Background
In Sub-Saharan Africa (SSA), the majority of the inflammatory and metabolic data are from youth living in urban areas. We examined differences between youth with perinatally acquired HIV (YPHIV) in urban vs rural Uganda.
Methods
YPHIV (n=100) were enrolled from urban and rural Uganda in an observational cohort study along with age- and sex- matched, population-based HIV-seronegative (n=99) comparators. YPHIVs were on ART with HIV-1 RNA level ≤400 copies/mL. We compared fasting lipids, insulin resistance (HOMA-IR), and plasma inflammatory/gut biomarkers between rural and urban sites using Wilcoxon rank-sum tests and chi-square tests. Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) was conducted to identify key discriminating factors. General linear regression models were used to assess factors associated with metabolic and inflammatory biomarkers, adjusting for HIV status, socioeconomic factors, and other covariates.
Results
Median age was 16.2 years, there was more females in rural than urban Uganda (55% vs 48% respectively). Median viral load was 112 copies/mL, 52% rural vs 96% urban YPHIV had HIV-RNA <50 copies/mL, 93% of YPHIV were on TDF/3TC/DTG. OPLS-DA shows variables that could discriminate between urban and rural participants (Figure). More rural participants lived in extreme poverty, lacked access to clean water, and had lower dietary diversity compared to urban participants (p<0.001). Overall, compared to HIV-, YPHIV had lower BMI, higher waist-to-hip ratio, less dyslipidemia (p≤0.05), and higher sCD163, IFAB, IL6, hsCRP and sCD14 (p≤0.03). Urban YPHIV were more likely to have higher BMI, HOMA-IR, total cholesterol and low-density lipoprotein than rural YPHIV(p<0.001), however almost all biomarkers were higher in rural vs urban YPHIV including sCD14, sCD163, hsCRP, IL6, TNFRI, and LBP (p≤.015). After adjusting for demographic, socioeconomic, viral load and ART duration, only sCD14 remained elevated in the rural YPHIV (β-580, 95% CI -1015; -145).
Conclusions
Urban and rural participants have distinct socioeconomic, metabolic, and inflammatory signatures. The separation of these factors was not directly attributed to HIV status. The monocyte activation marker sCD14, was associated with HIV status and remained elevated in rural YPHIV even after adjusting for differences in HIV factors. Increasing the inclusion of rural populations in SSA is paramount as we focus on preventing cardiometabolic comorbidities in aging YPHIV.
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