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.
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.
Background:
Underweight prevalence continues to be major public health challenge worldwide, particularly in developing countries like Pakistan. This study is focused on socio-economic and demographic aspects of underweight prevalence among children under-five in Punjab.
Methods:
In this study, several socioeconomic and demographic factors are considered using MICS-4 data-set. Only those variables which are usually described in the nutritional studies of children were picked. Covariates include: the age of children, sex of the children, age of mother, total number of children born to women, family wealth index quintile, source of drinking water, type of sanitation, place of residence, parents' education and occupation. All Categorical variables are effect coded. The child's age and the mother's age are assumed to be nonlinear, geographical region is spatial effect, while other variables are parametric in nature. Since, the response is binary, covariate comprises linear terms, nonlinear effects of continues covariates and geographic effects, so we have use Geo-additive models (based on Fully Bayesian approach) with binomial family under logit link. Statistical analysis is performed on Statistical package R using Bayes X and R2 Bayes X Libraries.
Results:
Underweight status of children was found to be positively associated with number of under-five children in household, total number of children ever born to women and age of mother when the child was born. Whereas, it negatively associated with place of residence, parent's education and family wealth index quintile. On the regional effect, the Southern Punjab has higher prevalence of underweight compared to Central and Northern Punjab.
Conclusion:
Similarity of our results with several other studies demonstrate that the Geo-additive models are an ideal substitute of other statistical models to analyze the underweight prevalence among children. Moreover, our findings suggest the Punjab Government, to introduce target-oriented programs such as poverty reduction and enhancement of education and health facilities for poor population and disadvantaged regions, especially Southern Punjab.
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