Assessment of treatment burden among older adults attending a geriatric clinic in Southwestern Nigeria: a cross-sectional study

Abstract Introduction Treatment burden is an emerging health problem, causing a rise in morbidity and mortality, especially among older adults. Ageing has been associated with multimorbidity, and its management could lead to increased treatment burden.1 Despite previous efforts to understand the concept of treatment burden, the treatment burden of people living with multimorbidity has not been thoroughly explored, which may limit our understanding of treatment burden in older adults. An awareness of the burden of treatment can lead to effective patient-centered care, better health outcomes, and improved quality of life for older adults.2 However, few empirical data exist on treatment burden among older adults in sub-Saharan African countries. Aim This study aimed to assess the treatment burden and factors contributing to it among older adults. Methods A cross-sectional study of 361 older adults ≥60 years, selected consecutively at the geriatric clinic in a hospital was carried out between May and August 2025. An interviewer-administered semi-structured validated Multimorbidity Treatment Burden Questionnaire (MTBQ) was used to obtain information on socio-demographic characteristics and used to assess their treatment burden. SPSS was used to analyse the data using descriptive statistics and ordinal regression. Descriptive analyses such as frequencies and percentages were used to analyse categorical variables, with means and standard deviations for continuous variables. Ordinal regression was used to analyse treatment burden score to examine associations. Statistical significance was set at p ≤ 0.05. Results The mean age of respondents was 72.02 ± 7.8 years, female were 70.9% (n = 256), and the median MTBQ score was 4 (IQR 0–7). In total, 244 (67.6%) reported treatment burden (MTBQ score 1); of these 182 (50.4%) had low treatment burden, 52 (14.4%) had medium treatment burden and 10 (2.8%) reported high treatment burden, while 117 (32.4%) reported no burden. Ordinal regression showed that 9 of the 13 multimorbidity treatment burden items were statistically significant in predicting a higher burden category (p 0.05). The most common items associated with treatment burden included difficulties with remembering to take medications (23.1; 6.4%), monitoring your medical conditions (31.0; 8.6%), paying for prescriptions (135; 37.4%), attending appointments (70; 19.4%), and having to rely on help from family and friends (123; 34.1%). However, arranging appointments, seeing healthcare professionals, getting healthcare in the evenings and weekends, and obtaining clear information were not statistically significant in predicting treatment burden. Among adults aged 60–69 years, 98 (65.3%) experienced treatment burden, compared with 99 (70.7%) of those aged 70–79. Conclusion Treatment burden was reported by two-thirds of the older adults, thus, reducing treatment burden among these older adults may require addressing financial burdens, self-management issues, and factors that limit their capacity to care for themselves. These findings highlight the need for financial support for older adults which will alleviate the burden of paying for medications, and digital health solutions like telemedicine that help support self-management and reduce reliance on others for their health management. The limitation of this study is its quantitative design which may not fully capture the depth of participants’ opinions.