Cardiovascular risk factors in a treatment-naïve, human immunodeficiency...

[Full title: Cardiovascular risk factors in a treatment-naïve, human immunodeficiency virus-infected rural population in Dikgale, South Africa]

[Find the meaning and references behind the names: Jean, Francis, Low, Main, Robert, Pierre, Marianne]

South African Family Practice 2014; 56(3):190–195 Open Access article distributed under the terms of the Creative Commons License [CC BY-NC-ND 4.0] http://creativecommons.org/licenses/by-nc-nd/4.0 South African Family Practice is co-published by Medpharm Publications, NISC (Pty) Ltd and Cogent, Taylor & Francis Group Introduction Human immunodefi ciency virus (HIV) is one of the greatest worldwide public health challenges. An estimated 22.5 million people lived with HIV in sub-Saharan Africa in 2007, which comprised approximately 68% of global infection 1 Cardiovascular disease (CVD) is becoming a signifi cant cause of morbidity and mortality in HIV-infected patients 2 HIV is a risk factor for CVD 3 It induces chronic infl ammation that leads to several CVD-associated risk factors, such as type 2 diabetes, insulin resistance (IR), hypertension and dyslipidaemia, 4-6 mediated by decreased adiponectin levels 6 Dyslipidaemia in HIV infection is characterised by decreased levels of total cholesterol (TC), low-density lipoprotein (LDL) cholesterol and high-density lipoprotein (HDL) cholesterol 7-10 Higher triglycerides (TG) levels were reported in advanced disease (acquired immune deficiency syndrome) 11,12 Additionally, high levels of tobacco use, alcohol consumption and lower body mass index (BMI) are associated with CVD in HIV-infected people 13-15 Studies on the lipid profi les of treatment-naïve, HIV-infected people in South Africa show contradictory results on TC and TG levels, while HDL cholesterol and LDL cholesterol levels were reported by only one study 9,16 Little is known of CVD risk factors in HIV-infected people in the rural province of Limpopo. The purpose of our study was to determine whether or not CVD risk factors were more elevated in HIV-infected than in HIV-uninfected rural people. We also determined associations between CVD risk factors and HIV and CD 4 count. We searched for major predictors of low HDL cholesterol, an independent risk factor for CVD Method Study design and setting The study was a cross-sectional, nested, case control substudy of the main project, ThePrevention, Control and Management of Chronic Disease project in a rural population, South Africa. The study was conducted in Dikgale Health and Demographic Surveillance System (HDSS) Centre, situated 50 km north east of Polokwane, the capital city of Limpopo province. There are approximately 35 000 inhabitants in the Dikgale HDSS Centre, most of whom speak Northern Sotho Study participants Eight hundred and fifteen randomly selected people participated in the main project. Participants who received pre-counselling were tested for HIV. Participants who tested S Afr Fam Pract ISSN 2078-6190 EISSN 2078-6204 © 2014 The Author(s) RESEARCH Cardiovascular risk factors in a treatment-naïve, human immunodeficiency virus-infected rural population in Dikgale, South Africa Felistas Mashinya, a * Marianne Alberts, a Robert Colebunders b and Jean-Pierre Van Geertruyden b a Department of Medical Science, Public Health and Health Promotion, School of Health Sciences, University of Limpopo b International Health Unit, Department of Epidemiology and Social Medicine, Faculty of Medicine, Antwerp University, Belgium*Corresponding author: e-mail: mashinyaf@gmail.com Objective: The objective was to determine lipid levels and cardiovascular risk factors in treatment-naïve, human immunodeficiency virus (HIV)-infected rural African people in Limpopo province Design: This was a case control study Setting and subjects: The setting was Dikgale Health and Demographic Surveillance System Centre, Limpopo province. Treatment naïve, HIV-infected and HIV-negative people participated in the study. Outcome measures: Demographic, lifestyle and chronic disease data were collected using the World Health Organization stepwise approach to surveillance (STEPS) questionnaire. Biochemical parameters were tested using standard biochemical methods. HIV testing and CD 4 counts were performed using the Alere Determine™ HIV 1/2 Ag/Ab kit and The Alere Pima™ Analyser. Insulin resistance, low-density lipoprotein cholesterol (LDL cholesterol), and non-high-density lipoprotein cholesterol (non-HDL cholesterol) levels were calculated Results: The mean age of participants (years) was 49.7 ± 16.6. More HIV-infected than HIV-uninfected women consumed alcohol (25.4% vs. 11.9%, p -value < 0.05), and the prevalence of abdominal obesity was higher in HIV-uninfected than in HIV-infected women (74.6% vs. 54.8%, p -value < 0.05). Levels of total cholesterol (TC), HDL cholesterol, non-HDL cholesterol, LDL cholesterol and apolipoprotein A 1 (ApoA 1) were significantly lower in the HIV-infected than in the HIV-uninfected group. The prevalence of low HDL cholesterol was higher in HIV-infected than in HIV-uninfected people (62.4% vs. 41.6%, p -value < 0.01). HIV infection increased the likelihood of low HDL cholesterol by 2.7 times ( p -value 0.001). Male gender and alcohol use decreased the likelihood of low HDL cholesterol by 61% ( p -value 0.002) and 48% ( p -value 0.048), respectively. HIV infection was associated with low HDL cholesterol, ApoA 1, LDL cholesterol and TC. Low CD 4 count was associated with low body mass index, LDL cholesterol and high diastolic blood pressure Conclusion: The prevalence of cardiovascular risk factors was equally high in HIV-infected and in HIV-uninfected rural people, except for low HDL and alcohol consumption, which were significantly higher in HIV-infected people, while abdominal obesity was significantly higher in HIV-uninfected people. There is a need to raise awareness of cardiovascular risk factors in rural people in Limpopo province Keywords: abdominal obesity, alcohol, diabetes, hypertension, lipids http://dx.doi.org/10.1080/20786204.2014.936665

[Find the meaning and references behind the names: Milan, Elisa, April]

S Afr Fam Pract 2014;56(3):190–195 191 HIV-positive and who were not on antiretroviral treatment according to the questionnaire formed the cases (89). The controls (178), matched for gender and age (± 2 years), were randomly selected from those who tested negative for HIV. Pregnant women were excluded from the study. Participants received information on the study prior to participation through door-to-door visits by trained fi eldworkers and signed consent forms. Despite providing consent, some participants indicated that they did not want to know their results. Consenting participants were advised of participation dates, the local venue and times a week in advance. Participants received pre-counselling from trained counsellors on the scheduled date. The HIV results were revealed in postcounselling to participants who wanted to know their status. HIV-positive participants, and those with other abnormal biochemical abnormalities parameters, were referred to the local clinic or hospital for further analysis and management. Trained fi eldworkers revisited participants and administered the questionnaire Ethical considerations Permission for the study was sought from tribal chiefs. Ethical approval was obtained from the Ethics Committee of the University of Limpopo, Medunsa Campus. Written informed consent was obtained from participants and guardians of minors (< 18 years) prior to the study Data collection The World Health Oganization (WHO) stepwise approach to surveillance (STEPS) questionnaire 17 was used to obtain information on the medical condition of the subjects. Tuberculosis and HIV information was obtained using an additional questionnaire. The data collection was conducted from August 2011 to April 2012. Anthropometric measurements Weight was measured using Omron® BF 400 (Omron Healthcare, Kyoto, Japan). Subjects were asked to take off their shoes and heavy coats. Weight was measured to the nearest 0.1 kg. Height was measured with a stadiometer. Barefoot subjects were asked to stand in an upright position. Height was measured to the nearest 0.1 cm. BMI was calculated by dividing weight (kg) by height (m 2 ). A BMI of 18.50–24.99 kg/m 2 was considered to be normal, 25–29.99 kg/m 2 overweight and ≥ 30 kg/m 2 obese 18 Waist circumference (WC) and hip circumference (HC) were measured using a measuring tape. WC was measured around the area between the last rib and the hip bone, while HC was measured around the widest part in the gluteal area. Both parameters were measured to the nearest 0.1 cm, and were used to calculate the waist to hip ratio Blood pressure measurements Blood pressure (BP) was measured using the Omron® M 5-1 (Omron Healthcare, Kyoto, Japan). The subjects were asked to sit and relax for fi ve minutes before the fi rst measurement was taken, and were restricted from talking during the measurement procedure. Three measurements were taken, with a few minutes’ break inbetween. The mean of the last two values was calculated for systolic blood pressure (SBP) and diastolic blood pressure (DBP). High BP was defi ned as SBP above 140 mmHg and/or DBP above 90 mmHg, 19 and/or a selfreported history of antihypertensive drug use Blood collection Fasting venous blood samples were drawn by registered nurses. Whole blood was used to measure CD 4 count on the day of collection. Serum from clotted blood and plasma from whole blood were separated through centrifugation at 2 000 rpm for 15 minutes. Glucose and HIV status were analysed soon after centrifugation using plasma. The remaining samples were stored at −80°C until analysis Biochemical analysis Triglycerides (TGs), TC, HDL cholesterol, glucose and creatinine levels were determined on ILab® 300 Plus Chemistry System (Instrumentation Laboratory Company, Milan, Italy). Insulin levels were measured on Beckman® Access Immunoassay System (Beckman Coulter, USA). Apolipoprotein B (ApoB), Apolipoprotein A 1 (ApoA 1) and high-sensitivity C-reactive protein (hsCRP) levels were measured on the IMMAGE® Immunochemistry System (Beckman Coulter, USA). Determine™ HIV-1/2 Ag/Ab Combo was initially used for HIV testing. Positive samples and 10% of negative samples were re-run using DoubleCheckGold™ Ultra HIV 1/2 kit. Both kits are Elisa®-based and supplied by Inverness Medical, Tokyo, Japan. CD 4 count was measured using the Pima ® Analyser (Inverness Medical, Tokyo, Japan). LDL cholesterol and IR were calculated using Friedewald 20 and homeostatic model assessment-insulin resistance 21 formulas, respectively. Non-HDL cholesterol was determined by subtracting the concentration of cholesterol in the HDL from that in the total plasma Statistical analysis Statistical analysis was performed with Statistical Package for Social Science® version 20. Variables were tested for normality using frequency histograms and line graphs. Data that were not normally distributed were logarithmically transformed for analysis. To make a comparison of group diff erences in respect of socio-demographic characteristics and lipid profi les, the independent Student’s t -test was used for continuous variables and the chi-square test for categorical variables. Normally and not normally distributed data were presented as mean ± standard deviation and median interquartile range, respectively. Bivariate correlation was used to establish associations between HIV, CD 4 count and CVD-associated risk factors. Bivariate logistic regression was used to ascertain the individual influence of CVD-associated risk factors on HDL cholesterol levels. Multivariate stepwise forward and backward regression modelling was used to determine significant predictors of low HDL cholesterol levels Results The mean age (years) of the participants was 49.7 ± 16.6. HIV-infected participants and HIV-uninfected participants had similar measurements in weight, height, BMI, WC, HC, hsCRP, insulin, DBP and SBP. Equally high prevalence rates of tobacco use (18% vs. 15.2%), IR (23.9% vs. 21.9%), hypertension (42.7% vs. 45.5%) and diabetes mellitus (13.5% vs. 13.5%) were observed between the HIV-positive and HIV-negative participants, respectively. The prevalence rate of low HDL cholesterol was signifi cantly higher in HIV-infected than in HIV-uninfected individuals (62.4% vs. 41.6%, p -value < 0.01). A signifi cantly higher percentage of HIV-positive women than HIV-negative women consumed alcohol (25.4% vs. 11.9%, p -value < 0.05), and abdominal obesity was present in a signifi cantly higher percentage of HIV-negative women (74.6 % vs. 54.8%, p -value < 0.05), while their BMI remained below the threshold of 30 (Table 1).

Cardiovascular risk factors in a treatment-naïve, human immunodefi ciency virus-infected rural population in Dikgale, South Africa 192 Total cholesterol, HDL cholesterol, non-HDL cholesterol and LDL cholesterol levels were signifi cantly lower ( p -value < 0.05) in the HIV-infected than in the control group, while no statistical diff erence was observed between TG levels (Table 2) The pattern persisted in males, while LDL cholesterol and non- HDL cholesterol levels were not signifi cantly diff erent between HIV-positive and HIV-negative females. ApoB levels were not significantly different in HIV-positive than in HIV-positive people. ApoA 1 levels were significantly lower in the HIVpositive group than in the control group. Glucose levels were signifi cantly lower in HIV-infected than in the control group ( p -value 0.04). Glucose levels remained significantly lower ( p -value 0.01) in females, while no signifi cant diff erence was observed in males HIV infection significantly correlated negatively with HDL cholesterol ( r = -0.23, p -value < 0.00), ApoA 1 ( r = -0.24, p -value 0.00), LDL cholesterol ( r = -0.18, p -value 0.00) and TC ( r = -0.23, p -value 0.00), while CD 4 count [only available for 52 participants (mean value 397 cells/μl)] signifi cantly correlated positively with BMI ( r = 0.37, p -value 0.00) and LDL cholesterol ( r = 0.30, p -value 0.03), but negatively with DBP ( r = -0.43, p -value 0.00) (Table 3) Table 1: Characteristics of human immunodeficiency virus-infected and human immunodeficiency virus-uninfected rural African people Characteristics All participants Males Females HIV-negative n = 178 HIV-positive n = 89 HIV-negative n = 52 HIV-positive n = 26 HIV-negative n = 126 HIV-positive n = 63 Age 49.7 ± 16.6 49.7 ± 16.8 54.4 ± 18.3 55 ± 18.8 47.7 ± 15.5 47.6 ± 15.6 Weight (kg) 68.3 ± 15.7 69.2 ± 17.9 66.4 ± 15.3 65.9 ± 11 69.1 ± 15.8 70.6 ± 19.9 Height (m) 1.60 ± 0.09 1.62 ± 0.09 1.66 ± 0.09 1.68 ± 0.09 1.58 ± 0.08 1.60 ± 0.08 Body mass index 26.2 ± 6.5 25.9 ± 7.2 23.7 ± 5.4 23.1 ± 5.2 27.2 ± 6.7 27 ± 7.7 WC (cm) 88.1 ± 14.4 85.5 ± 16.5 83.5 ± 13.5 80.9 ± 10.7 90.0 ± 14.3 87.3 ± 18.1 HC (cm) 102.3 ± 14.4 100.8 ± 13.5 93.8 ± 11.4 97.3 ± 7.4 105.8 ± 14.1 102.1 ± 15.2 WC to HC 0.87 ± 0.12 0.84 ± 0.09* 0.90 ± 0.15 0.83 ± 0.08* 0.85 ± 0.11 0.84 ± 0.09 DBP (mmHg) 81.8 ± 12.3 81.1 ± 15.8 83.1 ± 11.7 80.0 ± 13.2 81.3 ± 12.5 81.6 ± 16.8 SBP (mmHg) 129.5 ± 21.6 128.2 ± 24.8 136.0 ± 22.1 129.9 ± 26.4 126.8 ± 20.9 127.5 ± 24.3 Alcohol, n (%) 35 (19.7) 26 (29.2) 20 (38.5) 10 (38.5) 15 (11.9) 16 (25.4)* Tobacco use, n (%) 27 (15.2) 16 (18) 17 (32.7) 8 (30.8) 10 (7.9) 8 (12.7) IR,* n (%) 39 (21.9) 21 (23.9) 13 (25) 8(30.8) 26 (20.6) 13 (21) Hypertension,** n (%) 81 (45.5) 38 (42.7) 29 (55.8) 10 (38.5) 52 (41.3) 28 (44.4) Diabetes,*** n (%) 24 (13.5) 12 (13.5) 6 (11.5) 5 (19.2) 18 (14.3) 7 (11.1) Abdominal obesity,**** n (%) 105 (59) 36 (41.4)* 11 (21.2) 2 (8) 94 (74.6) 34 (54.8)* Low HDL cholesterol,***** n (%) 74 (41.6) 53 (62.4)** 10 (19.2) 14 (53.8)** 64 (50.8) 39 (66.1) DBP: diastolic blood pressure, HC: hip circumference, HDL: high-density lipoprotein, IR: insulin resistance, SBP: systolic blood pressure, WC: waist circumference Values are mean ± standard deviation, median interquartile range * p -value < 0.05, ** p -value < 0.01 * Insulin resistance ≥ 2.5 ** Hypertension or systolic blood pressure > 140 mmHg, diastolic blood pressure > 90 mmHg, and a history of high blood pressure *** Diabetes glucose > 7 mmol/l and a history of diabetes **** Abdominal obesity [waist circumference > 94 cm (males) and waist circumference > 80 cm (females)] ***** Low high-density lipoprotein cholesterol [high-density lipoprotein cholesterol ≤ 1.3 mmol/l (females), and high-density lipoprotein cholesterol ≤ 1.1 mmol/l (males)] Table 2: Biochemical characteristics of human immunodeficiency virus-infected and human immunodeficiency virus-uninfected rural African people Characteristics All participants Males Females HIV-negative n = 178 HIV-positive n = 89 HIV-negative n = 52 HIV-positive n = 26 HIV-negative n = 126 HIV-positive n = 63 hsCRP (mg/l) 2.32 (0.88-6.09) 1.87 (0.68-5.64) 1.86 (0.87-3.17) 3.79 (0.93-10.03) 2.81 (0.88-6.99) 1.58 (0.61-5.23) Glucose (mmol/l) 5.79 ± 2.78 5.22 ± 1.63* 5.29 ± 0.93 5.51 ± 2.13 6.00 ± 3.23 5.11 ± 1.38* Insulin (uIU/ml) 6.28 (3.27-9.42) 4.91 (2.56-9.33) 5.80 (2.74-9.63) 4.85 (2.37-15.20) 6.37 (3.43-9.43) 4.91 (3.12-9.10) TG (mmol/l) 1.18 (0.83-1.70) 1.12 (0.78-1.67) 1.29 (0.87-1.74) 1.03 (0.74-2.15) 1.14 (0.79-1.70) 1.15 (0.78-1.52) TC (mmol/l) 4.74 ± 1.15 4.16 ± 1.27* 4.74 ± 1.00 3.92 ± 1.02* 4.75 ± 1.21 4.27 ± 1.35* LDL cholesterol (mmol/l) 2.76 ± 0.95 2.37 ± 1.10* 2.69 ± 0.85 2.15 ± 1.03* 2.79 ± 0.99 2.47 ± 1.12 HDL cholesterol (mmol/l) 1.37 ± 0.35 1.17 ± 0.44* 1.39 ± 0.33 1.07 ± 0.36* 1.36 ± 0.36 1.21 ± 0.46* Non-HDL cholesterol (mmol/l) 3.38 ± 1.05 2.99 ± 1.10* 3.36 ± 0.94 2.85 ± 0.98* 3.39 ± 1.10 3.05 ± 1.15 ApoB (mg/dl) 89.0 ± 27.9 83.9 ± 24.3 85.8 ± 26.3 78.8 ± 26.7 90.3 ± 28.5 86.3 ± 23.0 ApoA 1 (mg/dl) 150.5 ± 32 133.4 ± 33.3* 153.4 ± 33.3 121.8 ± 25.8* 149.3 ± 31.4 138.5 ± 35.3* ApoA 1: apolipoprotein A 1, ApoB: apolipoprotein B, HDL: high-density lipoprotein, hsCRP: high-sensitivity C-reactive protein, LDL: low-density lipoprotein, TC: total cholesterol, TG: triglycerides Values are presented as mean ± standard deviation, median interquartile range * p -value < 0.05 Cut-offs: Low-density lipoprotein cholesterol < 3 mmol/l, total cholesterol < 5 mmol/l, and triglycerides < 1.7 mmol/l

S Afr Fam Pract 2014;56(3):190–195 193 The current study focused on HDL cholesterol levels as the latter is regarded as a signifi cant independent risk factor for CVD 2,22-24 Bivariate analysis showed that an HIV-positive person is 2.3 times more likely to have low HDL cholesterol than an HIVnegative person (Table 4). HIV infection increased the likelihood of low HDL cholesterol by 2.7 times in a multivariate analysis. Overall, HIV-positive status, gender and alcohol consumption were signifi cant predictors of low HDL cholesterol in this study Discussion The mean age (years) of the participants was 49.7 ± 16.6. There was no signifi cant diff erence in mean anthropometric values, BP measurements and insulin levels between HIV-positive and HIV-negative people. These similarities may indicate that our study population was in the early to mid stage of HIV infection, which was confirmed by the mean CD 4 count of nearly 400 cells/μl. Similarities in BMI, WC and HC between treatmentnaïve HIV-infected and HIV-uninfected people have also been observed elsewhere 25 The prevalence rates of diabetes mellitus, hypertension and IR were not diff erent between HIV-positive and HIV-negative males and females. However, overall, the prevalence rates were high, putting both HIV-positive and HIV-negative people at risk of CVD occurrence Similar prevalence rates of diabetes mellitus between treatment-naïve HIV-infected and HIV-uninfected women were reported in a menopause study, 25 and are consistent with those found in the current study. Higher prevalence rates of diabetes mellitus were reported in HIV-uninfected than in HIV-infected men (12% vs. 7%, p -value < 0.0001) by Womack et al 26 Several hypothesis have been made about the relationship between HIV and diabetes, including the chronic infl ammation state, leading to decreased adiponectin levels and IR, genetic susceptibility, obesity prevalence, sedentariness and the use of opiates 4,25,27 A significant difference in the hypertension prevalence rate between HIV-infected and HIVuninfected people was not found in this study. Similar results were reported by Baekken et al 28 Other investigators found a signifi cantly higher prevalence rate of hypertension in HIVuninfected women relative to that in HIV-infected women (31.4% vs. 20.1%, p -value < 0.001), while no significant diff erence was observed in men 29 These inconsistencies could relate to diff erences in HIV duration and diff erent populations 5 Abdominal obesity was more predominant in HIV-negative than in HIV-positive females (59% vs. 41.1%, p -value < 0.05). Although this study did not include a dietary analysis, earlier reports found that the Dikgale HDSS community consumed high carbohydrates and low-fat, low-dietary fi bre which may favour the development of abdominal obesity 30 Similarly, a study conducted in a South African rural area showed obesity to be signifi cantly more common in HIV-uninfected than in HIV-infected adults (24.5% vs. 20%, p -value < 0.001), and this difference was largely contributed by women (34% HIVuninfected vs. 23.8% HIV-infected), while obesity rates were not signifi cantly diff erent in HIV-infected and HIV-uninfected men 29 A signifi cantly higher prevalence rate of HIV-infected than HIVuninfected females consumed alcohol (25.4% vs. 11.9%, p -value < 0.05), while similar rates were observed in HIV-infected and HIV-uninfected males. Dikgale HDSS is a poor rural community, and poverty is a driver of commercial sex work for most women, exposing them to the sale of alcohol and the risk of HIV infection. Signifi cantly higher alcohol use by HIV-positive than HIV-negative women has been reported elsewhere 31 The current study observed similar tobacco usage in HIV-positive and HIV-negative males and females. Higher tobacco use in HIVpositive than in HIV-negative people was reported elsewhere 32 Table 3: Bivariate correlations of cardiovascular disease-associated factors with human immunodeficiency virus and CD 4 count HDL cholesterol ApoA 1 LDL cholesterol TC BMI DBP HIV −0.239* −0.240* −0.179* −0.225* −0.02 −0.02 CD 4 count −0.04 −0.21 0.303** 0.25 0.370 * −0.43* ApoA 1: Apolipoprotein A 1, BMI: body mass index, DBP: diastolic blood pressure, HDL: high-density lipoprotein, HIV: human immunodeficiency virus, LDL: low-density lipoprotein, TC: total cholesterol Values are correlation coefficients * p -value < 0.01, ** p -value < 0.05 Table 4: Predictors of low high-density lipoprotein cholesterol levels in participants in the Dikgale Health and Demographic Surveillance System Centre ( n = 267) Predictors Bivariate logistic regression Multivariate logistic regression OR (95% CI) p -value Adjusted OR (95% CI) p -value HIV-positive 2.33 (1.37–3.96) 0.002 2.69 (1.52–4.75) 0.001 Male 0.35 (0.20–0.62) < 0.001 0.39 (0.22–0.71) 0.002 Alcohol 0.49 (0.27–0.90) 0.02 0.52 (0.27–0.99) 0.047 WC obesity 1.63 (1–2.66) 0.05 IR 1.21 (0.67–2.16) 0.53 hsCRP 2.07 (0.97–4.40) 0.06 Hypertension 0.91 (0.56–1.48) 0.71 Smoking 0.48 (0.24–0.96) 0.04 Diabetes 0.78 (0.38–1.59) 0.49 CI: confidence interval, HIV: human immunodeficiency virus, hsCRP: C-reactive protein, IR: insulin resistance, OR: odds ratio, WC: waist circumference Values are unadjusted odds ratio (95% confidence interval) from bivariate logistic regression, and adjusted odds ratio (95% confidence interval) from multivariate stepwise forward and backward logistic regression modelling

[Find the meaning and references behind the names: Badri, Reid, Rose, Tracy, Heart, Med]

Cardiovascular risk factors in a treatment-naïve, human immunodefi ciency virus-infected rural population in Dikgale, South Africa 194 The lipid profile in HIV-infected people (89) was altered, compared to that in HIV-uninfected people (Table II). Our study showed significant decreases in TC, LDL cholesterol and HDL cholesterol in HIV-positive people compared to that in HIV-negative people. This lipoprotein pattern is associated with the potential risk of premature CVD developing 33 The dyslipidaemia caused by the eff ects of the virus itself results from the infl ammatory cytokine response to HIV infection 34,35 Several studies have reported similar decreases in TC, HDL cholesterol and LDL cholesterol, 36-39 while higher LDL cholesterol levels have been reported elsewhere 40-42 Interestingly, a study 16 conducted on urban South African women reported no significant difference in TC between treatment-naïve HIV-positive and HIV-negative women, while HDL cholesterol and LDL cholesterol were not reported. The current study observed no signifi cant diff erence in TG levels between HIV-positive and HIV-negative people for the whole group, and for males and females separately. Some studies have demonstrated disparate TG results 9,38,42 Variations in TG levels were attributed to the diff erence in degree of immunosuppression, with TG levels escalating with an increase in immunosuppression 11,43 Consistent with the current study, Baker et al 44 reported no signifi cant association between HDL cholesterol and CD 4 count. By contrast, two earlier studies by El-Sadr et al 45 and Rose et al 46 reported signifi cant associations between HDL cholesterol and CD 4 count Even though the contribution of HIV to lipid abnormalities may be diffi cult to distinguish from that of classical cardiovascular risk factors, in the current study, after controlling for the eff ect of each risk factor, the multivariate regression model indicated HIV infection, male gender and alcohol use as significant predictors of low HDL cholesterol. Having 2.8 times more likelihood of low HDL cholesterol in HIV-infected people therefore increases the risk of CVD in this HIV-infected rural population. Similarly, Oka et al 12 reported an association between HIV disease and lipid metabolism in a Japanese male population The strength of this study was that standardised techniques were used, which included the WHO STEPS questionnaire and the repeated measurement of BP and HIV, as well as the use of controls in analysing the biochemical parameters. Limitations of the study included the relatively small number of study subjects. Moreover, the sample largely comprised people living at home, thus it was skewed towards an older sedentary group. Migrant workers and people with employment were away from home when the study was conducted. This could have biased the results. A similar study is needed on the migrant population. Information on smoking and alcohol use was obtained using the WHO STEPS questionnaire, considered to be a reliable instrument. Conclusion The treatment-naïve, HIV-infected rural population in the Dikgale HDSS had significantly lower levels of TC, LDL cholesterol, HDL cholesterol and ApoA 1, but not TG, than an HIV-uninfected rural population. The study also revealed a high prevalence of CVD risk factors, such as hypertension, diabetes, IR, tobacco use and alcohol consumption in treatment-naïve, HIV-infected people, which confirms an earlier report on the general population 47 To our knowledge, this study is the fi rst to have reported on CVD risk factors in treatment-naïve, HIV-infected people in the Limpopo province. HIV outreach programmes should focus more on the management of noncommunicable diseases in rural areas where elderly people reside. Further studies on subclasses of lipoproteins may provide more in-depth knowledge of the risk of CVD in this rural population Conflict of interest — The authors declare no conflict of interest Acknowledgements — Acknowledgement is given to the fieldworkers and Dikgale HDSS team members for recruitment of the subjects and collection of the data. Gratitude is also extended to the community at Dikgale HDSS site for their collaboration during this study. We are grateful for the support of the Belgium Development Co-operation through Vlaamse Interuniversitaire Raad-University Development Cooperation (VLIR-UOS) within the framework of an institutional colla– boration between the University of Limpopo and Flemish universities References 1. Joint United Nations Programme on HIV/AIDS, World Health Organization. AIDS epidemic update. UNAIDS [homepage on the Internet]. c 2012. Available from: http://data.unaids.org/pub/ epislides/2007/2007_epiupdate_en.pdf 2. Duprez DA, Kuller LH, Tracy R, et al. Lipoprotein particle subclasses, cardiovascular disease and HIV infection. Atherosclerosis. 2009;5(1):1–6 3. Baker JV, Lundgren JD. Cardiovascular implications from untreated human immunodeficiency virus infection. Eur Heart J. 2011;32(8):945–951 4. Reid MJA, Tsima BM, Kirk B. HIV and diabetes in Africa. African Journal of Diabetes Medicine. 2012; 20(2):28–32 5. Manner IW, Baekken M, Oektedalen O, et al. Effects of HIV duration on ambulatory blood pressure in HIV-infected individuals with high office blood pressure. Blood Press. 2010;19(3):188–195 6. Palios J, Kadoglou NPE, Lampropoulous S. The pathophysiology of HIV/HAART-related metabolic syndrome leading to cardiovascular disorders: the emerging role of adipokines. Exp Diabetes Res. 2012;2012:103063 7. Rose H, Hoy J, Woolley I, et al. HIV infection and high density lipoprotein metabolism. Atherosclerosis. 2008;199(1):79–86 8. Baker JW, Ayenew H, Quick KH, et al. High-density lipoprotein particles and markers of inflammation and thrombotic activity in patients with untreated HIV infection. J Infect Dis. 2010;201(2):285–292 9. Fourie CMT, Van Rooyen JM, Kruger A, Schutte AE. Lipid abnormalities in a never-treated HIV-1 subtype C-infected African population. Lipids. 2010;45(1):73–80 10. Oka F, Naito T, Oike M, et al. Correlation between HIV disease and lipid metabolism in anti-retroviral naïve HIV infected patients in Japan. J Infect Chemother. 2011;18(1)17–21 11. Grunfeld C, Pang M, Doerrler W, et al. Lipids, lipoproteins, triglyceride clearance and cytokines in human immunodeficiency virus infection and the acquired immunodeficiency syndrome. J Clin Endocrinol Metab. 1992;74(5):1045–1052 12. Feingold KR, Krauss RM, Pang M. The hypertriglyceridemia of acquired immunodeficiency syndrome is associated with an increased prevalence of low density lipoprotein subclass B. J Clin Endocrinol Metab. 1993;76(6):1423–1427 13. Neuman T, Reinsch N, Esser S, et al. Smoking behaviour of HIV-infected patients. Health. 2010;2(8):913–918 14. Freiberg MS, McGinnis KA, Kraemer K, et al. The association between alcohol consumption and prevalent cardiovascular diseases among HIV infected and uninfected men. J Acquir Immune Defic Syndr. 2010;53(2): 247–253 15. Lemmer CE, Badri M, Visser M, Mayosi BM. A lower body mass index is associated with cardiomyopathy in people with HIV infection: evidence from a case comparison study. S Afr Med J. 2011;101(2):1–4.

[Find the meaning and references behind the names: De Boever, Liu, Man, Lopez, Rodriguez, Walsh, Kumar, Figueroa, Sarwar, Good]

S Afr Fam Pract 2014;56(3):190–195 195 16. Hattingh Z, Walsh C, Veldman FJ, Bester CJ. The metabolic profiles of HIV-infected and non-infected women in Mangaung, South Africa. S Afr J Clin Nutr. 2009;22(1):23–28 17. World Health Organization. Chronic diseases and health promotion: STEPwise approach to surveillance (STEPS). WHO [homepage on the Internet]. c 2013. Available from: http://www.who.int/chp/steps/en/ 18. World Health Organization. Physical status: the use and interpretation of anthropometry. Geneva: WHO; 1995. 19. Federation R. Risk factor: blood pressure. World Health Organization [homepage on the Internet]. c 2012. Available from: http://www. who.int/cardiovascular_diseases/en/cvd_atlas_05_HBP.pdf 20. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifugation. Clin Chem. 1972;18(6):499–502 21. Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412–419 22. Asztalos BF, Schaefer EJ. HDL in atherosclerosis: actor or bystander? Atheroscler Suppl. 2003;4(1):21–29. 23. Jericho C, Knobel H, Sorli ML, et al. Prevalence of cardiovascular risk factors in HIV-infected patients. Rev Clin Esp. 2006;206(11):556–559 24. Di Angelantonio E, Sarwar N, Perry P, et al. Major lipids, apolipoproteins and risk of vascular disease. JAMA. 2009;302(18):1993–2000 25. Howard AA, Floris-Moore M, Arnsten JH, et al. Disorders of glucose metabolism among HIV-infected women. Clin Infect Dis. 2005;40(10):1492–1499 26. Womack JA, Goulet JL, Gibert C, et al. Increased risk of fragility fractures among HIV infected compared to uninfected male veterans. PLoS One. 2011;6(2):e 17217 27. Samaras K. Prevalence and pathogenesis of diabetes mellitus in HIV-1 infection treated with combined antiretroviral therapy. J Acquir Immune Defic Syndr. 2009;50(5):499–505. 28. Baekken M, Os I, Sandvik L, Oektedalen O. Hypertension in an urban HIV positive population compared with the general population: influence of combination anti-retroviral therapy. J Hypertens. 2008;28(11):2126–2133 29. Malaza A, Mossong J, Barnighausen T, Newell M. Hypertension and obesity in a high HIV prevalence rural area in South Africa. PloS One. 2012;7(10):1–6 30. Steyn NP. Nutrition and chronic diseases of lifestyle in South Africa. South African Medical Research Council [homepage on the Internet]. c 2013. Available from: http://www.mrc.ac.za/chronic/ cdlchapter 4.pdf 31. Figueroa-Cosme WI, Lopez-Cordova NM, Capriles-Qoiros JA. Mothers of adolescents girls: comparing HIV positive and HIV negative women. Ethn Dis. 2010;20(1 Suppl 1):S 1–S 127 32. Crothers K, Goulet JL, Rodriguez-Barradas MC, et al. Impact of cigarette smoking on mortality in HIV-positive and HIV negative veterans. AIDS Educ Prev. 2009;21(3 Suppl):40–53. 33. Anastos K, Ndamage F, Lu D, et al. Lipoprotein levels and cardiovascular risk in HIV infected and uninfected Rwandan women. AIDS Res Ther. 2010;7:34 34. Oh J, Hegele RA. HIV-associated dyslipidaemia pathogenesis and treatment. Lancet Infec Dis. 2007;7(12):787–796. 35. Inankur A, Nicholls SJ, Jahangiri A. High density lipoprotein: is the good cholesterol turning bad? Curr Cardiovasc Risk Rep. 2011;5:18–28 36. Badiou S, De Boever CM, Dupuy AM, et al. Decrease in LDL size in HIV-positive adults before and after lopinavir/ritonavircontaining regimen: an index of atherogenicity? Atherosclerosis. 2003;168(1):107–113. 37. Riddle SA, Smit E, Cole SR, et al. Impact of HIV infection and HAART on serum lipids in men. JAMA. 2003;289(22):2978–2982 38. Oduola T, Akinbolade AA, Oladokun LO, et al. Lipid profiles in people living with HIV/AIDS on ARV therapy in an urban area of Osun State, Nigeria. World J Med Sci. 2009;4:18–21 39. Nguemaim NF, Mbuagbaw J, Nkoa T, et al. Serum lipid profiles in highly active antiretroviral therapy-naïve HIV-infected patients in Cameroon: a case-control study. HIV Med. 2010;11(6): 353–359 40. Tien PC, Schneider MF, Cox C, et al. HIV, HAART, and lipoprotein particle concentrations in the Women’s Interagency HIV Study. AIDS. 2010;24(18):2809–2817 41. Adewole OO, Eze S, Betiku Ye, et al. Lipid profile in HIV/AIDS patients in Nigeria. Afr Health Sci. 2010;10(2):144–149 42. Kumar A, Sathian B. Assessment of lipid profile in patients with human immunodeficiency virus (HIV/AIDS) without antiretroviral therapy. Asian Pacific Journal of Tropical Disease. 2011:24–27. 43. Armstrong C, Liu E, Grispoon S, et al. Dyslipidemia in an HIV-positive, antiretroviral treatment-naïve population in Dar es Salaam, Tanzania. J Acquir Immune Defic Syndr. 2011;57(2):141–145 44. Baker JV, Neuhaus J, Duprez D, et al. Inflammation predicts changes in high-density lipoprotein particles and apolipoprotein A 1 following initiation of antiretroviral therapy. AIDS. 2011;25(17):2133–2142 45. El-Sadr WM, Mullin CM, Gibert C, et al. Effects of HIV disease on lipid, glucose and insulin levels: results from a large antiretroviral-naïve cohort. HIV Med. 2005;6(2):114–121 46. Rose H, Woolley I, Hoy J, et al. HIV infection and high density lipoprotein: the effect of the disease vs the effect of treatment. Metabolism. 2006;55(1):90–95 47. Alberts M, Urdal P, Steyn K, et al. Prevalence of cardiovascular diseases and associated risk factors in a rural black population of South Africa. Euro J Cardiovasc Prev and Rehabil. 2005;12(4):347–354 Received: 02-04-2013 Accepted: 06-07-2013

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