Rate of Dyslipidemia Higher Among Women Living With HIV

A Comparison of Metabolic and Cardiovascular Health in a Cohort to Study Aging in HIV

EAB Russell; AYK Albert; HCF Côté; AYY Hsieh; A Nesbitt; AR Campbell; EJ Maan; J Brophy; N Pick; MCM Murray


HIV Medicine. 2020;21(7):418-428. 

In This Article


Although studies of metabolic abnormalities and cardiovascular risk in PLWH have demonstrated increased risk in PLWH, studies focusing specifically on WLWH are rare. Women represent close to half of all persons living with HIV worldwide,[1] and as these women live longer with cART, it is important to understand the metabolic and cardiovascular changes women experience with HIV infection.

In our study, the age distribution differed between the two groups, and thus significantly fewer WLWH were menopausal at the study visit. In agreement with other studies,[35,36] WLWH had shorter LTL than HIV-negative women, suggesting increased cellular aging, although this was not significantly associated with any of the metabolic or cardiovascular outcomes presented here. There were nonsignificant associations between dyslipidaemia and both shorter LTL and lower mtDNA which may have reached significance had our sample size been larger.

Framingham Risk Score

We saw no significant difference in FRS between WLWH and HIV-negative women, although the literature suggests increased cardiovascular risk in WLWH.[11] FRS may not be a good marker of long-term cardiovascular risk in this relatively young population, and their lifetime risk may remain high.[25] HIV infection may expose this population to inflammatory pathways that increase cardiovascular risk but are not incorporated into FRS.[37] Alternative risk estimators for PLWH are currently lacking and are an area of future study.


Regardless of HIV status, there was a significant positive association between hypertension and ACB ethnicity among the study participants, which supports data from previous studies.[38]

Among WLWH, higher CD4 count was associated with an increased prevalence of hypertension. Although there is conflicting evidence,[39] higher CD4 count has been associated with higher BMI (as a measure of health),[40,41] which may explain this finding.

Metabolic Syndrome

Both lower mtDNA and smoking were independently associated with metabolic syndrome in all women. Under severe stress, mtDNA content may decrease as damaged mitochondria are eliminated,[42] possibly resulting in mitochondrial dysfunction. Mitochondrial dysfunction may in turn promote atherosclerosis and metabolic syndrome, as seen in mouse and human studies.[43,44]

As discussed above, the association between metabolic syndrome and higher current CD4 counts may be associated with improved health and weight gain. HIV medication may also play a role, as PI use was associated with metabolic syndrome in our WLWH. There is evidence that PI-based cART increases the risk of lipid derangements (which contribute to metabolic syndrome).[3,9] There is significant overlap between the diagnoses of dyslipidaemia and metabolic syndrome, as they share two criteria (triglycerides ≥ 1.7 mmol/L and HDL cholesterol ≤ 1.3 mmol/L). This overlap was illustrated in our sample, where most women with metabolic syndrome also had dyslipidaemia (23 of 28 HIV-negative women; 42 of 43 WLWH).


Nearly two-thirds of WLWH in our study met our criteria for dyslipidaemia, despite a relatively young median age (43.5 years), with participants as young as 12 years of age being included in the study. Among WLWH with dyslipidaemia, 33.7% were under the age of 40 years. Although FRS currently appears low, the cardiovascular risk in these women is likely to increase substantially as they age. Most women diagnosed with dyslipidaemia in this study met the criteria as a consequence of low HDL cholesterol measurements.

The association between HIV infection and dyslipidaemia seen in our study, and previously in PLWH, is probably multifactorial, involving host factors, direct effects of the virus, and cART.[45] HIV infection has been associated with overproduction of hepatic very low density lipoprotein cholesterol and decreased clearance of triglycerides.[3] It has also been associated with low levels of HDL cholesterol, and this is probably attributable to poor nutrition and direct effects of viral proteins, which promote atherosclerosis and affect HDL cholesterol metabolism.[3,45] When LDL cholesterol and triglycerides are normal, higher HDL cholesterol has been linked to a lower risk of cardiovascular disease.[46] Interventions such as physical activity, smoking cessation and weight loss that are linked to increased HDL cholesterol should therefore be encouraged in this population.[47]

In our sample, WLWH were significantly more likely to smoke tobacco, consistent with previous studies in PLWH,[48] and smoking was independently associated with both dyslipidaemia and metabolic syndrome. The life expectancy of PLWH who smoke is reduced compared to former or never smoking PLWH,[49] and thus smoking cessation is important to improve outcomes in PLWH.

Similar to meta-analysis findings in PLWH,[50] HCV infection was more prevalent in WLWH. Previous data suggest that HIV/HCV coinfection may increase the risk of cardiovascular events.[51] Although HCV infection was more prevalent in the WLWH cohort in our study, it did not appear to significantly modulate the increased prevalence of dyslipidaemia in our WLWH.

Strengths and limitations

Strengths. Our study included a local control group that shared many risk factors for cardiovascular and metabolic disease with the WLWH, reducing potential confounders. We included participants over a broad age range, allowing us to examine the effect of HIV while adjusting for age.

Limitations. As with all cross-sectional studies, it is not possible to determine causality. Furthermore, sample size may have limited our ability to detect small differences between groups, especially for less prevalent conditions. With respect to associations between cART and metabolic abnormalities or cardiovascular risk, we limited our investigation to current use and basic types of cART, and hence we cannot make inferences about specific antiretroviral agents.