Uncovering Hidden Marginalized Populations in Lung Cancer Screening via Latent Class Analysis

Area of Science:

• Public Health
• Epidemiology
• Health Disparities

Background:

• Lung cancer screening eligibility criteria aim to identify high-risk individuals.
• Existing research often overlooks nuanced population segments influencing screening uptake.
• Understanding diverse characteristics impacting screening is vital for equitable healthcare access.

Purpose of the Study:

• To identify previously overlooked and marginalized populations with shared characteristics influencing lung cancer screening rates.
• To analyze demographic, socioeconomic, geographic, and clinical factors associated with lung cancer screening.
• To inform the development of targeted interventions for underserved groups.

Main Methods:

• Utilized Behavioral Risk Factor Surveillance System data (2018-2021) for 11,096 eligible individuals.
• Employed multiple-group latent class analysis with 10 indicators and race/ethnicity as covariates.
• Accounted for complex survey designs to ensure robust statistical analysis.

Main Results:

• Identified 11 latent classes with varying screening probabilities.
• Three classes (12% of population) with lowest screening rates (≤5%) lacked insurance and primary care access.
• Healthy working/retired individuals (53%) showed low screening rates (15-17%) despite primary care access.
• Individuals with COPD and poor health status had higher screening rates (16-41%).

Conclusions:

• A nuanced approach beyond individual factors is necessary for lung cancer screening.
• Complex interactions of multiple factors significantly influence screening disparities.
• Findings provide a foundation for developing effective interventions to address screening inequities.