Particle concentrations in inner-city homes of children with asthma: the effect of smoking, cooking, and outdoor pollution.

Wallace, Lance A.; Mitchell, Herman; O’Connor, George T.; Neas, Lucas M.; Lippmann, Morton; Kattan, Meyer; Koenig, Jane Q.; Stout, James; Vaughn, Ben; Wallace, Dennis; Walter, Michelle; Adams, Ken; Liu, Lee-Jane Sally

doi:10.1289/ehp.6135

Cited by 210 publications

(198 citation statements)

References 36 publications

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“…Season-specific models are also supported by the strong relationship between F inf and air exchange rates, which in turn are seasonal dependent (Janssen et al, 2002;Wallace et al, 2003;Koenig et al, 2005;Strand et al, 2006).…”

Section: Infiltration (F Inf ) Modeling Resultsmentioning

confidence: 86%

“…Studies examining residential PM 2.5 infiltration (F inf , defined as the fraction of ambient PM 2.5 that penetrates indoors and remains suspended) have found substantial variation both between residences and within residences over time (Allen et al, 2003;Wallace et al, 2003;Meng et al, 2005;Wallace and Williams, 2005;Barn et al, 2007). As individuals spend, on average, nearly 70% of their time inside their homes (Klepeis et al, 2001), failure to consider F inf differences may contribute to exposure misclassification and impact the precision and magnitude of health effect estimates in epidemiological studies.…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies have demonstrated correlations between F inf and a number of building, meteorological and behavioral factors; however, such studies do not use data readily available for large populations. Factors found to be related to F inf include housing variables such as age, size, value, square footage, and ventilation conditions (Wallace, 1996;Sherman and Dickerhoff, 1998;Ozkaynak et al, 1999;Ebelt et al, 2000;Sherman and Matson, 2001;Thornburg et al, 2001;McKone et al, 2002;Hanninen et al, 2005;Chan et al, 2005); meteorological factors including temperature and exposure to wind and precipitation (Sherman and Dickerhoff, 1998;Chao and Tung, 2001;McKone et al, 2002); and occupant behaviors and characteristics, such as occupant income, window opening, and use of air conditioners and air filters (Sherman and Dickerhoff, 1998;Mosley et al, 2001;Janssen et al, 2002;Wallace et al, 2003;Koenig et al, 2005). A study by Chan et al (2005) analyzed approximately 70,000 air leakage measurements (a parameter related to F inf ) in the United State to determine predictive housing characteristics and found year of construction, size of dwelling and whether the dwelling was either energy-efficient or occupied by a low-income family to be important predictors of normalized leakage.…”

Section: Introductionmentioning

confidence: 99%

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Modeling residential fine particulate matter infiltration for exposure assessment

Hystad

Setton

Allen

et al. 2008

J Expo Sci Environ Epidemiol

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Individuals spend the majority of their time indoors; therefore, estimating infiltration of outdoor-generated fine particulate matter (PM 2.5 ) can help reduce exposure misclassification in epidemiological studies. As indoor measurements in individual homes are not feasible in large epidemiological studies, we evaluated the potential of using readily available data to predict infiltration of ambient PM 2.5 into residences. Indoor and outdoor light scattering measurements were collected for 84 homes in Seattle, Washington, USA, and Victoria, British Columbia, Canada, to estimate residential infiltration efficiencies. Meteorological variables and spatial property assessment data (SPAD), containing detailed housing characteristics for individual residences, were compiled for both study areas using a geographic information system. Multiple linear regression was used to construct models of infiltration based on these data. Heating (October to February) and non-heating (March to September) season accounted for 36% of the yearly variation in detached residential infiltration. Two SPAD housing characteristic variables, low building value, and heating with forced air, predicted 37% of the variation found between detached residential infiltration during the heating season. The final model, incorporating temperature and the two SPAD housing characteristic variables, with a seasonal interaction term, explained 54% of detached residential infiltration. Residences with low building values had higher infiltration efficiencies than other residences, which could lead to greater exposure gradients between low and high socioeconomic status individuals than previously identified using only ambient PM 2.5 concentrations. This modeling approach holds promise for incorporating infiltration efficiencies into large epidemiology studies, thereby reducing exposure misclassification.

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Section: Infiltration (F Inf ) Modeling Resultsmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modeling residential fine particulate matter infiltration for exposure assessment

Hystad

Setton

Allen

et al. 2008

J Expo Sci Environ Epidemiol

View full text Add to dashboard Cite

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“…Without ETS, the contribution of within-subject variation to total variance was of the same magnitude for indoor and personal concentrations. In another population group susceptible for air pollution effects, asthmatic children, the within-subject variation was also found to account for over half of the total variation in indoor PM 2.5 (Wallace et al, 2003). Among adults, day-to-day variation in exposure has been observed to be higher than interpersonal variability also for the pollutants NO 2 and SO 2 (Lee et al, 2004).…”

Section: Discussionmentioning

confidence: 91%

“…The information can also be used in the construction of exposure models. The determinants of PM 2.5 most often identified (besides outdoor concentrations) are exposure to environmental tobacco smoke (ETS) and cooking events (Ö zkaynak et al, 1996;Wallace et al, 2003;He et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Determinants of personal and indoor PM2.5 and absorbance among elderly subjects with coronary heart disease

Lanki¹,

Ahokas²,

Alm³

et al. 2006

J Expo Sci Environ Epidemiol

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Epidemiological studies have established an association between outdoor levels of fine particles (PM 2.5 ) and cardiovascular health. However, there is little information on the determinants of PM 2.5 exposures among persons with cardiovascular disease, a potentially susceptible population group. Daily outdoor, indoor and personal PM 2.5 and absorbance (proxy for elemental carbon) concentrations were measured among elderly subjects with cardiovascular disease in Amsterdam, the Netherlands, and Helsinki, Finland, during the winter and spring of 1998-1999 within the framework of the ULTRA study. There were 37 non-smoking subjects in Amsterdam and 47 in Helsinki. In Amsterdam, where there were enough exposure events for analyses, exposure to environmental tobacco smoke (ETS) indoors was a major source of between-subject variation in PM 2.5 exposures, and a strong determinant of PM 2.5 and absorbance exposures. When the days with ETS were excluded, within-subject variation accounted for 89% of the total variation in personal PM 2.5 and 97% in absorbance in Amsterdam. The respective figures were 66% and 61% in Helsinki. In both cities, outdoor levels of PM 2.5 and absorbance were major determinants of personal and indoor levels. Traffic was also an important determinant of absorbance: living near a major street increased exposure by 22%, and every hour spent in a motor vehicle by 13% in Amsterdam. The respective increases were 37% and 9% in Helsinki. Cooking was associated with increased levels of both absorbance and PM 2.5 . Our results demonstrate that by using questionnaires in connection with outdoor measurements, exposure estimation of PM 2.5 and its combustion originating fraction can be improved among elderly persons with compromised health.

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A Randomized Trial of Air Cleaners and a Health Coach to Improve Indoor Air Quality for Inner-City Children With Asthma and Secondhand Smoke Exposure

Butz

Matsui

Breysse

et al. 2011

Arch Pediatr Adolesc Med

144

168

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Objective: To test an air cleaner and health coach intervention to reduce secondhand smoke exposure compared with air cleaners alone or no air cleaners in reducing particulate matter (PM), air nicotine, and urine cotinine concentrations and increasing symptom-free days in children with asthma residing with a smoker. Design: Randomized controlled trial, with randomization embedded in study database. Settings: The Johns Hopkins Hospital Children’s Center and homes of children. Participants: Children with asthma, residing with a smoker, randomly assigned to interventions consisting of air cleaners only (n=41), air cleaners plus a health coach (n=41), or delayed air cleaner (control) (n=44). Main Outcome Measures: Changes in PM, air nicotine, and urine cotinine concentrations and symptom-free days during the 6-month study. Results: The overall follow-up rate was high (91.3%). Changes in mean fine and coarse PM (PM2.5 and PM2.5–10) concentrations (baseline to 6 months) were significantly lower in both air cleaner groups compared with the control group (mean differences for PM2.5 concentrations: control, 3.5 μg/m3; air cleaner only, −19.9 μg/m3; and air cleaner plus health coach, −16.1 μg/m3; P=.003; and PM2.5–10 concentrations: control, 2.4 μg/m3; air cleaner only, −8.7 μg/m3; and air cleaner plus health coach, −10.6 μg/m3; P=.02). No differences were noted in air nicotine or urine cotinine concentrations. The health coach provided no additional reduction in PM concentrations. Symptom-free days were significantly increased in both air cleaner groups compared with the control group (P=.03). Conclusion: Although the use of air cleaners can result in a significant reduction in indoor PM concentrations and a significant increase in symptom-free days, it is not enough to prevent exposure to secondhand smoke.

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Particle concentrations in inner-city homes of children with asthma: the effect of smoking, cooking, and outdoor pollution.

Abstract: Investigators in the Inner-City Asthma Study are listed in the Appendix. We thank the participants for making their homes available to us for 2-week periods. We also thank our excellent staff for performing the many tasks involved in a multiyear, multicity field study.

Cited by 210 publications

References 36 publications

Modeling residential fine particulate matter infiltration for exposure assessment

Modeling residential fine particulate matter infiltration for exposure assessment

Determinants of personal and indoor PM2.5 and absorbance among elderly subjects with coronary heart disease

A Randomized Trial of Air Cleaners and a Health Coach to Improve Indoor Air Quality for Inner-City Children With Asthma and Secondhand Smoke Exposure

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