An Analysis of the State of Empowerment of Females vis-à-vis Males at Old Ages in India

Sanjeev Bakshi and Dr. Prasanta Pathak

Abstract

The problem of ageing population in the developing countries has a special gender dimension as females not only outnumber males among older adults, but also differ from their male counterparts with respect to economic status, marital status and health status. The state of well being of older adults is understood partially by their level of empowerment. Importance of social and economic aspects in daily life makes it worth to investigate the empowerment of older female vis-à-vis older males in social and economic spheres. Active participation in either or both of social and economic matters indicates that an older adult has a decision making role in either or both of the two matters. Thus, active participation of older adults in socio-economic matters is an indicator of their empowerment. The present study addresses these issues using the 42nd Round data of the National Sample Survey (NSS). This study defines certain empowerment indicators and investigates their variation and interrelationships across the provinces. A three tier conceptual framework consisting of individual, household and social characteristics has been proposed to find out the factors that are associated with empowerment. The gender dimension of the state of empowerment has also been investigated. The findings establish that suffering from certain diseases is negatively associated with the state of empowerment. Currently married older females are found more empowered than other older females. Economic dependence is negatively associated with empowerment. The findings emphasize the need of providing greater support to older females in India for maintaining good health and economic condition.

Keywords: autonomy, empowerment.

  1. Introduction

Positive developments in economic and health scenario have resulted in an increase in size of population in the developing countries and also added years to life of units of these populations. Enhanced longevity and reduced fertility is further resulting in the ageing of these populations. Faced with twin problems of bulging of size of populations and ageing of populations, ensuring the “quality of life” is a major challenge to policy makers in these countries where resources are already constrained.

“Quality of life,” is a term not intended to be defined precisely in the present discussion. We shall take the common definition of the term meaning good life. Gender differences in the quality of life are well known. But lesser is known about the gender scenario at older ages. The data from 42nd round of the national sample survey reveals some facets of this scenario. It shows that the prevalence of widowhood in older females is 27.01 times more likely as compared to older males (Table-A.1). Illiteracy and economic dependency were respectively 4.40 and 17.30 times more likely to prevail in older females as compared to older males. Older females were 11.85 times more likely not to be economically active than their male counterparts. They were also 0.16 times less likely to participate in management of assets that they possessed when compared to older males. The same is the case with management of owned property, the figure here was 0.17. In social sphere also their role seems to be contracted. As compared to older males their likelihood of non-participation in social matters, religious matters and daily household chores is respectively 2.02, 1.81 and 1.66 times higher. As far as health aspects are concerned they seemed to be in a better condition in case of chronic diseases like chronic cough, piles, urinary problems, heart disease and diabetes but were in worse condition with respect to diseases like pain in joints and limbs and hypertension. The prevalence of severe immobility was 1.54 times more likely in older females as compared to older males. All these findings show the prevalence of gender differences at older ages and the present study is an attempt to get information on the empowerment scenario of older women in India vis-à-vis older men.

Kar et al (1999) have identified four domains or aspects of life that affect overall quality life (QOL) of the powerless. These are basic human rights, equal rights for women, economic enhancement and health promotion and disease prevention. These things are true for older adult in particular older women also. It is further added that “empowerment is a means and QOL is an end.”

Before initiating analysis of the available data, let us try to define the concept called empowerment of women and distinguish it from closely related concepts of female autonomy and status of women.

1.1.According to Kar et al (1999) “empowerment is defined as a process through which individuals, communities and organizations gain control over issues and problems that concern them most[1].”

1.2.Dixon (1998) mentions three closely related terms viz. status, autonomy and empowerment and defines them as follows:

1.2.1.Def 1: The Status of Women refers to the positions that women occupy in the family and in society relative to those of men and of women of other classes, other countries, other times.

1.2.2.Def 2: Female Autonomy refers to an individual’s capacity to act independently of the authority of others.

1.2.3.Def 3: Female Empowerment (empowerment of women) refers to the capacity of individual women or of women as a group to resist the arbitrary imposition of controls on their behaviour or the denial of their rights, to challenge the power of others if it is deemed illegitimate, and to resolve a situation in their favour.

These definitions imply a relationship that exists between these concepts. Empowerment does imply autonomy leading to enhanced status of women as compared to men and autonomy can be considered as a means to empowerment. Therefore when data on empowerment are not available, the autonomy serves as a good proxy to empowerment.

Autonomy as a concept cannot be simple or one-dimensional. Particularly relevant are social and economic realms in which most of the day to day activities of a person take place. In a study of women aged 15-59, Roy et al (2004), citing from Jejeebhoy (1998), have considered decision-making, freedom of movement and access to money as direct indicators of autonomy. Balk (1997), in a study of women aged between 15 and 56, identifies physical mobility and women’s authority in household decision making as indicators of status of women.

In these studies the age group under study covers females in their reproductive period. Their functions and priorities do not remain the same when they transit to old age. Therefore, decision making has to be replaced by participation in the form of giving suggestions in day to day social and economic matters. Henceforth, this feature shall be termed as autonomy/empowerment in what follows.

Participation shows that they have a role to play and are not marginalized creatures. The present study is an attempt in this direction. It was initiated with following aims:

To identify the indicators of empowerment for older adults.

To investigate the associations and relationships between these indicators and the gender aspects therein.

To investigate the effect of socio-economic factors on these indicators

The 42nd round of the NSS investigates the participation of the older adults in social/religious as well as economic matters. The definitions used in the survey are as follows:

  • Def 1: participation in social matters means physical or mental (giving advice) participation in arranging important functions such as marriage, shraadh ceremony etc.
  • Def 2: participation in religious matters means physical or mental (giving advice) participation in arranging religious functions.

For participation in economic matters we have information on whether an older adult is involved in the management of assets/property that he owns.

The following section raises some questions, the answers to which may help revealing the empowerment scenario of older females in India.

  1. Research Questions (RQ)
  2. What are the social and economic indicators of autonomy for the older adults? Are the indicators of autonomy and gender associated?
  3. What are the interrelations and associations between the indicators of autonomy with reference to the gender? This question incorporates the following questions:
  4. How does the association between Having and Managing Property and Participation in Social Matters varies with gender when controlled for other factors? In other words does economic autonomy implies social autonomy, and if it is the case how does gender affect it?
  5. How does the association between Having and Managing Assets and Participation in Social Matters varies with gender when controlled for other factors? In other words does economic autonomy implies social autonomy, and if it is the case how does gender affect it?
  6. How does the association between Having and Managing Property and Participation in Religious Matters varies with gender when controlled for other factors?
  7. What are the determinants of autonomy (which is a means to empowerment) for the older adults? Do they vary with Gender? More specifically the following hypotheses shall be tested:
  8. H01: Net of all effects widows are less likely to be empowered in social or economic aspects.
  9. Hypotheses about availability of children and socio-economic empowerment:
  10. H02e: Net of all effects older adults with less number of children are more likely to participate in management of assets/property.
  11. H02s: Net of all effects older adults with less number of children are less likely to participate in social/religious matters.
  12. Hypotheses concerning economic dependency, economic activity and empowerment:
  13. H03a: Net of all effects partially dependent and dependent older adults are less likely to participate in social and religious matters when compared to those older adults who are not dependent on others.
  14. H03b: Net of all effects, participation in social/religious matters varies with activity status of older adults.
  15. H03c: Net of all effects, participation in management of property/assets varies with activity status of older adults.
  16. Hypotheses regarding effect of diseases and disability on empowerment:
  17. H04a: Net of all effects prevalence of a chronic disease reduces the likelihood of participation in management of assets/property and participation in social/religious matters.
  18. H04b: Net of all effects severe/partial immobility adversely effects the empowerment.
  19. Hypotheses regarding household characteristics and empowerment:
  20. H05a: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with living arrangements of older adults.
  21. H05b: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with size of household.
  22. H05c: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with ownership of house.
  23. H05d: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with economic status of the household.
  24. Hypotheses regarding social, cultural and geographic factors and empowerment:
  25. H06a: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with educational status of older adults.
  26. H06b: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with religion of older adults.
  27. H06c: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with caste of older adults.
  28. H06d: Net of all effects participation in social/religious matters and participation in management of assets/properties differ with place of residence of older adults.
  29. Methodology
  30. We look upon autonomy as a means to empowerment. The indicators of autonomy comprise of two sets. The one comprising of indicators of economic autonomy and the other comprising of indicators of social autonomy. The former includes two variables namely having and managing property and having and managing assets (1.1.1). The other includes two variables namely participating in social matters andparticipating in religious matters (1.1.2).
  31. Each of the variables in the set comprises of three categories namely not having, having and not managing and having and managing the respective resources. The set comprises of binary categorical variables with categories participating and not participating.
  32. To have a broad view of the situation, we start with presenting the odds ratio for older female Vs older male, for all the four indicators, for various states of India. The data for economic empowerment includes those older male and female who have property or assets. The rest of the analysis concerns pooled all India data.
  33. To probe deeper into the association and interrelationship between these variables a log-linear framework is proposed. The gender aspect is incorporated by including sex along with the variables and. This makes up a 23322 contingency table containing 72 cells corresponding to a multinomial distribution with parameters, where n(56192) is the sample size and i =1, 2…I, j =1, 2…J, k =1,2…K, l =1, 2…L, m =1,2…M and n =1,2…N. Here, denote the probability of an outcome represented by a cell with ith, jth, kth, lth and mth levels of sex, and.
  34. Letting denote the count in a cell with ith, jth, kth, lth and mth levels of sex, and.

3.6. The saturated log-linear model fitted to data has the following form:

The superscripts in the terms show the order of interaction of the variables and the subscripts show the categories of the respective variables. An appropriate model, that best accounts for the data, shall be found out and the odds ratios shall be used to answer the research questions.

The odds ratios for So Vs E shall be used to investigate the association between these two factors (RQ2.2.1). Similarly associations between indicators of empowerment shall be used to investigate RQ2.2.2 and RQ2.2.3.

Conceptual framework for estimating the effect of other factors on indicators of empowerment:

The state of empowerment and its four indicator variables are looked upon as functions of three sets of factors. These factors are individual level characteristics, household characteristics and social level characteristics.

  1. Individual level characteristics

The individual level characteristics include the demographic characteristics, Economic characteristics and Health characteristics. These characteristics indicate internal effects. The characteristics and their indicator variables are as follows:

Individual level demographic characteristics: Age, marital status and availability of son.

Individual level Economic characteristics: Activity status, and economic dependency.

Individual level Health characteristics: Prevalence of chronic diseases and disability.

  1. Household level characteristics

These characteristics indicate household conditions. The household level characteristics are as follows:

Characteristics of household economic condition: Per capita income and dwelling.

Characteristics of household composition: Size, living arrangements and ownership.

  1. Socio-cultural and geographic characteristics

These characteristics are macro ones and affect the individuals as groups (excluding education). These characteristics indicate overall external environment. The ones that are included in the present study are religion, caste, education (including course) and place of residence.

Suppose we have a binary response, Yi, coded 1 if empowered (participating in management of property/management of assets/social matters/religious matters, as the case may be) and 0 otherwise. Letting, i denote the probability of empowerment i.e.

Let Xi=(x1, x2...xk) be a set of explanatory variables that influence Yi. Then the logistic regression model is given as:

Where, β’s are the coefficients. The analysis includes logistic regression models for each of the four indicators of empowerment, for older females as well as older males (eight logistic regression models).

  1. Findings and Analysis

The first sub-section of this section addresses the issues of empowerment at old age, the social and economic indicators of empowerment and the gender angle there in (RQ2.1). The second sub-section analyses the associations and interrelationships of the indicators of empowerment. Finally, the third sub-section analyzes the three tier conceptual framework, proposed in the previous section, incorporating the gender perspective.

4.1.The autonomy enjoyed by older women vis-à-vis the older men in social and economic realms are reflected in Table-1. A common observation over all states of India and for all the four indicators of autonomy is that the older women are less likely to play part in social and economic decision making as compared to their male counterparts. The negative association between sex and socio-economic autonomy is clear.

Table 1: Odds Ratios for Older Female Vs Older Male for Different Indicators of Empowerment

States / Older Female Vs Older Male Odds Ratio for Autonomy in
Participation in / Management of
Social Matters / Religious Matters / Assets / Property
Andhra Pradesh / 0.440 / 0.510 / 0.112 / 0.135
Assam / 0.488 / 0.574 / 0.100 / 0.105
Bihar / 0.512 / 0.663 / 0.201 / 0.202
Gujarat / 0.471 / 0.511 / 0.100 / 0.108
Haryana / 0.692 / 0.562 / 0.102 / 0.181
Himachal Pradesh / 0.362 / 0.392 / 0.243 / 0.254
Jammu and Kashmir / 0.316 / 0.333 / 0.094 / 0.108
Karnataka / 0.295 / 0.308 / 0.084 / 0.081
Kerala / 0.385 / 0.380 / 0.113 / 0.121
Madhya Pradesh / 0.426 / 0.474 / 0.165 / 0.146
Maharashtra / 0.549 / 0.639 / 0.126 / 0.153
Manipur / 0.336 / 0.243 / 0.407 / 0.426
Meghalaya / 0.534 / 0.761 / 0.263 / 0.378
Nagaland / 0.119 / 0.229 / 0.000 / 0.098
Orissa / 0.318 / 0.396 / 0.105 / 0.097
Punjab / 0.414 / 0.394 / 0.168 / 0.191
Rajasthan / 0.455 / 0.445 / 0.219 / 0.258
Sikkim / 0.220 / 0.200 / 0.879 / 0.364
Tamilnadu / 0.509 / 0.503 / 0.142 / 0.147
Tripura / 0.421 / 0.574 / 0.128 / 0.093
Utter Pradesh / 0.510 / 0.628 / 0.164 / 0.167
West Bengal / 0.452 / 0.619 / 0.074 / 0.085
A & N Islands / 0.515 / 0.502 / 0.106 / 0.095
Arunanchal Pradesh / * / * / * / *
Chandigarh / 0.767 / 0.682 / 0.667 / 0.526
D & NH / 0.073 / 0.118 / 0.071 / 0.074
Delhi / 0.714 / 0.958 / 0.103 / 0.155
Goa Daman and Diu / 0.359 / 0.298 / 0.701 / 0.537
Lakshadweep / 0.285 / 0.214 / * / 0.043
Mizoram / 0.398 / 0.542 / 0.246 / 0.235
Pondicherry / 0.183 / 0.166 / * / 0.588

* Data not available

The odds ratio for participation in social matters and the odds ratio for participation in religious matters are positively correlated (Fig 1). Similarly the odds ratio for participation in management of assets is positively correlated with the odds ratio for management of property (Fig 2). It should also be noted that none of the any of the other two pairs of indicators showed any correlation. This implies that though autonomy of one kind implies other in social sphere or economic sphere but autonomy in social sphere may not imply autonomy in economic sphere. For in-depth investigation of the interrelations between these indicators of autonomy a log linear model is used in the following discussion.

4.2.The best log-linear model fitted to the data has the following form: