Washington D.C., USA, 22-27 July 2012www.aids2012.org

Improved employment and children’s education outcomes in households of HIV-positive adults

with high CD4 counts: evidence from a community-wide health campaign in Uganda

H. Thirumurthy*, G. Chamie, J. Kabami, V. Jain, T. Clark, D.

Kwarisiima, E. Geng, M.L. Petersen, M.R. Kamya, E.D.

Charlebois, D.V. Havlir, and the SEARCH Collaboration

*Department of Health Policy and Management, Gillings School of Global Public Health, UNC-Chapel Hill

Background

• HIV known to influence wide range of socio-economic outcomes– Several studies compare HIV and no-HIV households– Facility-based studies showing pre-ART SES decline

and post-ART improvement

• Association between CD4 and SES unknown, particularly among undiagnosed & untreated– Useful for assessing potential economic benefits of

early ART initiation– Requires population-level data, with CD4 information

Community-wide HIV testing

• Community health campaigns are a vehicle for widespread HIV testing– Essential component of test-and-treat strategy of

SEARCH Collaboration

• Campaign in May 2011 in rural community (population 6,000) near Mbarara, Uganda– All individuals offered rapid HIV testing and screening

for communicable & non-communicable diseases– Chamie et al., IAC 2012 Abstract # MOAE0103– Jain et al., IAC 2012 Abstract # TULBE04

Study objectives

• Determine the association between CD4 cell counts of HIV-infected adults and– Employment measures– Education outcomes of children

• Association examined for those on & not on ART• Primary research questions

– Over what range of CD4 counts do we observe declining SES?

– To what extent does poor adult health influence the well-being of children?

Data and methods

• Data collected on employment, education, and other characteristics of participants/households– All adult participants interviewed during CHC– After CHC, household survey of all HIV-infected and

random sample of HIV–uninfected participants

• Outcomes– Adult employment: # of days worked in past month and

# of hours worked on typical day in past week– Whether or not child reported to be enrolled in school

• Regression analysis used to determine association with CD4 count

Participant characteristics

• 2,323 adults attended one of three CHC sites (74% participation)

• 179/2282 (7.8%) of adults tested HIV+

• High female participation

• Campaign resulted in new diagnoses of HIV-infected adults with high CD4 counts

• 37% on ART

HIV- HIV+ P-valueN 2,103 179Female 65% 77% <0.01Age 39.5 33.2 <0.01Married 67% 58% 0.01Above primary education 20% 18% 0.52Above secondary education 4% 4% 0.93Household size 6.1 4.7 <0.01Number of children 2.7 1.9 <0.01

CD4 count among HIV+ Median 416IQR (283-568)

Newly diagnosed 46%On ART 37%

Participant characteristics

Primary occupation Asset comparison

HIV- HIV+N 2,103 179Peasant farmer 70% 63%Commercial farmer 2% 2%Market vendor 1% 3%Shopkeeper 2% 5%Transport worker 1% 3%Teacher 3% 3%Student 5% 1%Other 16% 20%

HIV- HIV+ P-valueN 2,103 179# acres of land owned 4.4 2.5 <0.01# acres ≥ 1 88% 72% <0.01# of cows owned 2.4 0.6 <0.01# cows ≥ 1 0.3 0.1 <0.01# of poultry owned 2.5 1.8 0.07

Significant differences in assets

Employment and CD4 cell count

• Among HIV+ adults not on ART, higher CD4 associated with more days worked per month

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25

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29

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35

Day

s w

ork

ed in

pa

st m

onth

0 100 200 300 400 500 600 700 800 900 1000 1100 1200CD4 cell count

Degree: 0Local polynomial smooth

Nonparametric regression results (kernel-weighted local polynomial, width=100, n=50)

Half-day increase in days worked for ΔCD4 of 100

Significantly higher employment at CD4≥500 among adults not on ART

• Compared to CD4<200, CD4≥500 associated with– 5.8 more days/month– 2.2 more hours/day (40%

more than ref. mean of 5.5)

• Linear regression model with age, age-squared, and sex included as controls

• ** p<0.05, * p<0.10• Reference group has CD4<200

Regression model coefficients(1) (2)

Outcome:Days worked in the

past monthHours worked on usual day in past

CD4<200 Reference ReferenceCD4 200-349 2.7 1.8CD4 350-499 4.8 0.9CD4 ≥500 5.8** 2.2*Observations 107 107CD4≥500 worked

nearly 1 week/month more than those with CD4<200, and as much as HIV-uninfected adults

Positive employment-CD4 association among adults on ART

• Compared to CD4<200, CD4 350-499 worked 6.4 more days/month

• Controlling for CD4 count, those on ART worked less than those not on ART

– Suggests benefit of avoiding CD4 decline through early ART initiation

• Linear regression model with age, age-squared, and sex included as controls

• ** p<0.05, * p<0.10• Reference group has CD4<200

Regression model coefficients(1) (2)

Outcome:Days worked in the

past monthHours worked on usual day in past

CD4<200 Reference ReferenceCD4 200-349 2.6 2.3*CD4 350-499 6.4* 0.4CD4 ≥500 3.4 1.4Observations 60 60

Adult CD4 count and children’s education

• In RLS with limited insurance & risk-coping mechanisms, adult health and productivity known to influence children’s outcomes

• Older children likely to be diverted away from school to provide on-farm or other labor

Better education outcomes at CD4≥350

• No association among young children

• Older children’s enrollment rates 15% higher in households with CD4≥350 compared to CD4<350

– 75% enrolled in CD4<350 households • Linear probability model with age, age-squared,

and sex included as controls• * p<0.10

Linear probability model coefficients(2) (3)

Outcome:Sample: Age 6-11 Age 12-18CD4<350 Reference ReferenceCD4 ≥350 0.04 0.15*Observations 50 57Mean (reference) 0.95 0.75

Enrolled in school

Conclusions

• Population-representative data that includes undiagnosed adults shows strong association between CD4 and employment– SES decline may begin at CD4 counts well above 500

• Early ART initiation could potentially maintain SES at levels similar to HIV-uninfected adults and households

• Longitudinal data and RCT design necessary for further establishing these benefits

Acknowledgements

Residents of Kakyerere Parish, Mbarara, Uganda

Kakyerere Parish Local Councilors

Uganda Ministry of Health

Geoff Lavoy, MU-UCSF