Nitrogen dioxide exposure assessment and cough among preschool children

Comparison of regression models with land-use and emissions data to predict the spatial distribution of traffic-related air pollution in Rome

Spatial modeling of traffic-related air pollution typically involves either regression modeling of land-use and traffic data or dispersion modeling of emissions data, but little is known to what extent land-use regression models might be improved by incorporating emissions data. The aim of this study was to develop a land-use regression model to predict nitrogen dioxide (NO2) concentrations and compare its performance with a model including emissions data. The association between each land-use variable and NO2 concentrations at 68 locations in Rome in 1995 and 1996 was assessed by univariate linear regression and a multiple linear regression model that was constructed based on the importance of each variable. Traffic emissions (particulate matter, carbon monoxide, nitrogen oxides, and benzene) were estimated for 164 areas of the city based on vehicle type, traffic counts and driving patterns. Mean NO2 concentration across the 68 sites was 46.8 microg/m3 (SD 9.8 microg/m3; inter-quartile range 11.5 microg/m3; min 24 microg/m3; max 73 microg/m3). The most important predicting variables were the circular traffic zones (main ring road, green strip, inner ring road, traffic-limited zone), distance from busy streets, size of the census block, the inverse population density, and altitude. A multiple regression model including these variables resulted in an R2 of 0.686. The best-fitting model adding an emission term of benzene resulted in an R2 of 0.690, but was not significantly different from the model without emissions (P=0.147). In conclusion, these results suggest that a land-use regression model explains the traffic-related air pollution levels with reasonable accuracy and that emissions data do not significantly improve the model.

A nationwide study of indoor and outdoor environments in allergen avoidance and conventional daycare centers in Sweden

Sweden has had specialized 'allergen avoidance daycare centers' (AADC) since 1979. The aim was to compare AADC with ordinary daycare centers (ODC). Through contacts with municipalities and hospitals, 72 AADC were identified. For each AADC, the two nearest ODCs served as controls. A questionnaire was sent to the local directors of the 216 daycare centers (531 sections), 83% responded. A total of 39% of the ODCs had ever had dampness/molds, 12% were near (<500 m) stables/farms, 23% were closer than 50 m to a heavy trafficked road, and 13% were exposed to wood smoke in winter. Only 11% of the AADCs had any child with furred pets at home, while 97% of the ODCs had children with furred pets. Bans on smoking at home and on perfumes were more common at the AADCs (P = 0.001). Fewer AADCs had PVC floors (OR = 0.53; P = 0.01), dampness/molds (OR = 0.55; P = 0.04), shelves (OR 3.03; P = 0.001), curtains (OR = 1.67; P = 0.047), and flowers (OR = 0.03; P < 0.001), while more had daily floor cleaning (OR = 19.9; P = 0.004), weekly wiping of furniture (OR = 11.0; P = 0.001), and washing of pillows/mattresses (OR = 2.74; P = 0.005) and curtains (OR = 9.07; P = 0.001). In conclusion, allergy avoidance daycare centers differ from other daycare centers, and may have better indoor environments.

PRACTICAL IMPLICATIONS

There is a need to improve the indoor environments of daycare centers, including reduction of building dampness and molds. Allergen avoidance daycare centers (AADC) in Sweden differ from ordinary daycare centers in many respects, with fewer indoor and building factors related to dust, allergens and irritants. This shows that the indoor environments of daycare centers can be improved. Data suggest that AADC may have lower levels of pet allergens, and this is beneficial for children with pet allergy. The effects of these improvements on indoor exposures and health of the children need to be further evaluated.

Association of indoor nitrogen dioxide exposure with respiratory symptoms in children with asthma

RATIONALE

Chronic exposure to indoor nitrogen dioxide (NO2) is a public health concern. Over half of U.S. households have a source of NO2, and experimental data suggest potential for adverse respiratory effects.

OBJECTIVE

To examine associations of indoor NO2 exposure with respiratory symptoms among children with asthma.

METHODS

NO2 was measured using Palmes tubes, and respiratory symptoms in the month before sampling were collected during home interviews of mothers of 728 children with active asthma. All were younger than 12 yr, lived at the sampled home for at least 2 mo, and had asthma symptoms or used maintenance medication within the previous year.

MEASUREMENTS

Respiratory symptoms (wheeze, persistent cough, shortness of breath, chest tightness).

RESULTS

Mean (SD) NO2 was 8.6 (9.1) ppb in homes with electric ranges and 25.9 (18.1) ppb in homes with gas stoves. In models stratified by housing type (a factor associated with socioeconomic status), gas stove presence and elevated NO2 were each significantly associated with respiratory symptoms, controlling for age, ethnicity, medication, mold/mildew, water leaks, and season of sampling. Among children in multifamily housing, exposure to gas stoves increased likelihood of wheeze (odds ratio [OR], 2.27; 95% confidence interval [95% CI], 1.15, 4.47), shortness of breath (OR, 2.33; 95% CI, 1.12, 5.06), and chest tightness (OR, 4.34; 95% CI, 1.76, 10.69), whereas each 20-ppb increase in NO2 increased both likelihood of any wheeze (OR, 1.52; 95% CI, 1.04, 2.21) or chest tightness (OR, 1.61; 95% CI, 1.04, 2.49), and days of wheeze (rate ratio (RR), 1.33; 95% CI, 1.05, 1.68) or chest tightness (RR, 1.51; 95% CI, 1.18, 1.91).

CONCLUSION

Exposure to indoor NO2 at levels well below the Environmental Protection Agency outdoor standard (53 ppb) is associated with respiratory symptoms among children with asthma in multifamily housing.

A review and evaluation of intraurban air pollution exposure models

The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity-space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.

Estimation of occupational and nonoccupational nitrogen dioxide exposure for Korean taxi drivers using a microenvironmental model

Occupational and nonoccupational personal nitrogen dioxide (NO(2)) exposures were measured using passive samplers for 31 taxi drivers in Asan and Chunan, Korea. Exposures were also estimated using a microenvironmental time-weighted average model based on indoor, outdoor and inside the taxi area measurements. Mean NO(2) indoor and outdoor concentrations inside and outside the taxi drivers' houses were 24.7+/-10.7 and 23.3+/-8.3 ppb, respectively, with a mean indoor to outdoor NO(2) ratio of 1.1. Mean personal NO(2) exposure of taxi drivers was 30.3+/-9.7 ppb. Personal NO(2) exposures for drivers were more strongly correlated with interior vehicle NO(2) levels (r = 0.89) rather than indoor residential NO(2) levels (r = 0.74) or outdoor NO(2) levels (r = 0.71). The main source of NO(2) exposure for taxi drivers was considered to be occupational driving. Interestingly, the NO(2) exposures for drivers' using LPG-fueled vehicles (26.3+/-1.3 ppb) were significantly lower than those (38.1+/-1.3 ppb) using diesel-fueled vehicle (P <0.01). Since drivers spent most of their time inside their vehicle and indoors at home, a microenvironmental model was used to estimate the personal NO(2) exposure with indoor and outdoor NO(2) levels of the residence, and interior vehicle NO(2) levels (P <0.001). Some subpopulations, such as professional drivers, might be exposed to high NO(2) levels because they drive diesel-using vehicles outdoors in Korea.