiatr Sci 2023; 32:e22. [PMID: 37066768 PMCID: PMC10130844 DOI: 10.1017/s2045796023000161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 02/08/2023] [Accepted: 03/23/2023] [Indexed: 04/18/2023] Open
Abstract
AIMS We examine the association between high ambient temperature and acute mental health-related healthcare encounters in New York City for children, adolescents and young adults. METHODS This case-crossover study included emergency department (ED) visits and hospital encounters with a primary diagnosis of any mental health disorder during warm-season months (June-August) in New York City from 2005 to 2011 from patients of three age groups (6-11, 12-17 and 18-25 years). Using a distributed lag non-linear model over 0-5 lag days, by fitting a conditional logistic regression for each age group, we calculated the cumulative odds ratios of mental health encounters associated with an elevated temperature. Analyses were stratified by race/ethnicity, payment source and mental health categories to elucidate vulnerable subpopulations. RESULTS In New York City, there were 82,982 mental health-related encounters for young people aged 6 to 25 years during our study period months. Elevated temperature days were associated with higher risk of mental health-related ED and hospital encounters for the 6- to 11-year-olds (odds ratio [OR]: 1.28, 95% confidence interval [CI]: 1.13-1.46), for the 12- to 17-year-olds (OR: 1.17, 95% CI: 1.09-1.25) and for the 18- to 25-year-olds (OR: 1.09, 95% CI: 1.04-1.15). Children with reaction disorders, adolescents with anxiety and bipolar disorders, young adults with psychosis and reaction disorders and Black and non-Hispanic children and adolescents showed vulnerability to elevated temperature. CONCLUSIONS We found that elevated ambient temperatures were associated with acute mental health ED or hospital encounters across childhood, adolescence and young adulthood.
Collapse
Affiliation(s)
- Li Niu
- Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Blean Girma
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bian Liu
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Leah H. Schinasi
- Department of Environmental and Occupational Health and Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
| | - Jane E. Clougherty
- Department of Environmental and Occupational Health and Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA, USA
| | - Perry Sheffield
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| |
Collapse
|
9
|
Liu H, Zhao H, Huang J, He M. Air pollution associated with hospital visits for mental and behavioral disorders in Northeast China. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1090313. [PMID: 38455902 PMCID: PMC10910900 DOI: 10.3389/fepid.2023.1090313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 03/10/2023] [Indexed: 03/09/2024]
Abstract
Background Related studies have found that air pollution is an important factor affecting mental and behavioral disorders. Thus, we performed this time-series study to evaluate the relationship between short-term exposure to ambient air pollutants and visits to hospital by patients with mental and behavioral disorders in northeastern China. Methods We used quasi-Poisson regression models and generalized additive models to probe the links between air pollution and mental and behavioral disorders. The possible influences were also explored stratified by season, age and gender. Results We found that sulfur dioxide (SO2) had a cumulative effect on mental and behavioral disorders at lag04-lag07 and had the greatest effect at lag07 [Relative risk (RR) = 1.068, 95%CI = 1.021-1.117]. Particulate matter of size 2.5 μm (PM2.5) and SO2 had a cumulative effect on depression and both had the largest effect at lag07 (RR = 1.021, 95%CI = 1.002-1.041; RR = 1.103, 95%CI = 1.032-1.178); SO2 also had a cumulative effect on anxiety disorders, with the largest effect at lag06 (RR = 1.058, 95%CI = 1.009-1.110). In the stratified analysis, people are more susceptible in the cold season compared to the warm season and females and the 18-60-year age group are more sensitive to air pollutants. It is suggested to strengthen management and preventive measures to decrease air pollution exposure. Conclusion This study found an association between increased concentrations of air pollutants and increased outpatient visits for mental and behavioral disorders. We recommend that preventive and protective measures should be strengthened in an effort to reduce exposure to air pollution in order to maintain physical and mental health.
Collapse
Affiliation(s)
- Huo Liu
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
| | - Hang Zhao
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
| | - Jinling Huang
- Department of Hospital Management Office, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Miao He
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
| |
Collapse
|
10
|
Corvetto JF, Helou AY, Dambach P, Müller T, Sauerborn R. A Systematic Literature Review of the Impact of Climate Change on the Global Demand for Psychiatric Services. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:1190. [PMID: 36673946 PMCID: PMC9858749 DOI: 10.3390/ijerph20021190] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/03/2023] [Accepted: 01/05/2023] [Indexed: 06/17/2023]
Abstract
Climate Change (CC) imposes important global health risks, including on mental health (MH). They are related mostly to psychological suffering caused by climate-related events and to the heat-vulnerability caused by psychiatric disorders. This growing burden may press MH services worldwide, increasing demand on public and private systems in low-, middle-, and high-income countries. According to PRISMA, two independent reviewers searched four databases for papers published before May 2022 that associated climate-related events with healthcare demand for psychiatric conditions. Of the 7432 papers retrieved, we included 105. Only 29 were carried out in low- and middle-income countries. Twelve related the admission numbers to (i) extreme events, while 93 to (ii) meteorological factors-mostly heat. Emergency visits and hospitalizations were significantly higher during hot periods for MH disorders, especially until lag 5-7. Extreme events also caused more consultations. Suicide (completed or attempted), substance misuse, schizophrenia, mood, organic and neurotic disorders, and mortality were strongly affected by CC. This high healthcare demand is evidence of the burden patients may undergo. In addition, public and private services may face a shortage of financial and human resources. Finally, the increased use of healthcare facilities, in turn, intensifies greenhouse gas emissions, representing a self-enforcing cycle for CC. Further research is needed to better clarify how extreme events affect MH services and, in addition, if services in low- and middle-income countries are more intensely demanded by CC, as compared to richer countries.
Collapse
Affiliation(s)
- Julia Feriato Corvetto
- Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, 69120 Heidelberg, Germany
| | - Ammir Yacoub Helou
- Department of Anatomy, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-900, Brazil
| | - Peter Dambach
- Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, 69120 Heidelberg, Germany
| | - Thomas Müller
- Private Clinic Meiringen, 3860 Meiringen, Switzerland
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland
| | - Rainer Sauerborn
- Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, 69120 Heidelberg, Germany
| |
Collapse
|
11
|
Liang M, Min M, Ye P, Duan L, Sun Y. Are there joint effects of different air pollutants and meteorological factors on mental disorders? A machine learning approach. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:6818-6827. [PMID: 36008583 DOI: 10.1007/s11356-022-22662-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
Exposure to air pollutants is considered to be associated with mental disorders (MD). Few studies have addressed joint effect of multiple air pollutants and meteorological factors on admissions of MD. We examined the association between multiple air pollutants (PM2.5, PM10, O3, SO2, and NO2), meteorological factors (temperature, precipitation, relative humidity, and sunshine time), and MD risk in Yancheng, China. Associations were estimated by a generalized linear regression model (GLM) adjusting for time trend, day of the week, and patients' average age. Empirical weights of environmental exposures were judged by a weighted quantile sum (WQS) model. A machine learning approach, Bayesian kernel machine regression (BKMR), was used to assess the overall effect of mixed exposures. We calculated excess risk (ER) and 95% confidence interval (CI) for each exposure. According to the effect of temperature on MD, we divided the exposure of all factors into different temperature groups. In the high temperature group, GLM found that for every 10 μg/m3 increase in O3, PM2.5 and PM10 exposure, the ERs were 1.926 (95%CI 0.345, 3.531), 1.038 (95%CI 0.024, 2.062), and 0.780 (95% CI 0.052, 1.512) after adjusting for covariates. Temperature, relative humidity, and sunshine time also reported significant results. The WQS identified O3 and temperature (above the threshold) had the highest weights among air pollutants and meteorological factors. BKMR found a significant positive association between mixed exposure and MD risks. In the low temperature group, only O3 and temperature (below the threshold) showed significant results. These findings provide policymakers and practitioners with important scientific evidence for possible interventions. The association between different exposures and MD risk warrants further study.
Collapse
Affiliation(s)
- Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Min Min
- Anhui Institute of Medical Information (Anhui Medical Association), Hefei, 230061, Anhui, China
| | - Pengpeng Ye
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Leilei Duan
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China.
- Chaohu Hospital, Anhui Medical University, Hefei, 238000, Anhui, China.
| |
Collapse
|
12
|
Wang C, Qi Y, Chen Z. Explainable Gated Recurrent Unit to explore the effect of co-exposure to multiple air pollutants and meteorological conditions on mental health outcomes. ENVIRONMENT INTERNATIONAL 2023; 171:107689. [PMID: 36508748 DOI: 10.1016/j.envint.2022.107689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/03/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m3 of NO2, and 14.1 µg/m3 of SO2 at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM2.5, and O3 interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.
Collapse
Affiliation(s)
- Ce Wang
- School of Energy and Environment, Southeast University, Nanjing 210096, PR China; State Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Southeast University, Nanjing 210096, PR China.
| | - Yi Qi
- School of Architecture and Urban Planning, Nanjing University, No. 22 Hankoulu Road, Nanjing 210093, PR China
| | - Zhenhua Chen
- Department of Information, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, RP China.
| |
Collapse
|
13
|
Meng L, Zhou C, Xu Y, Liu F, Zhou C, Yao M, Li X. The lagged effect and attributable risk of apparent temperature on hand, foot, and mouth disease in Changsha, China: a distributed lag non-linear model. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:11504-11515. [PMID: 36094702 DOI: 10.1007/s11356-022-22875-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 08/31/2022] [Indexed: 06/15/2023]
Abstract
Hand, foot, and mouth disease (HFMD) is the leading Category C infectious disease affecting millions of children in China every year. In the context of global climate change, the understanding and quantification of the impact of weather factors on human health are particularly critical to the development and implementation of climate change adaptation and mitigation strategies. The aim of this study was to quantify the attributable burden of a combined bioclimatic indicator (apparent temperature) on HFMD and to identify temperature-specific sensitive populations. A total of 123,622 HFMD cases were included in the study. The non-linear relationship between apparent temperature and the incidence of HFMD was approximately M-shaped, with hot weather being more likely to be attributable than cold conditions, of which moderately hot accounting for the majority of cases (21,441, 17.34%). Taking the median apparent temperature (19.2 °C) as reference, the cold effect showed a short acute effect with the highest risk on the day of lag 0 (RR = 1.086, 95% CI: 1.024 ~ 1.152), whereas the hot effect lasted longer with the greatest risk at a lag of 7 days (RR = 1.081, 95% CI: 1.059 ~ 1.104). Subgroup analysis revealed that males, children under 3 years old, and scattered children tended to be more vulnerable to HFMD in hot weather, while females, those aged 3 ~ 5 years, and nursery children were sensitive to cold conditions. This study suggests that high temperatures have a greater impact on HFMD than low temperatures as well as lasting longer, of particular concern being moderately high temperatures rather than extreme temperatures. Early intervention takes on greater importance during cold days, while the duration of HFMD intervention must be longer during hot days.
Collapse
Affiliation(s)
- Lijun Meng
- Department of Epidemiology and Health Statistics, Xiang Ya School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Chunliang Zhou
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, Hunan, China
| | - Yiqing Xu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, Hunan, China
| | - Fuqiang Liu
- Hunan Provincial Center for Disease Control and Prevention, Changsha, 410005, Hunan, China
| | - Cui Zhou
- Department of Epidemiology and Health Statistics, Xiang Ya School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Meng Yao
- Department of Epidemiology and Health Statistics, Xiang Ya School of Public Health, Central South University, Changsha, 410078, Hunan, China
| | - Xingli Li
- Department of Epidemiology and Health Statistics, Xiang Ya School of Public Health, Central South University, Changsha, 410078, Hunan, China.
| |
Collapse
|
14
|
Assessing the Impact of Meteorological Conditions on Outpatient Visits for Childhood Respiratory Diseases in Urumqi, China. J Occup Environ Med 2022; 64:e598-e605. [DOI: 10.1097/jom.0000000000002640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
15
|
Deng X, Brotzge J, Tracy M, Chang HH, Romeiko X, Zhang W, Ryan I, Yu F, Qu Y, Luo G, Lin S. Identifying joint impacts of sun radiation, temperature, humidity, and rain duration on triggering mental disorders using a high-resolution weather monitoring system. ENVIRONMENT INTERNATIONAL 2022; 167:107411. [PMID: 35870379 DOI: 10.1016/j.envint.2022.107411] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/08/2022] [Accepted: 07/11/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Mental disorders (MDs) are behavioral or mental patterns that cause significant distress or impairment of personal functioning. Previously, temperature has been linked to MDs, but most studies suffered from exposure misclassification due to limited monitoring sites. We aimed to assess whether multiple meteorological factors could jointly trigger MD-related emergency department (ED) visits in warm season, using a highly dense weather monitoring system. METHODS We conducted a time-stratified, case-crossover study. MDs-related ED visits (primary diagnosis) from May-October 2017-2018 were obtained from New York State (NYS) discharge database. We obtained solar radiation (SR), relative humidity (RH), temperature, heat index (HI), and rainfall from Mesonet, a real-time monitoring system spaced about 17 miles (126 stations) across NYS. We used conditional logistic regression to assess the weather-MD associations. RESULTS For each interquartile range (IQR) increase, both SR (excess risk (ER): 4.9%, 95% CI: 3.2-6.7%) and RH (ER: 4.0%, 95% CI: 2.6-5.4%) showed the largest risk for MD-related ED visits at lag 0-9 days. While temperature presented a short-term risk (highest ER at lag 0-2 days: 3.7%, 95% CI: 2.5-4.9%), HI increased risk over a two-week period (ER range: 3.7-4.5%), and rainfall hours showed an inverse association with MDs (ER: -0.5%, 95% CI: 0.9-(-0.1)%). Additionally, we observed stronger association of SR, RH, temperature, and HI in September and October. Combination of high SR, RH, and temperature displayed the largest increase in MDs (ER: 7.49%, 95% CI: 3.95-11.15%). The weather-MD association was stronger for psychoactive substance usage, mood disorders, adult behavior disorders, males, Hispanics, African Americans, individuals aged 46-65, or Medicare patients. CONCLUSIONS Hot and humid weather, especially the joint effect of high sun radiation, temperature and relative humidity showed the highest risk of MD diseases. We found stronger weather-MD associations in summer transitional months, males, and minority groups. These findings also need further confirmation.
Collapse
Affiliation(s)
- Xinlei Deng
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Jerald Brotzge
- Program Manager, New York State Mesonet, University at Albany, the State University of New York, Albany, NY, USA
| | - Melissa Tracy
- Department of Epidemiology and Biostatistics, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Howard H Chang
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Xiaobo Romeiko
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Wangjian Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Ian Ryan
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Fangqun Yu
- Department of Earth and Atmospheric Sciences, Atmospheric Sciences Research Center, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, Guangdong, China
| | - Gan Luo
- Department of Earth and Atmospheric Sciences, Atmospheric Sciences Research Center, University at Albany, the State University of New York, Rensselaer, NY, USA
| | - Shao Lin
- Department of Environmental Health Sciences, School of Public Health, University at Albany, the State University of New York, Rensselaer, NY, USA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
| |
Collapse
|
16
|
Wondmagegn BY, Xiang J, Dear K, Williams S, Hansen A, Pisaniello D, Nitschke M, Nairn J, Scalley B, Xiao A, Jian L, Tong M, Bambrick H, Karnon J, Bi P. Understanding current and projected emergency department presentations and associated healthcare costs in a changing thermal climate in Adelaide, South Australia. Occup Environ Med 2022; 79:421-426. [DOI: 10.1136/oemed-2021-107888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 02/18/2022] [Indexed: 11/03/2022]
Abstract
BackgroundExposure to extreme temperatures is associated with increased emergency department (ED) presentations. The resulting burden on health service costs and the potential impact of climate change is largely unknown. This study examines the temperature-EDs/cost relationships in Adelaide, South Australia and how this may be impacted by increasing temperatures.MethodsA time series analysis using a distributed lag nonlinear model was used to explore the exposure–response relationships. The net-attributable, cold-attributable and heat-attributable ED presentations for temperature-related diseases and costs were calculated for the baseline (2014–2017) and future periods (2034–2037 and 2054–2057) under three climate representative concentration pathways (RCPs).ResultsThe baseline heat-attributable ED presentations were estimated to be 3600 (95% empirical CI (eCI) 700 to 6500) with associated cost of $A4.7 million (95% eCI 1.8 to 7.5). Heat-attributable ED presentations and costs were projected to increase during 2030s and 2050s with no change in the cold-attributable burden. Under RCP8.5 and population growth, the increase in heat-attributable burden would be 1.9% (95% eCI 0.8% to 3.0%) for ED presentations and 2.5% (95% eCI 1.3% to 3.7%) for ED costs during 2030s. Under the same conditions, the heat effect is expected to increase by 3.7% (95% eCI 1.7% to 5.6%) for ED presentations and 5.0% (95% eCI 2.6% to 7.1%) for ED costs during 2050s.ConclusionsProjected climate change is likely to increase heat-attributable emergency presentations and the associated costs in Adelaide. Planning health service resources to meet these changes will be necessary as part of broader risk mitigation strategies and public health adaptation actions.
Collapse
|
17
|
Liang M, Ding X, Wu Y, Sun Y. Temperature and risk of infectious diarrhea: a systematic review and meta-analysis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:68144-68154. [PMID: 34268683 DOI: 10.1007/s11356-021-15395-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 07/07/2021] [Indexed: 06/13/2023]
Abstract
Infectious diarrhea (ID) is an intestinal infectious disease including cholera, typhoid and paratyphoid fever, bacterial and amebic dysentery, and other infectious diarrhea. There are many studies that have explored the relationship between ambient temperature and the spread of infectious diarrhea, but the results are inconsistent. It is necessary to systematically evaluate the impact of temperature on the incidence of ID. This study was based on the PRISMA statement to report this systematic review. We conducted literature searches from CNKI, VIP databases, CBM, PubMed, Web of Science, Cochrane Library, and other databases. The number registered in PROSPERO is CRD42021225472. After searching a total of 4915 articles in the database and references, 27 studies were included. The number of people involved exceeded 7.07 million. The overall result demonstrated when the temperature rises, the risk of infectious diarrhea increases significantly (RRcumulative=1.42, 95%CI: 1.07-1.88, RRsingle-day=1.08, 95%CI: 1.03-1.14). Subgroup analysis found the effect of temperature on the bacillary dysentery group (RRcumulative=1.85, 95%CI: 1.48-2.30) and unclassified diarrhea groups (RRcumulative=1.18, 95%CI: 0.59-2.34). The result of the single-day effect subgroup analysis was similar to the result of the cumulative effect. And the sensitivity analysis proved that the results were robust. This systematic review and meta-analysis support that temperature will increase the risk of ID, which is helpful for ID prediction and early warning in the future.
Collapse
Affiliation(s)
- Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Xiuxiu Ding
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China
| | - Yile Wu
- Department of Hospital Infection Prevention and Control, The Second Affiliated Hospital of Anhui Medical University, No. 678 Furong Road, Hefei, 230601, Anhui, People's Republic of China
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China.
- Center for Evidence-Based Practice, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, People's Republic of China.
| |
Collapse
|
18
|
Liang M, Ding X, Yao Z, Duan L, Xing X, Sun Y. Effects of ambient temperature and fall-related injuries in Ma'anshan, Anhui Province, China: a distributed lag nonlinear analysis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:58092-58103. [PMID: 34105075 DOI: 10.1007/s11356-021-14663-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 05/27/2021] [Indexed: 06/12/2023]
Abstract
Despite the significant economic cost of falls and injuries to individuals and communities, little is known about the impact of meteorological factors on the incidence of fall-related injuries (FRIs). Therefore, a time-series study was conducted to explore the effects of meteorological factors on FRIs in Ma'anshan City, East China. Injury data from 2011 to 2017 were collected from the National Injury Monitoring Station in Ma'anshan City. A distributed lag nonlinear model was used in this study to evaluate the correlation between ambient temperature and fall injuries. The results showed a significant exposure-response relationship between temperature and FRIs in Ma'anshan City. The high temperatures increased the risk of FRIs (RR = 1.110; 95% CI, 1.005-1.225; lag 0). The lag effect appeared at lag 10 (RR = 1.032; 95% CI, 1.003-1.063), and then gradually remained stable after lag 25 (RR = 1.077; 95% CI, 1.045-1.110). The effect of ambient temperature varied with age and gender. The lag effect of high temperature appeared in the male group after lag 15 (RR = 1.042; 95% CI, 1.006-1.079). In contrast, the effect of the female group appeared for the first time at lag 0 (RR = 1.187; 95% CI, 1.042-1.352). And the ≥ 60 years subgroup seemed to be more sensitive in low temperature (RR = 1.017; 95% CI, 1.004-1.031; lag 0; RR = 1.003; 95% CI, 1.000-1.007; lag 25). The cumulative result is similar to the single-day effect. From the results, this study would help the establishment of fall-related injury prediction and provide evidence for the formulation and implementation of preventive strategies and measures in the future.
Collapse
Affiliation(s)
- Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xiuxiu Ding
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Zhenhai Yao
- Anhui Meteorological Service Center, Anhui Meteorological Bureau, Hefei, 230000, Anhui, China
| | - Leilei Duan
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Xiuya Xing
- Department of Chronic Noncommunicable Disease Control and Prevention, Anhui Provincial Center for Disease Control and Prevention, No. 12560, Fanhua Road, Hefei, 230601, Anhui, China.
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China.
- Center for Injury Control and Prevention, School of Public Health, Anhui Medical University, Hefei, 230032, Anhui, China.
| |
Collapse
|
19
|
Wang C, Feng L, Qi Y. Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China. ENVIRONMENTAL RESEARCH 2021; 202:111740. [PMID: 34329635 DOI: 10.1016/j.envres.2021.111740] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 07/16/2021] [Accepted: 07/19/2021] [Indexed: 06/13/2023]
Abstract
Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of input features in the complex system of environmental stressors - mental disorders (MDs), especially for exposure to air pollution mixture. In this study, we combined deep learning neural networks (DLNNs) with SHapley Additive exPlanation (SHAP) to predict the illness risk of MDs on the population level, and then provided explanations for risk factors. The modeling system, which was trained on day-by-day hospital outpatient visits of two major hospitals in Nanjing, China from 2013/07/01 through 2019/02/28, visualized the time-varying prediction, contributing factors, and interaction effects of informative features. Our results suggested that NO2, SO2, and CO made outstanding contributions in magnitude of feature attributions under circumstances of mixed air pollutants. In particular, NO2 at high concentration level was associated with an increase in illness risk of MDs, and the maximum and mean absolute SHAP value were approximated to 10 and 2 as a local and global measure of feature importance, respectively. It presented a marginally antagonistic effect for two pairs of gaseous pollutants, i.e., NO2 vs. SO2 and CO vs. NO2. In contrast, CO and SO2 displayed the opposite direction of feature effects to the rise of observed concentrations, but an apparent synergistic effect was obviously captured. The primary risk factors driving a sharp increase in acute attack or exacerbation of MDs were also identified by depicting prediction paths of time-series samples. We believe that the significance of coupling accurate predictions from DLNNs with interpretable explanations of why a prediction is completed has broad applicability throughout the field of environmental health.
Collapse
Affiliation(s)
- Ce Wang
- School of Energy and Environment, Southeast University, Nanjing, 210096, PR China; State Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Southeast University, Nanjing, 210096, PR China.
| | - Lan Feng
- National-Provincial Joint Engineering Research Center of Electromechanical Product Packaging, College of Civil Engineering, Nanjing Forestry University, Nanjing, 210037, PR China.
| | - Yi Qi
- School of Architecture and Urban Planning, Nanjing University, No. 22 Hankoulu Road, Nanjing, 210093, PR China.
| |
Collapse
|
20
|
Yoo EH, Eum Y, Roberts JE, Gao Q, Chen K. Association between extreme temperatures and emergency room visits related to mental disorders: A multi-region time-series study in New York, USA. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 792:148246. [PMID: 34144243 DOI: 10.1016/j.scitotenv.2021.148246] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 05/21/2021] [Accepted: 05/31/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND There is growing evidence suggesting that extreme temperatures have an impact on mental disorders. We aimed to explore the effect of extreme temperatures on emergency room (ER) visits for mental health disorders using 2.8 million records from New York State, USA (2009-2016), and to examine potential effect modifications by individuals' age, sex, and race/ethnicity through a stratified analysis to determine if certain populations are more susceptible. METHOD To assess the short-term impact of daily average temperature on ER visits related to mental disorders, we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, as well as long-term and seasonal time trends. We also conducted a meta-analysis to pool the region-specific risk estimates and construct the overall cumulative exposure-response curves for all regions. RESULTS We found positive associations between short-term exposure to extreme heat (27.07 ∘C) and increased ER visits for total mental disorders, as well as substance abuse, mood and anxiety disorders, schizophrenia, and dementia. We did not find any statistically significant difference among any subgroups of the population being more susceptible to extreme heat than any other. CONCLUSIONS Our findings suggest that there is a positive association between short-term exposure to extreme heat and increased ER visits for total mental disorders. This extreme effect was also found across all sub-categories of mental disease, although further research is needed to confirm our finding for specific mental disorders, such as dementia, which accounted for less than 1% of the total mental disorders in this sample.
Collapse
Affiliation(s)
- Eun-Hye Yoo
- Department of Geography, State University of New York at Buffalo, NY, USA.
| | - Youngseob Eum
- Department of Geography, State University of New York at Buffalo, NY, USA
| | - John E Roberts
- Department of Psychology, State University of New York at Buffalo, NY, USA
| | - Qi Gao
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China; Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA; Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| |
Collapse
|
21
|
Zhao Q, Wigmann C, Areal AT, Altug H, Schikowski T. Effect of non-optimum ambient temperature on cognitive function of elderly women in Germany. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117474. [PMID: 34087635 DOI: 10.1016/j.envpol.2021.117474] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 04/19/2021] [Accepted: 05/24/2021] [Indexed: 06/12/2023]
Abstract
Non-optimum ambient temperature has been associated with a variety of health outcomes in the elderly population. However, few studies have examined its adverse effects on neurocognitive function. In this study, we explored the temperature-cognition association in elderly women. We investigated 777 elderly women from the German SALIA cohort during the 2007-2010 follow-up. Cognitive function was evaluated using the CERAD-Plus test battery. Modelled data on daily weather conditions were assigned to the residential addresses. The temperature-cognition association over lag 0-10 days was estimated using multivariable regression with distributed lag non-linear model. The daily mean temperature ranged between -6.7 and 26.0 °C during the study period for the 777 participants. We observed an inverse U-shaped association in elderly women, with the optimum temperature (15.3 °C) located at the 68th percentile of the temperature range. The average z-score of global cognitive function declined by -0.31 (95%CI: 0.73, 0.11) for extreme cold (the 2.5th percentile of temperature range) and -0.92 (95%CI: 1.50, -0.33) for extreme heat (the 97.5th percentile of temperature range), in comparison to the optimum temperature. Episodic memory was more sensitive to heat exposure, while semantic memory and executive function were the two cognitive domains sensitive to cold exposure. Individuals living in an urban area and those with a low educational level were particularly sensitive to extreme heat. In summary, non-optimum temperature was inversely associated with cognitive function in elderly women, with the effect size for heat exposure particularly substantial. The strength of association varied by cognitive domains and individual characteristics.
Collapse
Affiliation(s)
- Qi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Claudia Wigmann
- Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Ashtyn Tracey Areal
- Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Hicran Altug
- Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany
| | - Tamara Schikowski
- Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, Germany.
| |
Collapse
|
22
|
Liu J, Varghese BM, Hansen A, Xiang J, Zhang Y, Dear K, Gourley M, Driscoll T, Morgan G, Capon A, Bi P. Is there an association between hot weather and poor mental health outcomes? A systematic review and meta-analysis. ENVIRONMENT INTERNATIONAL 2021; 153:106533. [PMID: 33799230 DOI: 10.1016/j.envint.2021.106533] [Citation(s) in RCA: 102] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Mental health is an important public health issue globally. A potential link between heat exposure and mental health outcomes has been recognised in the scientific literature; however, the associations between heat exposure (both high ambient temperatures and heatwaves) and mental health-related mortality and morbidity vary between studies and locations. OBJECTIVE To fill gaps in knowledge, this systematic review aims to summarize the epidemiological evidence and investigate the quantitative effects of high ambient temperatures and heatwaves on mental health-related mortality and morbidity outcomes, while exploring sources of heterogeneity. METHODS A systematic search of peer-reviewed epidemiological studies on heat exposure and mental health outcomes published between January 1990 and November 2020 was conducted using five databases (PubMed, Embase, Scopus, Web of Science and PsycINFO). We included studies that examined the association between high ambient temperatures and/or heatwaves and mental health-related mortality and morbidity (e.g. hospital admissions and emergency department visits) in the general population. A range of mental health conditions were defined using ICD-10 classifications. We performed random effects meta-analysis to summarize the relative risks (RRs) in mental health outcomes per 1 °C increase in temperature, and under different heatwaves definitions. We further evaluated whether variables such as age, sex, socioeconomic status, and climate zone may explain the observed heterogeneity. RESULTS The keyword search yielded 4560 citations from which we identified 53 high temperatures/heatwaves studies that comprised over 1.7 million mental health-related mortality and 1.9 million morbidity cases in total. Our findings suggest associations between heat exposures and a range of mental health-related outcomes. Regarding high temperatures, our meta-analysis of study findings showed that for each 1 °C increase in temperature, the mental health-related mortality and morbidity increased with a RR of 1.022 (95%CI: 1.015-1.029) and 1.009 (95%CI: 1.007-1.015), respectively. The greatest mortality risk was attributed to substance-related mental disorders (RR, 1.046; 95%CI: 0.991-1.101), followed by organic mental disorders (RR, 1.033; 95%CI: 1.020-1.046). A 1 °C temperature rise was also associated with a significant increase in morbidity such as mood disorders, organic mental disorders, schizophrenia, neurotic and anxiety disorders. Findings suggest evidence of vulnerability for populations living in tropical and subtropical climate zones, and for people aged more than 65 years. There were significant moderate and high heterogeneities between effect estimates in overall mortality and morbidity categories, respectively. Lower heterogeneity was noted in some subgroups. The magnitude of the effect estimates for heatwaves varied depending on definitions used. The highest effect estimates for mental health-related morbidity was observed when heatwaves were defined as "mean temperature ≥90th percentile for ≥3 days" (RR, 1.753; 95%CI: 0.567-5.421), and a significant effect was also observed when the definition was "mean temperature ≥95th percentile for ≥3 days", with a RR of 1.064 (95%CI: 1.006-1.123). CONCLUSIONS Our findings support the hypothesis of a positive association between elevated ambient temperatures and/or heatwaves and adverse mental health outcomes. This problem will likely increase with a warming climate, especially in the context of climate change. Further high-quality studies are needed to identify modifying factors of heat impacts.
Collapse
Affiliation(s)
- Jingwen Liu
- School of Public Health, The University of Adelaide, Australia
| | | | - Alana Hansen
- School of Public Health, The University of Adelaide, Australia
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, Australia; School of Public Health, Fujian Medical University, China
| | - Ying Zhang
- Sydney School of Public Health, The University of Sydney, Australia
| | - Keith Dear
- School of Public Health, The University of Adelaide, Australia
| | - Michelle Gourley
- Burden of Disease and Mortality Unit, Australian Institute of Health and Welfare, Australia
| | - Timothy Driscoll
- Sydney School of Public Health, The University of Sydney, Australia
| | - Geoffrey Morgan
- Sydney School of Public Health, The University of Sydney, Australia
| | - Anthony Capon
- Monash Sustainable Development Institute, Monash University, Australia
| | - Peng Bi
- School of Public Health, The University of Adelaide, Australia.
| |
Collapse
|
23
|
Yoo EH, Eum Y, Gao Q, Chen K. Effect of extreme temperatures on daily emergency room visits for mental disorders. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:39243-39256. [PMID: 33751353 DOI: 10.1007/s11356-021-12887-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/08/2021] [Indexed: 06/12/2023]
Abstract
Relatively few studies investigated the effects of extreme temperatures (both heat and cold) on mental health (ICD-9: 290-319; ICD-10: F00-F99) and the potential effect modifications by individuals' age, sex, and race. We aimed to explore the effect of extreme temperatures of both heat and cold on the emergency room (ER) visits for mental health disorders, and conducted a stratified analysis to identify possible susceptible population in Erie and Niagara counties, NY, USA. To assess the short-term impacts of daily maximum temperature on ER visits related to mental disorders (2009-2015), we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, long-term time trend, and seasonality. We found that there were positive associations between short-term exposure to extreme ambient temperatures and increased ER visits for mental disorders, and the effects can vary by individual factors. We found heat effect (relative risk (RR) = 1.16; 95% confidence intervals (CI), 1.06-1.27) on exacerbated mental disorders became intense in the study region and subgroup of population (the elderly) being more susceptible to extreme heat than any other age group. For extreme cold, we found that there is a substantial delay effect of 14 days (RR = 1.25; 95% CI = 1.08-1.45), which is particularly burdensome to the age group of 50-64 years old and African-Americans. Our findings suggest that there is a positive association between short-term exposure to extreme ambient temperature (heat and cold) and increased ER visits for mental disorders, and the effects vary as a function of individual factors, such as age and race.
Collapse
Affiliation(s)
- Eun-Hye Yoo
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA.
| | - Youngseob Eum
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA
| | - Qi Gao
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| | - Kai Chen
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT, USA
- Yale Center on Climate Change and Health, Yale School of Public Health, New Haven, CT, USA
| |
Collapse
|
24
|
Wondmagegn BY, Xiang J, Dear K, Williams S, Hansen A, Pisaniello D, Nitschke M, Nairn J, Scalley B, Xiao A, Jian L, Tong M, Bambrick H, Karnon J, Bi P. Increasing impacts of temperature on hospital admissions, length of stay, and related healthcare costs in the context of climate change in Adelaide, South Australia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 773:145656. [PMID: 33592481 DOI: 10.1016/j.scitotenv.2021.145656] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Revised: 01/21/2021] [Accepted: 02/01/2021] [Indexed: 05/22/2023]
Abstract
BACKGROUND A growing number of studies have investigated the effect of increasing temperatures on morbidity and health service use. However, there is a lack of studies investigating the temperature-attributable cost burden. OBJECTIVES This study examines the relationship of daily mean temperature with hospital admissions, length of hospital stay (LoS), and costs; and estimates the baseline temperature-attributable hospital admissions, and costs and in relation to warmer climate scenarios in Adelaide, South Australia. METHOD A daily time series analysis using distributed lag non-linear models (DLNM) was used to explore exposure-response relationships and to estimate the aggregated burden of hospital admissions for conditions associated with temperatures (i.e. renal diseases, mental health, diabetes, ischaemic heart diseases and heat-related illnesses) as well as the associated LoS and costs, for the baseline period (2010-2015) and different future climate scenarios in Adelaide, South Australia. RESULTS During the six-year baseline period, the overall temperature-attributable hospital admissions, LoS, and associated costs were estimated to be 3915 cases (95% empirical confidence interval (eCI): 235, 7295), 99,766 days (95% eCI: 14,484, 168,457), and AU$159 million (95% eCI: 18.8, 269.0), respectively. A climate scenario consistent with RCP8.5 emissions, and including projected demographic change, is estimated to lead to increases in heat-attributable hospital admissions, LoS, and costs of 2.2% (95% eCI: 0.5, 3.9), 8.4% (95% eCI: 1.1, 14.3), and 7.7% (95% eCI: 0.3, 13.3), respectively by mid-century. CONCLUSIONS There is already a substantial temperature-attributable impact on hospital admissions, LoS, and costs which are estimated to increase due to climate change and an increasing aged population. Unless effective climate and public health interventions are put into action, the costs of treating temperature-related admissions will be high.
Collapse
Affiliation(s)
- Berhanu Y Wondmagegn
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia; College of Health and Medical Sciences, Haramaya University, Dire Dawa, Ethiopia.
| | - Jianjun Xiang
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
| | - Keith Dear
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia
| | - Susan Williams
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
| | - Alana Hansen
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
| | - Dino Pisaniello
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
| | - Monika Nitschke
- South Australian Department of Health and Wellbeing, Adelaide, South Australia, Australia.
| | - John Nairn
- Australian Bureau of Meteorology, South Australia, Australia.
| | - Ben Scalley
- Metropolitan Communicable Disease Control, Department of Health WA, Perth, Western Australia, Australia.
| | - Alex Xiao
- Epidemiology Branch, Department of Health WA, Perth, Western Australia, Australia.
| | - Le Jian
- Epidemiology Branch, Department of Health WA, Perth, Western Australia, Australia.
| | - Michael Tong
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
| | - Hilary Bambrick
- School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia.
| | - Jonathan Karnon
- College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia.
| | - Peng Bi
- School of Public Health, The University of Adelaide, North Terrace, Adelaide, South Australia, Australia.
| |
Collapse
|
25
|
Liang M, Zhao D, Wu Y, Ye P, Wang Y, Yao Z, Bi P, Duan L, Sun Y. Short-term effects of ambient temperature and road traffic accident injuries in Dalian, Northern China: A distributed lag non-linear analysis. ACCIDENT; ANALYSIS AND PREVENTION 2021; 153:106057. [PMID: 33647596 DOI: 10.1016/j.aap.2021.106057] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/30/2020] [Accepted: 02/19/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Although traffic accidents cause considerable economic losses and injuries to individuals, families, and communities, little is known about the impact of meteorological factors on the incidence of traffic accident injuries (TAIs). Therefore, a time-series study was conducted to explore the effect of meteorological variables on TAIs in Dalian, Northern China. METHODS Poisson generalized linear models (PGLM) combined with distributed lag nonlinear models (DLNM) were used to estimate the association between daily TAIs and ambient temperature in Dalian, China, 2015-2017. The injury data collected by Dalian national injury surveillance hospitals, and meteorological data were extracted and accumulated from the National Meteorological Information Center. Modified the model with variables such as pressure, humidity, precipitation, PM2.5, SO2, O3, day of the week, seasonality, and time trend. In the subgroup analysis, the modification effects of gender and age were also examined. RESULTS Both high temperatures (RR = 1.198, 95%CI:1.017-1.411) and low temperatures (RR = 1.017, 95%CI:1.001-1.035) increased the risk of TAIs. The cumulative lag effect would last until after the 7th day. While the 40-59 years subgroup seemed to be more vulnerable in high temperature environments, those who are more than 60 years showed higher TAIs in low temperatures for both single-day and cumulative TAI risks. CONCLUSIONS Identifying the association between ambient temperature and traffic injuries could provide needed scientific evidence for relevant public health actions.
Collapse
Affiliation(s)
- Mingming Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Dongdong Zhao
- The First Affiliated Hospital of Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Yile Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Pengpeng Ye
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Yuan Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China
| | - Zhenhai Yao
- Anhui Meteorological Service Center, Anhui Meteorological Bureau, No. 16 Shihe Road, Hefei, 230000, Anhui, China
| | - Peng Bi
- School of Public Health, University of Adelaide, Adelaide, SA, 5005, Australia
| | - Leilei Duan
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100050, China.
| | - Yehuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China; Center for Injury Control and Prevention, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Hefei, 230032, Anhui, China.
| |
Collapse
|
26
|
Ghada W, Estrella N, Pfoerringer D, Kanz KG, Bogner-Flatz V, Ankerst DP, Menzel A. Effects of weather, air pollution and Oktoberfest on ambulance-transported emergency department admissions in Munich, Germany. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 755:143772. [PMID: 33229084 DOI: 10.1016/j.scitotenv.2020.143772] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 10/16/2020] [Accepted: 11/03/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Climate change and increasing risks of extreme weather events affect human health and lead to changes in the emergency department (ED) admissions and the emergency medical services (EMS) operations. For a better allocation of resources in the healthcare system, it is essential to predict ED numbers based on environmental variables. This publication aims to quantify weather, air pollution and calendar-related effects on daily ED admissions. METHODS Analyses were based on 575,725 admissions from the web-based IVENA system recording all patients in the greater Munich area with pre-hospital emergency care in ambulance operations during 2014-2018. Linear models were used to identify statistically significant associations between daily ED admissions and calendar, meteorological and pollution factors, allowing for lag effects of one to three days. Separate analyses were performed for seasons, with additional subset analyses by sex, age and surgical versus internal department. RESULTS ED admissions were exceptionally high during the three-week Oktoberfest, particularly for males and on the weekends, as well as during the New Year holiday. Admissions significantly increased during the years of study, decreased in spring and summer holidays, and were lower on Sundays while higher on Mondays. In the warmer seasons, admissions were significantly associated with higher temperature, adjusting for the effects of sunshine and humidity in all age groups except for the elderly. Adverse weather conditions in non-summer seasons were either linked to increasing ED admissions (from storms, gust) or decreasing them from rain. Mostly, but not exclusively, in winter, increasing ED admissions were associated with colder minimum temperatures as well as with higher NO and PM10 concentrations. CONCLUSIONS In addition to standard calendar-related factors, incorporating seasonal weather, air pollutant and interactions with patient demographics into resource planning models can improve the daily allocation of resources and staff of EMS operations at hospital and city levels.
Collapse
Affiliation(s)
- Wael Ghada
- TUM School of Life Sciences, Technical University of Munich, Freising, Germany.
| | - Nicole Estrella
- TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Dominik Pfoerringer
- Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Karl-Georg Kanz
- Klinik und Poliklinik für Unfallchirurgie, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany; Emergency Medical Services Authority, Munich, Germany
| | - Viktoria Bogner-Flatz
- Emergency Medical Services Authority, Munich, Germany; Department of General, Trauma and Reconstructive Surgery, Ludwig Maximilians University Hospital Munich, Munich, Germany
| | - Donna P Ankerst
- TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Department of Mathematics, Technical University of Munich, Garching, Germany
| | - Annette Menzel
- TUM School of Life Sciences, Technical University of Munich, Freising, Germany; Institute for Advanced Study, Technical University of Munich, Garching, Germany
| |
Collapse
|
27
|
Zhang S, Yang Y, Xie X, Li H, Han R, Hou J, Sun J, Qian ZM, Wu S, Huang C, Howard SW, Tian F, Deng W, Lin H. The effect of temperature on cause-specific mental disorders in three subtropical cities: A case-crossover study in China. ENVIRONMENT INTERNATIONAL 2020; 143:105938. [PMID: 32688157 DOI: 10.1016/j.envint.2020.105938] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 06/28/2020] [Accepted: 06/30/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Little is known about the association between ambient temperature and cause-specific mental disorders, especially in subtropical areas. OBJECTIVE To investigate the effect of ambient temperature on mental disorders in subtropical cities. METHOD Daily morbidity data for mental disorders in three Chinese cities (Shenzhen, Zhaoqing, and Huizhou) were collected from medical record systems of local psychiatric specialist hospitals, covering patients of all ages. Case-crossover design combined with a distributed lag nonlinear model (DLNM) was used to assess the nonlinear and delayed effects of temperatures on five specific mental disorders (affective disorders, anxiety, depressive disorders, schizophrenia, and organic mental disorders), with analyses stratified by gender and age. The temperature of minimum effect was used as the reference value to calculate estimates. RESULTS We observed inversed J-shaped exposure-response curves between temperature and mental morbidity and observed that low temperatures had a significant and prolonged effect on most types of mental disorders in the three cities. For example, the effect of the cold (2.5th percentile) on anxiety was consistently observed in the three cities with an odds ratio (OR) of 1.29 (95% CI: 1.06-1.57) in Zhaoqing, 1.26 (95% CI: 1.18-1.34) in Shenzhen, and 1.45 (95% CI: 1.17-1.81) in Huizhou. Low temperature was also associated with an increased risk of depressive disorders and schizophrenia. For the high temperature exposure (97.5th percentile), we only observed a significant, harmful effect on anxiety [OR = 1.30 (95% CI: 1.08, 1.58) in Shenzhen, OR = 1.16 (95% CI: 1.00, 1.34) in Zhaoqing], affective disorders [OR = 1.32 (95% CI: 1.08, 1.62) in Shenzhen], and schizophrenia [OR = 1.24 (95% CI: 1.03, 1.48) in Zhaoqing, OR = 1.03 (95% CI: 1.00, 1.06) in Huizhou]. CONCLUSIONS Our study suggests that both low and high temperatures might be important drivers of morbidity from mental disorders, and low temperature may have a more general and wide-spread effect on this cause-specific morbidity than high temperature.
Collapse
Affiliation(s)
- Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Yin Yang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - XinHui Xie
- Brain Function and Psychosomatic Medicine Institute, The Second People's Hospital of Huizhou, Huizhou, Guangdong, China
| | - Huan Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Rong Han
- Department of Psychiatry, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, Guangdong, China
| | - Jiesheng Hou
- The Third People's Hospital of Zhaoqing, Guangdong, China
| | - Jia Sun
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, USA
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, USA
| | - Shaowei Wu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, China
| | - Cunrui Huang
- Health Management and Policy, School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Steven W Howard
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, USA
| | - Fei Tian
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - WenFeng Deng
- Brain Function and Psychosomatic Medicine Institute, The Second People's Hospital of Huizhou, Huizhou, Guangdong, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| |
Collapse
|
28
|
Niu Y, Gao Y, Yang J, Qi L, Xue T, Guo M, Zheng J, Lu F, Wang J, Liu Q. Short-term effect of apparent temperature on daily emergency visits for mental and behavioral disorders in Beijing, China: A time-series study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 733:139040. [PMID: 32446053 PMCID: PMC7298617 DOI: 10.1016/j.scitotenv.2020.139040] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 04/23/2020] [Accepted: 04/25/2020] [Indexed: 05/06/2023]
Abstract
BACKGROUND The relationship between temperature and mental disorders is still unclear. This study aims to assess the short-term effect of apparent temperature (AT) on daily emergency visits of mental and behavioral disorders (MDs) in Beijing, China. METHODS Daily counts of emergency visits related to MDs in Beijing from 2016 to 2018 were obtained. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model (DLNM) was applied to analyze the lag-exposure-response relationship between AT and emergency admissions related to MDs. Sunshine duration, precipitation, PM2.5, SO2, O3, time trend, day of week and holiday were adjusted in the model. RESULTS Total daily emergency visits for MDs during the study period were 16,606. With the reference of -2.4 °C (temperature with the minimum emergency visit risk), the single day effects of low AT (-8.6 °C, 10th percentile) and high AT (9.2 °C, 90th percentile) on MDs emergency visits reached a relative risk peak of 1.043 (95%CI: 1.017-1.069) on lag day 4 and 1.105 (95%CI: 1.006-1.215) on lag day 1, respectively. The greatest cumulative effect of high AT emerged on lag 0-5 days and reached a relative risk of 1.435 (95%CI: 1.048-1.965), while no significant cumulative effect of low AT was observed. There was a significant effect of high AT on emergency visits of MDs due to psychoactive substance use and male patients. CONCLUSIONS Both low and high AT are demonstrated to be the significant risk factors of MDs, which highlights the need of strengthening the health interventions, patient medical services and early warning for patients.
Collapse
Affiliation(s)
- Yanlin Niu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; Beijing Center for Disease Prevention and Control, Institute for Nutrition and Food Hygiene, Beijing 100013, China; Research Center for Preventive Medicine of Beijing, Beijing 100013, China
| | - Yuan Gao
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Jun Yang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Li Qi
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Tao Xue
- Institute of Reproductive and Child Health, Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Moning Guo
- Beijing Municipal Health Commission Information Center, Beijing 100034, China; Beijing Municipal Health Commission Policy Research Center, Beijing 100034, China
| | - Jianpeng Zheng
- Beijing Municipal Health Commission Information Center, Beijing 100034, China; Beijing Municipal Health Commission Policy Research Center, Beijing 100034, China
| | - Feng Lu
- Beijing Municipal Health Commission Information Center, Beijing 100034, China; Beijing Municipal Health Commission Policy Research Center, Beijing 100034, China
| | - Jun Wang
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
| |
Collapse
|
29
|
Shao Y, Xu J, Qiao Y, Shao Y, Fei JM. The Effects of Temperature on Dynamics of Psychiatric Outpatients. Front Psychiatry 2020; 11:523059. [PMID: 33364983 PMCID: PMC7750496 DOI: 10.3389/fpsyt.2020.523059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 10/23/2020] [Indexed: 11/13/2022] Open
Abstract
Background: Climate changes affect mental states and alter the risk for psychiatric diseases. Seasonal changes in temperature lead to dynamics in the occurrence of psychiatric conditions and pose challenges in the administration of clinical psychiatry services. Methods: The present study aims to retrospectively analyze outpatient data with weather reports from January 2014 to March 2019 at Shanghai Mental Health Center, one of the largest psychiatric hospitals in the world, in order to provide policy insights into the administration of psychiatric clinics. Results: The results show steady increases in the number of overall patients over the past 5 years with several peaks within each year. Temperature changes and weather information reliably predict the increased number of psychiatric patients. Conclusions: We conclude that mental health hospitals should prepare for patient dynamics based on the weather forecast.
Collapse
Affiliation(s)
- Ying Shao
- Hospital Administration Office, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiahui Xu
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Ying Qiao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Shao
- Hospital Administration Office, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jian-Ming Fei
- Hospital Administration Office, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|