Pathways through which asthma risk factors contribute to asthma severity in inner-city children

Abstract

Background: Pathway analyses can be used to determine how host and environmental factors contribute to asthma severity.

Objective: To investigate pathways explaining asthma severity in inner-city children.

Methods: On the basis of medical evidence in the published literature, we developed a conceptual model to describe how 8 risk-factor domains (allergen sensitization, allergic inflammation, pulmonary physiology, stress, obesity, vitamin D, environmental tobacco smoke [ETS] exposure, and rhinitis severity) are linked to asthma severity. To estimate the relative magnitude and significance of hypothesized relationships among these domains and asthma severity, we applied a causal network analysis to test our model in an Inner-City Asthma Consortium study. Participants comprised 6- to 17-year-old children (n = 561) with asthma and rhinitis from 9 US inner cities who were evaluated every 2 months for 1 year. Asthma severity was measured by a longitudinal composite assessment of day and night symptoms, exacerbations, and controller usage.

Results: Our conceptual model explained 53.4% of the variance in asthma severity. An allergy pathway (linking allergen sensitization, allergic inflammation, pulmonary physiology, and rhinitis severity domains to asthma severity) and the ETS exposure pathway (linking ETS exposure and pulmonary physiology domains to asthma severity) exerted significant effects on asthma severity. Among the domains, pulmonary physiology and rhinitis severity had the largest significant standardized total effects on asthma severity (-0.51 and 0.48, respectively), followed by ETS exposure (0.30) and allergic inflammation (0.22). Although vitamin D had modest but significant indirect effects on asthma severity, its total effect was insignificant (0.01).

Conclusions: The standardized effect sizes generated by a causal network analysis quantify the relative contributions of different domains and can be used to prioritize interventions to address asthma severity.

Keywords: Asthma; allergy; children; environmental tobacco smoke exposure; inflammation; inner-city; lung function; pulmonary physiology; rhinitis; sensitization.

Copyright © 2016 American Academy of Allergy, Asthma & Immunology. All rights reserved.

Figures

FIGURE 1

Conceptual Model of Asthma Severity. This model was generated in advance of any analyses based on observations derived from the medical literature and became the test object of this study. Oval boxes indicate domains defined by multiple observed variables, while rectangles indicate domains defined by one observed variable only. An arrow connecting two domains represents the direction of the hypothesized relationship between the two domains.

FIGURE 2

Direct and Indirect Effects of All Pathways. Estimates are standardized direct effects that are interpreted as the standard deviation increase in the dependent domain for every one standard deviation increase in the independent domain. Estimates with associated p-values that are less than 0.05 are denoted by * and solid lines. Thick lines further denote statistically significant pathways by tests of indirect effects and mediation. Statistically insignificant estimates are denoted by dashed lines. All estimates are adjusted for age, sex and race.

FIGURE 3

Pathways to Asthma Severity. Estimates are standardized direct effects that are interpreted as the standard deviation increase in the dependent domain for every one standard deviation increase in the independent domain. Estimates with associated p-values that are less than 0.05 are denoted by * and solid lines. Thick lines further denote statistically significant pathways by tests of indirect effects and mediation. Statistically insignificant estimates are denoted by dashed lines. All estimates are adjusted for age, sex and race.