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Norm Finkelstein

Publications and source records attributed to Norm Finkelstein.

5 recordsLinked to original sources
PubMed2006

A land use regression model for predicting ambient concentrations of nitrogen dioxide in Hamilton, Ontario, Canada.

This paper reports on the development of a land use regression (LUR) model for predicting the intraurban variation of traffic-related air pollution in Hamilton, Ontario, Canada, an industrial city at the western end of Lake Ontario. Although land use regression has been increasingly used to characterize exposure gradients within cities, research to date has yet to test whether this method can produce reliable estimates in an industrialized location. Ambient concentrations of nitrogen dioxide (NO2) were measured for a 2-week period in October 2002 at > 100 locations across the city and subsequently at 30 of these locations in May 2004 to assess seasonal effects. Predictor variables were derived for land use types, transportation, demography, and physical geography using geographic information systems. The LUR model explained 76% of the variation in NO2. Traffic density, proximity to a highway, and industrial land use were all positively correlated with NO2 concentrations, whereas open land use and distance from the lake were negatively correlated with NO2. Locations downwind of a major highway resulted in higher NO2 levels. Cross-validation of the results confirmed model stability over different seasons. Our findings demonstrate that land use regression can effectively predict NO2 variation at the intraurban scale in an industrial setting. Models predicting exposure within smaller areas may lead to improved detection of health effects in epidemiologic studies.

Air Pollutants, Occupational↗
PubMed2005

Spatial analysis of air pollution and mortality in Los Angeles.

BACKGROUND: The assessment of air pollution exposure using only community average concentrations may lead to measurement error that lowers estimates of the health burden attributable to poor air quality. To test this hypothesis, we modeled the association between air pollution and mortality using small-area exposure measures in Los Angeles, California. METHODS: Data on 22,905 subjects were extracted from the American Cancer Society cohort for the period 1982-2000 (5,856 deaths). Pollution exposures were interpolated from 23 fine particle (PM2.5) and 42 ozone (O3) fixed-site monitors. Proximity to expressways was tested as a measure of traffic pollution. We assessed associations in standard and spatial multilevel Cox regression models. RESULTS: After controlling for 44 individual covariates, all-cause mortality had a relative risk (RR) of 1.17 (95% confidence interval=1.05-1.30) for an increase of 10 mug/m PM2.5 and a RR of 1.11 (0.99-1.25) with maximal control for both individual and contextual confounders. The RRs for mortality resulting from ischemic heart disease and lung cancer deaths were elevated, in the range of 1.24-1.6, depending on the model used. These PM results were robust to adjustments for O3 and expressway exposure. CONCLUSION: Our results suggest the chronic health effects associated with within-city gradients in exposure to PM2.5 may be even larger than previously reported across metropolitan areas. We observed effects nearly 3 times greater than in models relying on comparisons between communities. We also found specificity in cause of death, with PM2.5 associated more strongly with ischemic heart disease than with cardiopulmonary or all-cause mortality.

Air Pollution↗
PubMed2003

Relation between income, air pollution and mortality: a cohort study.

BACKGROUND: Community levels of air pollution have been associated with variability in mortality rates, but previous studies have inferred exposure to pollutants on a citywide basis. We investigated mortality in relation to neighbourhood levels of income and air pollution in an urban area. METHODS: We identified 5228 people in the Hamilton-Burlington area of southern Ontario who had been referred for pulmonary function testing between 1985 and 1999. Nonaccidental deaths that occurred in this group between 1992 and 1999 were ascertained from the Ontario Mortality Registry. Mean household income was estimated by linking the subjects' postal codes with the 1996 census. Mean neighbourhood levels of total suspended particulates and sulfur dioxide were estimated by interpolation from data from a network of sampling stations. We used proportional hazards regression models to compute mortality risk in relation to income and pollutant levels, while adjusting for pulmonary function, body mass index and diagnoses of chronic disease. Household incomes and pollutant levels were each divided into 2 risk categories (low and high) at the median. RESULTS: Mean pollutant levels tended to be higher in lower-income neighbourhoods. Both income and pollutant levels were associated with mortality differences. Compared with people in the most favourable category (higher incomes and lower particulate levels), those with all other income-particulate combinations had a higher risk of death from nonaccidental causes (lower incomes and higher particulate levels: relative risk [RR] 2.62, 95% confidence interval [CI] 1.67-4.13; lower incomes and lower particulate levels: RR 1.82, 95% CI 1.30-2.55; higher incomes and higher particulate levels: RR 1.33, 95% CI 1.12-1.57). Similar results were observed for sulfur dioxide. The relative risk was lower at older ages. INTERPRETATION: Mortality rates varied by neighbourhood of residence in this cohort of people whose lung function was tested. Two of the broader determinants of health--income and air pollution levels--were important correlates of mortality in this population.

Aged↗
PubMedDate not supplied

Spatial analysis of the air pollution-mortality relationship in the context of ecologic confounders.

Lack of control for confounding by ecological covariates that may relate to sulfate air pollution and mortality was a key criticism of the two studies that were the focus of the Particle Reanalysis Project. To assess the validity of this criticism, we address the question: "Does sulfate air pollution exert health effects when the impact of other individual and ecologic variables thought to influence health is taken into account?" A related question arises from the possibility of autocorrelation in the mortality risks and ecologic covariates. Failure to control for autocorrelation can lead to false positive significance tests and may indicate bias resulting from a missing variable or group of variables. We control for more than 25 individual risk factors and for 20 ecologic variables representing environmental, socioeconomic, demographic, health- care, and lifestyle determinants of health in a two-stage multilevel analysis. Four modeling strategies are used to control for spatial autocorrelation. Of the 20 ecologic variables tested, only sulfate and sulfur dioxide are significant in models that incorporate spatial autocorrelation. Accounting for autocorrelation also reduces the size and certainty of the sulfate effect on mortality when compared to results generated from Cox models where independent observations are assumed. Confidence limits for the sulfate relative risk include unity in models that simultaneously control for sulfur dioxide and autocorrelation.

Air Pollution↗