Evidence map›Paper›PMID 31996196›Full record

ArticleBMC public health2020

Investigating the spatial variation and risk factors of childhood anaemia in four sub-Saharan African countries.

Danielle J Roberts, Glenda Matthews, Robert W Snow, Temesgen Zewotir, Benn Sartorius

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 44 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 3 countries.

Danielle J RobertsSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South Africa. danjader@gmail.com.
Glenda MatthewsDepartment of Statistics, Durban University of Technology, Durban, South Africa.
Robert W SnowPopulation Health, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.
Temesgen ZewotirSchool of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban, South Africa.
Benn SartoriusFaculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
University of KwaZulu-Natal · ZADurban University of Technology · ZAKenya Medical Research Institute · KELondon School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe causes of childhood anaemia are multifactorial, interrelated and complex. Such causes vary from country to country, and within a country. Thus, strategies for anaemia control should be tailored to local conditions and take into account the specific etiology and prevalence of anaemia in a given setting and sub-population. In addition, policies and programmes for anaemia control that do not account for the spatial heterogeneity of anaemia in children may result in certain sub-populations being excluded, limiting the effectiveness of the programmes. This study investigated the demographic and socio-economic determinants as well as the spatial variation of anaemia in children aged 6 to 59 months in Kenya, Malawi, Tanzania and Uganda.

methodsThe study made use of data collected from nationally representative Malaria Indicator Surveys (MIS) and Demographic and Health Surveys (DHS) conducted in all four countries between 2015 and 2017. During these surveys, all children under the age of five years old in the sampled households were tested for malaria and anaemia. A child's anaemia status was based on the World Health Organization's cut-off points where a child was considered anaemic if their altitude adjusted haemoglobin (Hb) level was less than 11 g/dL. The explanatory variables considered comprised of individual, household and cluster level factors, including the child's malaria status. A multivariable hierarchical Bayesian geoadditive model was used which included a spatial effect for district of child's residence.

resultsPrevalence of childhood anaemia ranged from 36.4% to 61.9% across the four countries. Children with a positive malaria result had a significantly higher odds of anaemia [AOR = 4.401; 95% CrI: (3.979, 4.871)]. After adjusting for a child's malaria status and other demographic, socio-economic and environmental factors, the study revealed distinct spatial variation in childhood anaemia within and between Malawi, Uganda and Tanzania. The spatial variation appeared predominantly due to unmeasured district-specific factors that do not transcend boundaries.

conclusionsAnaemia control measures in Malawi, Tanzania and Uganda need to account for internal spatial heterogeneity evident in these countries. Efforts in assessing the local district-specific causes of childhood anaemia within each country should be focused on.

Indexed as

Health Status DisparitiesAnemiaChild, PreschoolFemaleHumansInfantKenyaMalawiMalePrevalenceRisk FactorsSpatial AnalysisTanzaniaUgandaAdjusted odds ratioAnaemiaBayesianChildHaemoglobin levelHierarchical geoadditive modelSpatial effect

Identifiers

PMID31996196
PMCPMC6990548
OpenAlexW3009644058

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.