Impact of children born with low birth weight on stunting and wasting in Sindh province of Pakistan: a propensity score matching approach

Abstract

Low Birth Weight (LBW) is considered as a major public health issue and leading cause of neonatal death. Almost one in four newborns are reported as underweight in Pakistan. Children born with low birth weight are highly vulnerable to develop diseases and death and/or remain undernourished (i.e., stunted and wasted). This study determines the LBW newborns are more prone to develop stunting and wasting in province of Sindh, Pakistan. Moreover, regression-based estimation of the impact of LBW on the child health outcomes of under five years of age, may be prone to selection bias because of the nature of non-experimental data set, thus, propensity score matching methods are used in this study. Data for this study was used from Multiple Indicators Cluster Survey (MICS-2014). MICS is a two-stage, stratified cluster sampling household level data covering urban and rural areas and consists of 19,500 households from five administrative divisions and 28 districts of Sindh province of Pakistan. The total sample size of children less than five years of age after cleaning the data are 7781, of which 2095 are LBW having birth weight categorized as “smaller than average and very small” and 5686 are normal birth weight (NBW) having birth weight very large, larger than average, and average. This study employed propensity score matching (PSM) regression methods to understand whether the children born as low birth weight are more prone to stunting and wasting and/or both. In province of Sindh, moderate wasting children under five years were 21%, severe wasting 6% and both wasting and stunting 10%. The propensity score results are shown significant in all groups. Specifically, all four types of PSM methods confirm a significant difference in the potential outcome variables—meaning that a child born with LBW has a significant adverse effect on the potential child health outcome variables (stunting, wasting and both). Thus, the propensity score matching findings confirm a significant and adverse effect of LBW on potential health outcomes of under five children. Similarly, low birth weight children are significantly more likely to be moderately wasted (OR = 1.5, CI = 1.3–1.6) and severely wasted (OR = 1.6, CI = 1.3–2.0) and both (stunted and wasted, OR = 2.0, CI = 1.7–2.3) as compared to children with normal birth weight. Male children, if born with low birth weight, are significantly more likely to be moderately wasted (OR = 1.3, CI = 1.1–1.5) and both (wasted and stunted, OR = 1.3, CI = 1.1–1.5) than girls. This large data analysis finding proved that the LBW newborns are on higher risk to develop wasting and stunting in Pakistan.

Total Usual Nutrient Intakes and Nutritional Status of United Arab Emirates Children (<4 Years): Findings from the Feeding Infants and Toddlers Study (FITS) 2021

“…In addition, stunting, which reflects a more chronic type of undernutrition, may result from failure to meet micronutrient requirements ( 47 ), a fact that was also observed in our study. In addition, the prevalence of LBW, a significant predictor of child stunting and wasting ( 48 ), was previously shown to be high in the UAE and to exceed the prevalence observed in neighboring countries. According to the WHO, the prevalence of LBW in the UAE was 12.7% in 2015, compared to 9.9% in Kuwait and 7.3% in Qatar ( 49 ).…”

Current dichotomous metrics obscure trends in severe and extreme child growth failure

“…Particularly relevant for interventions aimed at addressing severe and extreme CGF, future work should aim to relate the health consequences of CGF to low birthweight and short gestational age. Children who are born preterm are more likely to experience CGF even years after birth ( 21 , 22 ). Work linking severe and extreme CGF to preterm birth may identify that the most effective interventions take place upstream, aimed at preventing CGF instead of treating it ( 23 ).…”

Lead Exposure in Infancy and Subsequent Childhood Growth

“…Models were adjusted, based on literature, for maternal characteristics (education, material possession/wealth score, estimated pre-conceptional BMI) and child characteristics (sex, low birth weight, and iron deficiency at age 1) [35][36][37]. Because iron deficiency may increase susceptibility to elevated BLLs [38] and is also known to be associated with food insecurity [39], iron deficiency (yes, no) was additionally adjusted in the final models.…”