Poverty and Disability among Indian Elderly:
Evidence from Household Survey

Manoj K. Pandey
Institute of Economic Growth, Delhi

Abstract
This paper attempts to analyze the depth of poverty and examines the causal relationship between disability and poverty among Indian elderly. We use 58th round of National Sample Survey Organisation (NSSO) data surveyed in 2002. Our analysis finds higher level of poverty and income inequality among disabled elderly as compared to non-disabled elderly and those differences in the income levels vary significantly across different age groups, gender, social groups and educational status. Finally, the estimation results confirm the hypothesis of causal relationship between poverty and disability.

1. Introduction
2. Poverty and Disability: A Causal Relationship
3. Data and sample description
4. Unadjusted Poverty Estimates and Gini Index
5. Does differences of average income/expenditure significant across demographic composition of elderly?
6. Empirical analysis
7. Concluding observations
References:

1. Introduction

With prolonged human life, reduced mortality and fertility rates, ageing has become a global phenomenon in the 21st century. World Health Organisation (WHO) views ageing as a privilege and a societal achievement. This process started in developed countries and slowly shifting to developing countries like India with systematically increased in number of greying population and hence, their proportion in the total population. According to United Nations (2005) estimates, the population of the world has stood around 6.5 billion in the dawn of 21st century and is expected to rise to 9.3 billion by 2050. Also, proportion of the elderly3 to the total population is expected to increase from 10 percent in 2000 to 15 percent by 2025 and over 21 percent by 2050. The population growth trend of elderly in India is somewhat similar to the world’s trend. Following Population Census of India, the population of elderly was only 24 million in 1961; increased to 43 million in 1981; to 57 million in 1991 and about 77 million in 2001. Further, their share in the total population has also risen from 5.63 percent in 1961 to 6.58 percent in 1991 (Irudya Rajan et al., 1996 and 1999) and to 7.5 percent in 2001 (Irudya Rajan, 2006 and 2008).

The linkage between ageing and disability is a biological fact where the risk of disability increases with increase in age. However, with proper policy intervention, onset of disability can be delayed. Ageing should not be treated as synonymous of disability as a large proportion of older people live with good health status and without significant mental or physical decline. This link is very important particularly for the countries like India where age-structure of the total population is still predominantly young or middle aged but the age structure of disabled persons is predominantly elderly. In India, more than one-fourth of the Indian aged population is disabled and age-specific disability rates and the severity of disablement increase with age within old age bracket. In the age-groups young-old (60-64), middle-old (65-69), older-old (70-74) and oldest old (75 and above), the percentages of disabled persons are 36, 42, 51 and 61, respectively (NSSO, 2003). The absence of a safety net for the aged has exacerbated the problem.

Traditionally, the joint family took care of the aged but rapid urbanisation and the exodus of persons from rural to urban areas have created a vicious situation. In the absence of the ability to earn, and without community support, in the form of kinsmen or the extended family, the aged are rendered destitute.

On poverty front, it is already established in developed countries like UK that the proportion of elderly people living at or below the poverty line is very much higher than that of younger people (Townsend, 1981). It is also evident from Indian data that 40 percent of the elderly live below the poverty line and 90 percent are neither covered by any state pension nor have any family to take care of them.4 However, still little is known about poverty among the elderly. Government of India has some anti-poverty programs particularly for disabled people. Persons with Disabilities Act, 1995 (PWD hereafter) is one of the most important step forward in policy towards disabled people in India. However, World Bank (2007) finds some weaknesses in its design and coverage. Two important limitations are important in our context. One, the act covers only designated types of disability, which are not inclusive of several significant categories of disability (e.g. autism). Second, safety nets for PWD offer low coverage and limited financial protection, for example, the PWD act commits to reservations for PWD of not less than 3 percent in all poverty alleviation schemes, but it appears that PWD are well below 3 percent of beneficiaries in all schemes. Also, the new National Rural Employment Guarantee Act (NREGA) has dropped the provision for reservations for disabled people. However, social assistance cash payments for destitute elderly, widows and PWD is provided by the government through social pension and is one of the most helpful anti-poverty programs operating in recent times. One problem with such programs is the identification of functionally disabled people.

According to the World Bank report …significant categories of people who are functionally disabled will not typically be identified by households as being disabled. The primary example of this is elderly people with significant functional impairments who were not disabled before they became old. In field work, the standard answer on probing was that even seriously functionally impaired elderly people were “just old” or “like many other old people” rather than disabled.

Though literature is available on the relationship between disability and poverty, very few are focused on elderly in India (Sengupta and Agree, 2003; Prakash, 2003). Audinarayana and Sheela (2002) reveal that elderly people who belong to the higher socio-economic class were found to have lesser disabilities. Sengupta and Agree (2003) analyze covariates of mobility difficulty among the older adults in India and find that there is a substantial association between mobility and chronic diseases in the elderly. Kerketta et al. (2009) find that there is a high prevalence of physical disabilities with both non-communicable as well as communicable diseases among the elderly primitive tribal members and recommend for the implementation of a special health care strategy to reduce suffering at this crucial age and improve quality of life. In
India most of the studies are either just informative or descriptive without much statistical work and therefore, of limited scope. The relationship between disability and poverty in developing countries has not been well-established in the quantitative literature (Braithwaite and Mont,
2008). Also, studies like Sengupta and Agree (2003) and Prakash (2003) are based on old data
Sources and given the fact that in last two decades a lot of changes had taken place on the fronts of age structure, industrialization, urbanization, family disintegration and weakening of social safety nets for elderly in India and therefore, at least for the policy point of view, these studies may not be of much use.

In this paper, we try to re-look the relationship between disability and poverty among Indian elderly. Further, paper aims to compare the poverty scenario between individuals with disability and without disability using different measures of poverty and inequality. The estimation results confirm the causal relationship between poverty and disability. However, these findings must be read with caution as later phase of life is naturally associated with high rate of disability and incidences of poverty due to retirement and out of pocket expenditures on health and other necessities.

The outline of the paper is as follows: section II briefly describes what literature speaks on the causal relationship between poverty and disability followed by description of data and variables in section III. Unadjusted poverty estimates and gini index have been computed in section IV and mean per capita expenditures are compared across various groups in section V. Discussion on econometric models and results are done in section VI. Finally, concluding observations are presented in section VII.

2. Poverty and Disability: A Causal Relationship

The association between poverty and disability has been well documented (U.S. Census Bureau, 2004; Wittenburg & Favreault, 2003, Elwan, 1999) in the literature. The relationship is, in general, found to be causal (Braithwaite and Mont, 2008, Lustig et al., 2007; DFID, 2000; Moore and Yeo, 2003; Yeo, 2001). It is argued that though not all disability is caused by poverty, poor people who suffer from malnutrition and in lack of adequate access to health services including maternal care and trauma services, are more likely to suffer from disability which further ensure their exclusion and marginalization of by reducing their opportunities to contribute productively to the household and to the community, which in turn increases the risk of poverty. DFID (2002) and Moore and Yeo (2003) provide specific mechanism how the vicious circle between poverty and disability exists and work. DFID (2000) describes a vicious circle and the causal link between disability and poverty suggest that in one hand the poverty increases the likelihood of injury and impairment and hence the risk of disability; on the other hand the exclusion of disability leads to greater rates of poverty. Other studies also suggest that poverty increases the risk of disability through social role devaluation (Wolfensberger, 2000), environmental risk factors (Evans, 2004; Link & Phelan, 1995), negative group influences (Durlauf, 2001), and weakened sense of coherence (Antonovsky, 1987, 1991). Recently Lustig et al. (2007) emphasize that poverty limits access to resources that finally leads to a chronic health problem or disability. Research shows that this vicious circle varies as well within and between cultures and contexts, but is generally acknowledged to be strong. Thus, the link between poverty and disability may be attributed to the discrimination, social exclusion and denial of rights together with lack of access to basic services.

3. Data and sample description

The paper is based on micro-level 58th round of National Sample Survey Organization (NSSO) data collected during July 2002 to December 2002. The survey period was divided into two sub-rounds of three months duration each. Equal number of sample first stage units was allocated to each of these sub-rounds with a view to ensuring uniform spread of the interviews over the entire survey period. A stratified multi-stage sample design was adopted for the 58th round. The number of sample villages and urban blocks surveyed in central sample was 4637 and 3354, respectively. A total of 45571 and 24731 households were surveyed in rural and urban areas, respectively. The survey collects information relating to the magnitude and type of disability, age at onset of disability, possible cause of disability housing condition, village facilities, particulars of slum and consumer expenditure, employment and unemployment. The analysis is done on the truncated sample for individuals with age more than 60 years. Our analysis is based on a size is
41,499 elderly out of which 26,871 were from rural areas and remaining 14,628 were from urban areas of the country. The estimated population of elderly is about 76.15 thousands, 21.29 thousands and 97.44 thousands, respectively in rural, urban and all India.

Percentage distribution of disabled elderly according to their age group, sex, social status and education are shown in Table 1. It can be observed that about 46% of the elderly suffer from at least one kind of disability. However, the share of disabled elderly is little higher in urban India and this may be attributed to the fact that the likelihood of disability detection is higher in urban areas due to better health care facilities. Also, it is evident that with increase in age, the share of disabled elderly increases in both rural and urban areas. While only 36% of elderly are suffering from disability in the age-group 60-64, it becomes 42% in age bracket 65-69; 51% in 70-74 and about 61% in the age group 75+ years. The same trend exists in both rural and urban areas. Further, in the same line with individuals of all ages, the share of male elderly is higher than that
of female elderly in the old age population.

However, while more elderly reports for disability in urban India as compared to rural India (49% and 46%, respectively); the reverse is true in case of female elderly (44% and 45%, respectively for urban and rural areas).

Now, turning to social group wise distribution of disabled elderly in India, we find that the percentages of Scheduled Tribes elderly are the most disabled among all social classes in India. Scheduled caste elderly comes next followed by other backward castes and other castes. While nearly 52% of ST elderly have at least one disability, the percentage goes down to 49% in case of SC elderly. The proportion of OBC and other castes are 46% and 43%, respectively. Here also, Table 1 suggests that more disability live in urban areas as compared to rural part of the country. Furthermore, as expected most of disabled elderly are illiterate too. Table 1 indicates that among illiterate elderly, 48% suffer from disability. This figure reduced with 47% among elderly with primary education and about 43% who are educated with middle and higher level.

4. Unadjusted Poverty Estimates and Gini Index
After brief discussion about sample characteristics, in this section we will try to estimate unadjusted poverty for elderly with and without disability using standard poverty measures. For this purpose, we classify sample households with elderly by disability status-households with disabled elderly and households without any disabled family members. Further, we use average per capita monthly expenditure (PMCE) as an indicator of standard of living (see Deaton and Paxson, 1995; Pal and Palacios, 2008). Three measures of poverty are used: Head Count Ratio
(HCR), Poverty Gap (PG) and Squared Poverty Gap (SPG). The headcount is calculated by comparing the income y (i 1,2,.....n) i = , where n is the total number of households in the sample, of each household to the state-level poverty lines poverty line Zs . Let us suppose that q households have incomes below Zs, the HCR = q n .This does not take account of the depth of poverty and also does not satisfy the principle of transfers. The poverty gap measure sums of all the proportionate shortfalls below

This measure takes account of poverty depth but does not satisfy the principle of transfers. To incorporate the principle of transfers, SPG is used which measures the income gap by the gaps themselves awarding a higher weight to poorer households and given as

These poverty indices for elderly with and without disability are shown in Table 2.

Also, this is further classified according to gender, rural/urban, social group, education and age group. HCR for elderly with disability is little lower with higher standard error than those without disability. Poverty gap index is almost similar for both the elderly groups. However, SPG index suggests that in general households with disables elderly are having little higher value suggesting for higher level of poverty among households with disabled elderly. For simplicity, we would focus only on SPG index for interpretation purpose.

Table 2 also indicates that in each age group within elderly, as compared to persons without disability the value of SPG index is little higher for persons with disability. This infers that in each phase of old age disabled individuals are in a bad economic condition. It also shows that 21% disabled elderly male are living below poverty line as compared with 20% elderly male without disability. The percentage female elderly with and without disability are same (22% each). Again while 22% disabled elderly live in poverty as compared to 21% with no disability. Furthermore, the proportion of female disabled elderly is little higher than their male counterpart. This clearly indicates that disabled elderly, in particular female are little disadvantaged in terms of their living standard.

Now, the value of SPG index suggests that the while in rural India, the economic condition of elderly with and without disability are almost similar, in urban India elderly without disability are little well-off in comparison to elderly with disability. As far as social group is considered, SPG index value declines from SC to others and here also, higher level of poverty can be found for disabled elderly.

To increase our understanding about the income inequality, we calculate gini-index for elderly with and without disability. Gini-index for elderly according to their age- group, gender, location of residence (rural/urban) and social group are shown in Table 3. It suggests that across each age-group, gender, sector and social groups’ inequality among elderly without any disability is lower than that of persons with disability. This means that the distribution of income among disabled elderly is more unequal than that of non-disabled elderly. Interestingly, gini value for disabled male elderly is slightly higher than that of their female counter part. Also, Income inequality is more pronounced among disabled elderly living in urban areas (0.337) as compared to those who reside in rural part of the country (0.261). As for as income inequality within social group is concerned, scheduled castes (SCs) disabled elderly have least inequality, followed by disabled elderly from OBC, ST and other castes.

5. Does differences of average income/expenditure significant across demographic composition of elderly?

In order to answer this question, we use t-test of comparison of means followed by F-test for equality of variance for demographic indicators with dichotomous categories. For multiple category demographic variables, we apply Analysis of Variance (ANOVA hereafter). Table 4 documents results of t-test followed by F-test. It can be seen from the table that while there is no statistical difference in the mean PMCE between male and female elderly without any disability; elderly male with disability have significantly higher PMCE as compared with female disabled elderly. However, variation in the PMCE distribution is not significantly different between male and female elderly. Further, as expected average PMCE for urban elderly with and without disability are significantly higher in comparison to rural elderly. Also, variances of rural and urban PMCE are not statistically equal for all elderly, elderly with and without disability.

Mean and standard deviations of PMCE for elderly with and without disability according to their age group, social group and educational status are presented in Table 5 followed by analysis of variance and comparison of multiple means results in Table 6, 8 and 9, respectively.

ANOVA results for comparison of mean MPCE across age groups, social groups and educational level suggests for significance mean difference for all elderly persons with and without disability. Further, based on Chi-square statistics, Bartlett’s test rejects the null hypothesis of equal variances between groups. However, the results of difference of means between pair wise combination of age, social and educational groups is mixed.

Table 6 suggests for among elderly people with disability while there is no significant difference of mean PMCE between age groups 60-64 and 65-69; 60-64 and 70-74; 65-69 and 70-74 years, there are evidences of significant differences of mean PMCE between age groups 60-64 and 75+; 65-69 and 75+ and 70-74 and 75+ years. This suggests that though the per capita monthly expenditure for younger old, middle old and older old are not statistically differ, it is significantly different for the oldest old elderly with disability in comparison to elderly below 75 years of age.

Multiple comparison of MPCE according to ST, SC, OBC and others are shown in Table 7 which suggests for significant difference in mean MPCE across each paired combination of social groups for elderly with and without disability. Similar results are documented in Table 8 for educational status.

 

6. Empirical analysis

After exploring the economic condition and inequality among elderly with and without disability, in this section we would do some econometric exercise to explain the possible relationship between poverty and disability. Following the hypothesis that there is causal association between poverty and disability, our model is based on two-stage approach of estimation (Stern, 1989). In first stage, we estimate per capita monthly expenditure and disability using following equations (1) and (2),

The definition and descriptive statistics of the variables used in the analysis are presented in Table 9 and final stage results are presented in Table 10. Robust regression result of Table 10 suggests that increased disability among elderly is significantly and negatively associated with the per capita monthly expenditure. This means that with increase in the likelihood of being a disabled elderly, the likelihood of being poor increases significantly. Further, probit model estimates of disability also indicates that the effect of PMCE is negative on disability is negative and significant. Marginal effect of estimated log of per capita expenditure in second stage disability equation suggests that with each unit increase in it would reduce the probability of disability by 0.11. This means as the standard of living will go up; the likelihood of being disabled will get reduced. In other words, by reducing poverty among elderly Indians, the probability of being suffered from disability can be significantly reduced.

7. Concluding observations

The relation between poverty and disability is commonly accepted as a vicious circle and it is widely hypothesised that it is a two way relationship i.e. disability increases the risk of poverty and conditions of poverty increase the risk of disability. The objective of this analysis was mainly to understand the relationship between poverty and disability in the elderly population of India.

Based on different indices of poverty and inequality, our analysis suggests that as compared to non-disabled elderly, the poverty and income inequality level is higher for disabled elderly. Further, t-test and ANOVA results show that there are significant differences in the income levels of different age groups within elderly population, their gender, residence location, social groups and educational status. It was found that in general, being male, age beyond 60 years and its square, higher level of education, being unmarried, widowed, separated or divorced in comparison to being currently married are positively and significantly associated with disability of elderly whereas living in rural areas; being ST or SC as compared with OBC and others and household size are negatively associated with the likelihood of being disabled. Though the paper is not able to answer why it is the case, we suspect that apart from other reasons, reporting biasness and being not aware about the disability due to lack of health care facilities in rural areas and for the economically backward social classes could be possible explanations for this. Further investigation focused on the relationship between disability and poverty using two stage estimation methods confirms the causal relationship between poverty and disability in case of Indian elderly. Results suggest that disability is positively associated with the poor standard of living. At the same, poverty is positively associated with likelihood of being disabled.

In conclusion, if our analysis has any validity, it has far many policy implications. There is immediate need to strengthen social security safety nets to uplift poor elderly’s economic conditions in one hand and on the other hand, it is also essential to provide sufficient health care facilities to reduce the risk of disability among elderly.

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