VZCZCXRO7016
RR RUEHDU RUEHJO RUEHMR
DE RUEHSA #4995/01 3611325
ZNR UUUUU ZZH
R 271325Z DEC 05
FM AMEMBASSY PRETORIA
TO RUEHC/SECSTATE WASHDC 0649
INFO RUCNSAD/SOUTHERN AFRICAN DEVELOPMENT COMMUNITY
RUCPDC/DEPT OF COMMERCE WASHDC
RUEATRS/DEPT OF TREASURY WASHDC
RUEAUSA/DEPT OF HHS WASHDC
RUEHPH/CDC ATLANTA GA 0952

UNCLAS SECTION 01 OF 02 PRETORIA 004995 
 
SIPDIS 
 
STATE PASS TO AID WASH DC 
 
SIPDIS 
 
DEPT FOR AF/S; AF/EPS; AF/EPS/SDRIANO 
DEPT FOR S/OFFICE OF GLOBAL AIDS COORDINATOR 
STATE PLEASE PASS TO USAID FOR GLOBAL BUREAU KHILL 
USAID ALSO FOR GH/OHA/CCARRINO AND RROGERS, AFR/SD/DOTT 
ALSO FOR AA/EGAT SIMMONS, AA/DCHA WINTER 
HHS FOR THE OFFICE OF THE SECRETARY/WSTEIGER, NIH/HFRANCIS 
CDC FOR SBLOUNT AND DBIRX 
 
E.O.  12958: N/A 
TAGS: ECON KHIV SOCI TBIO EAID SF
SUBJECT:  LINKS BETWEEN POVERTY AND HIV/AIDS 
 
Summary 
------- 
 
¶1.  Summary.  In December 2005, an International Union for the 
Scientific Study of Population (IUSSP) conference in Cape Town 
presented demographic studies that highlighted the interactions 
between poverty and HIV/AIDS in Southern African nations of 
Malawi, Zambia, and South Africa.  No direct evidence was shown 
that poverty causes HIV/AIDS but there were strong correlations 
and associations between the two.  Because most of the new 
information was coming from surveying the same people over time 
(panel surveys), much discussion centered around the problems 
and interpretations of using this type of data for empirical 
investigations.  Eight of the 12 studies used Demographic 
Health Surveys, household-based national surveys having little 
detailed information concerning income.  These studies had to 
impute assets using either type of flooring, housing or other 
asset information having a presumed correlation with income, 
making the analysis of the interaction of poverty and HIV/AIDS 
subject to possible measurement and specification errors.  The 
South African studies used local surveys (in Free State and 
KZN) trying to determine the impact of socio economic status on 
orphans, antiretroviral treatment, and HIV affected households. 
Most studies showed relationships between poverty and HIV/AIDS, 
but no clear cut causation.  End Summary. 
 
Poverty and HIV/AIDS 
-------------------- 
 
¶2.  Prominent African politicians and researchers have long 
posited causality between poverty and HIV/AIDS, suggesting that 
increased poverty causes high HIV/AIDS prevalence.  In 
December, The International Union of Scientific Study of 
Population (IUSSP) sponsored a conference in Cape Town that 
presented 12 papers addressing the impacts of poverty and 
HIV/AIDS, focusing on income effects on topics ranging from 
orphans to receiving antiretroviral treatment.  The conference 
organizers hoped to provide empirical evidence on the 
hypothesis that HIV/AIDS' main solution lies in eradicating 
poverty. 
 
¶3.  The demographic studies focused on Southern African 
countries and used a variety of household panel surveys that 
were not designed for the specific study of HIV/AIDS 
interactions.  Several studies used Demographic Health Surveys, 
(nationally representative household surveys collected every 5 
years in most developing countries), or national and provincial 
surveys.  Focus countries included Malawi, Zambia, South 
Africa, Kenya, Cambodia, Thailand and Tanzania.  All studies 
used several waves of panel data, trying to discover long run 
impacts in order to highlight poverty's impact on various risk 
behaviors associated with higher HIV prevalence. 
 
¶4.  Four studies concentrated on South Africa, using provincial 
surveys, making generalized national observations difficult. 
The South African studies examined the socio-economic impacts 
of HIV/AIDS on household in the Free State; impacts of parental 
death on school enrollment in KZN; orphans and HIV risk 
behaviors among adolescents in KZN; and socioeconomic status as 
determinants in treatment outcomes in the Free State.  One Free 
State study (primary researcher, Sebastian Linnemayr from Ecole 
Normale Superieure, using data collected in a USAID-funded 
study at the University of the Free State) grouped HIV affected 
and non-affected by amount of liquid and illiquid assets and 
found the assets to be similar among groups, although since 40% 
of people had no income in both groups, one could argue that 
poverty impacted the results.  The study of the impacts of 
parental death on school achievement in KZN (primary 
researcher, Anne Case from Princeton University) found that 
that there was no link between socio economic status (SES) if 
the mother died, and a negative association if the father died; 
however children without mothers are behind in school relative 
to other children.  The study focusing on the orphanhood, 
poverty and HIV risk behaviors in KZN (prime researcher Kelly 
Hallman from the Population Council) found that orphans did 
begin sexual relations earlier than non orphans and differing 
income effects by gender, with girls in households with higher 
income having lower chances of early sexual debut while boys 
had higher chances of multiple partners.  Frikkee Booysen's 
 
PRETORIA 00004995  002 OF 002 
 
 
study (of the University of the Free State) found that only the 
well-off felt that they were getting the benefit of anti- 
retroviral treatment, having been on treatment and knowing 
their status longer. 
 
¶5.  The South African studies used different measures of 
poverty.  Hallman's study used consumption and household asset- 
based measures, Case's study used expenditures, assets, and 
access to piped water and electricity as indicators of wealth. 
Booysen's and Linnemayr's studies used the same Free State 
panel data which collected income, asset and access to services 
information.  Of the four studies, two found that income did 
not explain differences in HIV-impacted households or orphans 
and two found income to be an important determinant. 
 
¶6.  Studies that focused on other countries in Africa also 
found that income's impacts varied.  A Malawian study focused 
on the impact of HIV/AIDS on Intra-household Time Allocation 
and concluded that HIV/AIDS had no impact on men's allocation 
of time and it caused women to diversify income sources.  In a 
Zambian (focusing on prime age mortality, rather than death by 
HIV/AIDS) study, women's prime age mortality was not affected 
by income; prime age mortality is more likely to affect wealthy 
men. 
 
¶7.  All presented studies were preliminary and discussion 
focused on inherent problems using panel data.  Panel data 
gives temporal explanation but no causality.  Selectivity 
(caused by attrition in survey respondents) and measurement 
error biases are present.  Omitted variables and unobserved 
fixed effects also presents empirical challenges.  One 
agreement came from the conference:  further research is needed 
on the links between poverty and HIV/AIDS. 
 
TEITELBAUM