Application of the Boruta algorithm to assess the multidimensional determinants of malnutrition among children under five years living in southern Punjab, Pakistan

被引:4
作者
Saleem, Javeria [1 ]
Zakar, Rubeena [1 ]
Butt, Muhammad Salman [1 ]
Aadil, Rana Muhammad [2 ]
Ali, Zulfiqar [3 ]
Bukhari, Gul Mehar Javaid [4 ]
Ishaq, Muhammad [5 ]
Fischer, Florian [6 ]
机构
[1] Univ Punjab, Dept Publ Hlth, Lahore, Pakistan
[2] Univ Agr Faisalabad, Natl Inst Food Sci & Technol, Faisalabad, Pakistan
[3] Univ Punjab, Coll Stat Sci, Lahore, Pakistan
[4] Rawalpindi Med Univ, Dept Community Med, Rawalpindi, Pakistan
[5] Univ Punjab, Inst Social & Cultural Studies, Dept Sociol, Lahore, Pakistan
[6] Charite Univ Med Berlin, Inst Publ Hlth, Berlin, Germany
关键词
Malnutrition; Undernutrition; Stunting; Wasting; GROWTH; INTERVENTIONS; NUTRITION; HEALTH;
D O I
10.1186/s12889-024-17701-z
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
BackgroundMalnutrition causes nutrient deficiencies that have both physical and clinical consequences in severe acute malnutrition children. Globally, there were 47 million wasted children under the age of five in 2019. One in four were located in sub-Saharan Africa, with half being in South Asia. This study aims to apply the Boruta algorithm to identify the determinants of undernutrition among children under five living in Dera Ghazi Khan, one of the marginalized districts of densely populated Punjab Province in Pakistan.MethodsA multicenter cross-sectional study design was used to collect data from 185 children with severe acute malnutrition aged under five years visiting the OTPs centers located in Dera Ghazi Khan, Punjab, Pakistan. A purposive sampling technique was used to collect data using a pretested structured questionnaire from parents/caregivers regarding family sociodemographic characteristics, child nutrition, and biological and healthcare characteristics. Anthropometric measurements, including height, weight, and mid-upper arm circumference, were collected. The Boruta models were used to incorporate the children's anthropometric, nutritional, and household factors to determine the important predictive variables for undernutrition using the Boruta package in R studio.ResultsThis study included 185 children, with a mean age of 15.36 +/- 10.23 months and an MUAC of 10.19 +/- 0.96 cm. The Boruta analysis identifies age, mid-upper arm circumference, weaning practices, and immunization status as important predictors of undernutrition. Income per month, exclusive breastfeeding, and immunization status were found to be key factors of undernutrition in children under the age of five.ConclusionThis study highlights age, mid-upper arm circumference, weaning practices, and immunization status as key determinants of weight-for-height and weight-for-age in children under five years. It also suggests that economic context may influence undernutrition. The findings can guide targeted strategies for combating undernutrition.
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页数:10
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