It takes a village: An empirical analysis of how husbands, mothers-in-law, health workers, and mothers influence breastfeeding practices in Uttar Pradesh, India.

Melissa F Young,Sebanti Ghosh,Phuong Nguyen,Rasmi Avula,Purnima Menon,Rajeev Agrawal,Shivani Kachwaha,Jessica Escobar‐Alegria,Lan Tran Mai

doi:10.1111/mcn.12892

Abstract

Evidence on strategies to improve infant and young child feeding in India, a country that carries the world's largest burden of undernutrition, is limited. In the context of a programme evaluation in two districts in Uttar Pradesh, we sought to understand the multiple influences on breastfeeding practices and to model potential programme influence on improving breastfeeding. A cross‐sectional survey was conducted among 1,838 recently delivered women, 1,194 husbands, and 1,353 mothers/mothers‐in‐law. We used bivariate and multivariable logistic regression models to examine the association between key determinants (maternal, household, community, and health services) and breastfeeding outcomes [early initiation of breastfeeding (EIBF)], prelacteal feed, and exclusive breastfeeding (EBF). We used population attributable risk analysis to estimate potential improvement in breastfeeding practices. Breastfeeding practices were suboptimal: EIBF (26.3%), EBF (54%), and prelacteal feeding (33%). EIBF was positively associated with maternal knowledge, counselling during pregnancy/delivery, and vaginal delivery at a health facility. Prelacteal feeds were less likely to be given when mothers had higher knowledge, beliefs and self‐efficacy, delivered at health facility, and mothers/mothers‐in‐law had attended school. EBF was positively associated with maternal knowledge, beliefs and self‐efficacy, parity, and socio‐economic status. High maternal stress and domestic violence contributed to lower EBF. Under optimal programme implementation, we estimate EIBF can be improved by 25%, prelacteal feeding can be reduced by 25%, and EBF can be increased by 23%. A multifactorial approach, including maternal‐, health service‐, family‐, and community‐level interventions has the potential to lead to significant improvements in breastfeeding practices in Uttar Pradesh.

Highlights

Breastfeeding is one of the most cost-effective child survival interventions known; an estimated of 823,000 children, and 20,000 women's lives would be saved annually if breastfeeding practices were scaled up globally (Victora et al, 2016)
Under optimal programme implementation and conditions, we estimate early initiation of breastfeeding can be improved by 25%, prelacteal feeding can be reduced by 25%, and exclusive breastfeeding can be increased by 23%. (Bromberg Bar-Yam & Darby, 1997; Negin, Coffman, Vizintin, & Raynes-Greenow, 2016), few studies examined the role of MMILs and husbands in supporting women to breastfeed
We estimate that with improving maternal and family knowledge of breastfeeding, improving counselling on breastfeeding and providing support at delivery, improving self-efficacy, reducing maternal stress and domestic violence can together improve early initiation of breastfeeding (EIBF) by 25pp, prelacteal feeding can be reduced by 25pp, and exclusive breastfeeding (EBF) can be increased by 23pp

Summary

Introduction

Breastfeeding is one of the most cost-effective child survival interventions known; an estimated of 823,000 children, and 20,000 women's lives would be saved annually if breastfeeding practices were scaled up globally (Victora et al, 2016). In Uttar Pradesh, breastfeeding rates are much lower compared with the national average with EIBF at only 7% in National Family Health Survey (NFHS)-3 (2005–2006; IIPS, 2017b) and increasing to 25% in NFHS 4 (2015–2016); in this period, EBF rates decreased from 51% to 42%, slipping below global targets (IIPS, 2017b). To address these challenges, India has developed comprehensive infant and young child feeding programmes and policies that are well aligned with global guidance (Avula, Oddo, Kadiyala, & Menon, 2017; Bhutta et al, 2013; India-MoHFW, 2013; MoWCD, 2013; Vir et al, 2014). A review of the policy environment in India identified key implementation barriers such as lack of clear operational guidance, insufficient use of monitoring data to inform programme activities, and training/supervision capacity gaps (Avula et al, 2017)

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