Low Dose Computed Tomography (LDCT) Eligibility and Outcome differences between Sexual and Gender Minorities and their Sexual and Gender Majority Counterparts

点击翻译按钮获取中文摘要

Project Summary Cigarette smoking accounts for 1 in 5 preventable deaths in the United States. Sexual and gender minorities (SGM) are at higher risk of cigarette smoking and tobacco-related deaths. Preliminary evidence indicates that sexual minorities have higher eligibility rates for low dose computed tomography (LDCT), a reliable screening test that reduces the risk of lung cancer mortality caused by tobacco smoking. Recently, the age and smoking pack years were reduced in the eligibility guidelines, which determine who qualifies for LDCT screening. This led to an increase in the number of people who were eligible, but no work on differences by sexuality or gender identity comparing the new and old criteria has been conducted. One possible cause of SGM individuals having higher eligibility rates is the number of risk factors SGM individuals experience at the individual, interpersonal, community, and policy levels based on the social ecological model. However, individual national data sets do not contain enough individuals that identify as SGM to make inferences about possible risk factors and the corresponding high LDCT eligibility for SGM individuals. To improve estimates and identity potential disparities and risk factors among SGM individuals for LDCT eligibility, one promising option is to merge data from multiple national data sources. Additionally, there is a need to determine whether SGM individuals who are eligible for LDCT are smoking at a higher rate compared to heterosexual and cisgender individuals, especially over time. Overall, I have three main aims: 1) Merge four nationally representative data sets together, and compare these methods of merging to generate better estimates of cigarette smoking and LDCT eligibility for SGM individuals.; 2) Compare trends in the new and old LDCT screening eligibility criteria over time to understand how many people are eligible and how SGM individuals compare to their cisgender and heterosexual counterparts; and 3) Guided by the social ecological model, identify the risk factors associated with LDCT eligibility for SGM individuals. To address these aims, state-of-the-art techniques for merging data, complex survey analysis using longitudinal and multi-year cross-sectional data, and structural equation modeling will be used under the mentorship of Drs. West and McCabe to understand the effects multiple levels of the social ecological model have on LDCT eligibility. Upon completion of the aims, the papers, presentations, and reports will enhance my methodological and substantive training and advance multiple fields of research. In the survey methodology field, I will compare methods of data merging for small subpopulations, understand measurement differences, and improve estimates for SGM individuals. In the public health realm, I will expand our understanding of possible differences between SGM, heterosexual, and cis-gender individuals in LDCT eligibility, lung cancer, and lung conditions, and I will aim to understand the effects of multiple levels of the social ecological model on SGM individuals and their LDCT eligibility.