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      Risk factors of malaria in children under the age of five years old in Uganda

      research-article
      ,
      Malaria Journal
      BioMed Central
      Complex survey design, Generalized linear mixed model, Microscopy test, IRS, ITNs, LLINs

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          Abstract

          Background

          Malaria is the leading cause of morbidity in Uganda with 90–95 % of the population at risk and it contributing to approximately 13 % of under-five mortality. The aim of this study was to investigate the relationship between the malaria status of children under the age of 5 years old in Uganda and selected socio-economic, demographic and environmental factors, as well as to identify significant risk factors associated with malaria.

          Methods

          This study made use of data collected from the 2014 Malaria Indicator Survey conducted in Uganda. Two test procedures for malaria in children under the age of 5 years old were carried out. Due to the complex survey design, a generalized linear mixed model was used to test for associations between several independent variables and the response variable, which was whether a child tested positive or negative for malaria according to the microscopy test.

          Results

          The sample in this study was made up of 4939 children. Of those children, 974 tested positive for malaria, resulting in an observed malaria prevalence of 19.7 %. The socio-economic factors closely related to the risk of malaria were main floor material, main wall material and availability of electricity in the household. The event of indoor residual spraying (IRS) significantly reduced a child’s risk of malaria. An older child was associated with a higher risk of malaria, however their risk decreased with an increase in cluster altitude and an increase in their caregiver’s education level.

          Conclusion

          Although there has been a significant increase in the use of mosquito nets since the previous Malaria Indicator Survey done in 2009, particularly in the use of insecticide-treated nets (ITNs) and long-lasting insecticidal nets (LLINs), these control measures alone may not be sufficient. IRS will be a key strategy in reaching the malaria goals set by the government of Uganda. Supplementing these control measures with education of appropriate and consistent use of ITNs and LLINs, as well as education of practicing safe living habits, such as reducing outdoor activities during peak biting hours of a mosquito, can go a long way in aiding the reduction of the burden of malaria in Uganda.

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          Most cited references29

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          Prevalence and risk factors of malaria in Ethiopia

          Background More than 75% of the total area of Ethiopia is malarious, making malaria the leading public health problem in Ethiopia. The aim of this study was to investigate the prevalence rate and the associated socio-economic, geographic and demographic factors of malaria based on the rapid diagnosis test (RDT) survey results. Methods From December 2006 to January 2007, a baseline malaria indicator survey in Amhara, Oromiya and Southern Nation Nationalities and People (SNNP) regions of Ethiopia was conducted by The Carter Center. This study uses this data. The method of generalized linear model was used to analyse the data and the response variable was the presence or absence of malaria using the rapid diagnosis test (RDT). Results The analyses show that the RDT result was significantly associated with age and gender. Other significant covariates confounding variables are source of water, trip to obtain water, toilet facility, total number of rooms, material used for walls, and material used for roofing. The prevalence of malaria for households with clean water found to be less. Malaria rapid diagnosis found to be higher for thatch and stick/mud roof and earth/local dung plaster floor. Moreover, spraying anti-malaria to the house was found to be one means of reducing the risk of malaria. Furthermore, the housing condition, source of water and its distance, gender, and ages in the households were identified in order to have two-way interaction effects. Conclusion Individuals with poor socio-economic conditions are positively associated with malaria infection. Improving the housing condition of the household is one of the means of reducing the risk of malaria. Children and female household members are the most vulnerable to the risk of malaria. Such information is essential to design improved strategic intervention for the reduction of malaria epidemic in Ethiopia.
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            Factors determining the heterogeneity of malaria incidence in children in Kampala, Uganda.

            Malaria risk may be heterogeneous in urban areas of Africa. Identifying those at highest risk for malaria may lead to more targeted approaches to malaria control. A representative sample of 558 children aged 1-10 years were recruited from a census population in a single parish of Kampala and followed up for 2 years. Malaria was diagnosed when a child presented with a new episode of fever and a thick blood smear positive for parasites. Multivariate analysis was used to identify independent predictors of malaria incidence. A total of 695 episodes of uncomplicated malaria were diagnosed after 901 person years of follow-up. Sickle cell trait (relative risk [RR], 0.68 [95% confidence interval {CI}, 0.52-0.90]), glucose-6-phosphate dehydrogenase deficiency in female children (RR, 0.48 [95% CI, 0.31-0.75]), and use of an insecticide-treated bed net (RR, 0.52 [95% CI, 0.32-0.83]) were associated with a lower risk of malaria. The distance of the subject's residence from a swamp bordering the parish showed a strong "dose-response" relationship; living in the swamp was the strongest predictor of malaria risk (RR, 3.94 [95% CI, 2.61-5.97]). Malaria incidence was highly heterogeneous in this urban cohort of children. Malaria control interventions in urban areas should target populations living in pockets of high malaria risk.
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              Plasmodium infection and its risk factors in eastern Uganda

              Background Malaria is a leading cause of disease burden in Uganda, although surprisingly few contemporary, age-stratified data exist on malaria epidemiology in the country. This report presents results from a total population survey of malaria infection and intervention coverage in a rural area of eastern Uganda, with a specific focus on how risk factors differ between demographic groups in this population. Methods In 2008, a cross-sectional survey was conducted in four contiguous villages in Mulanda, sub-county in Tororo district, eastern Uganda, to investigate the epidemiology and risk factors of Plasmodium species infection. All permanent residents were invited to participate, with blood smears collected from 1,844 individuals aged between six months and 88 years (representing 78% of the population). Demographic, household and socio-economic characteristics were combined with environmental data using a Geographical Information System. Hierarchical models were used to explore patterns of malaria infection and identify individual, household and environmental risk factors. Results Overall, 709 individuals were infected with Plasmodium, with prevalence highest among 5-9 year olds (63.5%). Thin films from a random sample of 20% of parasite positive participants showed that 94.0% of infections were Plasmodium falciparum and 6.0% were P. malariae; no other species or mixed infections were seen. In total, 68% of households owned at least one mosquito although only 27% of school-aged children reported sleeping under a net the previous night. In multivariate analysis, infection risk was highest amongst children aged 5-9 years and remained high in older children. Risk of infection was lower for those that reported sleeping under a bed net the previous night and living more than 750 m from a rice-growing area. After accounting for clustering within compounds, there was no evidence for an association between infection prevalence and socio-economic status, and no evidence for spatial clustering. Conclusion These findings demonstrate that mosquito net usage remains inadequate and is strongly associated with risk of malaria among school-aged children. Infection risk amongst adults is influenced by proximity to potential mosquito breeding grounds. Taken together, these findings emphasize the importance of increasing net coverage, especially among school-aged children.
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                Author and article information

                Contributors
                danjader@gmail.com
                matthewsgsa@gmail.com
                Journal
                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                1475-2875
                27 April 2016
                27 April 2016
                2016
                : 15
                : 246
                Affiliations
                School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Westville, Private Bag X 54001, 4000 Durban, South Africa
                Article
                1290
                10.1186/s12936-016-1290-x
                4848810
                27121122
                e7876ffb-c73a-43d5-967b-080d11d8b9b6
                © Roberts and Matthews. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 3 February 2016
                : 13 April 2016
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Infectious disease & Microbiology
                complex survey design,generalized linear mixed model,microscopy test,irs,itns,llins

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