Identifying geographic areas with increased incidence of disease may elucidate community-level risk factors for intervention development. Lower respiratory illnesses (LRIs) are the leading cause of death in children and are associated with other morbidities. We assessed geographic clustering of LRIs and evaluated if these spatial patterns and associated risk factors differed by phenotype.
Participants enrolled at birth in the Tucson Children's Respiratory Study were followed through age three for physician diagnosed LRIs. Spatial clustering analysis, based upon each participant's birth address, was performed for four LRI phenotypes. We conducted principal component analysis at the census tract level to generate indices for lower socioeconomic status (SES), poorer housing conditions, and increased air pollution.
Enrollment addresses were mapped for 812 subjects, of whom 58.4%, 33.5%, 34.2%, and 23.4% had any LRI, a wheezing LRI, a viral LRI, and a respiratory syncytial virus (RSV) LRI, respectively. Patterns of spatial clustering and associated risk factors differed by LRI phenotype. Multivariable regression analyses showed that wheezing LRI clusters were associated with increased air pollution (OR = 1.18, P = 0.01). Being in a viral cluster was associated with poorer housing conditions (OR = 1.28, P = 0.01), while being in a RSV cluster was associated with increased air pollution (OR = 1.14, P = 0.006), poorer housing conditions (OR = 1.54, P = 0.003), and higher SES (OR = 0.77, P = 0.001).
Our use of social and environmental indices allowed us to identify broad contextual factors that may contribute to increased incidence of LRIs in specific geographic regions. To reduce LRI incidence, multifaceted interventions should be developed at the community level. Pediatr Pulmonol. 2016;51:633–642. © 2015 Wiley Periodicals, Inc.