India is located between 8°4'N to 37°6'N latitudes and 68°7'E to 97°25'E longitudes in the southern part of Asia (Figure 1). The country is surrounded by Arabian sea in the west, Indian ocean in the south and Bay of Bengal in the east. Its northern boundary is marked by lofty Himalayan Mountain system which provides a unique and diversified physiographic units blended with cultural ethos. With a population of 1,210.9 million, India is the second highest populated country in the of the world which accounts 17.50% of the global population 16. United Nations Population Fund’s (UNFPA) State of the World Population Report in 2023 estimated that India has surpassed China as the World’s most populous country 17. Sex ratio of the country is 943 females per 1,000 males indicates the male dominated outlook of the society. Indian society is blended with a diverse cultural values and social features which provides a unique ground for the investigation of gender relations. The study area consists of selected states of India and the selection is primarily limited by the availability of maternal mortality data for the selected states. Details of the list of states included in this study has been given in Table 2.

The present study is based on the secondary data collected from different sources such as National Family Health Survey (NFHS)-5 (2019-21), Periodic Labour Force Survey, Sample Registration System (SRS) report, Ministry of Law and Justice report. An inequality index was calculated by combining dimensions such as reproductive health, empowerment, and economic status. Reproductive health refers to the state of physical, mental and social well-being, and is an important dimension of women’s welfare. To analyze reproductive health, two indices of maternal mortality ratio (MMR) and adolescent fertility rate (AFR) have been used. AFR measures the pregnancy in adolescent age which endangers their overall health and future choices. Similarly, empowerment was accessed by two indices of educational attainment and parliamentary representation. Economic status was accessed by including labour force participation rate for both genders. Details of the data and variables are given in the Table 1.

The study employed different statistical techniques, graphs, and indexes to meet the objectives. In the first part, cross-tabulation and descriptive statistics were employed to explains the broad picture of the indicators. In the second part, a multidimensional inequality Index has been calculated to analyze the status of gender inequality and states have been ranked based on it. The Gender Inequality Index (GII) was proposed in the Human Development Report published by the United Nation Development Program (UNDP). The index which is used in this study as follows; Reproductive health is measured using the two indices of MMR and AFR. The MMR is rescaled by 0.1 to account for the truncation of the MMR at 10 in the following Equation 1:

Where,

MMR = Maternal Mortality Ratio

ABR = Adolescent Fertility Rate

Dimension of empowerment is obtained from Equation 2:

Where,

PR = Political Representation

EA = Educational Attainment

Economic status measured through labour force participation rate (LFPR) using the Equation 3:

Where, LFPR = Labour Force Participation Rate

In the next steps, all the dimensions are aggregated for each gender using geometric mean based on the following , to make the GII more sensitive 18:

All the indices have been aggregated across gender groups using a harmonic mean using the Equation 6 to identify inequality across gender and to create an index of equal gender distribution:

Where, HARM = Harmonic mean

In the next step, the geometric mean of the arithmetic means for each indicator using equal weights (to treat the genders equally) are calculated using the following Equation 7:

Lastly, Gender Inequality Index (GII) is calculated using the following Equation 8:

In the third part, spatial analysis was done by using Arc-GIS (10.7.1) software to understand the regional pattern across the selected states of India. In the fourth part, regression analysis has been done based on enter method using SPSS (27.0.1.0) software to explain the key determinants affecting the level of gender inequality index across states.

MMR is one of the important component of reproductive health. Over the last two decades, maternal mortality has declined by almost 70%, but still India accounts for one-fifth of the global maternal death 19. Today, MMR stands at 97 per 1,00,000 live births at the national level as per Sample Registration System (SRS) report for the period of 2018-20 with regional variations. State-wise analysis revels that most of the southern states except Karnataka have already achieved the global 2030 SDG target of 70 maternal deaths per 100,000 live births, before time. Kerala has the lowest MMR (19 deaths per 1,00,000 live births). Similarly, most of the Empowered Action Group states and Assam except Jharkhand have high maternal mortality in the range of 149-215 per 1,00,000 live births.

The United Nations defines adolescent fertility rate (AFR) as the annual number of births to women aged between 15-19 years per 1,000 women. Adolescent pregnancy is a serious public health concern associated with the risk of antenatal complications, obstructed labor, premature delivery and low birth weight of babies even deaths of child and mother 17. Teenage pregnancy further limits educational prospects and economic opportunities of women. Adolescent fertility rate stands at 43 births per 1000 women aged between 15-19 years for the country as per NFHS-5 (2019-21). Of the 19 selected states, West Bengal recorded the highest adolescent fertility rate (AFR) for women between 15-19 age groups with 81 births per 1000 women aged between 15-19 years, followed by Bihar (77) and Andhra Pradesh (67). The lowest AFR is recorded in Kerala with 18 births per 1,000 women aged between 15-19 years. Region wise pattern shows that Southern states (Andhra Pradesh, Karnataka, Telangana) have high AFR in the range of 40-60 births per 1,000 women aged between 15-19 years.

In the present times, gender inequalities in educational attainment is a major concern for both public and scientific discourse. Gender differences in educational outcome has a strong impact upon the occupation types which further related to vertical inequalities in status and pay 20. We examine the gender gaps in 10 or more year of schooling to understand the ground reality across the selected states. On an average, 42.38% of women have completed 10 or more year of schooling compared to 50.81% for men, which clearly indicates gender gaps in educational attainment. Out of 19 states, Kerala is the only state with high number of women (77%) with 10 or more year of schooling compared to men. Three states namely Bihar, Madhya Pradesh and Assam have less than thirty-percent women with at least 10 more year of schooling.

Post the economic reforms, the country has achieved rapid economic growth and notable reduction in the poverty level. But the inequality between male and women in many dimensions remains the major concerns for the country. The analysis of the data suggests huge gender gaps between male and women in labour force participation. Women participation in the labour market remain more or less stagnant over the last few years (Figure 2). At the national level, labour force participation remains at 75.8% and 26.3% for men and women respectively in 2019-20 which shows a clear gender-based divide at national level (Figure 2). Gender gaps in labour market remains high (above 50%) in states like Bihar, Assam, Uttar Pradesh, Haryana, West Bengal, and Punjab. It reflects the male dominant character labour market and less opportunities for women in workforce.

Another dimension of concern is the representation of women in legislative and decision-making body. Representation of women in political sphere is important to bring out a balance between the principles and practices of law and improving the quality of deliberation 21. In this paper, representation of male and women members in the state legislative assembly (MLAs) were taken into account. Women make half of the population of the country, but only 14.39% of women MP representing that half in the Parliament in the 17^th Lok Sabha. It shows that India still lags behind several countries like South Africa (46%), United Kingdom (35%). The analysis of the data suggests that all the selected states have male dominate representation in their state legislature. On an average only 9.2% of MLAs are women in the selected states. This shows that women have made overall less progress in the political sphere compared to education or in the labour market.

Descriptive statistics of the constituents of gender inequality index is given in Table 2. It is clear from the national GII (0.499) that situation of women is far below that of men in the country. Regional distribution of gender inequality across the country is shown in Figure 3.

The results reveals that no single state has achieves the “perfect” result (0.000), although there are some states like Kerala (0.379), Chhattisgarh (0.433), Uttarakhand (0.436), performs well on this index. On the other hand, Bihar (0.673) and Assam (0.664) have least satisfactory score on the index, which shows disadvantage position of women in the societies. It can also be observed that overall levels of gender inequality do not concentrate in one particular region, rather it spread across the states.

Figure 3

Human Development Index (HDI) measures the achievement in basic dimension of human development such as a long and healthy life, access to knowledge and a decent standard of living. The Figure 4 shows the level of GII plotted against HDI based on size of population. Regarding the categories by HDI level, we find that achievement in HDI do not keep pace with reducing GII level. Thus, it can be said that human development gains are not equally distributed between both genders. The figure clearly indicates the prevalence of gender inequality in the states of India in some forms or the other. Most of the Empowered Action Group (EAG) states marked in orange outline in the figure are showing highly male biased society with medium level of human development. Adjacent states are clustered around each other shows the similar level of gender inequality.

It was hypothesized that reproductive health, educational attainment, political representation, and labour force participation of women will predict the GII values.

Thus, the study seeks to investigate the explaining factors affecting the inequality index through a multiple regression analysis and its results are shown in Table 3.

Results shows that 94% of the variance in gender inequality can be accounted for by the selected predictors, collectively, F (5,13) = 57.478, p < 0.001. Looking at the unique individual contributions of the predictors, the results shows that maternal mortality ratio (β=0.348, t=3.532, p=0.004), and adolescent fertility rate (β=0.330, t=3.553, p=0.004) positively predicts the gender inequality. Furthermore, results also reveal that political representation (β=-0.328, t=-5.335, p=0.000) and women labour force participation (β=-0.475, t=-6.869, p=0.000) are more likely (negatively) to report the gender inequality. This suggests that poor reproductive health outcomes of women have positively affects general index level across the states. On the other hand, increasing political representation and labour force participation of women actively reduces gender inequalities.