Dataset Information

Indoor air quality in inner-city schools and its associations with building characteristics and environmental factors.

ABSTRACT: Indoor concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and carbon monoxide (CO) were measured across 16 urban public schools in three different seasons. Exceedance of the WHO guidelines for indoor air was observed, mainly for the hourly average NO2 concentrations. Seasonal variability was statistically significant for indoor NO2 and CO concentrations, with higher exposures in fall and winter. An extensive list of potential factors at the outdoor environment, school, and room level that may explain the variability in indoor exposure was examined. Factors with significant contributions to indoor exposure were mostly related to the outdoor pollution sources. This is evidenced by the strong associations between indoor concentration of CO and NO2 and factors including outdoor PM2.5 and NO2 concentrations, including length of the nearby roads and the number of nearby industrial facilities. Additionally, we found that poor conditions of the buildings (a prevalent phenomenon in the studied urban area), including physical defects and lack of proper ventilation, contributed to poor air quality in schools. The results suggest that improving building conditions and facilities as well as a consideration of the school surroundings may improve indoor air quality in schools.

SUBMITTER: Majd E

PROVIDER: S-EPMC6360122 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Indoor air quality in inner-city schools and its associations with building characteristics and environmental factors.

Majd Ehsan E McCormack Meredith M Davis Meghan M Curriero Frank F Berman Jesse J Connolly Faith F Leaf Philip P Rule Ana A Green Timothy T Clemons-Erby Dorothy D Gummerson Christine C Koehler Kirsten K

Environmental research 20181207

Indoor concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and carbon monoxide (CO) were measured across 16 urban public schools in three different seasons. Exceedance of the WHO guidelines for indoor air was observed, mainly for the hourly average NO2 concentrations. Seasonal variability was statistically significant for indoor NO2 and CO concentrations, with higher exposures in fall and winter. An extensive list of potential fa ...[more]

PMID: 30576993

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Project description:BackgroundSchool classrooms, where students spend the majority of their time during the day, are the second most important indoor microenvironment for children.ObjectiveWe investigated factors influencing classroom exposures to fine particulate matter (PM2.5), black carbon (BC), and nitrogen dioxide (NO2) in urban schools in the northeast United States.MethodsOver the period of 10 y (2008-2013; 2015-2019) measurements were conducted in 309 classrooms of 74 inner-city schools during fall, winter, and spring of the academic period. The data were analyzed using adaptive mixed-effects least absolute shrinkage and selection operator (LASSO) regression models. The LASSO variables included meteorological-, school-, and classroom-based covariates.ResultsLASSO identified 10, 10, and 11 significant factors (p<0.05) that were associated with indoor PM2.5, BC, and NO2 exposures, respectively. The overall variability explained by these models was R2=0.679, 0.687, and 0.621 for PM2.5, BC, and NO2, respectively. Of the model's explained variability, outdoor air pollution was the most important predictor, accounting for 53.9%, 63.4%, and 34.1% of the indoor PM2.5, BC, and NO2 concentrations. School-based predictors included furnace servicing, presence of a basement, annual income, building type, building year of construction, number of classrooms, number of students, and type of ventilation that, in combination, explained 18.6%, 26.1%, and 34.2% of PM2.5, BC, and NO2 levels, whereas classroom-based predictors included classroom floor level, classroom proximity to cafeteria, number of windows, frequency of cleaning, and windows facing the bus area and jointly explained 24.0%, 4.2%, and 29.3% of PM2.5, BC, and NO2 concentrations, respectively.DiscussionThe adaptive LASSO technique identified significant regional-, school-, and classroom-based factors influencing classroom air pollutant levels and provided robust estimates that could potentially inform targeted interventions aiming at improving children's health and well-being during their early years of development. https://doi.org/10.1289/EHP10007.

Project description:BACKGROUND:The associations between indoor environmental quality (IEQ) in homes and symptom reporting of children have been extensively studied, but only few large-scale studies have been done in schools. We examined associations between expert-assessed IEQ in schools and pupils' reporting of different symptoms, and whether associations were stronger if participants relate symptoms to the school environment. METHODS:The questionnaire survey was done in all primary and secondary schools in two areas of Helsinki, Finland. Primary school pupils (grade 3-6, n = 8775, 99 school-buildings) and secondary school pupils (grade 7-9, n = 3410, 30 school-buildings) reported their symptoms. Symptoms were combined into respiratory, lower respiratory, eye, skin, and general symptom groups. Surveys were also done among the parents of the primary school pupils (grade 1-6, n = 3540, 88 school buildings), but results are reported only in the supplement due to the low response rate (20% in 2017 and 13% in 2018). The associations between IEQ and symptoms were analyzed using multilevel logistic regression analysis. RESULTS:Several of the IEQ indicators were highly correlated and indicators were therefore mainly analyzed by combining them into a summary score and into latent classes. Dose-response associations were found between IEQ problems and higher reporting of respiratory and general symptoms among both primary and secondary school pupils. Some associations were also observed with lower respiratory and skin symptoms, but not with eye symptoms. The associations were somewhat stronger with symptoms related to the school environment compared to symptoms reported without such relation: for a unit change in IEQ summary score and respiratory symptoms in primary schools, odds ratios were 1.07 (95% CI 1.02-1.06) and 1.04 (95% CI 1.04-1.10), and in secondary schools 1.09 (95% CI 1.01-1.09) and 1.05 (95% CI 1.02-1.17), respectively. CONCLUSIONS:Expert-assessed IEQ problems in schools were associated with increased reporting of especially respiratory and general symptoms. The associations were only somewhat stronger in magnitude for symptoms reported in relation to the school environment compared to symptoms reported without such relation.

Project description:INTRODUCTION:Exposure to poor environmental conditions has been associated with deterioration of physical and mental health, and with reduction of cognitive performance. Environmental conditions may also influence cognitive development of children, but epidemiological evidence is scant. In developed countries, children spend 930 hours per year in a classroom, second only to time spent in their bedroom. Using continuous sensing technology, we investigate the relationship between indoor environmental quality (IEQ) and cognitive performance of school-aged children. The proposed study will result in a better understanding of the effects of environmental characteristics on cognitive performance, thereby paving the way for experimental studies. METHODS AND ANALYSIS:A study protocol is presented to reliably measure IEQ in schools. We will monitor the IEQ of 280 classrooms for 5 years, covering approximately 10 000 children. Each classroom in the sample is permanently equipped with a sensor measuring air quality (carbon dioxide and coarse particles), temperature, relative humidity, light intensity and noise levels, all at 1 min intervals. The location of sensing equipment within and across rooms has been validated by a pilot study. Academic performance of school-aged children is measured through standardised cognitive tests. In addition, a series of health indicators is collected (eg, school absence and demand for healthcare), together with an extensive set of sociodemographic characteristics (eg, parental income, education, occupational status). ETHICS AND DISSEMINATION:Medical Ethical Approval for the current study was waived by the Medical Ethical Committee azM/UM (METC 2018-0681). In addition, data on student performance and health stems from an already existing data infrastructure that are granted with ethical approval by the Ethical Review Committee Inner City faculties (ERCIC_092_12_07_2018). Health data are obtained from the 'The Healthy Primary School of the Future' (HPSF) project. Medical Ethical Approval for HPSF was waived by the Medical Ethical Committee of Zuyderland, Heerlen (METC 14 N-142). The HPSF study protocol was registered in the database ClinicalTrials.gov on 14-06-2016 with reference number NCT02800616, this study is currently in the Results stage. Data collection from Gemeentelijke Gezondheidsdienst Zuid-Limburg (GGD-ZL) is executed by researchers of HPSF, this procedure has been fully approved by the Medical Ethical Committee of Zuyderland. The questionnaires on level of comfort will be filled in anonymously by students and teachers. The study will follow the EU General Data Protection Regulation (EU GDPR) and Dutch data protection law to ensure protection of personal data, as well as maintain proper data management and anonymisation.The protocol discussed in this paper includes significant efforts focused on integrating results and making them available to both the scientific community and the wider public, including policy makers. The results will lead to multiple scientific articles that will be disseminated through peer-reviewed international journals, as well as through conference presentations. In addition, we will exploit ongoing collaboration with project stakeholders and project partners to disseminate information to the target audience. For example, the results will be presented to school boards in the Netherlands, through engagement with the Coalition for Green Schools, as well as to school boards in USA, through engagement with the Center for Green Schools. TRIAL REGISTRATION NUMBER:NCT02800616; Results.

Dataset Information

Indoor air quality in inner-city schools and its associations with building characteristics and environmental factors.

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Indoor air quality in inner-city schools and its associations with building characteristics and environmental factors.

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