Urban land-use and respiratory symptoms in infants

Background

Children's respiratory health has been linked to many factors, including air pollution. The impacts of urban land-use on health are not fully understood, although these relationships are of key importance given the growing populations living in urban environments.

Objectives

We investigated whether the degree of urban land-use near a family's residence is associated with severity of respiratory symptoms like wheeze among infants.

Methods

Wheeze occurrence was recorded for the first year of life for 680 infants in Connecticut for 1996–1998 from a cohort at risk for asthma development. Land-use categories were obtained from the National Land Cover Database. The fraction of urban land-use near each subject's home was related to severity of wheeze symptoms using ordered logistic regression, adjusting for individual-level data including smoking in the household, race, gender, and socio-economic status. Nitrogen dioxide (NO₂) exposure was estimated using integrated traffic exposure modeling. Different levels of urban land-use intensity were included in separate models to explore intensity-response relationships. A buffer distance was selected based on the log-likelihood value of models with buffers of 100–2000 m by 10 m increments.

Results

A 10% increase in urban land-use within the selected 1540 m buffer of each infant's residence was associated with 1.09-fold increased risk of wheeze severity (95% confidence interval, 1.02–1.16). Results were robust to alternate buffer sizes. When NO₂, representing traffic pollution, was added to the model, results for urban land-use were no longer statistically significant, but had similar central estimates. Higher urban intensity showed higher risk of prevalence and severity of wheeze symptoms.

Conclusions

Urban land-use was associated with severity of wheeze symptoms in infants. Findings indicate that health effect estimates for urbanicity incorporate some effects of traffic-related emissions, but also involve other factors. These may include differences in housing characteristics or baseline healthcare status.