Caesarean deliveries, subsequent reproductive behaviour and children ever born in India.

Against the backdrop of the alarming rise in Caesarean section (C-section) births in India, this study aimed to examine the association between C-section births, fertility decline and female sterilization in the country. A cross-sectional design was used to investigate the association between C-section delivery and subsequent reproductive behaviour in women in India. Data were from the National Family Health Survey (NFHS-4). The study sample comprised 255,726 currently married women in the age group of 15-49 years. The results showed a strong positive relationship between C-section births and female sterilization. The predicted probabilities (PP) from the multivariate regression model indicated a higher chance of female sterilization in women with C-section births (PP = 0.39, p<0.01) compared with those with non-C-section births (PP = 0.20, p<0.01). Both state-level correlation plots and Poisson regression estimates showed a strong negative relationship between C-section births and mean children ever born (CEB). Based on the results, it may be concluded that the use of C-sections and sterilization were strongly correlated in India at the time of the NFHS-4, thus together contributing to fertility decline. A strong negative association was found between the occurrence of C-sections and CEB. The increased and undesired use of C-section births and consequent female sterilization is a regressive socio-demographic process that often violates women's rights. Fertility decline should happen through informed choice of family planning and must protect the reproductive rights of women.

Labour room violence in Uttar Pradesh, India: evidence from longitudinal study of pregnancy and childbirth.

OBJECTIVES: The major objective of this study was to investigate the prevalence of labour room violence (LRV) (one of the forms of obstetric violence) faced by the women during the time of delivery in Uttar Pradesh (UP) (the largest populous state of India which is also considered to be a microcosm of India). Furthermore, this study also analyses the association between prevalence of obstetric violence and socioeconomic characteristics of the respondents. DESIGN: The study was longitudinal in design with the first visit to women made at the time of first trimester. The second visit was made at the time of second trimester and the last visit was made after the delivery. However, we have continuously tracked women over phone to keep record of developments and adverse consequences. SETTINGS: Urban and rural areas of UP, India. PARTICIPANTS: Sample of 504 pregnant women was systematically selected from the Integrated Child Development Scheme Register of pregnant women. OUTCOME: We aimed to assess the levels and determinants of LRV using data collected from 504 pregnant women in a longitudinal survey conducted in UP, India. The dataset comprised three waves of survey from the inception of pregnancy to childbirth and postnatal care. Logistic regression model has been used to assess the association between prevalence of LRV faced by the women at the time of delivery and their background characteristics. RESULT: About 15.12% of women are facing LRV in UP, India. Results from logistic regression model (OR) show that LRV is higher among Muslim women (OR 1.8, 95% CI 0.7 to 4.3) relative to Hindu women (OR 1). The prevalence of LRV is higher among lower castes relative to general category, and is higher among those women who have no mass media exposure (OR 4.7, 95% CI 1.7 to 12.8) compared with those who have (OR 1). CONCLUSION: In comparison with global evidence, the level of LRV in India is high. Women from socially disadvantaged communities are facing higher LRV than their counterparts.

World health status 1950-2015: Converging or diverging.

OBJECTIVE: To advance the goal of "Grand Convergence" in global health by 2035, this study tested the convergence hypothesis in the progress of the health status of individuals from 193 countries, using both standard and cutting-edge convergence metrics. METHODS: The study used multiple data sources. The methods section is categorized into two parts. (1) Health inequality measures were used for estimating inter-country inequalities. Dispersion Measure of Mortality (DMM) is used for measuring absolute inequality and Gini Coefficient for relative inequality. (2) We tested the standard convergence hypothesis for the progress in Infant Mortality Rate (IMR) and Life Expectancy at Birth (LEB) during 1950 to 2015 using methods ranging from simple graphical tools (catching-up plots) to standard parametric (absolute ß and σ-convergence) and nonparametric econometric models (kernel density estimates) to detect the presence of convergence (or divergence) and convergence clubs. FINDINGS: The findings lend support to the "rise and fall" of world health inequalities measured using Life Expectancy at Birth (LEB) and Infant Mortality Rate (IMR). The test of absolute ß-convergence for the entire period and in the recent period supports the convergence hypothesis for LEB (ß = -0.0210 [95% CI -0.0227 - -0.0194], p<0.000) and rejects it for IMR (ß = 0.0063 [95% CI 0.0037-0.0089], p<0.000). However, results also suggest a setback in the speed of convergence in health status across the countries in recent times, 5.4% during 1950-55 to 1980-85 compared to 3% during 1985-90 to 2010-15. Although inequality based convergence metrics showed evidence of divergence replacing convergence during 1985-90 to 2000-05, from the late 2000s, divergence was replaced by re-convergence although with a slower speed of convergence. While the non-parametric test of convergence shows an emerging process of regional convergence rather than global convergence. CONCLUSION: We found that with a current rate of progress (2.2% per annum) the "Grand convergence" in global health can be achieved only by 2060 instead of 2035. We suggest that a roadmap to achieve "Grand Convergence" in global health should include more radical changes and work for increasing efficiency with equity to achieve a "Grand convergence" in health status across the countries by 2035.