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◆ Patient preference and adherence2026-01-01

Pro-Rich Inequality in Health-Related Quality of Life Among Primary Care Diabetes Patients: A Cross-Sectional Study.

Haofei Li, Junyi He, Runhong Li, Yiyin Cao, Xu Jin, Yujin Wang, Mengyao Tian, Yanping Wang, Dongfu Qian, Weidong Huang, Yuchun Tao

一句话结论 · In one sentence

Income-related inequalities in HRQoL were evident among primary care diabetes patients in this cold-region setting. Socioeconomic disparities and modifiable health behaviors are important correlates of HRQoL inequality, warranting further investigation in longitudinal studies.

原始摘要(英文原文)· Original abstract
OBJECTIVE: This cross-sectional study aimed to assess HRQoL and to examine income-related inequalities among diabetes patients in Harbin, a cold-region city in China, where such evidence remains limited. METHODS: In July 2025, 433 adults with diabetes were recruited from two community health centers in Harbin using random sampling from electronic health records. HRQoL was measured using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) utility index and the EuroQol Visual Analogue Scale (EQ-VAS). Income-related inequality was quantified using the concentration index (CI) and the Erreygers-corrected CI. Wagstaff decomposition was applied to identify contributing factors, and horizontal inequity (HI) indices were computed after adjusting for need variables. Sensitivity analyses included Tobit model. RESULTS: The mean EQ-5D-5L utility index was 0.9303 (SD = 0.1294), and the mean EQ-VAS score was 77.60 (SD = 12.88). Significant pro-rich inequality was observed for both outcomes (standard CI: 0.0093 for EQ-5D-5L and 0.0131 for EQ-VAS; Erreygers index: 0.0249 and 0.0405, respectively). Household income was the largest contributor to inequality, accounting for 73.30% of the inequality in EQ-5D-5L utility index and 53.77% of the inequality in EQ-VAS score. Other notable contributors included blood glucose control, exercise habits, marital status, and digital health literacy for EQ-5D-5L, and adherence to chronic disease follow-up and exercise habits for EQ-VAS. After adjusting for need variables, the HI remained positive for both measures (0.0095 for EQ-5D-5L and 0.0135 for EQ-VAS). CONCLUSION: Income-related inequalities in HRQoL were evident among primary care diabetes patients in this cold-region setting. Socioeconomic disparities and modifiable health behaviors are important correlates of HRQoL inequality, warranting further investigation in longitudinal studies.
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Pro-Rich Inequality in Health-Related Quality of Life Among Primary Care Diabetes Patients: A Cross-Sectional Study. — 科研速览 Science Skim