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Xu J, Zhao H, Zhang Y, Yang W, Wang X, Geng C, Li Y, Guo Y, Han B, Bai Z, Vedal S, Marshall JD. Reducing Indoor Particulate Air Pollution Improves Student Test Scores: A Randomized Double-Blind Crossover Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:8207-8214. [PMID: 38647545 DOI: 10.1021/acs.est.3c10372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
Short-term exposure to air pollution is associated with a decline in cognitive function. Standardized test scores have been employed to evaluate the effects of air pollution exposure on cognitive performance. Few studies aimed to prove whether air pollution is responsible for reduced test scores; none have implemented a "gold-standard" method for assessing the association such as a randomized, double-blind intervention. This study used a "gold-standard" method─randomized, double-blind crossover─to assess whether reducing short-term indoor particle concentrations results in improved test scores in college students in Tianjin, China. Participants (n = 162) were randomly assigned to one of two similar classrooms and completed a standardized English test on two consecutive weekends. Air purifiers with active or sham (i.e., filter removed) particle filtration were placed in each classroom. The filtration mode was switched between the two test days. Linear mixed-effect models were used to evaluate the effect of the intervention mode on the test scores. The results show that air purification (i.e., reducing PM) was significantly associated with increases in the z score for combined (0.11 [95%CI: 0.02, 0.21]) and reading (0.11 [95%CI: 0.00, 0.22]) components. In conclusion, a short-term reduction in indoor particle concentration led to improved test scores in students, suggesting an improvement in cognitive function.
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Affiliation(s)
- Jia Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Hong Zhao
- College of Computer Science, Nankai University, Tianjin 300071, China
| | - Yujuan Zhang
- Department of Family Planning, The Second Hospital of Tianjin Medical University, Tianjin 300211, China
| | - Wen Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xinhua Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Chunmei Geng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yan Li
- College of Computer Science, Nankai University, Tianjin 300071, China
| | - Yun Guo
- College of Computer Science, Nankai University, Tianjin 300071, China
| | - Bin Han
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zhipeng Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington 98105, United States
| | - Sverre Vedal
- Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington 98105, United States
| | - Julian D Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington 98195, United States
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Ma X, Zou B, Deng J, Gao J, Longley I, Xiao S, Guo B, Wu Y, Xu T, Xu X, Yang X, Wang X, Tan Z, Wang Y, Morawska L, Salmond J. A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023. ENVIRONMENT INTERNATIONAL 2024; 183:108430. [PMID: 38219544 DOI: 10.1016/j.envint.2024.108430] [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: 09/03/2023] [Revised: 11/26/2023] [Accepted: 01/04/2024] [Indexed: 01/16/2024]
Abstract
Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.
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Affiliation(s)
- Xuying Ma
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China; College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China; International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Queensland 4000, Australia.
| | - Bin Zou
- School of Geosciences and Info-Physics, Central South University, Changsha, Hunan 410083, China.
| | - Jun Deng
- College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an 710054, China; Shaanxi Key Laboratory of Prevention and Control of Coal Fire, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Jay Gao
- School of Environment, Faculty of Science, University of Auckland, Auckland 1010, New Zealand
| | - Ian Longley
- National Institute of Water and Atmospheric Research, Auckland 1010, New Zealand
| | - Shun Xiao
- School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Bin Guo
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Yarui Wu
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Tingting Xu
- School of Software Engineering, Chongqing University of Post and Telecommunications, Chongqing 400065, China
| | - Xin Xu
- Xi'an Institute for Innovative Earth Environment Research, Xi'an 710061, China
| | - Xiaosha Yang
- Shandong Nova Fitness Co., Ltd., Baoji, Shaanxi 722404, China
| | - Xiaoqi Wang
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Zelei Tan
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Yifan Wang
- College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Queensland 4000, Australia.
| | - Jennifer Salmond
- School of Environment, Faculty of Science, University of Auckland, Auckland 1010, New Zealand
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Chalupka SM, Latter A, Trombley J. Climate and Environmental Change: A Generation at Risk. MCN Am J Matern Child Nurs 2023; 48:181-187. [PMID: 36943828 DOI: 10.1097/nmc.0000000000000924] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
ABSTRACT Climate and environmental changes have been described as the biggest global health threat of the 21st century, with the potential to cause immediate harm in early life with important lifelong effects, and important consequences for future generations. Pregnant women and children are increasingly being recognized as vulnerable populations in the context of climate change. The effects can be direct or indirect through heat stress, extreme weather events, and air pollution, potentially affecting both the immediate and long-term health of pregnant women and newborns through a broad range of mechanisms. Climate and environmental changes have wide-ranging effects on a woman's reproductive life including sexual maturation and fertility, pregnancy outcomes, lactation, breastfeeding, and menopause. A comprehensive overview of these impacts is presented as well as opportunities for interventions for nurses practicing in perinatal, neonatal, midwifery, and pediatric specialties.
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Kumar P, Singh AB, Arora T, Singh S, Singh R. Critical review on emerging health effects associated with the indoor air quality and its sustainable management. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162163. [PMID: 36781134 DOI: 10.1016/j.scitotenv.2023.162163] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Indoor air quality (IAQ) is one of the fundamental elements affecting people's health and well-being. Currently, there is a lack of awareness among people about the quantification, identification, and possible health effects of IAQ. Airborne pollutants such as volatile organic compounds (VOCs), particulate matter (PM), sulfur dioxide (SO2), carbon monoxide (CO), nitrous oxide (NO), polycyclic aromatic hydrocarbons (PAHs) microbial spores, pollen, allergens, etc. primarily contribute to IAQ deterioration. This review discusses the sources of major indoor air pollutants, molecular toxicity mechanisms, and their effects on cardiovascular, ocular, neurological, women, and foetal health. Additionally, contemporary strategies and sustainable methods for regulating and reducing pollutant concentrations are emphasized, and current initiatives to address and enhance IAQ are explored, along with their unique advantages and potentials. Due to their longer exposure times and particular physical characteristics, women and children are more at risk for poor indoor air quality. By triggering many toxicity mechanisms, including oxidative stress, DNA methylation, epigenetic modifications, and gene activation, indoor air pollution can cause a range of health issues. Low birth weight, acute lower respiratory tract infections, Sick building syndromes (SBS), and early death are more prevalent in exposed residents. On the other hand, the main causes of incapacity and early mortality are lung cancer, chronic obstructive pulmonary disease, and cardiovascular disorders. It's crucial to acknowledge anticipated research needs and implemented efficient interventions and policies to lower health hazards.
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Affiliation(s)
- Pradeep Kumar
- Department of Environmental Studies, Satyawati College, University of Delhi, Delhi 52, India
| | - A B Singh
- Institute of Genomics and Integrative Biology (IGIB), Mall Road Campus, Delhi 07, India
| | - Taruna Arora
- Division of Reproductive Biology, Maternal and Child Health, Indian Council of Medical Research, Ansari Nagar, New Delhi 110029, India
| | - Sevaram Singh
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, India; Jawaharlal Nehru University, New Mehrauli Road, New Delhi 110067, India
| | - Rajeev Singh
- Department of Environmental Studies, Satyawati College, University of Delhi, Delhi 52, India; Department of Environmental Science, Jamia Millia Islamia (A Central University), New Delhi 110025, India.
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He Q, Wang Y, Qiu Q, Su Y, Wang Y, Wei H, Li J. Joint effects of air PM 2.5 and socioeconomic dimensions on posted emotions of urban green space visitors in cities experiencing population urbanization: A pilot study on 50 cities of East China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 861:160607. [PMID: 36460101 DOI: 10.1016/j.scitotenv.2022.160607] [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: 07/21/2022] [Revised: 11/02/2022] [Accepted: 11/26/2022] [Indexed: 06/17/2023]
Abstract
People may perceive and expose negative sentiments in days with PM2.5 pollutions, but evidence is still insufficient about the joint effects of PM2.5 and socioeconomic factors on human sentiments. In this study, a total of 8032 facial photos of urban green space visitors were obtained from Sina Weibo in 50 cities of East China and rated for happy, sad, neutral scores and net positive emotion index (NPE; happy minus sad). Seasonal air PM2.5 concentrations were collected from days when people exposed faces in cities that were categorized to medium, large, outsize, and mega sizes according to resident populations (RPs). In summer, people posted lower sad score (11.28 %) than in winter (13.51 %; P = 0.0357) and higher NPE (35.86 %) than in autumn (30.92 %; P = 0.0009). Multivariate linear regression on natural logarithms revealed that factors of gross domestic product per capita (parameter estimate: 0.45), RP (0.59), non-production electricity consumption (0.34), and length of road transport (0.34) together generated positive contributions to posted happy score, while the total retail trade of consumer goods (-1.25) and PM2.5 (-0.50) were perceived as joint depressors on NPE. Overall, cities with more rich households and activated retail sales attracted more people who exposed smiles in weathers with PM2.5 compared to cities where local economy is reliable on heavy industry. The summertime in mega cities will be recommended to enjoy a higher frequency to perceive satisfaction due to exposure to low PM2.5.
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Affiliation(s)
- Qian He
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China.
| | - Yue Wang
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China.
| | - Quan Qiu
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China.
| | - Yan Su
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China.
| | - Yang Wang
- Department of Arts & Social Sciences, National University of Singapore, Arts Link 117570, Singapore.
| | - Hongxu Wei
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Jiyue Li
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou 510642, China.
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Hou X, Guo Q, Hong Y, Yang Q, Wang X, Zhou S, Liu H. Assessment of PM 2.5-related health effects: A comparative study using multiple methods and multi-source data in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 306:119381. [PMID: 35500711 DOI: 10.1016/j.envpol.2022.119381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 04/25/2022] [Accepted: 04/26/2022] [Indexed: 06/14/2023]
Abstract
In China, PM2.5 pollution has caused extensive death and economic loss. Thus, an accurate assessment of the spatial distribution of these losses is crucial for delineating priority areas for air pollution control in China. In this study, we assessed the PM2.5 exposure-related health effects according to the integrated exposure risk function and non-linear power law (NLP) function in 338 prefecture-level cities in China by utilizing online monitoring data and the PM2.5 Hindcast Database (PHD). Our results revealed no significant difference between the monitoring data and PHD (p value = 0.66 > 0.05). The number of deaths caused by PM2.5-related Stroke (cerebrovascular disease), ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer at the national level estimated through the NLP function was 0.27 million (95% CI: 0.06-0.50), 0.23 million (95% CI: 0.08-0.38), 0.31 million (95% CI: 0.04-0.57), and 0.31 million (95% CI: 0.16-0.40), respectively. The total economic cost at the national level in 2016 was approximately US$80.25 billion (95% CI: 24.46-132.25). Based on a comparison of Z statistics, we propose that the evaluation results obtained using the NLP function and monitoring data are accurate. Additionally, according to scenario simulations, Beijing, Chongqing, Tianjin, and other cities should be priority areas for PM2.5 pollution control to achieve considerable health benefits. Our statistics can help improve the accuracy of PM2.5-related health effect assessments in China.
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Affiliation(s)
- Xiaoyun Hou
- School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, 310016, China; Zhejiang Academy of Ecological Civilization, Hangzhou, 310016, China
| | - Qinghai Guo
- School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, 310016, China; Zhejiang Academy of Ecological Civilization, Hangzhou, 310016, China.
| | - Yan Hong
- School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, 310016, China
| | - Qiaowei Yang
- School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, 310016, China
| | - Xinkui Wang
- Dongying Development and Reform Commission, Dongying, 370502, China
| | - Siyang Zhou
- School of Environment, State Key Laboratory of Water Environment Simulation, Beijing Normal University, Beijing, 100875, China
| | - Haiqiang Liu
- School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, 310016, China
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Ammons S, Aja H, Ghazarian AA, Lai GY, Ellison GL. Perception of worry of harm from air pollution: results from the Health Information National Trends Survey (HINTS). BMC Public Health 2022; 22:1254. [PMID: 35752789 PMCID: PMC9233822 DOI: 10.1186/s12889-022-13450-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 05/17/2022] [Indexed: 11/28/2022] Open
Abstract
Background Air pollution exposure has been associated with a multitude of diseases and poses a significant concern to public health. For targeted environmental risk communication and interventions to be effective, it is important to correctly identify characteristics associated with worry of harm from air pollution. Methods Using responses from 3,630 participants of the Health Information National Trends Survey 4 Cycle 2, we assessed worry of harm from exposure to indoor (IAP) and outdoor (OAP) air pollution separately. Multinomial logistic regression models were used to calculate odds ratios and 95% confidence intervals. Results Hispanics were more likely to worry about harm from IAP and OAP compared to non-Hispanic whites. Participants who lived in metropolitan counties were more likely to worry about harm from IAP and OAP compared to those who lived in rural counties. Finally, those who believed their chance of getting cancer was high were more likely to worry about harm from IAP and OAP compared to those who thought their likelihood of getting cancer was low. Conclusions Worry of harm from IAP and OAP varied across sociodemographic and cancer-related characteristics. Public health professionals should consider these characteristics when developing targeted environmental risk communication and interventions. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-13450-z.
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Affiliation(s)
- Samantha Ammons
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, MD, Bethesda, USA
| | - Hayley Aja
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, MD, Bethesda, USA.,Extramural Research Branch, Extramural Research and Partnerships Division, Office of Science Advisor, Policy, and Engagement, U.S. Environmental Protection Agency, Washington, DC, USA
| | - Armen A Ghazarian
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, MD, Bethesda, USA
| | - Gabriel Y Lai
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, MD, Bethesda, USA
| | - Gary L Ellison
- Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, MD, Bethesda, USA.
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Abstract
PURPOSE OF REVIEW There is increasing interest in the links between exposure to air pollution and a range of health outcomes. The association with mental health however is much less established. This article reviews developments in the field over the past 12 months, highlighting the evidence for causation, associations between multiple air pollutants and mental health outcomes, and assesses the challenges of researching this topic. RECENT FINDINGS Increasingly rigorous methods are being applied to the investigation of a broader range of mental health outcomes. These methods include basic science, neuroimaging, and observational studies representing diverse geographical locations. Cohort studies with linked high-resolution air pollutant exposure data are common, facilitating advanced analytic methods. To date, meta-analyses have demonstrated small and significant positive associations between long-term exposure to fine particulate matter and depressive symptoms and cognitive decline. Methodological complexities in measuring exposure and outcome pose ongoing difficulties for the field. SUMMARY Literature on this topic has recently seen an appreciable expansion. Work that better estimates daily exposure, controls for complex confounders, and is driven by hypotheses founded in candidate causal mechanisms would help clarify associations, and inform targeted interventions and policymakers.
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