HIV & Education in Young South African Women

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Presented at the Regional RENEWAL 3 Workshop at the Glenburn Lodge, South Africa.

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HIV & Education in Young South African Women

  1. 1. HIV &Education inYoung South African WomenCatherine MacPhail
  2. 2. UNAIDS 2006
  3. 3. 55% HIV Prevalence by Age and Gender among South African youth50% age 15-24 years45%40% Males Females35% 31.2% 95% Confidence Interval 28.9%30% 26.3% 25.0%25%20% 14.4%15% 13.8% 12.2% 11.0% 9.4%10% 7.9% 4.1% 6.0% 5.8% 4.0%5% 2.3% 3.6% 2.1% 2.6% 4.1% 2.0%0% Age Age Age Age Age Age Age Age Age Age 15 16 17 18 19 20 21 22 23 24 Pettifor A, et al. AIDS 2005, 19: 1525-1534.
  4. 4. High risk behaviors not observed• We found that young South African women do not report engaging in “high risk” sexual activity, despite the incredibly high incidence and prevalence of HIV among young women.• The median age of first sex in our national sample of 15-24 year olds was 17 for young women and 16 for young men• 7.8% of young women reported having sex before the age of 15• Condom use at last sex was reported by 48% of young women and 57% of young men.• Young women reported a mean of 2.3 lifetime partners and young men 4.9 partners.• Among sexually active young women, the mean and median age of first pregnancy was 18 years.• Only 2% of young women reported ever having engaged in transactional sex.
  5. 5. Determinants of Infectiousness and Susceptibility in Young Women• Behavioral/Contextual/Structural – Gender power inequities • Less able to negotiate condom use (Unprotected sex) • Less able to refuse unwanted sex (Forced sex) – Older male partners – Sugar Daddies? Transactional sex? – Education/Poverty• Biological – Anatomy – Higher Transmission Probability from Men to Women – Use of Hormonal Contraception? – STIs – Pregnancy?
  6. 6. Underlying Proximate Biological Health Demographic determinants determinants determinants outcomes outcome New sex partner “c” Context Coital frequency Exposure of Socio-economic Concurrency susceptible toSociocultural including Abstinence infected person gender Sexual mixing Demographic Education Intervention Condom use programs Other STIs “β” HIV Circumcision Efficiency of Disease MortalityHIV testing &counseling infection STI control Type of sex transmission Education for Biological per contactknowledge & changing susceptibility attitudes Treatment w/ARVs “D” Treatment of OIs Duration of infectivity Proximate-determinants framework for factors affecting the risk of sexual transmission of HIV (Boerma & Weir JID 2005)
  7. 7. Education in young women in South Africa• Among young women with one lifetime partner, those who had not completed high school were almost 4 times more likely to be HIV infected compared to those that had completed HS (AOR 3.75 95% CI 1.34–10.46) (Pettifor A et al. IJE 2008)
  8. 8. Education and HIV: protection or risk?• Data from early in the epidemic suggested that more education was associated with increased risk of HIV infection• Two recent reviews on HIV and education indicate a protective association between higher education and HIV infection, particularly as epidemics mature (Hargreaves et al. AIDS 2008, Jukes et al. AIDS 2008)
  9. 9. Promising data from longitudinal studies• In Zambia, young women with more education were less likely to be HIV infected than those with less education, and declines in infection rates from 1995-2003 were greatest in young women with the most education (Michelo C et al. AIDS 2006)• In Uganda, HIV infection rates declined most rapidly in young women with a secondary school education (de Walque D et al. TMIH 2005)• In South Africa, participants were 7% less likely to become infected with HIV for each year of education they had completed (Barnighausen T, et al AIDS 2007)
  10. 10. A Social Vaccine? HIV prevalence by education category, Rural Uganda, 1990-2001. Individuals aged 18-29De Walque and J Whitworth, MRC Uganda (2002)
  11. 11. Percentage of young women and men age 15-24 whoreported being in school (primary or secondary) in South Africa 2003
  12. 12. Percentage of young women and men 15-24 completing grade 12 (High School (HS)) in South Africa 2003
  13. 13. Association between school attendance and HIV awareness,sexual behavior and HIV infection among 3682 females aged 15-19 from South Africa, 2003 Currently Dropped out Adjusted for Unadjusted Variable Attending or Never age, province Model School Attended and urban/rural N % N % POR (95% CI) aPOR (95% CI) Total N 2800 882Knows ways to prevent 2672 95.5 814 92.3 0.97 (0.93, 1.01) 0.97 (0.94, 1.00)HIV infectionLack of Parental 1448 52.0 503 56.5 1.09 (0.92, 1.28) 1.02 (0.84, 1.23)CommunicationNot Had an HIV test 2484 89.2 650 74.4 0.83 (0.75, 0.93) 0.85 (0.74, 0.96)Ever had sex 1075 36.5 666 76.3 2.09 (1.83, 2.38) 1.47 (1.32, 1.62)Unwanted sex at 77 7.1 37 6.2 0.87 (0.46, 1.66) 0.93 (0.50, 1.73)debut*More than 1 partner 161 17.0 94 11.6 0.68 (0.42, 1.12) 0.83 (0.55, 1.26)during previous year*Early Debut* 159 13.2 115 16.3 1.24 (0.69, 2.24) 2.40 (1.66, 3.48)Ever pregnant 207 17.6 351 54.1 3.07 (1.90, 4.96) 2.41 (1.70, 3.42)Ever pregnant before 150 11.3 221 33.0 2.93 (1.28, 6.23) 3.19 (2.06, 4.96)age 18Partner AgeDifference* 105 8.6 121 15.8 1.84 (1.28, 2.66) 1.68 (1.14, 2.49)(partner >3 years vs. <2years older)No condom use at least 428 34.7 400 58.2 1.67 (1.22, 2.31) 1.38 (1.10, 1.72)sex*HIV-positive 180 5.8 121 11.4 1.97 (1.38, 2.80) 1.24 (0.83, 1.86)
  14. 14. Association between school attendance and HIV awareness, sexual behavior and HIV infection among 3555 males aged 15-19 from South Africa, 2003 Currently Dropped out or Adjusted for age, Unadjusted Variable Attending Never province and Model School Attended urban/rural N % N % POR (95% CI) aPOR (95% CI)Total N 2836 719Knows ways to prevent 2684 92.4 645 82.6 0.89 (0.80, 1.00) 0.87 (0.80, 0.96)HIV infectionLack of Parental 1831 62.5 438 64.1 1.03 (0.81, 1.30) 1.16 (0.92, 1.46)Communication 2569 91.1 605 90.5 0.99 (0.94, 1.05) 0.99 (0.96, 1.03)Not Had an HIV testEver had sex 1257 46.9 503 59.0 1.26 (0.90, 1.75) 1.01 (0.88, 1.15)Unwanted sex at debut* 7 0.3 4 0.9 2.84 (0.57, 14.2) 2.06 (0.66, 6.48)More than 1 partner 439 42.1 181 45.5 1.08 (0.87, 1.34) 1.09 (0.88, 1.34)during previous year*Early Debut* 292 29.3 88 18.8 0.64 (0.49, 0.84) 1.16 (0.71, 1.89)Partner AgeDifference* 4 0.5 7 0.6 1.36 (0.23, 8.02) 1.02 (0.06, 16.24)(partner >3 years vs. <2years older)No condom use at least 473 43.7 201 42.2 0.97 (0.72, 1.30) 1.20 (0.94, 1.54)sex*HIV-positive 77 2.5 27 2.4 0.97 (0.52, 1.78) 0.96 (0.51, 1.80)
  15. 15. Proportion of young South African women ages 15-19 who dropped out of high school by current sex partner age difference (n=1750)
  16. 16. Proportion of young South African women ages 20-24 who reported completing high school by the age difference of their most recent sex partner (n=1848)
  17. 17. Reduced risk of sexual behaviors associated with school attendance• Study of ~2000 14-25 year olds in rural South Africa• Young female students less likely – To have 2 or more partners – To have a partner > 3 yrs older – To have had unprotected sex in the last year• Young male students less likely – To have three or more partners – To have HIVHargreaves et al. J Epi Comm Health 2008.
  18. 18. Impact of education extends beyond HIV to almost every health and development outcome • Better educated women are more likely than their less educated peers to delay coital debut, use condoms more often, delay marriage and childbearing, have fewer children and healthier babies, and enjoy better earning potential. • In 17 countries in Africa and 4 in Latin America, better-educated girls were found to delay age of first sex and were more likely to use condoms.World Bank. Education and HIV/AIDS a window of hope. Washington D.C.: World Bank; 2002.
  19. 19. Education and HIV risk: causal mechanism BLACK BOX Reduced risk ofEducation HIV infection Exposure to HIV messages
  20. 20. Education and HIV risk: causal mechanism BLACK BOX Reduced risk ofEducation HIV infection Better understanding of messages
  21. 21. Education and HIV risk: causal mechanism BLACK BOX Reduced risk ofEducation HIV infection Increased self- esteem/self efficacy/decision making power
  22. 22. Education and HIV risk: causal mechanism BLACK BOX Reduced risk ofEducation HIV infection Different social/sexual networks
  23. 23. Education and HIV risk: causal mechanism BLACK BOX Reduced risk ofEducation HIV infection Structured time in school
  24. 24. Education and HIV risk: causal mechanism BLACK BOX Reduced risk ofEducation HIV infection Socio-economic status
  25. 25. Why target girls?• HIV incidence highest in young women• Barriers to school attendance and drop out appear greater for girls than boys• Observed effects on education and HIV are greater for girls than boys• Programs that have reduced barriers to education have had greater effects for girls than boys
  26. 26. Barriers to Education• For many poor families the costs associated with school make it an economic impossibility.• School fees/costs of education represent an important barrier to school attendance in South Africa and are often cited as reasons for not attending an educational institution and for not furthering education.• In South Africa, 65% of young people who were not in school indicated that they did not have enough money to continue their education.• The second most common reason for school drop-out for girls is pregnancy; 30% of girls who were not in school indicated that they left school due to pregnancy. Samson 2004
  27. 27. Barriers to education (2)• Young women are often taken out of school to find employment to support the family or to care for sick family members.• Family commitments was cited as the reason for not attending an educational institution by 9% of non-school attending South African females, as opposed to <1% of non-attending males
  28. 28. Cash Transfers to keep young women in school• Children in South African households that receive government social welfare grants are more likely to attend school and the observed effects are greater for young women than young men (Samson 2004) – the greatest benefit of social welfare grants on educational outcomes appears to be for young women from the poorest households
  29. 29. Cash Transfers increase school attendance• In Mexico, the Progresa program, which provides conditional cash transfers to poor families to send their children to school, has found that the program increases school enrollment, particularly for girls (Schultz T IFPRI 2000)• Evaluations also find positive impacts on girls school enrollment and/or attendance at primary and/or secondary levels in Nicaragua, Ecuador, Colombia, Brazil, Jamaica, Bangladesh, Cambodia, Turkey, and Pakistan (Adato and Bassett 2008)
  30. 30. Do reducing barriers to education reduce HIV risk?• One RCT conducted in Kenya where school uniforms were provided free of charge, a reduction in self-reported pregnancy was documented (Duflo E et al. 2006)
  31. 31. Study Design CM Yes CM NoCCT Yes CCT+ CM CCT OnlyCCT No CM only No intervention
  32. 32. Study Site • Agincourt area, Mpumalanga • DHSS site – population ~84,000 • ~2,500 HH with girl aged 14-16 years • Wealth quintile associated with school attendance • 21 secondary schools • High HIV prevalence
  33. 33. Study Objectives1. Impact of CCT on girls’ HIV risk compared to control group2. Impact of community mobilization on general population aged 18-35 years compared to control communities3. Comparison of HIV risk among young women receiving CCT in CM villages with girls receiving CCT alone
  34. 34. Study Assessments COMMUNITY (18-34 years) •ACASI assessments at baseline & 36 months (n=1200) •Ethnography - mobilizationHOUSEHOLD ACASI assessments at baseline & 36 monthsGIRLS •ACASI assessments at baseline, 12, 24, 36 months •Ethnographic Research quarterly •School Attendance monitoring
  35. 35. Study Measures ACASI •Unprotected sex in past 3 months •PregnancyGIRLS •Age difference with partner •School attendance •Sexual debut •HIV •HSV2
  36. 36. Study Measures Ethnography •How did CT work? •Did parents ensure school attendance? •How did it change life?GIRLS •Did it reduce barriers to education? •Impact on unprotected sex? •Did it reduce HIV risk and how? • What did HH do with money?
  37. 37. Study MeasuresHOUSEHOLD Living Standards Measurement SurveyGIRLS
  38. 38. Study Measures COMMUNITY (18-34 years) •Gender norms •Social Mobilization •Collective EfficacyHOUSEHOLD •Unprotected Sex •Concurrency •Intimate Partner ViolenceGIRLS
  39. 39. Formative Research •Confirm poverty as main reason for drop outIDIs •Food FGDs •Pregnancy a major factor (10/15) •Decision made by girl •Parents think education important BUT don’t act on this belief •Educators report lack of parental involvement •Limited feedback on intervention
  40. 40. Formative Research• Next phase – Better information on planned intervention using scenarios in FGDs – School survey to better understand implementation of programme in schools

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