Relationship between traffic-related air pollution and inflammation biomarkers using structural equation modeling

Area of Science:

• Environmental Health
• Epidemiology
• Toxicology

Background:

• Traffic-related air pollution (TRAP) and social stressors are implicated in increased systemic inflammation.
• Assessing complex associations requires analytical approaches that integrate multiple exposure and outcome markers.
• Previous studies highlight the need for robust methods to evaluate TRAP's inflammatory impact.

Purpose of the Study:

• To apply structural equation modeling (SEM) to assess the association between traffic-related air pollution (TRAP) and socio-economic status (SES) constructs with an inflammation construct.
• To compare SEM findings with traditional generalized linear models (GLM).
• To evaluate the utility of multi-marker constructs in understanding environmental exposures and health outcomes.

Main Methods:

• The Community Assessment of Freeway Exposure and Health (CAFEH) study (N=408) data were utilized.
• Traffic-related air pollution (TRAP) was characterized using spatiotemporal modeling of particle number concentration (PNC) with time-activity adjustment (TAA-PNC) and highway proximity.
• Socio-economic status (SES) was assessed via education and income; inflammation markers included hsCRP, IL-6, and TNFRII. SEM and GLM were employed.

Main Results:

• Generalized linear models (GLM) showed associations between time-activity adjusted particle number concentration (TAA-PNC) and inflammation biomarkers (e.g., 14% hsCRP increase per IQR).
• Structural equation modeling (SEM) demonstrated that the TRAP construct association with the inflammation construct was twice as large as associations with individual biomarkers.
• Socio-economic status (SES) exhibited an inverse relationship with inflammation; SEM analysis strengthened confidence in TRAP's association with inflammation via indirect effects.

Conclusions:

• A multi-marker TRAP construct showed stronger associations with a combined inflammation construct compared to individual biomarkers, validating the use of integrated statistical approaches.
• The findings support the hypothesis that traffic-related air pollution exposure poses an inflammatory risk.
• This study underscores the value of SEM in elucidating complex environmental health relationships.