Evidence map›Paper›PMID 39063413›Full record

ArticleInternational journal of environmental research and public health2024

Unmasking the Risk Factors Associated with Undiagnosed Diabetes and Prediabetes in Ghana: Insights from Cardiometabolic Risk (CarMeR) Study-APTI Project.

Thomas Hormenu, Iddrisu Salifu, Juliet Elikem Paku, Eric Awlime-Ableh, Ebenezer Oduro Antiri, Augustine Mac-Hubert Gabla, Rudolf Aaron Arthur, Benjamin Nyane, Samuel Amoah, Cecil Banson and 1 more

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

11 authors.

Thomas HormenuDepartment of Health, Physical Education and Recreation, Faculty of Science Technology Education, College of Education Studies, University of Cape Coast, Cape Coast 00233, Ghana.ORCID 0000-0002-9416-4406
Iddrisu SalifuCardiometabolic Epidemiology Research Laboratory, Department of Health, Physical Education and Recreation, University of Cape Coast, Cape Coast 00233, Ghana.ORCID 0000-0002-1605-5941
Juliet Elikem PakuDepartment of Health, Physical Education and Recreation, Faculty of Science Technology Education, College of Education Studies, University of Cape Coast, Cape Coast 00233, Ghana.
Eric Awlime-AblehDepartment of Health, Physical Education and Recreation, Faculty of Science Technology Education, College of Education Studies, University of Cape Coast, Cape Coast 00233, Ghana.
Ebenezer Oduro AntiriDepartment of Health, Physical Education and Recreation, Faculty of Science Technology Education, College of Education Studies, University of Cape Coast, Cape Coast 00233, Ghana.ORCID 0000-0001-8841-8628
Augustine Mac-Hubert GablaDepartment of Health, Physical Education and Recreation, Faculty of Science Technology Education, College of Education Studies, University of Cape Coast, Cape Coast 00233, Ghana.
Rudolf Aaron ArthurCardiometabolic Epidemiology Research Laboratory, Department of Health, Physical Education and Recreation, University of Cape Coast, Cape Coast 00233, Ghana.
Benjamin NyaneCardiometabolic Epidemiology Research Laboratory, Department of Health, Physical Education and Recreation, University of Cape Coast, Cape Coast 00233, Ghana.
Samuel AmoahDirectorate of University Health Services, University of Cape Coast, Cape Coast 00233, Ghana.
Cecil BansonDirectorate of University Health Services, University of Cape Coast, Cape Coast 00233, Ghana.
James Kojo PrahDirectorate of University Health Services, University of Cape Coast, Cape Coast 00233, Ghana.ORCID 0000-0001-7024-1123

Funding

African Academy of Sciences APTI-18-03
6 · The paper itself

Abstract

introductionUndiagnosed diabetes poses significant public health challenges in Ghana. Numerous factors may influence the prevalence of undiagnosed diabetes among adults, and therefore, using a model that takes into account the intricate network of these relationships should be considered. Our goal was to evaluate fasting plasma levels, a critical indicator of diabetes, and the associated direct and indirect associated or protective factors.

methodsThis research employed a cross-sectional survey to sample 1200 adults aged 25-70 years who perceived themselves as healthy and had not been previously diagnosed with diabetes from 13 indigenous communities within the Cape Coast Metropolis, Ghana. Diabetes was diagnosed based on the American Diabetes Association (ADA) criteria for fasting plasma glucose, and lipid profiles were determined using Mindray equipment (August 2022, China). A stepwise WHO questionnaire was used to collect data on sociodemographic and lifestyle variables. We analyzed the associations among the exogenous, mediating, and endogenous variables using a generalized structural equation model (GSEM).

resultsOverall, the prevalence of prediabetes and diabetes in the Cape Coast Metropolis was found to be 14.2% and 3.84%, respectively. In the sex domain, females had a higher prevalence of prediabetes (15.33%) and diabetes (5.15%) than males (12.62% and 1.24%, respectively). Rural areas had the highest prevalence, followed by peri-urban areas, whereas urban areas had the lowest prevalence. In the GSEM results, we found that body mass index (BMI), triglycerides (TG), systolic blood pressure (SBP), gamma-glutamyl transferase (GGT), and female sex were direct predictive factors for prediabetes and diabetes, based on fasting plasma glucose (FPG) levels. Indirect factors influencing diabetes and prediabetes through waist circumference (WC) included childhood overweight status, family history, age 35-55 and 56-70, and moderate and high socioeconomic status. High density lipoprotein (HDL) cholesterol, childhood overweight, low physical activity, female sex, moderate and high socioeconomic status, and market trading were also associated with high BMI, indirectly influencing prediabetes and diabetes. Total cholesterol, increased TG levels, WC, age, low physical activity, and rural dwellers were identified as indirectly associated factors with prediabetes and diabetes through SBP. Religion, male sex, and alcohol consumption were identified as predictive factors for GGT, indirectly influencing prediabetes and diabetes.

conclusionsDiabetes in indigenous communities is directly influenced by blood lipid, BMI, SBP, and alcohol levels. Childhood obesity, physical inactivity, sex, socioeconomic status, and family history could indirectly influence diabetes development. These findings offer valuable insights for policymakers and health-sector stakeholders, enabling them to understand the factors associated with diabetes development and implement necessary public health interventions and personalized care strategies for prevention and management in Ghana.

Indexed as

Diabetes MellitusPrediabetic StateAdultAgedBlood GlucoseCardiometabolic Risk FactorsCross-Sectional StudiesFemaleGhanaHumansMaleMiddle AgedPrevalenceRisk FactorsBlood Glucosefasting plasma glucosegeneralized structural equation modelGhanarisk factorsundiagnosed diabetes

Identifiers

PMID39063413
PMCPMC11276330

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.