Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 https://doi.org/10.1186/s12872-022-02805-4 RESEARCH Open Access Determinants of metabolic syndrome among patients attending diabetes clinics in two sub-urban hospitals: Bono Region, Ghana Timothy Agandah Abagre1, Delia Akosua Bandoh2 and Adolphina Addoley Addo‑Lartey1* Abstract Background: Over 70% of individuals with type 2 diabetes mellitus (T2DM) may have metabolic syndrome in sub‑ Saharan Africa. Evidence about the prevalence, clustering, and determinants of metabolic syndrome components is needed to guide the implementation of interventions to prevent cardiovascular diseases in low‑income countries. Methods: A clinic‑based cross‑sectional study was conducted among 430 out‑patients attending two‑selected diabetes mellitus clinics in the Bono Region of Ghana. Data was collected in June 2016 among participants aged 30–79 years. The prevalence of metabolic syndrome was assessed using the harmonized definition. Patients were interviewed using semi‑structured questionnaires and T2DM status was confirmed by reviewing medical records. The components of MS that were assessed included body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, triglycerides, high‑density lipoprotein (HDL)‑cholesterol, and blood glucose. Multiple logistic regression models were constructed to evaluate the risk factors of MS. Results: The mean age of participants was 58.8 ± 11.49 years. The prevalence of MS was 68.6% (95% CI: 64.0–72.8), higher among women (76.3%, 95% CI: 70.6–81.2) than men (58.0%, 95% CI: 35.0–49.4) and in the 50–59‑year age group (32.1%). The majority of participants [248 (57.7%)] had either two [124 (28.8%)] or four [124 (28.8%)] compo‑ nents of MS. Excluding fasting blood glucose (78.4%), the predominant components of MS identified in the study were reduced HDL cholesterol (70.2%), high waist circumference (60.9%), and elevated systolic blood pressure (49.8%). The study found that the odds of MS in women are 2.2‑fold higher than in men (95% CI: 1.29–3.58, p = 0.003). Dura‑ tion of T2DM (OR 5.2, 95% CI: 2.90–9.31, p < 0.001) and overweight status (OR 6.1, 95% CI: 3.70–10.07 p < 0.001) were also found to be significant determinants of MS. Conclusions: Metabolic syndrome was common among patients attending routine diabetes mellitus clinics in sub‑urban hospitals in the middle belt of Ghana. Significant factors associated with metabolic syndrome included being female, living with diabetes for more than five years, and being overweight. Nationwide advocacy for routine screening and prevention of the syndrome should be initiated to prevent cardiovascular disease and mortality in this vulnerable population. Keywords: Type 2 diabetes, Insulin resistance, Metabolic syndrome, Out‑patients, Ghana Background *Correspondence: aaddo‑lartey@ug.edu.gh Metabolic syndrome (MS) is a pathologic state charac- 1 terized by the clustering of metabolic abnormalities [1]. Department of Epidemiology and Disease Control, School of Public Health, College of Health Sciences, University of Ghana, P. O. Box LG 13, Legon, Accra, Metabolic syndrome is known by many names includ- Ghana ing, syndrome X, insulin resistance syndrome, the deadly Full list of author information is available at the end of the article © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom‑ mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 2 of 13 quartet, the metabolic cardiovascular syndrome, or the avoiding smoking [25]. Dietary concepts such as the atherothrombogenic syndrome [2, 3]. The syndrome Mediterranean and Dietary Approaches to Stop Hyper- (MS) occurs when a person has a combination of any tension have also been shown to have protective effects three or more of the following metabolic factors: raised on MS [26–30]. blood glucose or diabetes, high blood pressure, obesity, International guidelines for the clinical diagnoses and elevated triglycerides, and low levels of HDL cholesterol. management of MS have been recommended [31, 32]. Global estimates indicate that about a third of the At present, there are no standard treatment guidelines population in every country is affected by MS with pre- for MS in Ghana. This is perhaps the case because of dictions of a worldwide increase, primarily in develop- the dearth of data to support the burden of the con- ing countries [1]. Kalk and Joffe reported that 47% of dition in the country. Further, the lack of a uniform Africans with type 2 diabetes mellitus (T2DM) in South approach for classifying MS has made it problem- Africa may be affected by MS [4]. Ipadeola and Adeleye atic when comparing prevalence data across studies. have also reported an MS prevalence of over 66% among Accordingly, the implications of the information on the patients with T2DM in Ibadan, Nigeria [5]. In Ghana, up burden and associated risk factors of MS depend on the to 58% of people with T2DM in metropolitan areas may method used. To address the inconsistencies in meth- have the syndrome [6]. These estimates are of importance ods, a group of experts has proposed a harmonized def- because MS is linked to heart diseases, stroke, and other inition for classifying MS [18]. conditions affecting the blood vessels [7–10]. In adverse In Ghana, most studies on MS among people with conditions, the risk of developing cardiovascular diseases T2DM have been conducted using either the Interna- (CVD) and mortality in people with MS is two to three tional Diabetes Federation (IDF) or the National Cho- times higher than in those without the syndrome [1, 7, 9]. lesterol Education Program’s Adult Treatment Panel III The concept of MS has existed for many decades albeit (NCEP: ATP III) definitions [6, 22, 33]. The majority of with controversies regarding its pathogeneses. Whiles these studies have been conducted in teaching hospi- some have associated it with obesity as a result of cen- tals in metropolitan areas in the northern or southern tral adipose tissue [11, 12], others have linked it to insulin regions of Ghana, but less so in sub-urban areas in the resistance [13, 14]. In one review, it was suggested that middle-belt regions of the country. This study used the elevated plasma-free fatty acids in obese subjects induced new harmonized criterion to investigate the prevalence, insulin resistance [15]; an effect known to elicit the devel- distribution of MS components, and associated risk opment of MS factors [13]. Excess dietary energy has factors among people attending diabetes mellitus clin- also been implicated in MS pathogenesis [16]. Alema- ics in two-selected sub-urban district hospitals in the ny’s review analyzed the contribution of adipose tissue Bono Region of Ghana. inflammation to the development of MS and concluded that excess dietary energy (largely fat), elicits insulin resistance, thus creating the problem of excess accumula- Methods and materials tion of fat in body cells [16]. Study design Despite the diverse schools of thought about the The study was an analytical cross-sectional study pathogenesis of MS, it appears there is a general leaning involving routine diabetes mellitus clinic attendants towards central obesity as the biggest cause of the syn- to determine the prevalence and determinants of MS. drome brought in part by the global rise of obesity, con- Study participants were adult out-patients with known sumption of high-energy diets, and sedentary lifestyle diagnoses of T2DM. Enrolment of participants was [17, 18]. Furthermore, increased age [19, 20], as well as done on clinic days when patients attend for care. Data being female have been identified as risk factors in the on individual characteristics and exposure to risk fac- clustering of MS among individuals with diabetes [21, tors were collected alongside information about the 22]. outcome of interest (MS). While there are pharmacological approaches for the Cochrane’s formula ( ss z2 2= ∗ p(1− p)/d ) was used treatment of MS components [23, 24], lifestyle changes to calculate the sample size needed to determine the are the preferred and sustainable approaches to treat- prevalence of MS at a 95% confidence interval (z) and ing MS [13]. Lifestyle change involves managing all the 0.05 precision (d). Assuming a p of 0.58 (58% preva- components in one approach through modifications to lence of MS among people with T2DM) [6], the mini- personal lifestyle without the use of drugs. The lifestyle mum required sample size for this study was calculated approach involves dietary and physical activity modi- to be 379. To cater for nonresponse and/or incomplete fications, weight management, limiting alcohol, and questionnaires, an additional 15% was added to give an estimated sample size of 436 participants. A bagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 3 of 13 Study setting hypogonadism, hypothyroidism, acromegaly, and any Dormaa Presbyterian and Berekum Holy Family Hospi- other chronic diseases were not selected for the study. tals are district hospitals located in the Bono Region of Patients on prolonged steroid use and those who were Ghana. Both hospitals provide secondary level care ser- on active drug treatment for obesity at the time of the vices and serve as referral care facilities for cases requir- study and critically ill participants, including those with ing specialist care from primary health facilities. The two self-reported cardiac problems and amputees, were also hospitals also provide out- and in-patient services. The excluded from the study. average weekly attendance at the Diabetes Mellitus clinic at Dormaa Presbyterian Hospital is 140 patients, while Data collection that at the Berekum Holy Family Hospital is 110 patients. Data collection was carried out from May to June 2016. The selection of hospitals for this study was based on The diabetes status of each participant was confirmed the following criteria: (i) That the hospital(s) was a dis- with medical records before data collection. Face-to-face trict or municipal hospital not located in the regional interviews were conducted using semi-structured ques- capital, Sunyani; (ii) That the hospital(s) had a diabetes tionnaires to collect participants’ socio-demographic clinic with monthly attendance greater than the esti- information, including age, sex, educational attainment, mated sample size of 436; (iii) That the hospital(s) had a marital status, occupation, and duration of T2DM. Infor- functioning accredited clinical biochemical laboratory. mation on participants’ lifestyle factors such as engage- ment in physical activity, alcohol consumption, and Participants’ recruitment dietary habits was obtained through interviews using Participants in Dormaa Presbyterian and Berekum Holy an adapted semi-quantitative Fenland Food Frequency Family Hospitals were recruited on a ratio of 5:4 respec- questionnaire [35]. We also conducted physical measure- tively based on the average weekly clinic attendance. ments to determine participants’ BMI, WC, and blood Consequently, 56% (249) and 44% (195) participants were pressure. randomly selected for the study at Dormaa and Berekum Blood samples of participants were collected from the Hospitals respectively. All T2DM patients attending the laboratories of the respective participating hospitals as hospital’s diabetes clinic for care during the study period part of the routine services that diabetes mellitus patients were considered eligible for participation in the survey. A undergo monthly. Each participant’s blood sample was list of all T2DM clinic attendants was made and a con- collected between 7:00 and 9:00 AM after 12–14  h of secutive number from 1 to n (number of clinic attend- overnight fasting. A sterile single-use syringe and nee- ants for a specific day) was assigned to each attendant on dle set were used to draw blood from each participant’s the list. Using a random number generator on Microsoft antecubital fossa. In addition to practicing hand hygiene, Office excel 2013, a set of random numbers equal to n1 laboratory personnel wore fitting non-sterile gloves dur- (sub-sample size for the particular clinic, on a specific ing blood sample collection. About 5 ml of venous blood day) was generated. The generated random numbers was drawn from each study participant and dispensed in were then used to select the participants from the list of serum separator tubes with gel and temporally stored in attendants. These steps were repeated at each hospital styrofoam boxes without cold packs but protected from until the sample size was attained. sunlight. The collected blood samples were subsequently centrifuged at 1000  rpm before being analyzed within 24 h after collection. In both Dormaa and Berekum, fast- Inclusion and exclusion criteria Participants were included in the study if they were 30 to ing blood glucose, triglycerides, and HDL-cholesterol 79 years of age with clinical diagnoses of T2DM accord- levels were assayed enzymatically from blood plasma ing to WHO criteria [34] regardless of the duration of using Mindray BS-120 automated chemical analyzer. illness. All study participants were apparently healthy adults including those on treatment for hypertension and Quality control diabetes. We included only participants whose diabetes Data collection was carried out by trained health per- status had been confirmed by a physician and there was sonnel and entered into pre-defined forms. In addition, information on the patient’s hospital records to confirm blood samples were collected and analyzed by qualified the diagnosis. Only those who had consented and were laboratory technicians using standard operating proce- available to participate were included in the research. dures. To ensure the accuracy of data and measurements, Pregnant or lactating mothers were excluded from all the pieces of equipment, including weighing scales, the study. Also, participants with type 1 diabetes mel- stadiometers, blood pressure monitors, and blood ana- litus, history of heart failure, myocardial infarction, lyzers were calibrated in accordance with manufactur- ers’ instructions before data collection. Also, to ensure Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 4 of 13 that blood samples were correctly matched to the results, and/or diastolic ≥ 85 mm Hg; and elevated fasting glu- serum separator tubes were labeled with unique partici- cose ≥ 100 mg/dL (or treatment of elevated glucose). pant identification numbers. Variables Statistical analysis The independent variables in this study were the socio- Data analysis was done using Stata version 13.1. This demographic and lifestyle factors, while the outcome study had a response rate of 96.8%. The mean and variable was MS. Noting that MS results from the clus- standard deviation was used to describe continuous tering of three or more MS components, we determined variables such as age, waist circumference, blood glu- that the MS components BMI, WC, FBG, BP, TG, and cose, blood pressure, high-density lipoprotein choles- HDL-cholesterol constituted the intermediary variables. terol, and triglycerides. Discrete variables such as the All the variables were measured as binary or categorical sex- and age-specific prevalence of MS and its com- variables. ponents were presented as proportions and 95% con- fidence intervals (CI). We performed the chi-square Measurements test on categorical variables to test the association A total of 444 respondents were interviewed; how- between potential risk factors and MS. For continuous ever, laboratory, physical and medical information variables, the Students t-test or Wilcoxon rank-sum test were obtained for 430 participants. Most of the partici- was used in assessing the difference in mean measure- pants 426 (99.1%) were undergoing treatment for only ments between men and women and by the MS status. T2DM, while 4(0.9%) of them were on medication for Two logistic regression models were performed to test both T2DM and hypertension. To ensure standardiza- the strength of association between risk factors and tion of interviews and measurements, two registered MS. Despite the fact that hypertension is one of the nurses were trained on questionnaire administration, confounding factors for the development of MS, we data extraction, and using measurement tools. Partici- did not stratify our analyses based on the presence or pants’ heights and weights were measured using the Seca absence of diabetes and hypertension or exclude those weighing scale and stadiometer respectively. A simple with hypertension from the analyses. This was due to tape measure calibrated in meters to the nearest centime- the fact that the study only included four individuals ter was used to measure waist circumference on the bare from the Dormaa Presbyterian Hospital who had just skin at the end of normal gentle respiration. Participants received a diagnosis of hypertension and were being were required to wear light clothing and without shoes treated for both it and T2DM. Because they had only during physical measurements. Measurement of waist obtained a diagnosis during the month prior to the data circumference was taken at the narrowest indentation collection and because their numbers were deemed midway between the lowest rib and the iliac- crest. insufficient to significantly affect the study’s conclu- The average of two blood pressure readings was taken sions, they were recruited into the study and included after five minutes apart using Omron electronic blood in all analyses. Simple logistic regressions were carried pressure monitor. Measurements were taken in the sit- out to test the crude relationships between exposures ting position after participants have had at least 15 min and MS. Multiple logistic regression analyses were then of rest. Participants’ blood samples were also collected used to evaluate the adjusted relationship between risk and tested for glucose, triglycerides, and HDL-choles- factors and MS. Statistical significance was assumed if terol level after which the results were documented in the p-values were < 0.05. questionnaires. Classification of metabolic syndrome Ethical considerations Metabolic syndrome (MS) was defined according to Ethical clearance for the study was obtained from the the new harmonized definition [18]. Based on this cri- Ghana Health Service Ethical Review Committee (GHS- terion, a person has MS if s/he has three or more of ERC: 08/12/15). Permission was also sought from the the following: elevated waist circumference of > 94  cm hospital authorities at Dormaa Presbyterian Hospital and for men or > 88  cm for women; elevated triglycerides Berekum Holy Family Hospital respectively. Informed (or treatment for elevated triglycerides) ≥ 150  mg/dL consent was delivered verbally and respondents were (1.7  mmol/L); reduced HDL-cholesterol (or treatment asked to sign or thumb-print the informed consent if for reduced HDL) < 40  mg/dL (1.0  mmol/L) in males they agreed to be enrolled in our study. All methods were and < 50 mg/dL (1.3 mmol/L) in females; elevated blood performed in agreement with the relevant guidelines and pressure (or history of hypertension)—systolic ≥ 130 regulations. A bagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 5 of 13 Results of the syndrome was higher among women [190 (76.3%)] Demographic, anthropometric, and biochemical than men [105 (58.0%)], p < 0.001 (Table 1). MS was also characteristics of participants more prevalent among unmarried (divorced, separated, This analysis involved 430 people with T2DM of whom or never married) respondents [112 (76.7%)] than mar- 249 (57.9%) were women (Table 1). The majority of par- ried participants [183 (64.4%)], p = 0.009. The prevalence ticipants 426 (99.1%) had only T2DM as the main diag- of MS increased from 5.6% in the 30–39-year age group nosis, while 4(0.9%) had both T2DM and hypertension. to 14.0% in the 40–49 years age group and peaked in the There were more married (66.0%) participants than 50–59-year age group (32.1%) before declining to 22.1% divorced, separated, or never married (34.0%) partici- in the 70–79-year age group. The relationship between pants. Farming was the main occupation for 258 (60.0%) respondent age group, occupation, or education, and MS of participants. Those who were formally employed were was not significant (p > 0.05) (Table 1). The mean age of 27 (6.3%), while 66 (15.4%) were unemployed or retired. participants was not different between participants with The rest of the participants were traders, carpenters, or MS and those without MS (p = 0.716). construction workers. Most participants [383 (89.1%)] in Participants who had lived with T2DM for five or more this study had less than senior high school education. The years had a higher prevalence of MS [139 (85.3%), 95% age of respondents ranged from 30 to 79 years with the CI: 78.9–90.0] than their counterparts who had lived majority [138 (32.1%)] of participants in the 50–59 years with the condition for less than five years [156 (58.4%), age category, while the minority [24 (5.6%)] of them were 95% CI: 52.4–64.2], p < 0.001. The difference in the mean in the 30–29 years age group. duration of T2DM between participants with MS and On lifestyle-related factors, 21 (4.8%) of participants those without MS was present in significant, p < 0.001 reported that they consumed any type of alcohol once (Table  3). Among participants with a family history of or less than once weekly, while the rest 409 (96.1%) T2DM, MS was observed in 214 individuals (69.9% CI: reported that they did not consume any type of alcohol. 64.5–74.8), while for those without a family history of Participants who engaged in moderate to vigorous physi- diabetes, MS was common in 81 persons (65.3%, 95% CI: cal activity at least 3 times per week were 98 (22.8%). The 56.2–73.3), p = 0.351. participants who reported that they consumed fruits daily were 22 (5.1%), while 82 (19.1%) reported consum- Clustering of metabolic syndrome components ing vegetables (except tomatoes) daily. Participants who The majority of participants [248 (57.7%)] had either reported consuming oil-cooked foods such as fried foods two [124 (28.8%)] or four [124 (28.8%)] components of and stews four to six times a week were 64 (14.8%). MS (Table  3). A total of 16 participants (3.7%) had one Table  2 shows the mean anthropometric and bio- MS component, while 116 (26.9%) had three MS com- chemical measurement of participants by sex and meta- ponents. Those who had the maximum of five MS com- bolic syndrome status. The mean age of participants ponents were [50 (11.6%)]. Besides FBG, the top three was 58.84 ± 11.49  years. Men had a higher mean age predominant MS components were reduced HDL-cho- (60.39 ± 11.46  years) than women (57.71 ± 11.40  years), lesterol [302 (70.2%)], elevated waist circumference [262 p = 0.015 (Table  2). All participants had previous diag- (60.9%)] and high SBP [214 (49.8%)]. Reduced HDL- noses of T2DM with an average disease duration of cholesterol (46.3%) high SBP (22.1%) and elevated WC 5.30 ± 3.84  years. The mean BMI of participants was (17.4%) were the most frequently occurring MS com- 25.76 ± 4.74  kg/m2. The six MS components measured ponents among men. In women, elevated WC (43.5%), in this study were WC, SBP, DBP, triglycerides, HDL, reduced HDL-cholesterol (42.6%) and high SBP (27.7%) and blood glucose. Except for triglyceride levels, there were the three predominant components. were no sex differences in the mean measurements of the remaining MS component. Men had higher mean Determinants of metabolic syndrome triglyceride level (127.12 ± 50.28  mg/dl) than women In the crude logistic regression analyses, factors such as (143.08 ± 57.24  mg/dl), p = 0.004. Between participants sex, marital status, duration of T2DM, overweight/obe- with MS and those without MS, the difference in mean sity, and being a trader were found to be associated with measurements for each component of MS was significant MS to varying extents (Table 4). The crude analysis indi- for all the components (p < 0.001) except FBG (p = 0.400). cated that the odds of MS were 2.3 times higher among women than men (95% CI: 1.53- 3.53), p < 0.001. Unmar- ried participants had 1.8 times the odds of MS compared Prevalence of metabolic syndrome with married participants (95% CI: 1.15–2.86), p < 0.001. Metabolic syndrome was present in 295 (68.6%) of par- Participants who had lived with T2DM for five or more ticipants (95% CI: 64.0 -72.8) (Table  3). The prevalence years were 4.1 times as likely to have MS compared with Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 6 of 13 Table 1 Characteristics of study participants and prevalence of MS Participants (N = 430) Metabolic syndrome (N = 295) Parameter N % Prevalence % 95% C.I p-value Sex < 0.000 Men 181 42.1 105 42.0 35.0–49.4 Women 249 57.9 190 76.3 70.6–81.2 Marital status 0.009 Married 284 66.0 183 64.4 58.7–69.8 Divorce/Not married 146 34.0 112 76.7 69.1–82.9 Age categories 0.697 30–39 24 5.6 16 66.7 44.5–83.3 40–49 60 14.0 46 76.7 64.0–85.9 50–59 138 32.1 93 67.4 59.0–74.8 60–69 113 26.3 75 66.7 57.0–74.6 70–79 95 22.1 65 68.4 58.2–77.1 Occupation 0.212 Farmers 258 60 173 67.1 61.0–72.6 Traders 64 14.9 52 81.3 69.5–89.2 Office‑related 27 6.3 17 63.0 42.5–79.7 Unemployed 66 15.3 43 65.2 52.6–75.9 Other 15 3.5 10 66.7 37.2–87.1 BMI Normal/underweight 207 48.1 106 51.2 44.4–55.6 < 0.001 Overweight/Obesity 223 51.9 189 84.8 79.4–88.9 Educational status 0.679 Less than SHS education 383 89.1 264 68.9 64.1–73.4 SHS or higher 47 10.9 31 66.0 50.9–78.4 Family history of T2DM Yes 306 71.2 214 69.9 64.5–74.8 0.351 No 124 28.8 81 65.3 56.2–73.3 Duration of T2DM < 0.001 Less than 5 years 267 62.1 156 58.4 52.4–64.2 5 years and above 163 37.9 139 85.3 78.9–90.0 Physical activity 0.153 Three or more times/week 98 22.8 73 74.5 64.8–82.3 Less than three times/week 332 77.2 222 66.9 61.6–71.7 Fruits 0.368 Daily 22 5.1 14 63.6 42.2–80.7 Not daily 408 94.9 281 68.9 64.2–73.2 Vegetables (excludes tomatoes) 0.946 Daily 82 19.1 56 68.3 57.3–77.6 Not daily 348 80.9 239 68.7 63.6–73.4 Oil‑cooked foods Daily 64 14.9 48 75.0 63.0–84.1 0.254 Not daily 366 85.1 247 67.5 62.5–72.1 Alcohol consumption At least occasionally 21 4.9 13 61.9 40.2–78.7 0.498 Don’t drink 409 96.1 282 68.5 64.2–73.3 Total 430 100.0 295 68.6 64.2–72.8 SHS Senior High School Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 7 of 13 Table 2 Mean physical and biochemical measurement of participants by sex and metabolic syndrome Total Male Female P-value MS Present MS Absent P-value Parameter Mean ± SD Mean ± SD Mean ± SD Age (years) 58.84 ± 11.49 60.39 ± 11.46 57.71 ± 11.40 0.015 58.71 ± 11.50 59.14 ± 11.50 0.716 Duration of T2DM (years) 5.30 ± 3.84 5.12 ± 3.42 5.41 ± 4.11 0.973 5.79 ± 3.92 4.22 ± 3.43 < 0.001 BMI (kg/m2) 25.76 ± 4.74 25.60 ± 4.17 25.87 ± 5.11 0.573 26.99 ± 4.69 23.06 ± 3.60 < 0.001 WC (cm) 91.37 ± 11.34 91.86 ± 10.23 91.02 ± 12.11 0.447 94.83 ± 10.50 83.82 ± 9.31 < 0.001 SBP (mm/Hg) 134.06 ± 20.35 134.54 ± 21.02 133.72 ± 19.87 0.674 138.94 ± 20.42 123.40 ± 15.61 < 0.001 DBP (mm/Hg) 82.48 ± 10.72 82.27 ± 10.51 82.63 ± 10.89 0.729 84.85 ± 10.75 77.30 ± 8.68 < 0.001 TG (mg/dL) 136.36 ± 54.92 127.12 ± 50.28 143.08 ± 57.24 0.004 148.52 ± 58.36 107.60 ± 31.17 < 0.001 HDL (mg/dL) 35.87 ± 15.41 34.31 ± 15.13 37.01 ± 15.54 0.061 33.20 ± 1438 41.71 ± 16.00 < 0.001 FBG (mg/dL) 137.97 ± 54.22 135.69 ± 54.43 139.62 ± 54.11 0.385 139.97 ± 52.31 134.71 ± 58.23 0.400 WC Waist circumference, SBP Systolic Blood Pressure, DBP Diastolic Blood Pressure, TG Triglycerides, HDL High-density lipoprotein, FBG Fasting Blood Glucose Table 3 Clustering of metabolic syndrome components among participants Type/No. of MS components Male (No.) % (95% CI) Female (No.) % (95% CI) Total (No.) % (95% CI) MS component High TG 44 24.3 (18.6–31.2) 95 38.2 (32.3–44.4) 139 32.3 (28.1–36.9) High DBP 65 35.9 (29.2–43.2) 91 36.5 (30.8–42.8) 156 36.3 (31.9–41.0) High SBP 95 52.5 (45.1–59.7) 119 47.8 (41.6–54.0) 214 49.8 (45.0–54.5) Elevated WC 75 41.1 (34.4–48.8) 187 75.1 (69.3–80.1) 262 60.9 (56.2–65.4) Elevated FBG 138 76.2 (69.4–81.9) 199 79.9 (74.4–84.5) 337 78.4 (74.2–82.0) Low HDL 119 65.4 (58.5–72.4) 183 73.5 (67.6–78.6) 302 70.2 (65.7–74.4) Obese/overweight 92 50.8 (43.5–58.1) 137 55.0 (48.8–61.1) 229 53.3 (48.5–57.9) No. of components present 1 5 2.8 (1.1–6.5) 11 4.4 (2.4–7.8) 16 3.7 (2.2–6.0) 2 74 40.9 (33.9–48.3) 50 20.1 (15.5–25.6) 124 28.8 (24.7–33.3) 3 53 29.3 (23.1–36.4) 63 25.3 (20.3–31.1) 116 26.9 (23.0–31.4) 4 38 21.0 (15.6–27.6) 86 34.5 (28.9–40.7) 124 28.8 (24.7–33.3) 5 11 6.1 (3.4–10.7) 39 15.7 (11.6–20.8) 50 11.6 (8.9–15.0) ≥ 3 (MS) 105 42.0 (35.0–49.4) 190 76.3 (70.6–81.2) 295 68.6 (64–0‑0.72.8) participants who had lived with MS for less than five respondents who had had T2DM for 5 or more years was years (95% CI 2.51–6.77, p < 0.001). Overweight/obese 5.2 times compared to those with a disease duration of participants were also more likely to have MS than nor- lesser than 5 years (95% CI: 2.90–9.31, p < 0.001). mal or underweight participants [crude OR: 5.5 (95% CI: 1.15–2.86, p < 0.001)]. Compared with farmers, respond- Discussion ents who were traders had 2.1 times the odds of having This study assessed the prevalence and risk factors of MS MS (95% CI: 1.08–4.20, p = 0.029). among people attending diabetes mellitus clinics using In the multiple logistic regression model, all the expo- the harmonized criterion. MS was defined as the pres- sures in the simple logistic regression model were con- ence of at least any three abnormal MS components. The trolled for each other as potential confounders. The results indicate that MS is a common occurrence (68.6%) adjusted results showed that sex, duration of T2DM, among people with T2DM who attend routine clinics in and overweight/obesity were associated with the odds suburban hospitals in the middle-belt region of Ghana. of developing MS (Table 4). The odds of developing MS The prevalence of MS was much higher in this study than among women were 2.15 times that of men (95% CI: in the earlier studies conducted in other parts of Ghana. 1.29–3.58, p < 0.003). Compared with normal or under- For instance, using the NCEP: APT III definition, Titty weight participants, overweight/obese participants (2010) conducted a prospected study among 240 patients were more likely to have MS [adjusted OR: 6.1 (95% recently diagnosed with diabetes mellitus in the Tamale CI: 3.70–10.07, p < 0.001)]. The adjusted odds of MS in Teaching Hospital and found that MS was present in Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 8 of 13 Table 4 Factors associated with MS among people with T2DM Simple logistic regression Multiple logistic regression Parameter Crude OR 95% CI p-value Adjusted OR 95% CI p-value Sex Men Reference Reference Women 2.33 1.53–3.53 < 0.001 2.15 1.29–3.58 0.003 Duration of T2DM Less than 5 years Reference Reference More than 5 Year 4.12 2.51–6.77 < 0.001 5.20 2.90–9.31 < 0.001 Obesity status Obesity statusNot overweight/obese Reference Reference Obesity statusOverweight/obese 5.49 3.49–8.64 < 0.001 6.10 3.70–10.07 < 0.001 Age (years) Age (years)30–39 Reference 40–49 1.64 0.58–4.64 0.349 50–59 1.03 0.41–2.59 0.944 60–69 0.99 0.39–2.51 0.978 70–79 1.08 0.42–2.81 0.869 Marital status Married Reference Unmarried 1.82 1.15–2.86 0.010 Education Less than secondary Reference Secondary and higher 0.87 0.46–1.66 0.679 Occupation Farmers Reference Traders 2.13 1.08–4.20 0.029 Office‑related 0.84 0.37–1.90 0.668 Unemployed/pensioner 0.92 0.51–1.62 0.770 Other 0.98 0.33–2.97 0.975 Family history of T2DM No Reference Yes 1.24 0.79–1.92 0.351 Physical activity 3 or more times/week Reference Less than 3 times per week 1.45 0.87–2.41 0.154 Fruit consumption Daily Reference Not daily 1.26 0.52–3.09 0.607 Vegetable consumption Daily Reference Not daily 1.02 0 .61–1.71 0.946 Eating oil-cooked food Not daily Reference Daily 1.44 0.79–2.65 0.234 In the adjusted analyses, sex, duration of T2DM, and Obesity status are each adjusted for all the other covariates in the simple logistic regression analyses 43.3% of the cohort [33]. In another study at the Komfo ATP III definition of MS and reported an MS preva- Anokye Teaching Hospital in Kumasi, Nisiah et al. (2015) lence of 58.0% among 150 participants with T2DM [33]. conducted a cross-sectional study using the NCEP: Although the harmonized and NCEP: ATP III definitions Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 9 of 13 of MS are similar, there is a key difference in terms of the our findings could be attributed to ethnic and/or geo- cut-off points for elevated fasting blood glucose and high graphic differences. blood pressure. These cut-offs (being slightly lower in the Analysis of the risk factors of MS in this present study Harmonized definition), might explain the higher preva- revealed sex differences in the prevalence of MS. It was lence of MS recorded in our study. In contrast, Mogre observed that women were more likely to be diagnosed et  al. (2014) recruited 200 participants with T2DM for with MS than men. This finding is in agreement with the a cross-sectional study at the Tamale Teaching Hospital observations from several studies conducted in Ghana [6, and found that the prevalence of MS was 24.0% among 22, 33]; other parts of Africa [4, 5]; and elsewhere [9, 43]. participants using the IDF definition [22]. The prevalence However, one study conducted in India reported higher of MS in the Mogre et al. study might have been under- odds of MS in men compared with women [44]. The estimated given that the investigators excluded triglycer- higher odds of MS among women than in men observed ides and HDL-cholesterol components in their diagnosis in this present study could be attributed to a higher of MS. prevalence of obesity in women than in men. This is sup- The prevalence of MS in this study was also found to ported by evidence from several studies that have linked differ from those of studies conducted in other Afri- obesity to MS [45–47]. Other studies have linked differ- can countries. In one cross-sectional study among 254 ential clustering of metabolic factors in women and men patients with T2DM in a teaching hospital in Nigeria, to hormonal changes in adulthood [48], and the influence the prevalence of MS defined by the WHO criterion of genetic backgrounds, diet, level of physical activity, was reported in 59.0% of participants [36]. In South and under or over-nutrition [38]. Africa, using the IDF definition, MS prevalence of 46.5% Another important risk factor of MS that was identi- and 74.1% were reported among black and white South fied in this study was the duration of T2DM. The find- African patients with T2DM respectively [4]. Ipadeola ings of this study reveal that living with T2DM for more & Adeleye (2015) also conducted a study at a University than five years had a positive independent association Hospital in Ibadan, Nigeria, and found that MS preva- with MS (p < 0.001). Our observation is in agreement lence was 66.0% among 340 participants with T2DM with the Mogre et al. (2014) study conducted among peo- when classified by the IDF definition [5]. Among peo- ple with T2DM in a teaching hospital in northern Ghana ple with T2DM in Cameroon, the prevalence of MS was [22]. Similarly, a study among 159 diabetes patients in 71.7% as defined by the IDF criterion and 60.4% using the Ethiopia found that having diabetes for over five years NCEP-ATP III definition in the same study [37]. was significantly associated with MS [49]. The authors Beyond the study designs, sample sizes, and ethnic or suggested that lack of awareness and inadequate health geographical differences, the spatial variability of MS care for people with T2DM was likely to be implicated prevalence across studies conducted in Ghana and the in their findings. In contrast, a study in Japan [50] and African continent might have been influenced by differ- Hong Kong [51] found that living longer with T2DM cor- ences in approaches used to measure MS. Depending related positively with the prevalence of MS. Shimajiri on the type of criterion used to diagnose MS, the preva- et  al. (2008) attributed the inverse relationship between lence of the syndrome might differ between studies [38]. MS prevalence and duration of T2DM to improved BMI Reports from several studies suggest that the harmonized brought about by enhanced medical care and improved criterion is a more sensitive indicator of MS than the metabolic control [50]. This is understandable given that IDF, WHO, or NCEP: APT III definitions of MS [39–41]. stronger health care systems in such developed countries This might have explained why the prevalence of MS was could lead to improved health outcomes for people with higher in this present study than in the earlier studies T2DM. In this present study, the negative association conducted in Ghana [6, 22, 33]. between the duration of T2DM illness and MS may be Few studies have assessed the prevalence of MS among due to poor metabolic and glycaemic control as a result people with T2DM using the harmonized definition. of inadequate medical care. In Nigeria, Ogbera et  al. (2010) recruited patients with This present study also revealed differential patterns of T2DM from an urban hospital and reported an 86.0% MS between overweight/obese participants and normal- prevalence of MS among participants using the harmo- weight participants. Participants who were overweight/ nized definition [42]. In one Nepalese study involving obese were more likely to have MS than their counter- 1061 patients with T2DM, the prevalence of MS was parts who were not overweight/obese. A similar study reported in 80.3% of participants [39]. A similar study conducted among participants with T2DM in Nigeria conducted among participants with T2DM in India using the harmonized definition found MS to be sig- reported an MS prevalence of 71.9% [9]. The disagree- nificantly associated with obesity [42]. Population-based ments in the prevalence of MS between these studies and studies in the United States of America using the NCEP/ Abagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 10 of 13 ATP III definition have also reported obesity to be inde- Given that obesity has strong links with MS [45–47], it pendently associated with MS [47, 52]. These observa- was not unexpected to find increased WC as one of the tions are not unexpected given that obesity is a known three most common components of MS in this study. risk factor for MS [45, 46]. Similar studies among people with T2DM in Ghana [22] Contrary to existing evidence, this present study did using the IDF classification; Nigeria [42] using the new not associate MS with increased age [22, 48, 52, 53], harmonized definition; and Seychelles [55] using the or educational attainment. Similar studies conducted IDF, APT, and WHO definitions, have also reported WC among T2DM patients in Nigeria using the IDF criterion among the three predominant components of MS. In [5], and India using the harmonized criterion [9, 44] also contrast, among non-obese individuals with MS in India, did not associate MS with increased age. In contrast, sev- Dhanaraj et al. (2008) found elevated serum triglycerides eral cross-sectional studies among people with T2DM in men and low serum HDL-cholesterol in women, but [22, 53] and in the general population [48, 52] using not WC, to be the strongest determinant of MS using a various definitions of MS have reported age differences modified APT III classification of MS [56]. in the way MS is expressed. In terms of the relationship In agreement with the results of this study, several between MS and educational attainment the results of studies have also reported raised SBP among the three this study are comparable with the Bhatti et  al. (2015) commonest components of MS [6, 9, 57]. Using the study among T2DM patients in India [9], but at variance NCEP/ATP III criterion, Nsiah et  al. (2015) conducted with the Nsiah et al. (2015) study among diabetes patients a cross-sectional study among people with T2DM in a in southern Ghana [6]. While the mechanism explaining teaching hospital in southern Ghana and reported SBP the lack of association between MS and increased age or as the commonest component of MS [6]. In Nigeria, a educational attainment in our study is unclear; it could hospital-based study assessing MS among subjects with have been influenced by similarities in physical activity T2DM also reported SBP as the predominant component and under-or over-nutrition levels between younger and of MS among participants [57]. Similarly, a population- older participants. based study assessing MS among urban diabetic patients The three most common constituents of MS among in northern India found SBP to be the commonest com- participants in the study were reduced HDL-cholesterol ponent of MS among participants in the study [9]. The levels, elevated FBG (hyperglycemia), and high SBP. evidence appears to suggest that when hyperglycemia is Given that all the study participants were patients living excluded, reduced HDL-cholesterol, elevated WC, and with T2DM, we excluded elevated blood glucose lev- raised blood pressure emerged as the common MS com- els in the assessment because it is the main indicator of ponents that coexist in people with T2DM [11, 58]. diabetes. If raised FBG had not been excluded, it would This study has some limitations and strengths to note. have been the predominant component of MS among Owing to the cross-sectional design, this study was study participants. After excluding elevated FBG from unable to establish temporal associations between the the assessment, reduced HDL-cholesterol levels emerged explanatory factors and the occurrence of MS. Addition- as the most prevalent component of MS in the present ally, given that all participants were selected from a hos- study. This observation was consistent with the results pital setting, the findings of this present study might not from one study in Libya that used the WHO and IDF def- be representative of all persons with T2DM. Nonethe- initions to define MS [54]. In contrast, two earlier studies less, we believe our findings are reflective of MS preva- among people with T2DM in Ghana used the IDF [22] lence and its associated risk factors among patients with and the NCEP/ATP III [6] definitions of MS and reported T2DM and akin populations because of the relatively WC and high blood pressure as the predominant compo- large sample size of the participants. Also, using the new nents of MS respectively. In Nigeria, Ogbera et al. (2010), harmonized definition for metabolic syndrome aligns our used the harmonized criterion and found WC to be the research with current international guidelines for evalu- most commonest component of MS among study par- ating MS. ticipants with T2DM [42]. Nonetheless, reduced HDL- cholesterol was among the three principal components Conclusions of MS in these earlier studies [6, 22, 42]. The high preva- The findings of this study support the evidence from ear- lence of reduced HDL cholesterol among participants in lier studies that suggest that MS is widespread among this study could be a consequence of uncontrolled hyper- routine clinic attendants with T2DM in Ghana. Con- glycemia among participants in this study. Eckel et  al. sistent with the other studies conducted in Ghana and (2005) have suggested that people with elevated blood similar settings, this study found MS to be more com- glucose readings may also present with reduced HDL mon in women than in men. In addition, the duration cholesterol [13]. of T2DM and overweight/obesity status were identified A bagre et al. BMC Cardiovascular Disorders (2022) 22:366 Page 11 of 13 as important risk factors of MS in our population. The Competing Interests three most predominant components of MS identified The authors declare that they have no competing interests. in this study were low HDL cholesterol, high waist cir- Author details cumference, and elevated SBP. Tackling the MS epidemic 1 Department of Epidemiology and Disease Control, School of Public Health, requires targeted interventions to address these specific College of Health Sciences, University of Ghana, P. O. Box LG 13, Legon, Accra, Ghana. 2 Ghana Field Epidemiology and Laboratory Training Programme, components of MS among people with T2DM. School of Public Health, College of Health Sciences, University of Ghana, P. O. Box LG 13, Legon, Accra, Ghana. Received: 9 March 2022 Accepted: 2 August 2022 Implications The burden of MS in the present study reflects a need for the healthcare system (Ghana Health Service) to develop specific protocols and systems for the routine diagnosis and management of MS for people with T2DM in hos- References 1. 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