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International Journal of Endocrinology
Volume 2017, Article ID 1613657, 8 pages
Research Article

Metabolic Syndrome in People Living with Human Immunodeficiency Virus: An Assessment of the Prevalence and the Agreement between Diagnostic Criteria

1Non-Communicable Diseases Research Unit, South African Medical Research Council, Cape Town 7505, South Africa
2Department of Medicine, University of Cape Town, Cape Town 7935, South Africa
3United Nations Population Fund (UNFPA), Mildmay Uganda, P.O. Box 24985, Lweza, Uganda
4Department of Biomedical Sciences, Faculty of Health and Wellness Science, Cape Peninsula University of Technology, Cape Town 7535, South Africa
5Global Evaluation Science, Vancouver, BC, Canada V6H 3X4

Correspondence should be addressed to Kim Anh Nguyen;

Received 20 September 2016; Accepted 1 February 2017; Published 14 March 2017

Academic Editor: Andrea Tura

Copyright © 2017 Kim Anh Nguyen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Objectives. We determined metabolic syndrome (MetS) prevalence and assessed the agreement between different diagnostic criteria in HIV-infected South Africans. Method. A random sample included 748 HIV-infected adult patients (79% women) across 17 HIV healthcare facilities in the Western Cape Province. MetS was defined using the Joint Interim Statement (JIS 2009), International Diabetes Federation (IDF 2005), and Adult Treatment Panel III (ATPIII 2005) criteria. Results. Median values were 38 years (age), 5 years (diagnosed HIV duration), and 392 cells/mm3 (CD4 count), and 93% of the participants were on antiretroviral therapy (ART). MetS prevalence was 28.2% (95%CI: 25–31.4), 26.5% (23.3–29.6), and 24.1% (21–27.1) by the JIS, IDF, and ATPIII 2005 criteria, respectively. Prevalence was always higher in women than in men (all ), in participants with longer duration of diagnosed HIV (all ), and in ART users not receiving 1st-line regimens (all ). The agreement among the three criteria was very good overall and in most subgroups (all ). Conclusions. The three most popular diagnostic criteria yielded similarly high MetS prevalence in this relatively young population receiving care for HIV infection. Very good levels of agreement between criteria are unaffected by some HIV-specific features highlighting the likely comparable diagnostic utility of those criteria in routine HIV care settings.

1. Introduction

The introduction of multiple components antiretroviral therapy (ART) has led to a global decline in AIDS-related mortality among HIV-infected people, with the disease now regarded as a chronic condition. It remains, however, a major contributor to the global burden of disease, with HIV-infected individuals now succumbing to non-AIDS-related comorbidities. These are commonly associated with unhealthy lifestyle behaviours and ageing, similar to the general population, and are a testimony to the success of ART in extending lifespans. Cardiovascular diseases (CVDs) and their cardiometabolic risk factors of hypertension, type 2 diabetes mellitus (hereafter referred to as diabetes), dyslipidaemia, and obesity are rising health priorities in the HIV-infected population [1, 2]. Notably, these cardiometabolic conditions appear to be more prevalent and to occur at younger ages in the HIV-infected compared to noninfected populations [3].

Cardiometabolic diseases are known to frequently cluster with this constellation referred to as the metabolic syndrome (MetS). A diagnosis of MetS is important because it identifies individuals at increased risk for CVDs, diabetes, and all-cause mortality [4]. The pathophysiology of MetS in HIV-infected individuals is thought to be complex with HIV infection per se, prolonged use of ART drugs, and traditional CVD risk factors contributing to the process [5]. Moreover, weight gain may occur following the uptake of ART, with the use of protease inhibitors (PIs) or nucleoside reverse transcriptase inhibitors (NRTIs), in particular, leading to body fat depositions in the abdominal and dorsal regions; this may further contribute to the development of MS among HIV-infected individuals [6].

Considering the possible additional pathways, and thus the subsequent greater risk for the development of MetS in HIV-infected individuals, it is essential to determine the MetS prevalence in this population. According to a recent meta-analysis, the prevalence of MetS in the HIV-infected was 17–31% worldwide, depending on the diagnostic criteria used [7]. Although South Africa has the greatest number of HIV-infected individuals, who account for 17% of the global HIV/AIDS population [8], there is a dearth of literature on the MetS in the local HIV-infected population. Such data is required to guide the appropriate allocation of resources and the development of cost-effective therapeutic strategies and programmes for MetS care in the HIV-infected individuals. Furthermore, it underscores the importance of a holistic approach in the management of HIV-infected individuals. Thus, this study aimed to determine the MetS prevalence in HIV-infected patients receiving care at public healthcare facilities in the Western Cape Province of South Africa using various diagnostic criteria and to assess the agreement between these criteria.

2. Research Design and Methods

2.1. Study Population and Sampling

A cross-sectional study was conducted between March 2014 and February 2015 among HIV-infected men and women aged 18 years and older, who received care at primary healthcare facilities in the Western Cape. Details of the study method have been described previously [9]. In brief, the participants were sampled from 17 healthcare facilities including 10 facilities in Cape Town and seven in the surrounding rural municipalities using random sampling procedures. Patients who were pregnant or breastfeeding, bedridden, undergoing treatment for cancer, on corticosteroid treatment, unwilling, or unable to give consent were excluded from the study.

The study was approved by the South African Medical Research Council Ethics Committee and conducted in accordance with the principles of the Declaration of Helsinki. Permission to conduct the survey was obtained from the Health Research Office of the Western Cape Department of Health and the selected healthcare facilities.

2.2. Data Collection

A team of trained clinicians, nurses, and fieldworkers collected the data using questionnaires, clinical measurements, and biochemical analyses. The data were captured on personal digital assistants (PDAs), using the electronic case report forms with built-in checks for quality control. These were then encrypted at the point of collection and sent via mobile connections to a dedicated server where it was further checked, downloaded, and stored for future use. While the interviews and physical examinations were done on the day of recruitment, blood samples were taken the following day after the participant had fasted overnight.

Sociodemographic data and medical history were obtained using a structured interviewer-administered questionnaire adapted from the World Health Organization’s (WHO) STEPwise approach to Surveillance (STEPS) tool. Duration of diagnosed HIV infection, CD4 count, and ART regimens were obtained from participants’ records. The 1st-line regimen was a combination of 2 nucleoside reverse transcriptase inhibitors (2NRTIs) and a nonnucleoside reverse transcriptase inhibitor (NNRTI), while the 2nd regimens combined 2 nucleoside reverse transcriptase inhibitors (2NRTIs) and a boosted protease inhibitor (2PIs) [10].

Anthropometric measurements used standardised techniques. Heights and weights were taken with the participants in light clothing and barefooted. Waist circumference (WC) to the nearest centimetre was measured at the level of umbilicus. Blood pressure (BP) was measured on the right arm, using a digital automatic BP monitor (Omron M6 Comfort, Netherlands) after the participant was seated in a resting position for at least five minutes; three measurements were taken three minutes apart whereas the average value of the 2nd and 3rd measurements was used as BP level in the analysis.

Biochemical parameters were analyzed at an ISO 15189 accredited pathology laboratory (PathCare, Reference Laboratory, Cape Town, South Africa). Serum cholesterol and triglycerides were analyzed by enzymatic colorimetric methods; plasma glucose was measured by the hexokinase method; all are implemented using a Beckman Coulter AU 500 spectrophotometer. Insulin concentrations were measured by the chemiluminescence immunoassay method. The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated as the product of insulin (mIU/L) and glucose (mmol/L) by 22.5 [11].

2.3. Definitions of MetS

Several international organisations have proposed various definitions for MetS [12]. Those considered in the current study were the European Group for the Study of Insulin Resistance criteria (EGIR 1999) [13], ATPIII 2005 [14], IDF 2005 [15], and JIS 2009 [12], described in Table 1. Both WHO and EGIR definitions have proposed insulin resistance as a prerequisite for diagnosing the MetS. EGIR defines insulin resistance as plasma insulin levels above 75th percentile from nondiabetes populations [13] while WHO recommends the use of hyperinsulinaemic euglycaemic clamp—glucose uptake values below 25th percentile [16]. Because the hyperinsulinaemic euglycaemic clamp and urinary albumin excretion assessments were not undertaken in our study, the WHO criteria were excluded from our analysis [16].

Table 1: Criteria used for the diagnosis of the metabolic syndrome.
2.4. Statistical Analysis

The R statistical software version 3.0.3 (March 6, 2014) was used for statistical analysis. The numerical variables are expressed as means (±SD) or medians (25th–75th percentiles) and categorical variables as counts and percentages. Groups’ comparison used the Mann–Whitney U test and chi-square test as appropriate. The agreement between the diagnostic criteria for the MetS was assessed with the use of the kappa statistics. Kappa statistics values are interpreted as poor (), fair (0.2 < kappa ), moderate (0.4 < kappa ), substantial (0.6 < kappa ), and very good () [17]. In the main analysis, we determined the prevalence of the MetS by the ATPIII 2005, the IDF, and the JIS criteria and assessed the agreement between these three criteria. The criteria were then expanded to include the EGIR criteria in secondary analyses of a subsample of participants with data available on insulin resistance. A value of 0.05 is considered statistically significant.

3. Results

3.1. Characteristics of the Participants

Of the 831 participants recruited, 748 had complete data on all components of the MetS and are included in the present analyses. As presented in Table 2, 79% (591 participants) of the sample consisted of women. The median age of the participants was 38 years (25th–75th percentiles: 32–44), with men significantly older than women (41 years versus 37 years, ). The median duration of diagnosed HIV infection was 5 years (25th–75th percentiles: 2–9) with women diagnosed longer than men (5 years versus 4 years, ). The median CD4 count was 392 cells/mm3 (25th–75th percentiles: 240–604) with counts higher in women (410 cells/mm3, 253–627) compared to men (272 cells/mm3, 193–448), . Most participants (93%) were on ART, with the majority being 1st-line ART users (61%) and the distribution of ART regimens differing in men and women (). Compared with men, women were more likely to have greater BMI, waist circumference, total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and HOMA index (all ) but had a lower waist-to-hip ratio (WHR), systolic BP, triglycerides (TGs), and fasting plasma glucose (FPG) levels (all ).

Table 2: Characteristics of the HIV-infected participants.
3.2. Prevalence of the Metabolic Syndrome by the JIS, IDF, and ATPIII 2005 Criteria

The prevalence of MetS (95%CI) by the JIS, IDF, and ATPIII 2005 criteria was 28.2% (25–31.4), 26.5% (23.3–29.6), and 24.1% (21–27.1), respectively (Table 3). The MetS prevalence was significantly higher in women compared to men across the three criteria (all ): JIS (31.3% versus 16.6%), IDF (30.5% versus 11.5%), and ATPIII 2005 (26.9% versus 13.4%).

Table 3: Prevalence (95% confidence interval) of the metabolic syndrome by the JIS, IDF, and ATPIII 2005 criteria presented by gender and HIV-related subgroups.

The prevalence of MetS by the HIV-related characteristics is also presented in Table 3. MetS prevalence was higher in participants with ≥5 years’ compared with <5 years’ duration of diagnosed HIV infection (all ): JIS (32.6% versus 22.5%), IDF (30.5% versus 21%), and ATPIII 2005 (28.8% versus 17.9%). With regard to ART use, the prevalence of MetS in the 46 participants who were not on ART was 34.8% (21–48.6) by the JIS and 32.6% (19.1–46.2) by the IDF and ATPIII 2005 criteria. This was not significantly different compared to those on ART (all ). Across the three criteria by ART regimens, participants on 1st-line ART regimens had lower MetS prevalence compared with 2nd line or other regimens, (all ). There was a trend towards higher MetS prevalence with CD4 cells/mm3 compared with <392 cells/mm3. However, these were not significantly different by any of the three criteria (all ): JIS (32.6% versus 25.3%), IDF (32.1% versus 24.7%), and ATPIII 2005 (29.4% versus 21.0%).

3.3. Concordance between Different MetS Criteria

The concordance between the JIS, IDF, and ATPIII 2005 MetS criteria overall and by subgroups is shown in Table 4. The overall agreement was very good with a kappa of 0.96 (95%CI: 0.93–0.98) between the JIS and IDF criteria, 0.89 (95%CI: 0.86–0.93) between the JIS and ATPIII 2005 criteria, and 0.84 (95%CI: 0.80–0.89) between the IDF and ATPIII 2005 criteria. Similarly, high levels of agreement were found in women, by subgroups of diagnosed HIV infection duration, CD4 count, and ART regimens. The level of concordance in men was very good between the JIS and ATPIII 2005 criteria [kappa 0.88 (0.77–0.98)] but lower between the JIS and IDF criteria [kappa = 0.79 (0.65–0.93)] and the IDF and ATPIII 2005 criteria [0.62 (0.43–0.81)].

Table 4: Kappa statistics and 95% confidence interval for the concordance between the JIS, IDF, and ATPIII 2005 metabolic syndrome criteria presented by gender and HIV-related subgroups ().
3.4. Secondary Analyses in Participants with Insulin Resistance Data

In the subgroup of participants with data available on insulin resistance (), the prevalence of MetS and the agreement between the JIS, IDF, and ATPIII 2005 criteria, overall and within subgroups, were mostly similar to those observed in the main analysis (see Table S1 and Table S2 in Supplementary Material available online at In this subsample, the prevalence of MetS according to the EGIR criteria was as follows: overall: 12.4%; men versus women: 6.7% versus 13.9%, ; shorter versus longer duration of diagnosed HIV infection: 9.5% versus 15.2%, ; CD4 cells/mm3 versus ≥392 cells/mm3: 7.9% versus 17.2, ; and ART regimens: 10.1% (1st line), 19.4% (2nd line), and 14.4% (other regimens) () (Table S1). The agreement between EGIR and the other criteria was at most fair: EGIR versus JIS 0.33 (0.25–0.40); EGIR versus IDF 0.32 (0.24–0.40); and EGIR versus ATPIII 2005 0.38 (0.30–0.46) (Table S2).

4. Discussion

In the present study among HIV-infected participants who were mostly on ART, we found that (1) the prevalence of MetS was high based on the JIS, IDF, and ATPIII 2005 criteria but much lower by the EGIR criteria; (2) across the MetS definitions, the prevalence appeared to be higher among women, participants with longer duration of diagnosed HIV infection, and ART users not receiving 1st-line regimens but was mostly unaffected by CD4 count levels; and (3) the agreement between the JIS, IDF, and ATPIII 2005 was very good overall and in most subgroups, while the agreement of the three criteria with EGIR was generally fair.

4.1. MetS Prevalence by Different Criteria in the HIV-Infected Population

The prevalence of the MetS in this study by the different criteria was in line with the findings of a recent meta-analysis which revealed that nearly one-third of global HIV-infected populations have the MetS [7]. Compared with other criteria, the JIS identified the most participants with MetS, which was not surprising. The higher thresholds for WC in the ATPIII 2005 and the mandatory use of WC in the IDF criteria likely ruled out the participants diagnosed with MetS by the JIS criteria but who did not qualify for central obesity based on the IDF or ATPIII criteria. Similarly, the presence of insulin resistance and the higher thresholds for TG and FPG, as well as lower thresholds for HDL-C in women in the EGIR criteria, would explain the differences in the magnitude of MetS prevalence between EGIR and the three other set of criteria.

4.2. Comparison of MetS Prevalence in the HIV-Infected and General Populations

The MetS prevalence in this study was within the range of 17–46% published in the general population internationally [1820] and locally [21, 22]. Studies on the epidemiology of MetS in South Africa have provided the prevalent rates of 30.7% in urban black residents of Cape Town [22] and 26.5% in black adults in rural KwaZulu-Natal with the JIS criteria [21]. Using the JIS, IDF, and ATPIII 2001 criteria, and in a much older (mean age of 51 years) and highly obese urban colored population in Cape Town, Erasmus and coworkers found MetS prevalence of 62%, 60.6%, and 55.4%, respectively [23].

The higher prevalence of MetS among women compared to men in this study is consistent with the recent meta-analysis of MetS in people with HIV infection [7], and in line with the prevalence reports of MetS in the general population [2123]. Notably, the similarities in prevalent MetS between young HIV-infected people and a much older general population suggest the likely comparable risk of developing MetS-related conditions such as CVDs and diabetes in people with HIV infection, but at a much younger age.

4.3. MetS Prevalence and HIV-Related Characteristics

Higher prevalence of MetS was found among participants with longer duration of diagnosed HIV infection and ART users who were not on 1st-line regimens. These associations may in part be explained by older age and drug-related toxicity secondary to prolonged use of ART [24] or the 2nd-line regimens that contain protease inhibitors (PIs). Results of clinical trials suggest that PI-based regimens accelerate the progression of MetS, likely via chronic inflammation and incomplete restoration of the immune system after commencing ART [25, 26]. The lack of effect of CD4 count or ART use, mainly with 1st-line regimens, on the presence of MetS reported in this study, mirrors the results of a recent meta-analysis [7]. It is of note however that the effect of CD4 count was explored in a relatively small sample, with a possibility of low statistical power.

4.4. Agreement between Sets of Criteria

In the present study, the agreement between JIS, IDF, and ATPIII 2005 criteria was generally good, implying that with the exception of some subgroups, these sets of criteria generally classify the same individuals as having MetS, or ruled out the diagnosis in the same people. This is not surprising since all three criteria are based on the same components although not always with the same threshold for waist circumference. Generally, the agreement between EGIR and other three criteria was at most fair. The key feature explaining the low agreement was the use of insulin resistance as a criterion in the EGIR definition.

Only two studies have previously assessed the agreement between MetS criteria in HIV-infected people, and these have provided findings mostly in line with ours. Ayodele and colleagues reported a very good agreement between JIS and IDF criteria (kappa = 0.88) [27], whereas the agreement between IDF and EGIR was fair (kappa = 0.30) in the report by Cubero and coworkers [28].

The degree of agreement between the JIS, IDF, and ATPIII 2005 criteria in this study is consistent with data from studies conducted in general populations in Africa [21, 23, 29, 30] and other parts of the world [3133] with the agreement being better in women than in men [29, 30, 33]. Furthermore, the agreement in our sample was unaffected by HIV-specific characteristics, supporting the comparable diagnostic performance of the commonest sets of diagnostic criteria for MetS in a broader population of people with HIV infection and across the continuum of HIV care.

4.5. Strengths and Limitations

The present study has some limitations. The relatively fewer men and ART-naïve participants may lead to unstable estimates of MetS prevalence in these subgroups. The absence of an HIV-negative subgroup limits the direct comparison of our findings with those in the general population. In addition, missing data on HIV-related variables did not allow us to perform a regression analysis, which limited the identification of HIV-specific associations with MetS in our study.

Considering that most HIV-related studies in Africa are single-clinic-based, a major strength of this study is the inclusion of multiple healthcare facilities. Moreover, the included healthcare facilities, selected using random sampling methods, were based in both urban and rural areas known to influence MetS prevalence. This allows for the generalizability of the results to other South African HIV-infected population. Furthermore, this study has provided the most comprehensive analysis of the agreement between MetS diagnostic criteria in people with HIV infection.

5. Conclusions

This study has reported a high prevalence of MetS according to the three recent criteria in young adult South Africans with HIV infection, and the likely influence of some, but not all, HIV-related characteristics on the estimates. The very good agreement between these sets of criteria suggests that their sequential application is unlikely to explain differences in MetS prevalence in HIV-infected people across settings and time periods, nor would result in substantial mismatch of individuals’ MetS status if these criteria were applied interchangeably in routine settings for the purpose of risk screening and reduction. However, previous studies have advised against uncritical application to the general population in Africa, of internationally advocated diagnostic thresholds for some common parameters to these criteria such as WC, as this could lead to unacceptable MetS risk stratification. Extending these investigations to people with HIV infection should be part of future efforts to promote MetS screening in HIV-infected population in Africa using any of the set of criteria applied in the current study.


The founding bodies had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; and in the decision to publish the results.

Conflicts of Interest

The authors declare no conflict of interest.

Authors’ Contributions

Andre Pascal Kengne, Edward J. Mills, and Barbara Mukasa conceived the study and acquired the funding. Anniza de Villiers operationalized and supervised the data collection in collaboration with Tandi E. Matsha, Kim Anh Nguyen, and Nasheeta Peer who analyzed the data and drafted the manuscript. All coauthors substantially revised the manuscript and approved the submission.


The survey was funded by a grant from the Grand Challenge Canada, through the Global Alliance on Chronic Diseases initiative. Kim Anh Nguyen is supported by the NRF Innovation Doctoral Research Scholarship, Doctoral Scholarship, and Yeoman Bequest Bursary through the University of Cape Town.


  1. F. J. Palella Jr, R. K. Baker, A. C. Moorman et al., “Mortality in the highly active antiretroviral therapy era: changing causes of death and disease in the HIV outpatient study,” Journal of Acquired Immune Deficiency Syndromes, vol. 43, no. 1, pp. 27–34, 2006. View at Publisher · View at Google Scholar · View at Scopus
  2. R. Weber, M. Ruppik, M. Rickenbach et al., “Decreasing mortality and changing patterns of causes of death in the Swiss HIV cohort study,” HIV Medicine, vol. 14, no. 4, pp. 195–207, 2013. View at Publisher · View at Google Scholar · View at Scopus
  3. F. M. Islam, J. Wu, J. Jansson, and D. P. Wilson, “Relative risk of cardiovascular disease among people living with HIV: a systematic review and meta-analysis,” HIV Medicine, vol. 13, no. 8, pp. 453–468, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. A. S. Gami, B. J. Witt, D. E. Howard et al., “Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies,” Journal of the American College of Cardiology, vol. 49, no. 4, pp. 403–414, 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. A. A. Paula, M. C. Falcao, and A. G. Pacheco, “Metabolic syndrome in HIV-infected individuals: underlying mechanisms and epidemiological aspects,” AIDS Research and Therapy, vol. 10, no. 1, p. 32, 2013. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Grinspoon and A. Carr, “Cardiovascular risk and body-fat abnormalities in HIV-infected adults,” The New England Journal of Medicine, vol. 352, no. 1, pp. 48–62, 2005. View at Publisher · View at Google Scholar · View at Scopus
  7. K. A. Nguyen, N. Peer, E. J. Mills, and A. P. Kengne, “A meta-analysis of the metabolic syndrome prevalence in the global HIV-infected population,” PloS One, vol. 11, no. 3, Article ID e0150970, 2016. View at Publisher · View at Google Scholar · View at Scopus
  8. C. J. Murray, K. F. Ortblad, C. Guinovart et al., “Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013,” Lancet, vol. 384, no. 9947, pp. 1005–1070, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. K. A. Nguyen, N. Peer, A. de Villiers et al., “The distribution of obesity phenotypes in HIV-infected African population,” Nutrients, vol. 8, no. 6, 299 pages, 2016. View at Publisher · View at Google Scholar · View at Scopus
  10. WHO, HIV/AIDS: Summary of New Recommendations-Consolidated ARV Guidelines, June 2013,
  11. D. R. Matthews, J. P. Hosker, A. S. Rudenski, B. A. Naylor, D. F. Treacher, and R. C. Turner, “Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man,” Diabetologia, vol. 28, no. 7, pp. 412–419, 1985. View at Publisher · View at Google Scholar · View at Scopus
  12. K. G. Alberti, R. H. Eckel, S. M. Grundy et al., “Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity,” Circulation, vol. 120, no. 16, pp. 1640–1645, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. B. Balkau and M. A. Charles, “Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR),” Diabetic Medicine, vol. 16, no. 5, pp. 442–443, 1999. View at Publisher · View at Google Scholar · View at Scopus
  14. S. M. Grundy, J. I. Cleeman, S. R. Daniels et al., “Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement,” Circulation, vol. 112, no. 17, pp. 2735–2752, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. K. G. Alberti, P. Zimmet, and J. Shaw, “The metabolic syndrome--a new worldwide definition,” Lancet (London, England), vol. 366, no. 9491, pp. 1059–1062, 2005. View at Publisher · View at Google Scholar · View at Scopus
  16. K. G. Alberti and P. Z. Zimmet, “Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation,” Diabetic Medicine, vol. 15, no. 7, pp. 539–553, 1998. View at Publisher · View at Google Scholar
  17. J. R. Landis and G. G. Koch, “The measurement of observer agreement for categorical data,” Biometrics, vol. 33, no. 1, pp. 159–174, 1977. View at Publisher · View at Google Scholar
  18. S. M. Grundy, “Metabolic syndrome pandemic,” Arteriosclerosis, Thrombosis, and Vascular Biology, vol. 28, no. 4, pp. 629–636, 2008. View at Publisher · View at Google Scholar · View at Scopus
  19. W. H. Pan, W. T. Yeh, and L. C. Weng, “Epidemiology of metabolic syndrome in Asia,” Asia Pacific Journal of Clinical Nutrition, vol. 17, Suppl 1, pp. 37–42, 2008. View at Google Scholar
  20. F. Marquez-Sandoval, G. Macedo-Ojeda, D. Viramontes-Hörner, J. D. Fernández Ballart, J. Salas Salvadó, and B. Vizmanos, “The prevalence of metabolic syndrome in Latin America: a systematic review,” Public Health Nutrition, vol. 14, no. 10, pp. 1702–1713, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. A. A. Motala, T. Esterhuizen, F. J. Pirie, and M. A. Omar, “The prevalence of metabolic syndrome and determination of the optimal waist circumference cutoff points in a rural South African community,” Diabetes Care, vol. 34, no. 4, pp. 1032–1037, 2011. View at Publisher · View at Google Scholar · View at Scopus
  22. N. Peer, C. Lombard, K. Steyn, and N. Levitt, “High prevalence of metabolic syndrome in the Black population of Cape Town: the Cardiovascular Risk in Black South Africans (CRIBSA) study,” European Journal of Preventive Cardiology, vol. 22, no. 8, pp. 1036–1042, 2015. View at Publisher · View at Google Scholar · View at Scopus
  23. R. T. Erasmus, D. J. Soita, M. S. Hassan et al., “High prevalence of diabetes mellitus and metabolic syndrome in a South African coloured population: baseline data of a study in Bellville Cape Town,” South African Medical Journal, vol. 102, no. 11 Pt 1, pp. 841–844, 2012. View at Publisher · View at Google Scholar · View at Scopus
  24. J. A. Dave, E. V. Lambert, M. Badri, S. West, G. Maartens, and N. S. Levitt, “Effect of nonnucleoside reverse transcriptase inhibitor-based antiretroviral therapy on dysglycemia and insulin sensitivity in South African HIV-infected patients,” Journal of Acquired Immune Deficiency Syndromes, vol. 57, no. 4, pp. 284–289, 2011. View at Publisher · View at Google Scholar · View at Scopus
  25. D. L. Jacobson, A. M. Tang, D. Spiegelman et al., “Incidence of metabolic syndrome in a cohort of HIV-infected adults and prevalence relative to the US population (National Health and Nutrition Examination Survey),” Journal of acquired immune deficiency syndromes (1999), vol. 43, no. 4, pp. 458–466, 2006. View at Publisher · View at Google Scholar · View at Scopus
  26. S. Krishnan, J. T. Schouten, B. Atkinson et al., “Changes in metabolic syndrome status after initiation of antiretroviral therapy,” Journal of Acquired Immune Deficiency Syndromes (1999), vol. 68, no. 1, pp. 73–80, 2015. View at Publisher · View at Google Scholar · View at Scopus
  27. O. E. Ayodele, A. O. Akinboro, S. O. Akinyemi et al., “Prevalence and clinical correlates of metabolic syndrome in Nigerians living with human immunodeficiency virus/acquired immunodeficiency syndrome,” Metabolic Syndrome and Related Disorders, vol. 10, no. 5, pp. 373–379, 2012. View at Publisher · View at Google Scholar · View at Scopus
  28. J. M. Cubero, P. Domingo, M. Sambeat et al., “Prevalence of metabolic syndrome among human immunodeficiency virus-infected subjects is widely influenced by the diagnostic criteria,” Metabolic Syndrome and Related Disorders, vol. 9, no. 5, pp. 345–351, 2011. View at Publisher · View at Google Scholar · View at Scopus
  29. A. P. Kengne, S. N. Limen, E. Sobngwi, C. F. Djouogo, and C. Nouedoui, “Metabolic syndrome in type 2 diabetes: comparative prevalence according to two sets of diagnostic criteria in sub-Saharan Africans,” Diabetology and Metabolic Syndrome, vol. 4, no. 1, 22 pages, 2012. View at Publisher · View at Google Scholar · View at Scopus
  30. C. Kelliny, J. William, W. Riesen, F. Paccaud, and P. Bovet, “Metabolic syndrome according to different definitions in a rapidly developing country of the African region,” Cardiovascular Diabetology, vol. 7, no. 1, 27 pages, 2008. View at Publisher · View at Google Scholar · View at Scopus
  31. A. S. Can and T. P. Bersot, “Analysis of agreement among definitions of metabolic syndrome in nondiabetic Turkish adults: a methodological study,” BMC Public Health, vol. 7, no. 1, 353 pages, 2007. View at Publisher · View at Google Scholar · View at Scopus
  32. M. A. Saad, G. P. Cardoso, A. Martins Wde, L. G. Velarde, and R. A. Cruz Filho, “Prevalence of metabolic syndrome in elderly and agreement among four diagnostic criteria,” Arquivos Brasileiros de Cardiologia, vol. 102, no. 3, pp. 263–269, 2014. View at Google Scholar
  33. A. Alkerwi, A. F. Donneau, N. Sauvageot et al., “Prevalence of the metabolic syndrome in Luxembourg according to the Joint Interim Statement definition estimated from the ORISCAV-LUX study,” BMC Public Health, vol. 11, no. 1, 4 pages, 2011. View at Publisher · View at Google Scholar · View at Scopus