Anthropometric Risk Factors for Metabolic Syndrome in HIV patients

FATORES DE RISCO ANTROPOMÉTRICOS PARA SÍNDROME METABÓLICA EM PACIENTES COM HIV

Abstracts

OBJECTIVE:

Metabolic syndrome, which affects the general population in epidemic proportions, is associated with a set of cardiovascular disease risk factors. The aims of this cross-sectional study were to determine the prevalence and investigate the risk factors associated with metabolic syndrome in outpatients living with HIV/AIDS using anthropometric and clinical evaluations.

METHOD:

The study was carried out on 253 HIV infected outpatients. Metabolic syndrome was classified according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATPIII) and the International Diabetes Federation (IDF) criteria. Logistic regression was used to identify factors associated with the metabolic syndrome.

RESULTS:

The prevalence of metabolic syndrome varied from 19.4% to 26.4%, according to the criterion used. The factors associated with it in the two classifications used, when adjusted by sex and BMI, were age (≥ 40years) and subscapular skinfold (> 12 mm). In the final model, using the NCEP/ATPIII criterion the risk factors associated with metabolic syndrome were age ≥ 40 years (OR = 3.18; CI95% = 1.42; 7.14) and subscapular skinfold > 12 mm (OR = 2.85, CI95% = 1.13; 7.17). In the final model, using the IDF criterion the risk factors associated with metabolic syndrome were age (OR = 3.38, CI95% = 1.61; 7.10) and subscapular skinfold > 12 mm (OR = 4.37, CI95% = 1.84; 10.39).

CONCLUSION:

In clinical practice, the regular monitoring of subscapular skinfold can help in the identification of HIV infected individuals in risk of MS.

KEYWORDS:
Metabolic Syndrome; HIV; Anthropometric

OBJETIVO:

A síndrome metabólica afeta a população em geral em proporções epidêmicas e está associada a um conjunto de fatores de risco de doenças cardiovasculares. Os objetivos deste estudo transversal foram determinar a prevalência e investigar os fatores de risco associados à síndrome metabólica em pacientes ambulatoriais afetados por HIV/AIDS usando avaliações antropométricas e clínicas.

MÉTODO:

O estudo foi realizado em 253 pacientes ambulatoriais infectados pelo HIV. A síndrome metabólica foi classificada de acordo com o National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATPIII) e os critérios da International Diabetes Federation (IDF). A regressão logística foi utilizada para identificar os fatores associados à síndrome metabólica.

RESULTADOS:

A prevalência de síndrome metabólica variou entre 19,4% e 26,4%, de acordo com o critério utilizado. Os fatores associados nas duas classificações utilizadas, quando ajustados por sexo e IMC, foram: idade (≥ 40 anos) e subescapular (> 12 mm). No modelo final, utilizando o critério do NCEP/ATPIII os fatores de risco associados à síndrome metabólica foram idade ≥ 40 anos (OR = 3,18; IC95% = 1,42; 7,14) e dobra cutânea subescapular > 12 mm (OR = 2,85, IC95% = 1,13; 7,17). No modelo final, utilizando o critério IDF os fatores de risco associados à síndrome metabólica foram idade (OR = 3,38, IC95% = 1,61; 7,10) e dobra cutânea subescapular > 12 mm (OR = 4,37, IC95% = 1,84; 10,39).

CONCLUSÃO:

Na prática clínica, o acompanhamento regular da dobra cutânea subescapular pode ajudar na identificação de indivíduos infectados pelo HIV em risco de MS.

PALAVRAS-CHAVE:
síndrome metabólica; HIV; Antropometria

INTRODUCTION

The widespread use of antiretroviral therapy for the treatment of HIV has resulted in sustained reductions of morbidity and mortality associated with the infection.¹ However, long-term toxicity is becoming recognized, and a variety of metabolic abnormalities,^2,3 as well as the antiretroviral therapy itself have also been associated with metabolic complications that may increase patients' risk of cardiovascular disease.^4-6

Metabolic syndrome (MS), which affects the general population in epidemic proportions, is associated with a set of cardiovascular disease risk factors.^7-9 HIV treatment guidelines recommend screening patients for metabolic complications and providing therapeutic interventions with the objective of preventing cardiovascular diseases.^10-11

The aims of this cross-sectional study were to determine the prevalence and investigate risk factors associated with MS in outpatients living with HIV/AIDS using anthropometric and clinical evaluations.

MATERIALS AND METHODS

Population and Study Design

This transversal study was performed on adult outpatients, in the Hospital Eduardo de Menezes-HEM, Fundação Hospitalar do Estado de Minas Gerais-FHEMIG, Belo Horizonte, Minas Gerais, Brazil. It was approved by the Ethical Review Board of the Universidade Federal de Minas Gerais (N. 0563.0.203.000-09).

The sample size (n = 1,400 inclusions) was calculated based on the total number of HIV-infected individuals who regularly attended the Infectious Diseases Service of the HEM/FHEMIG. The prevalence of metabolic syndrome in the population seen at our service ranged from 17% to 45.3%; the sample number was calculated on the basis of a prevalence of 50%, with a range of 6%, at a 95% confidence level. A minimum sample of 222 subjects was obtained. The study included HIV infected individuals who were over 18 and agreed to participate in the research through the signing of a Free and Informed Consent Agreement. Pregnant women with HIV were excluded. The subjects in this study were selected after drawing among those who were booked on the day for an appointment at the Hospital Eduardo de Menezes. All the selected subjects agreed to participate and had their data collected.

Data Collection

Data collection was performed by a single researcher, from July 2006 to August 2008. During the interviews, socio-economic, demographic and anthropometric information was obtained. Laboratory test results (CD4 cell count, viral load, serum lipids and blood glucose) performed on the date nearest the interview were collected from the medical records. All blood for tests were collected after exposure to a 12-hour fast.

Counting of T-CD4+ lymphocytes and viral load determination were performed by the Laboratory of the Fundação Ezequiel Dias, Belo Horizonte, Minas Gerais; other biochemical tests were processed the Clinical Analysis Laboratory of the HEM/FHEMIG. Counting of T-CD4+ lymphocytes was done by flow cytometry. The viral load was determined using the Versant^® HIV 1 RNA 3.0 (bDNA) (Bayer^®, Tarrytown, NY, USA) test, with a detection limit of 50 copies/ml of plasma. Plasma glucose, total cholesterol, HDL-cholesterol and triglycerides were analyzed enzymatically by colorimetric method (Vitros Chemistry Products, Johnson & Johnson Clinical Diagnostics^®, Rochester, USA).

All procedures for obtaining anthropometric measurements were carried out in accordance with standardized criteria. ¹⁵

The body circumferences were obtained using a tape to measure the patient in an upright position with the sole of the feet on the ground. The measurement of waist circumference was performed at the midpoint between the last rib and the iliac crest. In obese individuals, measurements were taken at the smaller diameter or true waist. The arm circumference was measured at the midpoint of the arm, located between the acromial process and the olecranon with the arm extended. The calf circumference was obtained at the largest circumference level of the calf, by sliding he tape upward till the largest circumference. ¹⁵

Gauging skinfold was performed with the Cescorf^® caliper (sensitivity of 0.1 mm, reading range 88 mm, pressure 10 g/mm²), Three readings of each skinfold were obtained and the averge was considered.¹⁵

The subscapularis skinfold was measured obliquely to the longitudinal axis, following the direction of the ribs and located two centimeters below the lower angle of the scapula. In situations where the location was difficult to identify, such as in obese individuals, this was done with the arm bent back. The triceps skinfold thickness was measured at the back of the arm, parallel to the longitudinal axis, at half the distance between the upper-lateral edge of the acromion and the olecranon. The biceps skinfold thickness was measured along the longitudinal axis of the arm, on its anterior face at the point of greatest apparent circumference of the biceps. The suprailiac skinfold was measured obliquely along the longitudinal axis, at half the distance between the last rib and the iliac crest, on the medial axillary line.¹⁵

Definition of Metabolic Syndrome

MS was classified according to the criteria of the National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATPIII) guidelines,¹⁶ the International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute (IDF/AHA/NHLBI).¹⁷ The criteria were specifically modified by inserting the recorded diagnosis of diabetes in lieu of high levels of fasting serum glucose, and the recorded diagnosis of hypertension in lieu of high blood pressure.

The following cutoff points for central obesity of South American populations were used: (a) waist circumference > 102 cm for men or > 88 cm for women according to the NCET/ATPIII; (b) waist circumference ≥ 90 cm for men or ≥ 80 cm for women, according to the IDF.¹⁸

Statistical Analysis

Data analysis was carried out with Stata software, version 10.0, at a 5% significance level. Categorical variables were described through frequencies. The Shapiro Wilk test was used to evaluate the normality of continuous variables that were described by means, medians and dispersion measures (25 and 75 percentiles). The χ-Squared test or the Fischer's Exact test was used to compare frequencies. To compare means, the t-Student test was used. To compare medians, the U-Mann-Whitney test was used.

Continuous variables with temporal information on infection diagnosis, antiretroviral therapy exposure and skinfold (triciptal, biciptal and subscapular) were categorized using the median as cutoff point. In terms of Body Mass Index, subjects were classified as underweight (BMI < 18.5 kg/m²), normal weight (18.5 ≤ BMI < 25 kg/m²) and overweight (BMI ≥ 25 kg/m²).¹⁵

A logistic regression model was used to evaluate the association between metabolic syndrome and other investigated variables (demographic, socio-economic, clinical, anthropometric and laboratory).¹⁹ The strength of the association was measured through Odds Ratio (OR), with 95% confidence interval (IC). The variables that presented p < 0.25 in univariate logistic regression analysis were selected for final model construction. Goodness-of-fit was verified with the Hosmer and Lemeshow statistic method. As initially noted, a p value < 0.05 was considered statistically significant.

RESULTS

Among the 253 HIV-infected individuals, the male gender corresponds to 66.4%. The mean age of the HIV-infected men and women was 41.2 ± 7.6 years (median: 40.4 years) and 41.9 ± 9.2 years (median: 41.6 years) (p = 0.53), respectively.

Illicit drug use and alcohol consumption was greater among men. The proportion of individuals not exposed to antiretrovirals was greater among women, as shown in Table 1.

Table 1
Characteristics of HIV-infected outpatients, stratified by gender

Characteristic	Total n (%)	Men n (%)	Women n (%)	p
Age (years)
< 40	105 (41,5)	73 (43.45)	32 (37,65)
≥ 40	148 (58,5)	95 (56,55)	53 (62,35)	0.37
BMI (kg/m2)
< 18.5	18 (7.2)	10 (6.0)	8 (9.5)
18.5 ≤ BMI < 25	153 (61.2)	110 (66.3)	43 (51.2)
≥ 25	79 (31.6)	46 (27.7)	33 (39.3)	0.06
Illicit drug user
No	241 (96.0)	156 (94.0)	85 (100.0)
Yes	10 (4.0)	10 (6.0)	0 (0.0)	0.02
Alcoholic beverages user
No	182 (71.9)	113 (67.3)	69 (81.2)
Yes	71 (28.1)	55 (32.7)	16 (18.8)	0.02
Current tobacco smoker
No	181 (74.1)	118 (70.2)	63 (74.1)
Yes	72 (25.9)	50 (29.8)	22 (25.9)	0.52
Duration of HIV infection (years)
< 6	124 (49.0)	83 (49.4)	41 (48.2)
≥ 6	129 (51.0)	85 (50.6)	44 (51.8)	0.86
Viral load detectable
No	154 (60.9)	102 (60.7)	52 (61.2)
Yes	99 (39.1)	66 (39.3)	33 (38.8)	0.94
Current Antiretroviral therapy
None	31 (12.4)	15 (9.0)	16 (19.2)
Without PI	120 (48.2)	88 (53.0)	32 (38.6)
With PI	98 (39.4)	63 (38.0)	35 (42.2)	0.03
Duration of antiretroviral therapy (years)
< 5	100 (45.0)	73 (47.7)	27 (39.1)
≥ 5	122 (55.0)	80 (52.3)	42 (60.9)	0.23

• BMI, Body Mass Index; PI, Protease Inhibitor

The overall prevalence of MS, according to the IDF/AHA/NHLBI and the NCEP/ATPIII criteria, was 26.4% and 19.4%, respectively. Independently of the criterion used, the prevalence of metabolic syndrome, low HDL and abdominal obesity was greater among women.

According to the IDF/AHA/NHLBI criterion, the prevalence of MS in the age group < 40 years, was 14.4% (15/104); in the age group ≥ 40 years it was 37.1% (43/116); this difference is statistically significant (p <0.005). According to the NCEP/ATPIII criterion, the respective prevalences were lower, at 10.4% (11/106) in the < 40 age group and 27.3% (33/121) in ≥ 40 age group. This difference is also significant (p = 0.001).

The men had lower BMI and skinfold measurements than women. Men also showed greater calf circumference values than women, as shown in Table 3.

Table 2
Metabolic syndrome and its defining criteria, by sex

Characteristic	Total n (%)	Men n (%)	Women n (%)	p
Metabolic syndrome (NCEP/ATPIII)
No	183 (80.6)	132 (85.2)	51 (70.8)
Yes	44 (19.4)	23 (14.8)	21 (29.2)	0.01
Metabolic syndrome (IDF/AHA/NHLBI)
No	162 (73.6)	121 (80.1)	41 (59.4)
Yes	58 (26.4)	30 (19.9)	28 (40.6)	0.002
Abdominal Obesity (NCEP/ATPIII)
No	211 (84.4)	161 (97.0)	50 (59.5)
Yes	39 (15.6)	5 (3.0)	34 (40.5)	< 0.0005
Abdominal Obesity (IDF/AHA/NHLBI)
No	151 (60.4)	130 (78.3)	21 (25.0)
Yes	99 (39.6)	36 (21.7)	63 (75.0)	< 0.0005
Hypertension
No	231 (95.8)	155 (95.1)	76 (97.4)
Yes	10 (4.2)	8 (4.9)	2 (2.6)	0.51
Diabetes
No	153 (62.7)	101 (61.6)	52 (65.0)
Yes	91 (37.3)	63 (38.4)	28 (35.0)	0.60
Low HDL (< 40 mg/dL (men) or < 50 mg/dL (women))
No	65 (38.2)	50 (43.9)	15 (26.8)
Yes	105 (61.8)	64 (56.1)	41 (73.2)	0.03
Triglycerides ≥ 150 mg/dL
No	122 (50.4)	80 (49.1)	42 (53.2)
Yes	120 (49.6)	83 (50.9)	37 (46.8)	0.55

• NCEP/ATPIII, National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATPIII); IDF/AHA/NHLBI, International Diabetes Federation and the American Heart Association/ National Heart, Lung, and Blood Institute; HDL, high-density lipoprotein

Table 3
Anthropometric characteristics of HIV-infected outpatients, stratified by gender

		Total		Men		Women
Anthropometry	n	Median(25-75%a)	n	Median(25-75%)	n	Median(25-75%)	p
BMI (kg/m2)	250	22.6 (20.5-25.7)	166	22.4 (20.4-25.3)	84	23.6 (21.4- 26.8)	0.04
Skinfold thickness (mm)
Triciptal	252	7.0 (5.0-10.0)	167	6.0 (5.0-8.0)	85	11.0 (8.0-15.0)	0.0001
Biciptal	251	4.0 (3.0-6.0)	167	3.3 (3.0-5.0)	84	6.0 (4.3-9.3)	0.0001
Suprailiac	248	7.7 (5.0-12.0)	167	6.0 (4.0-9.0)	81	13.0 (8.0-15.0)	0.0001
Subscapular	245	12.0 (8.0-16.0)	165	10.0 (7.0-15.0)	80	15.0 (12.0-20.0)	0.0001
Body Circumferences (cm)
Arm	251	28.0 ± 3.3b	167	28.5 ± 8.9	84	27.8 ± 3.9	0.10
Calf	251	34.6 ± 3.2	167	35.0 ± 2.9	84	33.8 ± 3.6	0.003
Waist	250	83.8 (78.5-89.5)	166	83.0 (78.5-89.0)	84	86.2 (79.8-94.0)	0.09

• ^a
  Percentiles; BMI, Body Mass Index;
• ^b
  Means ± DV

Table 4 shows the results of univariate logistic regression analysis of risk factors for MS. This analysis of univariate logistic regression allowed the selection and use of different variables according to the diagnostic criteria used, and the variables: age, sex, BMI, all skinfold, calf circumference and exposure to antiretroviral therapy used for the SM NCEP/ATPIII and the variables: age, sex, BMI, all skinfold, calf circumference and smoking when used the IDF/AHA/NHLBI.

Table 4
Odds ratio for characteristics associated with metabolic syndrome diagnosed according to NCEP/ATPIII and IDF/AHA/NHLBI criteria in HIV outpatients

Characteristic	Metabolic syndrome (NCEP/ATPIII)			Metabolic syndrome (IDF/AHA/NHLBI)
	No	Yes	Odds Ratio (95%CI)	No	Yes	Odds Ratio (95%CI)
Gender
Men	132	23	1	121	30	1
Women	51	21	2.36 (1.20; 4.64)	41	28	2.75 (1.47; 5.14)
Age (years)
< 40	94	11	1	89	15	1
≥ 40	88	33	3.24 (1.54; 6.80)	73	43	3.49 (1.80; 6.79)
Alcoholic beverages user
No	129	31	1	112	43	1
Yes	54	13	1.00 (0.49;2.06)	50	15	0.78 (0.40; 1.54)
Current tobacco smoker
No	126	34	1	110	46	1
Yes	57	10	0.65 (0.30; 1.41)	52	12	0.55 (0.27; 1.13)
Duration of HIV infection (years)
< 6	93	20	1	78	29	1
≥ 6	90	24	1.24 (0.64; 2.40)	84	29	0.93 (0.51; 1.69)
Viral load detectable
No	112	29	1	95	39	1
Yes	71	15	0.82 (0.41; 1.63)	67	19	0.69 (0.37; 1.30)
Current Antiretroviral therapy
None	17	8	1	17	8	1
Without PI	93	17	0.39 (0.06; 1,62)	79	26	0.70 (0.27; 1.81)
With PI	70	19	0.58 (0.21; 1.54)	64	24	0.80 (0.30; 2.09)
Duration of antiretroviral therapy (years)
Without antiretroviral therapy	17	8	1	17	8	1
< 5	77	15	0.41 (0.15; 1.13)	62	23	0.79 (0.30; 2.07)
≥ 5	89	21	0.50 (0.19; 1.32)	83	27	0.69 (0.27; 1.78)
BMI (kg/m2)			1.20 (1.09; 1.31)			1.21 (1.11; 1.32)
Triciptal Skinfold thickness
≤ 7 mm	112	17	1	103	22	1
> 7 mm	70	27	2.54 (1.29; 5.00)	58	36	2.90 (1.56; 5.40)
Biciptal Skinfold
≤ 4 mm	116	17	1	108	19	1
> 4 mm	66	27	2.79 (1.42; 5.50)	53	39	4.18 (2.20; 7.93)
Subscapular Skinfold
≤ 12 mm	111	10	1	106	12	1
> 12 mm	68	32	5.22 (2.41; 11.30)	53	43	7.17 (3.49; 4.72)

• NCEP/ATPIII, National Cholesterol Education Program Adult Treatment Panel III (NCEP/ATPIII); IDF/AHA/NHLBI, International Diabetes Federation and the American Heart Association/ National Heart, Lung, and Blood Institute; CI, Confidence Interval; BMI: Body Mass Index; PI, Protease Inhibitor

In the final model using the NCEP/ATPIII criterion, adjusted by BMI and sex, the risk factors associated with MS in HIV infected individuals were age ≥ 40 (OR = 3.18; CI95% = 1.42; 7.14) and subscapular skinfold > 12 mm (OR = 2.85, CI95% = 1.13; 7.17). In the final model using IDF/AHA/NHLBI criterion, adjusted by BMI and sex, the risk factors associated with MS in HIV infected individuals were also age > 40 (OR = 3.38, CI95% = 1.61; 7.10) and subscapular skinfold > 12 mm (OR = 4.37, CI95% = 1.84; 10.39), table 5.

Table 5
Risk Factors for Metabolic Syndrome in HIV infected outpatients

Classification		Odds Ratio(95%CI)
Metabolic syndrome (NCEP/ATPIII)a
	Age group ≥ 40	3.18 (1.42; 7.14)
	Subscapular Skinfold thickness > 12 mm	2.85 (1.13; 7.17)
Metabolic syndrome (IDF/AHA/NHLBI)b
	Age group ≥ 40	3.38 (1.61; 7.10)
	Subscapular Skinfold thickness > 12 mm	4.37 (1.84; 10.39)

• ^a,b
  Ajusted by sex and body mass index CI, Confidence Interval; NCEP/ATPIII, National Cholesterol Education Program Adult Treatment Panel III; (NCEP/ATPIII); IDF/AHA/NHLBI, International Diabetes Federation and the American Heart Association/National Heart, Lung, and Blood Institute.

DISCUSSION

In this study we note that the prevalence of MS in HIV infected outpatients varied from 19.4% to 26.4%, according to the criterion used. The factors associated with MS, when adjusted by sex and BMI, were similar in the two classifications used. For individuals infected with HIV or Aids, the variables of age (≥ 40) and subscapular skinfold (> 12 mm) were associated with MS.

Previous studies on the prevalence of MS in HIV infected individuals, carried out in Brazil, found prevalence levels that varied between 15% and 36%.^20-23 Studies performed in Brazil on non HIV infected individuals found a prevalence of MS varying from 25.4% to 30%.^24-26 Differences between the studied population groups and diagnostic criteria make it difficult to compare these reports.

In this study, the prevalence of MS, independent of the criterion used was greater among women infected with HIV. This result was also found by other investigations.^5,13,20,22

The main limitation of this study relates to the distribution of MS defining criteria that may have been underestimated through the use of secondary data. The absence of information in medical records impeded the classification of individuals that had two defining conditions for metabolic syndrome and who did not have information on seric levels of HDL or triglycerides. This could have contributed to underestimating the prevalence of MS in the population studied. This limitation has also been noted in other studies that used secondary data in the investigation of MS in HIV infected patients.^13,14,27 The fact of not having used alternative criteria for fasting glycemia, blood pressure and serum triglycerides, such as the use of antihypertensive, antidiabetic or lipid lowering drugs may also have contributed towards underestimating the distribution MS defining conditions and, consequently, its prevalence.

Other limitations that merit consideration are related to the epidemiological design. The main limitations of a cross-sectional study in identifying risk factors is the temporal bias, because the time sequence cannot be established and because of the survival bias, both of which may affect prevalence.

Regardless of the criterion used to classify MS, the ≥ 40 age group was identified as a risk factor for this syndrome. Studies had already identified age^22,28-31 and the ≥ 40 age group²⁰ as independent risk factors for MS in individuals infected with HIV. Individuals in the ≥ 40 age group who participated in this study presented a greater prevalence of obesity, diabetes and hypertension when compared with younger groups (data not shown).

In this study, a subscapular skinfold thickness > 12 mm was identified as a risk factor for MS, regardless of the criterion used. Since the two models for MS were adjusted by BMI and sex, this result cannot be attributed to the increase in body weight nor to the fact that women presented greater skinfold values when compared to the men. These results indicate that the accumulation of fat in the trunk region is an important risk factor; moreover, they are corroborated by studies, carried out by Jacobson et al.,³² which noted that the increase in the trunk fat/body fat ratio was associated with metabolic syndrome, after being adjusted for BMI and weight gain. The accumulation of fat in the trunk region has been noted in individuals infected with HIV, in the absence of clinical lipodystrophy.³³

In conclusion, Metabolic syndrome was associated with the ≥ 40 age group and with increase in subscapular skinfold thickness. In clinical practice, regular monitoring of subscapular skinfold thickness can help in the identification of HIV infected individuals at risk of MS.

REFERENCES

• ¹
  Sterne JA, Hernan MA, Ledergerber B, Tilling K, Weber R, Sendi P, et al. Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study. Lancet 2005;366(9483):378-84. http://dx.doi.org/10.1016/S0140-6736(05)67022-5
  » http://dx.doi.org/10.1016/S0140-6736(05)67022-5
• ²
  Carr A, Samaras K, Burton S, Law M, Freund J, Chisholm DJ, Cooper DA, et al. A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance in patients receiving HIV protease inhibitors. AIDS 1998;12(7):F51-8. http://dx.doi.org/10.1097/00002030-199807000-00003
  » http://dx.doi.org/10.1097/00002030-199807000-00003
• ³
  Holmberg SD, Moorman AC, Williamson JM, Tong TC, Ward DJ, Wook KC, et al. Protease inhibitors and cardiovascular outcomes in patients with HIV-1. Lancet 2002;360(9347):1747-8. http://dx.doi.org/10.1016/S0140-6736(02)11672-2
  » http://dx.doi.org/10.1016/S0140-6736(02)11672-2
• ⁴
  Mary-Krause M, Cotte L, Simon A, Partisani M, Costagliola D. Increased risk of myocardial infarction with duration of protease inhibitor therapy in HIV-infected men. AIDS 2003;17(17):2479-86. http://dx.doi.org/10.1097/00002030-200311210-00010
  » http://dx.doi.org/10.1097/00002030-200311210-00010
• ⁵
  Baum MK, Rafie C, Lai S, Xue L, Sales S, Page JB, et al. Coronary Heart Disease (CHD) Risk Factors and Metabolic Syndrome in HIV-Positive Drug Users in Miami. Am J Infect Dis 2006;2(3):173-9. http://dx.doi.org/10.3844/ajidsp.2006.173.179
  » http://dx.doi.org/10.3844/ajidsp.2006.173.179
• ⁶
  Jarret OD, Wanke CA, Ruthazer R, Bica L et al., Isaac R, Knox TA. Metabolic syndrome predicts all-Cause mortality in persons with human immunodeficiency virus. Aids Patient Care and STDs 2013;27(5):266-271. http://dx.doi.org/10.1089/apc.2012.0402
  » http://dx.doi.org/10.1089/apc.2012.0402
• ⁷
  Isomaa B, Almgren P, Tuomi T, Forsén B, Lahti K, Nissém M, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001;24(4):683-9. http://dx.doi.org/10.2337/diacare.24.4.683
  » http://dx.doi.org/10.2337/diacare.24.4.683
• ⁸
  Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 2002;288(21):2709-16. http://dx.doi.org/10.1001/jama.288.21.2709
  » http://dx.doi.org/10.1001/jama.288.21.2709
• ⁹
  Ninomiya JK, L'italien G, Criqui MH, White JL, Gamst A, Chen RS. Association of the metabolic syndrome with history of myocardial infarction and stroke in the Third National Health and Nutrition Examination Survey. Circulation 2004;109:42-6. http://dx.doi.org/10.1161/01.CIR.0000108926.04022.0C
  » http://dx.doi.org/10.1161/01.CIR.0000108926.04022.0C
• ¹⁰
  Aberg JA, Gallant JE, Anderson J, Oleske JM, Libman H, Currier JS, et al. Primary care guidelines for the management of persons infected with human immunodeficiency virus: recommendations of the HIV Medicine Association of the Infectious Diseases Society of America. Clin Infect Dis 2004;39(5):609-29. http://dx.doi.org/10.1086/423390
  » http://dx.doi.org/10.1086/423390
• ¹¹
  Dube MP, Stein JH, Aberg JA, Fichtenbaum CJ, Tashima KT, Henry WK. Guidelines for the evaluation and management of dyslipidemia in human immunodeficiency virus (HIV)-infected adults receiving antiretroviral therapy: recommendations of the HIV Medical Association of the Infectious Disease Society of America and the Adult AIDS Clinical Trials Group. Clin Infect Dis 2003;37(5):613-27. http://dx.doi.org/10.1086/378131
  » http://dx.doi.org/10.1086/378131
• ¹²
  Worm SW, Sabin CA, Reiss P, El-Sadr W, Monforte AD, Oreadier C, et al. Presence of the metabolic syndrome is not a better predictor of cardiovascular disease than the sum of its components in HIV-infected individuals: data collection on adverse events of anti-HIV drugs (D:A:D) study. Diabetes Care 2009;32(3):474-480. http://dx.doi.org/10.2337/dc08-1394
  » http://dx.doi.org/10.2337/dc08-1394
• ¹³
  Elgalib A, Aboud M, Kulasegaram R, Dimian C, Duncan A, Wierzbicki. et al. The assessment of metabolic syndrome in UK patients with HIV using two different definitions: CREATE 2 study. Curr Med Res Opin 2011;27(1):63-9. http://dx.doi.org/10.1185/03007995.2010.537212
  » http://dx.doi.org/10.1185/03007995.2010.537212
• ¹⁴
  Gazzaruso C, Sacchi P, Garzaniti A, Fratino P, Bruno R, Filice G. Prevalence of metabolic syndrome among HIV patients. Diabetes Care 2002;25(7):1253-4. http://dx.doi.org/10.2337/diacare.25.7.1253
  » http://dx.doi.org/10.2337/diacare.25.7.1253
• ¹⁵
  Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 1995;854:1-452.
• ¹⁶
  Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106(25):3143-421.
• ¹⁷
  Alberti KG, Eckel RH, Grundy SM, Cleeman JL, Donato KA, Fruchart JC, 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 2009;120(16):1640-5. DOI: 10.1161/CIRCULATIONAHA.109.192644.
  » https://doi.org/10.1161/CIRCULATIONAHA.109.192644
• ¹⁸
  Grundy SM, Cleeman JL, Daniels SR, Donato KA, Eckel, RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome/An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005; 112(17):2735-52. DOI: 10.1161/CIRCULATIONAHA.105.169404.
  » https://doi.org/10.1161/CIRCULATIONAHA.105.169404
• ¹⁹
  Lee J, Chia KS. Use of the prevalence ratio v the prevalence odds ratio as a measure of risk in cross sectional studies. Occup Environ Med 1994;51(12):841.
• ²⁰
  Diehl LA, Dias JR, Paes ACS, Thomazini MC, Garcia LR, Cinagawa E, et al. Prevalence of HIV-associated lipodystrophy in Brazilian outpatients: relation with metabolic syndrome and cardiovascular risk factors. Arq Bras Endocrinol Metabol 2008;52(4):658-67. http://dx.doi.org/10.1590/S0004-27302008000400012
  » http://dx.doi.org/10.1590/S0004-27302008000400012
• ²¹
  Werberich AP, Ceren J, Romancini JLH, Pimentel GGA, Junir MS, Pupulin ART, et al. Metabolic Syndrome in People with HIV/AIDS. World Journal Of AIDS 2013;3(4):293-97. DOI: 10.4236/wja.2013.34037
  » https://doi.org/10.4236/wja.2013.34037
• ²²
  Alvarez C, Salazar R, Galindez J, Rangel F, Castaãeda ML, Lopardo G, et al. Metabolic syndrome in HIV-infected patients receiving antiretroviral therapy in Latin America. Braz J Infect Dis 2010;14(3):256-63. http://dx.doi.org/10.1590/S1413-86702010000300010
  » http://dx.doi.org/10.1590/S1413-86702010000300010
• ²³
  Alencastro PR, Fuchs SC, Wolff FH, Ikeda ML, Brandão ABM, Barcellos NT. Independent Predictors of Metabolic Syndrome in HIV-Infected Patients. AIDS Patient Care and STDS 2011;25(11):627-634. doi:10.1089/apc.2010.0360.
  » https://doi.org/10.1089/apc.2010.0360
• ²⁴
  Marquezine GF, Oliveira CM, Pereira AC, Krieger JE, Mill JG. Metabolic syndrome determinants in an urban population from Brazil: social class and gender-specific interaction. Int J Cardiol 2008;129(2):259-65. http://dx.doi.org/10.1016/j.ijcard.2007.07.097
  » http://dx.doi.org/10.1016/j.ijcard.2007.07.097
• ²⁵
  Salaroli LB, Barbosa GC, Mill JG, Molina MC. Prevalence of metabolic syndrome in population-based study, Vitoria, ES-Brazil. Arq Bras Endocrinol Metabol 2007;51(7):1143-52. http://dx.doi.org/10.1590/S0004-27302007000700018
  » http://dx.doi.org/10.1590/S0004-27302007000700018
• ²⁶
  de Oliveira EP, de Souza ML, de Lima MD. Prevalence of metabolic syndrome in a semi-arid rural area in Bahia. Arq Bras Endocrinol Metabol 2006;50(3):456-65. http://dx.doi.org/10.1590/S0004-27302006000300008
  » http://dx.doi.org/10.1590/S0004-27302006000300008
• ²⁷
  Adeyemi O, Rezai K, Bahk M, Badri S, Thomas-Gossain N. Metabolic syndrome in older HIV-infected patients: data from the CORE50 cohort. AIDS Patient Care STDS 2008;22(12):941-5. http://dx.doi.org/10.1089/apc.2008.0119
  » http://dx.doi.org/10.1089/apc.2008.0119
• ²⁸
  Jericó C, Knobel H, Montero M, Ordoñez-Lianos J, Guelar A, Gimeno JL, et al. Metabolic syndrome among HIV-infected patients: prevalence, characteristics, and related factors. Diabetes Care 2005;28(1):132-7. http://dx.doi.org/10.2337/diacare.28.1.132
  » http://dx.doi.org/10.2337/diacare.28.1.132
• ²⁹
  Bonfanti P, Ricci E, de Socio G, Zeme D, Carradori S, Penco G, et al. Metabolic syndrome: a real threat for HIV-positive patients?: Results from the SIMONE study. J Acquir Immune Defic Syndr 2006;42(1):128-31. http://dx.doi.org/10.1097/01.qai.0000219775.20174.2d
  » http://dx.doi.org/10.1097/01.qai.0000219775.20174.2d
• ³⁰
  Bernal E, Masiá M, Padilla S, Martín-Hidalgo A, Gutiérrez F. Prevalence and characteristics of metabolic syndrome among HIV-infected patients from a Mediterranean cohort. Med Clin (Barc) 2007;128(5):172-5. http://dx.doi.org/10.1157/13098391
  » http://dx.doi.org/10.1157/13098391
• ³¹
  Squillace N, Zona S, Stentarelli C, Orlando G, Beghetto B, Nardini G. Detectable HIV viral load is associated with metabolic syndrome. J Acquir Immune Defic Syndr 2009;52(4):459-64. http://dx.doi.org/10.1097/QAI.0b013e3181b93a23
  » http://dx.doi.org/10.1097/QAI.0b013e3181b93a23
• ³²
  Jacobson DL, Tang AM, Spiegelman D, Thomas AM, Skinner S, Gorbach SL, 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). J Acquir Immune Defic Syndr 2006;43(4):458-66. http://dx.doi.org/10.1097/01.qai.0000243093.34652.41
  » http://dx.doi.org/10.1097/01.qai.0000243093.34652.41
• ³³
  Kosmiski L, Kuritzkes D, Hamilton J, Sharp T, Lichtenstien K, Hill J, et al. Fat distribution is altered in HIV-infected men without clinical evidence of the HIV lipodystrophy syndrome. HIV Med 2003;4(3):235-40. http://dx.doi.org/10.1046/j.1468-1293.2003.00151.x
  » http://dx.doi.org/10.1046/j.1468-1293.2003.00151.x

Publication Dates

• Publication in this collection
  Jul-Aug 2016

History

• Received
  21 Apr 2016
• Reviewed
  19 May 2016
• Accepted
  25 June 2016