The outcome of this paper presents a significant inequality of out-of-pocket spending on elderly health at the levels of economic quantile, sector, gender, social group, and religion. The most affluent population is more likely to pay more for healthcare services than the poorest. It shows that the ability to pay for healthcare services is concentrated among the richest population, which is also confirmed through the concentration indices, reflecting that the accessibility and affordability of healthcare services are costly. Previous literature suggests that out-of-pocket spending among the most affluent population is high, and low-income people are less likely to spend on healthcare services due to high costs or just ignore the illness to take care of (Jane & Thomas, 2012; A. Pandey et al., 2018). This result might imply that the elderly population pays a large amount of out-of-pocket due to the direct relationship between aging and health deterioration. At old age, ignorance of healthcare would be likely to compromise their quality of life. The poor older adults might not be able to afford the increasing cost of healthcare services, and therefore their quality of life might worsen.
Above mention Fig. 2 shows that Indian elderly spends, on average, approximately 17% of their consumption budget on healthcare services. For both inpatient (17%) and outpatient (14%) services, out-of-pocket spending is relatively high in the case of the elderly population. But the share of out-of-pocket consumption budget is quite high for both inpatient and outpatient services among the poorest compared to the richest. The poorest population spends twice as much of their consumption budget on healthcare services than the richest counterpart. This result is consistent with previous literatures that the increased share of out-of-pocket spending scenario among the poorest compared to the richest is observed as a very regressive in low-income countries (Chaudhuri & Roy, 2008; Ruger & Kim, 2007; Sirag & Nor, 2021; Van Damme et al., 2004; Wagstaff et al., 2020). Higher spending on healthcare might occur due to income gap across economic quantiles and less expensive but frequent outpatient visits than hospitalization might increase their out-of-pocket spending. Older people need healthcare support and cannot be ignored these services at old age which can reflect the financial burden on the bread-winner due to high out-of-pocket spending.
There is no well-defined threshold level to measure the incidence of catastrophic health expenditure (CHE) (Azzani et al., 2019). Hence, it is better to take a range of threshold levels for both subsistence and non-subsistence expenditure methods to estimate the incidence of CHE. The above result, Table 3, shows that 46.5% and 13.7% of the elderly population incurred CHE that exceeded 10% and 40% threshold levels based on subsistence expenditure, whereas 42.2% (26.2%) and 26.2% (28.8%) of the elderly population incurred CHE that exceeded 20% and 40% of non-subsistence expenditure according to Tendulkar (Rangarajan) committee poverty line. Past studies found, mainly based on at 40% threshold level of non-subsistence expenditure, 7% of CHE incidence among older adults (Brinda et al., 2015) and recently, 19% of CHE incidence among households with an older adults (Panda & Mohanty, 2022). Similarly, In China, the CHE, measured at 40% of non-subsistence expenditure, among elderly has been increased from 12.9% in 2011 to 27.9% in 2015 (Y. Zhou et al., 2021). The overall incidence of CHE for health services in India was 12.5% (2004), 13.4% (2014), and 9.1% (2018) at the 40% threshold level (Mohanty & Dwivedi, 2021). Finding in this paper is solely among elderly population with subsistence expenditure and two different measurement of non-subsistence expenditure. The occurrence of CHE among the elderly population by non-subsistence expenditure measures is much higher than in subsistence expenditure measures. This estimate reflects that a large amount of the Indian population spends on essential consumption (Panikkassery, 2020), which is seen through the past literature that people in low-income countries spend primarily on food and other necessities (Banerjee & Duflo, 2007).
As above mention result, Table 3, shows that socio-economic inequality persists in accessing and affordability of healthcare services between rich-poor, rural-urban, male-female, social groups, and religions. The incidence and intensity of CHE among the elderly population being poor, living in rural areas, being a male, and belongs from schedule castes is higher than their respective counterparts. This result is consistent with past studies which show that these variables are the risk factors of incurring CHE (Azzani et al., 2019; Pal, 2012; Yardim et al., 2010). The intensity of CHE among older adults is quite high in non-subsistence expenditure methods than the subsistence one. Within non-subsistence expenditure methods, Rangarajan method of non-subsistence expenditure shows an extreme intensity of facing a high risk of CHE among older adults due to out-of-pocket spending. Low income, lack of economic independence, expensive healthcare services, low coverage of health insurance, frequent visits of quackery, and private medical motive of profit maximization, lack of healthcare facilities, long distance of medical care from remote areas, transportation facilities at midnight and its costs, and patriarch lineage of property rights can be some of the reasons of facing the risk of CHE among older adults. Overall, at a 10% threshold level of subsistence expenditure or a 20% threshold level of non-subsistence expenditure, every socio-economic group bears the high expenses for elderly healthcare services. As we increase the threshold up to 40% for both subsistence and non-subsistence expenditure, the occurrence of CHE declines, which means that marginalized socio-economic groups either they cannot bear more expenses for elderly healthcare services or not seeking healthcare services at all.
Further, we measure the incidence of impoverishment due to CHE. We utilize both Tendulkar (2011-12) as well as Rangarajan (2014) committee poverty lines to estimate the incidence of poverty among the elderly population in India. In Table 4, the incidence of poverty headcount of the elderly population before accounting for the healthcare payments is 4.3% (10.6%) by Tendulkar (Rangarajan) approach, and after considering healthcare payments, the poverty headcount increases to 14.2% (22.2%) respectively. 9.8% (11.5%) of the elderly population are being pushed towards poverty after out-of-pocket spending. It shows that more than half of the elderly population below the poverty line are further pushed into extreme poverty, which might be a poverty trap for them. According to the World Bank poverty estimate (a person living on less than 1.90 US dollars a day), about 20% of India's population lives in extreme poverty (World Bank, 2017). According to the NITI Aayog report (2021), the overall multidimensional headcount ratio is 25.01%, in which rural and urban areas consist of 32.75% and 8.81%, respectively. In Table 5, the incidence of poverty headcount in rural areas is greater than the urban areas. According to Tendulkar (Rangarajan) committee, 12.4% (13.8%) and 5.3% (7.3%) of the elderly population are falling into poverty due to healthcare payments in rural and urban areas, respectively. The rural elderly population below the poverty line is further pushed into deep poverty than their urban counterparts. If we interpret these results in numbers, that would be quite high since India is the second most populous country in the world, where 104 million consists of the elderly population (Census, 2011), and still rising.