Why under five children are stunted in Pakistan? A multilevel analysis of Punjab Multiple indicator Cluster Survey (MICS-2014)

• Main Authors: Tahir Mahmood, Faisal Abbas, Ramesh Kumar, Ratana Somrongthong
• Format: Article
• Language: English
• Published: BMC 2020-06-01
• Series: BMC Public Health
• Subjects: Undernutrition; Stunting; Child health; Pakistan; Punjab; Multilevel models
• Online Access: http://link.springer.com/article/10.1186/s12889-020-09110-9

Abstract Background Pakistan is facing a serious problem of child under-nutrition as about 38% of children in Pakistan are stunted. Punjab, the largest province by population and contributes high gross domestic product (GDP) share in economy has reported 27% moderately and 10% severely stunted children of less than 5 years. Thus, this study aims at examining the determinants of stunting (moderate and severe) at different level of hierarchy empirically in Punjab province of Pakistan. Methodology Data for this study is coming from Punjab Multiple Indicators Cluster Survey (MICS-2014), used two-stage, stratified cluster sampling approach. Sub-national level data covering urban and rural areas were used for this study consists of 25,067 children less than 5 year’s ages, from nine administrative divisions and 36 districts of Punjab province of Pakistan. Descriptive statistics and multilevel hierarchical models were estimated. Multilevel data analyses have an advantage because it provides robust standard error estimates and helps in finding variation in the data at various levels. Results Punjab has a stunting prevalence of about 27% moderately and 10% severely stunted children of less than 5 years. The results depict that increasing the age of the child, increasing birth order, illiterate mothers and fathers, lack of sanitation facilities and being poor are associated significantly with the likelihood of moderate and severe stunting. Surprisingly, there is a gender bias in stunting in Punjab, Pakistan and being a girl child is more likely associated with moderate and severe stunting, which shows the patriarchal nature of the society and a substantial prevalence of gender bias in household resource allocations. Conclusion This outcome of our analysis points towards targeting not only households (focus on girls) but also their families and communities.