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Guo J, Xue T, Cao M, Han X, Pan Z, Huang D, Sun W, Mi J, Liu Y, Guan T. Ambient temperature anomalies induce electrocardiogram abnormalities: Findings from a nationwide longitudinal study. ENVIRONMENTAL RESEARCH 2024; 246:117996. [PMID: 38128602 DOI: 10.1016/j.envres.2023.117996] [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: 09/13/2023] [Revised: 12/02/2023] [Accepted: 12/19/2023] [Indexed: 12/23/2023]
Abstract
Electrocardiogram (ECG) outcomes serve as early manifestations of cardiovascular functional or structural changes. While temperature fluctuation has been demonstrated to be a risk factor for cardiovascular diseases, few epidemiological studies have reported its relationship with ECG outcomes. In this study, we employed temperature anomaly (TA) as an innovative indicator of temperature fluctuation to quantify its detrimental impacts on ECG outcomes. A longitudinal study design was conducted using the repeated ECG records of the China National Stroke Screening Survey from 2013 to 2019. Only individuals undergoing at least two ECG tests were included. The daily temperature was assimilated by combining three kinds of data: in situ observations, satellite remote sensing measurements and weather research forecast simulations. We used generalized estimating equations to control for autocorrelation among repeated records and to estimate the association between TA and the risk of ECG abnormalities. We found 6837 events of ECG abnormalities in 47,286 individuals with 102,030 visits. Each unit increment of TA increased the risk of ECG abnormalities [odds ratio (OR) = 1.009, 95% confidence interval (CI): 1.001-1.017] and the risk of myocardial ischemia (OR = 1.061, 95% CI: 1.012-1.111). Hierarchic analyses presented a similar association of TA with both ECG abnormalities (OR = 1.017, 95% CI: 1.008-1.026) and myocardial ischemia (OR = 1.061, 95%CI: 1.011-1.114) in Northern China, but not in Southern China. The exposure-response relationship was estimated as a U-shaped curve centered at the TA value of zero. Sudden warming tended to increase the risk of ECG abnormalities and myocardial ischemia, and sudden cooling tended to increase the risk of atrial fibrillation. All these detrimental effects of TA could be modified by specific individual characteristics. In summary, ambient temperature fluctuation increased the risk of ECG abnormalities. This result indicated that regular ECG tests could be an early-warning measure for monitoring the adverse health effects of temperature fluctuations.
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Affiliation(s)
- Jian Guo
- State Key Laboratory for Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing, 100730, China; Department of Cardiology, Peking Union Medical College Hospital, Beijing, 100730, China
| | - Tao Xue
- Department of Epidemiology and Biostatistics/Ministry of Education Key Laboratory of Epidemiology of Major Diseases (PKU), School of Public Health, Peking University Health Science Centre, Beijing, 100191, China; State Environmental Protection Key Laboratory of Atmospheric Exposure and Health Risk Management, Center for Environment and Health, Peking University, Beijing, 100871, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China.
| | - Man Cao
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Xueyan Han
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Zhaoyang Pan
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Dengmin Huang
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Wei Sun
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Jiarun Mi
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Yuanli Liu
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China
| | - Tianjia Guan
- School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 10005, China.
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Wu J, Wu Y, Wu Y, Yang R, Yu H, Wen B, Wu T, Shang S, Hu Y. The impact of heat waves and cold spells on pneumonia risk: A nationwide study. ENVIRONMENTAL RESEARCH 2024; 245:117958. [PMID: 38135100 DOI: 10.1016/j.envres.2023.117958] [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: 09/14/2023] [Revised: 12/02/2023] [Accepted: 12/15/2023] [Indexed: 12/24/2023]
Abstract
Climate change affects human health and has been linked to several infectious diseases in recent year. However, there is limited assessment on the impact of heat waves and cold spells on pneumonia risk. This study aims to examine the association of heat waves and cold spells with daily pneumonia hospitalizations in 168 cities in China. Data on pneumonia hospitalizations between 2014 and 2017 were extracted from a national claim database of 280 million beneficiaries. We consider combining temperature intensity and duration to define heat waves and cold spells.This association was quantified using a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model. Exposure-response curves and potential effect modifiers were also estimated. We found that the peak relative risk (RR) of cold spells on daily hospitalizations for pneumonia was observed in relatively mild cold spells with a threshold below the 3 days at the 2nd percentile (RR = 1.69, 95% CI: 1.46-1.92). The risk of heat waves increased with the thresholds, and the greatest risk was found for extremely heatwave period of 4 days at the 98th percentile (RR = 1.69, 95% CI: 1.46-1.92). Heat waves and cold spells are more likely to adversely affect women. In conclusion, our study provided novel and strong evidence that exposure to heat waves and cold spells was associate with increased hospital visits for pneumonia, especially in females. This is the first national study in China to comprehensively evaluate the influence of heat waves and cold spells on pneumonia risk, and the findings may offer valuable insights into the impact of climate change on public health.
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Affiliation(s)
- Junhui Wu
- School of Nursing, Peking University, 38 Xueyuan Road, Hai Dian District, Beijing, China; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China.
| | - Yao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Yiqun Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
| | - Ruotong Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
| | - Huan Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
| | - Bo Wen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China; Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia; Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China
| | - Shaomei Shang
- School of Nursing, Peking University, 38 Xueyuan Road, Hai Dian District, Beijing, China.
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 100191, Beijing, China; Medical Informatics Center, Peking University, 100191, Beijing, China.
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Liu S, Ho HC. Effects of socioeconomic status and greenspace on respiratory emergency department visits under short-term temperature variations: An age-stratified case time-series study. Soc Sci Med 2024; 343:116613. [PMID: 38290398 DOI: 10.1016/j.socscimed.2024.116613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/07/2023] [Accepted: 01/18/2024] [Indexed: 02/01/2024]
Abstract
INTRODUCTION Neighborhood socioeconomic status (SES) and greenspace can affect respiratory health. However, it is unclear whether effects of neighborhood SES and greenspace on respiratory health still exist regardless of temperature variations. METHODS This paper conducted a two-stage, age-stratified case time-series study. The first goal is to examine the associations between two temperature metrics (daily mean temperature [DMT] and diurnal temperature range [DTR]) and respiratory emergency department (ED) visits among four age groups in New York City. The second goal is to evaluate whether neighborhood SES and greenspace would be determinants of respiratory ED visits independent from temperature varying factors. A distributed lag nonlinear model was applied on ED data from 135 zip codes (October 2016 - February 2020). RESULTS Our first-stage analysis indicated that older adults aged 65+ had higher risk of ED visits (RR=2.78, 95% eCI: 2.41, 3.22; with 7 days of lag) on days with low DMT (-10°C), followed by adults aged 18-64 (RR=2.48, 95% eCI: 2.32, 2.65), children and youth aged 5-17 (RR=1.38, 95% eCI: 1.24, 1.53), and young children aged 0-4 (RR=1.04, 95% eCI: 0.96, 1.13). However, no excess respiratory ED visits were observed on days with high DMT (30°C). Higher DTR was associated with higher risk, with children and youth more susceptible when DTR was high (DTR 20°C; RR=5.70, 95% eCI: 3.42, 9.49; with 7 days of lag). The second-stage analysis indicated neighborhood SES and greenspace had significant associations with respiratory ED visits regardless of temperature variations. Specifically, Higher income and greenspace exposure were negatively associated with ED visits among all age groups. CONCLUSIONS Neighborhood SES and greenspace could affect respiratory morbidity regardless of weather conditions. Daily temperature variations accelerated the short-term risk among population subgroups under different weather conditions (e.g., higher risk of days with low DMT among older adults, higher risk of days with high DTR among children and youth aged 5-17), which could create co-effects with neighborhood SES and greenspace on respiratory health.
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Affiliation(s)
- Shengjie Liu
- Spatial Sciences Institute, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA 90089, United States of America; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America.
| | - Hung Chak Ho
- Department of Public and International Affairs, City University of Hong Kong, Kowloon, Hong Kong.
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Lane M, Ebelt S, Wu Z, Scovronick N, D'Souza RR, Chang HH. Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period. Environ Health 2024; 23:9. [PMID: 38254140 PMCID: PMC10804549 DOI: 10.1186/s12940-024-01048-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 01/07/2024] [Indexed: 01/24/2024]
Abstract
BACKGROUND Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD. METHODS For the period of 1993-2019, we analyzed over 12 million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade. RESULTS All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes. CONCLUSIONS Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.
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Affiliation(s)
- Morgan Lane
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA.
| | - Stefanie Ebelt
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Zhen Wu
- Department of Biostatistics and Bioinformatics, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Rohan R D'Souza
- Gangarosa Department of Environmental Health, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
| | - Howard H Chang
- Department of Biostatistics and Bioinformatics, Emory University, 1518 Clifton Rd, Atlanta, GA, USA
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Zhai C, Bai L, Xu Y, Liu Y, Sun H, Gong X, Yu G, Zong Q, Hu W, Wang F, Cheng J, Zou Y. Temperature variability associated with respiratory disease hospitalisations, hospital stays and hospital expenses the warm temperate sub-humid monsoon climate. Public Health 2023; 225:206-217. [PMID: 37939462 DOI: 10.1016/j.puhe.2023.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 08/25/2023] [Accepted: 10/06/2023] [Indexed: 11/10/2023]
Abstract
OBJECTIVES The abrupt change of climate has led to an increasing trend of hospitalised patients in recent years. This study aimed to analyse the temperature variability (TV) associated with respiratory disease (RD) hospitalisations, hospital stays and hospital expenses. STUDY DESIGN The generalized linear model combined with distributed lag non-linear model was used to investigate the association between TV and RD hospitalisations. METHODS TV was determined by measuring the standard deviation of maximum and minimum temperatures for the current day and the previous 7 days. RD hospitalisations data were obtained from three major tertiary hospitals in Huaibei City, namely, the Huaibei People's Hospital, the Huaibei Hospital Of Traditional Chinese Medicine and the Huaibei Maternal and Child Health Care Hospital. First, using a time series decomposition model, the seasonality and long-term trend of hospitalisations, hospital stays and hospital expenses for RD were explored in this warm temperate sub-humid monsoon climate. Second, robust models were used to analyse the association between TV and RD hospitalisations, hospital stays and hospital expenses. In addition, this study stratified results by sex, age and season. Third, using the attributable fraction (AF) and attributable number (AN), hospitalisations, hospital stays and hospital expenses for RD attributed to TV were quantified. RESULTS Overall, 0.013% of hospitalisations were attributed to TV0-1 (i.e. TV at the current day and previous 1 day), corresponding to 220 cases, 1603 days of hospital stays and 1,308,000 RMB of hospital expenses. Females were more susceptible to TV than males, and the risk increased with longer exposure (the highest risk was seen at TV0-7 [i.e. TV at the current day and previous 7 days] exposure). Higher AF and AN were observed at ages 0-5 years and ≥65 years. In addition, it was also found that TV was more strongly linked to RD in the cool season. The hot season was positively associated with hospital stays and hospital expenses at TV0-3 to TV0-7 exposure. CONCLUSIONS Exposure to TV increased the risk of hospitalisations, longer hospital stays and higher hospital expenses for RD. The findings suggested that more attention should be paid to unstable weather conditions in the future to protect the health of vulnerable populations.
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Affiliation(s)
- Chunxia Zhai
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Liangliang Bai
- School of Biomedical Engineering, Anhui Medical University, Hefei, Anhui, China
| | - Ying Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Yuqi Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Hongyu Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - XingYu Gong
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Guanghui Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Qiqun Zong
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Wanqin Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Fang Wang
- Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - Yanfeng Zou
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
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Rahman MM, Lorenzo M, Ban-Weiss G, Hasan Z, Azzouz M, Eckel SP, Conti DV, Lurmann F, Schlaerth H, Johnston J, Ko J, Palinkas L, Hurlburt M, Silva S, Gauderman WJ, McConnell R, Garcia E. Ambient temperature and air pollution associations with suicide and homicide mortality in California: A statewide case-crossover study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 874:162462. [PMID: 36858215 PMCID: PMC10465171 DOI: 10.1016/j.scitotenv.2023.162462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 02/04/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Higher ambient temperature and air pollution may contribute to increased risk of behaviors harmful to oneself or to others; however, quantitative evidence is limited. We examined the relationship of deaths due to suicide and homicide with temperature and air pollution in California-a state prone to high levels of both exposures. METHOD California death certificates from 2014 to 2019 were used to identify deaths due to suicide and homicide. Residential data for decedents were used to assign exposure to daily temperature (maximum[Tmax], minimum[Tmin]) and daily average air pollution concentrations (particulate matter <10 μm[PM10] and < 2.5 μm[PM2.5], nitrogen dioxide[NO2], ozone[O3]). Tmin served as a surrogate for nighttime temperature. A time-stratified case-crossover study design using conditional logistic regression was used to assess the effects of daily exposure to temperature and air pollutants on suicide and homicide mortality, adjusting for relative humidity. Effect modification by sex and age was assessed. RESULTS We observed 24,387 deaths due to suicide and 10,767 deaths due to homicide. We found a monotonic temperature association for both outcomes. A 5 °C increase in Tmax at lag-2 and Tmin at lag-0 was associated with 3.1 % (95 % confidence interval [CI]: 1.1 %-5.2 %) and 3.8 % (95%CI: 0.9 %-6.8 %) increased odds of death due to suicide, respectively. The increased odds of homicide mortality per 5 °C increase in Tmax at lag-0 and Tmin at lag-1 were 4.9 % (95%CI: 1.6 %-8.1 %) and 6.2 % (95%CI: 1.6 %-11.0 %), respectively. No air pollutant associations were statistically significant. Temperature associations were robust after adjustment for PM2.5. Some temperature effects were larger among women for suicide and men for homicide mortality, and among those over age 65 years for both outcomes. CONCLUSION Risk of suicide and homicide mortality increases with increasing daily ambient temperatures. Findings have public health relevance given anticipated increases in temperatures due to global climate change.
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Affiliation(s)
- Md Mostafijur Rahman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Melissa Lorenzo
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - George Ban-Weiss
- Department of Civil and Environmental Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Zainab Hasan
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Mehjar Azzouz
- Occupational and Environmental Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sandrah P Eckel
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - David V Conti
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Hannah Schlaerth
- Department of Civil and Environmental Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Jill Johnston
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Joseph Ko
- Department of Civil and Environmental Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Lawrence Palinkas
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Suzanne Dworak Peck School of Social Work, University of Southern California, Los Angeles, CA, USA
| | - Michael Hurlburt
- Suzanne Dworak Peck School of Social Work, University of Southern California, Los Angeles, CA, USA
| | - Sam Silva
- Department of Civil and Environmental Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Earth Sciences, University of Southern California, Los Angeles, CA, USA
| | - W James Gauderman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Rob McConnell
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Erika Garcia
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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Makunyane MS, Rautenbach H, Sweijd N, Botai J, Wichmann J. Health Risks of Temperature Variability on Hospital Admissions in Cape Town, 2011-2016. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:1159. [PMID: 36673914 PMCID: PMC9859170 DOI: 10.3390/ijerph20021159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 06/17/2023]
Abstract
Epidemiological studies have provided compelling evidence of associations between temperature variability (TV) and health outcomes. However, such studies are limited in developing countries. This study aimed to investigate the relationship between TV and hospital admissions for cause-specific diseases in South Africa. Hospital admission data for cardiovascular diseases (CVD) and respiratory diseases (RD) were obtained from seven private hospitals in Cape Town from 1 January 2011 to 31 October 2016. Meteorological data were obtained from the South African Weather Service (SAWS). A quasi-Poisson regression model was used to investigate the association between TV and health outcomes after controlling for potential effect modifiers. A positive and statistically significant association between TV and hospital admissions for both diseases was observed, even after controlling for the non-linear and delayed effects of daily mean temperature and relative humidity. TV showed the greatest effect on the entire study group when using short lags, 0-2 days for CVD and 0-1 days for RD hospitalisations. However, the elderly were more sensitive to RD hospitalisation and the 15-64 year age group was more sensitive to CVD hospitalisations. Men were more susceptible to hospitalisation than females. The results indicate that more attention should be paid to the effects of temperature variability and change on human health. Furthermore, different weather and climate metrics, such as TV, should be considered in understanding the climate component of the epidemiology of these (and other diseases), especially in light of climate change, where a wider range and extreme climate events are expected to occur in future.
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Affiliation(s)
- Malebo Sephule Makunyane
- School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria 0002, South Africa
- South African Weather Service, Pretoria 0001, South Africa
| | - Hannes Rautenbach
- School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria 0002, South Africa
- Faculty of Natural Sciences, Akademia, Pretoria 0002, South Africa
| | - Neville Sweijd
- Applied Centre for Climate and Earth Systems Science, Council for Scientific and Industrial Research, Cape Town 7700, South Africa
| | - Joel Botai
- South African Weather Service, Pretoria 0001, South Africa
- Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria 0002, South Africa
| | - Janine Wichmann
- School of Health Systems and Public Health, Faculty of Health Sciences, University of Pretoria, Pretoria 0002, South Africa
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8
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Lv S, Liu X, Li Z, Lu F, Guo M, Liu M, Wei J, Wu Z, Yu S, Li S, Li X, Gao W, Tao L, Wang W, Xin J, Guo X. Causal effect of PM 1 on morbidity of cause-specific respiratory diseases based on a negative control exposure. ENVIRONMENTAL RESEARCH 2023; 216:114746. [PMID: 36347395 DOI: 10.1016/j.envres.2022.114746] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/27/2022] [Accepted: 11/04/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Extensive studies have linked PM2.5 and PM10 with respiratory diseases (RD). However, few is known about causal association between PM1 and morbidity of RD. We aimed to assess the causal effects of PM1 on cause-specific RD. METHODS Hospital admission data were obtained for RD during 2014 and 2019 in Beijing, China. Negative control exposure and extreme gradient boosting with SHapley Additive exPlanation was used to explore the causality and contribution between PM1 and RD. Stratified analysis by gender, age, and season was conducted. RESULTS A total of 1,183,591 admissions for RD were recorded. Per interquartile range (28 μg/m3) uptick in concentration of PM1 corresponded to a 3.08% [95% confidence interval (CI): 1.66%-4.52%] increment in morbidity of total RD. And that was 4.47% (95% CI: 2.46%-6.52%) and 0.15% (95% CI: 1.44%-1.78%), for COPD and asthma, respectively. Significantly positive causal associations were observed for PM1 with total RD and COPD. Females and the elderly had higher effects on total RD, COPD, and asthma only in the warm months (Z = 3.03, P = 0.002; Z = 4.01, P < 0.001; Z = 3.92, P < 0.001; Z = 2.11, P = 0.035; Z = 2.44, P = 0.015). Contribution of PM1 ranked first, second and second for total RD, COPD, and asthma among air pollutants. CONCLUSION PM1 was causally associated with increased morbidity of total RD and COPD, but not causally associated with asthma. Females and the elderly were more vulnerable to PM1-associated effects on RD.
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Affiliation(s)
- Shiyun Lv
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Xiangtong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Zhiwei Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Feng Lu
- Beijing Municipal Health Commission Information Center, Beijing, 100034, China
| | - Moning Guo
- Beijing Municipal Health Commission Information Center, Beijing, 100034, China
| | - Mengmeng Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA
| | - Zhiyuan Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Siqi Yu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Shihong Li
- Department of Respiratory, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Xia Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, 3086, Australia
| | - Wenkang Gao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Lixin Tao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China
| | - Wei Wang
- School of Medical Sciences and Health, Edith Cowan University, WA6027, Perth, Australia
| | - Jinyuan Xin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, 100069, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China.
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Zhao J, Zhang Y, Ni Y, He J, Wang J, Li X, Guo Y, Li C, Zhang W, Cui Z. Effect of ambient temperature and other environmental factors on stroke emergency department visits in Beijing: A distributed lag non-linear model. Front Public Health 2022; 10:1034534. [PMID: 36466462 PMCID: PMC9709270 DOI: 10.3389/fpubh.2022.1034534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/24/2022] [Indexed: 11/18/2022] Open
Abstract
Background Most studies have focused on the relationship between ambient temperature and stroke mortality, but studies on the relationship between ambient temperature and stroke occurrence are still limited and inconsistent. Objective This study aimed to analyze the effect of ambient temperature and other environmental factors on emergency stroke visits in Beijing. Methods Our study utilized stroke visit data from the Beijing Red Cross Emergency Medical Center during 2017-2018, and applied a generalized additive model (GAM) as well as a distributed lag non-linear model (DLNM), respectively, regarding the direct, lagged, and cumulative effects of ambient temperature alone and with correction for other environmental factors on stroke occurrence. Results With a total of 26,984 emergency stroke patients in 2017-2018, both cold and hot effects were observed and weakened after correction for other environmental factors. Compared to the reference temperature, in the multi-factor model, extreme cold (-10°C) reached a maximum relative risk (RR) of 1.20 [95% Confidence Interval (CI): 1.09, 1.32] at lag 14 days, and extreme hot (30°C) had a maximum RR of 1.07 (95% CI: 1.04, 1.11) at lag 6 days. The cumulative effect of extreme cold reached a maximum of 2.02 (95% CI: 1.11, 3.67) at lag 0-14 days, whereas the cumulative effect of extreme hot temperature is greatest at lag 0-10 days, but no statistically significant effect was found. In addition, ischemic stroke patients, the elderly, and males were more susceptible to the effects of cold temperature. Conclusions There is a non-linear relationship between ambient temperature and stroke occurrence, with cold temperature having a greater and longer-lasting impact than hot temperature.
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Affiliation(s)
- Jinhua Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yongming Zhang
- Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, National Clinical Research Center for Respiratory Diseases, Beijing, China
| | - Ying Ni
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Junyu He
- Ocean College, Zhejiang University, Zhoushan, China,Ocean Academy, Zhejiang University, Zhoushan, China
| | - Jianping Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Xuan Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Changping Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Wenyi Zhang
- Chinese PLA Center for Disease Control and Prevention, Beijing, China,Wenyi Zhang
| | - Zhuang Cui
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China,*Correspondence: Zhuang Cui
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