» Articles » PMID: 3494136

Nutritional and Socio-demographic Risk Indicators of Malaria in Children Under Five: a Cross-sectional Study in a Sudanese Rural Community

Overview
Journal J Trop Med Hyg
Specialty Public Health
Date 1987 Apr 1
PMID 3494136
Citations 14
Authors
Affiliations
Soon will be listed here.
Abstract

This paper reports the results of a cross-sectional study of the association between nutritional, environmental and socio-demographic factors, and malaria occurrence among 445 children under 5 years of age in a Sudanese rural community. The overall frequency of malaria as defined by a history of clinical illness during the previous 2 months was 27%. Malaria occurrence was positively associated with the degree of malnutrition as assessed by weight-for-age. The age-adjusted odds ratio for mild malnutrition and history of malaria was 1.2 (95% confidence interval (CI): 0.7-2.0) and for moderate malnutrition and malaria was 2.1 (95% CI: 1.1-4.0). Malaria was less frequent among children 0-11 months of age relative to older children (OR = 0.4; 95% CI:0.2-0.7), and was inversely associated with ownership of a refrigerator (OR = 0.5; 95% CI:0.36-0.94), an indicator of socio-economic status. Indicators of crowding were the best predictors of the risk of malaria. Less malaria was observed in households with three or more rooms (OR = 0.6; 95% CI:0.37-0.98) and more malaria was observed in households with more than five people (OR = 2.5; 95% CI:1.4-4.5). Malaria was slightly, but not significantly, more frequent among boys and was associated with anaemia, which was probably an outcome of malaria in the past. These data suggest that undernutrition may increase the risk of malaria, and draw attention to the importance of socio-economic and environmental factors in relation to this disease. These relationships deserve further examination in prospective follow-up studies that are better able to evaluate the temporal relations of malnutrition and malaria.

Citing Articles

Identifying individual, household and environmental risk factors for malaria infection on Bioko Island to inform interventions.

Garcia G, Janko M, Hergott D, Donfack O, Smith J, Eyono J Malar J. 2023; 22(1):72.

PMID: 36859263 PMC: 9979414. DOI: 10.1186/s12936-023-04504-7.


Spatio-temporal analysis and prediction of malaria cases using remote sensing meteorological data in Diébougou health district, Burkina Faso, 2016-2017.

Bationo C, Gaudart J, Dieng S, Cissoko M, Taconet P, Ouedraogo B Sci Rep. 2021; 11(1):20027.

PMID: 34625589 PMC: 8501026. DOI: 10.1038/s41598-021-99457-9.


Mice chronically fed a high-fat diet are resistant to malaria induced by Plasmodium berghei ANKA.

Oliveira-Lima O, Almeida N, Almeida-Leite C, Carvalho-Tavares J Parasitol Res. 2019; 118(10):2969-2977.

PMID: 31482465 DOI: 10.1007/s00436-019-06427-2.


Malaria epidemiology and comparative reliability of diagnostic tools in Bannu; an endemic malaria focus in south of Khyber Pakhtunkhwa, Pakistan.

Jahan F, Khan N, Wahid S, Ullah Z, Kausar A, Ali N Pathog Glob Health. 2019; 113(2):75-85.

PMID: 30894081 PMC: 6493316. DOI: 10.1080/20477724.2019.1595904.


Impact of the 2013 Floods on the Incidence of Malaria in Almanagil Locality, Gezira State, Sudan.

Elsanousi Y, Elmahi A, Pereira I, Debacker M PLoS Curr. 2018; 10.

PMID: 30443430 PMC: 6209411. DOI: 10.1371/currents.dis.8267b8917b47bc12ff3a712fe4589fe1.