Metabolic syndrome among Nigerians with type 2 diabetes mellitus: a comparative study of the diagnostic criteria.

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Taoreed Adegoke Azeez, Jokotade Adeleye, Omololu Adedoyin Enigbokan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-795474/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Metabolic syndrome is associated with increased cardiovascular death. The objectives of this study were to find the frequency of metabolic syndrome among Nigerians with type 2 diabetes and to compare the modified NCEP ATP III criteria and the IDF criteria Methods The study involved 134 participants. Sixty-seven were cases with type 2 diabetes while the rest were the controls without type 2 diabetes. Ethical approval was granted by the institution’s ethics review committee. Anthropometric, clinical and laboratory parameters were obtained using standard protocols. Data were analyzed with SPSS version 22. Means were compared with Student’s t test while proportions were compared with the Pearson’s chi square. Point biserial correlation was used to determine the association between the dichotomous variables and interval variables. Agreement between the criteria was tested with the Cohen’s kappa test. Results Type 2 diabetes was associated with a higher prevalence of hypertension and truncal obesity. The frequency of metabolic syndrome was lower with the IDF criteria compared with the modified NCEP criteria (65.7% vs 71.6%). Although there was a strong agreement between the IDF and the modified NCEP criteria (κ=0.862; p<0.0001) yet, the IDF criteria missed 8.3% of diabetic individuals diagnosed with metabolic syndrome by the modified NCEP criteria. Cardiovascular risk is better predicted when the modified NCEP criteria were used to diagnose metabolic syndrome. Conclusion Metabolic syndrome is very common among Nigerians with type 2 diabetes and it is better diagnosed with the modified NCEP ATP III criteria. Endocrinology & Metabolism Metabolic syndrome diabetes mellitus type 2 comparative study Nigeria cardiovascular risk diagnosis criteria Introduction A syndrome is a constellation of symptoms and signs attributed to a disease. 1 It is a term that suggests that the occurrence of certain clinical manifestations are not just due to chance. In 1988, an American Endocrinologist, Gerald Reaven, described a cluster of clinical features which were considered to be linked together and insulin resistance was posited to be the central theme of the cluster. 2 He called the cluster ‘syndrome X’. Since then, there has been disagreement among researchers and experts on the definition, nomenclature and criteria for the syndrome. 1 Apart from insulin resistance, the other components of the syndrome include elevated blood pressure, dyslipidaemia, glucose intolerance and central obesity. 3 In 1998, the World Health Organization (WHO) Consultation Group came up with a definition based on the presence of obesity and certain metabolic abnormalities. 4 The syndrome became more commonly referred to as ‘metabolic syndrome’. The WHO criteria for the diagnosis of metabolic syndrome are shown in Table 1 below. 4 Table 1 WHO criteria for metabolic syndrome Criteria Requirement for diagnosis 1. Glucose intolerance, impaired glucose tolerance, or diabetes mellitus and/or insulin resistance. (1) and any other 2 are required for the diagnosis. 2. Blood pressure ≥ 140/90 mmHg 3. Waist-hip ratio > 0.9 in males or > 0.85 in females and/or body mass index ≥ 30kg/m 2 4. Plasma triglycerides ≥ 150 mg/dl and/or high density lipoprotein- cholesterol < 35 mg/dl in men or < 39mg/dl in women 5. Urinary albumin excretion ≥ 20µg/min or albumin-creatinine ratio ≥ 30µg/mg In 1999, shortly after the publication of the WHO criteria for metabolic syndrome, the European Group for the Study of Insulin Resistance (EGIR) reported their own criteria for metabolic syndrome. 5 The term favoured by the group was ‘insulin resistance syndrome’. The EGIR required an elevated plasma insulin > 75th percentile before the diagnosis of metabolic syndrome could be made. 4 In addition, the focus was on abdominal obesity while the presence of diabetes and microalbuminuria were dropped. 6 In 2001, in the executive summary of the third report of the National Cholesterol Education Program on the detection, evaluation and treatment of high blood cholesterol in adults – adults treatment panel III (NCEP ATP III), the criteria for the diagnosis of metabolic syndrome were described. 7 The panel did not believe that insulin resistance was mandatory for the development of metabolic syndrome, rather, abdominal obesity was seen as the main culprit hence, they favoured the term ‘metabolic syndrome’. 4 Also, waist circumference was adopted to quantify abdominal obesity instead of the waist-hip ratio. Moreover, plasma triglycerides (TG) and high density lipoprotein cholesterol (HDL-C) were considered as independent criteria. The NCEP ATP criteria are depicted in Table 2 below. 8 Table 2 NCEP ATP III criteria for metabolic syndrome Criteria Requirement for diagnosis 1. Fasting plasma glucose > 100 mg/dl* or previously diagnosed with type 2 diabetes Any 3 of the criteria are required for the diagnosis. 2. Systolic blood pressure > 130 mmHg and/or diastolic blood pressure > 85 mmHg or on treatment for previously diagnosed hypertension. 3. Waist circumference ≥ 102 cm in males or ≥ 88 cm in females. 4. Plasma triglycerides ≥ 150 mg/dl 5. HDL-C < 40 mg/dl in men or < 50mg/dl in women *- In the original criteria, FPG value required for diagnosis was 110 mg/dl but it was later reduced to 100 mg/dl following a similar reduction by the American Diabetes Association. 9 In 2005, due to the profuse controversies generated from the definition of metabolic syndrome by various bodies, the International Diabetes Federation (IDF) came up with a global consensus definition for metabolic syndrome. 10 It also established central obesity as the focal point in metabolic syndrome. Waist circumference was also used in quantifying central obesity but the cut-off points became ethnic- and gender-specific. The Europoids cut off is adopted for Africans and it is what is shown in Table 3 below. 4 Table 3 IDF criteria for metabolic syndrome Criteria Requirement for diagnosis 1. Waist circumference ≥ 80 cm in males or ≥ 94 cm in females.* (1) and any other 2 are required for the diagnosis. 2. Systolic blood pressure > 130 mmHg and/or diastolic blood pressure > 85 mmHg or on treatment for previously diagnosed hypertension 3. Fasting plasma glucose > 100 mg/dl or previously diagnosed with type 2 diabetes 4. Plasma triglycerides ≥ 150 mg/dl 5. HDL-C < 40 mg/dl in men or < 50mg/dl in women *- The waist circumference is dependent on ethnicity. The figure for Africans was quoted. Following the publication of the IDF criteria, the modified NCEP ATP III criteria came on board. 11 The modified version agreed with the IDF criteria and the fixed waist circumference shown in Table 2 was dropped for the ethnic-based waist circumference. However, despite the modification, abdominal obesity continues to be seen as a component rather than a prerequisite for the diagnosis of metabolic syndrome and this distinguishes the modified NCEP ATP III criteria from the IDF criteria. 11 Insulin resistance is defined as the attenuated biological response to the usual amount of insulin. 12 Despite the various controversies, many authors still aver that insulin resistance is the underlying mechanism of insulin resistance which results from an interplay of genetic and environmental factors. 13 Previous studies have also shown an association between insulin resistance and the various components of metabolic syndrome. 14 Insulin resistance cannot be directly measured clinically but there are surrogate markers for it. 15 Among the surrogate markers of insulin resistance, the homeostatic model of assessment of insulin resistance (HOMA-IR) is the most commonly quoted. 16 Metabolic syndrome is a cluster of cardiovascular risk factors and is therefore associated with increased cardiovascular death. 17 Cardiovascular risk is said to be 50–60% higher in people with metabolic syndrome compared with those without metabolic syndrome. 18 There are different cardiovascular risk calculators that have been documented in the literature. In the primary prevention of atherosclerotic cardiovascular disease, risk estimation is of crucial importance. 19 The American Heart Association/American College of Cardiology (AHA/ACC) Atherosclerotic Cardiovascular Disease (ASCVD) risk score predicts 10-year cardiovascular risk of heart disease or stroke and is validated in many ethnic groups. 20 Objectives The study was aimed at Comparing the profile of cardiovascular risk factors between Nigerians with and without type 2 diabetes mellitus, Comparing the prevalence of metabolic syndrome among Nigerians with type 2 diabetes using the modified NCEP ATP III and IDF criteria, Determining the association between metabolic syndrome diagnosed with the modified NCEP ATP III and IDF criteria among Nigerians with type 2 diabetes and HOMA-IR, waist circumference and ASCVD risk score, and Estimating the extent of agreement between the modified NCEP ATP III and IDF criteria for the diagnosis of metabolic syndrome among Nigerians with type 2 diabetes Methods The study design was an analytical cross-sectional study with a control group. One hundred and thirty-four participants were involved in the study. The cases were 67 individuals previously diagnosed with type 2 diabetes mellitus and the controls were also 67 individuals without type 2 diabetes mellitus. The cases were the individuals selected by systematic random sampling from the type 2 diabetes mellitus patients attending the diabetes clinic of a public tertiary hospital in Southern Nigeria. The controls were apparently healthy individuals without type 2 diabetes mellitus selected randomly from the community. Potential controls were asked if they had ever been diagnosed with type 2 diabetes and were also screened for type 2 diabetes with fasting plasma glucose and glycated haemoglobin. Only those confirmed as not having type 2 diabetes were recruited into the study. Inclusion criterion for the cases was prior diagnosis with type 2 diabetes (more than 6 months). Exclusion criteria were type 1 diabetes mellitus, on-going active weight loss programme, metabolic decompensation, hospital admission in the preceding 3 months to recruitment, pregnancy and prior diagnosis of cardiovascular disease (stroke, myocardial infarction and peripheral arterial disease). Inclusion criterion for the controls was the absence of type 2 diabetes mellitus. The exclusion criteria were similar to those of the cases earlier stated. The institution ethics review committee (with the reference number NHREC/05/01/2008a) granted ethical approval for the study. The reference number of the approval is UI/EC/17/0284. After thorough explanation, the potential participants gave written consent for participation in the study and publication of the findings before they were recruited into the study. Waist circumference was measured with an inelastic tape measure as the horizontal abdominal girth at the midpoint between the lowest rib and the iliac rest after tidal expiration. The WHO standard protocol on waist circumference measurement was carefully followed. 21 Using the American Heart Association blood pressure measurement guidelines, each participant had his systolic blood pressure (SBP) as well as the diastolic blood pressure (DBP) measured with a sphygmomanometer (Accoson brand, made in England). A fasting blood ample was obtained from each participant. Fasting plasma glucose was determined using the enzymatic method run on an Autochemistry analyzer (Accurex Biomedical, Mumbai, India). Fasting plasma triglyceride and HDL-C were also measured using the appropriate enzymatic method. Fasting plasma insulin was assayed using the enzyme-linked immunosorbent assay (ELISA) technique with Cell Biolab Human Insulin ELISA kit (California, USA). The recommended high performance liquid chromatography method was adopted in measuring the glycated haemoglobin (HbA1c). Automated glycohaemoglobin analyzer (Bio-Rad 220 − 0212, Hercules, California, USA) was used for this purpose. HOMA-IR was calculated using the standard formula given below. 22 Insulin resistance was defined as HOMA-IR > 2 as defined by a previous study involving Nigerians. 23 See formula 1 in the supplementary files section. The 10-year cardiovascular risk score was determined using the ASCVD risk estimator on the American College of Cardiology website. 24 ASCVD score below 5.0 was taken as ‘low risk’ while ASCVD score ≥ 5.0 was taken as ‘intermediate/high risk’. 25 Metabolic syndrome was defined using the modified NCEP ATP III and IDF criteria respectively. 4 , 11 Statistical analysis was performed with the Statistical Package for Social Sciences (SPSS) version 22. Continuous variables were summarized as mean ± standard deviation while nominal variables were summarized as frequencies and percentages. The association between the presence or absence of metabolic syndrome (using the modified NCEP ATP III and IDF criteria) and interval variables (ASCVD risk score, waist circumference and HOMA-IR) was determined using point biserial correlation. The means of continuous variables were compared with the independent sample student’s t test. The frequencies of nominal variables were compared with the Pearson’s chi square test. Agreement between two dichotomous nominal variables was determined using the Cohen’s kappa statistic. Cohen’s kappa coefficient (κ) was interpreted as shown in Table 4 below. 26 A p < 0.05 was considered as being statistically significant. Table 4 Interpretation of Cohen’s kappa coefficient (κ) Cohen’s kappa coefficient (κ) Interpretation ≤ 0 No agreement 0.01–0.2 None to slight agreement 0.21–0.4 Fair agreement 0.41–0.6 Moderate agreement 0.61–0.8 Substantial agreement 0.81 -1.0 Almost perfect agreement Results The characteristics of the participants are shown in Table 5 below. The mean age of the cases was 53.21 ± 9.71 and it was not significantly different from that of the controls (p = 0.792). The gender distribution of both the cases and the controls were the same with females accounting for 50.7%. Male cases with type 2 diabetes had a higher waist circumference compared with male controls without type 2 diabetes (p < 0.0001) but this was not reproducible in females (p = 0.158). The subjects had a significantly higher SBP compared with that of the controls (p = 0.002). Interestingly, this study did not show any significant difference in TG and HDL-C between cases with type 2 diabetes and controls without the disease. Insulin resistance and 10-year cardiovascular risk were significantly higher among the cases compared with those of the controls (p < 0.0001). The frequency of metabolic syndrome among individuals living with diabetes was slightly higher using the modified NCEP ATP III criteria (71.6%) than using the IDF criteria (65.7%). As expected, irrespective of the criteria used, metabolic syndrome was significantly commoner in the participants with type 2 diabetes mellitus compared with the controls without type 2 diabetes mellitus (p < 0.0001). Table 6 indicates the point biserial correlation between the presence of metabolic syndrome among the individuals with type 2 diabetes mellitus (using either the modified NCEP ATP III criteria or the IDF criteria) and HOMA-IR as well as 10-year cardiovascular risk (using the ASCVD risk score). Among Nigerians living with type 2 diabetes mellitus, those diagnosed with metabolic syndrome using the modified NCEP ATP III criteria were likely to have a higher ASCVD risk score (p = 0.04). However, this could not be said for those diagnosed with the IDF criteria. However, there was a significant association between metabolic syndrome and waist circumference irrespective of the criteria used (p < 0.0001) Table 7 shows the level of agreement between the diagnostic criteria for metabolic syndrome. There is almost perfect agreement between using the IDF criteria and the modified NCEP ATP III criteria in diagnosing metabolic syndrome (κ = 0.862; p < 0.0001). Also, there was a fair agreement between metabolic syndrome diagnosed with the modified NCEP ATP III criteria and the presence of intermediate/high cardiovascular risk (κ = 0.213; p = 0.029). Table 5 The characteristics of the participants Variable Mean ± SD OR Frequency (%) Test statistic p value Case Control Age (years) 53.21 ± 9.71 52.94 ± 9.96 t = 0.265 0.792 Gender Males Females 34 (50.7%) 33 (49.3%) 34 (50.7%) 33 (49.3%) χ 2 = 0.000 1.000 Waist circumference(cm) Males Females 94.82 ± 4.69 90.67 ± 6.96 87.91 ± 6.40 87.90 ± 8.63 t = 5.079 t = 1.429 0.000** 0.158** SBP (mmHg) 126.79 ± 18.93 112.13 ± 13.08 t = 3.278 0.002** DBP (mmHg) 80.72 ± 11.97 80.03 ± 10.92 t = 0.414 0.680 FPG (mg/dl) 113.72 ± 15.95 86.75 ± 8.13 t = 8.550 0.000** HbA1c (%) 6.99 ± 0.73 4.95 ± 0.47 t = 13.380 0.000** HDL-C (mg/dl) Males Females 46.85 ± 10.32 53.36 ± 13.32 48.67 ± 9.83 51.72 ± 10.14 t = 0.746 t = 0.168 0.458 0.575 Fasting TG (mg/dl) 101.51 ± 17.10 97.58 ± 20.01 t = 0.237 0.813 Fasting insulin (µmol/L) 9.36 ± 3.13 8.13 ± 1.46 t = 2.748 0.008** HOMA-IR 2.59 ± 0.83 1.70 ± 0.72 t = 6.758 0.000** ASCVD risk score 18.75 ± 10.33 3.94 ± 3.24 t = 8.011 0.000** Frequency of MS NCEP ATP III IDF 48 (71.6%) 44 (65.7%) 12 (17.9%) 7 (10.4%) χ 2 = 31.561 χ 2 = 43.337 0.000** 0.000** MS – Metabolic syndrome **- statistically significant Table 6 Point biserial correlation between cardiovascular risk and metabolic syndrome MS with modified NCEP ATP III MS with IDF r pb p r pb p HOMA-IR 0.014 0.909 0.030 0.810 ASCVD score 0.251 0.040** 0.228 0.063 Waist circumference 0.502 0.000** 0.589 0.000** **- statistically significant r pb – point biserial correlation coefficient Table 7 Level of agreement among the diagnostic criteria and cardiovascular risk NCEP ATP III IDF κ p Κ p NCEP ATP III - - 0.862 0.000** IDF 0.862 0.000** - - Insulin resistance (HOMA-IR) 0.143 0.144 0.116 0.273 ASCVD risk categories 0.213 0.029** 0.156 0.080 -** - statistically significant Discussion This study showed a higher frequency of cardiovascular risk factors such as truncal obesity and elevated systolic blood pressure among individuals living with type 2 diabetes compared to the controls who did not have type 2 diabetes. In another study involving Nigerians with type 2 diabetes mellitus, the researchers posited that cardiovascular risk factors were more common among the individuals with type 2 diabetes compared with those without type 2 diabetes. 16 Several authors in the past have noted this cluster of risk factors and that was the genesis of the studies on metabolic syndrome. 27 Previous studies have also documented a higher frequency of elevated systolic blood pressure among individuals with diabetes compared with the general population, just as it was found in the present study. 28 , 29 Type 2 diabetes causes arterial stiffening especially in the presence of sub-optimal metabolic control and this is believed to be one of the links between type 2 diabetes and elevated systolic blood pressure. 30 Other mechanisms that have been documented as the plausible explanations for a higher frequency of elevated systolic blood pressure among individuals with diabetes are endothelial dysfunction, sodium retention, sympathetic over-activity, renin-angiotensin-aldosterone activation and nephropathy. 31 However, as hypothesized by some authors, the relationship between type 2 diabetes and hypertension is more reciprocal than causal. 32 As noted in the present study, truncal obesity, represented by weight circumference, was higher among individuals with type 2 diabetes and similar observation has been reported from previous studies. 33 Abdominal distribution of fat is a better determinant of the risk of developing type 2 diabetes than the total body fat mass. 34 Truncal obesity is characterized with increased inflammatory cytokines and non-esterified fatty acids as well as hormonal dysregulation which are thought to be the underlying processes leading to insulin resistance and eventually type 2 diabetes mellitus. 35 Quite striking was the observation, in this study, that the HDL-C and fasting triglycerides of those with or without type 2 diabetes mellitus were not significantly different. In the general population, an epidemiological study quoted by Laakso has demonstrated that the lipid profiles of individuals with type 2 diabetes were not remarkably different from that of the general population. 36 However, our study was a hospital based study and previous hospital-based studies have documented a significantly lower HDL-C and higher triglycerides (a cluster sometimes called diabetic dyslipidaemia) among individuals with type 2 diabetes. 37 , 38 Nevertheless, Zheng et al posited that the association between hypertriglyceridemia and type 2 diabetes is better appreciated in the presence of poor glycaemic control. Since the participants in this present study had averagely good glycaemic control, evidenced by the Hba1c (6.99 ± 0.73%), it would not be out of place to get a triglyceride and HDL-C profile that are not remarkably different from those of the controls without type 2 diabetes. 38 As expected, HOMA-IR, a marker of insulin resistance was higher among the cases with type 2 diabetes when compared with that of the controls. Insulin resistance is a core pathophysiological pathway in the development of type 2 diabetes mellitus. 39 Also, this study showed a significantly higher 10-year cardiovascular risk score among Nigerians with type 2 diabetes when compared with those without type 2 diabetes. This is not surprising because type 2 diabetes is associated with a concurrent cluster of other cardiovascular risk factors such as obesity and hypertension, as demonstrated in this study and other previous studies. 40 , 41 Again, insulin resistance has been suggested as a potential culprit behind this observation. 40 Going by the results of this study, the prevalence of metabolic syndrome in people living with type 2 diabetes depends on the diagnostic criteria used. The frequency of metabolic syndrome, using the modified NCEP ATP III criteria, was 71.6%. However, the frequency was slightly lower (65.7%) when IDF criteria were applied. A previous study done among Nigerians with type 2 diabetes mellitus patients was 66.7%. 42 However, while the previous study used the conventional NCEP ATP III criteria, this present study used the modified NCEP ATP III criteria and this may account for the lower frequency in the previous study (66.7% vs 71.6%) as it has been suggested that the modified criteria have a better performance. 11 In support of this assertion, a study done in Ethiopia that used the Modified NCEP ATP III criteria, reported a prevalence of 70.1% which is quite similar to 71.6% found in this present study. The frequency of metabolic syndrome among type 2 diabetes mellitus patients diagnosed with the IDF criteria in this present study (65.7%) is quite similar to what was found in a previous study in Nigeria that also used the IDF criteria (63.6%). 43 The prevalence of metabolic syndrome is significantly higher among patients with type 2 diabetes when compared with the general population whether the modified NCEP ATP III criteria (71.6% vs 17.9%; p < 0.0001) or the IDF criteria (65.7% vs 10.4%; p < 0.0001) were used in making the diagnosis. A study done in Nigeria, using the IDF criteria for metabolic syndrome in the general population without type 2 diabetes mellitus, found a prevalence of 8.8% which is comparable to 10.4% documented in the present study. 44 Another study done in Nigeria that used the NCEP ATP III criteria to diagnose metabolic syndrome in apparently healthy individuals not previously diagnosed with type 2 diabetes reported a prevalence rate of 12.1% which is lower than 17.9% found in this present study. This may be because while the previous study used the old NCEP ATP II criteria, the present study used the modified NCEP ATP III criteria which has been shown to have a better performance. Using point biserial correlation, there was no statistically significant association between HOMA-IR (a marker of insulin resistance) and the presence of metabolic syndrome in type 2 diabetes mellitus whether the IDF criteria (p = 0.810) or the modified NCEP ATP III criteria (p = 0.909) were used. There is now a paradigm shift in what is believed to be the core component of metabolic syndrome. It is now thought that waist circumference, or truncal obesity, is more important than insulin resistance in the diagnosis of metabolic syndrome and this informed the IDF criteria which insist on the presence of increased waist circumference as a prerequisite for the diagnosis of metabolic syndrome. 4 Interestingly, this present study found a significant association between metabolic syndrome, whether the modified NCEP ATP III or IDF criteria were used, and waist circumference (p < 0.0001). Previous studies have also demonstrated an association between metabolic syndrome and waist circumference. 45 , 46 This study showed a significant association between metabolic syndrome and 10-year cardiovascular risk score only when the modified NCEP ATP III criteria were used in diagnosing metabolic syndrome (p = 0.04) although the strength of the association was weak. This association was not demonstrable using the IDF criteria. This is in keeping with the hypothesis by previous researchers that the modified NCEP ATP III criteria have a better performance than the IDF criteria. 11 This study was able to demonstrate an almost perfect agreement between using NCEP ATP II and IDF criteria in the diagnosis of metabolic syndrome among Nigerians with type 2 diabetes mellitus. (κ = 0.862; p < 0.0001). It is still worthy of note that the IDF criteria missed 8.3% of the participants with type 2 diabetes which met the NCEP ATP criteria. However, neither NCEP ATP criteria (κ = 0.143; p = 0.116) nor the IDF criteria (κ = 0.144; p = 0.273) had a significant agreement with insulin resistance (using HOMA-IR). Again, this is in agreement with the hypothesis that insulin resistance is not a prerequisite in the diagnosis of metabolic syndrome. This study also found a fair but significant agreement between metabolic syndrome diagnosed with the modified NCEP ATP criteria (κ = 0.213; p = 0.029) and intermediate-to-high cardiovascular risk (using ASCVD risk categories) but this was not found with metabolic syndrome diagnosed with the IDF criteria. This suggests that the modified NCEP ATP III criteria predict cardiovascular risk much better than the IDF criteria. Limitations A larger sample size would be an advantage in this kind of study. The recruited cases with type 2 diabetes mellitus were already being managed in a multidisciplinary setting which may make some of the findings different from what is obtainable in the community. Conclusion Cardiovascular risk factors are commoner in people living with type 2 diabetes. The prevalence of metabolic syndrome among Nigerians with type 2 diabetes is slightly lower if IDF criteria are used than if the modified NCEP ATP III criteria are used. Using the modified NCEP ATP criteria to diagnose metabolic syndrome predicts cardiovascular risk better than using the IDF criteria. IDF criteria compares well with the modified NCEP ATP III criteria but it still misses out some people. The modified NCEP ATP III criteria appears to be a better diagnostic tool for metabolic syndrome among Nigerians with type 2 diabetes mellitus. Declarations Ethical approval and consent to participate: Ethical approval was granted by the ethical committee of the Institute Advanced Medical Research and Training with the reference number NHREC/05/01/2008a. The ethical approval number for the study was UI/EC/17/0284. Also, the recruited participants gave written informed consent to partake in the study. Consent for publication: was taken from all participants. Availability of data and material: Available, if required. Funding : Self-funded Competing interest: None. Acknowledgement : None Abbreviations ACC – American College of Cardiology AHA- American Heart Association ASCVD - Atherosclerotic Cardiovascular Disease DBP – Diastolic blood pressure EGIR - European Group for the Study of Insulin Resistance FPG – Fasting plasma glucose HbA1c - Glycated haemoglobin HDL-C - High density lipoprotein-cholesterol HOMA-IR - Homeostatic model of assessment of insulin resistance IDF – International Diabetes Federation NCEP ATP III - National Cholesterol Education Program on the detection, evaluation and treatment of high blood cholesterol in adults – adults treatment panel III SBP – Systolic blood pressure TG – Fasting plasma triglycerides WHO - World Health Organization References P.M. Nilsson, J. Tuomilehto, L. Rydén. The metabolic syndrome – What is it and how should it be managed? Eur J Prev Cardiolog. 2019 Dec 1;26(2_suppl):33–46 G.M. Reaven. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes. 1988 Dec;37(12):1595–607 V. 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Available from: http%3a%2f%2fwww.acc.org%2flatest-in-cardiology%2farticles%2f2018%2f11%2f14%2f07%2f10%2fnew-aspects-of-the-risk-assessment-guidelines M.L. McHugh, Interrater reliability: the kappa statistic. Biochem Med (Zagreb) 15 (3), 276–282 (2012 Oct) 22( E. Oda, Metabolic syndrome: its history, mechanisms, and limitations. Acta Diabetol. 49 (2), 89–95 (2012 Apr) Y. Akalu, Y. Belsti, Hypertension and Its Associated Factors Among Type 2 Diabetes Mellitus Patients at Debre Tabor General Hospital, Northwest Ethiopia. DMSO. 2020 May 13;13:1621–31 V. Tsimihodimos, C. Gonzalez-Villalpando, J.B. Meigs, E. Ferrannini. Hypertension and Diabetes Mellitus. Hypertension. 2018 Mar 1;71(3):422–8 E. Ferrannini, W.C. Cushman, Diabetes and hypertension: the bad companions. Lancet. 2012 Aug 11;380(9841):601–10 B.M.Y. Cheung, C. Li, Diabetes and hypertension: is there a common metabolic pathway? Curr Atheroscler Rep 14 (2), 160–166 (2012 Apr) G. Colussi, A. Da Porto, A. Cavarape, Hypertension and type 2 diabetes: lights and shadows about causality. J Hum Hypertens 34 (2), 91–93 (2020 Feb) P.N. Båvenholm, J. Kuhl, J. Pigon, A.K. Saha, N.B. Ruderman, S. Efendic, Insulin resistance in type 2 diabetes: association with truncal obesity, impaired fitness, and atypical malonyl coenzyme A regulation. J Clin Endocrinol Metab. 88 (1), 82–87 (2003 Jan) N. Freemantle, J. Holmes, A. Hockey, S. Kumar, How strong is the association between abdominal obesity and the incidence of type 2 diabetes? Int J Clin Pract. 2008 Sep;62(9):1391–6 A.S. Al-Goblan, M.A. Al-Alfi, M.Z. Khan, Mechanism linking diabetes mellitus and obesity. Diabetes Metab Syndr Obes. 2014 Dec 4;7:587–91 M. Laakso, Cardiovascular Disease in Type 2 Diabetes From Population to Man to Mechanisms. Diabetes Care. 33 (2), 442–449 (2010 Feb) C.L. Haase, A. Tybjærg-Hansen, B.G. Nordestgaard, R. Frikke-Schmidt. HDL Cholesterol and Risk of Type 2 Diabetes: A Mendelian Randomization Study. Diabetes. 2015 Sep 1;64(9):3328–33 D. Zheng, J. Dou, G. Liu, Y. Pan, Y. Yan, F. Liu et al. Association Between Triglyceride Level and Glycemic Control Among Insulin-Treated Patients With Type 2 Diabetes. The Journal of Clinical Endocrinology & Metabolism. 2019 Apr 1;104(4):1211–20 T. Azeez, M. Osundina, Insulin resistance and non-alcoholic fatty liver disease: a review of the pathophysiology and the potential targets for drug actions. Journal of Diabetes and Obesity 2 (1), 0–0 (2020 Nov) 6( M.M. Adeva-Andany, J. Martínez-Rodríguez, M. González-Lucán, C. Fernández-Fernández, E. Castro-Quintela, Insulin resistance is a cardiovascular risk factor in humans. Diabetes Metab Syndr 13 (2), 1449–1455 (2019 Apr) T.A. Azeez, Association between lipid indices and 10-year cardiovascular risk of a cohort of black Africans living with type 2 diabetes mellitus. Journal of Advances in Internal Medicine 14 (1), 38–42 (2021 May) 10( C.U. Osuji, B.A. Nzerem, C.E. Dioka, E.I. Onwubuya. Metabolic syndrome in newly diagnosed type 2 diabetes mellitus using NCEP-ATP III, the Nnewi experience. Nigerian Journal of Clinical Practice. 2012 Oct 1;15(4):475 F.H. Puepet, A. Uloko, I.Y. Akogu, E. Aniekwensi, Prevalence of the metabolic syndrome among patients with type 2 diabetes mellitus in urban North-Central Nigeria. African Journal of Endocrinology and Metabolism 8 (1), 12–14 (2009) Muazu. Metabolic syndrome and its associated factors among apparently “healthy” adults residing in rural settlements in Dutse, Northwestern Nigeria: A community-based study [Internet]. [cited 2021 Jun 4]. Available from: https://www.jhrr.org/article.asp?issn=2394 -2010;year=2019;volume=6;issue=3;spage=95;epage=101;aulast=Muazu;type=3 W. Shen, M. Punyanitya, J. Chen, D. Gallagher, J. Albu, X. Pi-Sunyer et al., Waist Circumference Correlates with Metabolic Syndrome Indicators Better Than Percentage Fat. Obesity (Silver Spring). 2006 Apr;14(4):727–36 M. Gierach, J. Gierach, M. Ewertowska, A. Arndt, R. Junik, Correlation between Body Mass Index and Waist Circumference in Patients with Metabolic Syndrome. ISRN Endocrinology 4;2014 , e514589 (2014 Mar) Supplementary Files formula.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-795474","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":45478918,"identity":"4f69d37b-c9b0-4b33-b401-2cbd2174fca2","order_by":0,"name":"Taoreed Adegoke Azeez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYFCCBCA+AMTsIE4FA4MB8VqYQZwzJGthbCNCC3978uEXH87Y2PU3Mz+T5p13WN6cvfkAw4+KbTi1SJx5lmY540Za8ozDbMbGvNsOG+7sOZbA2HPmNm5rbuSYGfN8OJzMcJjB8DFQC+OGGzkGzIxtuLXI38j/BtTyP1n+MPuHw7xzDtsT1GJwI4f5Mc+NA3YGh3mAtjQcTiSoxfDMMzPGGWeSEwwP8xQbzjmWnrzhzLGEg/j8Inc8+fGHD8fs7OWOt2+TeFNjbbvhePPBBz8q8HifgYFNAkgkNgAJJh6GZrDQAXzqgYD5A5CwB7EYfzDUEVA8CkbBKBgFIxEAAFyPY5ZIJzQoAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-3982-5790","institution":"University College Hospital Ibadan","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Taoreed","middleName":"Adegoke","lastName":"Azeez","suffix":""},{"id":45478919,"identity":"b80e38c7-1c45-4010-af7b-f9dbab0679ad","order_by":1,"name":"Jokotade Adeleye","email":"","orcid":"","institution":"University College Hospital Ibadan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jokotade","middleName":"","lastName":"Adeleye","suffix":""},{"id":45478920,"identity":"caba4ba3-93ca-4bd2-90ee-45b51b8187cd","order_by":2,"name":"Omololu Adedoyin Enigbokan","email":"","orcid":"","institution":"University College Hospital Ibadan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Omololu","middleName":"Adedoyin","lastName":"Enigbokan","suffix":""},{"id":45478921,"identity":"e1108ada-1459-4970-b83d-7fac9db0e52c","order_by":3,"name":"Bolaji Adejimi","email":"","orcid":"","institution":"University College Hospital Ibadan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bolaji","middleName":"","lastName":"Adejimi","suffix":""},{"id":45478922,"identity":"45368845-c9f3-406e-a0ad-378b7edb0a36","order_by":4,"name":"John Sunday Oladapo","email":"","orcid":"","institution":"University College Hospital Ibadan","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"John","middleName":"Sunday","lastName":"Oladapo","suffix":""}],"badges":[],"createdAt":"2021-08-09 06:47:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-795474/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-795474/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":13709844,"identity":"c31d9d42-a83f-438f-9a77-c6d893fe4eb5","added_by":"auto","created_at":"2021-09-17 14:15:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":352044,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-795474/v1/7fbe036e-a91b-490e-9dfe-f4bd576737cc.pdf"},{"id":12433628,"identity":"bc317f9c-8a0c-4b42-834f-18a6e1225fc3","added_by":"auto","created_at":"2021-08-14 15:15:59","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15965,"visible":true,"origin":"","legend":"","description":"","filename":"formula.docx","url":"https://assets-eu.researchsquare.com/files/rs-795474/v1/10e001d3f519bbfc9eb53905.docx"}],"financialInterests":"","formattedTitle":"Metabolic syndrome among Nigerians with type 2 diabetes mellitus: a comparative study of the diagnostic criteria.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA syndrome is a constellation of symptoms and signs attributed to a disease.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e It is a term that suggests that the occurrence of certain clinical manifestations are not just due to chance. In 1988, an American Endocrinologist, Gerald Reaven, described a cluster of clinical features which were considered to be linked together and insulin resistance was posited to be the central theme of the cluster.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e He called the cluster \u0026lsquo;syndrome X\u0026rsquo;. Since then, there has been disagreement among researchers and experts on the definition, nomenclature and criteria for the syndrome.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Apart from insulin resistance, the other components of the syndrome include elevated blood pressure, dyslipidaemia, glucose intolerance and central obesity.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn 1998, the World Health Organization (WHO) Consultation Group came up with a definition based on the presence of obesity and certain metabolic abnormalities.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The syndrome became more commonly referred to as \u0026lsquo;metabolic syndrome\u0026rsquo;. The WHO criteria for the diagnosis of metabolic syndrome are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWHO criteria for metabolic syndrome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRequirement for diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Glucose intolerance, impaired glucose tolerance, or diabetes mellitus and/or insulin resistance.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(1) and any other 2 are required for the diagnosis.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/90 mmHg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Waist-hip ratio\u0026thinsp;\u0026gt;\u0026thinsp;0.9 in males or \u0026gt;\u0026thinsp;0.85 in females and/or body mass index\u0026thinsp;\u0026ge;\u0026thinsp;30kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Plasma triglycerides\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/dl and/or high density lipoprotein- cholesterol\u0026thinsp;\u0026lt;\u0026thinsp;35 mg/dl in men or \u0026lt;\u0026thinsp;39mg/dl in women\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Urinary albumin excretion\u0026thinsp;\u0026ge;\u0026thinsp;20\u0026micro;g/min or albumin-creatinine ratio\u0026thinsp;\u0026ge;\u0026thinsp;30\u0026micro;g/mg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn 1999, shortly after the publication of the WHO criteria for metabolic syndrome, the European Group for the Study of Insulin Resistance (EGIR) reported their own criteria for metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The term favoured by the group was \u0026lsquo;insulin resistance syndrome\u0026rsquo;. The EGIR required an elevated plasma insulin\u0026thinsp;\u0026gt;\u0026thinsp;75th percentile before the diagnosis of metabolic syndrome could be made.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e In addition, the focus was on abdominal obesity while the presence of diabetes and microalbuminuria were dropped.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn 2001, in the executive summary of the third report of the National Cholesterol Education Program on the detection, evaluation and treatment of high blood cholesterol in adults \u0026ndash; adults treatment panel III (NCEP ATP III), the criteria for the diagnosis of metabolic syndrome were described.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The panel did not believe that insulin resistance was mandatory for the development of metabolic syndrome, rather, abdominal obesity was seen as the main culprit hence, they favoured the term \u0026lsquo;metabolic syndrome\u0026rsquo;.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Also, waist circumference was adopted to quantify abdominal obesity instead of the waist-hip ratio. Moreover, plasma triglycerides (TG) and high density lipoprotein cholesterol (HDL-C) were considered as independent criteria. The NCEP ATP criteria are depicted in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNCEP ATP III criteria for metabolic syndrome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRequirement for diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Fasting plasma glucose\u0026thinsp;\u0026gt;\u0026thinsp;100 mg/dl* or previously diagnosed with type 2 diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAny 3 of the criteria are required for the diagnosis.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Systolic blood pressure\u0026thinsp;\u0026gt;\u0026thinsp;130 mmHg and/or diastolic blood pressure\u0026thinsp;\u0026gt;\u0026thinsp;85 mmHg or on treatment for previously diagnosed hypertension.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Waist circumference\u0026thinsp;\u0026ge;\u0026thinsp;102 cm in males or \u0026ge;\u0026thinsp;88 cm in females.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Plasma triglycerides\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/dl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. HDL-C\u0026thinsp;\u0026lt;\u0026thinsp;40 mg/dl in men or \u0026lt;\u0026thinsp;50mg/dl in women\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e*- In the original criteria, FPG value required for diagnosis was 110 mg/dl but it was later reduced to 100 mg/dl following a similar reduction by the American Diabetes Association.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn 2005, due to the profuse controversies generated from the definition of metabolic syndrome by various bodies, the International Diabetes Federation (IDF) came up with a global consensus definition for metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e It also established central obesity as the focal point in metabolic syndrome. Waist circumference was also used in quantifying central obesity but the cut-off points became ethnic- and gender-specific. The Europoids cut off is adopted for Africans and it is what is shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIDF criteria for metabolic syndrome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCriteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRequirement for diagnosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Waist circumference\u0026thinsp;\u0026ge;\u0026thinsp;80 cm in males or \u0026ge;\u0026thinsp;94 cm in females.*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e(1) and any other 2 are required for the diagnosis.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Systolic blood pressure\u0026thinsp;\u0026gt;\u0026thinsp;130 mmHg and/or diastolic blood pressure\u0026thinsp;\u0026gt;\u0026thinsp;85 mmHg or on treatment for previously diagnosed hypertension\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Fasting plasma glucose\u0026thinsp;\u0026gt;\u0026thinsp;100 mg/dl or previously diagnosed with type 2 diabetes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Plasma triglycerides\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/dl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. HDL-C\u0026thinsp;\u0026lt;\u0026thinsp;40 mg/dl in men or \u0026lt;\u0026thinsp;50mg/dl in women\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e*- The waist circumference is dependent on ethnicity. The figure for Africans was quoted.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eFollowing the publication of the IDF criteria, the modified NCEP ATP III criteria came on board.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e The modified version agreed with the IDF criteria and the fixed waist circumference shown in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e was dropped for the ethnic-based waist circumference. However, despite the modification, abdominal obesity continues to be seen as a component rather than a prerequisite for the diagnosis of metabolic syndrome and this distinguishes the modified NCEP ATP III criteria from the IDF criteria.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eInsulin resistance is defined as the attenuated biological response to the usual amount of insulin.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Despite the various controversies, many authors still aver that insulin resistance is the underlying mechanism of insulin resistance which results from an interplay of genetic and environmental factors.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Previous studies have also shown an association between insulin resistance and the various components of metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Insulin resistance cannot be directly measured clinically but there are surrogate markers for it.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Among the surrogate markers of insulin resistance, the homeostatic model of assessment of insulin resistance (HOMA-IR) is the most commonly quoted.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMetabolic syndrome is a cluster of cardiovascular risk factors and is therefore associated with increased cardiovascular death.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Cardiovascular risk is said to be 50\u0026ndash;60% higher in people with metabolic syndrome compared with those without metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e There are different cardiovascular risk calculators that have been documented in the literature. In the primary prevention of atherosclerotic cardiovascular disease, risk estimation is of crucial importance.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e The American Heart Association/American College of Cardiology (AHA/ACC) Atherosclerotic Cardiovascular Disease (ASCVD) risk score predicts 10-year cardiovascular risk of heart disease or stroke and is validated in many ethnic groups.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"Objectives","content":"\u003cp\u003eThe study was aimed at\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eComparing the profile of cardiovascular risk factors between Nigerians with and without type 2 diabetes mellitus,\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eComparing the prevalence of metabolic syndrome among Nigerians with type 2 diabetes using the modified NCEP ATP III and IDF criteria,\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDetermining the association between metabolic syndrome diagnosed with the modified NCEP ATP III and IDF criteria among Nigerians with type 2 diabetes and HOMA-IR, waist circumference and ASCVD risk score, and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEstimating the extent of agreement between the modified NCEP ATP III and IDF criteria for the diagnosis of metabolic syndrome among Nigerians with type 2 diabetes\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe study design was an analytical cross-sectional study with a control group. One hundred and thirty-four participants were involved in the study. The cases were 67 individuals previously diagnosed with type 2 diabetes mellitus and the controls were also 67 individuals without type 2 diabetes mellitus. The cases were the individuals selected by systematic random sampling from the type 2 diabetes mellitus patients attending the diabetes clinic of a public tertiary hospital in Southern Nigeria. The controls were apparently healthy individuals without type 2 diabetes mellitus selected randomly from the community. Potential controls were asked if they had ever been diagnosed with type 2 diabetes and were also screened for type 2 diabetes with fasting plasma glucose and glycated haemoglobin. Only those confirmed as not having type 2 diabetes were recruited into the study.\u003c/p\u003e \u003cp\u003eInclusion criterion for the cases was prior diagnosis with type 2 diabetes (more than 6 months). Exclusion criteria were type 1 diabetes mellitus, on-going active weight loss programme, metabolic decompensation, hospital admission in the preceding 3 months to recruitment, pregnancy and prior diagnosis of cardiovascular disease (stroke, myocardial infarction and peripheral arterial disease). Inclusion criterion for the controls was the absence of type 2 diabetes mellitus. The exclusion criteria were similar to those of the cases earlier stated.\u003c/p\u003e \u003cp\u003e The institution ethics review committee (with the reference number NHREC/05/01/2008a) granted ethical approval for the study. The reference number of the approval is UI/EC/17/0284. After thorough explanation, the potential participants gave written consent for participation in the study and publication of the findings before they were recruited into the study.\u003c/p\u003e \u003cp\u003eWaist circumference was measured with an inelastic tape measure as the horizontal abdominal girth at the midpoint between the lowest rib and the iliac rest after tidal expiration. The WHO standard protocol on waist circumference measurement was carefully followed.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Using the American Heart Association blood pressure measurement guidelines, each participant had his systolic blood pressure (SBP) as well as the diastolic blood pressure (DBP) measured with a sphygmomanometer (Accoson brand, made in England).\u003c/p\u003e \u003cp\u003eA fasting blood ample was obtained from each participant. Fasting plasma glucose was determined using the enzymatic method run on an Autochemistry analyzer (Accurex Biomedical, Mumbai, India). Fasting plasma triglyceride and HDL-C were also measured using the appropriate enzymatic method. Fasting plasma insulin was assayed using the enzyme-linked immunosorbent assay (ELISA) technique with Cell Biolab Human Insulin ELISA kit (California, USA). The recommended high performance liquid chromatography method was adopted in measuring the glycated haemoglobin (HbA1c). Automated glycohaemoglobin analyzer (Bio-Rad 220\u0026thinsp;\u0026minus;\u0026thinsp;0212, Hercules, California, USA) was used for this purpose.\u003c/p\u003e \u003cp\u003eHOMA-IR was calculated using the standard formula given below.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Insulin resistance was defined as HOMA-IR\u0026thinsp;\u0026gt;\u0026thinsp;2 as defined by a previous study involving Nigerians.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eSee formula 1 in the supplementary files section.\u003c/strong\u003e\u003c/p\u003e \u003cp\u003eThe 10-year cardiovascular risk score was determined using the ASCVD risk estimator on the American College of Cardiology website.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e ASCVD score below 5.0 was taken as \u0026lsquo;low risk\u0026rsquo; while ASCVD score\u0026thinsp;\u0026ge;\u0026thinsp;5.0 was taken as \u0026lsquo;intermediate/high risk\u0026rsquo;.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Metabolic syndrome was defined using the modified NCEP ATP III and IDF criteria respectively.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStatistical analysis was performed with the Statistical Package for Social Sciences (SPSS) version 22. Continuous variables were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation while nominal variables were summarized as frequencies and percentages. The association between the presence or absence of metabolic syndrome (using the modified NCEP ATP III and IDF criteria) and interval variables (ASCVD risk score, waist circumference and HOMA-IR) was determined using point biserial correlation. The means of continuous variables were compared with the independent sample student\u0026rsquo;s t test. The frequencies of nominal variables were compared with the Pearson\u0026rsquo;s chi square test. Agreement between two dichotomous nominal variables was determined using the Cohen\u0026rsquo;s kappa statistic. Cohen\u0026rsquo;s kappa coefficient (κ) was interpreted as shown in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e below.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e A \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as being statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eInterpretation of Cohen\u0026rsquo;s kappa coefficient\u003c/em\u003e (κ)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohen\u0026rsquo;s kappa coefficient (κ)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.01\u0026ndash;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone to slight agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.21\u0026ndash;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFair agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.41\u0026ndash;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.61\u0026ndash;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSubstantial agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.81 -1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlmost perfect agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe characteristics of the participants are shown in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e below. The mean age of the cases was 53.21\u0026thinsp;\u0026plusmn;\u0026thinsp;9.71 and it was not significantly different from that of the controls (p\u0026thinsp;=\u0026thinsp;0.792). The gender distribution of both the cases and the controls were the same with females accounting for 50.7%. Male cases with type 2 diabetes had a higher waist circumference compared with male controls without type 2 diabetes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) but this was not reproducible in females (p\u0026thinsp;=\u0026thinsp;0.158). The subjects had a significantly higher SBP compared with that of the controls (p\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e \u003cp\u003eInterestingly, this study did not show any significant difference in TG and HDL-C between cases with type 2 diabetes and controls without the disease. Insulin resistance and 10-year cardiovascular risk were significantly higher among the cases compared with those of the controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eThe frequency of metabolic syndrome among individuals living with diabetes was slightly higher using the modified NCEP ATP III criteria (71.6%) than using the IDF criteria (65.7%). As expected, irrespective of the criteria used, metabolic syndrome was significantly commoner in the participants with type 2 diabetes mellitus compared with the controls without type 2 diabetes mellitus (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e indicates the point biserial correlation between the presence of metabolic syndrome among the individuals with type 2 diabetes mellitus (using either the modified NCEP ATP III criteria or the IDF criteria) and HOMA-IR as well as 10-year cardiovascular risk (using the ASCVD risk score). Among Nigerians living with type 2 diabetes mellitus, those diagnosed with metabolic syndrome using the modified NCEP ATP III criteria were likely to have a higher ASCVD risk score (p\u0026thinsp;=\u0026thinsp;0.04). However, this could not be said for those diagnosed with the IDF criteria. However, there was a significant association between metabolic syndrome and waist circumference irrespective of the criteria used (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001)\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows the level of agreement between the diagnostic criteria for metabolic syndrome. There is almost perfect agreement between using the IDF criteria and the modified NCEP ATP III criteria in diagnosing metabolic syndrome (κ\u0026thinsp;=\u0026thinsp;0.862; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Also, there was a fair agreement between metabolic syndrome diagnosed with the modified NCEP ATP III criteria and the presence of intermediate/high cardiovascular risk (κ\u0026thinsp;=\u0026thinsp;0.213; p\u0026thinsp;=\u0026thinsp;0.029).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe characteristics of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD OR Frequency (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTest statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCase\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eControl\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e53.21\u0026thinsp;\u0026plusmn;\u0026thinsp;9.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e52.94\u0026thinsp;\u0026plusmn;\u0026thinsp;9.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eMales\u003c/p\u003e \u003cp\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (50.7%)\u003c/p\u003e \u003cp\u003e33 (49.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (50.7%)\u003c/p\u003e \u003cp\u003e33 (49.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference(cm)\u003c/p\u003e \u003cp\u003eMales\u003c/p\u003e \u003cp\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.82\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69\u003c/p\u003e \u003cp\u003e90.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.91\u0026thinsp;\u0026plusmn;\u0026thinsp;6.40\u003c/p\u003e \u003cp\u003e87.90\u0026thinsp;\u0026plusmn;\u0026thinsp;8.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;5.079\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;1.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003cp\u003e0.158**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e126.79\u0026thinsp;\u0026plusmn;\u0026thinsp;18.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e112.13\u0026thinsp;\u0026plusmn;\u0026thinsp;13.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;3.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e80.72\u0026thinsp;\u0026plusmn;\u0026thinsp;11.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e80.03\u0026thinsp;\u0026plusmn;\u0026thinsp;10.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.680\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e113.72\u0026thinsp;\u0026plusmn;\u0026thinsp;15.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e86.75\u0026thinsp;\u0026plusmn;\u0026thinsp;8.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;8.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;13.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C (mg/dl)\u003c/p\u003e \u003cp\u003eMales\u003c/p\u003e \u003cp\u003eFemales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.85\u0026thinsp;\u0026plusmn;\u0026thinsp;10.32\u003c/p\u003e \u003cp\u003e53.36\u0026thinsp;\u0026plusmn;\u0026thinsp;13.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.67\u0026thinsp;\u0026plusmn;\u0026thinsp;9.83\u003c/p\u003e \u003cp\u003e51.72\u0026thinsp;\u0026plusmn;\u0026thinsp;10.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.746\u003c/p\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting TG (mg/dl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e101.51\u0026thinsp;\u0026plusmn;\u0026thinsp;17.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e97.58\u0026thinsp;\u0026plusmn;\u0026thinsp;20.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting insulin (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e9.36\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;2.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;6.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASCVD risk score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e18.75\u0026thinsp;\u0026plusmn;\u0026thinsp;10.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003et\u0026thinsp;=\u0026thinsp;8.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of MS\u003c/p\u003e \u003cp\u003eNCEP ATP III\u003c/p\u003e \u003cp\u003eIDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (71.6%)\u003c/p\u003e \u003cp\u003e44 (65.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (17.9%)\u003c/p\u003e \u003cp\u003e7 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;31.561\u003c/p\u003e \u003cp\u003eχ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e \u0026thinsp;=\u0026thinsp;43.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eMS \u0026ndash; Metabolic syndrome\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e**- statistically significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePoint biserial correlation between cardiovascular risk and metabolic syndrome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMS with modified NCEP ATP III\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMS with IDF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003csub\u003epb\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003csub\u003epb\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASCVD score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.040**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e**- statistically significant r\u003csub\u003epb \u0026ndash;\u003c/sub\u003e point biserial correlation coefficient\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLevel of agreement among the diagnostic criteria and cardiovascular risk\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNCEP ATP III\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eIDF\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eκ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eΚ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNCEP ATP III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin resistance (HOMA-IR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.273\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASCVD risk categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.029**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e-** - statistically significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study showed a higher frequency of cardiovascular risk factors such as truncal obesity and elevated systolic blood pressure among individuals living with type 2 diabetes compared to the controls who did not have type 2 diabetes. In another study involving Nigerians with type 2 diabetes mellitus, the researchers posited that cardiovascular risk factors were more common among the individuals with type 2 diabetes compared with those without type 2 diabetes.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Several authors in the past have noted this cluster of risk factors and that was the genesis of the studies on metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePrevious studies have also documented a higher frequency of elevated systolic blood pressure among individuals with diabetes compared with the general population, just as it was found in the present study.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Type 2 diabetes causes arterial stiffening especially in the presence of sub-optimal metabolic control and this is believed to be one of the links between type 2 diabetes and elevated systolic blood pressure.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Other mechanisms that have been documented as the plausible explanations for a higher frequency of elevated systolic blood pressure among individuals with diabetes are endothelial dysfunction, sodium retention, sympathetic over-activity, renin-angiotensin-aldosterone activation and nephropathy.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e However, as hypothesized by some authors, the relationship between type 2 diabetes and hypertension is more reciprocal than causal.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs noted in the present study, truncal obesity, represented by weight circumference, was higher among individuals with type 2 diabetes and similar observation has been reported from previous studies.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Abdominal distribution of fat is a better determinant of the risk of developing type 2 diabetes than the total body fat mass.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Truncal obesity is characterized with increased inflammatory cytokines and non-esterified fatty acids as well as hormonal dysregulation which are thought to be the underlying processes leading to insulin resistance and eventually type 2 diabetes mellitus.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eQuite striking was the observation, in this study, that the HDL-C and fasting triglycerides of those with or without type 2 diabetes mellitus were not significantly different. In the general population, an epidemiological study quoted by Laakso has demonstrated that the lipid profiles of individuals with type 2 diabetes were not remarkably different from that of the general population.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e However, our study was a hospital based study and previous hospital-based studies have documented a significantly lower HDL-C and higher triglycerides (a cluster sometimes called diabetic dyslipidaemia) among individuals with type 2 diabetes.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e Nevertheless, Zheng et al posited that the association between hypertriglyceridemia and type 2 diabetes is better appreciated in the presence of poor glycaemic control. Since the participants in this present study had averagely good glycaemic control, evidenced by the Hba1c (6.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73%), it would not be out of place to get a triglyceride and HDL-C profile that are not remarkably different from those of the controls without type 2 diabetes.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAs expected, HOMA-IR, a marker of insulin resistance was higher among the cases with type 2 diabetes when compared with that of the controls. Insulin resistance is a core pathophysiological pathway in the development of type 2 diabetes mellitus.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Also, this study showed a significantly higher 10-year cardiovascular risk score among Nigerians with type 2 diabetes when compared with those without type 2 diabetes. This is not surprising because type 2 diabetes is associated with a concurrent cluster of other cardiovascular risk factors such as obesity and hypertension, as demonstrated in this study and other previous studies.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e Again, insulin resistance has been suggested as a potential culprit behind this observation.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eGoing by the results of this study, the prevalence of metabolic syndrome in people living with type 2 diabetes depends on the diagnostic criteria used. The frequency of metabolic syndrome, using the modified NCEP ATP III criteria, was 71.6%. However, the frequency was slightly lower (65.7%) when IDF criteria were applied. A previous study done among Nigerians with type 2 diabetes mellitus patients was 66.7%.\u003csup\u003e42\u003c/sup\u003e However, while the previous study used the conventional NCEP ATP III criteria, this present study used the modified NCEP ATP III criteria and this may account for the lower frequency in the previous study (66.7% vs 71.6%) as it has been suggested that the modified criteria have a better performance.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e In support of this assertion, a study done in Ethiopia that used the Modified NCEP ATP III criteria, reported a prevalence of 70.1% which is quite similar to 71.6% found in this present study. The frequency of metabolic syndrome among type 2 diabetes mellitus patients diagnosed with the IDF criteria in this present study (65.7%) is quite similar to what was found in a previous study in Nigeria that also used the IDF criteria (63.6%).\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe prevalence of metabolic syndrome is significantly higher among patients with type 2 diabetes when compared with the general population whether the modified NCEP ATP III criteria (71.6% vs 17.9%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) or the IDF criteria (65.7% vs 10.4%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) were used in making the diagnosis. A study done in Nigeria, using the IDF criteria for metabolic syndrome in the general population without type 2 diabetes mellitus, found a prevalence of 8.8% which is comparable to 10.4% documented in the present study.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e Another study done in Nigeria that used the NCEP ATP III criteria to diagnose metabolic syndrome in apparently healthy individuals not previously diagnosed with type 2 diabetes reported a prevalence rate of 12.1% which is lower than 17.9% found in this present study. This may be because while the previous study used the old NCEP ATP II criteria, the present study used the modified NCEP ATP III criteria which has been shown to have a better performance.\u003c/p\u003e \u003cp\u003eUsing point biserial correlation, there was no statistically significant association between HOMA-IR (a marker of insulin resistance) and the presence of metabolic syndrome in type 2 diabetes mellitus whether the IDF criteria (p\u0026thinsp;=\u0026thinsp;0.810) or the modified NCEP ATP III criteria (p\u0026thinsp;=\u0026thinsp;0.909) were used. There is now a paradigm shift in what is believed to be the core component of metabolic syndrome. It is now thought that waist circumference, or truncal obesity, is more important than insulin resistance in the diagnosis of metabolic syndrome and this informed the IDF criteria which insist on the presence of increased waist circumference as a prerequisite for the diagnosis of metabolic syndrome.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Interestingly, this present study found a significant association between metabolic syndrome, whether the modified NCEP ATP III or IDF criteria were used, and waist circumference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Previous studies have also demonstrated an association between metabolic syndrome and waist circumference.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis study showed a significant association between metabolic syndrome and 10-year cardiovascular risk score only when the modified NCEP ATP III criteria were used in diagnosing metabolic syndrome (p\u0026thinsp;=\u0026thinsp;0.04) although the strength of the association was weak. This association was not demonstrable using the IDF criteria. This is in keeping with the hypothesis by previous researchers that the modified NCEP ATP III criteria have a better performance than the IDF criteria.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis study was able to demonstrate an almost perfect agreement between using NCEP ATP II and IDF criteria in the diagnosis of metabolic syndrome among Nigerians with type 2 diabetes mellitus. (κ\u0026thinsp;=\u0026thinsp;0.862; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). It is still worthy of note that the IDF criteria missed 8.3% of the participants with type 2 diabetes which met the NCEP ATP criteria. However, neither NCEP ATP criteria (κ\u0026thinsp;=\u0026thinsp;0.143; p\u0026thinsp;=\u0026thinsp;0.116) nor the IDF criteria (κ\u0026thinsp;=\u0026thinsp;0.144; p\u0026thinsp;=\u0026thinsp;0.273) had a significant agreement with insulin resistance (using HOMA-IR). Again, this is in agreement with the hypothesis that insulin resistance is not a prerequisite in the diagnosis of metabolic syndrome. This study also found a fair but significant agreement between metabolic syndrome diagnosed with the modified NCEP ATP criteria (κ\u0026thinsp;=\u0026thinsp;0.213; p\u0026thinsp;=\u0026thinsp;0.029) and intermediate-to-high cardiovascular risk (using ASCVD risk categories) but this was not found with metabolic syndrome diagnosed with the IDF criteria. This suggests that the modified NCEP ATP III criteria predict cardiovascular risk much better than the IDF criteria.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eA larger sample size would be an advantage in this kind of study. The recruited cases with type 2 diabetes mellitus were already being managed in a multidisciplinary setting which may make some of the findings different from what is obtainable in the community.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCardiovascular risk factors are commoner in people living with type 2 diabetes. The prevalence of metabolic syndrome among Nigerians with type 2 diabetes is slightly lower if IDF criteria are used than if the modified NCEP ATP III criteria are used. Using the modified NCEP ATP criteria to diagnose metabolic syndrome predicts cardiovascular risk better than using the IDF criteria. IDF criteria compares well with the modified NCEP ATP III criteria but it still misses out some people. The modified NCEP ATP III criteria appears to be a better diagnostic tool for metabolic syndrome among Nigerians with type 2 diabetes mellitus.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate:\u0026nbsp;\u003c/strong\u003eEthical approval was granted by the ethical committee of the Institute Advanced Medical Research and Training with the reference number NHREC/05/01/2008a. The ethical approval number for the study was UI/EC/17/0284. Also, the recruited participants gave written informed consent to partake in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003ewas taken from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eAvailable, if required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: Self-funded\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest:\u0026nbsp;\u003c/strong\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e: None\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACC \u0026ndash; American College of Cardiology\u003c/p\u003e\n\u003cp\u003eAHA- American Heart Association\u003c/p\u003e\n\u003cp\u003eASCVD - Atherosclerotic Cardiovascular Disease\u003c/p\u003e\n\u003cp\u003eDBP \u0026ndash; Diastolic blood pressure\u003c/p\u003e\n\u003cp\u003eEGIR - European Group for the Study of Insulin Resistance\u003c/p\u003e\n\u003cp\u003eFPG \u0026ndash; Fasting plasma glucose\u003c/p\u003e\n\u003cp\u003eHbA1c -\u0026nbsp;Glycated haemoglobin\u003c/p\u003e\n\u003cp\u003eHDL-C - High density lipoprotein-cholesterol\u003c/p\u003e\n\u003cp\u003eHOMA-IR - Homeostatic model of assessment of insulin resistance\u003c/p\u003e\n\u003cp\u003eIDF \u0026ndash; International Diabetes Federation\u003c/p\u003e\n\u003cp\u003eNCEP ATP III - National Cholesterol Education Program on the detection, evaluation and treatment of high blood cholesterol in adults \u0026ndash; adults treatment panel III\u003c/p\u003e\n\u003cp\u003eSBP \u0026ndash; Systolic blood pressure\u003c/p\u003e\n\u003cp\u003eTG \u0026ndash; Fasting plasma triglycerides\u003c/p\u003e\n\u003cp\u003eWHO - World Health Organization\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eP.M. 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Obesity (Silver Spring). 2006 Apr;14(4):727\u0026ndash;36\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM. Gierach, J. Gierach, M. Ewertowska, A. Arndt, R. Junik, Correlation between Body Mass Index and Waist Circumference in Patients with Metabolic Syndrome. ISRN Endocrinology \u003cb\u003e4;2014\u003c/b\u003e, e514589 (2014 Mar)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Metabolic syndrome, diabetes mellitus type 2, comparative study, Nigeria, cardiovascular risk, diagnosis criteria","lastPublishedDoi":"10.21203/rs.3.rs-795474/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-795474/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMetabolic syndrome is associated with increased cardiovascular death. The objectives of this study were to find the frequency of metabolic syndrome among Nigerians with type 2 diabetes and to compare the modified NCEP ATP III criteria and the IDF criteria \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe study involved 134 participants. Sixty-seven were cases with type 2 diabetes while the rest were the controls without type 2 diabetes. Ethical approval was granted by the institution’s ethics review committee. Anthropometric, clinical and laboratory parameters were obtained using standard protocols. Data were analyzed with SPSS version 22. Means were compared with Student’s t test while proportions were compared with the Pearson’s chi square. Point biserial correlation was used to determine the association between the dichotomous variables and interval variables. Agreement between the criteria was tested with the Cohen’s kappa test.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eType 2 diabetes was associated with a higher prevalence of hypertension and truncal obesity. The frequency of metabolic syndrome was lower with the IDF criteria compared with the modified NCEP criteria (65.7% vs 71.6%). Although there was a strong agreement between the IDF and the modified NCEP criteria (κ=0.862; p\u0026lt;0.0001) yet, the IDF criteria missed 8.3% of diabetic individuals diagnosed with metabolic syndrome by the modified NCEP criteria. Cardiovascular risk is better predicted when the modified NCEP criteria were used to diagnose metabolic syndrome.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMetabolic syndrome is very common among Nigerians with type 2 diabetes and it is better diagnosed with the modified NCEP ATP III criteria.\u003c/p\u003e","manuscriptTitle":"Metabolic syndrome among Nigerians with type 2 diabetes mellitus: a comparative study of the diagnostic criteria.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-14 15:15:57","doi":"10.21203/rs.3.rs-795474/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"22eff03b-3347-4a7c-ac41-19a51794bbab","owner":[],"postedDate":"August 14th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":6457991,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2021-08-14T15:15:57+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-14 15:15:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-795474","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-795474","identity":"rs-795474","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}