Socioeconomic and demographic factors determining the underweight prevalence among children under-five in Punjab

Rizwan Farooq1, Hina Khan2, Masood Amjad Khan3

  • 1Bureau of Statistics, Government of the Punjab Lahore, Lahore, Pakistan.

BMC Public Health
|December 1, 2020
PubMed

Insights

Underweight children in Punjab are linked to larger families and younger mothers. Improving education, wealth, and sanitation, especially in Southern Punjab, is crucial for public health interventions.

Area of Science:

  • Public Health
  • Pediatric Nutrition
  • Biostatistics

Background:

  • Underweight prevalence in children under five remains a significant global public health issue, particularly in developing nations like Pakistan.
  • This study investigates the socioeconomic and demographic determinants of underweight status among young children in Pakistan's Punjab province.

Purpose of the Study:

  • To identify key socioeconomic and demographic factors associated with underweight prevalence in children under five in Punjab.
  • To apply advanced statistical modeling for a comprehensive analysis of nutritional status determinants.

Main Methods:

  • Utilized the MICS-4 dataset, incorporating variables such as child's age, maternal age, family size, wealth index, water and sanitation access, residence, and parental education.
  • Employed Geo-additive models within a Fully Bayesian framework, using a binomial family and logit link function to account for linear, nonlinear, and spatial effects.
  • Statistical analyses were conducted using R, specifically leveraging the Bayes X and R2 Bayes X libraries.

Main Results:

  • Positive associations with underweight were observed for a higher number of children under five, total children ever born, and younger maternal age at birth.
  • Negative associations were found with improved place of residence, higher parental education levels, and increased family wealth index quintiles.
  • Southern Punjab exhibited a higher prevalence of underweight children compared to Central and Northern regions.

Conclusions:

  • Geo-additive models are effective for analyzing child underweight prevalence, offering an alternative to traditional statistical methods.
  • Findings underscore the need for targeted government programs in Punjab focusing on poverty reduction, education, and healthcare, particularly for disadvantaged areas like Southern Punjab.
Abstract

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