Introduction: Since the advent of antiretroviral therapy, the vital prognosis of people living with HIV (PLWHA) has improved significantly. However, the risk of metabolic complications is high, thus making the bed of cardiovascular disease. Our objective was to compare the prevalence of metabolic abnormalities among PLWHA receiving ARVs to that observed in those who are not treated. Methods: We conducted a cross-sectional study (January to April 2010) at the PLWHA ambulatory care center of national university hospital (CNHU-Hubert K. Maga) in Cotonou, Bénin. We recruited 420 PLWHA (210 treated for at least 6 months and 210 untreated). We determined the prevalence of metabolic syndrome (MS) defined by the criteria of NCEP-ATP III, and the prevalence of abnormal glucose and lipid, and lipodystrophy. Association between metabolic syndrome and ARVs used was analyzed by binomial regression. Confidence intervals were calculated at 95% and 5% alpha level. Results: The prevalence of MS was 16% (18% of patients treated vs. 13% of non-treated, p = 0.18). That of hyperglycemia was 18% (30% of patients treated vs. 6% of untreated; p < 0.001) and of diabetes 7% (12% of patients treated vs 2% of untreated; p < 0.0001). The total cholesterol prevalence was 29% (44% of treated vs 13% of untreated; p <0.02). That of lipodystrophy in 210 patients was 29% (lipoatrophy16%, lipohypertrophy 8%, mixed form 6%). Factors associated with metabolic syndrome were age, hypertension, diabetes (personal or family), BMI, exposure to stavudine (OR = 1.59 [1.02 to 2.47], p = 0.04) and indinavir booted with ritonavir (OR = 2.23 [1.11 to 4 46], p = 0.02). Conclusion: The metabolic abnormalities are more common in PLWHA treated with ARVs. Preventing these anomalies should be made to the initiation of antiretroviral therapy and during the therapeutic monitoring.
Since the advent of antiretroviral therapy (ART), the vital prognosis of people living with HIV (PLWHA) have improved significantly. However, the risk of metabolic complications including metabolic syndrome is high [
1) Determine the prevalence of metabolic syndrome and other metabolic abnormalities in PLWHA treated by ART and in those who are untreated.
2) Identify factors associated to metabolic syndrome in these patients.
The work was performed at the PLWHA ambulatory care center (CTA) of national university hospital (CNHU- Hubert K. Maga) in Cotonou, Bénin. This is a cross-sectional study, descriptive and analytical, conducted from January to April 2010 within the CTA active cohorte.
Sampling: The study involved two groups of patients living with HIV: those treated with ART and those who had just been admitted to the center or that were followed but had not yet started treatment. The sample size was determined by comparison of two proportions formula and was 356 subjects. For convenience, we had successively recruited during consultations 420 patients: 210 treated with ART and 210 untreated.
Inclusion criteria: Selected patients should be 18 years or older, be regularly followed in the center; have given their informed consent to participate in the study. Those treated should have started ART for at least 6 months. Patients with a Karnofsky index <70% or suffering from any ailment requiring hospitalization and pregnant women were not included.
Demographic variables, anthropometric and lifestyles: The age, gender, tobacco and alcohol consumption were recorded by a questionnaire and patient’s clinical file. Height was measured with a wall-mounted microtoise to the nearest 0.5 cm. Weight was measured with a weighing scale in adults marque “SECA”. Body mass index (BMI) was calculated by dividing weight (kg) by the square of height (m2). The BMI was classified in accordance with the WHO classification. Waist circumference was measured midway between the inferior angle of the ribs and the suprailiac crest with a measuring tape to the nearest 1 cm.
Clinical, biological and therapeutic variables: Personal and family history of hypertension and diabetes were searched by questionnaire. The type of HIV, WHO clinical stage, CD4 count and, ART regimen and duration were obtained by patient’s clinical records. We measured Blood pressure with a mercury sphygmomanometer mark “VAQUEZ”, in the sitting position on the upper arm after-15-min rest period. A venous sample was performed in patients at baseline, before breakfast, to dose fasting glucose, triglycerides, total cholesterol, LDL cholesterol and HDL cholesterol. These samples were aliquoted and then stored in the laboratory of CTA. Laboratory tests were carried out by the enzymatic method end point in the hospital laboratory biochemistry after subjects recruitment phase. The dependent variable was the presence of metabolic syndrome. It was determined in the 2 groups.
Operational definitions: Smoking was retained if the subject claims to have an estimated smoking at least 10 pack-years and alcoholism if the daily consumption of alcoholic beverage is more than one liter in women and one and a half liters in humans. Metabolic abnormalities have been determined as follows:
・ Metabolic syndrome was defined according to the criteria of NCEP-ATP III (National Cholesterol Education Program-Adult Treatment Panel III), namely, the existence of at least 3 of 5 following criteria: waist circumference > 102 cm in women and > 88 cm for men; systolic blood pressure > 130 mmHg and/or diastolic blood pressure > 85 mmHg; a triglyceride fasting > 150 mg/dL; a cholesterol HDL < 40 mg/dL in men and <50 mg/dL in women and fasting glucose greater than or equal to 110 mg/dL [
・ Glycemic abnormalities: Hyperglycemia if fasting glucose is ≥110 mg/dL and diabetes if the fasting glucose is ≥126 mg/dL.
・ Dyslipidemia: Total Hypercholesterolemia (values ≥ 200 mg/dL), LDL Hypercholesterolemia (≥130 mg/dL), HDL hypocholesterolemia (<35 mg/dL in men and <45 mg/dL in women), hypertriglyceridemia (≥200 mg/dL).
・ The lipodystrophy was defined by the presence of at least one characteristic sign reported by the patient and confirmed by the doctor or objectified by the doctor and approved by the patient. Lipoatrophy were distinguished (thinned skin atrophy of the face, protrusion of the muscles and/or veins, flattening of the buttocks), lipohypertrophy (abdominal hypertrophy, breast, buffalo hump) or a mixed form.
Computer tools Epi Data and SAS version 9.2 (SAS Institute, Cary, North Carolina, USA) were used for codification, data entry and statistical analysis. Quantitative variables were described by calculating their mean and standard deviation. Their comparisons were made by Student’s test. By cons for qualitative variables, we determined the prevalence. The Khi2 or fischer tests were used for their comparisons. The binomial regression univariate and multivariate analysis was used to identify factors significantly associated with the metabolic syndrome. Tests were performed with a 5% significance level and a 95% confidence interval.
Participation in the study was voluntary with informed consent. Data collection sheets and blood samples were identified by an anonymous number. The lipid blood test is not part of routine examinations free and was paid by the research team. Patients in whom metabolic anomalies were observed receive a treatment or adequately monitored.
The 420 enrolled patients included 68% women: 74% in the group of subjects treated versus 61% in those untreated (p = 0.005). Their average age was 39 ± 10 years (extremes: 19 and 81 years). Patients treated were older than untreated: average age 41 ± equal 10 years versus 36 ± 10 years (p = 0.001). The majority of the subjects treated has been received for the first time in the center at clinical stage 3 or 4 WHO: 65% versus 35% (p = 0.001) with a CD4 count ≤ 200 cells/mm3: 81% versus 16%. The history and other clinical characteristics were comparable in both groups (
Of the 420 PLWHA, 66 (16%) had metabolic syndrome including 38 treated and 28 untreated subjects. The prevalence of metabolic syndrome was 18% in the group of subjects treated versus 13% in the group of untreated: OR = 1.36 [0.87 to 2.13]; p = 0.18 (
In univariate analysis, the clinical factors associated with metabolic syndrome were age, hypertension, diabetes (personal or family) and BMI (
Total enrollment n = 420 | Patients treated n = 210 | Patients untreated n = 210 | p valueμ,† | |
---|---|---|---|---|
Mean age ± SD (years) | 39 ± 10 | 41 ± 10 | 36 ± 10 | 0.001 |
Gender n (%) Male Female | 135 (32) 285 (68) | 54 (26) 156 (74) | 81 (39) 129 (61) | 0.005 |
Antecedent to admission n (%) | ||||
Alcoholism Smoking Hypertension Diabetes Family hypertension Family diabetes | 32 (8) 19 (5) 35 (8) 13 (3) 172 (41) 71 (17) | 11 (5) 7 (3) 19 (9) 8 (4) 78 (37) 37 (18) | 21 (10) 12 (6) 16 (8) 5 (2) 94 (45) 34 (16) | 0.06 0.24 0.59 0.39 0.11 0.69 |
HIV-1 n (%) | 418 (99) | 210 (100) | 208 (99) | 0.5 |
BMI (kg/m2) n (%) <25 25 - 30 ≥30 | 280 (67) 96 (23) 44 (10) | 143 (68) 48 (23) 19 (9) | 137 (65) 48 (23) 25 (12) | 0.62 |
WHO stage at admission (%) Stage 1 and 2 Stage 3 and 4 | 209 (50) 211 (50) | 73 (35) 137 (65) | 136 (65) 74 (35) | 0.001 |
Initial CD4 (cells/mm3) n (%) ≤200 200 - 350 ≥350 | 203 (48) 84 (20) 133 (32) | 170 (81) 34 (16) 6 (3) | 33 (16) 50 (24) 127 (60) | < 0.001 |
Last CD4 > 200 cells/mm3 n (%) | 329 (78) | 158 (75) | 171 (82) | 0.30 |
†: chi-square test for comparing proportions; μ: Student test for comparison of averages.
Total enrollment n = 420 | Patients treated n = 210 | Patients untreated n = 210 | value p† | |
---|---|---|---|---|
Glycemic abnormalities n (%) Hyperglycemia Diabetes | 46 (11) 29 (7) | 38 (18) 25 (12) | 8 (4) 4 (2) | <0.0001 <0.0001 |
Dyslipidemia n(%) Hyper TC Hyper LDL-C Hypo HDL-C Hyper TG | 121 (29) 156 (37) 281 (67) 8 (2) | 93 (44) 121 (78) 121 (58) 4 (2) | 28 (13) 35 (22) 160 (76) 4 (2) | 0.02 <0.0001 0.0001 1 |
Lipodystrophy n (%) Lipoatrophy Lipohypertrophy Mixedlipodystrophy | NA NA NA NA | 62 (29) 34 (16) 17 (8) 11 (5) | NA NA NA NA |
†Comparison of treated versus untreated patients; TC: Total Cholesterol; LDL-C: LDL cholesterol; HDL-C: HDL cholesterol; TG: triglycerides; NA: not applicable.
Metabolic syndrome n (%) | OR [IC‡(95%)] | Value p† | ||
---|---|---|---|---|
Yes | No | |||
Age¥ (year) | - | - | 1.03 [1.01 - 1.04] | <0.0001 |
Gender Male Female | 20 (15) 46 (16) | 115 (85) 239 (84) | 1 1.09 [0.67 - 0.87] | 0.72 |
Hypertension No Yes | 48 (12) 18 (51) | 337 (88) 17 (49) | 1 4.12 [2.72 - 6.26] | <0.001 |
Diabetes No Yes | 59 (15) 7 (54) | 348 (85) 6 (46) | 1 3.71 [2.13 - 6.47] | <0.001 |
Family Hypertension No Yes | 40 (16) 26 (15) | 208 (84) 146 (85) | 1 0.94 [0.59 - 1.48] | 0.77 |
Family diabetes No Yes | 47 (13) 19 (27) | 302 (87) 302 (87) | 1 1.98 [1.24 - 3.18] | 0.004 |
---|---|---|---|---|
Alcoholism No Yes | 57 (15) 9 (28) | 331 (85) 23 (72) | 1 1.9 [1.04 - 3.50] | 0.03 |
Smoking No Yes | 63 (16) 3 (16) | 338 (84) 16 (84) | 1 1[0.35 - 2.91] | 0.99 |
WHO Stage Stage 1 and Stage 2 Stage 3 and Stage 4 | 29 (19) 37 (18) | 180 (81) 174 (82) | 1 1.26 [0.81 - 1.98] | 0.30 |
BMI (kg/m2) <25 25-30 ≥30 | 24 (9) 23 (24) 19 (43) | 256 (91) 73 (76) 25 (57) | 1 2.80 [1.66 - 4.71] 5.04 [0.22 - 0.87] | <0.001 |
InitialCD4 (cells/mm3) ≤200 200 - 350 ≥350 | 32 (16) 9 (11) 25 (19) | 171 (84) 75(89) 108 (81) | 1 0.68 [0.34 - 1.36] 1.19 [0.74 - 1.92] | 0.3 |
Last CD4¥ (cells/mm3) | - | - | 1 [1 - 1.03] | 0.08 |
OR = Odds ratio; ‡IC (95%): confidence interval = 95%; ¥continuously variable treated; †p value of the Wald chi-square; BMI = body mass index.
Metabolic syndrome n (%) | OR [IC‡(95%)] | Valeur p† | ||
---|---|---|---|---|
Oui | Non | |||
Zidovudine No Yes | 45 (15) 21 (18) | 260 (85) 94 (23) | 1 1.24 [0.77 - 1.98] | 0.37 |
Stavudine No Yes | 249 (87) 28 (21) | 38 (13) 105 (79) | 1 1.59 [1.02 - 2.47] | 0.04 |
Didanosine No Yes | 62 (16) 4 (18) | 336 (84) 18 (82) | 1 1.17 [0.47 - 2.91] | 0.74 |
Tenofovir No Yes | 65 (16) 1 (33) | 352 (84) 2 (67) | 1 2.14 [0.42-10.7] | 0.35 |
Efavirenz No Yes | 36 (14) 30 (19) | 228 (86) 126 (81) | 1 1.41 [0.91 - 2.19] | 0.13 |
Névirapine No Yes | 55 (15) 11 (17) | 302 (85) 52 (83) | 1 1.13 [0.63 - 2.04] | 0.67 |
Nelfiavir No Yes | 62 (16) 4 (17) | 335 (84) 19 (83) | 1 1.11 [0.44 - 2.79] | 0.81 |
Indinavir + ritonavir No Yes | 60 (15) 6 (33) | 342 (85) 12 (67) | 1 2.23 [1.11 - 4.46] | 0.02 |
Lopinavir + ritonavir No Yes | 65 (16) 1 (11) | 346 (84) 8 (89) | 1 0.7 [0.11 - 4.51] | 0.71 |
OR = Odds ratio; ‡IC (95%): confidence interval = 95%; ¥continuously variable treated; †p value of the Wald chi-square for comparison of patients who have undergone at least once exposure to each molecule, versus those who have never suffered, including untreated patients.
The prevalence of metabolic syndrome in our study population, according to the NCEP-ATP III was 16%: 18% in the group treated versus 13% in untreated with no significant difference. In Africa, the frequency of metabolic syndrome varies from 10% to 21% in patients receiving ART [
Classically, age is quoted in the general population, as a cardiovascular risk factor. It is the same in PLWHA. Indeed, PLWHA, aged over 50, have a history of the disease and treatment history longer than the younger subjects and thus would develop more of metabolic abnormalities. Various studies confirm these facts [
BMI was statistically associated with the occurrence of the metabolic syndrome in our study population. Patients overweight and obese had respectively 3 and 5 times the risk of those with a weight below normal. Patients who are overweight are more wear priori to present abdominal obesity and dyslipidemia than others. However, abdominal obesity and dyslipidemia are key parameters for the diagnosis of metabolic syndrome. The relationship between BMI and the metabolic syndrome can explain this fact. It was also observed in most of the previous studies. In France, the SHIVA cohort [
Patients who consume alcohol increase 90% their risk of developing metabolic syndrome. The metabolic syndrome is associated with an inflammation of the adipose tissue with macrophage infiltration in the original hyperproduction of pro-inflammatory cytokines, an increase in the free fatty acid stream and a decrease of adiponectin, resulting hepatic lipotoxicity, or steatohepatitis [
The impact of antiretroviral therapy on the metabolic profile of PLWHA is real. Classical cardiovascular risk factors (including age, overweight, hypertension, and diabetes) and the use of certain ARVs drugs as indinavir boosted by ritonavir and stavudine predispose to the occurrence of the metabolic syndrome in these types of patients. In developing countries, in support of national programs for PLWHA the use of ARVs at high risk of metabolic disorders must definitively be ended. They also must imperatively implement prevention strategies and management of metabolic abnormalities in treated PLWHA. In doing so, we can expect long-term minimizing the risk of cardiovascular events in PLWHA.
We are grateful to the entire team Ambulatory care center for people living with HIV at CNHU-Hubert K. Maga and Dr. Idrissou Abdoulaye, head of the Laboratory of Biochemistry CNHU-Hubert K. Maga for their valuable contributions.
Djimon MarcelZannou,11,AngèleAzon-Kouanou,11,Manoela ChristelleAhomadegbe,11,Kuessi AnthelmeAgbodande,JocelynAkakpo,Comlan AlbertDovonou,Kuassi DanielAmoussou-Guenou,YessoufouTchabi,GabrielAde,FabienHoungbe, (2015) Influence of Antiretroviral Therapy on the Metabolic Profile of People Living with HIV Followed at University Hospital, Cotonou, Benin. Open Journal of Internal Medicine,05,106-114. doi: 10.4236/ojim.2015.54015