Associations between income/employment status and diabetes care processes, health behaviors, and health outcomes in Japan: A cross‐sectional study using claims data linked to a questionnaire survey

Abstract

ABSTRACT Aims/Introduction We aimed to explore the associations between income/employment status and diabetes care processes, health behaviors and health outcomes. Materials and Methods This cross‐sectional study used health insurance claims data between April 2021 and March 2022, and a questionnaire survey between December 2022 and January 2023 in Tsukuba City. The study analyzed the participants with diabetes (other than type 1) from those selected by stratified random sampling. We evaluated diabetes care processes, health behaviors and health outcomes by calculating weighted proportions among the groups. We also assessed the associations between income/employment status and these variables using multivariable modified Poisson regression models. Results Of the 264 identified participants, 161 (64.2%) were men and 168 (72.8%) were aged ≥65 years old. Compared with the low‐income groups, the high‐income group had a higher proportion of sodium–glucose cotransporter 2 inhibitors or glucagon‐like peptide‐1 receptor agonists use (adjusted risk ratio [aRR] 1.70, 95% confidence interval (CI) 1.07–2.72), a higher proportion of attendance to annual health checkups for ≥2 years (aRR 1.68, 95% CI 1.07–2.64) and a lower proportion of all‐cause hospitalization (aRR 0.15, 95% CI 0.04–0.48); additionally, the middle‐income group had a lower proportion of high total outpatient medical expenses (aRR 0.57, 95% CI 0.35–0.92). Compared to the no work time group, the full‐time work group had a lower proportion of exercise habits (aRR 0.59, 95% CI 0.35–0.99) and a higher proportion of good self‐reported health (aRR 2.08, 95% CI 1.22–3.55). Conclusions Several variables were associated with income/employment status. Policy intervention should focus on high‐risk groups identified by considering these associations.

Keywords

• Claims analysis
• Healthcare quality assessment
• Socioeconomic status