Women’s Autonomy, Women’s Status and Nutrition in India

Sandip Chakraborty[1], Kaushlendra Kumar[2] and Faujdar Ram[3]

Abstract

The constitution of India makes no distinction between the sexes. But this politically granted equality has not been very evident in practice and the social and economic status of women has not been on par with that of men. There is a need to study the differences in status of men and women in India, and, the changes that have occurred in these differences over time.

Several indicators like expectation of life at birth, adulthood literacy, workers in the modern sector, singulate mean age at marriage etc. were selected to study the relative status of men and women at several points of time, at a macro level. The data for the present study have been taken from different Censuses (particularly from 1971 to 2001) and Sample Registration System. Taxanomic method is used to classify and compare the status of men and women in the major states of India for the several periods. Cluster analysis has been performed to show the homogeneity among the several states in India in terms of status of men and women both.

The result shows that the gap between status of men and women are closer over the period and particularly in the period between 1991 and 2001. The status of men and women are high in the states like Kerala, Punjab etc. Though there is no difference in the clustering of states in terms of status for the period 1971 and 1981, but for the period 1991 and 2001, position of some states have changed.

Introduction:

Measuring women’s status and autonomy can be problematic. Women’s status has traditionally been measured using education and employment status variables. In a study of female autonomy in India, Dyson and Moore (1983) stated that autonomy represents the ‘capacity to manipulate one’s personal environment,’ and that ‘equality of autonomy between the sexes…implies equal decision-making ability with regard to personal affairs.’ Autonomy has thus increasingly been defined as a woman’s ‘ability or lack thereof to make decisions in the household’ (Hindin, 2000b). Higher levels of women’s autonomy, though context-specific and therefore measured slightly differently in different studies, have been associated with nutritional status (Hindin, 2000a), maternal health care utilization (Beegle, Frankenberg & Thomas, 2001; Bloom, Wypij, Das Gupta, 2001), and fertility behaviors and contraceptive use (Balk, 1994; Hindin, 2000b; Govindasamy & Malhotra, 1996; Al Riyami, Afifi & Mabri, 2004; Moursund & Kravdal , 2003), lower rates of child mortality (Castle, 1993). Malhotra et al. (2002) provide an overview of women’s status, empowerment, and decision-making autonomy, and a review of the literature linking these variables to health outcomes.

In developing countries females are in disadvantageous position with regard to health and well being (Santow, 1995). The cultures of South Asia are largely gender stratified, characterized by patrilineal descent, patrilocal residence, inheritence and succession practices that exclude women, and hierarchical relations in which the patriarch or his relatives have authority over family members (Jejeebhoy and Sathar, 2001). Patriarchal kinship and economic systems limit women’s autonomy and as a result the health status of both women and children, particularly female children, suffers in relation to that of males (Caldwell, 1986).

Autonomy and Nutrition:

Although women have tended to be producers for the family in many agricultural settings, their lack of access to the income from this labour leaves them resource-poor (Abbas, 1997). There has been some evidence to suggest that women who have lower levels of autonomy and status within in the household are more likely to experience under nutrition (Hindin, 2000) or have a lower BMI (Bindon & Vitzthum, 2002; Baqui et.al, 1994).

Aim of the Study:

The purpose of the study is to explore the extent of women’s autonomy and its relationship with the nutritional status of the women in India. The core hypothesis behind the paper is that, women with low autonomy and status will be less likely to obtain adequate food resources and will be more likely to experience under nutrition or Chronic Energy Deficiency (CED).

Data Source:

The nationwide data from India’s National Family Health Survey (NFHS-2) conducted during 1998-99 was used for this study. This survey covered a representative sample of 90,303 ever married women in the age group of 15-49 years, from 27 states of India. The sample comprised more than 99 percent of India’s population (IIPS, 2000). The survey used uniform questionnaires, sample designs, and field procedures to facilitate comparability of the data within the country, so as to achieve a high level of data quality.

Methodology:

For the purposes of the study, the sample was limited to non-pregnant married women who had not given birth in the last three months. These constraints led to a sample of 74, 391 women in India.

Measure of Nutrional Status:

National Family Health Survey provides the information on height and weight of the woman. Based on these two information, Body Mass Index (BMI) is calculated to the restricted population. Lastly, a dichotomous measure, Chronic Energy Deficiency (CED), based on the standard BMI cutoff of<18.5 kg/m2 was generated. This measure was used as a nutritional status of the individual.

Measures of Sociodemographic characteristics, Women’s and Partners’ characteristics:

The Sociodemographic characteristics of the sample are divided into two groups: household level characteristics and women characteristics. The household level characteristics include: i) Residence ii) Caste iii) Religion iv) Standard of living v) Size of the household and vi) Husband living in the household.

The women characteristics included in the analysis: i) Age ii) Number of births iii) Education and iv) Occupation. Education (for both the respondent and her partner/husband) was divided into four categories viz. Illiterate, Up to Primary, Up to secondary and higher. Occupation (for both the respondent and her partner/husband) was coded into five categories viz. Unemployed or not-working, working in agricultural, unskilled/skilled manual, non-manual and professional.

Partners’ characteristics include: i) Education and ii) Occupation.

Measures of Women’s relative status, Women’s status in society and Decision-making Autonomy:

Women’s relative status: Women’s relative status is conceptualized as their status relative to their partner’s status in terms of age, education and occupation. For age, three categories were used based on the continuous measures of age:

a)  respondents were four or more years older than their partners

b)  respondents were six or more years younger than their partners

c)  everyone else who was near the same age as their partners

Relative educational status was calculated as a difference between the partners’ schooling levels with three categories:

a)  respondent has more

b)  the couple has same level

c)  the partner has more

A relative occupational difference was calculated using the five occupational levels with three categories:

a) respondent has more

b) the couple has same level

c) the partner has more

Women’s status in society: In National Family Health Survey, women were asked about their attitudes toward wife beating. The women were asked to give their opinion about the justification of wife beating by their husband in the following situations:

a)  if she is unfaithful

b)  if her family does not give money

c)  if she shows disrespects

d)  if she goes out without permission

e)  if she neglects children and house

f)  if she does not cook properly

From these dichotomus variables (yes/no), an index was created based on whether women think it is justified for a husband to beat his wife, under any of the circumstances. This variable is used as a proxy to measure women’s status.

Measures of decision making: In the National Family Health Survey, women were asked about the person who has the final say or she has to need any permission over the following aspects:

a)  Final say over what to cook

b)  Final say over health care

c)  Final say about purchase jewelry

d)  Final say about staying with family

e)  Permission to visits relatives and friends house

f)  Permission to go to market

g)  Allowed to have money set aside

For each of these questions, the women were given the following response options:

a)  themselves

b)  husband/partner

c)  respondent and husband/partner jointly

d)  someone else

e)  respondent and someone else jointly

A set of dichotomous variables was created for each of the decision making dimension to reflect patterns of decision making. For each domain, the variable was coded as 1 if the women had the final say over that decision alone and 0 if the women did not have the final say. An index of autonomy was constructed on the basis of the decision taken by the women alone. Index of autonomy is a simple measure by summing up all the domains where the women (alone) had the final say. This index is categorized into three categories:

a) low (if the index lies between 0-2)

b) medium (if the index lies between 3-4)

c) high (if the index value is 5 or more)

Statistical analysis: Univariate and Bivariate analyses were used to study the level of autonomy, women’s status and nutritional status of women. Multivariate analyses were used to explore the determinants of Chronic Energy Deficiency (CED) and the level of autonomy. The multivariate analyses were done by Binary and Multinomial logistic regression analysis.

Binary Logistic Regression: The basic form of the logistic regression is

Where is constant, are the coefficients of

is the estimated probability of having Chronic Energy Deficiency (CED)

Multinomial Logistic Regression: In this model the response variable is mutually exclusive and exhaustive. The Multinomial Logit model can be given as:

= +, i= 1, 2, 3……………n;

= +, i= 1, 2, 3……………n;

p1 + p2 + p3 = 1. Where a1 and a2 are constants and b1i, b2i are the coefficients of xi’s.

For example in the present analysis, p1 is the estimated probability of medium level of autonomy p2 denotes the estimated probability of high level of autonomy and p3 is the probability of low level of autonomy. Here p3 is the reference category.

Results:

Table 1 represents the prevalence of Chronic Energy Deficiency (CED), Sociodemographic characteristics, Husbands characteristics, Women’s autonomy in decision making and Womens status in society. In India the percentage of women with Chronic Energy Deficiency (CED) is about 32 percent. Most of the women are rural resident (68 percent), Hindu (78 percent), general category (42 percent), having at least one child (91 percent), from large family (55 percent), representing medium standard of living (48 percent), higher age group (79 percent), illiterate (49 percent) and unemployed (63 percent). At the time of survey only 5 percent of women reported that their husband were not living with them, their husband’s were having at least secondary level of education (55 percent) and they were from agricultural and unskilled/skilled work group (66 percent).

In terms of women’s relative status fewer women (less than 1 percent) were older than their wives, 47 percent of the husbands were older than their wives and 53 percent of the couples were in same age. In India, women and their partner attain same level of education or men have more education than their partners. Only 6 percent of women have higher status job than their partners.

In India, most of the women have low status of autonomy (58 percent). Women from Western and Southern part have substantially more autonomy than the other parts of the country. In different domains of decision making, only in what to cook, women have more final say. Even in health care she has depend on others (mostly husband) decision. Most of the women need permission to go elsewhere. In terms of women’s status in society 54 percent of women in India believe it is OK for husbands to beat their wives in at least one of the six domains posed in the questionnaire. Interestingly it was found that even in Western and Southern part where the autonomy is high as compared to rest of the country, most of the women (55 percent and 66 percent) have the believe about the justification of wife beating by their husbands.

Level of autonomy by different background characteristics:

From table 2 it is clear that woman who belongs to rural area, low standard of living, childless, residing in large family and younger in age have less autonomy in decision making. They are unable to take decisions (alone) if husbands live with them. Education and occupation have positive relationship with the level of autonomy, as the level of education and occupation increases the level of autonomy also increases. If the woman has higher level of education and higher status of job as compared to her husband, she has more autonomy in decision making.

Factors associated with women’s autonomy in decision making:

To find out the influential factors on autonomy, the multinomial logistic regression has been applied by taking low autonomy as reference category. The coefficient under represents the effects of predictor variables on medium level of autonomy over low autonomy and represents the effects of predictor variables on high autonomy over low autonomy. The results in table 3 show that when the womens education level and occupation level are increasing the relative risk ratio of having high autonomy is also increasing, particularly for those women who are in non-manual, professional and higher level of education as compared to unemployed and illiterates. Women who are in professional jobs , their odd values is almost 2.5 times more as compared to unemployed and who are possessing higher level of education, their odd values is 1.7 times more as compared to illiterate. With respect to medium level of autonomy the corresponding ratio is about 1.8 times more as compared to unemployed and 1.5 times as compared to illiterate.

The standard of living index of the household does not play any significant role in autonomy whereas place of residence has some significant effect on autonomy, as the results show.