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Tao C, Liu Z, Fan Y, Yuan Y, Wang X, Qiao Z, Li Z, Xu Q, Lou Z, Wang H, Li X, Li R, Lu C. Estimating neighborhood-based mortality risk associated with air pollution: A prospective study. JOURNAL OF HAZARDOUS MATERIALS 2024; 475:134861. [PMID: 38870855 DOI: 10.1016/j.jhazmat.2024.134861] [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: 04/08/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 06/15/2024]
Abstract
Effect modification of integrated neighborhood environment on associations of air pollution with mortality remained unclear. We analyzed data from UK biobank prospective study (n = 421,650, median 12.5 years follow-up) to examine disparities of mortality risk associated with air pollution among varied neighborhood settings. Fine particulate matter (PM2.5), PM10 and nitrogen dioxide (NO2) were measured and assigned to each participants' address. Diverse ecological and societal settings of neighborhoods were integrated with principal component analysis and categorized into disadvantaged, intermediate and advantaged levels. We estimated mortality risk associated with air pollution across diverse neighborhoods using Cox regression. We calculated community-level proportions of mortality attributable to air pollutants. There was evidence of higher all-cause and respiratory disease mortality risk associated with PM2.5 and NO2 among those in disadvantaged neighborhoods. In disadvantaged communities, air pollutants explained larger proportions of deaths and such disparities persisted over past decades. Across 2010-2021, reducing PM2.5 and NO2 to 10 μg/m3 (World Health Organization limits) would save 87,000 (52,000-120,000) and 91,000 (37,000-145,000) deaths of populations aged ≥ 40 years, with 150 000 deaths occurred in disadvantaged neighborhood settings. These findings suggested that disadvantaged neighborhoods can exacerbate mortality risk associated with air pollution.
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Affiliation(s)
- Chengzhe Tao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhaoyin Liu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yun Fan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yiting Yuan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xinru Wang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ziyan Qiao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhi Li
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Qiaoqiao Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhe Lou
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Haowei Wang
- School of Public Health, Imperial College London, UK; MRC Centre for Global Infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
| | - Xiang Li
- School of Public Health, Imperial College London, UK; MRC Centre for Global Infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
| | - Ruiyun Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Chuncheng Lu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
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Karimi B, Samadi S. Long-term exposure to air pollution on cardio-respiratory, and lung cancer mortality: a systematic review and meta-analysis. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2024; 22:75-95. [PMID: 38887768 PMCID: PMC11180069 DOI: 10.1007/s40201-024-00900-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 04/02/2024] [Indexed: 06/20/2024]
Abstract
Air pollution is a major cause of specific deaths worldwide. This review article aimed to investigate the results of cohort studies for air pollution connected with the all-cause, cardio-respiratory, and lung cancer mortality risk by performing a meta-analysis. Relevant cohort studies were searched in electronic databases (PubMed/Medline, Web of Science, and Scopus). We used a random effect model to estimate the pooled relative risks (RRs) and their 95% CIs (confidence intervals) of mortality. The risk of bias for each included study was also assessed by Office of Health Assessment and Translation (OHAT) checklists. We applied statistical tests for heterogeneity and sensitivity analyses. The registration code of this study in PROSPERO was CRD42023422945. A total of 88 cohort studies were eligible and included in the final analysis. The pooled relative risk (RR) per 10 μg/m3 increase of fine particulate matter (PM2.5) was 1.080 (95% CI 1.068-1.092) for all-cause mortality, 1.058 (95% CI 1.055-1.062) for cardiovascular mortality, 1.066 (95%CI 1.034-1.097) for respiratory mortality and 1.118 (95% CI 1.076-1.159) for lung cancer mortality. We observed positive increased associations between exposure to PM2.5, PM10, black carbon (BC), and nitrogen dioxide (NO2) with all-cause, cardiovascular and respiratory diseases, and lung cancer mortality, but the associations were not significant for nitrogen oxides (NOx), sulfur dioxide (SO2) and ozone (O3). The risk of mortality for males and the elderly was higher compared to females and younger age. The pooled effect estimates derived from cohort studies provide substantial evidence of adverse air pollution associations with all-cause, cardiovascular, respiratory, and lung cancer mortality. Supplementary Information The online version contains supplementary material available at 10.1007/s40201-024-00900-6.
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Affiliation(s)
- Behrooz Karimi
- Department of Environmental Health Engineering, School of Health, Arak University of Medical Sciences, Arak, Iran
| | - Sadegh Samadi
- Department of Occupational Health and safety, School of Health, Arak University of Medical Sciences, Arak, Iran
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Riggs DW, Baumgartner KB, Baumgartner R, Boone S, Judd SE, Bhatnagar A. Long-term exposure to air pollution and risk of stroke by ecoregions: The REGARDS study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 345:123367. [PMID: 38280465 PMCID: PMC10996890 DOI: 10.1016/j.envpol.2024.123367] [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: 09/18/2023] [Revised: 01/11/2024] [Accepted: 01/14/2024] [Indexed: 01/29/2024]
Abstract
Several cohort studies have found associations between long-term exposure to air pollution and stroke risk. However, it is unclear whether the surrounding ecology may modify these associations. This study evaluates associations of air pollution with stroke risk by ecoregions, which are areas of similar type, quality, and quantity of environmental resources in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. We assessed the incidence of stroke in 26,792 participants (45+ yrs) from the REGARDS study, a prospective cohort recruited across the contiguous United States. One-yr and 3-yr means of PM2.5, PM10, O3, NO2, SO2, and CO were estimated at baseline using data from the Center for Air, Climate, & Energy Solution, and assigned to participants at the census block group level. Incident stroke was ascertained through September 30, 2020. Relations of air pollutants with the risk of incident stroke were estimated using Cox proportional hazards models, adjusting for relevant demographics, behavioral risk factors, and neighborhood urbanicity. Models were stratified by EPA designated ecoregions. A 5.4 μg/m3 (interquartile range) increase in 1-yr PM10 was associated with a hazard ratio (95 %CI) for incident stroke of 1.07 (1.003, 1.15) in the overall study population. We did not find evidence of positive associations for PM2.5, O3, NO2, SO2, and CO in the fully adjusted models. In our ecoregion-specific analysis, associations of PM2.5 with stroke were stronger in the Great Plains ecoregion (HR = 1.44) than other ecoregions, while associations for PM10 were strongest in the Eastern Temperate Forests region (HR = 1.15). The associations between long-term exposure to air pollution and risk of stroke varied by ecoregion. Our results suggests that the type, quality, and quantity of the surrounding ecology can modify the effects of air pollution on risk of stroke.
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Affiliation(s)
- Daniel W Riggs
- Christina Lee Brown Envirome Institute, University of Louisville, Louisville, KY, United States; Department of Epidemiology and Population Health, University of Louisville, Louisville, KY, United States.
| | - Kathy B Baumgartner
- Department of Epidemiology and Population Health, University of Louisville, Louisville, KY, United States
| | - Richard Baumgartner
- Department of Epidemiology and Population Health, University of Louisville, Louisville, KY, United States
| | - Stephanie Boone
- Department of Epidemiology and Population Health, University of Louisville, Louisville, KY, United States
| | - Suzanne E Judd
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, University of Louisville, Louisville, KY, United States
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Riggs DW, Bhatnagar A. Invited Perspective: A Natural Prescription for Hypertension? ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:31301. [PMID: 38427032 PMCID: PMC10906658 DOI: 10.1289/ehp14482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 03/02/2024]
Affiliation(s)
- Daniel W. Riggs
- Department of Medicine, University of Louisville, Louisville, Kentucky, USA
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, University of Louisville, Louisville, Kentucky, USA
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Goldney J, Henson J, Edwardson CL, Khunti K, Davies MJ, Yates T. Long-term ambient air pollution exposure and prospective change in sedentary behaviour and physical activity in individuals at risk of type 2 diabetes in the UK. J Public Health (Oxf) 2024; 46:e32-e42. [PMID: 38103023 PMCID: PMC10901272 DOI: 10.1093/pubmed/fdad263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Air pollution may be a risk factor for physical inactivity and sedentary behaviour (SED) through discouraging active lifestyles, impairing fitness and contributing to chronic diseases with potentially important consequences for population health. METHODS Using generalized estimating equations, we examined the associations between long-term particulate matter with diameter ≤2.5 μm (PM2.5), ≤10 μm (PM10) and nitrogen dioxide (NO2) and annual change in accelerometer-measured SED, moderate-to-vigorous physical activity (MVPA) and steps in adults at risk of type 2 diabetes within the Walking Away from Type 2 Diabetes trial. We adjusted for important confounders including social deprivation and measures of the built environment. RESULTS From 808 participants, 644 had complete data (1605 observations; 64.7% men; mean age 63.86 years). PM2.5, NO2 and PM10 were not associated with change in MVPA/steps but were associated with change in SED, with a 1 ugm-3 increase associated with 6.38 (95% confidence interval: 0.77, 12.00), 1.52 (0.49, 2.54) and 4.48 (0.63, 8.34) adjusted annual change in daily minutes, respectively. CONCLUSIONS Long-term PM2.5, NO2 and PM10 exposures were associated with an annual increase in SED: ~11-22 min/day per year across the sample range of exposure (three standard deviations). Future research should investigate whether interventions to reduce pollution may influence SED.
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Affiliation(s)
- Jonathan Goldney
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Joseph Henson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Charlotte L Edwardson
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- Leicester Real World Evidence Unit, Leicester Diabetes Centre, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Melanie J Davies
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
| | - Thomas Yates
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, University Hospitals of Leicester NHS Trust and University of Leicester, Gwendolen Rd, Leicester LE5 4PW, UK
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Wu W, Wu G, Wei J, Lawrence WR, Deng X, Zhang Y, Chen S, Wang Y, Lin X, Chen D, Ruan X, Lin Q, Li Z, Lin Z, Hao C, Du Z, Zhang W, Hao Y. Potential causal links and mediation pathway between urban greenness and lung cancer mortality: Result from a large cohort (2009 to 2020). SUSTAINABLE CITIES AND SOCIETY 2024; 101:105079. [PMID: 38222851 PMCID: PMC10783447 DOI: 10.1016/j.scs.2023.105079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Urban greenness, as a vital component of the urban environment, plays a critical role in mitigating the adverse effects of rapid urbanization and supporting urban sustainability. However, the causal links between urban greenness and lung cancer mortality and its potential causal pathway remain poorly understood. Based on a prospective community-based cohort with 581,785 adult participants in southern China, we applied a doubly robust Cox proportional hazard model to estimate the causal associations between urban greenness exposure and lung cancer mortality. A general multiple mediation analysis method was utilized to further assess the potential mediating roles of various factors including particulate matter (PM1, PM2.5-1, and PM10-2.5), temperature, physical activity, and body mass index (BMI). We observed that each interquartile range (IQR: 0.06) increment in greenness exposure was inversely associated with lung cancer mortality, with a hazard ratio (HR) of 0.89 (95 % CI: 0.83, 0.96). The relationship between greenness and lung cancer mortality might be partially mediated by particulate matter, temperature, and physical activity, yielding a total indirect effect of 0.826 (95 % CI: 0.769, 0.887) for each IQR increase in greenness exposure. Notably, the protective effect of greenness against lung cancer mortality could be achieved primarily by reducing the particulate matter concentration.
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Affiliation(s)
- Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, USA
| | - Wayne R Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Xinlei Deng
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, USA
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xiao Lin
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Dan Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xinling Ruan
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Qiaoxuan Lin
- Department of Statistics, Guangzhou Health Technology Identification & Human Resources Assessment Center, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China
| | - Chun Hao
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, China
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Brown SC, Aitken WW, Lombard J, Parrish A, Dewald JR, Ma R, Messinger S, Liu S, Nardi MI, Rundek T, Szapocznik J. Longitudinal Impacts of Precision Greenness on Alzheimer's Disease. J Prev Alzheimers Dis 2024; 11:710-720. [PMID: 38706287 PMCID: PMC11061009 DOI: 10.14283/jpad.2024.38] [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: 06/16/2023] [Accepted: 11/13/2023] [Indexed: 05/07/2024]
Abstract
BACKGROUND The potential for greenness as a novel protective factor for Alzheimer's disease (AD) requires further exploration. OBJECTIVES This study assesses prospectively and longitudinally the association between precision greenness - greenness measured at the micro-environmental level, defined as the Census block - and AD incidence. DESIGN Older adults living in consistently high greenness Census blocks across 2011 and 2016 were compared to those living in consistently low greenness blocks on AD incidence during 2012-2016. SETTING Miami-Dade County, Florida, USA. PARTICIPANTS 230,738 U.S. Medicare beneficiaries. MEASUREMENTS U.S. Centers for Medicare and Medicaid Services Chronic Condition Algorithm for AD based on ICD-9 codes, Normalized Difference Vegetation Index, age, sex, race/ethnicity, neighborhood income, and walkability. RESULTS Older adults living in the consistently high greenness tertile, compared to those in the consistently low greenness tertile, had 16% lower odds of AD incidence (OR=0.84, 95% CI: 0.76-0.94, p=0.0014), adjusting for age, sex, race/ethnicity, and neighborhood income. Age, neighborhood income and walkability moderated greenness' relationship to odds of AD incidence, such that younger ages (65-74), lower-income, and non-car dependent neighborhoods may benefit most from high greenness. CONCLUSIONS High greenness, compared to low greenness, is associated with lower 5-year AD incidence. Residents who are younger and/or who reside in lower-income, walkable neighborhoods may benefit the most from high greenness. These findings suggest that consistently high greenness at the Census block-level, may be associated with reduced odds of AD incidence at a population level.
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Affiliation(s)
- S C Brown
- William W. Aitken, M.D., on behalf of the University of Miami Built Environment, Behavior, and Health Research Group, University of Miami Miller School of Medicine, 1120 NW 14th Street, Suite #1065, Miami, FL 33136, USA. Tel.: +1 305-519-5136.
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Li W, Tian A, Shi Y, Chen B, Ji R, Ge J, Su X, Pu B, Lei L, Ma R, Wang Q, Ban J, Song L, Xu W, Zhang Y, He W, Yang H, Li X, Li T, Li J. Associations of long-term fine particulate matter exposure with all-cause and cause-specific mortality: results from the ChinaHEART project. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 41:100908. [PMID: 37767374 PMCID: PMC10520991 DOI: 10.1016/j.lanwpc.2023.100908] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 08/14/2023] [Accepted: 09/05/2023] [Indexed: 09/29/2023]
Abstract
Background The chronic effects of fine particulate matter (PM2.5) at high concentrations remains uncertain. We aimed to examine the relationship of long-term PM2.5 exposure with all-cause and the top three causes of death (cardiovascular disease [CVD], cancer, and respiratory disease), and to analyze their concentration-response functions over a wide range of concentrations. Methods We enrolled community residents aged 35-75 years from 2014 to 2017 from all 31 provinces of the Chinese Mainland, and followed them up until 2021. We used a long-term estimation dataset for both PM2.5 and O3 concentrations with a high spatiotemporal resolution to assess the individual exposure, and used Cox proportional hazards models to estimate the associations between PM2.5 and mortalities. Findings We included 1,910,923 participants, whose mean age was 55.6 ± 9.8 years and 59.4% were female. A 10 μg/m3 increment in PM2.5 exposure was associated with increased risk for all-cause death (hazard ratio 1.02 [95% confidence interval 1.012-1.028]), CVD death (1.024 [1.011-1.037]), cancer death (1.037 [1.023-1.052]), and respiratory disease death (1.083 [1.049-1.117]), respectively. Long-term PM2.5 exposure nonlinearly related with all-cause, CVD, and cancer mortalities, while linearly related with respiratory disease mortality. Interpretation The overall effects of long-term PM2.5 exposure on mortality in the high concentration settings are weaker than previous reports from settings of PM2.5 concentrations < 35 μg/m³. The distinct concentration-response relationships of CVD, cancer, and respiratory disease mortalities could facilitate targeted public health efforts to prevent death caused by air pollution. Funding The Chinese Academy of Medical Sciences Innovation Fund for Medical Science, the National High Level Hospital Clinical Research Funding, the Ministry of Finance of China and National Health Commission of China, the 111 Project from the Ministry of Education of China.
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Affiliation(s)
- Wei Li
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Aoxi Tian
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Yu Shi
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, Guangdong Province, People’s Republic of China
| | - Bowang Chen
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Runqing Ji
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Jinzhuo Ge
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Xiaoming Su
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Boxuan Pu
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Lubi Lei
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Runmei Ma
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Qing Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Jie Ban
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Lijuan Song
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Wei Xu
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Yan Zhang
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Wenyan He
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Hao Yang
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
| | - Xi Li
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
- Central China Sub-center of the National Center for Cardiovascular Diseases, Zhengzhou, People’s Republic of China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China
| | - Jing Li
- National Clinical Research Center for Cardiovascular Diseases, NHC Key Laboratory of Clinical Research for Cardiovascular Medications, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, National Center for Cardiovascular Diseases, Beijing, People’s Republic of China
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Wu W, Du Z, Wang Y, Zhang Y, Chen S, Ju X, Wu G, Li Z, Sun J, Jiang J, Hu W, Lin Z, Qu Y, Xiao J, Zhang W, Hao Y. The complex role of air pollution on the association between greenness and respiratory mortality: Insight from a large cohort, 2009-2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 899:165588. [PMID: 37474059 DOI: 10.1016/j.scitotenv.2023.165588] [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: 05/18/2023] [Revised: 07/08/2023] [Accepted: 07/15/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Although emerging studies have illuminated the protective association between greenness and respiratory mortality, efforts to quantify the potentially complex role of air pollution in the causal pathway are still limited. We aimed to examine the potential roles of air pollution in the causal pathway between greenness and respiratory mortality in China. METHODS We used data from a community-based prospective cohort of 654,115 participants in southern China (Jan 2009-Dec 2020). We evaluated the greenness exposure as a three-year moving average Normalized Difference Vegetation Index (NDVI) within the 500 m buffer around the residence. Cox proportional hazards model was applied to estimate the association between greenness and respiratory mortality. Causal mediation analysis combined with a four-way dimensional decomposition method was utilized to simultaneously quantify the interaction and mediation role of air pollution including PM2.5, PM10, or NO2 on the greenness-respiratory mortality relationship. FINDINGS We observed 6954 respiratory deaths during 12 years of follow-up. Increasing NDVI level from the lowest to the highest quartile is associated with a 19 % (95%CI: 13-25 %) reduction in the respiratory mortality risk. For the total protective effect, the proportion attributable to the overall negative interaction between greenness and air pollution (PM2.5, PM10, or NO2) was 2.2 % (1.7-3.2 %), 3.5 % (0.4-3.7 %), or 25.0 % (22.8-27.1 %), respectively. Simultaneously, we estimated 25.5 % (20.1-32.0 %), 49.5 % (32.5-71.9 %), or 1.0 % (0.8-1.2 %) of the total protective association was mediated through a reduction in PM2.5, PM10, or NO2, respectively. INTERPRETATION Increased greenness exposure mitigated respiratory mortality through both the antagonistic interaction and mediation pathway of air pollution (PM2.5, PM10, or NO2).
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Affiliation(s)
- Wenjing Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Ying Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Yuqin Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shirui Chen
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xu Ju
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhiqaing Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jie Sun
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jie Jiang
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
| | - Weihua Hu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China
| | - Ziqiang Lin
- Department of Preventive Medicine, School of Basic Medicine and Public Health, Jinan University, Guangzhou, China
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangzhou, Guangdong, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research &Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Peking, China.
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Ye L, Zhou J, Tian Y, Cui J, Chen C, Wang J, Wang Y, Wei Y, Ye J, Li C, Chai X, Sun C, Li F, Wang J, Guo Y, Jaakkola JJK, Lv Y, Zhang J, Shi X. Associations of residential greenness and ambient air pollution with overweight and obesity in older adults. Obesity (Silver Spring) 2023; 31:2627-2637. [PMID: 37649157 DOI: 10.1002/oby.23856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Revised: 05/28/2023] [Accepted: 05/31/2023] [Indexed: 09/01/2023]
Abstract
OBJECTIVE This study aimed to examine the impact of greenness and fine particulate matter <2.5 μm (PM2.5 ) on overweight/obesity among older adults in China. METHODS A total of 21,355 participants aged ≥65 years were included from the Chinese Longitudinal Healthy Longevity Survey between 2000 and 2018. Normalized difference vegetation index (NDVI) with a radius of 250 m and PM2.5 in a 1 × 1-km grid resolution were calculated around each participant's residence. Cox proportional hazards models were used to estimate the effects of NDVI and PM2.5 on overweight/obesity. Interaction and mediation analyses were conducted to explore combined effects. RESULTS The study observed 1895 incident cases of overweight/obesity over 109,566 person-years. For every 0.1-unit increase in NDVI the hazard ratio of overweight/obesity was 0.91 (95% CI: 0.88-0.95), and for every 10-μg/m3 increase in PM2.5 the hazard ratio was 1.11 (95% CI: 1.07-1.14). The effect of NDVI on overweight/obesity was partially mediated by PM2.5 , with a relative mediation proportion of 20.10% (95% CI: 1.63%-38.57%). CONCLUSIONS Greenness exposure appears to lower the risk of overweight/obesity in older adults in China, whereas PM2.5 , acting as a mediator, partly mediated this protective effect.
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Affiliation(s)
- Lihong Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Jinhui Zhou
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yanlin Tian
- Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jia Cui
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chen Chen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jun Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yueqing Wang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Yuan Wei
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Jiaming Ye
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Chenfeng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Anhui Medical University, Hefei, China
| | - Xin Chai
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chris Sun
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fangyu Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- School of Public Health, Anhui Medical University, Hefei, China
| | - Jiaonan Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yanbo Guo
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China
| | - Jouni J K Jaakkola
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
- Finnish Meteorological Institute, Helsinki, Finland
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Juan Zhang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
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Li J, Xie Y, Xu J, Zhang C, Wang H, Huang D, Li G, Tian J. Association between greenspace and cancer: evidence from a systematic review and meta-analysis of multiple large cohort studies. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:91140-91157. [PMID: 37474858 DOI: 10.1007/s11356-023-28461-5] [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: 01/27/2023] [Accepted: 06/23/2023] [Indexed: 07/22/2023]
Abstract
Cancer is a chronic disease that seriously endangers human health, and studies on its association with greenspace have been published. We aimed to systematically review the epidemiological evidence and obtain the best available evidence. PubMed, Web of Science, Embase, and Cochrane Library were used as search databases, the time limit was September 12, 2022, and the cited articles were manually supplemented. Two researchers independently performed literature screening and data extraction. We performed a meta-analysis of data using a normalized difference vegetation index (NDVI) as the greenspace measure, providing hazard ratio (HR) and corresponding 95% CI. After standardization of the data, we used a random effects model for pooling. We also assessed the risk of bias for each study and the quality of each evidence body. We identified 10,108 items and included 14 studies from 11 institutions in eight countries. All studies had a low risk of bias. Quantitative analysis of 13 studies found a beneficial association of greenspace with the mortality of lung cancer (pooled HR [95% CI]=0.965 [0.947, 0.983]) and prostate cancer (HR [95% CI]=0.939 [0.898, 0.980]) based on 0.1-unit NDVI increment and a potential beneficial association with the incidence of prostate, lung, and breast cancer. Greenspace had opposite associations with cancer mortality for urban and rural populations. Indirect comparisons did not find statistically significant differences in the effects of greenspace on different cancer outcomes. The evidence body assessment was considered to be "very low." This review indicated potential beneficial associations between greenspace for lung, prostate, and breast cancer outcomes. However, there was a lack of mediation analysis to explore the underlying mechanism of a causal association. Meanwhile, the interstudy heterogeneity was large. Therefore, future studies should consider more accurate exposure assessment and more comprehensive covariate coverage, while focusing on mediating analysis. PROSPERO: CRD42022361068.
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Affiliation(s)
- Jiang Li
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yafei Xie
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou, 730000, China
- The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China
| | - Jianguo Xu
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Chun Zhang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Huilin Wang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Danqi Huang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Guoqiang Li
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Jinhui Tian
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou University, Lanzhou, 730000, China.
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China.
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Anderson LB, Kanneganti D, Houk MB, Holm RH, Smith T. Generative AI as a Tool for Environmental Health Research Translation. GEOHEALTH 2023; 7:e2023GH000875. [PMID: 37502196 PMCID: PMC10369501 DOI: 10.1029/2023gh000875] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/30/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023]
Abstract
One valuable application for generative artificial intelligence (AI) is summarizing research studies for non-academic readers. We submitted five articles to Chat Generative Pre-trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight-oriented activities, such as the production of eighth-grade reading level summaries, and summaries highlighting the most important findings and real-world applications. The general summary request was rated lower. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.
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Affiliation(s)
- Lauren B. Anderson
- Christina Lee Brown Envirome InstituteSchool of MedicineUniversity of LouisvilleLouisvilleKYUSA
- Department of Urban and Public AffairsCollege of Arts and SciencesUniversity of LouisvilleLouisvilleKYUSA
| | - Dhiraj Kanneganti
- Christina Lee Brown Envirome InstituteSchool of MedicineUniversity of LouisvilleLouisvilleKYUSA
| | - Mary Bentley Houk
- Christina Lee Brown Envirome InstituteSchool of MedicineUniversity of LouisvilleLouisvilleKYUSA
| | - Rochelle H. Holm
- Christina Lee Brown Envirome InstituteSchool of MedicineUniversity of LouisvilleLouisvilleKYUSA
| | - Ted Smith
- Christina Lee Brown Envirome InstituteSchool of MedicineUniversity of LouisvilleLouisvilleKYUSA
- University of Louisville Superfund Research CenterLouisvilleKYUSA
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Anderson LB, Kanneganti D, Houk MB, Holm RH, Smith T. Generative AI as a Tool for Environmental Health Research Translation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.14.23285938. [PMID: 36865187 PMCID: PMC9980240 DOI: 10.1101/2023.02.14.23285938] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Generative artificial intelligence, popularized by services like ChatGPT, has been the source of much recent popular attention for publishing health research. Another valuable application is in translating published research studies to readers in non-academic settings. These might include environmental justice communities, mainstream media outlets, and community science groups. Five recently published (2021-2022) open-access, peer-reviewed papers, authored by University of Louisville environmental health investigators and collaborators, were submitted to ChatGPT. The average rating of all summaries of all types across the five different studies ranged between 3 and 5, indicating good overall content quality. ChatGPT’s general summary request was consistently rated lower than all other summary types. Whereas higher ratings of 4 and 5 were assigned to the more synthetic, insight-oriented activities, such as the production of a plain language summaries suitable for an 8 th grade reading level and identifying the most important finding and real-world research applications. This is a case where artificial intelligence might help level the playing field, for example by creating accessible insights and enabling the large-scale production of high-quality plain language summaries which would truly bring open access to this scientific information. This possibility, combined with the increasing public policy trends encouraging and demanding free access for research supported with public funds, may alter the role journal publications play in communicating science in society. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) from its current capability.
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Cruz-Piedrahita C, Roscoe CJ, Howe C, Fecht D, de Nazelle A. Holistic approach to assess the association between the synergistic effect of physical activity, exposure to greenspace, and fruits and vegetable intake on health and wellbeing: Cross-sectional analysis of UK Biobank. Front Public Health 2022; 10:886608. [PMID: 36249200 PMCID: PMC9561552 DOI: 10.3389/fpubh.2022.886608] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/30/2022] [Indexed: 01/21/2023] Open
Abstract
Background Urban agriculture has been shown to contribute to healthy lifestyle behaviors, such as increased fruit and vegetable intake and greater exposure to greenspaces and there is plenty of evidence linking these lifestyle behaviors to better health and wellbeing. However, most evidence relates to assessing one behavior at a time despite available epidemiological research showing how the combined effects of multiple behaviors are associated with health and wellbeing. This research aims to examine the association of the interactions between various lifestyle behaviors and exposures related to urban agriculture and health and wellbeing. Methods We used data from the UK Biobank baseline questionnaire (N~500, 000) to assess the association of two lifestyle behaviors (fruit and vegetable intake and physical activity) and greenspace exposure, with four health and wellbeing markers (blood pressure, BMI, self-health assessment, and self-reported loneliness) independently, and in combination. Associations between lifestyle behaviors, greenspace exposure, and the possible interactions with health and wellbeing were explored using general linear models (GLMs), adjusted for socio-demographic confounders including age, sex, educational qualifications, index of multiple deprivation, and ethnicity, and a lifestyle confounder: smoking status. Results After removing missing data, as well as participants who did not meet the inclusion criteria, the final study sample was n = 204,478. The results indicate that meeting recommended levels of the World Health Organization (WHO) for fruits and vegetable intake, and the advice from the UK Chief Medical Officer for physical activity, is linked to better health and wellbeing markers. We found that UK Biobank participants who lived in greener areas and were physically active were more likely to feel alone and think their health was poor. Participants who were physically active and met the recommended intake of fruits and vegetables were more likely to have healthy blood pressure, feel less lonely, and rate their health as good. Evidence of three-way interactions was weak, and mostly was not associated with the health and wellbeing markers assessed here. Conclusion Taken in combination, healthy diets, physical activity and exposure to greenspaces are associated with health and wellbeing. In some cases, these effects are synergistic, indicating associations above and beyond the mere additive effect of the behaviors considered independently. Promoting such behaviors together, for example, through urban agriculture, is therefore more likely to generate greater public health changes than if they are promoted through independent policies and programs. Inter-relationships between these pathways and different health and wellbeing markers, however, are complex, and require further investigation to understand optimal environments and conditions for urban health promotion.
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Affiliation(s)
| | - Charlotte J. Roscoe
- Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Caroline Howe
- Centre for Environmental Policy, Imperial College London, London, United Kingdom
| | - Daniela Fecht
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Audrey de Nazelle
- Centre for Environmental Policy, Imperial College London, London, United Kingdom
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