Life expectancies of HIV-positive patients have been increasing with the rapid implementation of antiretroviral therapy (ART). This has led to an increase in comorbidities such as diabetes mellitus (DM) and hypertension (HT) amongst the HIV population. The burden of the non-communicable diseases (NCDs) such as DM and HT need to be quantified in order to ensure that patients receive optimal integrated care as patients often access care at different clinics compromising holistic care.
The aim of the study was to determine the prevalence of DM and HT amongst the HIV-positive population.
The study was conducted at Wentworth Hospital, a district facility in South Durban, KwaZulu-Natal.
This cross-sectional study was undertaken to determine the prevalence of two NCDs, namely DM and HT in HIV-positive patients attending the ART clinic at a district hospital in the eThekwini district. We compared the socio-demographic and clinical profiles of those with and without comorbidities. A sample of 301 HIV-positive patients were administered a structured questionnaire.
Of the 301 patients, 230 (76.41%) had HIV only (95% confidence interval [CI]: 71.25–80.89) and 71 (23.59%) had HIV and at least one comorbidity, namely DM and/or HT (95% CI: 19.11-28.75). Hypertension was the most prevalent comorbidity. This study revealed that there was no association between the duration of ART and comorbidities. Older age and body mass index (BMI) were associated with comorbidities, whilst gender and ethnicity were not associated.
Non-communicable diseases such as DM and HT do pose a burden for HIV-positive patients attending the ARV clinic at this district facility. This study highlights the definite need to plan for the increased burden of NCDs as HIV-positive patients live longer and gain weight.
Human immunodeficiency virus (HIV) and non-communicable diseases (NCDs) are major public health concerns.
KwaZulu-Natal (KZN) has the highest prevalence rate of HIV (18.9%) amongst adults aged 15 to 49 years of age. In SSA, the prevalence of diabetes mellitus (DM) and hypertension (HT) amongst the HIV population is also significantly high. Hypertension is a common condition that often coexists with DM with both conditions together causing an increased risk of cardiovascular morbidity and mortality.
People that are HIV-positive have three risk factors for contracting NCDs, namely from the HIV infection itself, from the adverse metabolic effects of ART and from the risk associated with increasing age. Gender, ethnicity and socio-economic status have also been associated with increased risk of contracting NCDs.
This epidemiological hospital based cross-sectional study generated quantitative data by means of a structured pretested questionnaire. A chart review was also conducted to confirm comorbidities amongst the study population.
The study was conducted at Wentworth Hospital, a district facility in South Durban, KZN and the sample size of 301 was estimated using a confidence level of 95% with a precision of 5% based on a study population of 1379 patients that collected ART at the hospital during July 2016.
The content of the research instrument was validated by consulting with experts in the ART clinic and a biostatistician. A pilot study was conducted amongst 10 participants at another eThekwini hospital. After the content validity and pilot study, minor adjustments were made to the study tool. Data from the pilot study were captured on a Microsoft Excel spreadsheet and analysed. The results from this analysis confirmed that it would adequately address the aim and objectives of the study.
Study participants included HIV positive men and women who attended the Wentworth Hospital ART clinic who were 18 years and older and consented to participate. All consecutive patients met the inclusion criteria (all patients who were HIV-positive, above 18 years of age and those who agreed to participate in the study were asked to participate). Patients were approached as they waited in line to be consulted by the doctor.
Questionnaires were translated into isiZulu for easy comprehension and each participant was given an information sheet and signed the consent form after an explanation of the study was provided and queries addressed. Data were collected from May 2017 until November 2017. If a patient refused, then the next consecutive patient in line was approached to participate. Fieldwork was conducted from Monday to Friday during the clinics operating hours from 08:00 to 16:00. Trained fieldworkers collected the data whilst patients were in the waiting rooms of the ART clinic. The variables included patients’ socio-demographic characteristics and clinical information. Piloting of the questionnaire was performed on 10 participants and minor adjustments were then made to the study tool. All questionnaires were checked to ensure that most questions were answered. Those who had a substantial amount of missing data were rejected. Questionnaires were completed but it was found that some patients chose not to answer many questions resulting in substandard information so the questionnaire was rejected and a new study participant was recruited. This occurred for 13 participants. Eventually 301 patients satisfactorily completed the questionnaire.
Coded data from the patient questionnaire was entered on a Microsoft Excel 2010 spreadsheet. The data were then imported into the statistical software package STATA version 14 for data analysis. Prevalence was reported as percentages with 95% confidence intervals (CIs). A statistical significance level of
The study was approved by the Biomedical Research Ethics Committee at the University of KwaZulu-Natal (BE645/16) and from the KwaZulu-Natal Department of Health and Wentworth Hospital. All participants were assured that anonymity and strict confidentiality was maintained during the entire duration of the study. Participation was voluntary and participants could withdraw at any time during the study period. Informed consent and questionnaires for patients were provided in both English and isiZulu; however, all patients opted to use the English questionnaire. Patients signed the informed consent prior to participation in the study.
Altogether 301 patients participated in the study. Their demographic features are shown in
Demographic characteristics of participants.
Variable | Gender |
||||||
---|---|---|---|---|---|---|---|
Female |
Male |
Total |
|||||
% | % | % | |||||
Ethnicity | African | 171 | 91.0 | 107 | 94.7 | 278 | 92.4 |
Indian | 1 | 0.5 | 1 | 0.9 | 2 | 0.7 | |
Mixed-race | 10 | 5.3 | 3 | 2.7 | 13 | 4.3 | |
White | 6 | 3.2 | 2 | 1.8 | 8 | 2.7 | |
Total | 188 | 100.0 | 113 | 100.0 | 301 | 100.0 | |
Employed | Employed | 60 | 33.0 | 41 | 36.3 | 101 | 34.2 |
Unemployed | 120 | 65.9 | 70 | 61.9 | 190 | 64.4 | |
Unknown | 2 | 1.1 | 2 | 1.8 | 4 | 1.4 | |
Total | 182 | 100.0 | 113 | 100.0 | 295 | 100.0 | |
Education level | Primary | 12 | 6.4 | 7 | 6.2 | 19 | 6.3 |
Secondary | 121 | 64.4 | 74 | 65.5 | 195 | 64.8 | |
Tertiary | 13 | 6.9 | 4 | 3.5 | 17 | 5.6 | |
Missing | 42 | 22.3 | 28 | 24.8 | 70 | 23.3 | |
The mean age (and s.d.) amongst the female participants was 41.2 (11.2 s.d.) years and amongst male participants was 42.2 (10.9 s.d.) years and the entire group was 41.6 (11.0 s.d.) years.
Prevalence of comorbidities (
Variable | % | 95% CI for prevalence | Mean age | s.d. | 95% CI for mean age | |
---|---|---|---|---|---|---|
HIV only | 230 | 76.4 | 71.3–81.8 | 39.1 | 10.2 | 37.8–40.5 |
HIV and DM | 6 | 2.0 | 0.9–4.4 | 43.2 | 8.5 | 34.2–52.1 |
HIV and HT | 55 | 18.3 | 14.3–23.1 | 49.4 | 9.7 | 46.8–52.0 |
HIV, DM and HT | 10 | 3.3 | 1.8–6.1 | 53.9 | 9.8 | 46.960.9 |
HIV and at least one comorbidity | 71 | 23.6 | 18.1–28.9 | 49.5 | 9.8 | 47.251.8 |
HIV, human immunodeficiency virus; CI, confidence interval; s.d., standard deviations; DM, diabetes mellitus; HT, hypertension.
In this population, 71 (23.59%) of the participants had one or more comorbidities. There was a statistically significant difference in age between the subgroups (
The association between selected risk factors and presence or absence of any comorbidity was examined using binary logistic regression. These are tabulated in
Factors associated with comorbidities.
Independent variable | Unadjusted odds ratios |
Adjusted odds ratios |
||||||
---|---|---|---|---|---|---|---|---|
OR | 95% CI for OR |
AOR | 95% CI for AOR |
|||||
Lower | Upper | Lower | Upper | |||||
< 0.001 | 1.10 | 1.07 | 1.13 | < 0.001 | 1.10 | 1.07 | 1.14 | |
< 0.001 | 1.07 | 1.03 | 1.10 | 0.04 | 1.04 | 1.00 | 1.08 | |
0.68 | 1.00 | 0.96 | 1.01 | - | - | - | - | |
Male | 0.85 | 0.95 | 0.55 | 1.65 | - | - | - | - |
Female | - | Reference | - | - | - | - | - | - |
African people | - | Reference | - | - | - | - | - | - |
Indian people | 0.39 | 3.41 | 0.21 | 55.34 | - | - | - | - |
Mixed-race people | 0.20 | 2.13 | 0.67 | 6.75 | - | - | - | - |
White people | 0.88 | 1.14 | 0.22 | 5.78 | - | - | - | - |
OR, odds ratio; AOR, adjusted odds ratio; CI, confidence interval; BMI, body mass index; ART, antiretroviral therapy.
, Adjusted for age and body mass index.
There was no association between the duration of ART and comorbidities (
Duration of treatment was calculated in months between starting ARVs and the date of close of data extraction, that is, 11 August 2017. The results are depicted in
Box and Whisker plot for months on anti by comorbidities.
The time of treatment was skewed, with a mean of 52 months and median of 46 months. The range was from 1.9 to 201 months. A non-parametric Kruskal–Wallis test was used to test the null hypothesis that there was no difference in months on ARVs between the groups.
The key findings were that the prevalence of comorbidities in this population was 23.59% (95% CI: 19.1–28.9). Older age and BMI were positively associated with comorbidities (
Hypertension prevalence amongst the HIV-positive population varies between 6.0% and 39.0% and this figure is consistent with our study.
Diabetes mellitus prevalence in the HIV population is emerging as the major non-infectious comorbidity.
Various studies reported a prevalence of DM and HT as being higher in the population with HIV compared with the general population.
Diabetes mellitus prevalence was associated with older age, increased BMI and longer duration of treatment in the study in Ethiopia.
The Tanzanian study revealed an increase in the prevalence of obesity from 33.0% to 58.0% after commencement of ART.
Older age is an independent risk factor for NCDs in the HIV population.
In our study, duration of ART was not associated with comorbidities but this was not consistent with other studies.
Data are available regarding metabolic syndrome and gender on patients on HIV treatment.
One of the strengths of this study is that this is one of few studies to describe the prevalence of DM and HT amongst the HIV population in an urban district hospital setting. One of the limitations of the study is that the results of this study cannot be generalised to the population at large because of the small sample size, cross-sectional design and being conducted in one study site. Another limitation in our study was that as the most stable patients on treatment were down referred to primary health care (PHC) clinics hence the shorter duration of treatment in the study population. Data on ART regimens were not collected and 13 questionnaires were rejected and new participants enrolled because of substandard data collection. This facility serviced predominately the black population and mixed race population and inferences cannot be made for the population at large.
Health promotion messages need to be incorporated into routine care as HIV-positive patients live and age with HIV. Sometimes health promotion in the ART clinics is neglected and priority is given to adherence to HIV treatment. It is important that NCDs and HIV is managed at one point of care as fragmented care comprises the quality and continuity of care as patients are observed to prioritise NCDS over HIV or vice versa. It is therefore important to integrate HIV and NCD clinics where patients are managed for all their conditions by trained clinicians upskilled in ART and NCDs treatment.
Non-communicable diseases such as DM and HT add to the burden of the HIV patients attending this district facility. Older age and increased BMI were predictors of comorbidities amongst the HIV population in our study. It was highlighted that almost a quarter of the patients who presented at this ART clinic had a comorbidity. Based on the findings of this study, it is imperative that health awareness and ongoing health education is conducted to highlight the NCDs risk factors and self-management of risk factors. It is important for clinicians involved in HIV care to note the importance that age and BMI play in increasing the odds of developing NCDs. Screening for NCDs need to be an integral part of the follow up routine care of HIV-positive patients and all patients that enter healthcare facilities.
The authors would like to thank all the fieldworkers involved in data collection.
The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
A.R. conducted this study under the supervision of M.N. Both A.R. and M.N. were responsible for conceptualising the study and A.R. collected and analysed the data and wrote the final report under the supervision of M.N.
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
As a result of the private nature of the data, data for the study will be available only upon request and approval of the KwaZulu-Natal Department of Health.
The views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of any affiliated agency of the authors.