Equity and Elderly Health in India: Reflections from 75th Round National Sample Survey, 2017-18, amidst the COVID-19 Pandemic

doi:10.21203/rs.3.rs-41285/v2

Background: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) outbreak, called coronavirus disease - 2019 (COVID-19), has affected more than 200 countries across the globe with a higher fatality rate in the elderly population. Historical experience shows that the pandemic disproportionately afflicts the socioeconomically disadvantaged population. Aim of the study is to highlight the vulnerability of the aged amidst the current pandemic, in the light of the recent international evidence, and what government could do to mitigate their vulnerability.

Methods: Data from the recently released (November 2019) 75 th Round National Sample Survey (NSS), which was conducted from July 2017 to June 2018, across 8077 rural villages and 6181 urban wards was used for this study. Data collected from 555115 individuals (rural: 325232; urban: 229232) included that of 42762 elderly individuals (60 years or above). Bivariate and multivariate analysis was used for the calculation.

Results: 27.7 % of elderly reported suffering from any ailment in the last 15 days, whereas 8.5% had hospitalization during the last 365 days. Hospitalization rate was higher in the urban areas (OR: 1.21), general category (OR: 1.18), richest economic quintile (OR: 1.68), and among elderly living alone (OR: 2.05), which was statistically significant. 64% of the scheduled tribe and 51.0% of the poorest income quintile elderly utilized public facilities during hospitalization. Cardiovascular ailments were major cause for hospitalization (18.1%) and outpatient visit (32.0%) in the elderly. Diabetes and hypertension together constituted 55% of outpatient visit for the elderly. 18.9% of the elderly has health insurance though chances of facing catastrophic health expenditure was high in the elderly. 6.6% of elderly female and 1.6% male live alone, and 27.5% of elderly of age 80 years or above are immobile. 50% of male and 90% of female are financially dependent on others and more so in poorer economic quintiles.

Conclusions: The vulnerability of India’s elderly increases across various equity dimensions which include the place of residence, gender, caste, marital status, economic quintile, living arrangements, surviving children, and economic dependence. The current COVID-19 pandemic poses a greater risk of social isolation among the elderly, which may lead to detrimental health impact.

Infectious Diseases

Geriatrics & Gerontology

Health Policy

Elderly Heath

Equity

COVID-19

India

As the current Coronavirus Disease (COVID-19) pandemic is spreading across the globe, the elderly population (60 years or above) becomes more vulnerable [1, 2]. Being elderly in itself is a fragile condition, and the current COVID-19 pandemic exposes it more.

Mortality data from different countries and various other studies show that the elderly population is more susceptible compared to their younger counterparts [2, 3]. However, all elderly are not equally vulnerable to COVID-19. Mortality data from South Korea shows fatality due to COVID-19 was 1.8% in the age group 60-69 years, 6.3% in 70-79 years, and 13% in the age group 80 years or above [4]. Emerging studies from the United States also show that chances contracting COVID-19 was three times higher in black counties compared to white counties, and similarly, the death rate in black counties was six times higher than white counties [5]. Even in India, spread and fatality of COVID-19 is significantly higher in slums where poor people live [6].

In this regard, it is imperative to understand the current status of the elderly’s health and related socioeconomic dimensions in India. This may provide valuable insights about mitigation strategies to take care of the elderly during the current COVID-19 pandemic, equitably. Recently released data (November. 2019) by the National Sample Survey (NSS) for its 75^th Round, 2017-18, on social consumption related to health, gives a valuable opportunity to visit health status of elderly in the country [7]. It also gives the opportunity to see health status and social support system of the elderly across socioeconomic indicators. To the best of the author’s knowledge, this is the most recent national-level unit data on the elderly before the outbreak of the COVID-19 pandemic. Aim of this study is to present the current health status of the elderly in the country across various socioeconomic categories, and to relate it with the impact of COVID-19 pandemic. Even in the elderly population, vulnerability varies across various equity dimensions viz-a-viz place of residence, gender, caste, occupation, income quintile, living arrangements, and economic dependence. This study also aims to provide insights about the interplay of these factors. This paper is organized as follows:, Section II presents details of the methods used for analysis: Section III presents results related to elderly health status, access to healthcare, financial risk protection, living arrangements, economic dependence, physical immobility, perception of self-health, and changes in the health status of elderly from 2014 to 2017-18; Section IV presents a discussion on lessons learned from these finding, and Section V concludes with a few suggestion for mitigating the adverse impact of the current pandemic on the elderly in India.

Data for the current study is extracted from the 75^th Round of NSS, which is a nation-wide sample survey conducted by the Government of India from July 2017 to June 2018 [7]. Data was collected from 113823 sample households and 555115 individuals (Rural: 325883; Urban: 229232; Male: 283200; Female: 271877) from randomly selected 8077 villages and 6181 urban wards by double stage sampling. In the first stage, rural villages and urban wards were selected, and in the second stage, households were selected. This entire sample included 42762 elderly individuals.

The 75^th Round NSS, 2017-18, collected data related to demographic details, household characteristics, morbidity and mortality, hospitalization in the last 365 days, health insurance coverage, out-of-pocket expenditure (OOPE), healthcare utilization, immunization coverage, maternal health, and elderly health [8].Survey considers 15 days recall period in self-reporting of acute ailments. One of the possible reasons for choosing 15 days recall period over monthly recall (30 days) might be to reduce the recall bias in reporting the ailments. There is a higher chance of forgetfulness in monthly reporting over 15 days. Also, monthly reporting of acute ailment might erase significant fraction of relevant actions (doctors visit, expenditure on health, duration of illness etc.) taken by individuals, and more so in lower socio-economic population [8]The current study focuses on elderly health and indicators related to that.

For analysis purpose, age of the elderly was categorized as 60-69, 70-79, and 80 years and above. Employment status was broadly categorized as self-employed, regular wage, casual labourer, and others. Economic quintiles for the household were assigned based on the Usual Annual per capita Consumption Expenditures (UAPCE) for rural and urban areas, respectively. UAPCE includes household expenditures other than for healthcare. It categorizes households into five economic quintiles (1-poorest, 2-poor, 3-middle, 4-rich, 5-richest). All individuals above the age of seven were categorized under broader education categories of illiterate, up to primary (8^th std.), up to secondary (10^th std.), and above secondary level.

Members of households were asked whether they were hospitalized in the last 365 days; and whether they suffered from any long term chronic ailment or acute ailment in the last 15 days. Data on chronic and acute ailments were used for calculating Proportion of Ailing Person (PAP) in the last 15 days.

The survey also collected information from households on where they sought care from private or public facilities, and the amount spent for various services, including physician fees, drugs, diagnostics, and non-medical expenses such as travel, food etc., for both inpatient and outpatient services, and who paid for such expenses.

A total of 63 different reported ailments were broadly grouped under following 15 ailment-categories. These are: infections, cancer, blood disease, endocrine and metabolic disease including diabetes, psychiatric and neurological, genito-urinary, eye, ear, cardio-vascular including hypertension, respiratory, gastrointestinal, skin, musculoskeletal, injuries, obstetric, and unclassified conditions.

Detailed information on how expenses were met from various sources and who paid for such expenses were obtatined for each episode of illness and service utilization. Out of pocket expenditures (OOPEs) were calculated (which is net of medical and transportation expenditures after deducting reimbursement from the insurance schemes). Catastrophic health expenditure at 10% (CHE-10) and 25% (CHE-25) threshold was calculated if the total annual health expenditure of the household was higher than 10% and 25%, respectively, of UAPCE, based on WHO SDG goals[9].

Elderly were asked additional questions regarding their living conditions: whether 1) Living with spouse and other members, 2) Living with spouse only, 3) Living without spouse but with children or relatives, 4) Living alone but not as an inmate of old age home, and 5) Living alone as an inmate of old age home. Financially, whether they are totally independent, partially independent, or totally dependent on others. For our analysis, partially dependent or totally dependent were considered as “dependent”.

Besides, information on their physical mobility, which is an indicators of their disability [10], was recorded. In present study, “confined to bed”, “confined to home”, “movement on wheelchair” are considered as ‘physically immobile’.

Elderly were also asked about their surviving children. We categorize them as living under “at least one living child” and “no child” for analysis purpose.

It is important to note that the elderly were asked about their self-perception of current health status, which was categorized as excellent, good, and poor. They were also asked to compare their perception of current health status with the previous year’s health status, such as, ‘much better’, ‘somewhat better’, ‘nearly the same’, ‘somewhat worse’, and ‘worse’. “Somewhat worse” and “worse” have been categorized as “worse” in our analysis.

Binary logistic regression was used to understand factors affecting hospitalization, PAP, CHE-10, CHE-25, living arrangements, and economic dependence in the elderly. In case of hospitalization, the dependent variable was the incidence of hospitalization, and independent variables were age group, place of residence, gender, marital status, surviving children, social group (caste), education category, household occupation, economic quintile, insurance coverage, economic independence, and living arrangements. Similarly, for the incidence of PAP, the same independent variables were used like hospitalization except insurance coverage since by mandate, insurance schemes do not cover outpatient care. For CHE-10 and CHE-25, other than the above mentioned independent variables, choice of provider (public or private) was used. To understand factors affecting living arrangements and economic independence in the elderly population, chances of ‘living alone’, and chances of ‘being dependent’ were dependent variables, with same independent variables (except economic independence and living arrangments) mentioned above for the logit model hospitalization, These variables have been included based on suggestions from existing literature [11–16] . No multicollinearity was found among independent variables.

Findings of the 75^th Round NSS, 2017-18, were also compared with 71^st Round NSS, 2014, for similar indicators, to understand the change in state of elderly health from 2014 to 2017-18. Bivariate and multivariate analyses was performed using STATA version 14.1.

Findings of the study are presented under eight themes: 1) Demographic characteristics 2) Disease burden and access to healthcare, 3) Financial hardship, 4) Living arrangements, 5) Economic dependence, 6) Physical immobility, 7) Perception towards own health, and 8) Change in health status of the elderly from 2014 (71^st Round NSS) to 2017-18 (75^th Round NSS). All observations relate to the elderly population, unless stated otherwise.

Demographic characteristics. The average age of the elderly population in India was 67.5 years (Table 1). Out of total elderly population (60 years or above), 66.1% are in the age group of 60-69 years, 25.9% in (70-79), and 8% are aged 80 years or above. 67.1% of India’s elderly live in rural areas. Proportion of female (50.9%) is higher than male (49.1%). In terms of the social groups, 6.2% elderly belongs to ST category, 17.4% SC Category, 42.3% to OBC, and 34.3% belongs to general category. More than half (54.1%) of the elderly people are illiterate, and 20% belongs to those households where casual labour is the main household occupation. 4.3% of the elderly in India do not have a surviving child (Table 1).
Disease-burden and access to healthcare:

2.1 Outpatient care. Out of every 100 elderly, 27.7 pesons reported ailments during the previous 15 days; of this, 22.4 reported chronic ailments, and 5.7 reported acute ailments (Table 2). PAP was significantly higher among 80 years or above (36.7%), those in urban areas (34.0%), widowed (30.8%), general category (33.2%), having regular wages (31.5%) and in the richest economic quintile (rural-36.8%, urban-43.8%, Table 2, Table 3). The logistic model shows that chances of reporting ailment in last 15 days was 1.43 times higher among 80 years or above compared to those in age group 60-69 years; 1.40 times higher in urban areas compared to rural areas, 1.1 times higher in males compared to females, 2.27 times higher in general category compared to lower socio-economic groups (ST category), 1.32 times higher among those with primary level education compared to illiterate, 1.16 times higher among casual labourerers compared to regular wage earners, and 2.23 times higher among those in the richest economic quintile compared to their poorest counterparts (Table 3).

Cardiovascular conditions including hypertension (32.0%), endocrine conditions including diabetes (22.5%), musculoskeletal conditions (13.9%), infectious diseases (10.0%), and respiratory ailments (7.3%) were the top-five conditions for seeking outpatient care among the elderly in the last 15 days (Table 4). 33.6% of the elderly went to a public provider in the last 15 days, particularly for cancer (55.8%) and eye-related problems (47.5%,Table 4). Public healthcare utilization was higher in rural areas (39.7%), ST category (43.5%), casual labourer (50.3%), illiterate (37.7%), never married or divorced (47.6%) and poorest economic quintile (rural-45.3%, urban-41.6%, Table 2).

2.2 Inpatient care. Overall hospitalization rate among the elderly was 8.5%, and was highest among 80 years or above (14.3%) - it was significantly higher for male (9.5%), those in urban areas (10.1%), never married/divorced (8.8%), those with no surviving children (21.3%), in general social category (10.0%), regular wages earners (9.2%) and those in the richest income quintile (rural-11.2%, urban-11%) compared (Table 2 and Table 3). Cardiovascular disease (18.1%), infectious diseases (16.6%), eye ailments (8.4%), psychiatric or neurological conditions (8.2%), and injuries (7.9%) were the top five reasons for hospitalization in last 365 days (Table 4).

Public facilities accounted for 39.8% of all inpatient services - it was higher in rural areas (44.5%), those with no surviving children (46.0%), ST category (64.0%), illiterate (46.1%), and poorest income quintile (rural-51.0%, urban-47.7%, Table 2). Share of the public sector was higher for cancer treatment (52.8%), skin related ailments (50.3%), infectious diseases (48.3%), and blood diseases (46.8%) whereas the share of the private sector was higher for most other conditions. For instance, private facilities accounted for 72.2% of genito-urinary, 63.2% of psychiatric and neurological conditions, and 63.1% of injury related inpatient care (Table 4).

Financial risk protection

Publicly funded health insurance (PFHI) coverage and tax based subsidized public provisioning are the two major strategies used by the government for providing financial risk protection in India [17].

3.1 Health Insurance. Overall, 18.9% of the elderly are coved by insurance based health; where PFHIs covered 14.3% population. PFHIs only cover inpatient care in India, whereas Central Government Health Schemes CGHS (2.1%) and ESIS (0.7%) also cover outpatient care. Private insurance also provided coverage (1.8%), but for inpatient care alone [7]. PFHIs coverage among the elderly was higher in rural areas (16.6%), ST category (20.7%), illiterate (16.6%), casual labourer (18.2%), and poorest rural quintile (12.8%) in India. Insurance coverage in urban areas was more equitable compared to rural areas, since PFHI coverage was higher in poorer quintile compared to richer quintile in urban elderly. In the rural areas, PFHI coverage was higher in top two quintiles compared to the bottom two quintiles (Table 5).

3.2 Outpatient care. OOPE for outpatient care was Rs. 390 per visit under public sector, and Rs.852 per visit under private sector (Table 5). OOPE was significantly higher for those 80 years or above age group (public: 430, private: 1039). OOPE was almost the same under rural and urban India. OOPE was higher for male compared to the female gender in the public sector, whereas under the private sector it was nearly the same. OOPE was higher in ST category population compared to general category population in both public and private sectors. The public sector was more equitable compared to the private sector. For instance, under public sector, OOPE was Rs. 371 for the poorest income quintile as Rs.564 for the richest quintile. On the other hand, under the private sector, OOPE was Rs. 995 for the poorest quintile and Rs. 916 for the richest quintile.

3.3 Inpatient care. Average OOPE was Rs. 6209 under public sector and Rs. 38709 under private sector. OOPE was significantly higher for male, urban areas, never married or divorced, elderly without children, ST category, above secondary literate, and richest quintiles compared to their counterparts (lower quintiles). For instance, OOPE for the poorest rural quintile was Rs. 5084 in public and Rs. 19410 in private provider; whereas it was Rs. 7949 and Rs. 39683 in the richest rural quintile, respectively (see Table 5).

CHE-10 and CHE-25 were calculated to estimate the impact of OOPE on the households. 23.2% of inpatients in public sector faced CHE-10, whereas 64.9% faced CHE-10 under private sector. Similarly, CHE-25 was 9.1% under public sector, and 37.0% under private sector. CHE-10 and CHE-25 were higher among those in 60-69 years age group, rural areas, male gender, never-married individuals, ST category, casual labourer, and poorest income quintile compared to their counterparts (Table 5). Chances of facing CHE-10 and CHE-25 was statistically higher for rural areas, male gender, those with no surviving children, in the poorest quintile, non-insured population, who used private provider and among the elderly living alone (Table 3). Similarly, chances of facing CHE-10 and CHE-25 was 8.17 and 7.5 times higher, respectively, under the private sector compared to the public sector.

Living arrangements:

4.2% of the elderly population lived alone, whereas 14.1% lived with spouse only (Table 6). The elderly population living alone was higher in rural areas (4.4%), female gender (6.6%), never married or divorced individuals (22.2%), elderly with no surviving child (16.1%), illiterate population (5.0%), and the richest income quintile (rural-7.0%, urban-6.5%). Also, those living with their spouse were higher in the top two income quintiles compared to the bottom two quintiles. Chances of living alone was higher in 60-69 years age group, rural areas (OR: 1.35), female (OR: 1.24), widowed (OR: 2.4), general category (OR: 1.45), and richest income quintile (OR: 1.87), and it was statistically significant ( Table 3).

Economic dependence

47% of elderly in India were financially on others; 30.1% were independent, and 22.9% were partially dependent (Table 6). In other words, 70% of India’s elderly were, partially or entirely, financially dependent on others. Complete financial dependence was higher among those 80 years or above (70.8%), female (67.1%), widowed (62.8%), illiterate (55.5%), and poorer quintiles. Chances of being economically dependent were higher in 80 years or above (OR: 3.36), female (OR: 9.5), general category population (OR: 1.20), elderly not living alone, and poorer quintiles and it was statistically significant (see Table 3).

Physical immobility:

Physical mobility is one of the proxy indicators for locomotor disability. In India, 7.6% of the elderly were either completely (bedridden) or partially immobile (on a wheelchair or restricted within the home). It was considerably high among those 80 years above (27.5%), female gender (8.9%), widowed (11.9%), illiterate population (8.7%), and poorer income quintiles. However, immobility increases steeply for the richest quintile (rural-8.3%, urban- 9.5%) compared to other quintiles (Table 6).

Perception of self-health

In India, one in five elderly (19.6%) felt their current health was poorer, and a similar proportion (21.0%) that their health condition had deteriorated compared to the previous year (Table 6). Perception of health being poor was higheramong those above 80 of years; in rural areas it was 21.4% and among the widowed elderly, it was 26%. About 20% of those in poorest urban quintile perceived their health had deteriorated compared to the previous year (Table 6)

Change in the health status of the elderly in NSS 75^th Round, 2017-18, compared to NSS 71^st Round, 2014

Hospitalization rate among elderly fell from 10.9% in 2014 to 8.5% in 2017-18 (see Table 7). Also, PAP fell from 30.3 (out of 100 reported elder persons) in 2014 to 27.7 in 2017-18. Share of the public sector in outpatient care increased from 28.3% in 2014, to 33.6% in 2017-18, whereas its share in inpatient care increased from 35.9% to 39.0%. OOPEs under public sector fell from Rs. 547 (in 2014) to Rs. 390 (in 2017-18) for per outpatient visit and from Rs. 7177 to Rs 6209 for per-hospitalization visit. On the other hand, OOPEs under private sector increased from Rs. 802 to Rs 852 per outpatient visit, and Rs. 31,875 to Rs. 38,709 per hospitalization visit, during the same period (see table 7).

Proportion of elderly population living alone almost remained the same, whereas proportion of the elderly population dependent on others fell marginally from 71.7% (in 2014) to 69.7% (in 2017-18). Similarly, elderly population who felt their health has deteriorated compared to last year dropped from 25%, in 2014, to 21%, 2017-18 (see Table 7).

Here we discuss the extent to which the elderly population is vulnerable in the light of the emerging international literature and evidence.

Disease burden in the elderly population (PAP: 27.7%, hospitalization rate: 8.5%- Table 2) is disproportionately higher compared to the population below the age of 60 years (PAP: 5.9 %, hospitalization rate: 2.4 %) [7]. Self-reported hospitalization rate and PAP was significantly higher in upper socioeconomic population compared to the lower socioeconomic population since perceived healthcare needs are higher in upper socioeconomic population. Various studies have shown that poor and marginalized section of society has a higher burden of non-communicable diseases and chronic conditions [18]. In current COVID-19 pandemic, studies from China, Italy, Spain, and the United States have shown that NCD patient are at higher risk of mortality due to COVID-19 [19–21]. In the elderly population, these comorbid conditions further aggravate the COVID-19 condition and increase mortality [22].

In India, one-third of the elderly went to public healthcare facilities (hospitalization: 39.8%, outpatient care: 33.6% -Table 2), whereas remaining two-third went to private healthcare facilities. Often, elderly patients require lifelong treatment, curative and rehabilitative, for their chronic conditions. These conditions require regular follow-up, which includes doctor’s consultation, continued medication, and diagnostic tests. India’s healthcare systems, both public and private, lack this continuity of care, which leads to poor quality of care for the elderly, and it has its detrimental effects on the elderly’s health [23]. Rehabilitative care is almost absent in India’s public health system and in some urban areas where private sector provides this care is prohibitively costly, which poor and middle income elderly cannot afford [24]. All these may lead to further suffering, poor quality of life, and mortality for the elderly.

In the current COVID-19 pandemic, the public healthcare system has been overstretched in handling the avalanche of COVID-19 patients. It has seriously disrupted provision of regular services at public healthcare facilities which include immunization, child and maternal health, dialysis services, emergency surgeries, and general outpatient care [25]. A recent study done by Stop TB Partnership shows that for every month of lockdown in India, there would be an additional 2,32,665 TB cases and 71,290 deaths in the period of 2020-2025 [26]. Public facilities are major service providers for the poor and marginalized elderly in society. For instance, 64% of ST, 54% of the casual labourer, and 51% of rural poorest elderly took inpatient care under the public facility in 2017-18 (see Table 2).

Private sector, which provides two-thirds of care for the elderly, has not been able to respond adequately in the country [27, 28]. A significant proportion of private providers has either stopped providing care due to fear of the spread of the diseases or they have started charging exorbitantly high which cannot be afforded by the poor and middle-class person of the society [29, 30].

Availability of regular drugs, related to chronic conditions, face additional logistic constraints after the nation-wide lockdown [31]. As part of the latest controversy on the use of hydroxychloroquine drug for covid-19 patients , this drug became unavailable for rheumatic patients, which is a common ailment in the elderly population in India and across the world [32, 33]. Public health facilities, where these drugs are provided free of cost to patients (who are largely poor), reported shortage of regular NCD drugs [34]..

Elderly face greater risk of financial hardships due to chronic nature of ailment and comorbidities, which require long term care. In India, OOPE was Rs. 390 under public and Rs. 852 under private sector for per outpatient visit whereas it was Rs. 6209 and Rs. 38709 for inpatient care, respectively, for elderly.

Another dimension of financial hardship for the elderly comes from the fact that 70% are partially or wholly financially dependent on others (see Table 6). It is even higher for those in the lower socioeconomic groups. For instance, 50% of elderly males and 90% of females are dependent on other family members for financial support. In rural areas, elderly parents are dependent on their children who work as a migrant labourer in urban settings. In the current crisis with lockdown, the unemployed, migrants from urban areas to rural areas, would find it difficult to send money back home to their elderly dependent parents [35].

One of the direct impacts of the current pandemic for the elderly could be lack of access to food leading to starvation. For instance, study done by Pradhan, shows that 50% of India’s rural households are eating less compared to pre-COVID-19 outbreak [36]. Studies across the world also fear that food insecurity, hunger, and malnutrition could be one of the worst outcomes of the pandemic [37].

In terms of social welfare schemes, central and state governments have announced various measures for delivering free food grains and direct transfer of pension for the elderly people [38]. However, there is considerable variations in old age pension across states of India. The highest state government contribution is from Puducherry (Rs. 1800) followed by Haryana (Rs. 1600), whereas states like Arunachal Pradesh, Assam, Karnataka and North- Eastern States do not contribute at all. There are only six states in India who have a share of old-age pension beneficiaries more than 50% of the total older population whereas 14 states have beneficiaries less than a quarter of the eligible elderly [39]. At all India level, only 29.6% of the elderly receive an old-age pension of the total older population. It is important to note that mandate for the old-age pension is for all irrespective of being from APL or BPL families. These figures show that old-age pension, one of the social care policies, is highly inadequate and leaves out a large section of the elderly population in India. Evidently, current COVID-19 situation makes the elderly more vulnerable financially.

Physical/social distancing has considerably increased social isolation and more so for the elderly population [40]. Studies have established that social isolation increases depression, suicidality, and a higher chance of increased inflammatory response in the elderly [41, 42]. This will also exacerbate the vulnerability of those elderly who are already suffering from psychiatric or neurological conditions (8.2% of total hospitalization in the last 365 days and 4.4% of PAP in last 15 days). For instance, recent studies published post-COVID-19 outbreak has shown that this pandemic has considerably increased the vulnerability of demented patients and their caregivers across the world [43, 44]. One of the suggestions which have been given to elderly by Ministry of Health and Family Welfare (MoHFW), Government of India [45], and Centre for Diseases Control and Prevention (CDC), Atlanta, United States [46], is to be in contact with significant others in current COVID-19 outbreak, through mobile phone and video call. However, a significant proportion of the elderly population finds it difficult to operate a mobile phone which is one of the instrumental activities of daily living (IADL) [47]. In India, 4.2% (50 lakhs) of elderly live alone, and it was more so for women (6.6%), never married elderly (22.2%), elderly without children (16.1%) and illiterate (5.0%).

In India, 7.6% elderly (one crore individuals) population are immobile, and it is even more so among poorest (rural: 8.4%, urban: 8.5%), illiterate (8.7%), and widowed (11.3%) elderly. Often, they are taken care of by a family member; care provision through a hired provider is rare. In current social distancing measures, it has adversely impacted the caregiving for these elderly. Studies also show informal or unpaid caregiving has been associated with an elevated level of depression and anxiety, higher use of psychoactive medication, worst self-reported physical health, compromised immune function, and increased risk of early death in caregiver providers of elderly [48].

This unprecedented situation of COVID-19 draws our attention towards the need for strengthening public healthcare facilities in the country. With all its inadequacies and inefficiencies, the public healthcare system is largely managing the pandemic across the country. COVID-19 is a wake-up call for greater investment in public health facilities which include strengthening public infrastructure, skill building for health professionals, strengthening diseases surveillance system, improving quality of care in public healthcare facilities, and better continuity of care between primary and tertiary care. The idea of “Health and Wellness Centre (HWCs)” under Ayushman Bharat is a welcome decision since it proposes to provide comprehensive primary healthcare at health sub-centre (HSC), or nearer to home. The elderly population and poor will be the major beneficiaries of this scheme since they bear the greater diseases burden. Current COVID-19 pandemic shows the need of implementing the HWCs scheme as envisaged in the policy document is more than ever [49].

One of the possible limitations of the study could be the fact that it uses 2017-18 data and not the real-time data collected during the COVID-19 outbreak. Real-time data has a greater possibility of capturing the human response to pandemic more accurately. We have not been able to capture the life experiences and coping mechanisms of the elderly during the current pandemic. Such studies would provide enormous sociological insights and inputs for more “responsive” policy measures to enhance the quality of life of the elderly.

The vulnerability of India’s elderly increases across various equity dimensions which include the place of residence, gender, caste, marital status, economic quintile, living arrangements, surviving children, and economic dependence. The current COVID-19 pandemic poses a greater risk of social isolation among the elderly, which may lead to detrimental health impact. The poor among the elderly has suffered more than others. As a result, their access to regular primary healthcare services, and continuity of care that is essential for those suffering from non-communicable diseases, given their dependency and lack of mobility, may have worsened further during this pandemic. Overall, given the evidence on the possible hardships that the elderly may be have already gone through during the pandemic and hardships that they may face in the future, the importance of strengthening public health care system cannot be over-emphasized. We urge a greater investment by government to mitigate adverse impact of the pandemic and enhance the quality of life of the elderly in the future.

CHE: Catastrophic health expenditure

CHE-10: Proportion of households in a population who face catastrophic health expenditure computed using the threshold of 10% of usual annual consumption expenditure

CHE-25: Proportion of households in a population who face catastrophic health expenditure computed using the threshold of 25% of usual annual consumption expenditure.

HSC: Health Sub Centre

HWC: Health and Wellness Centre

NSS: National sample survey

NSSO: National sample survey office

OOPE: Out-of-pocket expenditure

PFHI: Public Funded Health Insurance

PHC: Primary Health Centre

UAPCE: Usual annual per capita expenditure

UMPCE: Usual monthly per capita expenditure

Ethics approval and consent to participate: The data analysed for this article are from the National Sample Survey, 75^th Round, which contains anonymised data in the public domain (online available). The researchers had no access to personal identifiable data. The survey is undertaken by the National Sample Survey Office (NSSO) of the Ministry of Statistics and Programme Implementation of the Government of India. Data available in public domain are approved for use for research purpose by Ministry of Statistics and Programme Implementation, Government of India [7].

Consent for publication: Not Applicable.

Availability of data and materials: The present study is based on India’s National Sample Survey, 2017-18, which is freely available in the public domain (http://www.mospi.gov.in/unit-level-data-report-nss-75th-round-july-2017-june-2018-schedule-250social-consumption-health) [7].

Competing interests: The author declares there was competing interest.

Funding: None.

Author’s contributions: RA and VRM contributed to the study design, to the interpretation of results, and writing the manuscript. RA analyzed the data and VRM verified the results. Both authors read and approved the final version of the manuscript.

Acknowledgements: Not applicable.

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Table 1: Demographic and Socio-economic characteristics of sample elderly population in India

	India	Sample size (N)
Mean Age (years)	67.5	42762
Age group (years)
60-69	66.1	27769
70-79	25.9	11235
80 and above	8.0	3758
Place of Residence
Rural	67.1	23599
Urban	32.9	19163
Gender
Male	49.1	21902
Female	50.9	20858
Marital Status
Never Married/ divorced/ separated	0.9	395
Currently married	64.7	29324
Widowed	34.4	13043
Surviving Children
At least one surviving child	95.7	41409
No child	4.3	1353
Social Groups
ST	6.2	3913
SC	17.4	6133
OBC	42.3	16519
General	34.3	16197
Education
Illiterate	54.1	20194
Up to primary	21.1	9375
Up to secondary	14.3	7752
Above Secondary	10.5	5441
Household occupation
Self employed	48.1	20986
Regular Wages	15.5	8536
Casual Labourer	20.0	6709
Others	16.5	6531
Economic quintile-Rural
Poorest	19.1	3773
Poor	19.0	3945
Middle	21.0	4651
Rich	19.5	4949
Richest	21.3	6281
Economic quintile-Urban
Poorest	21.7	4776
Poor	18.0	3614
Middle	20.9	3696
Rich	22.0	3537
Richest	17.3	3540

Source: Authors’ computation from unit records of NSSO 75^th Round 2017-18

Table 2: Disease burden and access to healthcare in elderly population of India

	Hospitalization (in %)		Out-patient care (in %)
	Hospitalization rate	Share of hospitalization under public sector	Proportion of population reporting chronic condition	Proportion of population reporting ailment in last 15 days	PAP in last 15 days	Share of PAP under public sector
Total	8.5	39.8	22.4	5.7	27.7	33.6
Age group (years)
60-69	7.1	40.4	20.3	5.2	25.1	34.0
70-79	10.1	40.8	25.3	6.8	31.7	33.2
80 and above	14.3	35.5	31.2	6.8	36.7	32.2
Place of Residence
Rural	7.7	44.5	19.0	6.0	24.6	39.7
Urban	10.1	32.7	29.5	5.2	34.0	25.5
Gender
Male	9.5	40.3	22.2	5.8	27.5	33.5
Female	7.5	39.3	22.6	5.7	27.9	33.7
Marital Status
Never Married/ divorced/	8.8	41.8	23.1	2.2	25.0	47.6
Currently married	7.8	38.1	21.2	5.3	26.1	32.1
Widowed	7.7	40.4	24.8	6.5	30.8	35.7
Surviving Children
At least one surviving child	7.8	38.9	22.5	5.8	27.9	33.5
No child	21.3	46.0	19.9	4.5	24.2	37.0
Social Groups
ST	5.5	64.0	10.6	7.3	17.8	43.5
SC	7.5	53.2	18.4	6.5	24.7	38.6
OBC	8.2	38.4	20.9	5.6	26.0	42.2
General	10.0	33.8	28.5	5.3	33.2	22.7
Education
Illiterate	6.1	46.1	17.8	5.9	23.4	37.7
Up to primary	10.3	42.8	26.5	6.8	32.6	41.2
Up to secondary	9.7	29.1	30.4	4.9	34.5	26.7
Above Secondary	8.0	17.4	27.5	3.7	30.8	15.3
Household occupation
Self employed	7.1	36.5	20.1	6.0	25.8	31.0
Regular Wages	9.2	37.4	25.7	6.2	31.5	27.1
Casual Labourer	6.5	53.8	18.6	5.8	24.0	50.3
Economic quintile-Rural
Poorest	5.0	51.0	9.6	7.3	16.7	45.3
Poor	5.0	52.2	15.8	5.9	21.5	34.9
Middle	6.7	47.1	15.6	6.2	21.6	39.1
Rich	8.3	44.3	20.0	5.6	25.3	39.4
Richest	11.2	37.7	32.7	5.1	36.8	40.5
Economic quintile-Urban
Poorest	9.7	47.7	22.5	4.7	26.7	41.6
Poor	9.7	41.6	28.4	3.4	31.4	31.5
Middle	9.7	35.1	27.3	8.3	35.1	27.1
Rich	10.1	26.4	30.8	4.8	34.7	22.5
Richest	11.0	14.4	40.2	4.3	43.8	12.5

Source: Authors’ computation from unit records of NSSO 75^th Round 2017-18

Table 3: Factors affecting hospitalization, PAP, CHE-10/25, living arrangements and economic independence in India’s elderly

Total	Reporting of hospitalization OR (95% CI)	Reporting of PAP OR (95% CI)	CHE-10 OR (95% CI)	CHE-25 OR (95% CI)	Living alone OR (95% CI)	Economically dependent OR (95% CI)
Age group (years, ref:60-69)
70-79	1.28 (1.22-1.35)*	1.23 (1.17-1.29)*	1.05 (0.95-1.16)	1.09(0.98-1.2)	0.62 (0.51-0.76)*	1.88 (1.77-1.99)*
80 and above	1.26 (1.17-1.36)*	1.43 (1.33-1.55)*	1.06 (0.91-1.23)	1.03 (0.88-1.22)	0.33 (0.25-0.45)*	3.36 (3.02-3.74)*
Place of Residence (ref: rural)
Urban	1.21(1.15-1.28)*	1.40 (1.33-1.47)*	0.51 (0.45-0.56)*	0.53(0.47-0.59)*	0.74 (0.60-0.91)**	0.90 (0.84-0.95)
Gender (ref: male)
Female	0.64 (0.60-0.67)*	0.93 (0.89-0.98)*	0.85 (0.76-0.95)**	0.83 (0.74-0.94)**	1.24 (1.00-1.54)**	9.5 (8.90-10.13)*
Marital Status (ref: never married)
Currently married	0.92(0.72-1.17)	0.94 (0.73-1.20)	1.65 (1.5-2.59)**	1.52(0.92-2.51)	0.01(0.01-0.03)*	0.44 (0.33-0.57)*
Widowed	1.17(0.92-1.49)	1.08 (0.85-1.39)	1.30 (0.82-2.05)	1.26(0.75-2.09)	2.4 (1.54-3.98)*	0.61 (0.46-0.80)*
Surviving Children (ref: no child)
At least one child	0.97(0.85-1.10)	1.29 (1.12-1.48)*	0.71 (0.56-0.90)**	0.77(0.60-0.99)**	0.32 (0.24-0.45)*	2.21 (1.91-2.56)*
Social Groups (ref: ST)
SC	1.09(0.99-1.20)	1.97 (1.76-2.19)*	1.33 (1.08-1.64)**	1.54(1.18-1.99)**	1.58(1.07-2.34)**	1.04 (0.94-1.15)*
OBC	1.16(1.07-1.26)*	2.02 (1.83-2.22)*	1.44 (1.20-1.73)*	1.67(1.32-2.11)*	1.36(0.96-1.94)	1.22 (1.12-1.34)*
General	1.18 (1.08-1.29)*	2.27(2.06-2.51)*	1.39 (1.16-1.68)*	1.58(1.25-2.00)*	1.45 (1.01-2.08)*	1.20 (1.09-1.32)*
Education (ref: illiterate)
Up to primary	1.10 (1.04-1.17)*	1.32 (1.25-1.40)*	1.17 (1.04-1.31)**	1.25(1.09-1.42)**	0.76 (0.60-0.97)**	0.86 (0.80-0.92)*
Up to secondary	1.01(0.94-1.08)	1.19 (1.11-1.27)*	1.36(1.19-1.56)*	1.47(1.27-1.70)*	0.32 (0.23-0.44)*	0.55 (0.51-0.59)*
Above Secondary	0.94(0.86-1.02)	1.01 (0.93-1.10)	1.43(1.22-1.69)*	1.56(1.31-1.86)*	0.31 (0.22-0.44)*	0.27 (0.24-0.29)*
Household occupation (ref: self-employed)
Regular Wages	1.00(0.94-1.06)	1.05 (0.99-1.11)	1.02(0.90-1.15)	0.94(0.82-1.08)	0.40 (0.22-0.72)**	1.67 (1.55-1.70)*
Casual Labourer	1.01 (0.5-1.09)	1.16 (1.08-1.24)*	0.99 (0.86-1.14)	1.14 (0.97-1.33)*	2.45 (1.79-3.35)*	1.14 (0.82-0.95)
Economic quintile (ref: poorest)
Poor	1.1 (1.02-1.19)**	1.26 (1.17-1.37)*	0.62 (0.53-0.73)*	0.62 (0.52-0.74)*	0.62 (0.44-0.87)**	0.94(0.86-1.02)
Middle	1.31 (1.21-1.41)*	1.50 (1.39-1.61)*	0.55 (0.47-0.64)*	0.58(0.49-0.68)*	0.89 (0.66-1.21)	0.88(0.81-0.95)**
Rich	1.44 (1.33-1.55)*	1.58 (1.46-1.70)*	0.46 (0.40-0.54)*	0.50(0.43-0.59)*	1.37 (1.02-1.82)**	0.79 (0.73-0.86)*
Richest	1.68(1.56-1.81)*	2.23 (2.07-2.41)*	0.35 (0.30-0.41)*	0.40(0.34-0.47)*	1.87 (1.41-2.47)*	0.70 (0.64-0.76)*
Insurance coverage (ref: No)
Yes	1.26 (1.20-1.33)*	NA	0.51 (0.46-0.57)*	0.56(0.50-0.64)*	NA	NA
Provider (ref: public)
Private	NA	NA	8.17 (7.41-9.01)*	7.50(6.63-8.49)*	NA	NA
Economic independence (ref: independent)
Dependent	1.38 (1.30-1.46)*	1.26 (1.19-1.33)*	1.06 (0.95-1.18)	0.94(0.83-1.06)	0.25 (0.20-0.30)*	NA
Living arrangement (ref: with spouse/family)
Living alone	2.05 (1.76-2.39)*	1.53 (1.31-1.79)*	2.38 (1.84-3.07)	2.29(`1.76-2.98)*	NA	0.15 (0.12-0.18)*
Model Details
Number of observations	42755	42755	10801	10801	42755	42755
Pseudo R2	0.029	0.039	0.179	0.149	0.532	0.248
LR (chi2)	1444.70*	1999.79*	2676.89*	1804.33*	4399.85*	12793.77*

Note:

(*) p-value <0.001

(**) p-value<0.05

All estimates, except model details, are odds ratio (OR) and values in the parentheses are confidence interval of the estimates

Source: Authors’ computation from unit records of NSSO 75^th Round 2017-18

Table 4: Disease burden and health seeking behavior in elderly during hospitalization and out-patient care in India

	Hospitalization		Out-patient care
	Diseases burden during hospitalization	Share of hospitalization episodes treated under public sector	Diseases burden in out-patient care	Share of out-patient care treated under public sector
Infection	16.6	48.3	10.0	33.5
Cancers	4.6	52.8	0.5	55.8
Blood diseases	0.9	46.8	0.9	15.3
Endocrine, metabolic, nutritional (includes diabetes)	5.3	40.3	22.5	35.5
Psychiatric and Neurological	8.2	36.8	4.4	28.2
Genito-urinary	5.3	27.8	1.0	33.9
Eye	8.4	37.8	1.5	47.5
Ear	0.2	36.4	0.4	35.6
Cardio-vascular (includes hypertension)	18.1	37.7	32.0	33.4
Respiratory	7.8	45.3	7.3	37.5
Gastro-Intestinal	7.5	36.7	2.6	30.3
Skin	0.7	50.3	0.9	22.7
Musculo-skeletal	6.2	34.8	13.9	33.0
Injuries	7.9	34.9	0.7	31.1
Others	2.4	31.4	1.6	15.3
Total	100.0	39.8	100.0	33.6

Source: Authors’ computation from unit records of NSSO 75^th Round 2017-18

Table 5: Financial Protection during hospitalization and outpatient care for India’s Elderly

	Insurance coverage		OOPE in out-patient care		OOPE during hospitalization		CHE-10		CHE-25
	Total insurance coverage	Coverage under PFHI	Pub	Pvt	Pub	Pvt.	Pub	Pvt	Pub	Pvt.
Total	18.9	14.3	390	852	6209	38709	23.2	64.9	9.1	37.0
Age group (years)
60-69	19.3	14.5	410	822	5315	39051	22.2	67.5	7.6	38.8
70-79	17.8	13.9	336	841	8364	38523	25.4	63.0	13.0	36.6
80 and above	18.7	14.3	430	1039	4745	37828	23.0	58.9	6.4	30.7
Place of Residence
Rural	18.1	16.6	388	816	6180	32009	25.2	67.8	10.0	40.7
Urban	20.4	9.5	394	892	6268	47200	19.0	61.3	7.1	32.4
Gender
Male	19.0	14.1	441	857	7336	44666	25.7	67.6	10.8	41.2
Female	18.7	14.5	342	847	4780	31459	20.2	61.7	6.9	31.9
Marital Status
Never Married	17.3	14.6	318	1849	7857	88010	16.6	62.0	5.7	46.6
Currently married	18.3	13.5	484	861	6381	40639	21.7	67.1	9.5	38.6
Widowed	19.9	15.8	256	818	4370	26638	19.8	58.1	6.1	29.7
Surviving Children
At least one surviving child	18.7	14.1	393	849	5676	36426	20.3	63.5	8.1	35.3
No child	21.3	18.9	306	937	9320	56542	40.6	77.0	14.8	51.6
Social Groups
ST	22.5	20.7	246	613	4102	22546	25.2	69.2	3.5	43.3
SC	15.1	13.6	451	1063	7229	24972	27.8	61.2	12.8	31.8
OBC	20.0	16.9	324	782	5523	33098	23.6	66.8	8.9	38.8
General	18.8	10.3	492	860	6779	48538	19.9	64.1	8.5	36.5
Education
Illiterate	17.9	16.6	333	732	4409	25878	19.7	63.5	6.4	34.3
Up to primary	19.3	14.7	363	856	6065	31672	21.9	65.2	11.6	33.9
Up to secondary	19.4	11.8	530	786	6678	46869	23.7	63.7	8.7	39.6
Above Secondary	22.2	4.8	615	1222	13856	57350	21.2	63.3	7.5	36.6
Household occupation
Self employed	14.9	13.0	500	846	6961	37673	19.7	63.5	9.4	35.9
Regular Wages	24.3	10.4	308	1046	5998	36478	21.9	65.2	5.3	26.3
Casual Labourer	18.8	18.2	268	618	3509	22085	23.7	63.7	8.2	36.0
Others	25.2	17.1	387	830	5260	42098	21.2	63.3	8.4	43.3
Economic quintile-Rural
Poorest	13.5	12.8	381	761	5084	19410	43.3	75.2	17.5	47.4
Poor	10.6	10.1	477	908	4858	28978	24.3	67.7	4.4	45.1
Middle	19.0	18.2	360	725	6293	24807	19.3	71.4	8.7	37.8
Rich	20.9	19.6	421	659	5470	32435	22.6	72.9	10.7	44.6
Richest	25.6	21.7	353	918	7949	39683	22.7	60.6	9.9	36.5
Economic quintile-Urban
Poorest	13.4	10.4	371	995	5577	32077	27.6	77.1	11.8	44.4
Poor	18.1	13.2	322	862	4227	41811	21.6	63.2	6.4	34.7
Middle	18.3	9.1	352	845	5850	42262	13.6	63.8	3.7	34.2
Rich	19.2	9.0	441	868	7091	50633	11.6	62.3	4.9	28.2
Richest	35.6	5.5	564	916	13025	60067	11.2	48.6	6.2	26.0

Source: Authors’ computation from unit records of NSSO 75^th Round 2017-18

Table 6: Living arrangement and economic independence in elderly population of India

	Living arrangements				Economic independence			Physically immobile	Poor perception of current health	Perception of change in state of health being worse
	Living with spouse and other members	Living with spouse only	Living without-spouse but with children/relatives	Living alone	Independent	Partially dependent	Fully dependent	Physically immobile	Poor perception of current health	Perception of change in state of health being worse
Total	50.3	14.1	31.5	4.2	30.1	22.9	47.0	7.6	19.6	21.0
Age group (years)
60-69	54.9	16.0	25.1	4.1	35.0	23.9	41.2	4.5	13.6	16.2
70-79	44.2	11.5	39.9	4.5	23.1	22.5	54.4	9.3	26.8	26.3
80 and above	31.7	7.3	57.1	4.0	12.3	17.0	70.8	27.5	46.0	43.7
Place of Residence
Rural	51.1	13.4	31.1	4.4	28.5	24.5	47.0	7.6	21.4	22.8
Urban	48.6	15.5	32.2	3.7	33.3	19.7	47.0	7.5	16.1	17.3
Gender
Male	64.1	17.9	16.4	1.6	50.9	22.9	26.1	6.2	17.4	19.6
Female	37.0	10.4	46.0	6.6	10.0	23.0	67.1	8.9	21.7	22.4
Marital Status
Never Married/	4.6	3.6	69.6	22.2	37.3	17.1	45.6	8.4	21.7	19.4
Currently married	74.8	21.7	3.3	0.3	38.3	23.1	38.6	5.3	16.2	18.6
Widowed	5.4	0.2	83.4	11.0	14.5	22.7	62.8	11.9	26.0	25.6
Surviving Children
At least one child	52.1	12.8	31.5	3.6	29.1	23.5	47.5	7.6	19.7	21.3
No child	8.9	43.5	31.4	16.1	53.1	11.3	35.6	7.4	17.3	15.0
Social Groups
ST	48.7	12.6	34.5	4.2	25.7	25.3	49.1	6.4	17.6	15.7
SC	51.1	14.4	30.2	4.2	29.0	25.2	45.8	7.6	21.3	22.6
OBC	48.3	13.1	34.3	4.3	28.5	23.8	47.7	8.0	18.8	20.8
General	52.6	15.4	28.0	4.0	33.4	20.3	46.3	7.2	20.2	21.3
Education
Illiterate	44.9	11.3	38.8	5.0	21.0	23.5	55.5	8.7	21.8	23.5
Up to primary	54.0	13.2	29.4	3.4	29.5	26.0	44.5	7.6	20.2	20.3
Up to secondary	60.1	17.8	19.8	2.4	42.0	22.2	35.8	5.4	16.9	18.5
Above Secondary	57.0	25.4	13.8	3.8	61.8	15.0	23.2	4.5	10.9	12.8
Household occupation
Self employed	58.0	9.2	32.1	0.8	30.3	22.6	47.1	7.3	18.9	21.1
Regular Wages	56.3	3.5	39.7	0.5	21.8	26.0	52.2	9.3	17.5	18.4
Casual Labourer	48.3	10.2	38.5	3.1	26.7	25.9	47.4	7.9	22.0	22.8
Economic quintile-Rural
Poorest	55.3	10.5	29.7	4.5	26.2	28.1	45.7	8.4	21.8	22.5
Poor	54.2	6.0	36.7	3.1	25.4	25.3	49.3	7.6	22.3	20.9
Middle	53.7	12.3	31.5	2.5	27.0	25.7	47.4	6.4	19.5	24.5
Rich	49.2	14.5	31.4	4.8	29.1	23.5	47.4	7.2	21.3	21.8
Richest	43.6	22.7	26.7	7.0	34.2	20.5	45.3	8.3	22.1	24.1
Economic quintile-Urban
Poorest	54.2	6.6	35.9	3.2	26.3	25.4	48.4	8.5	16.5	20.4
Poor	56.0	7.5	34.3	2.3	30.6	19.5	49.9	7.3	16.9	17.9
Middle	50.4	12.6	34.7	2.3	30.6	18.5	50.8	5.9	17.4	17.3
Rich	45.8	22.2	27.8	4.3	35.9	18.6	45.5	6.8	14.1	15.1
Richest	35.6	29.8	28.2	6.5	45.1	15.7	39.3	9.5	15.5	15.6

Source: Authors’ computation from unit records of NSSO 75^th Round 2017-18

Table 7: Variation in various indicators of elderly health from 71^st Round NSS, 2014, to 75^th Round NSS, 2017-18

		71^st Round NSS, 2014	75^th Round NSS, 2017-18
Access
Inpatient care	Hospitalization rate	10.9	8.5
	Share of public sector during hospitalization	35.9	39.0
	Share of private sector during hospitalization	64.1	61.0
Out-patient care	PAP	30.3	27.7
	Share of public sector in out-patient care	28.3	33.6
	Share of private sector in out-patient care	71.7	66.4
Financial Protection
Inpatient care	Any insurance coverage	19.0	18.9
	PFHI coverage	16.2	14.3
	OOPE during hospitalization in public sector (in Rs.)	7177	6209
	OOPE during hospitalization in private sector (in Rs.)	31875	38709
	CHE-10 in public sector during hospitalization	27.3	23.2
	CHE-10 in private sector during hospitalization	65.9	64.9
	CHE-25in public sector during hospitalization	12.5	9.1
	CHE-25in private sector during hospitalization	38.2	37.0
Out-patient care	OOPE in out-patient care under public sector (in Rs.)	547	390
Out-patient care	OOPE in out-patient care under private sector (in Rs.)	802	852
Living Arrangements
Living with spouse and other members		47.0	50.3
Living with spouse only		14.8	14.1
Living without spouse but with children/relatives		34.1	31.5
Living alone but not in old age home		4.1	4.2
Economic Independence
Independent		28.3	30.1
Partially independent		20.0	22.9
Totally dependent		51.7	47.0
Physical mobility
Physically immobile-Confine to bed		1.6	1.4
Confined to home		6.0	5.5
Able to move outside but with wheelchair only		0.4	0.6
Physically mobile		92.0	92.5
Perception towards health
Own perception of current state of health
Excellent/ very good		6.8	8.8
Good/fair		70.6	71.6
Poor		22.4	19.6
Own perception about change in the state of health compared to previous year
Much better		4.6	5.8
Somewhat better		12.9	12.6
Nearly the same		57.5	60.6
Somewhat worse		20.5	18.3
Worse		4.5	2.6

Source: Authors’ computation from unit records of NSSO 71st, 2014, and 75^th Round 2017-18

Equity and Elderly Health in India: Reflections from 75th Round National Sample Survey, 2017-18, amidst the COVID-19 Pandemic

Status:

Journal Publication

Version 2

Abstract

Background

Methods

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Tables

Status:

Journal Publication

Version 2