Evidence mapPaperPMID 39315263Full record

ArticleResearch square2024

Metabolic Syndrome and Its Component Factors Among Corporate Company Employees in Kampala Uganda.

Jemimah Kiboss Kyeyune, Zandile June-Rose Mchiza, Mwambi Bashir, Prossy Merab Ingabire, Florence Wamuyu Githinji, Florence Nakaggwa, Ivan Gabriel Busulwa, Rose Clarke Nanyonga

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Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Jemimah Kiboss KyeyuneClarke International University.
Zandile June-Rose MchizaSouth African Medical Research Council.
Mwambi BashirClarke International University.
Prossy Merab IngabireChina-Uganda Friendship Hospital Naguru.
Florence Wamuyu GithinjiClarke International University.
Florence NakaggwaClarke International University.
Ivan Gabriel BusulwaIGB Health Consulting.
Rose Clarke NanyongaClarke International University.

Funding

FIC NIH HHS R25 TW011213
6 · The paper itself

Abstract

Background: Metabolic syndrome (MetS), a cluster of metabolic dysregulations indicative of increased cardiometabolic risk is on the rise in Sub-Saharan Africa. The study aimed to determine the prevalence of MetS and its components, among corporate employees in Kampala, Uganda. Methods: A cross-sectional survey was undertaken among 408 adults who were employees from seven corporate companies in Kampala, using the WHO STEPwise NCD screening approach. Metabolic syndrome was measured using the National Cholesterol Education Program Adult Treatment Panel (ATPIII) and the International Diabetes Federation (IDF) criteria with the waist circumference (WC) cut-off points adapted for Sub-Saharan African populations. Results: The mean population age (standard deviation [SD]) of the respondents was 34years (± 8.87) years and 52% of them were females. The prevalence of MetS was 22.8% (NCEP ATPIII) and 28.4% (IDF). Of the respondents who did not have MetS, 75% had at least one metabolic dysregulation. Of those respondents with MetS, only 31% perceived that they were at risk of this cluster of metabolic dysregulations. In this analysis, we observed that the systolic blood pressure (BP) and the body mass index (BMI) correlated strongly (r = 0.81 and r = 0.71) with the diastolic BP and waist circumference (WC), respectively. Age on the other hand correlated fairly with the WC and BMI (both r values = 0.46). Principal component analysis showed that the greatest loadings in principle factors one, two and three were from central obesity, with low HDL-C explaining 60.8% variance in the population. Age, BMI, family history of having cardiometabolic disorders, and perceived cardiometabolic disease risk (CMR) were associated with an increased risk of MetS by 5, 8.86, 1.55, and 2.73 (all P values were < 0.05) respectively in this group of respondents. These risks remained for age, BMI and perceived CMR after removing the confounding effects of education status, marital status and family history of cardiometabolic disease. Being single on the other hand, was associated with a reduced risk of MetS (0.23, p < 0.009). Conclusion: While the primary contributors to the high prevalence of MetS among corporate employees in Kampala, Uganda were the high BP, high WC and high fasting blood sugar (FBS); age, BMI and perceived CMR were the key determinants of MetS. Future MetS interventions should aim to control and monitor obesity indicators in this population. Additionally, the findings inform targeted screening parameters for cardiometabolic risk assessment and suggest the need for further research into a weighted algorithm for MetS in this population.

Indexed as

corporate employeesfactor analysisMetabolic syndromeprincipal components

Identifiers

PMID39315263
PMCPMC11419266

What Socratic holds

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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.