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Epidemiology of type 2 diabetes mellitus and treatment utilization patterns among the elderly from the first wave of Longitudinal Aging study in India (2017-18)using a Heckman selection model.
BMC Public Health 2023 April 15
INTRODUCTION: Unmanaged Type 2 diabetes mellitus (T2DM) substantially contributes to the multi-morbidity of the elderly. Fewer research has concentrated on understanding the determinants of treatment utilization among older people, with even lesser concerns about missing data in outcome variables leading to biased estimates. The present study intends to evaluate the epidemiology of T2DM in the elderly in India and explore the socioeconomic and behavioral risk factors determining the treatment utilization among the elderly > 60 years in India by addressing the missing data to generate robust estimates.
METHODS: The secondary analysis used data from the Longitudinal Ageing Study in India. The key dependent variables were the presence or absence of T2DM and treatment utilization. Descriptive statistics were used to understand the differences in the prevalence of diabetes and the utilization of treatment across various socio-demographic characteristics. Heckman's statistical technique evaluated the predictors of T2DM and treatment utilization. Analysis was done using STATA software version 14.0.
RESULTS: Almost 14% elderly reported to be living with T2DM. The odds of living with T2DM increased with non-working status, a sedentary lifestyle, and a higher BMI. A higher proportion of the elderly was on oral drugs than insulin and had been practicing lifestyle modifications to control their disease. The probability of developing T2DM was lower among females than males, but females had better odds for treatment utilization of health medication than males. Lastly, treatment utilization was significantly affected by socio-demographic characteristics like education and monthly per capita expenditure.
CONCLUSIONS: Treatment utilization by the elderly living with T2DM is significantly affected by socio-demographic characteristics. Keeping in mind the increasing proportion of the geriatric population in our country, it is pertinent to tailor-made counseling sessions for the elderly to improve medication utilization and adherence and realize our goals concerning non-communicable diseases.
METHODS: The secondary analysis used data from the Longitudinal Ageing Study in India. The key dependent variables were the presence or absence of T2DM and treatment utilization. Descriptive statistics were used to understand the differences in the prevalence of diabetes and the utilization of treatment across various socio-demographic characteristics. Heckman's statistical technique evaluated the predictors of T2DM and treatment utilization. Analysis was done using STATA software version 14.0.
RESULTS: Almost 14% elderly reported to be living with T2DM. The odds of living with T2DM increased with non-working status, a sedentary lifestyle, and a higher BMI. A higher proportion of the elderly was on oral drugs than insulin and had been practicing lifestyle modifications to control their disease. The probability of developing T2DM was lower among females than males, but females had better odds for treatment utilization of health medication than males. Lastly, treatment utilization was significantly affected by socio-demographic characteristics like education and monthly per capita expenditure.
CONCLUSIONS: Treatment utilization by the elderly living with T2DM is significantly affected by socio-demographic characteristics. Keeping in mind the increasing proportion of the geriatric population in our country, it is pertinent to tailor-made counseling sessions for the elderly to improve medication utilization and adherence and realize our goals concerning non-communicable diseases.
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