Evidence map›Paper›PMID 39883633›Full record

ArticlePloS one2025

Obesity phenotypes and dyslipidemia in adults from four African countries: An H3Africa AWI-Gen study.

Engelbert A Nonterah, Godfred Agongo, Nigel J Crowther, Shukri F Mohamed, Lisa K Micklesfield, Palwendé Romuald Boua, Alisha N Wade, Solomon S R Choma, Hermann Sorgho, Isaac Kissiangani and 9 more

Abstract read
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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

19 authors.

Engelbert A NonterahNavrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana.ORCID https://orcid.org/0000-0001-8491-6478
Godfred AgongoNavrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana.
Nigel J CrowtherFaculty of Health Sciences, Department of Chemical Pathology, National Health Laboratory Service, University of the Witwatersrand, Johannesburg, South Africa.
Shukri F MohamedAfrican Population and Health Research Center, Nairobi, Kenya.
Lisa K MicklesfieldFaculty of Health Sciences, MRC/Wits Developmental Pathways for Health Research Unit, University of the Witwatersrand, Johannesburg, South Africa.
Palwendé Romuald BouaInstitut de Recherché en Sciences de la Santé, Clinical Research Unit of Nanoro, Clinical Research Unit of Nanoro, Burkina Faso.
Alisha N WadeFaculty of Health Sciences, MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Solomon S R ChomaFaculty of Health Sciences, Department of Pathology and Medical Science, DIMAMO, School of Health Care Sciences, University of Limpopo, Polokwane, South Africa.
Hermann SorghoInstitut de Recherché en Sciences de la Santé, Clinical Research Unit of Nanoro, Clinical Research Unit of Nanoro, Burkina Faso.
Isaac KissianganiAfrican Population and Health Research Center, Nairobi, Kenya.
Gershim AsikiAfrican Population and Health Research Center, Nairobi, Kenya.
Patrick AnsahNavrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana.
Abraham R OduroNavrongo Health Research Centre, Ghana Health Service, Navrongo, Ghana.
Shane A NorrisFaculty of Health Sciences, MRC/Wits Developmental Pathways for Health Research Unit, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0001-7124-3788
Stephen M TollmanFaculty of Health Sciences, MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
Frederick J RaalFaculty of Health Sciences, Department of Medicine, Division of Endocrinology & Metabolism, Carbohydrate & Lipid Metabolism Research Unit, Johannesburg Hospital, University of the Witwatersrand, Johannesburg, South Africa.ORCID https://orcid.org/0000-0002-9170-7938
Marianne AlbertsFaculty of Health Sciences, Department of Pathology and Medical Science, DIMAMO, School of Health Care Sciences, University of Limpopo, Polokwane, South Africa.
Michele RamsayFaculty of Health Sciences, Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, Johannesburg.
as members of AWI-Gen and the H3Africa Consortium

Funding

Shared Core: Biobanking, Bioinformatics and Data ManagementU54HG006938 · NHGRI · WITS HEALTH CONSORTIUM (PTY), LTD · PI RAMSAY, MICHELE MICHELE · 2012 to 2022
$12.2M
NHGRI NIH HHS U54 HG006938
6 · The paper itself

Abstract

introductionThe contribution of obesity phenotypes to dyslipidaemia in middle-aged adults from four sub-Saharan African (SSA) countries at different stages of the epidemiological transition has not been reported. We characterized lipid levels and investigated their relation with the growing burden of obesity in SSA countries.

methodsA cross-sectional study was conducted in Burkina Faso, Ghana, Kenya and South Africa. Participants were middle aged adults, 40-60 years old residing in the study sites for the past 10 years. Age-standardized prevalence and adjusted mean cholesterol, LDL-C, HDL-C, triglycerides and non-HDL-C were estimated using Poisson regression analyses and association of body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WTHR) with abnormal lipid fractions modeled using a random effects meta-analysis. Obesity phenotypes are defined as BMI ≥ 30 kg/m2, increased WC and increased waist-to-hip ratio.

resultsA sample of 10,700 participants, with 54.7% being women was studied. Southern and Eastern African sites recorded higher age-standardized prevalence of five lipid fractions then West African sites. Men had higher LDL-C (19% vs 8%) and lower HDL-C (35% vs 24%) while women had higher total cholesterol (15% vs 19%), triglycerides (9% vs 10%) and non-HDL-cholesterol (20% vs 26%). All lipid fractions were significantly associated with three obesity phenotypes. Approximately 72% of participants in the sample needed screening for dyslipidaemia with more men than women requiring screening.

conclusionObesity in all forms may drive a dyslipidaemia epidemic in SSA with men and transitioned societies at a higher risk. Targeted interventions to control the epidemic should focus on health promoting and improved access to screening services.

Indexed as

DyslipidemiasObesityAdultAfrica South of the SaharaBody Mass IndexCross-Sectional StudiesFemaleHumansMaleMiddle AgedPhenotypePrevalenceTriglyceridesWaist CircumferenceWaist-Hip RatioTriglycerides

Identifiers

PMID39883633
PMCPMC11781721

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.