Evidence map›Paper›PMID 30392446›Full record

ArticleGlobal health action2018

Determinants of body mass index by gender in the Dikgale Health and Demographic Surveillance System site, South Africa.

Felistas Mashinya, Marianne Alberts, Ian Cook, Sam Ntuli

Abstract read
In one paragraph

Article in Global health action, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Association Between Renal Dysfunction and Lipid Ratios in Rural Black South Africans.International journal of environmental research and public health · 2025
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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

4 authors.

Felistas Mashinyaa Faculty of Health Sciences , University of Limpopo , Polokwane , South Africa.ORCID 0000-0002-4132-7558
Marianne Albertsa Faculty of Health Sciences , University of Limpopo , Polokwane , South Africa.ORCID 0000-0002-7628-8560
Ian Cookb Faculty of Humanities , University of Limpopo , Polokwane , South Africa.ORCID 0000-0001-5098-2936
Sam Ntulia Faculty of Health Sciences , University of Limpopo , Polokwane , South Africa.

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

backgroundThe study was conducted in the Dikgale Health and Demographic Surveillance System (DHDSS) site where we have observed increasing obesity levels, particularly in women, despite evidence of high physical activity (PA) and a relatively low daily energy intake.

objectiveThis study aimed to assess the socio-demographic, behavioural and biological determinants of body mass index (BMI) in adult residents permanently residing in the DHDSS.

methodsA cross-sectional study was conducted in which socio-demographic, behavioural and biological characteristics from 1143 participants (aged 40-60 years) were collected using a paper questionnaire and standard anthropometric measures. Human immunodeficiency virus (HIV) testing was performed on all participants except those who indicated that they had tested positive. Chi-square and Mann-Whitney tests were used to analyze categorical and continuous variables, respectively, while hierarchical multivariate regression was used to analyze predictors of BMI.

resultsThe median age of women and men was 51 (46-56) and 50 (45-55) years, respectively. The prevalence of overweight-obesity was 76% in women and 21% in men. A significant negative association of BMI with HIV and smoking and a significant positive association with socio-economic status (SES) was observed in both sexes. In women, BMI was negatively associated with sleep duration (p = 0.015) and age (p = 0.012), but positively associated with sugar-sweetened beverages (SSBs) (p = 0.08). In men, BMI was negatively associated with alcohol use (p = 0.016) and positively associated with being married (p < 0.001). PA was not associated with BMI in either sexes. Full models explained 9.2% and 20% of the variance in BMI in women and men, respectively.

conclusionBMI in DHDSS adults is not associated with physical inactivity but is associated wealth, marital status, sleep, smoking, alcohol use, and HIV status. Future studies should explore the contribution of nutrition, stunting, psycho-social and genetic factors to overweight and obesity in DHDSS.

Indexed as

Body Mass IndexSex FactorsSocial ClassAdolescentAdultAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMiddle AgedObesityOverweightPopulation SurveillancePrevalenceBMI distribution across African communitiesBody mass indexhierarchical modellingolder adultsrural

Identifiers

PMID30392446
PMCPMC6225484

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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 OpenQuestion graph.