학술논문

Valuing health states of people with type 2 diabetes: Analyses of the nationwide representative linked databases
Document Type
article
Source
Journal of Diabetes Investigation, Vol 12, Iss 9, Pp 1749-1758 (2021)
Subject
Health utilities
Health‐related quality of life
Type 2 diabetes
Diseases of the endocrine glands. Clinical endocrinology
RC648-665
Language
English
ISSN
2040-1124
2040-1116
Abstract
Abstract Aims/Introduction To estimate preference‐based measures of health‐related quality of life associated with sociodemographic and clinical characteristics in type 2 diabetes patients. Materials and Methods Individuals with EuroQol‐5 dimensions‐3 levels data were identified from Taiwan’s National Health Interview Survey in 2009 and 2013. Status of diabetes, comorbidities, complications and treatments were ascertained through data linkage to Taiwan’s National Health Insurance Research Database. Multivariable ordinary least squares, Tobit and median regression analyses were used to estimate the coefficients that represented independent impacts of patients’ characteristics on health‐related quality of life. Results The mean health utility score for 2,104 participants was 0.838. Being female, aging, divorced/widowed, never worked or underweight, or having a lower monthly household income, injectable glucose‐lowering therapy, comorbid connective tissue disease or depression were associated with lower health utilities. Having an amputation led to the largest reduction by 0.288 in health utilities, followed by debilitating stroke (0.266), heart failure (0.237), other coronary heart disease (0.185), kidney dialysis/transplant (0.148), coronary revascularizations (0.093), transient ischemic attack/stroke (0.078), diabetic neuropathy (0.062), polyneuropathy (0.055) and other neuropathy (0.043). Conclusions Major vascular complications, connective tissue disease and depression are associated with considerably worse health‐related quality of life. These health utility estimates can facilitate health economic evaluations to determine cost‐effective strategies for diabetes management.