PREVALENCE AND SOCIODEMOGRAPHIC INEQUALITIES IN DEVELOPING TYPE 2 DIABETES MULTIMORBIDITIES IN SERBIA - Janković, Janko; Đikanović, Bosiljka; Ayis, Salma; Todorović, Jovana; Parmar, Divya; Marović, Branko; Harding, Seeromanie; Šantrić-Milićević, Milena; Ćurčin, Vasa (Srpski medicinski časopis Lekarske komore, 2024)
Introduction: The number of people living with diabetes is increasing worldwide, with the majority of those affected residing in low- and middle-income countries. Type 2 diabetes mellitus (T2DM) is often associated with the co-occurrence of one or more long-term conditions (LTCs), which might be affected by patients’ socioeconomic characteristics, however, to what extent, it is as yet unknown in Serbia. Therefore, we have aimed to examine the prevalence and impact of sociodemographic factors on T2DM multimorbidity in Serbia.Method: Secondary data analysis of the Serbian National Health Surveys 2013 and 2019 was conducted in a population older than 45 years. Multinomial logistic regression models were used to investigate relative risk ratios with 95% confidence intervals and corresponding predicted probabilities between the sociodemographic profiles of participants in different disease groups (with/without T2DM and one or more LTCs). Results: The prevalence of T2DM comorbidity and multimorbidity was 8.8% and 29.5%, respectively. Most often, T2DM co-occurred with stroke, myocardial infarction, and liver cirrhosis. Multimorbidity was associated with older age, the female gender, lower level of education, and lower income. The biggest gender gap was identified in the predicted probabilities for having T2DM and two or more LTCs among the subjects with the lowest level of education (women: p = 0.333 vs. men: p = 0.208) and in the lowest income quintile (women: p = 0.366 vs. men: p = 0.236), while the gender gap was not identified among those with at least a bachelor's degree (women: p = 0.258 vs. men: p = 0.260). Conclusion: A comprehensive approach to identifying and subgrouping populations based on their risk of LTCs yields valuable insights that can facilitate early detection and disease management.
Keywords: diabetes mellitus type 2; long-term conditions; comorbidity; multimorbidity; prevalence; socio-demographic factors; gender; health inequalities