The effects of HIV and ART on serum lipids among adults in Agincourt in 2015

Nonterah, Engelbert Adamwaba
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Background: The burden of HIV infection is still high in South Africa. However, the use of ART has greatly improved treatment outcomes and survival. People infected with HIV and receiving ART are therefore living longer but with a likely increase in their cardiometabolic risk. Both HIV infection and anti-retroviral drugs have been shown to affect serum lipid levels and this may be among the reasons for the increased cardiometabolic risk in these subjects. The aim of this study was therefore to characterize the principal determinants of lipid levels in a large rural South African population with a high prevalence of HIV infection in which an array of factors that possibly modulate serum lipid levels had also been measured. Materials and methods: Data for this secondary analysis are drawn from a population-based cross-sectional study: the HAALSI/AWI-Gen collaborative study conducted in the Agincourt sub-district of the Mpumalanga province. 2110 adults 40+ years being monitored by the Agincourt health and socio-demographic surveillance system were randomly selected and recruited, after giving informed consent, between 2013-2016. Pretested questionnaires were used to collect personal, household, socio-demographic, behavioral, dietary, physical activity and self-reported health status. Anthropometric measurements were also conducted. Multivariable linear and logistic regression analyses were used to determine factors associated with serum lipid levels and dyslipidemia, respectively. Results: Results are presented for 2110 participants in this secondary analysis of which 60.3% were women with a mean population age of 58.54 ± 10.91 years. The HIV prevalence was 16.16% and did not differ substantially between men and women. Factors associated with total cholesterol level included age (unstandardized beta [95% CIs] was: 0.02 [0.01, 0.03]; p=0.014), male gender (-0.31 [-0.57, -0.05]; p=0.019), diabetes (0.31 [0.01, 0.61]; p=0.039), alcohol consumption (0.25 [0.02, 0.48]; p=0.038) and BMI (0.02 [0.01, 0.04]; p=0.030). Factors associated with triglycerides included age (0.01 [0.01, 0.03]; p=0.003), male gender (-0.09 [-0.19, 0.01]; p=0.053), diabetes (0.27 [0.13, 0.40]; p<0.0001), BMI (0.01 [0.01, 0.03]; p=0.044), hip circumference (-0.01 [-0.02, -0.01]; p=0.001) and waist circumference (0.01 [0.01, 0.02]; p<0.0001). Factors associated with HDL-C level included age (-0.01 [-0.01, 0.01]; p=0.055), male gender (-0.14 [-0.26, -0.02]; p=0.018), receiving ART (0.17 (0.04, 0.31); p=0.038), alcohol consumption (0.19 [0.07, 0.30]; p=0.002), waist circumference (-0.01 [-0.01, -0.001]; p=0.001) and visceral adipose tissue (-0.03 [-0.04, -0.01]; p=0.002). Age (0.02 (0.01, 0.03); p=0.005), male gender (-0.22 (-0.43, -0.01); p=0.044) and waist circumference (0.01 (0.01, 0.02); p<0.0001) were all associated with LDL-C levels. Being HIV+ and ART naive was associated with a higher risk of dyslipidemia (odds ratio [95% CIs] was 3.79 [1.27, 11.30]; p=0.032) compared to HIV negative participants. Other factors associated with dyslipidemia included being overweight (1.66 [1.20, 2.30] p=0.002) and obese (OR 1.85 [1.02, 3.35]; p=0.0004) and increased waist circumference (OR 1.02 [1.01, 1.03]; p<0.0001). Discussion and conclusion: We have demonstrated a high prevalence of HIV in an older population of rural South Africa, which mirrors the typical epidemiology of the epidemic in southern and eastern African regions. Our data suggest that HIV/ART status mainly influences HDL-C levels with ART use associated with higher HDL; and that untreated HIV infection can be linked to a greater risk of dyslipidemia. Dyslipidemia in the study population is driven by prevailing traditional cardiovascular risk factors such as obesity and diabetes. This data suggests that high ART coverage may reduce atherogenic risk and that lifestyle interventions to reduce the risk of obesity and diabetes are essential.
A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfillment of the requirements for the degree of Master of Science in Epidemiology in the field of Epidemiology & Biostatistics June, 2017