Selective Versus Generalized Gender Bias in Childhood Health and Nutrition: Evidence from India.
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ABSTRACT:
SUBMITTER: Rajan S
PROVIDER: S-EPMC5988261 | biostudies-literature | 2018 Jun
REPOSITORIES: biostudies-literature
Publications
Selective Versus Generalized Gender Bias in Childhood Health and Nutrition: Evidence from India.
Rajan Sowmya S Morgan S Philip SP
Population and development review 20180312 2
We use data from India's National Family Health Survey (conducted in 1992-93, 1998-99, and 2005-06) to study gender discrimination across India among children aged 0-35 months. We focus on four measures of parental investment: (1) immunization, (2) received medical treatment for acute respiratory infection (ARI), (3) breastfed beyond 17 months, and (4) severe stunting. We contrast <i>generalized discrimination</i> that affects all daughters (vs. sons) with selective <i>discrimination</i> that po ...[more]
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Project description:BackgroundPublicly Funded Health Insurance Schemes (PFHIS) are intended to play a role in achieving Universal Health Coverage (UHC). In countries like India, PFHISs have low penetrance and provide limited coverage of services and of family members within households, which can mean that women lose out. Gender inequities in relation to financial risk protection are understudied. Given the emphasis being placed on achieving UHC for all in India, this paper examined intersecting gender inequalities and changes in PFHIS coverage in southern India, where its penetrance is greater and of longer duration.Data and methodsThis study used the fourth (NFHS-4, 2015-16) and fifth (NFHS-5, 2019-21) rounds of India's National Family Health Survey for five southern states: namely, Andhra Pradesh, Karnataka, Kerala, Tamil Nadu, and Telangana. The World Health Organization's Health Equity Assessment Toolkit (HEAT) Plus and Stata were used to analyse PFHIS coverage disaggregated by seven dimensions of inequality. Ratios and differences for binary dimensions; Between Group Variance and Theil Index for unordered dimensions; Absolute and Relative Concentration Index (RCI) for ordered dimensions were computed separately for women and men.ResultsOverall, PFHIS coverage increased significantly (p < 0.001) among women and men in Andhra Pradesh, and Kerala from NFHS-4 to NFHS-5. Overall, men had higher PFHIS coverage than women, especially in Andhra Pradesh, Tamil Nadu, and Telangana in both surveys. In both absolute and relative terms, PFHIS coverage was concentrated among older women and men across all states; age-related inequalities were higher among women than men in both surveys in Andhra Pradesh, Kerala, and Telengana. The magnitude of education-related inequalities was twice as high as among women in Telangana (RCINFHS-4: -12.23; RCINFHS-5: -9.98) and Andhra Pradesh (RCINFHS-4: -8.05; RCINFHS-5: -7.84) as compared to men in Telangana (RCINFHS-4: -5.58; RCINFHS-5: -2.30) and Andhra Pradesh (RCINFHS-4: -4.40; RCINFHS-5: -3.12) and these inequalities remained in NFHS-5, suggesting that lower education level women had greater coverage. In the latter survey, a high magnitude of wealth-related inequality was observed in women (RCINFHS-4: -15.78; RCINFHS-5: -14.36) and men (RCINFHS-4: -20.42; RCINFHS-5: -13.84) belonging to Kerala, whereas this inequality has decreased from NFHS-4 to NFHS-5., again suggestive of greater coverage among poorer populations. Caste-related inequalities were higher in women than men in both surveys, the magnitude of inequalities decreased between 2015-16 and 2019-20.ConclusionsWe found gender inequalities in self-reported enrolment in southern states with long-standing PFHIS. Inequalities favoured the poor, uneducated and elderly, which is to some extend desirable when rolling out a PFHIS intended for harder to reach populations. However, religion and caste-based inequalities, while reducing, were still prevalent among women. If PFHIS are to truly offer financial risk protection, they must address the intersecting marginalization faced by women and men, while meeting eventual goals of risk pooling, indicated by high coverage and low inequality across population sub-groups.
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