BackgroundNeonatal mortality defined as a death during the first 28 days of life and is the most critical phase of child survival. In spite of the strong evidence supporting immediate and long term health benefits of timely initiation of breastfeeding in India, only two-fifths (44%) of children receive breastfeeding within 1 h of birth. This study aims to examine the role of a behavioral factor i.e., timing of initiation of breastfeeding on neonatal deaths.MethodsData from India Human Development Survey-II (IHDS-II), 2011–12, a nationally representative, large scale population-based dataset has been used. Sample Registration System (SRS) has been used to examine the rate of change in Neonatal Mortality Rates from the year 2011 to 2015. District Level Household & Facility Survey (DLHS-4), 2012–2013 and Annual Health Survey(AHS), 2012–13 data have been used to show the district wise distribution of women who have breastfed their child within 1 h of birth. Population Attributable fraction has been computed using binary logistic regression model for various scenarios of breastfeeding within first hour of birth.ResultsLess than one fourth (21%) of children were breastfed within 1 h of birth across the different districts of India, which varies from the lowest 15% in Sarasvati of Uttar Pradesh state to the highest 94.6% in Thiruvananthapuram of Kerala state. Findings suggest when women did not breastfeed their newborn within the 1 h after his birth, the odds of neonatal deaths were increased by nearly threefold (OR 2.93; 95% CI 1.89, 4.53) in comparison with those neonates who have breastfed within 1 h of birth. Population Attributable Risk estimates that the risk of the neonatal deaths could be reduced to a maximum of 15% when all babies would expose to early breastfeeding from the present level of breastfeeding.ConclusionsWe found that timely initiation of breastfeeding is beneficial for child survival within the first 28 days of birth, including all causes of mortality. Therefore, efforts in formulating an effective policy focusing on early initiation of breastfeeding are needed.

Objectives Despite threefold increase in investment (from Rs. 28,500 million to Rs. 90,000 million during 2014–17) in the allocation of funds for the Clean India movement, creating awareness and various social movements, more than half of the rural population (52.1%) of the country still defecates in the open. This study aims to examine the prevalence of improved sanitation facilities and safe stool disposal in India and its states. It also aims to further establish inter-linkages between safe stool disposal and child health. Study design The present study uses data from the fourth round of the recently conducted cross-sectional National Family Health Survey (NFHS-4, 2015–16). Methods Two proxy indicators used to assess the effect on child health are: stunting and mortality of children under the age of five years. Multivariate logistic regression analysis was employed to examine the impact of improved sanitation facilities and safe stool disposal on child health measured by height-for-age as a dichotomous variable. Multivariate discrete-time logistic model was used to examine the impact of improved sanitation facilities and safe stool disposal on under-five child deaths. Results The results reveal that unsafe disposal of stools are one of the main contributing factors responsible for stunting and under-five mortality among children. The prevalence was clearly seen to be higher in households where open defecation and unsafe stool disposal were practised. Conclusions The central behavioural change to be brought about among the people is to improve the cleanliness levels of the neighbourhood and help children spend their childhood free from the misery of malnourishment or in the worst case, death. It is not an impossible task for a country that houses the cleanest village in Asia, Mawlynnong in the Northeast state of Meghalaya, India. If one state could do it, it could be replicated in other states too.

Background Since 2005, India has experienced an impressive 77% reduction in maternal mortality compared to the global average of 43%. What explains this impressive performance in terms of reduction in maternal mortality and improvement in maternal health outcomes? This paper evaluates the effect of household wealth status on maternal mortality in India, and also separates out the performance of the Empowered Action Group (EAG) states and the Southern states of India. The results are discussed in the light of various pro-poor programmes and policies designed to reduce maternal mortality and the existing supply side gaps in the healthcare system of India. Using multiple sources of data, this study aims to understand the trends in maternal mortality (1997–2017) between EAG and non EAG states in India and explore various household, economic and policy factors that may explain reduction in maternal mortality and improvement in maternal health outcomes in India. Methods This study triangulates data from different rounds of Sample Registration Systems to assess the trend in maternal mortality in India. It further analysed the National Family Health Surveys (NFHS). NFHS-4, 2015–16 has gathered information on maternal mortality and pregnancy-related deaths from 601,509 households. Using logistic regression, we estimate the association of various socio-economic variables on maternal deaths in the various states of India. Results On an average, wealth status of the households did not have a statistically significant association with maternal mortality in India. However, our disaggregate analysis reveals, the gains in terms of maternal mortality have been unevenly distributed. Although the rich-poor gap in maternal mortality has reduced in EAG states such as Bihar, Odisha, Assam, Rajasthan, the maternal mortality has remained above the national average for many of these states. The EAG states also experience supply side shortfalls in terms of availability of PHC and PHC doctors; and availability of specialist doctors. Conclusions The novel contribution of the present paper is that the association of household wealth status and place of residence with maternal mortality is statistically not significant implying financial barriers to access maternal health services have been minimised. This result, and India’s impressive performance with respect to maternal health outcomes, can be attributed to the various pro-poor policies and cash incentive schemes successfully launched in recent years. Community-level involvement with pivotal role played by community health workers has been one of the major reasons for the success of many ongoing policies. Policy makers need to prioritise the underperforming states and socio-economic groups within the states by addressing both demand-side and supply-side measures simultaneously mediated by contextual factors.

ObjectivesThis paper analyses the patterns and trends in the mortality rates of infants and children under the age of 5 in India (1992–2016) and quantifies the variation in performance between different geographical states through three rounds of nationally representative household surveys.DesignThree rounds of cross-sectional survey data.SettingThe study is conducted at the national level: India and its selected good-performing states, namely Haryana, Kerala, Maharashtra, Punjab and Tamil Nadu, and selected poor-performing states, namely Bihar, Chhattisgarh, Madhya Pradesh and Uttar Pradesh.ParticipantsAdopting a multistage, stratified random sampling, 601 509 households with 699 686 women aged 15–49 years in 2015–2016, 109 041 households with 124 385 women aged 15–49 years in 2005–2006, and 88 562 households with 89 777 ever married women in the age group 13–49 years in 1992–1993 were selected.ResultsThrough the use of maps, this paper clearly shows that the overall trend in infant and child mortality is on a decline in India. Computation of relative change shows that majority of the states have witnessed over 50% reduction in both infant and under-5 mortality rates from National Family Health Survey (NFHS)-I to NFHS-4. However, the improvements are not evenly distributed, and there is huge variation in performance between states over time. Funnel plots show that the most populous states like Uttar Pradesh Bihar and Madhya Pradesh have underperformed consistently across the survey period from 1992 to 2016. Regression analysis comparing high-performing and low-performing states revealed that female infants and women with shorter birth intervals had greater risk of infant deaths in poor-performing states.ConclusionAttempts to reduce infant and child mortality rates in India are heading in the right direction. Even so, there is huge variation in performance between states. This paper recommends a mix of strategies that reduce child and infant mortality among the high-impact states where the biggest improvements can be expected, including the need to address neonatal mortality.

This study assessed caste differentials in family-level death clustering, linked survival prospects of siblings (scarring) and mother-level unobserved heterogeneity affecting infant mortality risk in the central and eastern Indian states of Jharkhand, Madhya Pradesh, Odisha and Chhattisgarh. Family-level infant death clustering was examined using bivariate analysis, and the linkages between the survival prospects of siblings and mother-specific unobserved heterogeneity were captured by applying a random effects logit model in the selected Indian states using micro-data from the National Family Health Survey-III (2005-06). The raw data clustering analysis showed the existence of clustering in all four states and among all caste groups with the highest clustering found in the Scheduled Castes of Jharkhand. The important factor from the model that increased the risk of infant deaths in all four states was the causal effect of a previous infant death on the risk of infant death of the subsequent sibling, after controlling for mother-level heterogeneity and unobserved factors. The results show that among the Scheduled Castes and Scheduled Tribes, infant death clustering is mainly affected by the scarring factor in Jharkhand and Madhya Pradesh, while mother-level unobserved factors were important in Odisha and both (scarring and mother-level unobserved factors) were key factors in Chhattisgarh. Similarly, the Other Caste Group was mainly influenced by the scarring factor only in Odisha, mother-level unobserved factors in Jharkhand and Chhattisgarh and both (scarring and mother-level unobserved factors) in Madhya Pradesh. From a government policy perspective, these results would help in identifying high-risk clusters of women among all caste groups in the four central and eastern Indian states that should be targeted to address maternal and child health related indicators.