title: Disparities in viral load and CD4 count trends among HIV-infected adults in South Carolina.
abstract: On a population level, trends in viral load (VL) and CD4 cell counts can provide a marker of infectivity and an indirect measure of retention in care. Thus, observing the trend of CD4/VL over time can provide useful information on disparities in populations across the HIV care continuum when stratified by demography. South Carolina (SC) maintains electronic records of all CD4 cell counts and HIV VL measurements reported to the state health department. We examined temporal trends in individual HIV VLs reported in SC between January 1, 2005 and December 31, 2012 by using mixed effects models adjusting for gender, race/ethnicity, age, baseline CD4 count, HIV risk category, and residence. Overall VL levels gradually decreased over the observation period. There were significant differences in the VL decline by gender, age groups, rural/urban residence, and HIV risk exposure group. There were significant differences in CD4 increases by race/ethnicity, age groups, and HIV risk exposure group. However, the population VL declines were slower among individuals aged 13-19 years compared to older age groups (p<0.0001), among men compared to women (p=0.002), and among people living with HIV/AIDS (PLWHA) with CD4 count ≤200 cell/mm(3) compared to those with higher CD4 counts (p<0.0001). Significant disparities were observed in VL decline by gender, age, and CD4 counts among PLWHA in SC. Population based data such as these can help streamline and better target local resources to facilitate retention in care and adherence to medications among PLWHA.
authors.affiliation: 1 Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina , Columbia, South Carolina.
authors.forename: Hrishikesh
authors.initials: H
authors.lastname: Chakraborty
authors.forename: Medha
authors.initials: M
authors.lastname: Iyer
authors.forename: Wayne A
authors.initials: WA
authors.lastname: Duffus
authors.forename: Ashok Varma
authors.initials: AV
authors.lastname: Samantapudi
authors.forename: Helmut
authors.initials: H
authors.lastname: Albrecht
authors.forename: Sharon
authors.initials: S
authors.lastname: Weissman
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D018791:CD4 Lymphocyte Count / Q000639:trends*; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D015658:HIV Infections / Q000097:blood / Q000208:ethnology* / Q000821:virology; D015497:HIV-1 / Q000302:isolation & purification*; D054624:Health Status Disparities; D006801:Humans; D008297:Male; D008875:Middle Aged; D010043:Outcome and Process Assessment, Health Care; D011159:Population Surveillance; D012367:RNA, Viral / Q000032:analysis; D012111:Residence Characteristics; D017678:Sex Distribution; D012959:Socioeconomic Factors; D013022:South Carolina / Q000453:epidemiology; D019562:Viral Load / Q000639:trends*; D055815:Young Adult
chemical_list: D012367:RNA, Viral