Journal of Clinical Research in HIV AIDS and Prevention
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Research Article | Open Access
  • Available online freely | Peer Reviewed
  • Physical Activity and Risk Factors Screening for Ischaemic Heart Disease in South African Individuals Living with HIV

    Ronel Roos 1       Hellen Myezwa 1     Helena van Aswegen 1     Eustatius Musenge 2    

    1University of the Witwatersrand, Faculty of Health Sciences, Department of Physiotherapy

    2University of the Witwatersrand, Faculty of Health Sciences, School of Public Health, Division of Epidemiology and Biostatistics

    Abstract

    People living with HIV (PLWH) are at risk of developing chronic lifestyle diseases such as ischaemic heart disease (IHD). Physical inactivity is a modifiable risk factor for IHD. The level of ambulation physical activity in individuals living with HIV in a South African context is unknown. The aim of this study was to assess the physical activity levels and other risk factors for IHD in PLWH on antiretroviral therapy (ARV). An observational study was conducted from October 2010 to June 2012 at an outpatient clinic in Johannesburg, South Africa. Two hundred and five individuals who were on ARV for 6-12 months were screened. Physical activity was measured with the Yamax SW200 pedometer over a seven day period. Physical activity of the sample was reduced at 7673.2 (±4017.7) steps/ day with women walking less than men 6993.3 (±3462.6) and 10076.3 (±4885.6)respectively. Body mass index was increased to 25.6 (±5.4) kg/m2 with women noted to be overweight [26.6 (±5.5) kg/m2]. Independent predictors of being overweight were systolic blood pressure, waist and hip circumference, CD4 count and daily fruit and vegetable intake. Smoking was less common in the study population with 16.1% of the sample being current smokers and 25.9% former smokers. Individuals’ mean perceived stress levels were 19.9 (±7.8) on the Cohen’s Perceived Stress Scale. The ambulation physical activity level of individuals living with HIV requires modification to assist with reducing risk factors of IHD.

     

    Received 17 Apr 2013; Accepted 27 Jan 2016; Published 05 Feb 2016;

    Academic Editor:Christophe Marchand, Staff Scientist Laboratory of Molecular Pharmacology Center for Cancer Research National Cancer Institute Bethesda, US.

    Checked for plagiarism: Yes

    Review by: Single-blind

    Copyright©  2016 Ronel Roos, et al.

    License
    Creative Commons License    This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Competing interests

    The authors have declared that no competing interests exist.

    Citation:

    Ronel Roos, Hellen Myezwa, Helena van Aswegen, Eustatius Musenge (2016) Physical Activity and Risk Factors Screening for Ischaemic Heart Disease in South African Individuals Living with HIV. Journal of Clinical Research In HIV AIDS And Prevention - 2(3):50-61.
    Download as RIS, BibTeX, Text (Include abstract )
    DOI10.14302/issn.2324-7339.jcrhap-13-255

    Introduction

    People living with the human immunodeficiency virus (HIV) (PLWH) are living longer since the introduction of antiretroviral therapy (ARV) 1. South Africa's health care face a quadruple burden of disease between chronic lifestyle diseases, HIV, perinatal and maternal disease and violence related injuries 2, 3. An estimated 17.3% of South Africans were living with HIV according to the 2011 World prevalence rates of HIV and only Swaziland, Botswana and Lesotho reported higher statistics 4. South Africa has managed to increase the roll-out of ARV and two million individuals are on ARV currently 5. This increase in ARV roll-out could alter the future causes of mortality in South Africa shifting the focus from communicable diseases to a more pronounced non-communicable diseases pattern such as ischaemic heart disease (IHD) and/or stoke.

    Chronic lifestyle diseases are of concern as mortality in individuals living with HIV is slowly shifting to non-aids related illnesses such as cardiovascular disease 6, 7. This shift could partially be explained by the prevalence of known risk factors of IHD such as smoking and obesity 8, 9 and specific HIV sequelae such as chronic inflammation, dyslipidemia and lipodystrophy 10, 11, 12. Independent of IHD risk factors, HIV replication (Plasma HIV-1 RNA levels > 50 copies/mL) is also associated with an elevated risk of myocardial infarction (odds ratio 1.51 (95% confidence interval, 1.09-2.10)) 13.

    Physical inactivity is a known modifiable risk factor for IHD and is estimated to account for 6% of the burden of disease related to IHD internationally 14. In the South African context this burden is noted to be much higher at an estimated value of 30% in the general population 15. Walking, as a form of exercise, is often suggested as a means of lowering and managing an individuals’ risk for heart disease as it does not have cost implications or require specific skills. PLWH are encouraged to do regular exercise to manage their disease. Physical activity and ambulation behaviour have been well researched in the general population but is still poorly understood in an HIV population. This paucity in studies may be attributed to different measuring instruments being used to evaluate physical activity and researchers defining physical activity differently 16.

    Considering the potential burden of IHD in a South African HIV context, it seems prudent to evaluate the level of physical activity and risk factors for IHD at a primary health care level. Such screening may inform the type of intervention programmes needed to influence the risk factors for IHD in this population. Therefore the aim of this study was to evaluate the ambulation physical activity level and other risk factors for IHD in PLWH initiated on ARV at an HIV clinic in Johannesburg, South Africa.

    Materials and Methods

    An observational study was carried out at an urban HIV outpatient clinic in Johannesburg South Africa from October 2010 to June 2012. Participants were sampled consecutively according to set inclusion and exclusion criteria. Individuals were included if they were between 20-65 years of age, on ARV for six to 12 months and ambulatory without an assistive device e.g. not using a walking frame or walking stick. They were excluded if they had a pre-existing history of angina, myocardial infarction, stroke or peripheral vascular disease; acute infection or active/current opportunistic AIDS-defining illness; pre-existing history of dementia, confusion, psychosis or current signs of emotional distress; known diagnosed peripheral neuropathy or a physical complaint of “sore” or “burning feet” influencing walking ability and pregnant or breast-feeding women. The study received ethical approval from The University of the Witwatersrand Human Research Ethics committee. Permission was received from the hospital and clinic management and all participants gave informed consent prior to participating in the study.

    The sample size was calculated at 195 participants using the prevalence rate for hypertension in the South African context as guide as no prevalence rates for IHD in South Africa were available at the start of the study 17. The alpha level was set at 5% and power at 80%. The sample was increased with a factor of 100/95 to allow for any loss to follow-up of participants accounting for a final sample size of 205. Since completion of the current study, prevalence rates for IHD in individuals living with HIV in South Africa were published and indicated that the disease itself is still at a low prevalence level in this population 18.

    The following risk factors for IHD were screened using a questionnaire and body measurements: smoking history (current and former), diet (vegetable and fruit intake), physical activity levels (walking behaviour), resting heart rate and blood pressure, self-reported hypertension and diabetes, body mass index (BMI), waist- and hip circumference and waist: hip ratio (WHR). The study participants’ perception regarding their body shape and weight changes in the last six months was documented.

    Physical activity was assessed using the Yamax SW200 pedometer to provide information on walking behaviour (daily step count). Participants were asked to wear a hip-mounted pedometer for seven consecutive days from getting up in the morning until going to bed at night and to document their daily steps on a physical activity log sheet. They were encouraged not to alter their normal physical activity routine. Reactivity related to the physical activity assessment was calculated following the pilot study. No significant alteration (p = 0.4) in physical activity level was observed between the first and last day of assessment in participants when wearing the hip-mounted pedometer and documenting their findings on a log sheet during the pilot study.

    The participants’ perceived stress levels were evaluated with the Cohen's Perceived Stress Scale-10 (PSS). The PSS is an instrument that measures the degree to which a person perceives their life as being stressful. The instrument consists of 10 questions that are rated on a 5-point Likert scale and range from “0 = never” to “4 = very often”. Total PSS score is computed by summing across all ten questions. Scores range from 0 to 40 where a higher score reflects a higher degree of perceived stress 19, 20, 21. The PSS has been used in South Africa 22 and in a HIV population 23, 24. In the current study, the Cronbach’s α for the PSS was 0.82 as evaluated during the pilot study.

    Resting heart rate and blood pressure were evaluated with an automated sphygmomanometer on both of the participant’s arms twice after sitting quietly for a minimum of five minutes. The average of these four measurements was calculated and recorded. Anthropometric measurements were done according to the American College of Sports Medicine Guidelines 25. BMI was calculated in kg/m2 and WHR as the ratio of the waist to the hip circumference. WHR values of > 0.95 in men and > 0.85 in women were considered abnormal. A waist circumference of ≥ 88 cm in women and ≥ 102 cm in men were considered as an increased risk for IHD 26. Information regarding time spent on ARV and type was gathered from each participant and from his/her clinic file. The latest CD4 and viral load counts of participants were collected from their clinic file or laboratory data base.

    The participants attended two sessions with the researcher. On the first visit all questionnaires were completed, the pedometer and pedometer log sheet was explained and an accuracy test of the pedometer was carried out. The second visit occurred approximately 10 to 14 days following the first visit where body measurements were taken and the pedometer with log sheet returned.

    Statistical Methods

    Data analysis was done with STATA 12 27 and IBM SPSS 20 28. Data were evaluated for normal distribution. Continuous data e.g. pedometer step count were summarised as means and standard deviations. Percentiles of the means were reviewed to evaluate the presence and percentage of risk factors. Categorical data e.g. gender were summarised as frequencies and percentages. Demographic data of the study sample were assessed as a whole but smoking status, physical activity levels, perceived levels of stress and body measurements were also reviewed in gender groups. Bivariate analysis was carried out to determine with which independent variables physical inactivity (step count ≤ 9999 steps/day) and overweight/obesity (BMI ≥ 25 kg/m2) had an association as abnormal values were noted in physical activity and body mass index. Having a step count ≥ 10000 steps/day one is considered ‘active’ 29 and a BMI value between 18.5 – 24.9 kg/m2 is considered a normal BMI range 25. A univariate logistic regression analysis was then done to explain the odd ratios between the physical inactivity and increased body mass index and their independent variables. The odds ratios were adjusted for age and gender in further multiple variable logistic regression. Findings were statistically significant if p ˂ 0.05.

    Results

    Two hundred and ninety six participants who were on ARV treatment for six to twelve months indicated interest in participating in the study. Fourteen individuals were excluded due to not meeting all the inclusion criteria. Two hundred and eighty two participants consented to participate in the study. Seventy seven individuals recruited did not attend their first scheduled session due to work obligations, financial difficulties, travelling outside the Gauteng province and/or were not able to be contacted telephonically. Two hundred and five participants attended their first session and eleven of these individuals did not attend their second session due to the same barriers identified following recruitment. One hundred and ninety four individuals’ data were complete and used during data analysis. Physical activity data for 195 participants were available for analysis due to the following reasons: three participants’ data were excluded during analysis due to not completing seven days of pedometer assessment, seven participants did not attend their second visit or return their pedometer and pedometer log sheet and three participants send a friend/family member to return their pedometer and physical activity log sheet if they could not attend their second session.

    Table 1 describes the demographic information of the study participants. The mean age of the sample was 38 (±9.8) years and consisted mostly of women (77.1%; n=158). The majority of the sample was employed (56.1%; n=115), had a secondary educational level (46.3%; n=95) and was supporting dependents (85.4%; n=158). The participants perceived their health as good (58.5%; n=120) and the mean time spend on ARV treatment was 8.7 (±2.3) months. The majority of study participants were on the current first line ARV regimen of South Africa; Lamivudine, Efavirenz and Tenofovir (76.8%; n=139).

    Table 1. Demographic information of study population (n = 205)
    Variable Percentage (n)/ Mean (±SD)
    Age (years) 38.2 (±9.5)
    Gender  
    Male 22.9% (47)
    Female 77.1% (158)
    Educational level  
    No education 2.9% (6)
    Primary school education 24.4% (50)
    Secondary school education 46.3% (95)
    Post-secondary school education 26.3% (54)
    Employment status  
    Unemployed 40.5% (83)
    Employed 56.1% (115)
    Self-employed 3.4% (7)
    Participants who had dependents  
    No 14.6% (30)
    Yes 85.4% (158)
    ARV categories  
    Lamivudine, Efavirenz, Tenofovir 67.8% (139)
    Lamivudine, Efavirenz, Stavudine 18.5% (38)
    Other 13.6% (28)
    Time on ARVs (months) 8.7 (± 2.3)
    CD4 count (cells/mm3) 285.1 (± 157)
    Viral load < 400 (copies/ml) 64.9% (133)

    The mean ambulation physical activity level of the study sample was 7673.2 (±4017.1) steps/day. Male participants were more active than female participants (men 10076.3 (±4885.6) and women 6993.3 (±3462.6)). Seventy three percent of the cohort walked less than the 10 000 steps/day (active category): 25. 4% walked less than 5000 steps/day (sedentary), 27.8% between 5000-7499 steps/day (light active category) and 20% between 7500-1000 steps/day (somewhat active category).

    Sixty percent of participants (n=123) perceived a change in their body shape in the last six months. Changes in body shape were explained by participants in the following ways: general weight gain or general weight loss or gaining weight centrally (around their abdomen, or at their breasts, or at their abdomen and breasts, or around their hips and buttocks, or at their breasts and buttocks). Sixty four percent (n=132) felt that they had gained weight and twenty three percent (n=49) felt that they had lost weight in the last six months. Table 2 is a representation of the risk factors for IHD that was measured during this study.

    Table 2. Non-invasive risk factors for ischemic heart disease in study population
    Risk factors n Percentage (n) / Mean (SD)
    Current smokers 205 16.1% (33)
    · Male 40.4% (19)
    · Female 8.9% (14))
    Former smokers 205 25.9% (53)
    · Male 59.6% (28)
    · Female 15.8% (25)
    Diabetes 205 0.005% (1)
    Hypertension 205 0.09% (19)
    Daily intake of vegetables/fruits 205 46.3% (95)
    Daily intake of 3-5 vegetables/fruit per day 205 33.2% (68)
    Perceived stress levels 205 19.9 (7.8)
    · Male 47 16.8 (9.1)
    · Female 158 20.8 (7.1)
    Body & Anthropometric measurements Resting heart rate (beats/minute)    
    · Male 194 82.7 (11.4)
    · Female 44 79.4 (10.7)
      150 83.7 (11.5)
    Systolic blood pressure (mmHg) 194 118.6 (13.0)
    · Male 44 121.7 (13.4)
    · Female 150 117.7 (12.8)
    Diastolic blood pressure (mmHg) 194 77.8 (9.9)
    · Male 44 82.0 (17.0)
    · Female 150 77.1 (9.9)
    Body Mass Index (kg/m2) 194 25.6 (5.4)
    · Male 44 22.3 (3.1)
    · Female 150 26.6 (5.5)
    Waist circumference (cm) 194 84.9 (11.1)
    · Male 44 82.7 (9.6)
    · Female 150 85.6 (11.5)
    Hip circumference (cm) 194 103.5 (11.6)
    · Male 44 95.8 (6.0)
    · Female 150 105 (11.9)
    Waist: hip ratio 194 0.8 (0.1)
    · Male 44 0.9 (0.1)
    · Female 150 0.8 (0.1)

    Men were more likely to smoke than female participants. One participant had a past medical history of diabetes and 19 participants were hypertensive and on treatment. Daily intake of vegetables and fruit was not regular (46.3%) and few individuals (33.2%) were able to partake in 3-5 vegetables/fruit per day. Female participants perceived higher levels of stress compared to their male counterparts. The mean resting heart rate was 82.7 (±11.4) beats/minute and BMI 25.6 (±5.4) kg/m2 was increased in the sample as a whole but more so in female participants. Waist circumference and WHR means were within the gender specific ranges 25. As such attention should be paid to the results where 5% of men and 25% of women had increased waist circumferences and 10% of men and 25% of women had increased WHR. Both these parameters indicate the presence of abdominal obesity in part of the study cohort. The mean systolic and diastolic blood pressure values were within the normal ranges (systolic 95-140 mmHg and diastolic 60-90 mmHg). Table 3 is a representation of the independent variables significantly influencing the risk of being overweight/obese and/or physically inactive.

    Table 3. Risk of being overweight and/or physically inactive associated with individual IHD risk factors
    Risk factor n Odds Ratio (95% CI) Adjusted for Age , Sex p-value
    Overweight/Obese      
    ▪ Systolic blood pressure 194 1.07 (1.04-1.10) 0
    ▪ Waist circumference 194 1.33 (1.23-1.46) 0
    ▪ Hip circumference 194 1.53 (1.34-1.75) 0
    ▪ Physical activity 195 0.99 (0.99-0.99) 0.05
    ▪ CD4 count 205 1.00 (1.00-1.00) 0.01
    ▪ Daily fruit/vegetable intake 205 1.80 (0.99-3.27) 0.05
    Physical inactive      
    ▪ Waist circumference 194 1.04 (1.00-1.08) 0.03

    Being overweight/obese was inversely related to physical activity level. Individuals with a higher CD4 count, systolic blood pressure, waist and hip circumference and daily intake of vegetables/fruit were also more likely to have a BMI ≥ 25 kg/m2. Waist circumference was significantly related to a physical activity level less than 10000 steps per day.

    Discussion

    Our findings build on international data that are available concerning the ambulation physical activity levels of PLWH and provide information regarding the South African context.

    Pedometer step count physical activity categories were first described by Tudor-Locke and Bassett 29 to assist with reference ranges for objective physical activity walking behaviour. A person is said to follow an “active” lifestyle if he/she accumulates more than 10000 steps/day; be “somewhat-active” if taking more than 7500 steps/day; “light active” between 5000 and 7499 steps/day and “sedentary” if accumulating less than 5000 steps/day. The physical activity level of the sample could be considered “somewhat active” when considering the average pedometer steps/ day. However, male participants were “active” while their female counterparts were “light active”. This pedometer step count finding was less than that reported in a study conducted by Cook et al 30in adolescent and adult South African individuals living in a rural area. The average step count in their sample was 12471 steps/day. The difference in physical activity level between the current urban HIV cohort and the previously stated rural study could possibly be firstly explained by differences in transportation. The urban population might rely more on public transportation whereas the rural population could walk more and accumulated more steps/day. Secondly, individuals living in a rural South African community often have to walk long distances to collect water and firewood. This could result in more walking activity and higher daily step counts than the urban group. Thirdly, study participants in this study were living with HIV whereas the HIV status of the rural participants was not known. Physical symptoms such as shortness of breath and fatigue were often reported by study participants. Immune status with accompanied physical symptoms might have resulted in these individuals resting more often during daily activity in an attempt to conserve energy resulting in fewer steps per day.

    The physical activity findings from the South African HIV cohort had similarities with a study conducted by Ramirez-Marrero in Hispanic adults living with HIV in San Juan, Porto Rico 31.Their research indicated a mean of 7418 (±2714) steps/day with men accumulating slightly less than the South African males at 7594 (±2817) steps/day and women slightly more at 7151 (±2589) steps/ day.

    The current study demonstrated a significant relationship between waist circumference and physical inactivity in study participants. This finding is consistent with research done by Saunders et al 32 that found a 0.15cm increase in waist circumference if sedentary behavior increased with 15 minute in study participants.

    Being physically active has many health benefits and a 10000 steps/day aim is suggested as a reasonable target for healthy individuals to reach to increase the health benefits related to activity 33. Physical activity levels of more than 10000 steps/ day are said to assist with reducing the risk for obesity 34 and reducing waist circumference and fasting glucose levels in the general population 35. In an HIV context, studies have demonstrated that physical activity programmes such as structured exercise may address risk factors for IHD such as BMI, waist circumference and WHR 36, 37. This study demonstrated that the ambulation physical activity levels of South African PLWH attending an urban HIV clinic could be improved. Implementing a physical activity modification programme as part of their clinic management early could potentially assist in reducing their risk for IHD in the long term. If the 10000 steps per day guideline is to be used in PLWH, it is however suggested that an incremental increase in their step count and regular monitoring of individuals be encouraged to evaluate how individuals react to such a programme given that there is no previously known data.

    Smoking was present in the study population but was not as prevalent as noted by international authors in HIV populations 9, 38, 39. A possible reason to explain the level of smoking is that the study population consisted mostly of women and individuals of black ethnic origin. Peer et al 40 reported that South African women are less likely to smoke than their male counterparts and that black men and women smoke significantly less than other population groups in South Africa.In the South African context where HIV prevalence remains disproportionally high in females in comparison to males 41 it might be suggested that more focus is needed on education and exercise programmes to address physical inactivity and overweight/ obesity compared to smoking cessation. Anthropometric abnormalities were noted in part of the study population at this early stage of their ARV treatment. This was partly consistent with findings noted in longitudinal studies conducted in South African PLWH initiated on ARV that consisted of the Stavudine containing regimen 10, 26. In this study, the main ARV regimen identified did not contain Stavudine but Tenofovir. It should however be emphasised that analysis did not reveal an association between BMI and ARV therapy and that such an investigation was not one of the aims of the current study. The association of increased BMI with other anthropometric measurements such as waist and hip circumference, may suggest that waist and hip circumference measurements and WHR calculation should be included in general HIV management to monitor individuals at risk of IHD due to the development of abdominal obesity. Education programmes that focus on what normal healthy weight is should also be encouraged. Hurley et al 26 noted that individuals in a South African HIV context often perceive their weight different to the measured reality and this might potentially hinder weight reduction programmes. Daily fruit and vegetable intake increased the possibility of being overweight in this population. This was a rather interesting finding as one would anticipate the opposite to be true. Body mass index provides information regarding the general nutritional status of individuals and could therefore indicate that participants that fell into the overweight/obese category had sufficient nutrition that allowed them to also partake in daily fruit and vegetable intake. The focus of the study was to screen diet as risk factor for IHD and not general diet. It is reported that a daily diet low in fruit and vegetable is considered a risk factor for IHD 42; hence the inclusion of investigation of fruit and vegetable intake in the current study. The majority of participants were unable to partake in daily fruit and vegetable intake. A frequent reason provided by participants for this finding was financial constraints due to unemployment. A solution for this risk factor would therefore require education regarding diet in relation to risk for IHD but more importantly as part of the wider response addressing social problems facing South Africa that includes unemployment.

    The perceived level of stress experienced by the study participants was slightly higher when compared to a low-income general South African cohort (mean 18.6 (±6.7)) 22 and this is to be expected as the participants in the current study had to cope with the stigma that surrounds HIV and the difficulties associated with employment and participation in the wider community.

    A limitation of the study was that only ambulation physical activity level was formally screened in study participants. How much time participants participated in other forms of physical activity e.g. domestic activities were not the specific aim of the study. It should thus be emphasized that the current manuscript provides information of participants walking level.

    In conclusion, risk factors of IHD were identified in PLWH initiated on ARV between 6 and 12 months. The risk factors included physical inactivity, presence of diabetes and hypertension, increased BMI, presence of abdominal obesity, diet that does not include daily fruit and vegetable intake and a small proportion of participants smoked. Education and specific intervention programmes focusing on promoting and increasing physical activity would be a means of addressing a number of these risk factors and could be included in the prevention, treatment, care and support programmes.

    Acknowledgements

    This study was possible due to support received from the Themba Lethu HIV clinic, Clinical HIV Research Unit, Right to Care and the Department of Medicine at Helen Joseph Hospital in Gauteng, South Africa. This study was supported by grants received from the University of the Witwatersrand (Medical Endowment and Faculty Research Committee grants), South African Society of Physiotherapy (Research Foundation grant), National Research Foundation (NRF) Thuthuka grant and Medical Research Council (MRC). Any opinion, findings and conclusions or recommendations expressed in this material are those of the author(s) and therefore the NRF does not accept any liability in regard thereto. The views and opinions expressed are not those of the MRC but of the author (s) of the material produced or publicized.

    References

    1.Johnson L F, Mossong J, Dorrington R E, Schomaker M. (2013) Life expectancies of South African adults starting antiretroviral treatment: collaborative analysis of cohort studies. , PLoS MED 10(4), 1001418.
    2.Mayosi B M, Flisher A J, Lalloo U G, Sitas F. (2009) The burden of non-communicable diseases in South Africa. , Lancet 374, 934-947.
    3.Mayosi B M, Lawn J E, A van Niekerk, Bradshaw D. (2012) . Health in South Africa: changes and challenges since2009. Lancet 380: 2029-2043.
    4. (2011) UNAIDS South African Country Overview accessed on2013-02-11.Accessible at http://www.unaids.org/en/regionscountries/countries/southafrica/.
    5.Shisana O, Rehle T, Simbayi L C, Zuma K. (2014) . South African National HIV Prevalence, Incidence and Behaviour Survey, 2012.Cape Town,HSRC Press.Accessible at http://www.hsrc.ac.za/uploads/pageContent/4565/SABSSM%20IV%20LEO%20final.pdf.Accessed on2016january21 .
    6.Palella FJ Jr, Baker R K, Moorman A C, Chmiel J S. (2006) Mortality in the highly active antiretroviral therapy era: changing causes of death and disease in the HIV Outpatient Study. , J Acquir Immune Defic Syndr 43, 27-34.
    7.French A L, Gawel S H, Hershow R, Benning L. (2009) Trends in mortality and cuases of death among women with HIV in the US: A ten-year study. , J Acquir Immune Defic Syndr 51(4), 399-406.
    8.Crum-Cianflone N, Roediger M P, Eberly L, Headd M. (2010) Increasing rates of obesity among HIV-infected persons during the HIV epidemic. , Plos One April 5(4), 10106.
    9.Reynolds N R. (2009) Cigarette smoking and HIV: more evidence for action. Aids Educ Prev21(3 Suppl): 106-121.
    10.George J A, WDF Venter, Van Deventer HE, Crowther N J. (2009) A longitudinal study of the changes in body fat and metabolic parameters in a South African population of HIV-positive patients receiving an antiretroviral therapeutic regimen containing stavudine. , Aids Research and Human Retroviruses 25(8), 771-781.
    11.Triant V A, Meigs J B, Grinspoon S K. (2009) Association of C-reactive protein and HIV infection with acute myocardial infarction. , J Acquir Immune Defic Syndr 51, 268-273.
    12.Grinspoon S K, Grunfeld C, Kotler D P, Currier J S. (2008) State of Science Conference: Initiative to decrease cardiovascular risk and increase quality of care for patients living with HIV/AIDS Executive Summary. , Circulation 118, 198-210.
    13.Lang S, Mary-Krause M, Simon A, Partisani M. (2012) HIV replication and immune status are independent predictors of the risk of myocardial infarction in HIV-infected individuals. , CID 55(4), 600-607.
    14.Lee I M, Shiroma E J, Lobelo E, Puska P. (2012) Effects of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. , Lancet 380, 219-229.
    15.Joubert J, Norman R, Lambert E V, Groenewald P. (2007) Estimating the burden of disease attributable to physical inactivity in South Africa in2000. , S Afr Med J 97, 725-731.
    16.Schuelter-Trevisol F, Wolff F H, Alencastro P R, Grigoletti S. (2012) Physical activity: Do patients infected with HIV practice? How much? A systematic review. , Curr HIV Res 10(6), 487-497.
    17.Steyn K. (2008) Hypertension in South Africa. In: Chronic diseases of lifestyle in South Africa since 1995-2005: 1-17. Accessible at http://www.mrc.ac.za/chronic.
    18.Sliwa K, Carrington M J, Becker A, Thienemann F. (2012) Contribution of the human immunodeficiency virus/acquired immunodeficiency syndrome epidemic to de novo presentations of heart disease in the Heart of Soweto Study cohort. , Eur Heart J 33, 866-874.
    19.Cohen S, Janicki-Deverts D. (2012) Who’s stressed? Distribution of psychological stress in the United States in probability samples from1983,2006and2009. , J Appl Social Psyc 42(6), 1320-1334.
    20.Cohen S, Williamson G M. (1988) Perceived stress in a probability sample of the United States. In: Spacapan S and Oskamp S (Eds) The Social psychology of Health.Newbury Park,CA:Sage.
    21.Cohen S, Kamarck T, Mermelstein R. (1983) A global measure of perceived stress. , J Health Soc Behav 24(4), 385-396.
    22.Hamad R, LCH Fernald, Karlan D S, Zinman J. (2008) Social and economic correlates of depressive symptoms and perceived stress in South African adults. , J Epidemiol Community Health 62, 538-544.
    23.Koopman C, Gore-Felton C, Marouf F, Butler D. (2000) Relationship of perceived stress to coping, attachment and social support among HIV-positive persons. , AIDS CARE 12(5), 663-672.
    24.Paddison J, Fricchione G, Gandhi R T, Freudenreich O. (2009) Fatigue in psychiatric HIV patients: a pilot study of psychological correlates. , Psychosomatics 50(5), 455-460.
    25. (2010) American College of Sports Medicine.ACSM’s guidelines for exercise testing and prescription 8th edition. Lippincott,Williams and Wilkins.
    26.Hurley E, Coutsoudis A, Giddy J, Knight S E. (2011) Weight evolution and perceptions of adults living with HIV following initiation of antiretroviral therapy in a South African urban setting. , S Afr Med J 101, 645-650.
    27.StataCorp. (2011) Stata Statistical Software: Release 12. College Station, TX: StataCorp LP.
    28.. IBMCorp.Released2011.IBM SPSS Statistics for Windows,Version20.0.Armonk,NY:IBM Corp .
    29.Tudor-Locke C, Basset DR Jr. (2004) How many steps/day are enough?. , Sports Med 34(1), 1-8.
    30.Cook I, Alberts M, Brits J S, Choma S R. (2010) Descriptive epidemiology of ambulatory ambulatory activity in rural, black South Africans. , Med Sci Sports Exerc 42(7), 1261-1268.
    31.Ramirez-Marrero F A, Rivera-Brown A M, Nazario C M, Rodriquez-Orengo J F. (2008) Self-reported physical activity in Hispanic adults living with HIV: comparison with accelerometer and pedometer. , Journal of the association of Nurses in Aids Care 19(4), 283-294.
    32.Saunders T J, Tremblay M S, Despres J P, Bouchard C. (2013) Sedentary behavior, visceral fat accumulation and cardiometabolic risk in adults: a 6-year longitudinal study from the Quebec Family study. , PLOS ONE 8(1), 54225.
    33.Tudor-Locke C, Craig C L, Brown W J, Clemes S A. (2011) How many steps/day are enough? For Adults. , International Journal of Behavioral Nutrition and Physical Activity 8(79), 1-17.
    34.Cook I, Alberts M, Lambert E V. (2011) Compliance with physical activity guidelines in rural, black South Africans in the Limpopo Province: an energy expenditure approach. , Br J Sports Med 45(8), 619-625.
    35.Musto A, Jacobs K, Nash M, Delrossi G. (2010) The effects of an incremental approach to 10000 steps/day on metabolic syndrome components in sedentary overweight women. , J Physical Activity and Health 7, 737-745.
    36.Fillipas S, Cherry C L, Cicuttini F, Smirneos L. (2010) The effects of exercise training on metabolic and morphological outcomes for people living with HIV: a systematic review of randomized controlled trials. , HIV Clin Trials 11(5), 270-282.
    37.Ogalha C, Luz E, Sampaio E, Souza R. (2011) A randomized controlled trial to evaluate the impact of regular physical activity on the quality of life, body morphology and metabolic parameters of patients with AIDS in Salvador. , Brazil, J Acquir Immune Defic Syndr 57, 179-185.
    38.Petrosillo N, Cicalini S. (2013) Smoking and HIV: time for a change?. , BMC Medicine 11, 16.
    39.Saves M, Chene G, Ducimetiere P, Leport C. (2003) Risk factors for coronary heart disease in patients treated for human immunidefiency virus infection compared with the general population. , Clin Infect Dis 37, 292-298.
    40.Peer N, Bradshaw D, Laubscher R, Steyn K. (2009) Trends in adult tobacco use from two South African Demographic and Health Surveys conducted in1998and2003. , S Afr Med J 99(10), 744-749.
    41.Shisana O, Rehle T, Simbayi L C, Suma K. (2009) South African national HIV prevalence, incidencem behaviour and communition survey 2008: a turning tide among teenagers? Cape Town:HSRCpress.
    42.Steyn K, Sliwa K, Hawken S, Commerford P.(2005)Risk factors associated with myocardial infarction in Africa:The. , INTERHEART Africa Study. Circulation 112, 3554-3561.