Prevalence and determinants of metabolic syndrome: a cross-sectional survey of general medical outpatient clinics using National Cholesterol Expanded Program-Adult Treatment Panel III criteria in Botswana

Abstract

BackgroundLow- and middle-income countries, including Botswana, are facing rising prevalence of obesity and obesity-related cardiometabolic complications. Very little information is known about clustering of cardiovascular risk factors in the outpatient setting during routine visits. We aimed to assess the prevalence and identify the determinants of metabolic syndrome among the general outpatients’ attendances in Botswana.MethodsA cross-sectional study was conducted from August to October 2014 involving outpatients aged ≥20 years without diagnosis of diabetes mellitus. A precoded questionnaire was used to collect data on participants’ sociodemographics, risk factors, and anthropometric indices. Fasting blood samples were drawn and analyzed for glucose and lipid profile. Metabolic syndrome was assessed using National Cholesterol Education Program-Adult Treatment Panel III criteria.ResultsIn total, 291 participants were analyzed, of whom 216 (74.2%) were females. The mean age of the total population was 50.1 (±11) years. The overall prevalence of metabolic syndrome was 27.1% (n=79), with no significant difference between the sexes (female =29.6%, males =20%, P=0.11). A triad of central obesity, low high-density lipoprotein-cholesterol, and elevated blood pressure constituted the largest proportion (38 [13.1%]) of cases of metabolic syndrome, followed by a combination of low high-density lipoprotein, elevated triglycerides, central obesity, and elevated blood pressure, with 17 (5.8%) cases. Independent determinants of metabolic syndrome were antihypertensive use and increased waist circumference.ConclusionMetabolic syndrome is highly prevalent in the general medical outpatients clinics. Proactive approaches are needed to screen and manage cases targeting its most important predictors.

Association Between Food Insecurity and Key Metabolic Risk Factors for Diet-Sensitive Non-Communicable Diseases in Sub-Saharan Africa: A Systematic Review and Meta-Analysis

“…Of the two remaining studies, Gebremichael et al 41 (n = 1 of high quality, 86%) reported that the was no statistically significant association between hypertension and food insecurity exposure in adultsonly study participants. In contrast, Omech et al 45 (n = 1 of average quality, 71%) in adults-only study participants, found that although consumption of vegetables, fruit, and berries showed a protective effect on dyslipidaemia and obesity, it was not statistically significant; thus the association between dyslipidemia, obesity, and exposure to food insecurity was inconclusive.…”

“…39 The remaining six studies recruited participants from both rural and urban settings. [40][41][42][43][44][45] Overall, the studies selected for inclusion (n = 22 studies) involved a total of 26 609 participants, 12 453 (46.8%) participants were males, and one study recruited only women of reproductive age living in informal settlements in Accra, Ghana 29 . The distribution of the rest of the studies by countries was as follows: 4 from Ethiopia, 25,27,40,41 ; 1 Nigeria, 24 ; 1 Madagascar, 26 ; 3 Ghana, 29,38,39 ; 1 Zambia, 37 ; 2 Tanzania, 28,35 ; 1 Malawi, 34 ; 1 Cameroon, 33 ; 2 Sudan, 30,31 ; 1 Burkina Faso, 42 ; 1 Kenya, 32 ; 1 Botswana, 45 and 3 studies from South Africa 36,43,44 .…”

“…In this group of studies, a subset (n = 3 studies) involved designs where researchers measured food insecurity at the household level using the food insecurity access scale criterion. 32,37,40 Another subset (n = 9 studies) measured food insecurity at an individual level using the Minimum Adequate Diet criterion, 24,25,27,31,33,36,37,42,43 the Minimum Dietary Diversity criterion (n = 5 studies), 28,29,38,39,45 and the last subset (n = 4 studies) used more than one tool to gauge food insecurity. 30,37,44,45 While studies on children ≤ 5 years used the Minimum Meal Frequency criterion, 30 the Weight-for-height criterion, 34 and the Quetelet index 26 to ascertain food insecurity.…”

Association between Insomnia and Metabolic Syndrome in a Chinese Han Population: A Cross-sectional Study

“…Metabolic syndrome is one of the major pandemics that affect health across the globe 2 . The prevalence of metabolic syndrome is approximately 30% in the world 3 – 5 , and ranges from 7% to 32% in China 6 – 10 .…”

Caffeic acid reduces lipid accumulation and reactive oxygen species production in adipocytes

“…Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License systems, especially in industrialized countries and is associated with several other comorbidities, such as metabolic syndrome, hypertension, type-2 diabetes, dyslipidemia and cardiovascular risk, with significant morbidity and mortality (Bocco et al, 2016;Omech et al, 2016). Worldwide, at least 2.8 million people die each year as a result of being overweight or obese (Organization, 2016).…”