Courtney J. Walker

Table S4 shows the joint association between race/ethnicity and socioeconomic status and mortality.

Table S5a shows the Cox proportional hazards model for oral cavity cancer, stratified by race/ethnicity and socioeconomic status. Table S5b shows the Cox proportional hazards model for pharyngeal cancers, stratified by race/ethnicity and socioeconomic status.

Table S6a shows the Cox proportional hazards model for laryngeal cancer, stratified by race/ethnicity and socioeconomic status. Table S6b shows the Cox proportional hazards model for sinonasal cancers, stratified by race/ethnicity and socioeconomic status.

Table S2 shows demographic and clinical characteristics of patients with primary head and neck cancer by race/ethnicity with missing socioeconomic status.

Table S3 shows demographic and clinical characteristics of patients with primary head and neck cancer by socioeconomic status.

Figure S2 shows cumulative incidence curves by socioeconomic status for the HNC-specific death by race/ethnicity.

Figure S1 shows flowchart of study participant selection.

Table S1 shows descriptive statistics of primary head and neck cancer patients with survival time <12 Months by race/ethnicity.

Background:Head and neck cancer (HNC) mortality differs by race, ethnicity, and socioeconomic status (SES). However, it is unclear whether the relationship between race/ethnicity and HNC-specific mortality varies according to the residence-level SES.Methods:Data from the Surveillance Epidemiology and End Results database included participants with primary HNC between 2006 and 2017 (followed through 2018) to assess the joint association of race/ethnicity and census-tract level SES Yost-index groups (quintiles) with all-cause and HNC-specific mortalities. Relative survival rates at 1, 5, and 10 years were calculated. Multivariable Cox proportional hazard regression models estimated hazard-ratios and 95% confidence intervals for all-cause mortality, and Fine-Gray subdistribution hazard models for HNC-specific mortality. Cumulative incidence curves for HNC-specific deaths were estimated.Results:76,095 patients were included in the analysis: 63.2% were <65 years, 73.4% male, and 11.3% non-Hispanic (NH) Black. Most patients (58.3%) were diagnosed at regional or distant stages and 20.6% died of HNC. The five-year relative survival rate increased with SES group, with 51.6% in the lowest SES group, and 74.1% in the highest SES group. NH-Black patients had higher risk of all-cause and HNC-specific mortality than NH-White patients, regardless of the SES group. NH-Asian/Pacific Islander and Hispanic patients had higher risk of HNC-specific mortality in some SES groups.Conclusions:NH-Black patients of all SES strata had significantly worse outcomes. Other factors, such as healthcare quality, may be associated with persistent disparities.Impact:The study highlights the persistence of significant racial disparities in HNC survival across socioeconomic categories. There is need to consider additional factors underlying these disparities.

Purpose: Despite high rates of lung disease and lung cancer among women, few studies have focused on adverse lung health risk factors among rural Appalachian women. We aim to describe the prevalence of demographic, behavioral, and economic characteristics among a cohort of rural Appalachian women and ascertain the association between these risk factors and lung function.Methods: Through a cross‐sectional study in two rural Appalachian Kentucky counties (2015–2017), we collected demographics, health history/behaviors, and lung function via pulmonary function tests. Restricting to female participants with interpretable pulmonary function tests (N = 456), we estimated prevalence ratios of the association between individual‐level characteristics and lung function using log binomial regression.Findings: Reduced lung function was high among this sample, including 20.8% with restrictive function and 18.4% with obstructive function. After adjustment, those age 65+ had 7× the prevalence of obstructive function compared to those <45 years, and current smokers had 6× the prevalence of never‐smokers. Conversely, those age 45–64 had over 5× the prevalence of restrictive function compared to those <45 years, and participants with an obese‐classified BMI or 2+ co‐morbidities had nearly 4× the prevalence of restrictive function compared to those with normal BMI or without a comorbid condition, respectively.Conclusions: This study highlights the high levels of reduced lung function among rural Appalachian women, including varying risk factors between those with restrictive and obstructive function. The high prevalence of restrictive function among middle‐aged women with high BMI, poor cardiovascular health, and multiple comorbidities suggests the need for culturally tailored health behavior interventions.