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He Y, Xu Y, Cao F, Gao Z, Ge M, He T, Zhang P, Zhao C, Wang P, Xu Z, Pan H. Association of Long-Term Exposure to PM 2.5 Constituents and Green Space With Arthritis and Rheumatoid Arthritis. GEOHEALTH 2024; 8:e2024GH001132. [PMID: 39508059 PMCID: PMC11538738 DOI: 10.1029/2024gh001132] [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: 06/12/2024] [Revised: 10/04/2024] [Accepted: 10/25/2024] [Indexed: 11/08/2024]
Abstract
There is limited evidence regarding the effects of long-term exposure to PM2.5 constituents on the risk of arthritis and rheumatoid arthritis, and the interaction between PM2.5 and green space remains unclear. This study examined the relationship between long-term exposure to PM2.5 constituents and the risk of arthritis and rheumatoid arthritis, with the exposure period extending from recruitment until self-reported outcomes, death, loss to follow-up, or end of follow-up. Additionally, the study assessed whether there was an interactive effect between PM2.5 and green space on these risks. We gathered cohort data on 18,649 individuals aged ≥45 years. We applied generalized linear mixed-effects models to estimate the effects of PM2.5 constituents, NDVI, and their interaction on arthritis and rheumatoid arthritis. The quantile g-computation and weighted quantile sum regression model were applied to estimate the combined effect of PM2.5 constituents. Our results showed that exposure to single and mixed PM2.5 constituents adversely affected arthritis and rheumatoid arthritis, and was mainly attributed to the black carbon component. We observed "U" or "J" shaped exposure-response curves for the effects of PM2.5, OM, NO3 - and NH4 + exposure on the development of arthritis/rheumatoid arthritis. Additionally, the odds ratio of arthritis for per interquartile range (IQR) increase in PM2.5 was 1.209 (95% CI:1.198, 1.221), per 0.1-unit decrease in NDVI was 1.091 (95% CI:1.033, 1.151), and the interaction term was 1.005 (95% CI:1.002, 1.007). These findings flesh out the existing evidence for PM2.5 constituents, NDVI and arthritis, rheumatoid arthritis, but the underlying mechanisms still require further exploration.
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Affiliation(s)
- Yi‐Sheng He
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Yi‐Qing Xu
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Fan Cao
- Beijing Ophthalmology & Visual Sciences Key LaboratoryBeijing Institute of OphthalmologyBeijing Tongren Eye CenterBeijing Tongren HospitalCapital Medical UniversityBeijingChina
| | - Zhao‐Xing Gao
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Man Ge
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Tian He
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Peng Zhang
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Chan‐Na Zhao
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
| | - Peng Wang
- Teaching Center for Preventive MedicineSchool of Public HealthAnhui Medical UniversityHefeiChina
| | - Zhiwei Xu
- School of Medicine and DentistryGriffith UniversityGold CoastQLDAustralia
| | - Hai‐Feng Pan
- Department of Epidemiology and BiostatisticsSchool of Public HealthAnhui Medical UniversityHefeiChina
- Inflammation and Immune Mediated Diseases Laboratory of Anhui ProvinceHefeiChina
- Anhui Provincial Institute of Translational MedicineHefeiChina
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Qiang N, Bao Y, Li Y, Zhang N, Zhou Y, Deng X, Han L, Ran J. Associations of long-term exposure to low-level PM 2.5 and brain disorders in 260,922 middle-aged and older adults. CHEMOSPHERE 2024; 362:142703. [PMID: 38925519 DOI: 10.1016/j.chemosphere.2024.142703] [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: 02/08/2024] [Revised: 05/22/2024] [Accepted: 06/24/2024] [Indexed: 06/28/2024]
Abstract
Long-term exposure to high-level ambient PM2.5 was associated with increased risks of brain disorders, while the associations remain uncertain when the exposure is lower than current air quality standards in numerous countries. This study aimed to assess the effects of PM2.5 exposure on the brain system in the population with annual mean concentrations ≤15 μg/m3. We analyzed data from 260,922 participants without preexisting brain diseases at baseline in the UK Biobank. The geographical distribution of PM2.5 in 2010 was estimated by a land use regression model and linked with individual residential address. We investigated associations of ambient PM2.5 with incident neurological (dementia, Parkinson's diseases [PD], epilepsy, and migraine) and psychiatric (major depressive disorder [MDD] and anxiety disorder) diseases through Cox proportional hazard models. We further estimated the links with brain imaging phenotypes by neuroimaging analysis. Results showed that in the population with PM2.5 concentrations ≤15 μg/m3, each interquartile range (IQR, 1.28 μg/m3) increment in PM2.5 was related to incidence risks of dementia, epilepsy, migraine, MDD, and anxiety disorder with hazard ratios of 1.08 (95% confidence interval [CI]: 1.03, 1.13), 1.12 (1.05, 1.20), 1.07 (1.00, 1.13), 1.06 (1.03, 1.09), and 1.05 (1.02, 1.08), respectively. We did not observe a significant association with PD. The association with dementia was stronger among the population with poor cardiovascular health (measured by Life's Essential 8) than the counterpart (P for interaction = 0.037). Likewise, per IQR increase was associated with specific brain imaging phenotypes, including volumes of total brain (β = -0.036; 95% CI: -0.050, -0.022), white matter (-0.030; -0.046, -0.014), grey matter (-0.030; -0.042, -0.017), respectively. The findings suggest long-term exposure to ambient PM2.5 at low-level still has an adverse impact on the neuro-psychiatric systems. The brain-relevant epidemiological assessment suggests that each country should update the standard for ambient PM2.5 following the World Health Organization Air Quality Guidelines 2021.
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Affiliation(s)
- Ne Qiang
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yujia Bao
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yongxuan Li
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Na Zhang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yanqiu Zhou
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaobei Deng
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Lefei Han
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Jinjun Ran
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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Fu L, Guo Y, Zhu Q, Chen Z, Yu S, Xu J, Tang W, Wu C, He G, Hu J, Zeng F, Dong X, Yang P, Lin Z, Wu F, Liu T, Ma W. Effects of long-term exposure to ambient fine particulate matter and its specific components on blood pressure and hypertension incidence. ENVIRONMENT INTERNATIONAL 2024; 184:108464. [PMID: 38324927 DOI: 10.1016/j.envint.2024.108464] [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: 10/17/2023] [Revised: 01/10/2024] [Accepted: 01/29/2024] [Indexed: 02/09/2024]
Abstract
BACKGROUND Epidemiological evidence on the association of PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) and its specific components with hypertension and blood pressure is limited. METHODS We applied information of participants from the World Health Organization's (WHO) Study on Global Ageing and Adult Health (SAGE) to estimate the associations of long-term PM2.5 mass and its chemical components exposure with blood pressure (BP) and hypertension incidence in Chinese adults ≥ 50 years during 2007-2018. Generalized linear mixed model and Cox proportional hazard model were applied to investigate the effects of PM2.5 mass and its chemical components on the incidence of hypertension and BP, respectively. RESULTS Each interquartile range (IQR = 16.80 μg/m3) increase in the one-year average of PM2.5 mass concentration was associated with a 17 % increase in the risk of hypertension (HR = 1.17, 95 % CI: 1.10, 1.24), and the population attributable fraction (PAF) was 23.44 % (95 % CI: 14.69 %, 31.55 %). Each IQR μg/m3 increase in PM2.5 exposure was also related to increases of systolic blood pressure (SBP) by 2.54 mmHg (95 % CI:1.99, 3.10), and of diastolic blood pressure (DBP) by 1.36 mmHg (95 % CI: 1.04, 1.68). Additionally, the chemical components of SO42-, NO3-, NH4+, OM, and BC were also positively associated with an increased risk of hypertension incidence and elevated blood pressure. CONCLUSIONS These results indicate that long-term exposure to PM2.5 mass and its specific components may be major drivers of escalation in hypertension diseases.
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Affiliation(s)
- Li Fu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; Tianhe District Center for Disease Control and Prevention, Guangzhou 510655, China
| | - Yanfei Guo
- Shanghai Municipal Centre for Disease Control and Prevention, Shanghai 200336, China; General Practice/Family Medicine, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Qijiong Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Zhiqing Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Siwen Yu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jiahong Xu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Weiling Tang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Cuiling Wu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Guanhao He
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Xiaomei Dong
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Pan Yang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Fan Wu
- Shanghai Medical College, Fudan University, Shanghai 200032, China.
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China.
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China; China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China
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