Women autonomy and its sociodemographic correlates in high focus states of India

INTRODUCTION

Autonomy is a complex concept that is difficult to quantify.¹ It refers to the independence or freedom of will of one's actions. It is the ability to receive knowledge and make judgments regarding one's problems.² Women's autonomy, according to Dixon (1978), is defined as "the degree of a woman's access to, and control over, financial resources such as food, income, land, and other kinds of wealth, as well as social resources such as knowledge, power, and status." Women's autonomy is influenced by a variety of social, cultural, and individual factors, including education, occupation, and financial status.³ Families with a low level of autonomy had significantly more children than other groups, indicating that autonomy is an important factor of fertility.⁴ Women's autonomy was found to be adversely proportional to fertility behavior in two research conducted in South and Southeast Asia.⁴ Women's autonomy will not only reduce mortality and enhance maternal health care usage for themselves but also improved health outcomes that can be seen among their children.⁵ Various research in Bangladesh, Nepal, Ethiopia, Nigeria, and Ghana have found that women's autonomy has a positive impact on maternity healthcare utilization.^6-11 These studies show that restricting women's autonomy by limiting their movement, participation in decision-making, and financial independence, consequences are relatively lower utilization of reproductive care services among women. Although a lot of prior research has looked at socioeconomic, demographic, and other factors that influence access to maternity care in India, the impact of women's autonomy on access to reproductive health services has received poor attention in this nation.^12-14 Women’s empowerment resulting in more justified distributions of power within the household may contribute to the prioritization of women’s own nutrition and health, which may manifest in improved body mass index (BMI) and micronutrient status.¹⁵ According to the NFHS-4 survey, 7.7% of women in India are aware of microcredit programs/loans, while 41.6 percent of women obtain money from their earnings. About 26.1% of women have physical movement for personal/family reasons.¹⁶ Furthermore, 28.1 percent of Indian women have access to women's autonomy for their own health care, followed by 13.4% in Nepal and 17.6% in Bangladesh.¹⁷ Furthermore, according to various Indian studies, one out of every four women is a victim of this occurrence, indicating a slight improvement from the deteriorating condition over the last decade.^16-19 It was found that the result of Violence against women functions at four measures at the individual level, personal level, community, and society level.²⁰ In this study, we aimed to determine the socio-demographic factors influencing women’s autonomy among study subjects and to find out the contribution of these significant factors.

METHODS

The present study used the fourth round of dataset from National Family Health Survey (NFHS-4) which was conducted during January 2015 to December 2016, and it is openly accessible online for secondary use. NFHS-4 is a nationally representative, population-based survey conducted in all states as well as union territories of India under the Ministry of Health and Family Welfare.

For the non-identical round of NFHS, the International Institute of Population Sciences has been assigned as the nodal agency. The present study is based on high focus states in India of the reproductive age group (15-49) women. The eight Empowered Action Group (EAG) states (Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Odessa, Rajasthan, Uttar Pradesh, and Uttarakhand) and Assam are designated as ‘High Focus States’ by the Government of India.²⁸ Total 381927 women in the reproductive age group (15-49) are taken in our study. Women's autonomy was measured by the five indicators such as Decision regarding own health care, large household purchases, visit to her family or relatives, decision on husband earning, and contraception use. Bivariate and logistic regression analysis, are used to access the association between various socio-demographic characteristics and women’s autonomy indicators. Binary logistic regression analysis is used to obtain the odds of different types of decision-making indicators among women. The dependent variables are five indicators, the decision regarding own health care, large household purchases, visit to her family or relatives, decision on husband earning and contraceptive use whereas the independent variables are age, place of residence, working status, no. of living children, wealth index, education, and religion. One composite index of woman autonomy is established based on the above five-question related to the decision-making of woman autonomy. Every five questions have been classified in two categories (1 = if woman alone or jointly decides, 0 = if women have not parted in the decision-making. Additionally, the index is calculated by adding the score obtained in five dimensions for each study subject. Index value (0-3) is bunched together in the “low autonomy” group and values (4-5) in the “high autonomy” group. Let Yi is the independent variable; Xi is the set of explanatory variables and βi is the coefficient, then the logistic regression equation is log(p/1-p) = β0 + β1X1 + β2X2 + …

Where p is predicted the probability and log odd of p and (1-p) provides the odds ratios on the reference category.

RESULTS

This table explain the exhaustive analysis of women who are the only authority in decision making. The decision-making authority of women alters with a change in their characteristics. Younger women are the least accord with sole decision-making authority.

Approximately 20 percent of women in the age group 30-34 have sole decision-making authority over the final decision on contraception while nearly 17 percent of women in the age group 45-49 can take an independent decision regarding visit to family or relative.

The results indicate that the working status of women acts as a facilitator in their sole decision-making authority. With the rise in the educational status of women, the sole decision-making authority among women decreases as a greater number of women with lesser education have sole authority over decision-making.

Women’s health is a key schedule in every development goal and most of the governments around the world would agree upon this, but still, women’s autonomy upon own health care needs a crucial view.

Nearly percent of women having the poorest wealth index have only decision-making authority over the large household purchases while nearly 16 percent of women having the richest wealth index have an independent decision regarding visit to family or relative.³⁰ Approximately 3 percent of women in the age group 15-19 cannot decide for their own health care without discussing/asking their husband or others in the family. Approximately 18 percent of the women in the age group 30-34 have the sole authority of decision-making regarding their own health care (Table 1).

Women's autonomy has been grabbed through various dimensions, and that gives a glance at a dim picture of women’s autonomy in high focus states (EAG and Assam) in India.

Only 9 percent of women have the autonomy to make decisions about their health care without taking any consent from anyone. Only 6.6 percent of the women have mobility autonomy, and nearly 8 percent of the women have sole authority over decisions regarding contraceptive use, and nearly 5 percent of women have sole autonomy to decide on major household purchases. Approximately 24 percent of the husband/partner is the primary decision-makers on their earning. Some of the decisions give best results when taken jointly with women and their partners like contraceptive use and large household purchases and it is reflected from the results where the contraceptive use 83 percent of women are deciding with their husband/partner while for large household’s purchases nearly 68 percent of women are making decisions with their husband/partner (Table 2).

** indicates significance at 1 % and * indicate significance at 5% level of significance

This table represents the percentage of women who reported that their household decision is either alone or with their husbands. Conclusion on decision-making has been drawn through five different domains of autonomy, and the outcomes of the crosstab represent the significant association between the decision-making and the socio-demographic characteristics of women. Women’s involvement (either alone or with their husband) is maximum in deciding the contraceptive use (91.6%) followed by the decision taken regarding their health care (73.8%), decision on husband earning (73%), large household purchase (72.6%), and a visit to family or relatives (72.1%). Nearly 72 percent of women in the age group 25-29 take decisions on their own health care either alone or with their husband. An identical trend can be seen for other decision-making domains excluding decisions on contraception. Their participation in all five dimensions of decision-making gradually increases with increase in their education and wealth condition. Participation of urban women, in all five dimensions of decision making, is more as compared to rural women. It can be seen from the table that education, income, increases in age, and the number of living children have a positive association with women's autonomy. Purchasing autonomy is lower among rural women (71%) as compared to urban women (77.8%), the reason behind this because of urban women are more educated, economically stable, and independent. Mobility can be seen as one of the significant measures of autonomy in a women's life. Urban women have higher mobility autonomy than their counterparts. No. of living children is positively associated with mobility index i.e., women having a large number of living children have higher autonomy than their counterparts and it is also positively associated with the husband earning and final decision on contraception (Table 3).

This table indicates the association between the decisions of married women on their own health, major household purchases, visit to her family or relatives, husband earning, and Contraception with selected background characteristics. The Odds of deciding their own health by the women in the age group 30-34, 35-39, 40-44, and 45-49 are 2.18, 2.38, 2.53, and 2.58 times higher as compare with those who belong to age group 15-19. Women of higher age group (age 30 and above) have nearly 2 times more say in health care, large household purchase, visit to family or relative, the decision on husband earning and final decision on contraception compared to the women of early age group (15-19).

Women’s employment shows a significant relationship with five covariates of women’s autonomy. It was found that women, who work for cash are more likely to participate in own health-care decision making, major household purchases, visit to her family or relatives, and in the decision on husband’s earning. Place of residence does not have any significant relationship with any of the covariates of women’s autonomy. The number of living children also plays a significant association in women’s decision-making power. The likely hood of participating in own health care decisions is approximately 1.5, 1.7, and 1.8 times higher than in women with one, two, and three or more living children respectively compared to those women who do not have any living children. It is also significantly associated with women’s say on the major household purchase and husband earning. Wealth Index is significantly associated with all covariates of women’s autonomy excluding the decision of poorer women on husband earning.

Education is also significantly associated with all covariates of women’s autonomy (Table 4). Shows the result of logistic regression between women's autonomy index and different socio-demographic variables. Women's autonomy index has been created by adding up all the five dimensions of decision-making. Index value (0-3) is bunched together in the “low autonomy” group and values (4-5) in the “high autonomy” group. The age of women is significantly associated with women's autonomy. Women who are in the age group 40-44 and 45-49 were approximately two times more likely to have autonomy than women in the reference group age 15-19. OR 1.86 and OR 1.84 (95% CI: 1.40-2.48, 1.38-2.45). Women in rural areas were less likely to have autonomy than women in urban areas. Education can be seen as one of the most important catalysts in achieving autonomy. Women with higher education are 1.6 times more likely to have higher autonomy than illiterate women. OR 1.61 (95% CI: 1.41-1.84). The Result does not show any association between wealth accumulations and autonomy therefore wealth is necessarily a means to achieve greater female autonomy as it has an ambivalent influence on women’s autonomy. The number of living children to an extent affects the autonomy since women without children have less autonomy than those who have living children (Table 5).

** indicates significance at 1 % and * indicate significance at 5% level of significance

Graph shows the percentage distribution of women's autonomy in high focus states of India where Jharkhand (8.6%) is the most autonomous state while Bihar (6.4%) is the least autonomous state, the reason behind it may be due to socio-economically backwardness and poorest literacy level in Bihar (Figure 1).

DISCUSSION

This study looked at how socio-demographic factors are associated with women's autonomy. Various previous studies which were conducted in South Asia have looked at the solely single determinant at a time at the individual level.²¹

This study covers the five major dimensions of women’s autonomy such as the decision on own health care, major household purchases, visit to her family or relatives, the decision on husband earning, and final decision on contraception. It was found in this study, as age increases, the autonomy of older women also increases regardless of the autonomy measure used. In 2009, a study conducted in India, Nepal, and Bangladesh also ratify that as women get older, they gain autonomy in household decision-making.²²

Behind this, a possible reason can happen in a household because a newly married daughter-in-law has less decision-making power and it is expected to perform the domestic or household duties under the supervision of her mother-in-law who is already a primary decision-maker.²³ The contribution of the place of residence in decision-making has been widely recognized as a crucial determinant beyond the physical environment.

This finding is consistent with a study conducted in South Asian countries that rural women are significantly less likely to involve in decision-making as compare to urban women.²²

The study reiterates that men are the primary decision-makers in the household for all the five dimensions hereupon there is a need to assess the impact of educating these men so that they can bring in positive changes in the household in terms of improved health outcomes, better education for their children, and overall development of the family.

The study clearly showed that women's autonomy as measured with decision-making authority is quite low when considering taken alone by women and this needs to be assessed in future studies. Women's autonomy (decision making either alone or with a partner) has increased significantly, the finding suggests that gender dynamics and male involvement are still very much valued in women’s decision-making.

There are some limitations of the study acknowledged that Women Autonomy Index cannot be thoroughly measured by a few households decision- making indicators as information gathered from the respondents on their husband’s characteristics might have been influenced by few omissions and biases.

Generally, in India men are the supreme decision maker and have whole control on their own families so there is possibility that joint decision might be reached convincing women to agree with men who is the head of the household.

CONCLUSION

The aim of the fifth sustainable development goal (SDG) was to promote gender equality and empower women by the year 2030 after the millennium development goal (MDG) could not achieved. It emphasizes empowering women and girls, to increase financial resources, must have equal benefits, equal rights, and opportunities. (MDG, SDG). The findings of this study shows that women’s autonomy varied with the socio-demographic and economic characteristics of women. Due to lack of education and employment, women are excluded from many households decision-making. The finding reveals that respondent currently working status is significantly associated with a higher level of autonomy. Women's participation in income-generating activities should also be prioritized by the government, as should women's access to property through land ownership and other economic assets. Our study suggests that the prosperity and development of our national women’s autonomy appear to be one of the important factors. In India, women’s autonomy is mostly dependent on various social factors like social backwardness and religious orthodox which have reduced the strength of decision-making power of women compared to men. Moreover, empowering the women to enhance their access, control over economic resources, and establishing and realizing their rights in decision-making- making, are the essential means to empower them.

ACKNOWLEDGMENTS

Scrutiny of the data (NFHS-4) has been done by Vikash Singh Patel which. Sandeep Patel analyzed the data. Vikash Singh Patel and Prince Kumar Patel contributed to drafting the manuscript and also intellectually revising it. All the authors take the responsibility for the integrity of the work and are given final approval for the publication.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Institutional Ethics Committee

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