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Modifiable Risk Factors and Socioeconomic Inequity in Diabetes: A Prospective Analysis in the UK Biobank
Yan Bo Zhang1, Qi Lu2, Yan Feng Zhou3
1Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China;Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
Objective:
To examine the association between overall socioeconomic status (SES) and incident diabetes, to estimate how much of the SES-diabetes association is explained by modifiable diabetes risk factors, and to assess whether the benefits of favorable risk factor profiles differ by SES.
Methods:
We analyzed 337,229 adults without diabetes at baseline from the UK Biobank. Overall SES was derived using latent class analysis based on income, occupation, and education. Modifiable diabetes risk factor scores were constructed across physiological, behavioral, environmental, and psychological domains. Cox proportional hazard models and additive hazard models were used to evaluate associations, mediation proportions, and interactions for incident diabetes.
Results:
During a median follow-up of 12.5 years, 11,557 participants developed diabetes ascertained through linkage to registries. The low SES group had 2.47-fold (95% CI: 2.33-2.62) diabetes risk and 2.7 (2.5-2.8) more incident diabetes cases per 1,000 person-years compared to the high SES group, 54.4% of which was explained by all modifiable factors jointly, with physiological score contributing to the largest proportion (39.1%). Favorable risk factor profiles were associated with lower diabetes risk across all SES groups, and absolute risk reductions associated with favorable profiles were greatest among individuals with low SES ( P for additive interaction ≤ 0.002).
Conclusion:
More than half of the excess diabetes risk associated with low SES can be explained by modifiable risk factors. Improving these factors may contribute to greater reduction in diabetes incidence among socioeconomically disadvantaged populations, supporting targeted diabetes prevention strategies to reduce socioeconomic disparities.
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