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Factors associated with stunting among children aged below 60 months from rural Malawi: a matched case-control study

Author

Listed:
  • Fungo, R
  • Zulu, R
  • Munthali, J
  • Mutua, M
  • Birachi, E

Abstract

Stunting currently affects 37% (1.1 million) of Malawian children and causing unfavorable impact for both children and their households. Identifying risk factors to stunting would go a long way in developing appropriate interventions. The objective of this study was to identify the risk factors of stunting among children aged below 60 months from Balaka, Dedza and Mzimba districts in Malawi. A matched cross-sectional case-control study was conducted among 913 (446 controls; 467 cases) children aged below 60 months from three regions of Malawi. Household demographic, anthropometric measurements, dietary intake, food security, and morbidity information were collected. Case-Control Stepwise multiple logistic regression models are used to determine risk factors of stunting. The following were identified as risk factors for stunting including; age of child (AOR= 6.3; 95% CI: 2.9, 8.9), polygamy (AOR= 8.9; 95%, CI: 3.3, 13.03), maternal education (AOR= 9.9; 95%, CI: 2.8, 20.1), access to markets (AOR= 1.3; 95%, CI: 0.2, 2.4), childhood infections (AOR= 2.11; 95%, CI: 1.4, 4.2) and presence of oedema (AOR= 2.5; 95%, CI: 1.3, 4.1). Also, lack of food any month (AOR= 1.31; 95%, CI: 1.01, 4.9), purchasing food on credit (AOR= 1.48; 95%, CI: 1.4, 1.7), begging for food (AOR= 1.55; 95%, CI: 1.2, 2.1), mothers or caregivers consuming less than 5 food groups (MDD-W) (AOR = 4.83; 95% CI: 1.9, 16.4), exclusive breastfeeding (AOR= 5.45; 95%, CI: 4.33, 7.61) children weaned on plain water (AOR= 1.6; 95%, CI: 1.6, 2.41), powdered milk (AOR= 0.63; 95%, CI: 0.4, 1.32), juices (AOR= 0.44; 95%, CI: 0.12, 0.96) and children fed on sugary food (AOR= 0.66; 95%, CI: 0.4, 0.99) were significantly related to stunting. Stunting is associated with increasing age of children, boys, polygamous households, lack of education by mothers or caregivers, inaccessible markets, childhood infections and presence of oedema, food insecurity, breastfeeding and complementary feeding among children and dietary diversity of mothers or caregivers. These results suggest that interventions against childhood stunting should be designed according to the factors that significantly affect stunting.

Suggested Citation

  • Fungo, R & Zulu, R & Munthali, J & Mutua, M & Birachi, E, 2023. "Factors associated with stunting among children aged below 60 months from rural Malawi: a matched case-control study," African Journal of Food, Agriculture, Nutrition and Development (AJFAND), African Journal of Food, Agriculture, Nutrition and Development (AJFAND), vol. 23(10), November.
    • Handle: RePEc:ags:ajfand:340768
    DOI: 10.22004/ag.econ.340768
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    References listed on IDEAS

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    1. Rana Khan & Muhammad Raza, 2016. "Determinants of malnutrition in Indian children: new evidence from IDHS through CIAF," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 299-316, January.
    2. Juan Merlo & Philippe Wagner & Nermin Ghith & George Leckie, 2016. "An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-31, April.
    3. Jane Kabubo-Mariara & Godfrey K. Ndenge & Domisiano K. Mwabu, 2009. "Determinants of Children's Nutritional Status in Kenya: Evidence from Demographic and Health Surveys," Journal of African Economies, Centre for the Study of African Economies, vol. 18(3), pages 363-387, June.
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