Evidence map›Paper›PMID 33293748›Full record

ArticleBulletin of the World Health Organization2020

Transitions between body mass index categories, South Africa.

Muchiri E Wandai, Jens Aagaard-Hansen, Samuel Om Manda, Shane A Norris

Abstract read
In one paragraph

Article in Bulletin of the World Health Organization, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Phenotypic and Genetic Diversity in Diabetes Across Populations.The Journal of clinical endocrinology and metabolism · 2025
    Review
  2. Article
  3. Article
  4. Article
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

4 authors.

Muchiri E WandaiSAMRC Developmental Pathways for Health Research Unit, University of the Witwatersrand, 27 St Andrew's Road, Parktown, Johannesburg 2193, South Africa.
Jens Aagaard-HansenSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Samuel Om MandaBiostatistics Research Unit, South Africa Medical Research Council (SAMRC), Pretoria, South Africa.
Shane A NorrisSAMRC Developmental Pathways for Health Research Unit, University of the Witwatersrand, 27 St Andrew's Road, Parktown, Johannesburg 2193, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo profile the prevalence of the three body mass index (BMI) categories by sociodemographic characteristics, and to calculate the percentage transitioning (or not) from one BMI category to another, to inform South African health policy for the control of obesity and noncommunicable diseases.

methodsWe used data from the National Income Dynamics Study, including sociodemographic characteristics and BMI measurements collected in 2008, 2010, 2012, 2014 and 2017. For each data collection wave and each population group, we calculated mean BMI and prevalence by category. We also calculated the percentage making an upwards transition (e.g. from overweight to obese), a downwards transition or remaining within a particular category. We used a multinomial logistic regression model to estimate transition likelihood.

findingsBetween 2008 and 2017, mean BMI increased by 2.3 kg/m

conclusionIn the development of national strategies to control obesity and noncommunicable diseases, our results will allow limited public health resources to be focused on the relevant population groups.

Indexed as

ObesityOverweightAdultBody Mass IndexCross-Sectional StudiesFemaleHumansMiddle AgedPrevalenceSouth AfricaYoung Adult

Identifiers

PMID33293748
PMCPMC7716104

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.