Evidence map›Paper›PMID 41078582›Full record

ArticleAJOG global reports2025

Metabolic syndrome in perimenopausal and postmenopausal women attending gynaecology outpatient department at a tertiary institution in South Africa.

Lawrence Marapo, Lineo Matsela, M E Chabalala, Olakunle Adewunmi Towobola

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Article in AJOG global reports, 2025. 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

4 authors.

Lawrence MarapoDepartment of Obstetrics and Gynecology, Sefako Makgatho University, Pretoria, Gauteng, South Africa.
Lineo MatselaDepartment of Obstetrics and Gynecology, Sefako Makgatho University, Pretoria, Gauteng, South Africa.
M E ChabalalaDepartment of Obstetrics and Gynecology, Sefako Makgatho University, Pretoria, Gauteng, South Africa.
Olakunle Adewunmi TowobolaDepartment of Internal Medicine and Clinical research, Sefako Makgatho University, Pretoria, Gauteng, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prevalence of metabolic syndrome in menopause varies globally. There is a paucity of data regarding knowledge of metabolic syndrome in menopause in South Africa. Objectives: The study was designed to describe the prevalence of metabolic syndrome in perimenopausal and postmenopausal and the lipid changes that occur during the menopause transition. Study Design: A prospective cross-sectional study was conducted at Dr George Mukhari Academic Hospital, the gynaecological outpatient department, Pretoria, South Africa. Perimenopausal and postmenopausal women were included. Six hundred ninety menopausal women were enrolled in this study. The participants were evaluated by physical examination. Blood samples were also taken for biochemical assay. The researcher also took their blood pressure. Data compiled from the study were analyzed using the Statistical Package for Social Sciences version 21. Descriptive statistical analysis established the range, mean (including 95% confidence interval), and standard deviation for quantitative variables. Categorical variables were analysed using Fisher's exact test, and risk analysis of factors associated with Metabolic syndrome was performed by calculating the odds ratio (OR) and its 95% confidence interval for both perimenopausal and postmenopausal women. A 2-tailed statistical analysis yielding a p-value <.05 was taken as statistically significant. Results: The study consisted of 690 women (n=690), including 338 perimenopausal women (n=338; 49.0%) and 352 postmenopausal women (n=352; 51.0%). The prevalence of metabolic syndrome was noted to be 47% and 61.4% in the perimenopausal and postmenopausal groups, respectively. The mean waist circumference was higher than the cut-off value of 88cm for perimenopausal and postmenopausal women. There were no statistically significant differences in lipid profiles between perimenopausal and postmenopausal women. The odds ratio for elevated triglycerides was 0.65 (95% CI: 0.32-1.01) and for low HDL levels was 0.83 (95% CI: 0.41-0.98). Perimenopausal women had significantly higher odds (OR 2.19, Conclusion: This study reflects the current high burden of metabolic syndrome amongst perimenopausal and postmenopausal women in South Africa. The prevalence of metabolic syndrome was noted to be higher in postmenopausal women as compared to perimenopausal women. There was a correlation between metabolic syndrome and age, sleep disorders, vasomotor symptoms, and dyslipidaemias.

Indexed as

dyslipidemiaglucosehormonal profilemetabolic syndromeoutpatient departmentperimenopausalpostmenopausal womenprevalencevasomotor symptomswaist circumference

Identifiers

PMID41078582
PMCPMC12514568

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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.