# Trends and determinants of prelacteal feeding practice in rural Bangladesh from 2004 to 2019: A multivariate decomposition analysis

## TL;DR

Prelacteal feeding in rural Bangladesh dropped from 89% in 2004 to 24% in 2019, with changes linked to factors like health facility deliveries and birth weight.

## Contribution

This study identifies shifts in factors associated with prelacteal feeding and quantifies the role of socio-demographic changes in its decline.

## Key findings

- The prevalence of prelacteal feeding decreased significantly from 89% in 2004 to 24% in 2019.
- Institutional deliveries and higher birth weight were key factors associated with reduced prelacteal feeding.
- Only 15% of the decline in prelacteal feeding was explained by measured variables, leaving 85% unaccounted for.

## Abstract

Prelacteal feeding (PLF)—giving infants food or liquid other than breastmilk within the first 3 days of life—remains common and hinders optimal breastfeeding in Bangladesh. This study assessed changes in PLF practices in rural Bangladesh from 2004 to 2019 and examined associate household, maternal, and infant factors. We analyzed data from two cluster-randomized trials in rural northwest Bangladesh (n = 16,551; n = 4,401). Trained staff collected sociodemographic and birth data through household visits. We used multivariable logistic regression to examine associations between household, maternal, and infant characteristics and PLF and a non-linear approximation of the Oaxaca-Blinder regression decomposition to understand the factors associated with the changing prevalence of PLF. The prevalence of PLF declined from 89% in 2004 to 24% in 2019. Factors associated with PLF shifted over time, particularly household wealth, infant sex, and birth weight. Institutional delivery (OR=0.27; 95% CI 0.22, 0.32 in 2004; OR=0.78; 95% CI 0.61, 1.00 in 2019) and multigravida status (OR=0.68; 95% CI 0.58, 0.79 in 2004; OR=0.73; 95% CI 0.58, 0.93 in 2019) were consistently associated with reduced odds of PLF across cohorts in the multivariable analysis. The decomposition analysis based on the two trials indicated that changes in prevalence of the covariates explained 15% of the decrease in prevalence of PLF, primarily accounted for by increases in health facility deliveries (86%), increases in infant birth weight (13%), and increasing gravidity (12%). 85% of the change remains unexplained by the measured variables. The prevalence of PLF declined considerably in rural Bangladesh over the 15-year period. There are shifts in factors associated with PLF overtime. Improvements in socio-demographic factors played a modest but meaningful role in reducing PLF. However the majority of the reduction remains unexplained by the measured variables. Further research is needed to identify other potential drivers for changes in the prevalence of PLF.