Dataset Information

Fine particles in homes of predominantly low-income families with children and smokers: Key physical and behavioral determinants to inform indoor-air-quality interventions.

ABSTRACT: Children are at risk for adverse health outcomes from occupant-controllable indoor airborne contaminants in their homes. Data are needed to design residential interventions for reducing low-income children's pollutant exposure. Using customized air quality monitors, we continuously measured fine particle counts (0.5 to 2.5 microns) over a week in living areas of predominantly low-income households in San Diego, California, with at least one child (under age 14) and at least one cigarette smoker. We performed retrospective interviews on home characteristics, and particle source and ventilation activities occurring during the week of monitoring. We explored the relationship between weekly mean particle counts and interview responses using graphical visualization and multivariable linear regression (base sample n = 262; complete cases n = 193). We found associations of higher weekly mean particle counts with reports of indoor smoking of cigarettes or marijuana, as well as with frying food, using candles or incense, and house cleaning. Lower particle levels were associated with larger homes. We did not observe an association between lower mean particle counts and reports of opening windows, using kitchen exhaust fans, or other ventilation activities. Our findings about sources of fine airborne particles and their mitigation can inform future studies that investigate more effective feedback on residential indoor-air-quality and better strategies for reducing occupant exposures.

SUBMITTER: Klepeis NE

PROVIDER: S-EPMC5435241 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Fine particles in homes of predominantly low-income families with children and smokers: Key physical and behavioral determinants to inform indoor-air-quality interventions.

Klepeis Neil E NE Bellettiere John J Hughes Suzanne C SC Nguyen Benjamin B Berardi Vincent V Liles Sandy S Obayashi Saori S Hofstetter C Richard CR Blumberg Elaine E Hovell Melbourne F MF

PloS one 20170517 5

Children are at risk for adverse health outcomes from occupant-controllable indoor airborne contaminants in their homes. Data are needed to design residential interventions for reducing low-income children's pollutant exposure. Using customized air quality monitors, we continuously measured fine particle counts (0.5 to 2.5 microns) over a week in living areas of predominantly low-income households in San Diego, California, with at least one child (under age 14) and at least one cigarette smoker. ...[more]

PMID: 28545099

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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:INTRODUCTION:Exposure to fine particulate matter in the home from sources such as smoking, cooking, and cleaning may put residents, especially children, at risk for detrimental health effects. A randomized clinical trial was conducted from 2011 to 2016 to determine whether real-time feedback in the home plus brief coaching of parents or guardians could reduce fine particle levels in homes with smokers and children. DESIGN:A randomized trial with two groups-intervention and control. SETTING/PARTICIPANTS:A total of 298 participants from predominantly low-income households with an adult smoker and a child aged <14 years. Participants were recruited during 2012-2015 from multiple sources in San Diego, mainly Women, Infants and Children Program sites. INTERVENTION:The multicomponent intervention consisted of continuous lights and brief sound alerts based on fine particle levels in real time and four brief coaching sessions using particle level graphs and motivational interviewing techniques. Motivational interviewing coaching focused on particle reduction to protect children and other occupants from elevated particle levels, especially from tobacco-related sources. MAIN OUTCOME MEASURES:In-home air particle levels were measured by laser particle counters continuously in both study groups. The two outcomes were daily mean particle counts and percentage time with high particle concentrations (>15,000 particles/0.01 ft3). Linear mixed models were used to analyze the differential change in the outcomes over time by group, during 2016-2017. RESULTS:Intervention homes had significantly larger reductions than controls in daily geometric mean particle concentrations (18.8% reduction vs 6.5% reduction, p<0.001). Intervention homes' average percentage time with high particle concentrations decreased 45.1% compared with a 4.2% increase among controls (difference between groups p<0.001). CONCLUSIONS:Real-time feedback for air particle levels and brief coaching can reduce fine particle levels in homes with smokers and young children. Results set the stage for refining feedback and possible reinforcing consequences for not generating smoke-related particles. TRIAL REGISTRATION:This study is registered at www.clinicaltrials.gov NCT01634334.

Dataset Information

Fine particles in homes of predominantly low-income families with children and smokers: Key physical and behavioral determinants to inform indoor-air-quality interventions.

Publications

Fine particles in homes of predominantly low-income families with children and smokers: Key physical and behavioral determinants to inform indoor-air-quality interventions.

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