Analysis of severity of childhood anemia in Malawi: a Bayesian ordered categories model

Ngwira, Alfred; Kazembe, Lawrence

doi:10.2147/oams.s95159

Cited by 14 publications

(20 citation statements)

References 21 publications

(32 reference statements)

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“…The set of explanatory variables used in this study was also used in various studies modeling childhood anemia; [10,11,12,13,15,16,17,18,19] just to name few. Consequently, this forms the theoretical framework that will underpin the current research.…”

Section: Methodsmentioning

confidence: 99%

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda

Habyarimana

Zewotir

Ramroop

2017

IJERPH

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Childhood anemia is among the most significant health problems faced by public health departments in developing countries. This study aims at assessing the determinants and possible spatial effects associated with childhood anemia in Rwanda. The 2014/2015 Rwanda Demographic and Health Survey (RDHS) data was used. The analysis was done using the structured spatial additive quantile regression model. The findings of this study revealed that the child’s age; the duration of breastfeeding; gender of the child; the nutritional status of the child (whether underweight and/or wasting); whether the child had a fever; had a cough in the two weeks prior to the survey or not; whether the child received vitamin A supplementation in the six weeks before the survey or not; the household wealth index; literacy of the mother; mother’s anemia status; mother’s age at the birth are all significant factors associated with childhood anemia in Rwanda. Furthermore, significant structured spatial location effects on childhood anemia was found.

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Section: Methodsmentioning

confidence: 99%

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda

Habyarimana

Zewotir

Ramroop

2017

IJERPH

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“…For example, studies show that the child anaemia prevalence depends on region (e.g. see [47]), therefore we have considered a model that include cross-level interaction, i.e. region by anaemia category interaction to see their joint effect.…”

Section: Multilevel Modelmentioning

confidence: 99%

Weighted Multilevel Models for Malaria Indicator Survey

Zewude

Debusho

2020

Preprint

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Background: The data generated from malaria indicator surveys have a multilevel structure where children or households are nested within cluster and this may result in dependent data. In a survey, clusters or units within clusters may be selected with unequal probabilities and often surveys are subjected to non-response. Modeling of these data must take into consideration these aspects as these could lead to incorrect inferences. The main purpose of this study is to assess the factors that affect child malaria diagnostic outcomes and to estimate the proportion of overall child-level variation in malaria outcome that is attributable to child and household-level predictors and the cluster-level predictors using various weighted multilevel models. In this study, cluster represents a "Kebele", which is the smallest administrative unit in regional states in Ethiopia. Methods: A sample of 4,384 under five years age children were in this study from three regional states of Ethiopia. Various multilevel models with random cluster effects were used taking into account the survey design weights. These weights are scaled to address unequal probabilities of selection within clusters. Results: The asymptotic chi-square mixture distribution test results suggested the need for the cluster-level random effects in all the models. The findings related to child / household- and cluster-level predictors are consistent with those available in existing literature. The overall variability has been partitioned into child/household-level and cluster-level variability and the results revealed that some of the differences between clusters in under five years age children malaria RDT outcomes explained by child/household factors. Conclusions: The use of weighted multilevel model to examine within- and between cluster variability in malaria RDT outcomes for under five years age children and of the extent to which between clusters variability is explained by child / household and cluster-level factors. The approach used in this paper allows investigation of how individual- and cluster-level factors including the public health authorities’ interventions plans related to health outcomes simultaneously. Such collective assessment approach may lead to more effective public health strategies and could have important policy implications for health promotion and for the reduction of health disparities.

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“…Thereof, this study will be adding to the cur-rent studies that the government and policy makers of these countries are using to allocate resources. A study conducted by [22] in Malawi excluded child nutritional status as covariate, this covariate have been identify by literatures as a significant factor associated to under five mortality. In addition, [25] conducted a study that focused more on child's food consumption variables in Senegal.…”

Section: Explanatory Variablesmentioning

confidence: 99%

“…A study conducted by [22] showed that the Malawian policy makers and government need to address poverty, maternal anemia and malnutrition challenges in attempt to reduce the risk of exposing children to anemia condition. In addition, the research by [23] revealed that improving malaria and anemia control in pregnancy will reduce child's risk of suffering from anemic condition.…”

Section: Introductionmentioning

confidence: 99%

Determinants of anemia in children under five years in Angola, Malawi and Senegal: A comparative study

Khulu

Ramroop

2019

Preprint

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Background: Anemia is defined as a condition where there is an insufficient quantity of homoglobin, hematocrit or red cell in the human body [1, 2]. Unicef (2017) report urged all countries to reduce under ve years mortality by 2030, thereof there is a need of understanding and determining factors contributing to child mortality. The significance of this study underpins the improvement in collaboration among the three countries and recommend to government the area to invest in order to meet the SDG target.Method: The current study used demographic health survey data from Angola (2016), Malawi (2016) and Senegal (2016). Using World Health Organisation (WHO) classification guidelines of anemia, the ordinal dependent variable was developed. The three categories of anemia condition used in this study are Mild (10.0 - 10.9 g/dl), Moderate (7.0 - 9.9 g/dl) and severe (<7 g/dl). Results: Gamma measure and chi-square test of independence was conducted to explore the association between anemia status and factors. The score test and Brant test were used to test the proportional odds model assumption and it was satisfied.Results from ordinal survey logistic regression model found place of residence, age of the child, wealth index, mother level of education and nutritional status to be significant factors associated with anemic condition of under five year children in all three countries. Discussion: The health institutions of Angola, Malawi and Senegal need to monitor under five years children that are suffering from malnutrition condition. The study showed that there is a high chance for under five years children to suffer from both malnutrition and anemia condition. This finding is similar to the results of the study that was conducted in Bangladesh and Burma [27, 28].Conclusion: The study identifieed place of residence, age of the child, wealth index, mother level of education and nutritional status as common factors associated with anemia in Angola, Malawi and Senegal. This nding is in agreement with that of the studies conducted by [27, 26, 36]. The results showed the necessity of collaboration between Angola, Malawi and Senegal in order to achieve the SGD target.

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Analysis of severity of childhood anemia in Malawi: a Bayesian ordered categories model

Cited by 14 publications

References 21 publications

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda

Structured Additive Quantile Regression for Assessing the Determinants of Childhood Anemia in Rwanda

Weighted Multilevel Models for Malaria Indicator Survey

Determinants of anemia in children under five years in Angola, Malawi and Senegal: A comparative study

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