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Liang KH, Colombijn JMT, Verhaar MC, Ghannoum M, Timmermans EJ, Vernooij RWM. The general external exposome and the development or progression of chronic kidney disease: a systematic review and meta-analyses. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024:124509. [PMID: 38968981 DOI: 10.1016/j.envpol.2024.124509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 06/07/2024] [Accepted: 07/03/2024] [Indexed: 07/07/2024]
Abstract
The impact of environmental risk factors on chronic kidney disease (CKD) remains unclear. This systematic review aims to provide an overview of the literature on the association between the general external exposome and CKD development or progression. We searched MEDLINE and EMBASE for case-control or cohort studies, that investigated the association of the general external exposome with a change in eGFR or albuminuria, diagnosis or progression of CKD, or CKD-related mortality. The risk of bias of included studies was assessed using the Newcastle-Ottawa Scale. Summary effect estimates were calculated using random-effects meta-analyses. Most of the 66 included studies focused on air pollution (n=33), e.g. particulate matter (PM) and nitric oxides (NOx), and heavy metals (n=21) e.g. lead and cadmium. Few studies investigated chemicals (n=7) or built environmental factors (n=5). No articles on other environment factors such as noise, food supply, or urbanization were found. PM2.5 exposure was associated with an increased CKD and end-stage kidney disease incidence, but not with CKD-related mortality. There was mixed evidence regarding the association of NO2 and PM10 on CKD incidence. Exposure to heavy metals might be associated with an increased risk of adverse kidney outcomes, however, evidence was inconsistent. Studies on effects of chemicals or built environment on kidney outcomes were inconclusive. In conclusion, prolonged exposure to PM2.5 is associated with an increased risk of CKD incidence and progression to kidney failure. Current studies predominantly investigate the exposure to air pollution and heavy metals, whereas chemicals and the built environment remains understudied. Substantial heterogeneity and mixed evidence were found across studies. Therefore, long-term high-quality studies are needed to elucidate the impact of exposure to chemicals or other (built) environmental factors and CKD.
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Affiliation(s)
- Kate H Liang
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands.
| | - Julia M T Colombijn
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Marianne C Verhaar
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marc Ghannoum
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands; National Poison Information Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Erik J Timmermans
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Robin W M Vernooij
- Department of Nephrology and Hypertension, University Medical Center Utrecht, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
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Chen R, Yang C, Guo Y, Chen G, Li S, Li P, Wang J, Meng R, Wang HY, Peng S, Sun X, Wang F, Kong G, Zhang L. Association between ambient PM 1 and the prevalence of chronic kidney disease in China: A nationwide study. JOURNAL OF HAZARDOUS MATERIALS 2024; 468:133827. [PMID: 38377899 DOI: 10.1016/j.jhazmat.2024.133827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 02/08/2024] [Accepted: 02/16/2024] [Indexed: 02/22/2024]
Abstract
Particulate of diameter ≤ 1 µm (PM1) presents a novel risk factor of adverse health effects. Nevertheless, the association of PM1 with the risk of chronic kidney disease (CKD) in the general population is not well understood, particularly in regions with high PM1 levels like China. Based on a nationwide representative survey involving 47,204 adults and multi-source ambient air pollution inversion data, the present study evaluated the association of PM1 with CKD prevalence in China. The two-year average PM1, particulate of diameter ≤ 2.5 µm (PM2.5), and PM1-2.5 values were accessed using a satellite-based random forest approach. CKD was defined as estimated glomerular filtration rate < 60 ml/min/1.73 m2 or albuminuria. The results suggested that a 10 μg/m3 rise in PM1 was related to a higher CKD risk (odds ratio [OR], 1.13; 95% confidence interval [CI] 1.08-1.18) and albuminuria (OR, 1.11; 95% CI, 1.05-1.17). The association between PM1 and CKD was more evident among urban populations, older adults, and those without comorbidities such as diabetes or hypertension. Every 1% increase in the PM1/PM2.5 ratio was related to the prevalence of CKD (OR, 1.03; 95% CI, 1.03-1.04), but no significant relationship was found for PM1-2.5. In conclusion, the present study demonstrated long-term exposure to PM1 was associated with an increased risk of CKD in the general population and PM1 might play a leading role in the observed relationship of PM2.5 with the risk of CKD. These findings provide crucial evidence for developing air pollution control strategies to reduce the burden of CKD.
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Affiliation(s)
- Rui Chen
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
| | - Chao Yang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Shanshan Li
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Pengfei Li
- Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Jinwei Wang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China
| | - Ruogu Meng
- National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Huai-Yu Wang
- National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Suyuan Peng
- National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Xiaoyu Sun
- Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Fulin Wang
- National Institute of Health Data Science at Peking University, Beijing 100191, China; Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China
| | - Guilan Kong
- Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science at Peking University, Beijing 100191, China
| | - Luxia Zhang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China; Research Units of Diagnosis and Treatment of Immune-mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, China; Advanced Institute of Information Technology, Peking University, Hangzhou, China; National Institute of Health Data Science at Peking University, Beijing 100191, China.
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Mollalo A, Hamidi B, Lenert L, Alekseyenko AV. Application of Spatial Analysis for Electronic Health Records: Characterizing Patient Phenotypes and Emerging Trends. RESEARCH SQUARE 2024:rs.3.rs-3443865. [PMID: 37886509 PMCID: PMC10602163 DOI: 10.21203/rs.3.rs-3443865/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Background Electronic health records (EHR) commonly contain patient addresses that provide valuable data for geocoding and spatial analysis, enabling more comprehensive descriptions of individual patients for clinical purposes. Despite the widespread use of EHR in clinical decision support and interventions, no systematic review has examined the extent to which spatial analysis is used to characterize patient phenotypes. Objective This study reviews advanced spatial analyses that employed individual-level health data from EHR within the US to characterize patient phenotypes. Methods We systematically evaluated English-language peer-reviewed articles from PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar databases from inception to August 20, 2023, without imposing constraints on time, study design, or specific health domains. Results Only 49 articles met the eligibility criteria. These articles utilized diverse spatial methods, with a predominant focus on clustering techniques, while spatiotemporal analysis (frequentist and Bayesian) and modeling were relatively underexplored. A noteworthy surge (n = 42, 85.7%) in publications was observed post-2017. The publications investigated a variety of adult and pediatric clinical areas, including infectious disease, endocrinology, and cardiology, using phenotypes defined over a range of data domains, such as demographics, diagnoses, and visits. The primary health outcomes investigated were asthma, hypertension, and diabetes. Notably, patient phenotypes involving genomics, imaging, and notes were rarely utilized. Conclusions This review underscores the growing interest in spatial analysis of EHR-derived data and highlights knowledge gaps in clinical health, phenotype domains, and spatial methodologies. Additionally, this review proposes guidelines for harnessing the potential of spatial analysis to enhance the context of individual patients for future clinical decision support.
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Wathanavasin W, Banjongjit A, Phannajit J, Eiam-Ong S, Susantitaphong P. Association of fine particulate matter (PM 2.5) exposure and chronic kidney disease outcomes: a systematic review and meta-analysis. Sci Rep 2024; 14:1048. [PMID: 38200164 PMCID: PMC10781728 DOI: 10.1038/s41598-024-51554-1] [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: 10/03/2023] [Accepted: 01/06/2024] [Indexed: 01/12/2024] Open
Abstract
Several studies have reported an increased risk of chronic kidney disease (CKD) outcomes after long-term exposure (more than 1 year) to particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5). However, the conclusions remain inconsistent. Therefore, we conducted this meta-analysis to examine the association between long-term PM2.5 exposure and CKD outcomes. A literature search was conducted in PubMed, Scopus, Cochrane Central Register of Controlled trials, and Embase for relevant studies published until August 10, 2023. The main outcomes were incidence and prevalence of CKD as well as incidence of end-stage kidney disease (ESKD). The random-effect model meta-analyses were used to estimate the risk of each outcome among studies. Twenty two studies were identified, including 14 cohort studies, and 8 cross-sectional studies, with a total of 7,967,388 participants. This meta-analysis revealed that each 10 μg/m3 increment in PM2.5 was significantly associated with increased risks of both incidence and prevalence of CKD [adjusted odds ratio (OR) 1.31 (95% confidence interval (CI) 1.24 to 1.40), adjusted OR 1.31 (95% CI 1.03 to 1.67), respectively]. In addition, the relationship with ESKD incidence is suggestive of increased risk but not conclusive (adjusted OR 1.16; 95% CI 1.00 to 1.36). The incidence and prevalence of CKD outcomes had a consistent association across all subgroups and adjustment variables. Our study observed an association between long-term PM2.5 exposure and the risks of CKD. However, more dedicated studies are required to show causation that warrants urgent action on PM2.5 to mitigate the global burden of CKD.
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Affiliation(s)
- Wannasit Wathanavasin
- Nephrology Unit, Department of Medicine, Charoenkrung Pracharak Hospital, Bangkok Metropolitan Administration, Bangkok, Thailand
| | - Athiphat Banjongjit
- Nephrology Unit, Department of Medicine, Vichaiyut Hospital, Bangkok, Thailand
| | - Jeerath Phannajit
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
- Division of Clinical Epidemiology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
- Center of Excellence for Metabolic Bone Disease in CKD Patients, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Somchai Eiam-Ong
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Paweena Susantitaphong
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand.
- Center of Excellence for Metabolic Bone Disease in CKD Patients, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
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5
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Xu W, Jia L, Lin Y, Zhang C, Sun X, Jiang L, Yao X, Wang N, Deng H, Wang S, Yang G. Association of air pollution and risk of chronic kidney disease: A systematic review and meta-analysis. J Biochem Mol Toxicol 2024; 38:e23610. [PMID: 38091339 DOI: 10.1002/jbt.23610] [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: 08/03/2023] [Accepted: 11/20/2023] [Indexed: 01/18/2024]
Abstract
Although epidemiological studies have evaluated the association between ambient air pollution and chronic kidney disease (CKD), the results remain mixed. To clarify the nature of the association, we conducted a comprehensive systematic review and meta-analysis to assess the global relationship between air pollution and CKD. The Web of Science, PubMed, Embase and Cochrane Library databases systematically were searched for studies published up to July 2023 and included 32 studies that met specific criteria. The random effects model was used to derive overall risk estimates for each pollutant. The meta-analysis estimated odds ratio (ORs) of risk for CKD were 1.42 (95% confidence interval [CI]: 1.31-1.54) for each 10 μg/m3 increase in PM2.5 ; 1.20 (95% CI: 1.14-1.26) for each 10 μg/m3 increase in PM10 ; 1.07 (95% CI: 1.05-1.09) for each 10 μg/m3 increase in NO2 ; 1.03 (95% CI: 1.02-1.03) for each 10 μg/m3 increase in NOX ; 1.07 (95% CI: 1.01-1.12) for each 1 ppb increase in SO2 ; 1.03 (95% CI: 1.00-1.05) for each 0.1 ppm increase in CO. Subgroup analysis showed that this effect varied by gender ratio, age, study design, exposure assessment method, and income level. Furthermore, PM2.5 , PM10 , and NO2 had negative effects on CKD even within the World Health Organization-recommended acceptable concentrations. Our results further confirmed the adverse effect of air pollution on the risk of CKD. These findings can contribute to enhance the awareness of the importance of reducing air pollution among public health officials and policymakers.
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Affiliation(s)
- Wenqi Xu
- Department of Food Nutrition and Safety, Dalian Medical University, Dalian, China
| | - Luzhu Jia
- Department of Epidemiology, Dalian Medical University, Dalian, China
| | - Yuxuan Lin
- Department of Food Nutrition and Safety, Dalian Medical University, Dalian, China
| | - Cong Zhang
- Department of Food Nutrition and Safety, Dalian Medical University, Dalian, China
| | - Xiance Sun
- Department of Occupational & Environmental Health, Dalian Medical University, Dalian, China
| | - Liping Jiang
- Department of Occupational & Environmental Health, Dalian Medical University, Dalian, China
| | - Xiaofeng Yao
- Department of Occupational & Environmental Health, Dalian Medical University, Dalian, China
| | - Ningning Wang
- Department of Food Nutrition and Safety, Dalian Medical University, Dalian, China
| | - Haoyuan Deng
- Department of Food Nutrition and Safety, Dalian Medical University, Dalian, China
| | - Shaopeng Wang
- Department of Cardiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Guang Yang
- Department of Food Nutrition and Safety, Dalian Medical University, Dalian, China
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6
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Wen F, Xie Y, Li B, Li P, Qi H, Zhang F, Sun Y, Zhang L. Combined effects of ambient air pollution and PM 2.5 components on renal function and the potential mediation effects of metabolic risk factors in China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 259:115039. [PMID: 37235899 DOI: 10.1016/j.ecoenv.2023.115039] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 05/28/2023]
Abstract
Growing evidence links long-term air pollution exposure with renal function. However, little research has been conducted on the combined effects of air pollutant mixture on renal function and multiple mediation effects of metabolic risk factors. This study enrolled 8996 adults without chronic kidney disease (CKD) at baseline from the CHCN-BTH cohort study. Three-year exposure to air pollutants [particulate matter ≤ 2.5 µm (PM2.5), PM10, PM1, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)] and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3-), sulfate (SO42-) and organic matter (OM)] were assessed using well-validated machine learning methods. Linear mixed models were applied to investigate the associations between air pollutants and estimated glomerular filtration rate (eGFR). Quantile G-computation was used to assess the combined effects of pollutant mixtures. Causal mediation analysis and Bayesian mediation analysis were employed to estimate the mediation effects of metabolic risk factors. An interquartile range increases in BC (-0.256, 95 %CI: -0.331, -0.180) and OM (-0.603, 95 %CI: -0.810, -0.397) were significantly associated with eGFR decline; while O3 (1.151, 95 %CI: 0.813, 1.489), PM10 (0.721, 95 %CI: 0.309, 1.133), NH4+ (0.990, 95 %CI: 0.638, 1.342), and NO3- (0.610, 95 %CI: 0.405, 0.815) were associated with higher eGFR. The combined effect of the PM2.5 component mixture was found to be associated with lower eGFR (-1.147, 95 % CI: -1.456, -0.839), with OM contributing 72.4 % of the negative effect. Univariate mediation analyses showed that high-density lipoprotein (HDL) mediated 7.1 %, 6.9 %, and 6.1 % effects of O3, BC, and OM, respectively. However, these mediation effects were not significant in Bayesian mediation analysis. These findings suggest the effect of the PM2.5 component mixture on eGFR decline and the strong contribution of OM. Metabolic risk factors may not mediate the effects of air pollutants. Further study is warranted to clarify the potential mechanisms involved.
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Affiliation(s)
- Fuyuan Wen
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yunyi Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Bingxiao Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Pandi Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Han Qi
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China; The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital and the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fengxu Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yuan Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
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7
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Nan N, Yan Z, Zhang Y, Chen R, Qin G, Sang N. Overview of PM 2.5 and health outcomes: Focusing on components, sources, and pollutant mixture co-exposure. CHEMOSPHERE 2023; 323:138181. [PMID: 36806809 DOI: 10.1016/j.chemosphere.2023.138181] [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: 12/06/2022] [Revised: 02/10/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
PM2.5 varies in source and composition over time and space as a complicated mixture. Consequently, the health effects caused by PM2.5 varies significantly over time and generally exhibit significant regional variations. According to numerous studies, a notable relationship exists between PM2.5 and the occurrence of many diseases, such as respiratory, cardiovascular, and nervous system diseases, as well as cancer. Therefore, a comprehensive understanding of the effect of PM2.5 on human health is critical. The toxic effects of various PM2.5 components, as well as the overall toxicity of PM2.5 are discussed in this review to provide a foundation for precise PM2.5 emission control. Furthermore, this review summarizes the synergistic effect of PM2.5 and other pollutants, which can be used to draft effective policies.
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Affiliation(s)
- Nan Nan
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
| | - Zhipeng Yan
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
| | - Yaru Zhang
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
| | - Rui Chen
- Beijing Key Laboratory of Occupational Safety and Health, Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology, Beijing, 100054, PR China; Beijing City University, Beijing, 11418, PR China.
| | - Guohua Qin
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China.
| | - Nan Sang
- College of Environment and Resource, Shanxi University, Taiyuan, Shanxi, 030006, PR China
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8
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Wei S, Semple S. Exposure to fine particulate matter (PM 2.5) from non-tobacco sources in homes within high-income countries: a systematic review. AIR QUALITY, ATMOSPHERE, & HEALTH 2022; 16:553-566. [PMID: 36467893 PMCID: PMC9703437 DOI: 10.1007/s11869-022-01288-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 11/19/2022] [Indexed: 06/17/2023]
Abstract
UNLABELLED The health impacts associated with exposure to elevated concentrations of fine particulate matter (PM2.5) are well recognised. There is a substantial number of studies characterising PM2.5 concentrations outdoors, as well as in homes within low- and middle-income countries. In high-income countries (HICs), there is a sizeable literature on indoor PM2.5 relating to smoking, but the evidence on exposure to PM2.5 generated from non-tobacco sources in homes is sparse. This is especially relevant as people living in HICs spend the majority of their time at home, and in the northern hemisphere households often have low air exchange rates for energy efficiency. This review identified 49 studies that described indoor PM2.5 concentrations generated from a variety of common household sources in real-life home settings in HICs. These included wood/solid fuel burning appliances, cooking, candles, incense, cleaning and humidifiers. The reported concentrations varied widely, both between sources and within groups of the same source. The burning of solid fuels was found to generate the highest indoor PM2.5 concentrations. On occasion, other sources were also reported to be responsible for high PM2.5 concentrations; however, this was only in a few select examples. This review also highlights the many inconsistencies in the ways data are collected and reported. The variable methods of measurement and reporting make comparison and interpretation of data difficult. There is a need for standardisation of methods and agreed contextual data to make household PM2.5 data more useful in epidemiological studies and aid comparison of the impact of different interventions and policies. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s11869-022-01288-8.
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Affiliation(s)
- Shuying Wei
- Faculty of Health Sciences and Sport, University of Stirling, Stirling, FK9 4LA UK
| | - Sean Semple
- Institute for Social Marketing and Health, University of Stirling, Stirling, FK9 4LA UK
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9
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Fine Particulate Matter Exposure Levels in Patients with Normal-Tension Glaucoma and Primary Open-Angle Glaucoma: A Population-Based Study from Taiwan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19074224. [PMID: 35409910 PMCID: PMC8998620 DOI: 10.3390/ijerph19074224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/28/2022] [Accepted: 03/29/2022] [Indexed: 11/20/2022]
Abstract
Patients with NTG or POAG with more than one outpatient or discharge diagnosis from the ophthalmology department were included in the study. These data were merged with the PM2.5 data from the Air Quality Monitoring Network for analysis. This was a case−control study, with 1006 participants in the NTG group and 2533 in the POAG group. To investigate fine particulate matter (PM2.5) exposure levels in patients with normal-tension glaucoma (NTG) and primary open-angle glaucoma (POAG), patient data were obtained from Taiwan’s Longitudinal Health Insurance Database 2000 for the 2008 to 2013 period. We used a multivariate logic regression model to assess the risk for each participant. The PM2.5 exposure levels were divided into four groups: <25th percentile (Q1), <617 μg/mm3; 25th to 50th percentile (Q2), 617 to 1297 μg/mm3; 50th to 75th percentile (Q3), 1297 to 2113 μg/mm3; and >75th percentile (Q4), >2113 μg/mm3. The results are expressed in terms of odds ratio (OR) and 95% CI. A multiple logistic regression was used to compare the results of the NTG group with those of the POAG group. Compared with the PM2.5 Q1 level, the OR of the PM2.5 Q2 level was 1.009 (95% CI 0.812−1.254), the PM2.5 Q3 level was 1.241 (95% CI 1.241−1.537, p < 0.05), and the PM2.5 Q4 level was 1.246 (95% CI 1.008−1.539, p < 0.05). Our research reveals that compared with POAG, the risk of developing NTG is more closely related with PM2.5 exposure, and PM2.5 has a concentration−dose effect. It is hoped that in the future, in the clinical judgment of NTG and POAG, the level of PM2.5 in the environment can be taken as a risk factor.
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10
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Huang J, Kwan MP, Cai J, Song W, Yu C, Kan Z, Yim SHL. Field Evaluation and Calibration of Low-Cost Air Pollution Sensors for Environmental Exposure Research. SENSORS 2022; 22:s22062381. [PMID: 35336552 PMCID: PMC8948698 DOI: 10.3390/s22062381] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/15/2022] [Accepted: 03/16/2022] [Indexed: 02/04/2023]
Abstract
This paper seeks to evaluate and calibrate data collected by low-cost particulate matter (PM) sensors in different environments and using different aggregated temporal units (i.e., 5-s, 1-min, 10-min, 30 min intervals). We first collected PM concentrations (i.e., PM1, PM2.5, and PM10) data in five different environments (i.e., indoor and outdoor of an office building, a train platform and lobby of a subway station, and a seaside location) in Hong Kong, using five AirBeam2 sensors as the low-cost sensors and a TSI DustTrak DRX Aerosol Monitor 8533 as the reference sensor. By comparing the collected PM concentrations, we found high linearity and correlation between the data reported by the AirBeam2 sensors in different environments. Furthermore, the results suggest that the accuracy and bias of the PM data reported by the AirBeam2 sensors are affected by rainy weather and environments with high humidity and a high level of hygroscopic salts (i.e., a seaside location). In addition, increasing the aggregation level of the temporal units (i.e., from 5-s to 30 min intervals) increases the correlation between the PM concentrations obtained by the AirBeam2 sensors, while it does not significantly improve the accuracy and bias of the data. Lastly, our results indicate that using a machine learning model (i.e., random forest) for the calibration of PM concentrations collected on sunny days generates better results than those obtained with multiple linear models. These findings have important implications for researchers when designing environmental exposure studies based on low-cost PM sensors.
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Affiliation(s)
- Jianwei Huang
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Mei-Po Kwan
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, China
- Correspondence:
| | - Jiannan Cai
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Wanying Song
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Changda Yu
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Zihan Kan
- Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China; (J.H.); (J.C.); (W.S.); (C.Y.); (Z.K.)
| | - Steve Hung-Lam Yim
- Asian School of the Environment, Nanyang Technological University, Singapore 639798, Singapore;
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 639798, Singapore
- Earth Observatory of Singapore, Nanyang Technological University, Singapore 639798, Singapore
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Rasking L, Vanbrabant K, Bové H, Plusquin M, De Vusser K, Roels HA, Nawrot TS. Adverse Effects of fine particulate matter on human kidney functioning: a systematic review. Environ Health 2022; 21:24. [PMID: 35135544 PMCID: PMC8822715 DOI: 10.1186/s12940-021-00827-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 12/27/2021] [Indexed: 05/24/2023]
Abstract
BACKGROUND Ambient fine particulate matter (PM < 2.5 μm, PM2.5) is gaining increasing attention as an environmental risk factor for health. The kidneys are considered a particularly vulnerable target to the toxic effects that PM2.5 exerts. Alteration of kidney function may lead to a disrupted homeostasis, affecting disparate tissues in the body. This review intends to summarize all relevant knowledge published between January 2000 and December 2021 on the effects of ambient PM2.5 and the adverse effects on kidney function in adults (≥ 18 years). RESULTS AND DISCUSSION Studies published in peer-reviewed journals, written in English, regarding the effects of PM2.5 on kidney function and the development and/or exacerbation of kidney disease(s) were included. Of the 587 nonduplicate studies evaluated, 40 were included, comprising of studies on healthy or diagnosed with pre-existing disease (sub)populations. Most of the studies were cohort studies (n = 27), followed by 10 cross-sectional, 1 ecological and 2 time-series studies. One longitudinal study was considered intermediate risk of bias, the other included studies were considered low risk of bias. A large portion of the studies (n = 36) showed that PM2.5 exposure worsened kidney outcome(s) investigated; however, some studies show contradictory results. Measurement of the estimated glomerular filtration rate, for instance, was found to be positively associated (n = 8) as well as negatively associated (n = 4) with PM2.5. LIMITATIONS AND CONCLUSION The main limitations of the included studies include residual confounding (e.g., smoking) and lack of individual exposure levels. The majority of included studies focused on specific subpopulations, which may limit generalizability. Evidence of the detrimental effects that ambient PM2.5 may exert on kidney function is emerging. However, further investigations are required to determine how and to what extent air pollution, specifically PM2.5, exerts adverse effects on the kidney and alters its function. REGISTRATION The systematic review protocol was submitted and published by the International Prospective Register of Systematic Reviews (PROSPERO; CRD42020175615 ).
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Affiliation(s)
- Leen Rasking
- Centre for Environmental Sciences, Hasselt University, Agoralaan Gebouw D, B-3590, Diepenbeek, Belgium
| | - Kenneth Vanbrabant
- Centre for Environmental Sciences, Hasselt University, Agoralaan Gebouw D, B-3590, Diepenbeek, Belgium
| | - Hannelore Bové
- Centre for Environmental Sciences, Hasselt University, Agoralaan Gebouw D, B-3590, Diepenbeek, Belgium
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Agoralaan Gebouw D, B-3590, Diepenbeek, Belgium
| | - Katrien De Vusser
- Nephrology and Kidney Transplantation, University Hospital Leuven, Leuven, Belgium
- Department of Microbiology, Immunology, and Transplantation, Leuven University, Leuven, Belgium
| | - Harry A Roels
- Centre for Environmental Sciences, Hasselt University, Agoralaan Gebouw D, B-3590, Diepenbeek, Belgium
- Louvain Centre for Toxicology and Applied Pharmacology, Université catholique de Louvain, Brussels, Belgium
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Agoralaan Gebouw D, B-3590, Diepenbeek, Belgium.
- Department of Public Health and Primary Care, Environment and Health Unit, Leuven University, Leuven, Belgium.
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Chen Y, Cao F, Xiao JP, Fang XY, Wang XR, Ding LH, Wang DG, Pan HF. Emerging role of air pollution in chronic kidney disease. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:52610-52624. [PMID: 34448134 DOI: 10.1007/s11356-021-16031-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 08/14/2021] [Indexed: 06/13/2023]
Abstract
Chronic kidney disease (CKD), a global disease burden related to high rates of incidence and mortality, manifests as progressive and irretrievable nephron loss and decreased kidney regeneration capacity. Emerging studies have suggested that exposure to air pollution is closely relevant to increased risk of CKD, CKD progression and end-stage kidney disease (ESKD). Inhaled airborne particles may cause vascular injury, intraglomerular hypertension, or glomerulosclerosis through non-hemodynamic and hemodynamic factors with multiple complex interactions. The mechanisms linking air pollutants exposure to CKD include elevated blood pressure, worsening oxidative stress and inflammatory response, DNA damage and abnormal metabolic changes to aggravate kidney damage. In the present review, we will discuss the epidemiologic observations linking air pollutants exposure to the incidence and progression of CKD. Then, we elaborate the potential roles of several air pollutants including particulate matter and gaseous co-pollutants, environmental tobacco smoke, and gaseous heavy metals in its pathogenesis. Finally, this review outlines the latent effect of air pollution in ESKD patients undergoing dialysis or renal transplant, kidney cancer and other kidney diseases. The information obtained may be beneficial for further elucidating the pathogenesis of CKD and making proper preventive strategies for this disease.
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Affiliation(s)
- Yue Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Fan Cao
- Department of Ophthalmology, The Second Affiliated Hospital of Anhui Medical University, 678 Furong Road, Hefei, Anhui, China
| | - Jian-Ping Xiao
- Department of Nephrology, Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Xin-Yu Fang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China
| | - Xue-Rong Wang
- Department of Nephrology, Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - Li-Hong Ding
- Department of Nephrology, Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
| | - De-Guang Wang
- Department of Nephrology, Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
| | - Hai-Feng Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China.
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