Health poverty among people with type 2 diabetes mellitus (T2DM) in Malaysia.
Parra-Mujica F., Roope LS., Abdul-Aziz A., Mustapha F., Ng CW., Rampal S., Lim L-L., Dakin H., Clarke P.
In the context of the escalating burden of diabetes in low and middle-income countries (LMICs), there is a pressing concern about the widening disparities in care and outcomes across socioeconomic groups. This paper estimates health poverty measures among individuals with type 2 diabetes mellitus (T2DM) in Malaysia. Using data from the National Diabetes Registry between 2009 and 2018, the study linked 932,855 people with T2DM aged 40-75 to death records. Cox proportional hazards models were used to estimate the 5-year survival probabilities for each patient, stratified by age and sex, while controlling for comorbidities and area-based indicators of socio-economic status (SES), such as district-level asset-based indices and night-time luminosity. Measures of health poverty, based on the Foster-Greer-Thorbecke (FGT) measures, were employed to capture excessive risk of premature mortality. Two poverty line thresholds were used, namely a 5% and 10% reduction in survival probability compared to age and sex-adjusted survival probability of the general population. Counterfactual simulations estimated the extent to which comorbidities contribute to health poverty. 43.5% of the sample experienced health poverty using the 5% threshold, and 8.9% were health poor using the 10% threshold. Comorbidities contribute 2.9% for males and 5.4% for females, at the 5% threshold. At the 10% threshold, they contribute 7.4% for males and 3.4% for females. If all patients lived in areas of highest night-light intensity, poverty would fall by 5.8% for males and 4.6% for females at the 5% threshold, and 4.1% for males and 0.8% for females at the 10% threshold. In Malaysia, there is a high incidence of health poverty among people with diabetes, and it is strongly associated with comorbidities and area-based measures of SES. Expanding the application of health poverty measurement, through a combination of clinical registries and open spatial data, can facilitate simulations for health poverty alleviation.