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

Document Type

Article

Publication Date

10-1-2016

Publication Title

The Journal of allergy and clinical immunology

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.

Medical Subject Headings

Adolescent; Asthma; Child; Disease Management; Environmental Exposure; Female; Humans; Male; Models, Theoretical; Poverty; Rhinitis, Allergic, Perennial; Risk Factors; Severity of Illness Index; Tobacco Smoke Pollution; Urban Population

PubMed ID

27720018

Volume

138

Issue

4

First Page

1042

Last Page

1050

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