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Unravelling Associations Between Patient Demographics, Socioeconomic Status, and Health-Related Quality of Life Among Patients with Peripheral Artery Disease
Chloe A Powell, Gloria Y Kim, Vanessa S Niba, Katherine Gallagher, Matthew A Corriere
University of Michigan, Ann Arbor, MI

Background: Patient reported outcomes have been increasing emphasized for assessment of peripheral artery disease (PAD) outcomes and PAD-specific health related quality of life (HRQoL). While it is well established that socioeconomic status (SES), including at the neighborhood level, is associated with general HRQoL measures, limited evidence exists regarding its association with PAD-specific HRQoL. We performed a cross-sectional study to evaluate the associations between neighborhood-level affluence, disadvantage, and PAD-specific HRQoL using the Vascular Quality of Life Questionnaire-6 (VascuQoL-6), a symptomatology and activity-based limitation focused questionnaire.
Methods: Patients were recruited from a diagnostic vascular unit based on referral for ankle brachial index (ABI). Residence address information was used to designate socioeconomic status as disadvantaged or affluent based on the National Neighborhood Data Archive Socioeconomic Status and Demographic Characteristics of United States Census Tracts. PAD-specific QOL was assessed using the VascuQol-6. Associations between affluence and disadvantage, and HRQoL were evaluated with simple non-parametric tests. Significant univariable associations were further evaluated in adjusted multivariable models controlling for age, gender, and Elixhauser co-morbidity. Statistical significance was assessed based on P<0.05.
Results: 107 patients were recruited; 95 patients had SES data available and were included. Mean age was 69.9 ± 9.7. Of the participants, 89.5% were White, 100% Non-Hispanic, and 41.1% female. 21% of participants had asymptomatic disease, 46% had claudication, 26% had CLTI. 24% of participants were from disadvantaged neighborhoods, and 25% were from affluent neighborhoods. Median VascuQoL-6 scores among patients from affluent neighborhoods was not significantly different from the rest of the sample [19 (IQR 13-21) versus 17 (IQR 11-20); (P=0.149) Participants from disadvantaged neighborhood, however, had lower VascuQoL-6 scores [ 12 (IQR 11-17) vs. 18 (IQR 13-20); (P=0.0146)]. The association between neighborhood disadvantage and lower HRQoL, however, was not significant in multivariable models adjusting for demographic factors and comorbidity (P=0.216) (Table). It was not associated with affluent neighborhood residence (0.1419). In multivariable analysis, there were no observed associations between neighborhood disadvantage and VascuQol-6 score (P=0.216). (Table)
Conclusions: Socioeconomic status is a complex variable that may be associated with patient-level characteristics, specifically age. Potential confounders and effect modifiers warrant evaluation when evaluating outcomes associated with SES. Further work will explore associations between SES and other PAD-specific HRQoL instruments.
Table. Univariate and multivariate analyses of VascuQoL score by demographic and clinical characteristics

UnivariateMultivariate
VariableMedianorCorrelation CoefficientIQRor95% Confidence IntervalP ValueObserved Estimate95% Confidence IntervalP Value
Affluent0.1419---
No (N=69)179
Yes (N=23)198
Disadvantage0.0146-3.422(-8.053, -0.369)0.216
No (N=69)187
Yes (N=23)126
Age0.384(0.195, 0.546)0.00020.210(0.002, 0.235)0.002
Gender0.3713-0.011(-1.483, 2.308)0.991
Female (N=37)157
Male (N=54)17.59
Elixhauser Comorbidity score-0.072(-0.276, 0.138)0.50170.074(-0.452, 0.229)0.642


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