The SA Journal Diabetes & Vascular Disease Vol 16 No 1 (July 2019)

RESEARCH ARTICLE

SA JOURNAL OF DIABETES & VASCULAR DISEASE

VOLUME 16 NUMBER 1 • JULY 2019

significant association between CD4 count and total cholesterol

level (Table 4).

Thirty-one (2.1%) subjects had a random blood glucose level

of > 7.8 mmol/l. These patients were referred to the physician for

fasting glucose determination and/or oral glucose tolerance tests.

Eight (0.55%) of those above 40 years of age had more than

10% risk of developing a major adverse cardiovascular event in 10

years, according the WHO (Afri-E) risk score performed on these

clients.

Discussion

In this study, cardiovascular screening of people living with HIV

revealed a significant prevalence of undiagnosed hypertension

(13.3%) and raised total cholesterol levels (14%), two of the

major cardiovascular risk factors. Possible aetiological factors for

hypertension include traditional risk factors (such as age, gender,

smoking and obesity), ART, or possibly HIV infection itself. Our

analysis of risk factors indicated significant associations between

the occurrence of hypertension and male gender, older age (> 40

years) and increased waist circumference. There was however no

association between ART regimen and hypertension, suggesting

that other factors may have been contributory.

In a population survey targeting a peri-urban community in

Nairobi, prevalence of hypertension was 22%,

which is higher

than seen in this study. One of the possible reasons for this

disparity is that despite living with HIV, the age of this cohort

was relatively young and with fewer smokers compared to those

reported in the general population (2015 Kenya STEPS survey).

Also, the prevalence of other known risk factors for hypertension

such as overweight and obesity was at 14%, well lower than

reported in the national STEPS survey (27%).

In another retrospective review of data from an HIV-positive

population in western Kenya, the prevalence of hypertension was

11.2% in men and 7.4% in women.

The figures observed in this

review compare well with those found in our study.

Possible aetiological factors for high cholesterol levels include

genetic factors, diet, ART or HIV infection itself. After adjusting for

confounders, elevated cholesterol level was associated with three

ART regimens (TDF, AZT and D4T) suggesting a potential causal

relationship. However, since a full lipid profile was not performed,

it remains unclear if this was due to a raised low-density lipoprotein

cholesterol level.

A study in Tanzania showed a high prevalence of dyslipidaemia

(low high-density lipoprotein cholesterol and elevated triglyceride

levels) in an ART-naïve cohort of HIV patients.

There is therefore a

need for further research to illustrate the role of ART therapy on the

patterns of dyslipidaemia.

The prevalence of smoking, obesity, glucose intolerance and

diabetes were low in this population at 1.9, 12.1 and 2.6%,

respectively, and only 0.6% had a WHO cardiovascular risk score

> 10%. This is much lower compared to the peri-urban population

study of Nairobi where 10% were smokers, 5% had diabetes, and

more than 40% had central obesity.

Our rural hospital setting may

present a different HIV population where disease and lifestyle advice

provided to the patients may have altered risk factors, particularly

smoking incidence.

With increasing longevity of people livingwith HIV, the prevalence

of hypertension, hyperlipidaemia and glucose intolerance is

likely to increase. Therefore routine and systematic screening for

cardiovascular risk factors among this population is crucial. The

majority of cardiovascular risk factors, also seen in people with HIV,

such as smoking, hypertension and obesity, aremodifiable, therefore

early identification and treatment of these conditions provides an

opportunity to improve the quality of care and possibly survival rate

in this population. Existing studies conducted in sub-Saharan Africa

suggest there is little knowledge of the risk posed by CVD in this

population.

There is therefore a need to establish CVD care in HIV

programmes to potentially mitigate adverse cardiovascular events

in these patients.

This study has several limitations, including collecting data from

patient charts at one time point. Further studies are needed to

establish how screening, referral and evidence-based interventions

could reduce cardiovascular risk of people living with HIV in rural

Kenya and beyond. Cardiovascular risk was determined after

a median duration of 32 months of ART. A longer period of

observation may be required to detect transition in cardiovascular

risk. However the high prevalence of hypertension indicates that

there was a considerable amount of undiagnosed incipient and

actual hypertension in this population. Lastly, fasting lipid profiles

were not performed where elevated non-fasting values were

found, and inferences from an elevated total cholesterol level may

not accurately reflect the prevalence of hypercholesterolaemia.

However, recent guidelines advocate the use of non-fasting

cholesterol tests.

Our data are from 2013 to 2016, and the

situation in terms of ART regimens and cardiovascular risk may

have changed since then.

Conclusion

CVD screening in a primary HIV-care clinic revealed a high prevalence

of undiagnosed hypertension and raised total cholesterol levels,

Table 4.

Unadjusted and adjusted odds ratios for elevated total

cholesterol

Unadjusted

OR Adjusted OR

Characteristic

OR (95% CI)

-value

OR (95% CI)

-value

Male gender

0.85 (0.61–1.17) 0.3194

0.83 (0.59–1.17) 0.2806

Age ≥ 40 years

2.21 (1.63–3.00) 0.0001

1.95 (1.42–2.69) 0.0001

Smoker

0.22 (0.03–1.64) 0.1404

0.22 (0.03–1.67) 0.1434

BMI ≥ 30 kg/m

2.15 (0.95–4.86) 0.0647

1.03 (0.39–2.74) 0.946

Random blood

glucose

≥ 7.8 mmol/l

1.96 (0.83–4.62) 0.1252

1.99 (0.82–4.81) 0.1278

Increased waist

circumference* 2.68 (1.64–4.36) 0.0001

2.06 (1.14–3.71) 0.0164

ART regimen

No ART

Ref

TDF-based

2.47 (1.45–4.22) 0.0009

2.20 (1.28–3.78) 0.0042

AZT-based

2.84 (1.72–4.71) 0.0001

2.50 (1.50–4.18) 0.0004

D4T-based

3.86 (2.14–6.95) 0.0001

3.13 (1.72–5.71) 0.0002

LPV-based

1.98 (0.55–7.17) 0.2968

1.85 (0.50–6.80) 0.3536

CD4 count

(cells/mm

)

Missing

0.74 (0.49–1.11) 0.147

0.87 (0.57–1.33) 0.5217

0–100

1.04 (0.42–2.60) 0.9306

1.13 (0.44–2.92) 0.7964

101–200

0.48 (0.20–1.16) 0.1029

0.46 (0.19–1.13) 0.0885

201–350

0.79 (0.51–1.22) 0.2884

0.79 (0.50–1.25) 0.3174

351–500

0.93 (0.62–1.39) 0.7106

0.92 (0.60–1.41) 0.6951

> 500

Ref

*Females ≥ 90 cm, males ≥ 100 cm.