Reproductive Health, HIV/AIDS and Poverty

Peter Glick

Cornell University, USA

pjg4@cornell.edu

Reproductive Health (WHO definition)

A state of physical, mental, and social well-being in all matters relating to the reproductive system at all stages of life

Reproductive Health Services (RHS)—‘standard’ and other

• Family planning• Maternal/antenatal care• STI treatment• HIV/AIDS prevention, testing and treatment • Condom provision/promotion• Male circumcision

Most of the HIV programs above are typically not part of standard RHS provision, but some argue they should be.

Interrelationships of Poverty, Reproductive Health,and HIV/AIDS

PovertyHIV

incidence/ prevalence

Reproductive Health

Services/ HIV interventions

Reproductive/ sexual

behaviors & knowledge

Reproductive Health

(non-HIV STIs, etc.)

What do we know about the links?

• Evidence• Policy issues• Methodological approaches• Gaps in knowledge: for further research

– Focus on what is useful and feasible for this project and for AERC researchers

HIV incidence/ prevalence

Reproductive Health

Services/HIV interventions

Reproductive/ sexual

behaviors & knowledge

Reproductive Health

(non-HIV STIs, etc.)

Pathways from reproductive health (and RH/HIV interventions) to HIV/AIDS

• Male circumcision:

Possibility of ‘risk compensation’

Our focus is on behavioral factors. Even for essentially medical interventions these can be important..

• Antiretroviral (ARV) therapy: Lower infectivity but increased sexual

activity of the treated Among others: ‘Treatment optimism’ effects

on behavior

Impacts of HIV interventions:

• Voluntary counseling and testing (VCT)

Behavioral interventions/services

• Information campaigns (e.g., ‘ABC’ approach)

• Condom provision, condom social marketing

• Other behavior change/education interventions

• Family planning/antenatal care (‘standard’ RHS)

Individual level randomization not very common, in part due to ethical considerations VCT study (Kenya, Tanzania): reductions in risky sex among those who

test positive and in serodiscordant couples, less among negative testers Male circumcision - ANRS Trial (S. Africa): cuts HIV acquisition by 2/3

Methodological challenges to evaluating behavioral HIV interventions

Randomized control trials (RCT) ideal

Community level randomization: Captures effects of local interactions and externalities

—through social networks, learning Intention to treat: accounts for uptake of programs

• STD control: Masaka and Rakai, Uganda; Mwanza, Tanzania

– Does efficacy varies with stage of the epidemic?

Community (or group) randomized trials

• School HIV education programs

Rakai, UG; Mwanza, TZ; rural Western Kenya; rural E. Cape, S. Africa

– Mixed findings for bio endpoints, behavior

Many other studies use a variety of non-experimental evaluation approaches: pre-,post-test designs, comparison groups, and (less commonly) instrumental variables, propensity score matching

Gaps in knowledge about impacts of HIV prevention strategies

• ‘ABC’ or just ‘C’? or just ‘A’?

• Behavioral impacts of ARV provision

• Efficacy of programs aimed at youth

• Advantages and disadvantages of integration of standard RHS and HIV prevention and care

• Mandatory/routine testing vs. VCT (opt out vs. opt in testing)

For many of these, social scientists can link up with planned interventions to assess behavioral outcomes.

Feedback linkages: HIV prevalence to reproductive/sexual behaviors

Effects on sexual risk behaviors (may have occurred in Uganda and elsewhere, though hard to

separate from effects of prevention campaigns):• Delayed age at first intercourse• Reduction in number of partners • Increased use of condoms

Effects on fertility not clear:• Reduction via reduced fecundity of HIV+ women • Reduction via fall in desired number of children (A. Young)

or increased prevention behavior (e.g., increase in AFI)..?• Increase via, e.g., ‘precautionary demand’ motive..?

Can examine the above using multi-country data (repeated DHSs) matched to HIV trends, or smaller multi-year datasets

PovertyHIV

incidence/ prevalence

Reproductive Health

Services/ HIV interventions

Reproductive/ sexual

behaviors & knowledge

Reproductive Health

(non-HIV STDs, etc.)

Pathways from poverty to reproductive health, services, and behavior and to HIV/AIDS

Poverty impacts on HIV/AIDS Potential impacts on HIV via reproductive health or risk behaviors and

knowledge:

The poor are• Less likely to know about prevention behaviors• Less likely to have had an HIV test• Less likely to have access to condoms• More likely to have untreated cofactor STIs

Other pathways:

The poor are more likely to have poor nutrition and health that can compromise immune defenses or increase receptivity to HIV infection

Knows that _ can prevent infection:

Limit PartnersBenin

Rural -0.008 -0.048 * 0.014 0.061 **Urban 0.046 * 0.008 -0.022 0.020

Burkina Faso Rural 0.077 0.063 0.092 0.095 *Urban -0.036 -0.003 0.017 0.047 **

GhanaRural 0.095 ** 0.059 ** -0.044 0.017Urban 0.009 -0.020 0.056 ** 0.052 **

KenyaRural 0.085 ** 0.053 -0.022 0.062 **Urban 0.020 0.075 ** 0.039 0.036

MozambiqueRural -0.078 0.174 * -0.078 -0.086Urban 0.002 0.000 0.014 0.024

NigeriaRural -0.027 0.018 -0.017 0.058Urban -0.048 0.054 0.039 0.155 **

TanzaniaRural 0.094 ** 0.102 ** 0.084 ** 0.054 **Urban -0.007 -0.003 0.008 0.000

UgandaRural ─ ─ ─ ─Urban ─ ─ ─ ─

Zambia

Rural 0.137 ** 0.094 * -0.086 0.183 **Urban 0.004 -0.037 -0.011 -0.034

Note: marginal effects from p robit models using most recent DHS Source: Glick and Sahn (2006). **: significant at 5%; *sig. at 10%

Men: Effects of Wealth on HIV Prevention Knowledge and Testing

Had HIV testCondom AbstinenceSample/Outcome:

Yet both within and across countries in Africa, HIV tends to be associated with greater wealth, not less…

• HIV prevalence is highest in relatively wealthy countries of Southern Africa (Botwana, S. Africa)

• More compelling: numerous recent DHS surveys with serotesting, as well as some earlier micro evidence, show generally positive associations of HIV prevalence and wealth

Why is a positive association of wealth and HIV observed?

The wealthy (and better educated) are more likely to have multiple concurrent partners:

Asset indexYears of

Schooling

BENINRural 0.021 -0.001Urban 0.074 * 0.007 *

BURKINA FASORural 0.087 * 0.001Urban 0.062 * 0.001

GHANARural 0.022 0.002 *Urban 0.016 0.001

KENYARural 0.033 * -0.001Urban -0.028 0.000

MOZAMBIQUERural 0.169 * 0.081 *Urban 0.051 * 0.131 *

NIGERIARural -0.039 0.005 *Urban -0.015 0.004 *

ZAMBIARural 0.001 -0.001Urban -0.188 * 0.003Note: based on ordered p robit estimates using most recent DHS Source: Glick and Sahn (2006)."*": sig. at 10% or better.

Men: Effects of wealth and education on the probability of having more than 1 sexual partner in the past year

The better-off in Africa:

• Can ‘afford’ more sexual partners (having multiple partners is a ‘normal’ good)

• Are more mobile

Less causally:

• HIV prevalence is higher in urban areas, which are wealthier

• HIV+ who are wealthy tend to survive longer, so more likely to show up in surveys

Impacts of Poverty on HIV/AIDS in Africa: Gaps in knowledge

• A development/HIV prevention conflict? Individual social/economic mobility increases HIV risk

– Should prevention policy target the better off?

• Does the poverty-HIV relation change as epidemics mature?

• Direct effects of wealth vs. structural/community cofounders

• Dealing with dynamics and simultaneity in estimation: HIV causes household impoverishment—limitations of cross section analysis

Can analyze (many of) there issues w/DHS, other surveys

Linkages from HIV/AIDS to poverty:Macro level perspectives

• Pathways: effects on supply of skilled labor, public budgets, firm investment, investments in education

=> (in theory) reduced growth, increased poverty

• Cross country regression analysis (data through mid,late 90s) suggest no or ambiguous effects on per capita economic growth. But for longer term impacts:

• Model results in conflict: ‘First generation models’: little effect on per capita

growth b/c of mortality: GDP falls but so does number of workers

A ‘reduced fertility dividend’? (Young) But other models (Bell et all.) predict huge falls in

per capita growth via collapse of investment in human capital, institutions

Effects on income:• Reduced labor supply, incomes or farm production, and• Health care expenses (S. Africa:1/3 household income); funeral expenses

=> Reduced consumption

Effects on children:

• Lower investments in schooling due to income, labor stresses

• Orphanhood => lower schooling: multicountry analysis by Monasch and Boerma, 2004, Case et al., 2004 Panel analysis for Kenya (Evans & Miguel) finds larger negative effects

Linkages from HIV/AIDS to poverty: Micro/household level perspectives

Impacts of HIV/AIDS on Poverty: Gaps in knowledge

• Intergenerational effects: education, health, socialization

Can analyze (many of) there issues w/DHS, other surveysBut panel data especially valuable

• Effects on fertility (micro), demographic transition (macro)• Modeling to predict long run economic, poverty effects

– Depends directly on parameters for behavioral responses (so good micro studies are essential)

• Coping mechanisms: effects on family/household structure, savings– How robust are family/community safety nets?