Examining treatment burden in relation to comorbidity among adults with type 2 diabetes: A cross-sectional study in a clinical setting in south India

Abstract

This study examines whether treatment burden differs between people living with diabetes alone and those with additional comorbidities. We interviewed 3,806 adults visiting Dr. Mohan’s Diabetes Specialities Centre in Chennai between 24 January 2024 and 13 January 2025. Comorbidities were assessed using a comprehensive list of 69 chronic conditions, developed through multiple rounds of clinician consultation and piloting. Treatment burden was measured using the 13-item Multimorbidity Treatment Burden Questionnaire, translated into the local language and pilot-tested before administration. The global score (0-100) was categorized as none (score=0), low (0<score<10), medium (10≤ score< 22) and high (score≥22). The association between treatment burden and the presence of any comorbidity was examined using proportional odds logistic regression, adjusting for demographic, socioeconomic, behavioural, and clinical factors. Overall, 95.2% of participants had at least one comorbidity in addition to diabetes, while 4.8% had diabetes alone. Seven percent reported high treatment burden, and 34% reported medium-to-high burden. Monitoring/self-management (e.g., lifestyle changes, condition monitoring) and accessing social support were the most burdensome domains, particularly for those with comorbidities. Participants with one or more comorbidities had significantly higher odds of reporting greater treatment burden than those without comorbidities (adjusted odds ratio=2.26, 95% CI=1.69-3.01, p-value<0.001). Findings were consistent across multiple sensitivity analyses. Treatment burden is substantial among adults with diabetes in India, particularly for those with comorbidity. These findings highlight the need for patient-centred care models that explicitly account for multimorbidity-related workload and provide targeted support for lifestyle modifications and self-management, especially in resource-constrained settings.