Exploring Drivers of Healthcare Utilization amongthe Working and Non-Working Elderly Population: Insights from LASI
aging population; geriatrics; healthcare; utilization; working elderly
Background: The elderly population of India has been growing exponentially over the past few decades, caused by a decline in fertility and an increase in life expectancy. The growth eventually has transcended the disease burden on the public healthcare system. This calls for a need to evaluate the healthcare utilization pattern of the elderly based on their socioeconomic and working condition. Methods: Study used access to public and private healthcare services to measure healthcare utilization. Descriptive analysis and multivariable logistic regression were used to understand utilization patterns by working status and some selected sociodemographic parameters. All the results were reported at a 95% confidence interval. Results: Using the data from the first wave of Longitudinal Ageing Study in India (LASI) with a sample of 22,680 older persons 60 years and above. The study identified that 50% of the working elderly access private services; however, 26% access public healthcare services. It was found that the working status of the elderly alone did not influence access to healthcare services, but education is also an essential indicator for utilizing healthcare services. Further, factors such as gender, marital status, religion, wealth, tobacco usage, self-rated health, ADL and IADL were significant predictors of healthcare services utilization for the elderly. Conclusion: This study suggests that there are not many differences found among working and non-working status with healthcare utilization, although some sociodemographic indicators are associated with the utilization of healthcare services, highlighting that increasing health needs among the elderly requires strengthening the quality and appropriate public investment in health. 2024 Taylor & Francis Group, LLC.
Nath N.J., Department of Media Studies, CHRIST (Deemed to be University), Bangalore, India; Chaudhary A., Department of Survey Research and Data Analytics, International Institute for Population Sciences, Mumbai, India; Kumar S., Department of Survey Research and Data Analytics, International Institute for Population Sciences, Mumbai, India