Socio-Economic Risk Profiling of Child Nutritional Status: Evidence from the Most Populous Province of Pakistan
Child malnutrition is considered one of the most focused areas of development, globally. The situation in developing countries, with lower literacy rate and lesser health awareness, is even more alarming and unpleasant. Pakistan a country of 220 million populations with literacy rate of 65 percent remains a prime candidate, worth studying the diverse nature of the issue. This research focuses on the analysis of Punjab based data the most populated province of Pakistan, sharing 50 percent of the total population of the country. Principally, this research advances the existing literature mainly on two fronts. Firstly, we study children nourishment status through ordinal scale and thus identify the more vulnerable and priority groups existent in the population. Secondly, we propose the use of WHO Infant and Young Children Feeding guidelines (IYCF) for food quality, as a determinant of child nourishment status. Also, we consider weight for age, as a composite anthropometric indicator to quantify the nourishment status of children of age under five years. Based on this indicator, child nourishment status is then categorized into three distinctive and hierarchical groups: severely malnourished (<-3.0 Z-score), moderately malnourished (-3.0 to -2.01 Z-score) and not malnourished (≥ 2.0 Z score). The objectives are achieved by using the Multiple Indicator Cluster Survey (MICS) 2017-2018 data for the Punjab province comprehending a sample of 25211 children. We observe that 7% children can be ranked as severely malnourished whereas, 14.5% children stayed in the moderately malnourished category. Moreover, bivariate analysis reveals statistically significant association between children nourishment status and, food intake diversity, mother education and health awareness, child previous health history and economic status of the household. The explanatory power of the determinants of malnourishment is assessed by employing various modeling strategies capable of entertaining diverse ordinal structures. We use Proportional Odds Model (POM), Non-Proportional Odds Model (NPOM). Based on keen application of statistical modeling techniques, our study suggests that NPOM can be considered as a more sophisticated approach to explore the factors affecting the child malnutrition. The findings of this research imply that, government and development organizations need to focus, not only, on improvement of overall household well-being but also required advocating the urgency for balanced food.
Abdu R Rahman, Zahid Asghar, Salman A Cheem, Tahir Munir