title: Improved employment and education outcomes in households of HIV-infected adults with high CD4 cell counts:  evidence from a community health campaign in Uganda.
abstract: BACKGROUND
  There is limited evidence on the association between socioeconomic outcomes and CD4 counts in populations that include HIV-infected adults who have high CD4 counts or have not been diagnosed. We examined this association among adults in a rural Ugandan parish.
  
  
  METHODS
  A community health campaign offering diagnostic and treatment services for HIV and other diseases was conducted with Ministry of Health support. Data on campaign participants' education and employment were collected and a detailed household socioeconomic survey was conducted among a subset of participants. Regression analyses were used to assess relationships between CD4 count and employment and education outcomes.
  
  
  RESULTS
  A total of 2323 adults (74% of the community) participated in the campaign; 179 of 2282 (7.8%) tested HIV-positive and 46% were newly diagnosed. Among HIV-infected adults not on antiretroviral therapy (ART), those with CD4 at least 500 worked 6.9 more days/month (P < 0.01; 39% more) and 2.5 more h per day (P < 0.05, 44% more) than those with CD4 less than 200. These effects were not significantly different from the effects for those with CD4 350-499. Children aged 6-11 years in households of adults with CD4 at least 350 did not have significantly different school enrollment rates than children in households of adults with CD4 less than 350, but differences were larger among children aged 12-18 years.
  
  
  CONCLUSIONS
  Outcomes of HIV-infected adults with CD4 at least 350 were better than those of adults with CD4 less than 200 and resembled those of HIV-uninfected adults. The results suggest that early ART initiation may generate economic benefits by preventing a decline in socioeconomic status, but further research is needed to determine the CD4 threshold at which these benefits would be largest.
authors.affiliation: Department of Health Policy and Management, University of North Carolina, Chapel Hill, NC, USA. harsha@unc.edu
authors.forename: Harsha
authors.initials: H
authors.lastname: Thirumurthy
authors.forename: Gabriel
authors.initials: G
authors.lastname: Chamie
authors.forename: Vivek
authors.initials: V
authors.lastname: Jain
authors.forename: Jane
authors.initials: J
authors.lastname: Kabami
authors.forename: Dalsone
authors.initials: D
authors.lastname: Kwarisiima
authors.forename: Tamara D
authors.initials: TD
authors.lastname: Clark
authors.forename: Elvin
authors.initials: E
authors.lastname: Geng
authors.forename: Maya L
authors.initials: ML
authors.lastname: Petersen
authors.forename: Edwin D
authors.initials: ED
authors.lastname: Charlebois
authors.forename: Moses R
authors.initials: MR
authors.lastname: Kamya
authors.forename: Diane V
authors.initials: DV
authors.lastname: Havlir
mesh_terms: D000293:Adolescent; D000328:Adult; D018791:CD4 Lymphocyte Count; D002648:Child; D003153:Community Health Services / Q000458:organization & administration*; D004522:Educational Status; D004651:Employment / Q000706:statistics & numerical data*; D005191:Family Characteristics; D005260:Female; D015658:HIV Infections / Q000453:epidemiology*; D007722:Health Knowledge, Attitudes, Practice; D006293:Health Promotion; D006297:Health Services Accessibility; D006801:Humans; D008297:Male; D017063:Outcome Assessment, Health Care; D010342:Patient Acceptance of Health Care; D011159:Population Surveillance; D012959:Socioeconomic Factors; D014454:Uganda / Q000453:epidemiology