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Chen H, Yin J, Xiang Y, Zhang N, Huang Z, Zhang Y, Tang D, Wang Z, Baimayangji, Chen L, Jiang X, Xiao X, Zhao X. Alcohol consumption and accelerated biological ageing in middle-aged and older people: A longitudinal study from two cohorts. Addiction 2024; 119:1387-1399. [PMID: 38679855 DOI: 10.1111/add.16501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 03/13/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND AND AIMS The relationship between alcohol consumption and age-related diseases is inconsistent. Biological age (BA) serves as both a precursor and a predictor of age-related diseases; however, longitudinal associations between alcohol consumption and BA in middle-aged and older people remain unclear. We measured whether there was a longitudinal association between drinking frequency and pure alcohol intake with BA among middle-aged and older people. DESIGN AND SETTING AND PARTICIPANTS This study involved two prospective cohort studies, set in Southwestern China and the United Kingdom. A total of 8046 participants from the China Multi-Ethnic Cohort study (CMEC) and 5412 participants from the UK Biobank (UKB), aged 30-79 years, took part, with complete data from two waves of clinical biomarkers. MEASUREMENTS BA was calculated by the Klemera Doubal's method. Accelerated BA equalled BA minus chronological age. Drinking frequency and pure alcohol intake were obtained through self-reported questionnaires. Drinking frequency in the past year was classified as current non-drinking, occasional (monthly drinking) and regular (weekly drinking). FINDINGS Compared with consistent current non-drinkers, more frequent drinkers [CMEC: β = 0.46, 95% confidence interval (CI) = 0.13-0.80; UKB: β = 0.65, 95% CI = 0.01-1.29)], less frequent drinkers (CMEC: β = 0.62, 95% CI = 0.37-0.87; UKB: β = 0.54, 95% CI = -0.01-1.09), consistent occasional drinkers (CMEC: β = 0.51, 95% CI = 0.23-0.79; UKB: β = 0.63, 95% CI = 0.13-1.13) and consistent regular drinkers (CMEC: β = 0.56, 95% CI = 0.17-0.95; UKB: β = 0.46, 95% CI = 0.00-0.91) exhibited increased accelerated BA. A non-linear relationship between pure alcohol intake and accelerated BA was observed among consistent regular drinkers. CONCLUSIONS In middle-aged and older people, any change in drinking frequency and any amount of pure alcohol intake seem to be positively associated with acceleration of biological ageing, compared with maintaining abstinence.
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Affiliation(s)
- Hongxiang Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jianzhong Yin
- School of Public Health, Kunming Medical University, Kunming, China
- Baoshan College of Traditional Chinese Medicine, Baoshan, China
| | - Yi Xiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ning Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Zitong Huang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yuan Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Dan Tang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ziyun Wang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Baimayangji
- School of Medicine, Tibet University, Lhasa, China
| | - Liling Chen
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Institute of Chronic Non-Communicable Disease Control and Prevention, Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Xiaoman Jiang
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Xiong Xiao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
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Kim K, Joyce BT, Zheng Y, Nannini DR, Wang J, Gordon-Larsen P, Bhatt A, Gabriel K, Shikany JM, Hu M, Chen A, Reges O, Carnethon MR, Lloyd-Jones DM, Zhang K, Hou L. Associations of Urban Blue and Green Spaces With Coronary Artery Calcification in Black Individuals and Disadvantaged Neighborhoods. Circulation 2024; 150:203-214. [PMID: 38934130 PMCID: PMC11250927 DOI: 10.1161/circulationaha.123.067992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 06/07/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Proximity to urban blue and green spaces has been associated with improved cardiovascular health; however, few studies have examined the role of race and socioeconomic status in these associations. METHODS Data were from the CARDIA study (Coronary Artery Risk Development in Young Adults). We included longitudinal measurements (1985-1986 to 2010-2011) of blue and green spaces, including percentage of blue space cover, distance to the nearest river, green space cover, and distance to the nearest major park. Presence of coronary artery calcification (CAC) was measured with noncontrast cardiac computed tomography in 2010 to 2011. The associations of blue and green spaces with CAC were assessed with generalized estimating equation regression with adjustment for demographics, individual and neighborhood socioeconomic status, health-related behaviors, and other health conditions. We conducted stratified analyses by race and neighborhood deprivation score to investigate whether the association varied according to social determinants of health. RESULTS The analytic sample included 1365 Black and 1555 White participants with a mean±SD age of 50.1±3.6 years. Among Black participants, shorter distance to a river and greater green space cover were associated with lower odds of CAC (per interquartile range decrease [1.45 km] to the river: odds ratio [OR], 0.90 [95% CI, 0.84-0.96]; per 10 percentage-point increase of green space cover: OR, 0.85 [95% CI, 0.75-0.95]). Among participants in deprived neighborhoods, greater green space cover was associated with lower odds of CAC (per a 10 percentage-point increase: OR, 0.89 [95% CI, 0.80-0.99]), whereas shorter distance to the park was associated with higher odds of CAC (per an interquartile range decrease [5.3 km]: OR, 1.07 [95% CI, 1.00-1.15]). Black participants in deprived neighborhoods had lower odds of CAC with shorter distance to a river (per an interquartile range decrease: OR, 0.90 [95% CI, 0.82-0.98]) and greater green space cover (per a 10 percentage-point increase: OR, 0.85 [95% CI, 0.75-0.97]). There was no statistical interaction between the blue and green spaces and race or neighborhood characteristics in association with CAC. CONCLUSIONS Longitudinally, shorter distance to a river and greater green space cover were associated with less CAC among Black participants and those in deprived neighborhoods. Shorter distance to a park was associated with increased odds of CAC among participants in deprived neighborhoods. Black participants residing in more deprived neighborhoods showed lower odds of CAC in association with greater exposure to river and green space cover.
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Affiliation(s)
- Kyeezu Kim
- Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon-si, Gyeonggi-do, South Korea
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Brian T. Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Drew R. Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ankeet Bhatt
- Kaiser Permanente San Francisco Medical Center, Kaiser Permanente Northern California Division of Research, San Francisco, CA, USA
| | - Kelley Gabriel
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - James M. Shikany
- Division of Preventive Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ming Hu
- School of Architecture, University of Notre Dame, Notre Dame, IN, USA
| | - Aimin Chen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Orna Reges
- Department of Health Systems Management, Ariel University, Israel
| | - Mercedes R. Carnethon
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kai Zhang
- Department of Environmental Health Sciences, University of Albany, State University of New York, Rensselaer, NY, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Pu F, Chen W, Li C, Fu J, Gao W, Ma C, Cao X, Zhang L, Hao M, Zhou J, Huang R, Ma Y, Hu K, Liu Z. Heterogeneous associations of multiplexed environmental factors and multidimensional aging metrics. Nat Commun 2024; 15:4921. [PMID: 38858361 PMCID: PMC11164970 DOI: 10.1038/s41467-024-49283-0] [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: 10/24/2023] [Accepted: 05/31/2024] [Indexed: 06/12/2024] Open
Abstract
Complicated associations between multiplexed environmental factors and aging are poorly understood. We manipulated aging using multidimensional metrics such as phenotypic age, brain age, and brain volumes in the UK Biobank. Weighted quantile sum regression was used to examine the relative individual contributions of multiplexed environmental factors to aging, and self-organizing maps (SOMs) were used to examine joint effects. Air pollution presented a relatively large contribution in most cases. We also found fair heterogeneities in which the same environmental factor contributed inconsistently to different aging metrics. Particulate matter contributed the most to variance in aging, while noise and green space showed considerable contribution to brain volumes. SOM identified five subpopulations with distinct environmental exposure patterns and the air pollution subpopulation had the worst aging status. This study reveals the heterogeneous associations of multiplexed environmental factors with multidimensional aging metrics and serves as a proof of concept when analyzing multifactors and multiple outcomes.
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Affiliation(s)
- Fan Pu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Weiran Chen
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Chenxi Li
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Jingqiao Fu
- Ocean College, Zhejiang University, Zhoushan, 316021, Zhejiang, China
| | - Weijing Gao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Chao Ma
- School of Economics and Management, Southeast University, Nanjing, 211189, Jiangsu, China
| | - Xingqi Cao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Lingzhi Zhang
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Meng Hao
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, 200433, China
| | - Jin Zhou
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University; Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China
| | - Rong Huang
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University; Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China
| | - Yanan Ma
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University; Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China.
| | - Kejia Hu
- Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China.
| | - Zuyun Liu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China.
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Yang Z, Liao J, Zhang Y, Lin Y, Ge Y, Chen W, Qiu C, Berhane K, Bai Z, Han B, Xu J, Jiang YH, Gilliland F, Yan W, Chen Z, Huang G, Zhang J(J. Critical windows of greenness exposure during preconception and gestational periods in association with birthweight outcomes. ENVIRONMENTAL RESEARCH, HEALTH : ERH 2024; 2:015001. [PMID: 38022394 PMCID: PMC10647935 DOI: 10.1088/2752-5309/ad0aa6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 10/26/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023]
Abstract
Few studies have examined the association between greenness exposure and birth outcomes. This study aims to identify critical exposure time windows during preconception and pregnancy for the association between greenness exposure and birth weight. A cohort of 13 890 pregnant women and newborns in Shanghai, China from 2016-2019 were included in the study. We assessed greenness exposure using Normalized Difference Vegetation Index (NDVI) during the preconception and gestational periods, and evaluated the association with term birthweight, birthweight z-score, small-for-gestational age, and large-for-gestational age using linear and logistic regressions adjusting for key maternal and newborn covariates. Ambient temperature, relative humidity, ambient levels of fine particles (PM2.5) and nitrogen dioxide (NO2) assessed during the same period were adjusted for as sensitivity analyses. Furthermore, we explored the potential different effects by urbanicity and park accessibility through stratified analysis. We found that higher greenness exposure at the second trimester of pregnancy and averaged exposure during the entire pregnancy were associated with higher birthweight and birthweight Z-score. Specifically, a 0.1 unit increase in second trimester averaged NDVI value was associated with an increase in birthweight of 10.2 g (95% CI: 1.8-18.5 g) and in birthweight Z-score of 0.024 (0.003-0.045). A 0.1 unit increase in an averaged NDVI during the entire pregnancy was associated with 10.1 g (95% CI: 1.0-19.2 g) increase in birthweight and 0.025 (0.001-0.048) increase in birthweight Z-score. Moreover, the associations were larger in effect size among urban residents than suburban residents and among residents without park accessibility within 500 m compared to those with park accessibility within 500 m. Our findings suggest that increased greenness exposure, particularly during the second trimester, may be beneficial to birth weight in a metropolitan area.
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Affiliation(s)
- Zhenchun Yang
- Duke Global Health Institute, Duke University, Durham, NC, United States of America
| | - Jiawen Liao
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Yi Zhang
- Children’s Hospital of Fudan University, Shanghai Key Laboratory of Birth Defect, Shanghai, People’s Republic of China
| | - Yan Lin
- Duke Global Health Institute, Duke University, Durham, NC, United States of America
| | - Yihui Ge
- Duke Global Health Institute, Duke University, Durham, NC, United States of America
| | - Wu Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Chenyu Qiu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Kiros Berhane
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States of America
| | - Zhipeng Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, People’s Republic of China
| | - Bin Han
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, People’s Republic of China
| | - Jia Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, People’s Republic of China
| | - Yong Hui Jiang
- Department of Genetics, Neuroscience, and Pediatrics, Yale University School of Medicine, New Haven, CT, United States of America
| | - Frank Gilliland
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Weili Yan
- Children’s Hospital of Fudan University, Shanghai Key Laboratory of Birth Defect, Shanghai, People’s Republic of China
| | - Zhanghua Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States of America
| | - Guoying Huang
- Children’s Hospital of Fudan University, Shanghai Key Laboratory of Birth Defect, Shanghai, People’s Republic of China
| | - Junfeng (Jim) Zhang
- Duke Global Health Institute, Duke University, Durham, NC, United States of America
- Division of Environmental Science and Policy, Nicholas School of the Environment, Duke University, Durham, NC, United States of America
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Xu X, Xu T, Wei J, Chen T. Gut microbiota: an ideal biomarker and intervention strategy for aging. MICROBIOME RESEARCH REPORTS 2024; 3:13. [PMID: 38841415 PMCID: PMC11149087 DOI: 10.20517/mrr.2023.68] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 12/15/2023] [Indexed: 06/07/2024]
Abstract
Population aging is a substantial challenge for the global sanitation framework. Unhealthy aging tends to be accompanied by chronic diseases such as cardiovascular disease, diabetes, and cancer, which undermine the welfare of the elderly. Based on the fact that aging is inevitable but retarding aging is attainable, flexible aging characterization and efficient anti-aging become imperative for healthy aging. The gut microbiome, as the most dynamic component interacting with the organism, can affect the aging process through its own structure and metabolites, thus holding the potential to become both an ideal aging-related biomarker and an intervention strategy. This review summarizes the value of applying gut microbiota as aging-related microbial biomarkers in diagnosing aging state and monitoring the effect of anti-aging interventions, ultimately pointing to the future prospects of microbial intervention strategies in maintaining healthy aging.
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Affiliation(s)
- Xuan Xu
- Institution of Translational Medicine, Jiangxi Medical College, Nanchang University, Nanchang 330031, Jiangxi, China
- Huankui Academy, Jiangxi Medical College, Nanchang University, Nanchang 330031, Jiangxi, China
- Authors contributed equally
| | - Tangchang Xu
- Institution of Translational Medicine, Jiangxi Medical College, Nanchang University, Nanchang 330031, Jiangxi, China
- Authors contributed equally
| | - Jing Wei
- Institution of Translational Medicine, Jiangxi Medical College, Nanchang University, Nanchang 330031, Jiangxi, China
| | - Tingtao Chen
- Institution of Translational Medicine, Jiangxi Medical College, Nanchang University, Nanchang 330031, Jiangxi, China
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Jackson P, Kempf MC, Goodin BR, A. Hidalgo B, Aroke EN. Neighborhood Environment and Epigenetic Age: A Scoping Review. West J Nurs Res 2023; 45:1139-1149. [PMID: 37902222 PMCID: PMC10748459 DOI: 10.1177/01939459231208304] [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] [Indexed: 10/31/2023]
Abstract
BACKGROUND Interest in how the neighborhood environment impacts age-related health conditions has been increasing for decades. Epigenetic changes are environmentally derived modifications to the genome that alter the way genes function-thus altering health status. Epigenetic age, a biomarker for biological age, has been shown to be a useful predictor of several age-related health conditions. Consequently, its relation to the neighborhood environment has been the focus of a growing body of literature. OBJECTIVE We aimed to describe the scope of the evidence on the relationship between neighborhood environmental characteristics and epigenetic age. METHODS Using scoping review following methods established by Arksey and O'Malley, we first defined our research questions and searched the literature in PubMed, PsycINFO, and EMBASE. Next, we selected the literature to be included, and finally, we analyzed and summarized the information. RESULTS Nine articles met the inclusion criteria. Most studies examined deprivation as the neighborhood characteristic of interest. While all studies were observational in design, the articles included diverse participants, including men and women, adults and children, and multiple ethnicities. Results demonstrated a relationship between the neighborhood environment and epigenetic age, whether the characteristic of interest is socioeconomic or physical. CONCLUSIONS Overall, studies concluded there was a relationship between neighborhood characteristics and epigenetic age, whether the characteristic of interest was socioeconomic or physical. However, findings varied based on how the neighborhood characteristic and/or epigenetic age was measured. Furthermore, a paucity of investigations on physical characteristics was noticeable and warrants increased attention.
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Affiliation(s)
- Pamela Jackson
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Burel R. Goodin
- Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Bertha A. Hidalgo
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Edwin N. Aroke
- School of Nursing, University of Alabama at Birmingham, Birmingham, AL, USA
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7
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Belsky DW, Baccarelli AA. To promote healthy aging, focus on the environment. NATURE AGING 2023; 3:1334-1344. [PMID: 37946045 DOI: 10.1038/s43587-023-00518-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 09/27/2023] [Indexed: 11/12/2023]
Abstract
To build health equity for an aging world marked by dramatic disparities in healthy lifespan between countries, regions and population groups, research at the intersections of biology, toxicology and the social and behavioral sciences points the way: to promote healthy aging, focus on the environment. In this Perspective, we suggest that ideas and tools from the emerging field of geroscience offer opportunities to advance the environmental science of aging. Specifically, the capacity to measure the pace and progress of biological processes of aging within individuals from relatively young ages makes it possible to study how changing environments can change aging trajectories from early in life, in time to prevent or delay aging-related disease and disability and build aging health equity.
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Affiliation(s)
- Daniel W Belsky
- Robert N. Butler Columbia Aging Center and Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Andrea A Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
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8
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Ni W, Nikolaou N, Ward-Caviness CK, Breitner S, Wolf K, Zhang S, Wilson R, Waldenberger M, Peters A, Schneider A. Associations between medium- and long-term exposure to air temperature and epigenetic age acceleration. ENVIRONMENT INTERNATIONAL 2023; 178:108109. [PMID: 37517177 PMCID: PMC10656697 DOI: 10.1016/j.envint.2023.108109] [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: 03/06/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 08/01/2023]
Abstract
Climate change poses a serious threat to human health worldwide, while aging populations increase. However, no study has ever investigated the effects of air temperature on epigenetic age acceleration. This study involved 1,725 and 1,877 participants from the population-based KORA F4 (2006-2008) and follow-up FF4 (2013-2014) studies, respectively, conducted in Augsburg, Germany. The difference between epigenetic age and chronological age was referred to as epigenetic age acceleration and reflected by Horvath's epigenetic age acceleration (HorvathAA), Hannum's epigenetic age acceleration (HannumAA), PhenoAge acceleration (PhenoAA), GrimAge acceleration (GrimAA), and Epigenetic Skin and Blood Age acceleration (SkinBloodAA). Daily air temperature was estimated using hybrid spatiotemporal regression-based models. To explore the medium- and long-term effects of air temperature modeled in time and space on epigenetic age acceleration, we applied generalized estimating equations (GEE) with distributed lag non-linear models, and GEE, respectively. We found that high temperature exposure based on the 8-week moving average air temperature (97.5th percentile of temperature compared to median temperature) was associated with increased HorvathAA, HannumAA, GrimAA, and SkinBloodAA: 1.83 (95% CI: 0.29-3.37), 11.71 (95% CI: 8.91-14.50), 2.26 (95% CI: 1.03-3.50), and 5.02 (95% CI: 3.42-6.63) years, respectively. Additionally, we found consistent results with high temperature exposure based on the 4-week moving average air temperature was associated with increased HannumAA, GrimAA, and SkinBloodAA: 9.18 (95% CI: 6.60-11.76), 1.78 (95% CI: 0.66-2.90), and 4.07 (95% CI: 2.56-5.57) years, respectively. For the spatial variation in annual average temperature, a 1 °C increase was associated with an increase in all five measures of epigenetic age acceleration (HorvathAA: 0.41 [95% CI: 0.24-0.57], HannumAA: 2.24 [95% CI: 1.95-2.53], PhenoAA: 0.32 [95% CI: 0.05-0.60], GrimAA: 0.24 [95%: 0.11-0.37], and SkinBloodAA: 1.17 [95% CI: 1.00-1.35] years). In conclusion, our results provide first evidence that medium- and long-term exposures to high air temperature affect increases in epigenetic age acceleration.
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Affiliation(s)
- Wenli Ni
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
| | - Nikolaos Nikolaou
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC, USA
| | - Susanne Breitner
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany
| | - Siqi Zhang
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany
| | - Rory Wilson
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany; German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Alexandra Schneider
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, Neuherberg, Germany
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Kim K, Joyce BT, Nannini DR, Zheng Y, Gordon-Larsen P, Shikany JM, Lloyd-Jones DM, Hu M, Nieuwenhuijsen MJ, Vaughan DE, Zhang K, Hou L. Inequalities in urban greenness and epigenetic aging: Different associations by race and neighborhood socioeconomic status. SCIENCE ADVANCES 2023; 9:eadf8140. [PMID: 37379393 PMCID: PMC10306284 DOI: 10.1126/sciadv.adf8140] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 05/24/2023] [Indexed: 06/30/2023]
Abstract
Slower epigenetic aging is associated with exposure to green space (greenness); however, the longitudinal relationship has not been well studied, particularly in minority groups. We investigated the association between 20-year exposure to greenness [Normalized Difference Vegetation Index (NDVI)] and epigenetic aging in a large, biracial (Black/white), U.S. urban cohort. Using generalized estimating equations adjusted for individual and neighborhood socioeconomic characteristics, greater greenness was associated with slower epigenetic aging. Black participants had less surrounding greenness and an attenuated association between greenness and epigenetic aging [βNDVI5km: -0.80, 95% confidence interval (CI): -4.75, 3.13 versus βNDVI5km: -3.03, 95% CI: -5.63, -0.43 in white participants]. Participants in disadvantaged neighborhoods showed a stronger association between greenness and epigenetic aging (βNDVI5km: -3.36, 95% CI: -6.65, -0.08 versus βNDVI5km: -1.57, 95% CI: -4.12, 0.96 in less disadvantaged). In conclusion, we found a relationship between greenness and slower epigenetic aging, and different associations by social determinants of health such as race and neighborhood socioeconomic status.
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Affiliation(s)
- Kyeezu Kim
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Brian T. Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Drew R. Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - James M. Shikany
- Division of Preventive Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Donald M. Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Ming Hu
- School of Architecture, University of Notre Dame, Notre Dame, IN, USA
| | - Mark J. Nieuwenhuijsen
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Douglas E. Vaughan
- Department of Medicine, Northwestern Feinberg School of Medicine, Chicago, IL, USA
- Potocsnak Longevity Institute, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Kai Zhang
- Department of Environmental Health Sciences, University of Albany, State University of New York, Rensselaer, NY, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Potocsnak Longevity Institute, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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10
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Sikarwar A, Rani R, Duthé G, Golaz V. Association of greenness with COVID-19 deaths in India: An ecological study at district level. ENVIRONMENTAL RESEARCH 2023; 217:114906. [PMID: 36423668 PMCID: PMC9678392 DOI: 10.1016/j.envres.2022.114906] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND The world has witnessed a colossal death toll due to the novel coronavirus disease-2019 (COVID-19). A few environmental epidemiology studies have identified association of environmental factors (air pollution, greenness, temperature, etc.) with COVID-19 incidence and mortality, particularly in developed countries. India, being one of the most severely affected countries by the pandemic, still has a dearth of research exploring the linkages of environment and COVID-19 pandemic. OBJECTIVES We evaluate whether district-level greenness exposure is associated with a reduced risk of COVID-19 deaths in India. METHODS We used average normalized difference vegetation index (NDVI) from January to March 2019, derived by Oceansat-2 satellite, to represent district-level greenness exposure. COVID-19 death counts were obtained through May 1, 2021 (around the peak of the second wave) from an open portal: covid19india.org. We used hierarchical generalized negative binomial regressions to check the associations of greenness with COVID-19 death counts. Analyses were adjusted for air pollution (PM2.5), temperature, rainfall, population density, proportion of older adults (50 years and above), sex ratio over age 50, proportions of rural population, household overcrowding, materially deprived households, health facilities, and secondary school education. RESULTS Our analyses found a significant association between greenness and reduced risk of COVID-19 deaths. Compared to the districts with the lowest NDVI (quintile 1), districts within quintiles 3, 4, and 5 have respectively, around 32% [MRR = 0.68 (95% CI: 0.51, 0.88)], 39% [MRR = 0.61 (95% CI: 0.46, 0.80)], and 47% [MRR = 0.53 (95% CI: 0.40, 0.71)] reduced risk of COVID-19 deaths. The association remains consistent for analyses restricted to districts with a rather good overall death registration (>80%). CONCLUSION Though cause-of-death statistics are limited, we confirm that exposure to greenness was associated with reduced district-level COVID-19 deaths in India. However, material deprivation and air pollution modify this association.
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Affiliation(s)
- Ankit Sikarwar
- French Institute for Demographic Studies (INED), Aubervilliers-Paris, France.
| | - Ritu Rani
- French Institute for Demographic Studies (INED), Aubervilliers-Paris, France; International Institute for Population Sciences, Mumbai, India
| | - Géraldine Duthé
- French Institute for Demographic Studies (INED), Aubervilliers-Paris, France
| | - Valérie Golaz
- French Institute for Demographic Studies (INED), Aubervilliers-Paris, France; Aix-Marseille University, IRD, LPED, Marseille, France
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11
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Wu Y, Xu R, Li S, Ming Wong E, Southey MC, Hopper JL, Abramson MJ, Li S, Guo Y. Epigenome-wide association study of short-term temperature fluctuations based on within-sibship analyses in Australian females. ENVIRONMENT INTERNATIONAL 2023; 171:107655. [PMID: 36476687 DOI: 10.1016/j.envint.2022.107655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 08/26/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation. METHODS Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant's home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0-1 to TV 0-7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied. RESULTS Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0-3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0-3). CONCLUSIONS Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.
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Affiliation(s)
- Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3010, Australia; Cancer Epidemiology Division, Cancer Council Victoria, VIC 3004, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Michael J Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Shuai Li
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC 3052, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
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12
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Xu R, Li S, Wu Y, Yue X, Wong EM, Southey MC, Hopper JL, Abramson MJ, Li S, Guo Y. Wildfire-related PM 2.5 and DNA methylation: An Australian twin and family study. ENVIRONMENT INTERNATIONAL 2023; 171:107704. [PMID: 36542997 DOI: 10.1016/j.envint.2022.107704] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 11/24/2022] [Accepted: 12/16/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Wildfire-related fine particulate matter (PM2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM2.5. METHODS We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. RESULTS The 3-year average wildfire-related PM2.5 (range: 0.3 to 7.6 µg/m3, mean: 1.6 µg/m3) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM2.5. CONCLUSIONS Long-term exposure to wildfire-related PM2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM2.5.
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Affiliation(s)
- Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Shanshan Li
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Xu Yue
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
| | - Ee Ming Wong
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia; Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Melbourne, VIC 3010, Australia; Cancer Epidemiology Division, Cancer Council Victoria, VIC 3004, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Michael J Abramson
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Shuai Li
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3800, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, VIC 3052, Australia
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia.
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13
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Greenspace and mortality in the U.K. Biobank: Longitudinal cohort analysis of socio-economic, environmental, and biomarker pathways. SSM Popul Health 2022; 19:101194. [PMID: 36059376 PMCID: PMC9429791 DOI: 10.1016/j.ssmph.2022.101194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 07/06/2022] [Accepted: 07/29/2022] [Indexed: 11/24/2022] Open
Abstract
Exposure to natural greenspace benefits health through direct and indirect pathways: increasing physical activity, improving mental health, relieving social isolation, reducing exposure to extreme temperature, noise, and air pollution. Understanding the etiologic pathway of greenspace and health is needed. Here, we used a large cohort follow-up data from the U.K. Biobank to quantify the magnitude of behavioural factors, psychological factors, biomarkers/physiological measurements, co-morbid diseases, and environmental exposure as potential mediators in the relationship between greenspace and mortality. We estimated hazard ratios (HR) with Cox proportional hazards models, and undertook exploratory mediation analyses to quantify the relative contribution of five types of mediators. Our results indicate greenspace was strongly associated with lower mortality risks [per IQR of public greenspace (HR = 0.90 (95% CI 0.86-0.84)) and domestic gardens (HR = 0.91, (95% CI 0.88-0.94))]. The protective associations were especially pronounced among those with lower individual-level socioeconomic status or living in places with area-level deprivation. Exploratory mediation analysis detected benefits in pathways through reducing air pollution, relieving social isolation and depression, increased physical activity and time spent outdoor, better lung function (FEV1/FVC), and having higher serum vitamin D levels.
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14
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Zhao Q, Yu P, Mahendran R, Huang W, Gao Y, Yang Z, Ye T, Wen B, Wu Y, Li S, Guo Y. Global climate change and human health: Pathways and possible solutions. ECO-ENVIRONMENT & HEALTH (ONLINE) 2022; 1:53-62. [PMID: 38075529 PMCID: PMC10702927 DOI: 10.1016/j.eehl.2022.04.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/13/2022] [Accepted: 04/28/2022] [Indexed: 12/13/2023]
Abstract
Global warming has been changing the planet's climate pattern, leading to increasing frequency, intensity and duration of extreme weather events and natural disasters. These climate-changing events affect various health outcomes adversely through complicated pathways. This paper reviews the main signs of climate change so far, e.g., suboptimal ambient temperature, sea-level rise and other conditions, and depicts the interactive pathways between different climate-changing events such as suboptimal temperature, wildfires, and floods with a broad range of health outcomes. Meanwhile, the modifying effect of socioeconomic, demographic and environmental factors on the pathways is summarised, such that the youth, elderly, females, poor and those living in coastal regions are particularly susceptible to climate change. Although Earth as a whole is expected to suffer from climate change, this review article discusses some potential benefits for certain regions, e.g., a more liveable environment and sufficient food supply. Finally, we summarise certain mitigation and adaptation strategies against climate change and how these strategies may benefit human health in other ways. This review article provides a comprehensive and concise introduction of the pathways between climate change and human health and possible solutions, which may map directions for future research.
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Affiliation(s)
- Qi Zhao
- Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Pei Yu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Rahini Mahendran
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Wenzhong Huang
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Yuan Gao
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Zhengyu Yang
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Tingting Ye
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Bo Wen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Yao Wu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Shanshan Li
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
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15
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Health Effects of Long-Term Exposure to Ambient PM 2.5 in Asia-Pacific: a Systematic Review of Cohort Studies. Curr Environ Health Rep 2022; 9:130-151. [PMID: 35292927 PMCID: PMC9090712 DOI: 10.1007/s40572-022-00344-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/10/2022] [Indexed: 12/21/2022]
Abstract
Abstract Purpose of Review Health effects of long-term exposure to ambient PM2.5 vary with regions, and 75% of the deaths attributable to PM2.5 were estimated in Asia-Pacific in 2017. This systematic review aims to summarize the existing evidence from cohort studies on health effects of long-term exposure to ambient PM2.5 in Asia-Pacific. Recent Findings In Asia-Pacific, 60 cohort studies were conducted in Australia, Mainland China, Hong Kong, Taiwan, and South Korea. They consistently supported associations of long-term exposure to PM2.5 with increased all-cause/non-accidental and cardiovascular mortality as well as with incidence of cardiovascular diseases, type 2 diabetes mellitus, kidney diseases, and chronic obstructive pulmonary disease. Evidence for other health effects was limited. Inequalities were identified in PM2.5-health associations. Summary To optimize air pollution control and public health prevention, further studies need to assess the health effects of long-term PM2.5 exposure in understudied regions, the health effects of long-term PM2.5 exposure on mortality and risk of type 2 diabetes mellitus, renal diseases, dementia and lung cancer, and inequalities in PM2.5-health associations. Study design, especially exposure assessment methods, should be improved. Supplementary Information The online version contains supplementary material available at 10.1007/s40572-022-00344-w.
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