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Ogurtsova K, Christensen GM, Soppa VJ, Jokisch M, Tzivian L, Weimar C, Dragano N, Schmidt B, Hüls A, Hoffmann B. Joint effects of environmental and neighborhood socioeconomic factors on cognitive function in the Heinz Nixdorf Recall Study. ENVIRONMENTAL RESEARCH 2025; 279:121830. [PMID: 40368041 DOI: 10.1016/j.envres.2025.121830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2025] [Revised: 04/25/2025] [Accepted: 05/10/2025] [Indexed: 05/16/2025]
Abstract
BACKGROUND Modifiable physical and social environments are believed to influence cognitive health in older age. OBJECTIVES To employ cutting-edge methods to analyze the impact of correlated environmental and socioeconomic neighborhood factors on cognitive function in German older participants. METHODS In the German Heinz Nixdorf Recall cohort study, participants underwent neuropsychological testing at the first follow-up examination (2006-2008) to derive a global cognitive score (GCS). Long-term exposure to air pollution was estimated by the land-use regression and chemistry transport models. Road traffic noise was assessed as outdoor weighted 24h and nighttime means. Seven neighborhood-level socioeconomic position (nSEP) characteristics were linked from administrative data. The joint effects of exposure combinations on GCS were estimated using two dimensionality reduction techniques: principal component (PC) analysis (PCA) and self-organizing maps (SOM). RESULTS Overall, 3748 individuals were included (median age 65 years; 50.7 % female). In single-exposure linear regression analysis, higher particle matter with aerodynamic diameter ≤2.5 μm (PM2.5) and nitrogen oxides exposure, higher proportion of welfare recipients, and lower living area per resident were negatively associated with GCS. In the PCA, the first principal component (PC), the direction of maximum variance, was positively correlated with all disadvantageous nSEP factors and higher concentrations of all environmental exposures except ozone. This PC was associated with lower GCS. SOM revealed associations with lower GCS for 3 of 6 exposure clusters. These clusters were characterized by low nSEP (Cluster 1), high environmental exposure (Cluster 4) and high concentration of accumulation mode particle number concentration (Cluster 5). DISCUSSION We identified associations between distinct combinations of intercorrelated air pollution, road traffic noise, and nSEP disadvantages with poorer cognitive function, using two different dimensionality reduction methods. Our findings highlight the importance of considering combined environmental and social exposures to systematically assess the potential benefits of multimodal urban interventions aimed at mitigating these risk factors.
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Affiliation(s)
- Katherine Ogurtsova
- Institute of Occupational, Social and Environmental Medicine, Center for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany.
| | - Grace M Christensen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Vanessa J Soppa
- Institute of Occupational, Social and Environmental Medicine, Center for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany
| | - Martha Jokisch
- University Medical Center Essen, Department of Neurology, Essen, Germany
| | - Lilian Tzivian
- Institute of Occupational, Social and Environmental Medicine, Center for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany; Institute of Clinical and Preventive Medicine, University of Latvia, Riga, Latvia
| | - Christian Weimar
- Institute of Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, University of Duisburg-Essen, Essen, Germany; BDH Clinic Elzach, Germany
| | - Nico Dragano
- Institute of Medical Sociology, Centre for Health and Society, University Hospital and Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Börge Schmidt
- Institute of Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Barbara Hoffmann
- Institute of Occupational, Social and Environmental Medicine, Center for Health and Society, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany
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Dalecká A, Kšiňan A, Szabó D, Čapková N, Pikhart H, Bobák M. Neighborhood environment and cognitive functioning in middle-aged and older population: A mediating role of physical activity. Int J Hyg Environ Health 2025; 264:114521. [PMID: 39808871 DOI: 10.1016/j.ijheh.2025.114521] [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: 10/01/2024] [Revised: 12/17/2024] [Accepted: 01/08/2025] [Indexed: 01/16/2025]
Abstract
BACKGROUND Evidence on the impact of complex neighborhood environment, including air pollution, greenness, and neighborhood socioeconomic deprivation (nSED) on cognitive health in older adults remains scarce. Both cognition and neighborhood environment are associated with physical activity, but little is known about the potential mediating role of physical activity in this association. METHODS Cross-sectional data of the Czech arm of the HAPIEE cohort study examined 4,178 participants (55.6% women) aged 45-69 years. Global cognitive score was constructed from memory, verbal fluency, and concentration domains. The exposures, assigned to participant's addresses, include 4-year (2000-2003) average concentrations of PM2.5, greenness index calculated from tree crown canopy cover estimation (2000), and census-based nSED characteristics. Physical activity and other covariates were assessed by a questionnaire. Structural equation modelling was used to estimate standardized β coefficients for the relationships between neighborhood environment, physical activity and cognitive performance. RESULTS After controlling for a range of covariates, global cognitive function was inversely associated with PM2.5 (β = -0.087; 95%CI: 0.122 to -0.052) and nSED (β = -0.147; 95%CI: 0.182 to -0.115), and positively associated with greenness (β = 0.036; 95%CI: 0.001 to 0.069). We identified a weak but statistically significant mediating role of physical activity in the associations of PM2.5 exposures and nSED on global cognitive score. Total mediation proportions ranged from 3.9% to 6.5% for nSED and PM2.5, respectively. CONCLUSIONS The neighborhood environment was associated with cognitive health in older individuals; the associations were partially mediated by physical activity.
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Affiliation(s)
- A Dalecká
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - A Kšiňan
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - D Szabó
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic
| | - N Čapková
- National Institute of Public Health, Prague, Czech Republic
| | - H Pikhart
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic; Institute of Epidemiology & Health Care, University College London, London, United Kingdom
| | - M Bobák
- RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic; Institute of Epidemiology & Health Care, University College London, London, United Kingdom.
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Ku BS, Yuan QE, Christensen G, Dimitrov LV, Risk B, Huels A. Exposure profiles of social-environmental neighborhood factors and persistent distressing psychotic-like experiences across four years among young adolescents in the US. Psychol Med 2025; 55:e53. [PMID: 39957496 PMCID: PMC11948089 DOI: 10.1017/s0033291725000224] [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] [Indexed: 02/18/2025]
Abstract
BACKGROUND Recent research has demonstrated that domains of social determinants of health (SDOH) (e.g. air pollution and social context) are associated with psychosis. However, SDOHs have often been studied in isolation. This study investigated distinct exposure profiles, estimated their associations with persistent distressing psychotic-like experiences (PLE), and evaluated whether involvement in physical activity partially explains this association. METHODS Analyses included 8,145 young adolescents from the Adolescent Brain and Cognitive Development Study. Data from the baseline and three follow-ups were included. Area-level geocoded variables spanning various domains of SDOH, including socioeconomic status, education, crime, built environment, social context, and crime, were clustered using a self-organizing map method to identify exposure profiles. Generalized linear mixed modeling tested the association between exposure profiles and persistent distressing PLE and physical activities (i.e. team and individual sports), adjusting for individual-level covariates including age, sex, race/ethnicity, highest level of parent education, family-relatedness, and study sites. RESULTS Five exposure profiles were identified. Compared to the reference Profile 1 (suburban affluent areas), Profile 3 (rural areas with low walkability and high ozone), and Profile 4 (urban areas with high SES deprivation, high crime, and high pollution) were associated with greater persistent distressing PLE. Team sports mediated 6.14% of the association for Profile 3. CONCLUSIONS This study found that neighborhoods characterized by rural areas with low walkability and urban areas with high socioeconomic deprivation, pollution concentrations, and crime were associated with persistent distressing PLE. Findings suggest that various social-environmental factors may differentially impact the development of psychosis.
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Affiliation(s)
- Benson S. Ku
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Qingyue E. Yuan
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Grace Christensen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Lina V. Dimitrov
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Benjamin Risk
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Anke Huels
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
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Wu J, Yin B, Wen R, Pei H, Zhu S, Zhao J, Li Y, Yang M, Hu Y, Xu Q, Li A, Ma Y. A systematic exposure-wide framework leveraging machine learning to identify multidomain exposure factors and their joint influence on cognitive function: Evidence from a neurological cohort. Alzheimers Dement 2025; 21:e14624. [PMID: 39998468 PMCID: PMC11853734 DOI: 10.1002/alz.14624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2024] [Revised: 01/17/2025] [Accepted: 01/17/2025] [Indexed: 02/26/2025]
Abstract
INTRODUCTION Cognitive decline has become a growing public concern, yet large-scale exposure data identifying the contributing factors remain limited. METHODS We conducted an exposure-wide association study involving 1142 participants and 207 exposures, using machine learning to assess the relative contribution and joint effects of key factors. Cluster analysis and intervention simulation trials helped identify high-risk subpopulations and the potential benefits of targeted interventions. RESULTS In adjusted mixed models, the socioeconomic status domain emerged as the strongest predictor of longitudinal global cognitive score (β = 2.91, p < 0.0001, q < 0.0001), while the dietary domain also played an important role in memory function. The cluster analysis found that the "unfavorable lifestyle" dominated phenotype was associated with the poorest cognitive outcomes. Simulation trials indicated that cognitive scores could improve by shifting individuals from unfavorable to favorable phenotypes. DISCUSSION Cognitive health requires multidomain interventions, particularly in the socioeconomic and dietary fields, and necessitates collaboration between government and individuals. HIGHLIGHTS The exposure-wide association study design, which assesses a broad range of exposures, is used to identify novel variables and understand their contributions to cognitive function. The findings from the multidomain analysis indicate that socioeconomic status is the most significant contributor to global cognitive function, while diet plays the largest role in memory function. Increasing the proportion of favorable phenotypes through multidomain interventions can significantly enhance public cognitive health.
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Affiliation(s)
- Jingtao Wu
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
- Medical Center for Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina
| | - Bowen Yin
- Department of Nutrition and Food HygieneSchool of Public HealthHebei Medical UniversityHebei Key Laboratory of Environment and Human HealthShijiazhuangChina
| | - Rui Wen
- Department of Nutrition and Food HygieneSchool of Public HealthHebei Medical UniversityHebei Key Laboratory of Environment and Human HealthShijiazhuangChina
| | - Huanting Pei
- Department of Nutrition and Food HygieneSchool of Public HealthHebei Medical UniversityHebei Key Laboratory of Environment and Human HealthShijiazhuangChina
| | - Siqi Zhu
- Department of Nutrition and Food HygieneSchool of Public HealthHebei Medical UniversityHebei Key Laboratory of Environment and Human HealthShijiazhuangChina
| | - Jiaxin Zhao
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
| | - Yanbing Li
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
| | - Ming Yang
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
- Medical Center for Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina
| | - Yaoyu Hu
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
- Medical Center for Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina
| | - Qun Xu
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
- Medical Center for Rare DiseasesPeking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina
| | - Ang Li
- Department of Epidemiology and BiostatisticsInstitute of Basic Medical Sciences Chinese Academy of Medical SciencesSchool of Basic Medicine Peking Union Medical CollegeBeijingChina
- Center of Environmental and Health SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijingChina
| | - Yuxia Ma
- Department of Nutrition and Food HygieneSchool of Public HealthHebei Medical UniversityHebei Key Laboratory of Environment and Human HealthShijiazhuangChina
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Hu Z, Wu N, An S, Deng M, Tao L, Liao D, Yu R, Yang J, Xiao Y, Zheng X, Zeng R, Liu Y, Xiong S, Xie Y, Liu X, Shen X, Shang X, Li Q, Zhou Y. Effect of combined exposure to phthalates and polycyclic aromatic hydrocarbons during early pregnancy on gestational age and neonatal size: A prospective cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:116868. [PMID: 39146592 DOI: 10.1016/j.ecoenv.2024.116868] [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: 04/02/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 08/17/2024]
Abstract
Many studies have indicated that individual exposure to phthalates (PAEs) or polycyclic aromatic hydrocarbons (PAHs) affects pregnancy outcomes. However, combined exposure to PAEs and PAHs presents a more realistic situation, and research on the combined effects of PAEs and PAHs on gestational age and newborn size is still limited. This study aimed to assess the effects of combined exposure to PAEs and PAHs on neonatal gestational age and birth size. Levels of 9 PAE and 10 PAH metabolites were measured from the urine samples of 1030 women during early pregnancy from the Zunyi Birth Cohort in China. Various statistical models, including linear regression, restricted cubic spline, Bayesian kernel machine regression, and quantile g-computation, were used to study the individual effects, dose-response relationships, and combined effects, respectively. The results of this prospective study revealed that each ten-fold increase in the concentration of monoethyl phthalate (MEP), 2-hydroxynaphthalene (2-OHNap), 2-hydroxyphenanthrene (2-OHPhe), and 1-hydroxypyrene (1-OHPyr) decreased gestational age by 1.033 days (95 % CI: -1.748, -0.319), 0.647 days (95 % CI: -1.076, -0.219), 0.845 days (95 % CI: -1.430, -0.260), and 0.888 days (95 % CI: -1.398, -0.378), respectively. Moreover, when the concentrations of MEP, 2-OHNap, 2-OHPhe, and 1-OHPyr exceeded 0.528, 0.039, 0.012, and 0.002 µg/g Cr, respectively, gestational age decreased in a dose-response manner. Upon analyzing the selected PAE and PAH metabolites as a mixture, we found that they were significantly negatively associated with gestational age, birth weight, and the ponderal index, with 1-OHPyr being the most important contributor. These findings highlight the adverse effects of single and combined exposure to PAEs and PAHs on gestational age. Therefore, future longitudinal cohort studies with larger sample sizes should be conducted across different geographic regions and ethnic groups to confirm the impact of combined exposure to PAEs and PAHs on birth outcomes.
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Affiliation(s)
- Zhongmei Hu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Department of Obstetrics and Gynecology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China; Department of Reproductive Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Nian Wu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Songlin An
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Mingyu Deng
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Department of Obstetrics and Gynecology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Lin Tao
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Dengqing Liao
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Rui Yu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Jing Yang
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Yanling Xiao
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Xingting Zheng
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Rong Zeng
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Yijun Liu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Shimin Xiong
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Yan Xie
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Xingyan Liu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Xubo Shen
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Xuejun Shang
- Department of Andrology, School of Medicine, Jinling Hospital, Nanjing University, Nanjing 210002, China
| | - Quan Li
- Department of Obstetrics and Gynecology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China.
| | - Yuanzhong Zhou
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China.
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Ku B, Yuan Q, Christensen GM, Dimitrov L, Risk B, Huels A. Exposure profiles of social-environmental neighborhood factors and psychotic-like experiences. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.21.24312315. [PMID: 39228699 PMCID: PMC11370530 DOI: 10.1101/2024.08.21.24312315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Importance Recent research has demonstrated that domains of social determinants of health (SDOH) (e.g., air pollution and social context) are associated with psychosis. However, SDOHs have often been studied in isolation. Objective To identify distinct exposure profiles, estimate their associations with persistent distressing psychotic-like experiences (PLE), and evaluate whether involvement with physical activities partially explains this association. Design Setting and Participants This population-based study used data from the Adolescent Brain and Cognitive Development (ABCD) Study. Participants were recruited from 22 US sites between September 2016 and January 2022. Data from baseline and three follow-ups were included. Exposures Area-level geocoded variables spanning various domains of SDOH, including socioeconomic status (SES), education, crime, built environment, social context, and crime, were clustered using a self-organizing map method to identify exposure profiles. Main Outcomes and Measures Persistent distressing PLE was derived from the Prodromal Questionnaire-Brief Child Version across four years. Generalized linear mixed modeling tested the association between exposure profiles and persistent distressing PLE as well as physical activities (i.e., team and individual sports), adjusting for individual-level covariates including age, sex, race/ethnicity, highest level of parent education, family-relatedness, and study sites. Results Among 8,145 participants (baseline mean [SD] age, 9.92 [0.63] years; 3,868 (47.5%) females; 5,566 (68.3%) White, 956 (11.7%) Black, 159 (2.0%) Asian, and 1,480 (18.4%) Hispanic participants), five exposure profiles were identified. Compared to the reference Profile 1 (suburban affluent areas, 2521 children, 30.9%), Profile 3 (rural areas with low walkability and high ozone; 1459 children, 17.9%; adjusted OR: 1.34, 95% CI: 1.09-1.64) and Profile 4 (urban areas with high SES deprivation, high crime, and high pollution; 715 children, 8.8%; adjusted OR: 1.40, 95% CI: 1.08-1.81), were associated with persistent distressing PLE. Team sports mediated 6.14% of the association for Profile 3. Conclusion and Relevance This study found that neighborhoods characterized by rural areas with low walkability and urban areas with high socioeconomic deprivation, air pollutants, and crime were associated with persistent distressing PLE. Further research is needed to explore the pathways through which different environmental factors may impact the development of psychosis.
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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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Dong Y, Cao W, Wei J, Chen Y, Zhang Y, Sun S, Hu F, Cai Y. Health effect of multiple air pollutant mixture on sarcopenia among middle-aged and older adults in China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 281:116634. [PMID: 38925034 DOI: 10.1016/j.ecoenv.2024.116634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 06/12/2024] [Accepted: 06/21/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND As the global aging process accelerates, the health challenges posed by sarcopenia among middle-aged and older adults are becoming increasingly prominent. However, the available evidence on the adverse effects of air pollution on sarcopenia is limited, particularly in the Western Pacific region. This study aimed to explore relationships of multiple air pollutants with sarcopenia and related biomarkers using the nationally representative database. METHODS Totally, 6585 participants aged over 45 years were enrolled from the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and 3443 of them were followed up until 2015. Air pollutants were estimated from high-resolution satellite-based spatial-temporal models. In the cross-sectional analysis, we used generalized linear regression, unconditional logistic regression analytical and restricted cubic spline (RCS) methods to assess the single-exposure and non-linear effects of multiple air pollutants on sarcopenia and related surrogate biomarkers (serum creatinine and cystatin C). Several popular mixture analysis techniques such as Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quantile-based g-computation (Qgcomp) were further used to examinate the combined effects of multiple air pollutants. Logistic regression was used to further analyze the longitudinal association between air pollution and sarcopenia. RESULTS Each interquartile range increase in PM2.5, PM10 and NO2 was significantly associated with an increased risk of sarcopenia, with adjusted odds ratios (aORs) of 1.09 [95 % confidence interval (CI): 1.01, 1.20], 1.24 (95 % CI: 1.14, 1.35) and 1.18 (95 % CI: 1.08, 1.28), respectively. Our findings also showed that five air pollutants were significantly associated with the sarcopenia index. In addition, employing a mixture analysis approach, we confirmed significant combined effects of air pollution mixtures on sarcopenia risk and associated biomarkers, with PM10 and PM2.5 identified as major contributors to the combined effect. The results of the exposure-response (E-R) relationships, subgroup analysis, longitudinal analysis and sensitivity analysis all showed the unfavorable impact of air pollution on sarcopenia risk and related vulnerable populations. CONCLUSIONS Single-exposure and co-exposure to multiple air pollutants were positively associated with sarcopenia among middle-aged and older adults in China. Our study provided new evidence that air pollution mixture was significantly associated with sarcopenia related biomarkers.
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Affiliation(s)
- Yinqiao Dong
- Public Health Department, Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Wangnan Cao
- Department of Social Medicine and Health Education, School of Public Health, Peking University, Beijing, PR China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, MD, United States
| | - Yingjie Chen
- Public Health Department, Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Yinghuan Zhang
- Public Health Department, Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China; School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Shengzhi Sun
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Fan Hu
- Public Health Department, Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
| | - Yong Cai
- Public Health Department, Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China.
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Li S, Liu Y, Li R, Xiao W, Ou J, Tao F, Wan Y. Association between green space and multiple ambient air pollutants with depressive and anxiety symptoms among Chinese adolescents: The role of physical activity. ENVIRONMENT INTERNATIONAL 2024; 189:108796. [PMID: 38838489 DOI: 10.1016/j.envint.2024.108796] [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: 02/21/2024] [Revised: 05/31/2024] [Accepted: 05/31/2024] [Indexed: 06/07/2024]
Abstract
OBJECTIVE To explore the association between green space, multiple ambient air pollutants and depressive/anxiety symptoms and the mediating role of physical activity (PA) in Chinese adolescents. METHOD A school-based health survey was conducted in eight provinces in China in 2021. 22,868 students aged 14.64 (±1.77) years completed standard questionnaires to record details of depressive, anxiety symptoms and PA. We calculated the average normalized difference vegetation index (NDVI) in circular buffers of 200 m, 500 m and 1000 m and estimated the concentrations of PM10, PM2.5, CO, NO2, O3, SO2 around the adolescents' school addresses. RESULTS The exposure-response curves showed that the lower the NDVI value, the higher the risk of depressive and anxiety symptoms. CO, PM2.5 and SO2 and air pollution score were associated with increased risk of depressive and anxiety symptoms. NDVI in all circular buffers decreased the risk of depressive and anxiety symptoms at low levels of PA, but the associations were not significant at high levels of PA. In the subgroup analysis, PM10, PM2.5, CO, NO2, SO2, AQI and air pollution score increased the risk of depressive and anxiety symptoms at low PA levels, but the associations were not significant at high levels of PA. Mediation analysis indicated that the mediating effect of PA on the association between NDVI, NDVI-200 m NDVI-500 m, CO, PM10, PM2.5, SO2, AQI and depressive/anxiety symptoms was statistically significant(p < 0.05). CONCLUSION Middle-high level PA could reduce the strength of association between air pollution and depressive and anxiety symptoms. Meanwhile, the association between green space/air pollution and depressive/anxiety symptoms was partly mediated by PA.
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Affiliation(s)
- Shuqin Li
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Yu Liu
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Ruoyu Li
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Wan Xiao
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Jinping Ou
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China.
| | - Fangbiao Tao
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China.
| | - Yuhui Wan
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China.
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Grekousis G, Sunarta IN, Stratoulias D. Tracing vulnerable communities to ambient air pollution exposure: A geodemographic and remote sensing approach. ENVIRONMENTAL RESEARCH 2024; 258:119491. [PMID: 38925467 DOI: 10.1016/j.envres.2024.119491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 05/29/2024] [Accepted: 06/22/2024] [Indexed: 06/28/2024]
Abstract
Most studies analyzing the effects of air pollution on disadvantaged populations use ground air quality measurements. However, ground stations are generally limited, with nearly 40% of countries having no official PM2.5 stations, not allowing air quality analysis for a significantly large share of the world's population. Furthermore, limited studies analyze community data from a geodemographic perspective, in other words, to delineate the sociodemographic profiles and geographically locate the socioeconomic groups more exposed to ambient air pollution. Therefore, a significant question arises: How can we trace vulnerable communities to air pollution in areas lacking air-quality ground data? Here, we propose a novel methodology to respond to this question. We use NO2, SO2, CO, and HCHO tropospheric column air-quality data from Sentinel-5P, a satellite that quantifies concentrations of atmospheric species from space operationally. We integrate them with census and environmental data and apply the local fuzzy geographically weighted clustering spatial machine learning method for segmentation analysis. Our findings for Bali, Indonesia, provide quantitative evidence for the benefits of this methodology in tracing and delineating the profiles of the communities most exposed to air pollution. For example, results show that communities with highly disadvantaged populations, such as unemployed (over 27.8%), low educated (over 27.9%), and children (over 22.1%) (mainly located around Bali's south and north coast touristic areas), exhibit very high values (over the 75th quartile) across the pollutants studied. The proposed method is reproducible easily, quickly, and at low cost, as it is based on freely available satellite data and not on costly ground station measurements. This will hopefully assist decision-makers in tracing the most vulnerable subpopulations, even in areas with inadequate air-quality monitoring networks, thus allowing local governments around the globe (even those that are financially weak) to achieve environmental justice and their sustainable development goals.
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Affiliation(s)
- George Grekousis
- School of Geography and Planning, Department of Urban and Regional Planning, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-sen University, China; Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou, China.
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11
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Frndak S, Deng Z, Ward-Caviness CK, Gorski-Steiner I, Thorpe RJ, Dickerson AS. Risk of dementia due to Co-exposure to air pollution and neighborhood disadvantage. ENVIRONMENTAL RESEARCH 2024; 251:118709. [PMID: 38493859 DOI: 10.1016/j.envres.2024.118709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 03/06/2024] [Accepted: 03/11/2024] [Indexed: 03/19/2024]
Abstract
BACKGROUND Co-exposure to air pollution and neighborhood disadvantage may influence cognition decline. We tested these associations in the context of dementia risk. METHODS We leveraged a cohort of adults ≥65 years (n = 5397) enrolled from 2011 to 2018 in the National Health and Aging Trends Study (NHATS). Particulate matter (PM) ≤ 10 μm in diameter, PM ≤ 2.5 μm in diameter, carbon monoxide, nitric oxide, and nitrogen dioxide - and neighborhood disadvantage were tested for joint associations with dementia risk. Pollutant concentrations at the 2010 census tract level were assigned using the US Environmental Protection Agency's Community Multiscale Air Quality Modeling System. Neighborhood disadvantage was defined using the tract Social Deprivation Index (SDI). Dementia was determined through self- or proxy-report or scores indicative of "probable dementia" according to NHATS screening tools. Joint effects of air pollutants and SDI were tested using quantile g-computation Cox proportional hazards models. We also stratified joint air pollution effects across SDI tertiles. Analyses adjusted for age at enrollment, sex, education, partner status, urbanicity, income, race and ethnicity, years at residence, census segregation, and census region. RESULTS SDI score (aHR = 1.08; 95% CI 0.96, 1.22), joint air pollution (aHR = 1.03, 95% CI 0.92, 1.16) and joint SDI with air pollution (aHR = 1.04, 95% CI 0.89, 1.22) were not associated with dementia risk. After accounting for competing risk of death, joint SDI with air pollution was not associated with dementia risk (aHR = 1.06; 95% CI 0.87, 1.29). In stratified models, joint air pollution was associated with greater risk of dementia at high (aHR = 1.19; 95% CI 0.87, 1.63), but not at medium or low SDI. CONCLUSION Air pollution was associated with greater dementia risk in disadvantaged areas after accounting for competing risks. Air pollution associations with dementia incidence may be attenuated when other risk factors are more prominent in disadvantaged neighborhoods.
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Affiliation(s)
- Seth Frndak
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, USA.
| | - Zhengyi Deng
- Department of Urology, Stanford School of Medicine, USA
| | - Cavin K Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency, USA
| | - Irena Gorski-Steiner
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, USA
| | - Roland J Thorpe
- Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, USA; Hopkins Center for Health Disparities Solutions, Johns Hopkins Bloomberg School of Public Health, USA; Johns Hopkins Alzheimer's Disease Resource Center for Minority Aging Research, USA
| | - Aisha S Dickerson
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, USA; Hopkins Center for Health Disparities Solutions, Johns Hopkins Bloomberg School of Public Health, USA
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12
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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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13
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Szeto JJ, Radack JK, DeMauro SB, Jensen EA, Gibbs K, Novick NP, Scott KA, Murosko DC, Burris HH, Nelin TD. Environmental Determinants of Post-Discharge Acute Respiratory Illness among Preterm Infants with Bronchopulmonary Dysplasia. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:648. [PMID: 38791862 PMCID: PMC11120865 DOI: 10.3390/ijerph21050648] [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: 04/19/2024] [Revised: 05/17/2024] [Accepted: 05/18/2024] [Indexed: 05/26/2024]
Abstract
OBJECTIVE To analyze the association of components of the Centers for Disease Control and Prevention (CDC) Environmental Justice Index (EJI) with respiratory health outcomes among infants with bronchopulmonary dysplasia (BPD) within one year after discharge from the neonatal intensive care unit. METHODS This was a retrospective cohort study of a cohort of preterm infants with BPD. Multivariable logistic regression models estimated associations of EJI and its components with medically attended acute respiratory illness, defined as an ED visit or inpatient readmission, within one year of discharge from the neonatal intensive care unit. A mediation analysis was conducted to evaluate how environmental injustice may contribute to racial disparities in acute respiratory illness. RESULTS Greater EJI was associated with an increased risk of medically attended respiratory illness (per EJI standard deviation increment, aOR 1.38, 95% CI: 1.12-1.69). Of the index's components, the Environmental Burden Module's Air pollution domain had the greatest association (aOR 1.44, 95% CI: 1.44-2.61). With respect to individual indicators within the EJI, Diesel Particulate Matter (DSLPM) and Air Toxic Cancer Risk (ATCR) demonstrated the strongest relationship (aOR 2.06, 95% CI: 1.57-2.71 and aOR 2.10, 95% CI: 1.59-2.78, respectively). Among non-Hispanic Black infants, 63% experienced a medically attended acute respiratory illness as compared to 18% of non-Hispanic White infants. DSLPM mediated 39% of the Black-White disparity in medically attended acute respiratory illness (p = 0.004). CONCLUSIONS Environmental exposures, particularly air pollution, are associated with post-discharge respiratory health outcomes among preterm infants with BPD after adjusting for clinical, demographic, and social vulnerability risk factors. Certain types of air pollutants, namely, DSLPM, are more greatly associated with acute respiratory illness. Environmental exposures may contribute to racial disparities in medically attended acute respiratory illness among infants with BPD.
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Affiliation(s)
- Jonathan J. Szeto
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA;
| | - Joshua K. Radack
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
| | - Sara B. DeMauro
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
- Neonatal Follow-Up Program, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Erik A. Jensen
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
- Newborn/Infant Chronic Lung Disease Program, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Kathleen Gibbs
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
- Newborn/Infant Chronic Lung Disease Program, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Nicolas P. Novick
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
| | - Kristan A. Scott
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
| | - Daria C. Murosko
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
- Leonard Davis Institute of Health Economics, Philadelphia, PA 19104, USA
| | - Heather H. Burris
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
- Leonard Davis Institute of Health Economics, Philadelphia, PA 19104, USA
- Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Timothy D. Nelin
- Division of Neonatology, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA (S.B.D.)
- Leonard Davis Institute of Health Economics, Philadelphia, PA 19104, USA
- Center of Excellence in Environmental Toxicology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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14
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Mei Y, Christensen GM, Li Z, Waller LA, Ebelt S, Marcus M, Lah JJ, Wingo AP, Wingo TS, Hüls A. Joint effects of air pollution and neighborhood socioeconomic status on cognitive decline - Mediation by depression, high cholesterol levels, and high blood pressure. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 923:171535. [PMID: 38453069 PMCID: PMC10965363 DOI: 10.1016/j.scitotenv.2024.171535] [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: 09/29/2023] [Revised: 12/21/2023] [Accepted: 03/04/2024] [Indexed: 03/09/2024]
Abstract
Air pollution and neighborhood socioeconomic status (N-SES) are associated with adverse cardiovascular health and neuropsychiatric functioning in older adults. This study examines the degree to which the joint effects of air pollution and N-SES on the cognitive decline are mediated by high cholesterol levels, high blood pressure (HBP), and depression. In the Emory Healthy Aging Study, 14,390 participants aged 50+ years from Metro Atlanta, GA, were assessed for subjective cognitive decline using the cognitive function instrument (CFI). Information on the prior diagnosis of high cholesterol, HBP, and depression was collected through the Health History Questionnaire. Participants' census tracts were assigned 3-year average concentrations of 12 air pollutants and 16 N-SES characteristics. We used the unsupervised clustering algorithm Self-Organizing Maps (SOM) to create 6 exposure clusters based on the joint distribution of air pollution and N-SES in each census tract. Linear regression analysis was used to estimate the effects of the SOM cluster indicator on CFI, adjusting for age, race/ethnicity, education, and neighborhood residential stability. The proportion of the association mediated by high cholesterol levels, HBP, and depression was calculated by comparing the total and direct effects of SOM clusters on CFI. Depression mediated up to 87 % of the association between SOM clusters and CFI. For example, participants living in the high N-SES and high air pollution cluster had CFI scores 0.05 (95 %-CI:0.01,0.09) points higher on average compared to those from the high N-SES and low air pollution cluster; after adjusting for depression, this association was attenuated to 0.01 (95 %-CI:-0.04,0.05). HBP mediated up to 8 % of the association between SOM clusters and CFI and high cholesterol up to 5 %. Air pollution and N-SES associated cognitive decline was partially mediated by depression. Only a small portion (<10 %) of the association was mediated by HBP and high cholesterol.
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Affiliation(s)
- Yiyang Mei
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Grace M Christensen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Zhenjiang Li
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Lance A Waller
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Stefanie Ebelt
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Michele Marcus
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - James J Lah
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA
| | - Aliza P Wingo
- Division of Mental Health, Atlanta VA Medical Center, Decatur, GA, USA; Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
| | - Thomas S Wingo
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA; Department of Human Genetics, Emory University, Atlanta, GA, USA
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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15
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Pett L, Li Z, Abrishamcar S, Hodge K, Everson T, Christensen G, Gearing M, Kobor MS, Konwar C, MacIsaac JL, Dever K, Wingo AP, Levey A, Lah JJ, Wingo TS, Hüls A. The association between neighborhood deprivation and DNA methylation in an autopsy cohort. Aging (Albany NY) 2024; 16:6694-6716. [PMID: 38663907 PMCID: PMC11087100 DOI: 10.18632/aging.205764] [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: 09/01/2023] [Accepted: 03/18/2024] [Indexed: 05/08/2024]
Abstract
Previous research has found that living in a disadvantaged neighborhood is associated with poor health outcomes. Living in disadvantaged neighborhoods may alter inflammation and immune response in the body, which could be reflected in epigenetic mechanisms such as DNA methylation (DNAm). We used robust linear regression models to conduct an epigenome-wide association study examining the association between neighborhood deprivation (Area Deprivation Index; ADI), and DNAm in brain tissue from 159 donors enrolled in the Emory Goizueta Alzheimer's Disease Research Center (Georgia, USA). We found one CpG site (cg26514961, gene PLXNC1) significantly associated with ADI after controlling for covariates and multiple testing (p-value=5.0e-8). Effect modification by APOE ε4 was statistically significant for the top ten CpG sites from the EWAS of ADI, indicating that the observed associations between ADI and DNAm were mainly driven by donors who carried at least one APOE ε4 allele. Four of the top ten CpG sites showed a significant concordance between brain tissue and tissues that are easily accessible in living individuals (blood, buccal cells, saliva), including DNAm in cg26514961 (PLXNC1). Our study identified one CpG site (cg26514961, PLXNC1 gene) that was significantly associated with neighborhood deprivation in brain tissue. PLXNC1 is related to immune response, which may be one biological pathway how neighborhood conditions affect health. The concordance between brain and other tissues for our top CpG sites could make them potential candidates for biomarkers in living individuals.
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Affiliation(s)
- Lindsay Pett
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Zhenjiang Li
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Sarina Abrishamcar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Kenyaita Hodge
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Todd Everson
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Grace Christensen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Marla Gearing
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Michael S. Kobor
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Chaini Konwar
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
| | - Julia L. MacIsaac
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Kristy Dever
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, BC, Canada
| | - Aliza P. Wingo
- Division of Mental Health, Atlanta VA Medical Center, Decatur, GA 30033, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Allan Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - James J. Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Thomas S. Wingo
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Human Genetics, Emory University, Atlanta, GA 30322, USA
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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Valdez MC, Freeborn DL, Valdez JM, Henriquez AR, Snow SJ, Jackson TW, Kodavanti PRS, Kodavanti UP. Influence of Mild Chronic Stress and Social Isolation on Acute Ozone-Induced Alterations in Stress Biomarkers and Brain-Region-Specific Gene Expression in Male Wistar-Kyoto Rats. Antioxidants (Basel) 2023; 12:1964. [PMID: 38001817 PMCID: PMC10669107 DOI: 10.3390/antiox12111964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/26/2023] Open
Abstract
Individuals with psychosocial stress often experience an exaggerated response to air pollutants. Ozone (O3) exposure has been associated with the activation of the neuroendocrine stress-response system. We hypothesized that preexistent mild chronic stress plus social isolation (CS), or social isolation (SI) alone, would exacerbate the acute effects of O3 exposure on the circulating adrenal-derived stress hormones, and the expression of the genes regulating glucocorticoid stress signaling via an altered stress adaptation in a brain-region-specific manner. Male Wistar-Kyoto rats (5 weeks old) were socially isolated, plus were subjected to either CS (noise, confinement, fear, uncomfortable living, hectic activity, and single housing), SI (single housing only, restricted handling and no enrichment) or no stress (NS; double housing, frequent handling and enrichment provided) for 8 weeks. The rats were then exposed to either air or O3 (0.8 ppm for 4 h), and the samples were collected immediately after. The indicators of sympathetic and hypothalamic-pituitary axis (HPA) activation (i.e., epinephrine, corticosterone, and lymphopenia) increased with O3 exposure, but there were no effects from CS or SI, except for the depletion of serum BDNF. CS and SI revealed small changes in brain-region-specific glucocorticoid-signaling-associated markers of gene expression in the air-exposed rats (hypothalamic Nr3c1, Nr3c2 Hsp90aa1, Hspa4 and Cnr1 inhibition in SI; hippocampal HSP90aa1 increase in SI; and inhibition of the bed nucleus of the stria terminalis (BNST) Cnr1 in CS). Gene expression across all brain regions was altered by O3, reflective of glucocorticoid signaling effects, such as Fkbp5 in NS, CS and SI. The SI effects on Fkbp5 were greatest for SI in BNST. O3 increased Cnr2 expression in the hypothalamus and olfactory bulbs of the NS and SI groups. O3, in all stress conditions, generally inhibited the expression of Nr3c1 in all brain regions, Nr3c2 in the hippocampus and hypothalamus and Bdnf in the hippocampus. SI, in general, showed slightly greater O3-induced changes when compared to NS and CS. Serum metabolomics revealed increased sphingomyelins in the air-exposed SI and O3-exposed NS, with underlying SI dampening some of the O3-induced changes. These results suggest a potential link between preexistent SI and acute O3-induced increases in the circulating adrenal-derived stress hormones and brain-region-specific gene expression changes in glucocorticoid signaling, which may partly underlie the stress dynamic in those with long-term SI.
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Affiliation(s)
- Matthew C. Valdez
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; (M.C.V.); (D.L.F.); (J.M.V.); (P.R.S.K.)
- Oak Ridge Institute for Science and Education Research Participation Program, US Department of Energy, Oak Ridge, TN 37831, USA; (A.R.H.); (T.W.J.)
| | - Danielle L. Freeborn
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; (M.C.V.); (D.L.F.); (J.M.V.); (P.R.S.K.)
| | - Joseph M. Valdez
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; (M.C.V.); (D.L.F.); (J.M.V.); (P.R.S.K.)
- Oak Ridge Institute for Science and Education Research Participation Program, US Department of Energy, Oak Ridge, TN 37831, USA; (A.R.H.); (T.W.J.)
| | - Andres R. Henriquez
- Oak Ridge Institute for Science and Education Research Participation Program, US Department of Energy, Oak Ridge, TN 37831, USA; (A.R.H.); (T.W.J.)
| | - Samantha J. Snow
- Cardiopulmonary and Immunotoxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA;
| | - Thomas W. Jackson
- Oak Ridge Institute for Science and Education Research Participation Program, US Department of Energy, Oak Ridge, TN 37831, USA; (A.R.H.); (T.W.J.)
- Cardiopulmonary and Immunotoxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA;
| | - Prasada Rao S. Kodavanti
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA; (M.C.V.); (D.L.F.); (J.M.V.); (P.R.S.K.)
| | - Urmila P. Kodavanti
- Cardiopulmonary and Immunotoxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA;
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Soloveva MV, Poudel G, Barnett A, Shaw JE, Martino E, Knibbs LD, Anstey KJ, Cerin E. Characteristics of urban neighbourhood environments and cognitive age in mid-age and older adults. Health Place 2023; 83:103077. [PMID: 37451077 DOI: 10.1016/j.healthplace.2023.103077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 05/29/2023] [Accepted: 06/22/2023] [Indexed: 07/18/2023]
Abstract
In this cross-sectional study, we examined the extent to which features of the neighbourhood natural, built, and socio-economic environments were related to cognitive age in adults (N = 3418, Mage = 61 years) in Australia. Machine learning estimated an individual's cognitive age from assessments of processing speed, verbal memory, premorbid intelligence. A 'cognitive age gap' was calculated by subtracting chronological age from predicted cognitive age and was used as a marker of cognitive age. Greater parkland availability and higher neighbourhood socio-economic status were associated with a lower cognitive age gap score in confounder- and mediator-adjusted regression models. Cross-sectional design is a limitation. Living in affluent neighbourhoods with access to parks maybe beneficial for cognitive health, although selection mechanisms may contribute to the findings.
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Affiliation(s)
- Maria V Soloveva
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, 3000, Australia.
| | - Govinda Poudel
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, 3000, Australia
| | - Anthony Barnett
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, 3000, Australia
| | - Jonathan E Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia; School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia; School of Life Sciences, La Trobe University, Melbourne, VIC, 3086, Australia
| | - Erika Martino
- School of Population and Global Health, University of Melbourne, Melbourne, VIC, 3053, Australia
| | - Luke D Knibbs
- School of Public Health, The University of Sydney, NSW 2006, Australia; Public Health Research Analytics and Methods for Evidence, Public Health Unit, Sydney Local Health District, Camperdown, NSW 2050, Australia
| | - Kaarin J Anstey
- School of Psychology, University of New South Wales, Kensington, NSW, 2052, Australia; Neuroscience Research Australia (NeuRA), Sydney, NSW, 2031, Australia; UNSW Ageing Futures Institute, Kensington, NSW, 2052, Australia
| | - Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, 3000, Australia; School of Public Health, The University of Hong Kong, Hong Kong, China; Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia; Department of Community Medicine, UiT the Artic University of Norway, 9019, Tromsø, Norway
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18
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Jovanovic T, Roberts A, Huels A. Intergenerational transmission of trauma: A biological perspective. J Trauma Stress 2023; 36:662-664. [PMID: 37218444 DOI: 10.1002/jts.22938] [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: 01/23/2023] [Revised: 03/22/2023] [Accepted: 03/22/2023] [Indexed: 05/24/2023]
Abstract
This commentary is based on an invited panel for the 2022 International Society of Traumatic Stress Studies (ISTSS) annual meeting entitled "Perspective Discourses On…Intergenerational Transmission of Trauma: A Biological Perspective." This was a new format introduced by ISTSS to facilitate discussion around timely topics. This session included scholars from different backgrounds (e.g., epidemiology, neuroscience, environmental health) who shared their approaches to understanding the biological bases of the intergenerational transmission of trauma. Specifically, the panel presented information about putative direct and indirect mechanisms of transmission, including epigenetic and environmental factors, and pointed to behavioral and neurobiological outcomes in offspring. This commentary synthesizes some of the current knowledge gained by these different approaches and identifies key areas to advance in future work.
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Affiliation(s)
- Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, Michigan, USA
| | - Andrea Roberts
- Department of Environmental Health, Harvard University, Cambridge, Massachusetts, USA
| | - Anke Huels
- Department of Epidemiology and Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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Ilango SD, Leary CS, Ritchie E, Semmens EO, Park C, Fitzpatrick AL, Kaufman JD, Hajat A. An Examination of the Joint Effect of the Social Environment and Air Pollution on Dementia Among US Older Adults. Environ Epidemiol 2023; 7:e250. [PMID: 37304341 PMCID: PMC10256342 DOI: 10.1097/ee9.0000000000000250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 04/06/2023] [Indexed: 06/13/2023] Open
Abstract
Evidence suggests exposure to air pollution increases the risk of dementia. Cognitively stimulating activities and social interactions, made available through the social environment, may slow cognitive decline. We examined whether the social environment buffers the adverse effect of air pollution on dementia in a cohort of older adults. Methods This study draws from the Ginkgo Evaluation of Memory Study. Participants aged 75 years and older were enrolled between 2000 and 2002 and evaluated for dementia semi-annually through 2008. Long-term exposure to particulate matter and nitrogen dioxide was assigned from spatial and spatiotemporal models. Census tract-level measures of the social environment and individual measures of social activity were used as measures of the social environment. We generated Cox proportional hazard models with census tract as a random effect and adjusted for demographic and study visit characteristics. Relative excess risk due to interaction was estimated as a qualitative measure of additive interaction. Results This study included 2,564 individuals. We observed associations between increased risk of dementia and fine particulate matter (µg/m3), coarse particulate matter (µg/m3), and nitrogen dioxide (ppb); HRs per 5 unit increase were 1.55 (1.01, 2.18), 1.31 (1.07, 1.60), and 1.18 (1.02, 1.37), respectively. We found no evidence of additive interaction between air pollution and the neighborhood social environment. Conclusions We found no consistent evidence to suggest a synergistic effect between exposure to air pollution and measures of the social environment. Given the many qualities of the social environment that may reduce dementia pathology, further examination is encouraged.
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Affiliation(s)
- Sindana D Ilango
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Cindy S Leary
- Center for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, Montana, USA
| | - Emily Ritchie
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Erin O Semmens
- Center for Population Health Research, School of Public and Community Health Sciences, University of Montana, Missoula, Montana, USA
| | - Christina Park
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Annette L Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Department of Family Medicine and Global Health, University of Washington, Seattle, Washington, USA
| | - Joel D Kaufman
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Anjum Hajat
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
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VoPham T, Jones RR. State of the science on outdoor air pollution exposure and liver cancer risk. ENVIRONMENTAL ADVANCES 2023; 11:100354. [PMID: 36875691 PMCID: PMC9984166 DOI: 10.1016/j.envadv.2023.100354] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Background There is emerging evidence that air pollution exposure increases the risk of developing liver cancer. To date, there have been four epidemiologic studies conducted in the United States, Taiwan, and Europe showing generally consistent positive associations between ambient exposure to air pollutants, including particulate matter <2.5 μm in aerodynamic diameter (PM2.5) and nitrogen dioxide (NO2), and liver cancer risk. There are several research gaps and thus valuable opportunities for future work to continue building on this expanding body of literature. The objectives of this paper are to narratively synthesize existing epidemiologic literature on the association between air pollution exposure and liver cancer incidence and describe future research directions to advance the science of understanding the role of air pollution exposure in liver cancer development. Future research directions include 1) accounting for potential confounding by established risk factors for the predominant histological subtype, hepatocellular carcinoma (HCC); 2) examination of incident primary liver cancer outcomes with consideration of potential differential associations according to histology; 3) air pollution exposure assessments considering early-life and/or historical exposures, residential histories, residual confounding from other sources of air pollution (e.g., tobacco smoking), and integration of geospatial ambient exposure modeling with novel biomarker technologies; 4) examination of air pollution mixtures experienced in the exposome; 5) consideration of increased opportunities for exposure to outdoor air pollution due to climate change (e.g., wildfires); and 6) consideration of modifying factors for air pollution exposure, such as socioeconomic status, that may contribute to disparities in liver cancer incidence. Conclusions In light of mounting evidence demonstrating that higher levels of air pollution exposure increase the risk for developing liver cancer, methodological considerations primarily concerning residual confounding and improved exposure assessment are warranted to robustly demonstrate an independent association for air pollution as a hepatocarcinogen.
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Affiliation(s)
- Trang VoPham
- Epidemiology Program, Public Health Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, Washington 98109, United States
- Department of Epidemiology, University of Washington, 3980 15th Avenue NE, Seattle, Washington 98195, United States
| | - Rena R. Jones
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, 9609 Medical Center Drive MSC 9776, Bethesda, Maryland 20850, United States
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Zhang X, Nan S, Lu S, Wang M. Spatial Effects of Air Pollution on the Siting of Enterprises: Evidence from China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14484. [PMID: 36361381 PMCID: PMC9656830 DOI: 10.3390/ijerph192114484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 11/01/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
The siting of enterprises is important for enterprises to formulate business objectives and business strategies, both of which are crucial to the development of enterprises in the future. Although there exists an irrefutable fact that the increasingly serious environmental problems are affecting the behaviors of enterprises, how air pollution affects the siting of enterprises has received little academic attention. Therefore, using the dataset of Chinese prefecture-level cities from 2014 to 2020, this paper employs the Spatial Durbin Model to investigate the direct and spatial spillover effects of air pollution on the site selection of enterprises. In addition, this paper also establishes a mediation effect model to explore the impact mechanism of air pollution on the site selection of enterprises. The empirical results show that air pollution exerts a negative impact on both the local and spatially related regions' enterprises' site selection, and the above conclusion is reinforced through a series of robustness checks. The heterogeneity analysis demonstrates that air pollution has a greater inhibitory effect on the siting of low-cleaning enterprises and small-scale enterprises for the local and adjacent regions. The mechanism analysis results indicate that air pollution inhibits the siting of enterprises by reducing the local labor endowment and market scale. Our study enriches the relevant theory of air pollution and enterprises' location nexus, and it also provides an empirical basis for the Chinese government to formulate policies related to air governance and the siting of enterprises.
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Zhuo H, Xiao J, Tseng WL, Liew Z. Developmental Milestones of Infancy and Associations with Later Childhood Neurodevelopmental Outcomes in the Adolescent Brain Cognitive Development (ABCD) Study. CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9101424. [PMID: 36291360 PMCID: PMC9600325 DOI: 10.3390/children9101424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 09/12/2022] [Accepted: 09/13/2022] [Indexed: 11/24/2022]
Abstract
The age at attaining infancy developmental milestones has been associated with later neurodevelopmental outcomes, but evidence from large and diverse samples is lacking. We investigated this by analyzing data of 5360 singleton children aged 9-10 from 17 states in the US enrolled in the Adolescent Brain Cognitive Development (ABCD) study during 2016-2020. Delays in four milestones (first roll over, unaided sitting, unaided walking, and speaking first words) were defined using the 90th percentile of age at attainment reported by children's biological mothers. Childhood neurocognitive function was measured by research assistants using the NIH toolbox, and children reported their behavioral problems using the Brief Problem Monitor. Linear mixed-effects models were employed to investigate the association between delays in single or multiple milestones and childhood neurobehavioral outcomes. Delays in first roll over, unaided sitting, or walking were associated with poorer childhood neurocognitive function, while delay in speaking first words was associated with both poorer neurocognitive function and behavioral problems. Children who had delays in both motor and language milestones had the worst neurocognitive function and behavioral outcomes. Our results suggest that delays in motor and language milestone attainment during infancy are predictive of childhood neurobehavioral outcomes.
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Affiliation(s)
- Haoran Zhuo
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA
- Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, CT 06510, USA
| | - Jingyuan Xiao
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA
- Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, CT 06510, USA
| | - Wan-Ling Tseng
- Yale Child Study Center, Yale School of Medicine, New Haven, CT 06519, USA
| | - Zeyan Liew
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT 06510, USA
- Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale School of Public Health, New Haven, CT 06510, USA
- Correspondence:
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