Background

With the faster rate of growth of the elderly population in developing countries compared to the global rate, in India too the proportion of elderly people is increasing at an increasing rate and is projected to reach 19 per cent in 2050 from 8 per cent in 2015. Unlike developed countries, the ageing process in developing countries is not accompanied by increases in personal income and the governments of the developing countries are slow in responding to the demographic shift (Kowal et al., Reference Kowal, Kahn, Ng, Naidoo, Abdullah, Bawah, Binka, Chuc, Debpuur, Ezeh, Gomez-Olive, Hakimi, Hirve, Hodgson, Juvekar, Kyobutungi, Menken, Minh, Mwanyangala, Razzaque, Sankoh, Streatfield, Wall, Wilopo, Byass, Chaterji and Tollman2010; Giridhar et al., Reference Giridhar, James and Kumar2017). Studies suggest that these developing countries will have even less time to adapt their institutional structures to the health and income problems of elderly people compared to developed countries like the United States of America (Smith, Reference Smith1994). This demographic shift has been a result of an advance in mortality transition, a movement from the dominance of child and adult mortality to old-age mortality, and this trend is visible in both rural and urban areas (Yadav and Arokiasamy, Reference Yadav and Arokiasamy2013). This demographic transition which the rich industrialised countries of Western Europe, North America and Japan experienced earlier, is now occurring in developing countries, being associated with a huge burden of non-communicable diseases (Beaglehole and Yach, Reference Beaglehole and Yach2003; Boutayeb, Reference Boutayeb2006; Ghosh and Arokiasamy, Reference Ghosh and Arokiasamy2009; Shradhha et al., Reference Shradhha, Prasantha and Prakash2012; Barik and Arokiasamy, Reference Barik and Arokiasamy2016). Along with the physical health morbidities, population ageing in India has led to a rise in mental health morbidities too (Chandrashekhar et al., Reference Chandrashekhar, Gududur and Reddy2014; George et al., Reference George, Deshpande, Kumar and Patil2017). In the case of India, by 2030 almost half of the disease burden will be borne by elderly people with high levels of non-communicable diseases, smoking habits and physical inactivity (Chatterji et al., Reference Chatterji, Kowal, Mathers, Naidoo, Verdes, Smith and Suzman2008; Munsur et al., Reference Munsur, Tareque and Rahman2010). The regional case studies in India and other countries also reflect that the prevalence of unhealthy lifestyles is associated with morbidity among elderly people (Simsek et al., Reference Simsek, Doganay, Budak and Ucku2014; Machón et al., Reference Machón, Vergara, Dorronsoro, Vrotsou and Larrañaga2016; Gagauz et al., Reference Gagauz, Avram and Pahomii2017; Kaur et al., Reference Kaur, Bansal, Anand, Kumar and Singh2017). Also there occurred a steady deterioration in self-perceived health status among Indian elderly people over the recent decades, even after controlling for socio-economic characteristics (Husain and Ghosh, Reference Husain and Ghosh2010). All these studies pointed towards policies to address the problems of geriatric health care.

Although in Asia and Africa, co-residence with adult children is most common, living arrangements are changing with rising education levels as families are becoming more nuclear due to migration to cities, preference for privacy, etc. (Bongaarts and Zimmer, Reference Bongaarts and Zimmer2002). Also urbanisation, modernisation and globalisation, leading to changing economic structure and the younger generation searching for new identities encompassing economic independence, led to reduced dependence on land which had been a factor in keeping the intergenerational bonding strong, weakening the joint family structure (Bhat and Dhruvarajan, Reference Bhat and Dhruvarajan2001). Also, the intergenerational spacing leading to the spread between grandparents and grandchildren is associated with lesser family bonding (Bloom and Eggleston, Reference Bloom and Eggleston2014). With erosion of the joint family system and moving towards the nuclear family system, the changes are leading to worsening of the physical and mental health of Indian elderly people and old-age homes are emerging in India (Lamb, Reference Lamb2007). Among elderly people, childlessness and widowhood have been important factors in deciding to opt for old-age homes (Munsur et al., Reference Munsur, Tareque and Rahman2010; Kalavar and Jamuna, Reference Kalavar and Jamuna2011). Although co-residence does not always ensure healthy relationships between successive generations as the elderly people often face abuse there (Munsur et al., Reference Munsur, Tareque and Rahman2010), nor does it always indicate flow of support from younger to elderly people as it also sometimes indicates child care or help in household chores by elderly people (Chan, Reference Chan1997; Irudaya, Reference Rajan Irudaya1999), empirical evidence is there that multigenerational households, the traditional form of living arrangement in India, have some potential protective health benefits for older adults (Ghosh and Husain, Reference Ghosh and Husain2010; Agarwal, Reference Agarwal2012; Samanta et al., Reference Samanta, Chen and Reeve2015).

In the face of decaying family support systems, economic security emerges as one of the most important determinants of health status as economic dependence has made elderly people more vulnerable (Alam and Karan, Reference Alam and Karan2011; Alam et al., Reference Alam, James, Giridhar, Sathyanarayana, Kumar, Raju, Syamala, Subaiya and Bansod2012; Gagauz et al., Reference Gagauz, Avram and Pahomii2017. Physical vulnerability in combination with economic vulnerability creates emotional vulnerability, which aggravates the self-perceived health status (Gupta and Sankar, Reference Gupta and Sankar2003). Irrespective of gender and place of residence, economically independent elderly people in comparison to their dependent counterparts reported better health status (Gupta and Sankar, Reference Gupta and Sankar2003; Rajan and Kumar, Reference Rajan and Kumar2003; Roy and Chaudhuri, Reference Roy and Chaudhuri2008; Alam, Reference Alam2009; Mini, Reference Mini2009; Ghosh and Husain, Reference Ghosh and Husain2010). Economic independence, by providing a sense of security, enhances the psycho-mental health conditions which gets reflected in a better self-perceived health status. Also, economically independent elderly people might have more decision-making power on spending as well (Alam et al., Reference Alam, Mazumdar and Yadav2015). Along with economic dependence, the economic position of the households which the elderly people belong to always acted as a significant influencer on the health status of elderly people. The rich enjoy a better health status compared to the poor (Huisman et al., Reference Huisman, Kunst and Mackenbach2003; Roy and Chaudhuri, Reference Roy and Chaudhuri2008; Kowal et al., Reference Kowal, Kahn, Ng, Naidoo, Abdullah, Bawah, Binka, Chuc, Debpuur, Ezeh, Gomez-Olive, Hakimi, Hirve, Hodgson, Juvekar, Kyobutungi, Menken, Minh, Mwanyangala, Razzaque, Sankoh, Streatfield, Wall, Wilopo, Byass, Chaterji and Tollman2010; Alam et al., Reference Alam, Mazumdar and Yadav2015; Gagauz et al., Reference Gagauz, Avram and Pahomii2017). Elderly people in upper expenditure quintiles are more likely to report better health compared to those in lower expenditure quintiles (Dhak, Reference Dhak2009) as elderly people in upper expenditure quintiles are better taken care of, provided with a healthier diet, less likely to face abuse and enjoy better health status compared to their counterparts in lower expenditure quintiles (Munsur et al., Reference Munsur, Tareque and Rahman2010). Across the world, economic condition appears to be a crucial factor as it influences many other determinants of health status (Husain and Ghosh, Reference Husain and Ghosh2010). At the country level too, although the effects of age have been much larger than national income on self-perceived health status, and self-perceived health status has deteriorated with age, the rate of deterioration has been much lower in the case of high-income countries compared to low-income countries. High national income moderates the influence of age on health status and thus the decline in health satisfaction with age is much stronger in poor countries than rich countries (Deaton, Reference Deaton2008). Among elderly people, the work participation rate is much higher among the poor and uneducated compared to rich and educated groups, which indicates that their workforce participation is out of economic compulsion (Alam et al., Reference Alam, James, Giridhar, Sathyanarayana, Kumar, Raju, Syamala, Subaiya and Bansod2012). Regarding the work status, the perception of bad health increased from paid workers to unpaid and not working elderly people (Dhak, Reference Dhak2009; Ghosh and Husain, Reference Ghosh and Husain2010; Tareque and Rahman, Reference Tareque and Rahman2010; Maniscalco et al., Reference Maniscalco, Miceli, Bono and Matranga2020). The influence of regular cash flow increases the likelihood of reporting better health in the case of employed elderly people compared to their unemployed counterparts by protecting from financial deprivation (Alam et al., Reference Alam, Mazumdar and Yadav2015; Smolic, Reference Smolic2017).

With this background, the purpose of this research is to investigate how the variables like state of economic independence and employment status influence the self-perceived health status of elderly people in India, and how these impacts vary across the level of expenditure quintiles of the households as with different levels of economic resources of the households, the importance of these variables on self-perceived health status may differ.

Database and methodology

In this study, we used the database of the Social Consumption: Health Survey of the 75th round of the National Sample Survey. The National Sample Survey Organization conducts nationally representative large-scale population-based surveys. The Health Survey was conducted from July 2017 to June 2018 with the purpose of collecting information on health at the household level. Apart from the basic demographic and socio-economic particulars, the dataset provides detailed information on people above 60 years of age. The information set includes self-reported health status, state of economic dependence, living arrangement, state of physical mobility, whether suffering from chronic morbidity or not, etc., which have been used in this study.

As the response variable in this model is the self-perceived health status which takes binary values, 0 in the case of poor health status and 1 in the case of good/excellent health status, the logistic regression model has been applied here. The main predictor variables in this model have been the state of economic dependence and the employment status. Regarding the state of economic dependence, the survey collects information on whether an elderly person is fully dependent, partially dependent on others or independent. Two categories have been formed for the state of economic dependence: the reference category including those partially or fully dependent on others and the second category representing those who are economically independent. The usual principal activity status codes are provided in the survey. A binary variable is formed for the employment status which takes the value of 1 when the elderly person is involved in any economic activity as self-employed/unpaid family worker/regular salaried/casual wage labour and 0 otherwise, being the reference category. As the objective of the study is to look into the impact of the state of economic independence and the employment status on self-perceived health status across different expenditure quintiles of households, logit regression has been run separately for each expenditure quintile group along with measuring the impact in aggregate for all the expenditure quintiles together.

The control variables in this model are the different demographic and socio-economic factors like place of residence in terms of rural and urban areas, gender, social category, marital status, general education, living arrangements, health-related factors like health insurance coverage, physical mobility and chronic illness. The reference categories in the case of place of residence, gender, social category, marital status are rural areas, male, other castes and currently married, respectively. Six age groups are formed for the following age brackets: 60–64, 65–69, 70–74, 75–79, 80–84, 85 and above, with 60–64 years being the reference group. Four levels of general education are created: level 1 consisting of those without literacy; level 2 for those who are literate with or without formal schooling; level 3 for those below primary to middle school; level 4 includes those with education up to secondary and higher-secondary; and level 5 representing graduates, postgraduates and above, with level 1 being the reference category. In the case of health insurance coverage, the reference category is elderly people without any insurance coverage. Living arrangement has been categorised into staying with spouse/children/spouse and children, and living alone/in old-age homes/living with relatives/non-relations, with the latter being the reference category. In case of physical mobility and chronic illness, those who are physically immobile and suffering from chronic disease are the reference categories, respectively.