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 (NO(2)) 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 NO(2), 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.
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 (NO(2)) 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 NO(2), 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.
Authors: Kathleen Belanger; William Beckett; Elizabeth Triche; Michael B Bracken; Theodore Holford; Ping Ren; Jean-ellen McSharry; Diane R Gold; Thomas A E Platts-Mills; Brian P Leaderer Journal: Am J Epidemiol Date: 2003-08-01 Impact factor: 4.897
Authors: Mercedes A Bravo; Keita Ebisu; Francesca Dominici; Yun Wang; Roger D Peng; Michelle L Bell Journal: Environ Health Perspect Date: 2016-09-20 Impact factor: 9.031
Authors: Pamela Zúñiga-Bello; Astrid Schilmann; Eunice Félix-Arellano; Gerardo Gama-Hernández; Urinda Alamo-Hernández Journal: Int J Environ Res Public Health Date: 2019-01-22 Impact factor: 3.390
Authors: Shepherd H Schurman; Mercedes A Bravo; Cynthia L Innes; W Braxton Jackson; John A McGrath; Marie Lynn Miranda; Stavros Garantziotis Journal: Sci Rep Date: 2018-08-23 Impact factor: 4.379