Evidence map›Paper›PMID 33110582›Full record

ReviewJournal of global health2020

Fertility is a key predictor of the double burden of malnutrition among women of child-bearing age in sub-Saharan Africa.

Jason Mulimba Were, Saverio Stranges, Irena F Creed

Open access · goldAbstract readReview
In one paragraph

Review in Journal of global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

17 citing papers in PubMed, 27 citations in OpenAlex.

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  4. Defining double burden of malnutrition across individual, household and population level: A narrative review.Nutrition & dietetics : the journal of the Dietitians Association of Australia · 2026
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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

3 authors at 2 institutions in 2 countries.

Jason Mulimba WereDepartment of Epidemiology and Biostatistics, Western University, London, Ontario, Canada.
Saverio StrangesDepartment of Epidemiology and Biostatistics, Western University, London, Ontario, Canada.
Irena F CreedDepartment of Biology, Western University, London, Ontario, Canada.
Western University · CAUniversity of Saskatchewan · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ongoing nutrition transition in sub-Saharan Africa (SSA) is exhibiting spatial heterogeneity and temporal variability leading to different forms of malnutrition burden across SSA, with some regions exhibiting the double burden of malnutrition. This study aimed to develop a predictive understanding of the malnutrition burden among women of child-bearing age.

methodsData from 34 SSA countries were acquired from the Demographic and Health Survey, World Bank, and Swiss Federal Institute of Technology. The SSA countries were classified into malnutrition classes based on their national prevalence of underweight, overweight, and obesity using a 10% threshold. Next, random forest analysis was used to examine the association between country-level demographic variables and the national prevalence of underweight, overweight and obesity. Finally, random forest analysis and multinomial logistic regression models were utilized to investigate the association between individual-level social and demographic variables and Body Mass Index (BMI) categories of underweight, normal weight, and combined overweight and obesity.

resultsFour malnutrition classes were identified: Class A had 5 countries with ≥10% of the women underweight; Class B had 11 countries with ≥10% each of underweight and overweight; Class C1 had 7 countries with ≥10% overweight; and Class C2 had 11 countries with ≥10% obesity. At the country-level, fertility rate predicted underweight, overweight and obesity prevalence, but economic indicators were also important, including the gross domestic product per capita - a measure of economic opportunity that predicted both overweight and obesity prevalence, and the GINI coefficient - a measure of economic inequality that predicted both underweight and overweight prevalence. At the individual-level, parity was a risk factor for underweight in underweight burdened countries and a risk factor for overweight/obesity in overweight/obesity burdened countries, whereas age and wealth were protective factors for underweight but risk factors for overweight/obesity.

conclusionsBeyond the effect of economic indicators, this study revealed the important role of fertility rate and parity, which may represent risk factors for both underweight and combined overweight and obesity among women of child-bearing age. Health professionals should consider combining reproductive health services with nutritional programs when addressing the challenge of malnutrition in SSA.

Indexed as

FertilityMalnutritionAfrica South of the SaharaFemaleHumansObesityOverweightPrevalenceRisk FactorsSocioeconomic FactorsThinness

Identifiers

PMID33110582
PMCPMC7568927
OpenAlexW3092280820

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.