Education and HIV/AIDS
A report prepared for the UNESCO Global Monitoring Report 2005 by Matthew
Jukes and Kamal Desai.
Section 1 – The relationship between Education and HIV prevalence
As the HIV epidemic shows few signs of slowing in Africa, and threatens to gather
momentum in much of Asia and Eastern Europe, an effective prevention response is
desperately sought. An educated population may be an important foundation for this
response. This paper examines the relationship between schooling, sexual behaviour
and HIV prevalence and investigates the role expanded primary school access and
increased literacy can play in tackling the HIV epidemic. The following sections
consider the relationship between literacy and HIV at the national level and then
examines data concerning sexual behaviour and HIV infections and its relationship
with education.
National level associations between Education and HIV.
At the national level in Africa there is a positive relationship between literacy rates
and HIV infection rates (Figure 1)1: More literate countries have higher rates of HIV
infection. More literate African countries tend to be the most developed on the
continent and they share a number of features that make them vulnerable to high rates
of HIV infection. First the most developed countries often have the largest income
disparities between men and women, a factor associated with HIV infection rates
(World Bank, 1997). Similarly, employment in the formal sector is associated with
HIV infection (Barongo, Borgdorff, Mosha, Nicoll, & al., 1992; Serwadda et al.,
1992). Second, increased migration and improved transport infrastructure can
facilitate the spread of HIV (Caldwell & Caldwell, 1993). Similarly, urban residence
is associated with higher levels of HIV infection (Barongo et al., 1992; Boerma,
Urassa, Senkoro, Klokke, & Ng'weshemi, 1999; Fylkesnes et al., 1997;
1
Permission not yet sought for reproduction of graphs.
1
Serwadda et al., 1992). Finally, as discussed below, higher levels of education per
se are associated with higher infection rates.
Although various demographic and socioeconomic conditions put the educated at
greater risk of HIV infection it has been hypothesized (Simon Gregson, Waddell, &
Chandiwana, 2001; Over & Piot, 1993) that they will be more likely to change their
behaviour in response to information about the epidemic. One way in which this trend
may manifest itself at the national level is in the weakening of the relationship
between literacy and HIV infection rates as the epidemic matures. In the early stages
of the epidemic the most educated will be at great risk and a strong relationship will
be expected between literacy and HIV infection rates. In later stages of the epidemic,
when information is available about prevention methods and education campaigns
have begun, the educated are more likely, it is argued, to change their behaviour and
this mitigates against socioeconomic factors putting them at greater risk of infection.
We would therefore expect the relationship between national HIV infection and
literacy to be weaker in later stages of the epidemic. This hypothesis has been tested
(Simon Gregson et al., 2001) by comparing the relationship between adult HIV
prevalence in 1999 and adult literacy in 1998 in three different regions of sub-Saharan
African. In two regions the epidemic is more mature and the relationship between
HIV prevalence and literacy is relatively weak. In West and Central Africa, a 1%
increase in national literacy rates is associated with a 0.077% rise in national HIV
prevalence; in East Africa a 1% rise in literacy rates is associated with a 0.033% rise
in HIV prevalence. For example, the literacy rates in Kenya (~80%) were much
greater than in Ethiopia (~40%) in 1998 but HIV prevalence estimates at the time
were similar for the two countries (~12% and ~10% respectively). This stands in
contrast with the relatively recent epidemic in Southern Africa where a 1% rise in
literacy rates is associated with a 0.35% rise in HIV prevalence. For example,
Zimbabwe has a higher literacy rate (~85%) than Malawi (~60%) and similarly
Zimbabwe has one of the highest prevalences in region (~23%) and Malawi one of
the lowest (~17%).
Thus, the evidence suggests that there is a strong relationship between education and
HIV prevalence in the early stages of an epidemic, but a weaker relationship or no
relationship in more mature epidemics. This analysis is consistent with the hypothesis
that education prepares individuals better to mount a response to the HIV/AIDS
2
epidemic but for a more fine-grained assessment of the hypothesis we look at the
relationship between HIV infection and education at the level of the individual.
Education and HIV at the level of the individual
Education and sexual behaviour
As with the picture at the national level, an individual level analysis suggests that
educated individuals should be at greater risk of infection at the early stages of an
HIV epidemic but should be better equipped to change their sexual behaviour when
faced with the facts of HIV transmission. There are a number of aspects of the sexual
behaviour of more education individuals that initially puts them at great risk of
infection. More educated individuals change partners more rapidly, in part because
they are more mobile and because they have greater control over their own sexual
behaviour (A. Blanc, 2000). The higher socioeconomic status of more educated men
gives them a greater disposable income, increase leisure time, increased ability to
travel and to use commercial sex partners (Berkley et al., 1989; Dallabetta et al.,
1993; Quigley et al., 1997). In addition, more educated women start having sex later
but delayed marriage to an even great extent. This leads to them being single and
sexually active for a longer period of time and thus to them having a greater number
of sexual partners (A. K. Blanc & Way, 1998). Choice of contraceptives may also be
influenced by education. Although educated people may be more likely to use
contraception overall, they are also more likely to choose methods, such as the
contraceptive pill, which do not protect against sexually transmitted diseases such as
HIV. Taken together, and in the absence of any response to an epidemic, these factors
increase the vulnerability of more educated individuals to HIV infection in the early
stages of an epidemic.
However, evidence and theory suggest that educated people should be more likely to
adopt safe sexual practices in response to health promotion (Fylkesnes et al., 1997)
or from other sources of information about HIV/AIDS. Social cognitive models point
to several key determinants of sexual behaviour. In all theories, knowledge and
understanding of a behaviour and its consequences is a necessary but not sufficient
condition for performing the behaviour and underpins the perception of (Rosentock,
1990) and attitudes (I Ajzen, 1985) towards that behaviour. In the context of HIV,
3
understanding transmission routes and methods to block them are essential for the
adoption of safe sexual behaviour. More educated people are more likely to be
exposed to such information as part of formal schooling and also through the media
(S. Gregson, Zhuwau, Anderson, & Chandiwana, 1998). For example, a study in 32
countries found that literate women were three times more likely than illiterate
women to know that a healthy looking person can have HIV, and four times more
likely to know the main way s to avoid AIDS (Vandemoortele & Delamonica, 2000).
Greater levels of education may also provide a framework of biological knowledge
and understanding of causality into which HIV prevention messages can be
assimilated. For example, children with a deeper understanding of the biological
mechanisms of viruses are more resistant to myths about HIV transmission
(Keselman, Kaufman, & Patel, 2004). A second key determinant of behaviour is the
perceived control one has over the behaviour. This includes self-efficacy, one’s belief
in one’s capabilities to perform a specific action required to attain a desired outcome
(Bandura, 1977), the perceived personal power one has over the behaviour (I Ajzen,
1985) and the actual personal power one has over a behaviour (I. Ajzen, 2002).
Evidence suggests that education is associated with increased self-efficacy in general
(Bandura, 1977) and in the context of the HIV epidemic in sub-Saharan Africa in
particular (Lindan et al., 1991). In addition, more educated people are more likely to
believe they have control over their own behaviour, rather than another individual or
fate, and they are more likely to have actual control over their own behaviour. For
example, educated women are more able to negotiate safe sex with a partner (GCE,
2004).
This analysis suggests that education should lead to a greater adoption of safe sexual
behaviour in response to the HIV epidemic. Data from Demographic and Health
Surveys (DHS) in 11 countries (GCE, 2004) showed that women with primary school
education were more likely than those with no education to report using a condom at
last sex. In nine of these countries, secondary education was associated with a further
increase likelihood of using a condom at last sex. Another study in Zimbabwe
(Simon Gregson et al., 2001) found that women with secondary education were less
likely to report having had unprotected casual sex. A study in the four African cities
of Cotonou in Benin, Ndola in Zambia, Yaoundé in Cameroon, and Kisumu in Kenya
found that education led to less risky sexual behaviour. Condom use was more
common amongst more educated individuals in all four cities (Lagarde et al., 2001).
4
Exchange of money for sex was less likely amongst educated women in all four cities
and amongst more educated men in Yaoundé. Non-marital sex without a condom was
less prevalent among more educated women in all four cities and among more
educated men in Cotonou and Kisumu. In Yaoundé, more educated men and women
were less likely to have sex with a casual partner on the day of meeting, and in Ndola,
for both men and women, not knowing a partner’s age was much more common
among those with little schooling (Glynn et al., 2004).
Other behaviours that reduce HIV infection are also more common among the
educated. For example, more educated people are more likely to seek treatment for
other sexually transmitted diseases which would otherwise increase their chances of
becoming infected with HIV (A. Blanc, 2000). Overall, the evidence suggests that
more educated people are at a greater risk of HIV infection in the early stages of an
epidemic but tend to adopt less risky sexual behaviours in response to the epidemic.
How is this reflected in empirical data on HIV prevalence and its relationship with
education?
Education and HIV prevalence
The majority of studies investigating this issue have found a positive relationship
between education and HIV infection. That is, HIV prevalence is higher among
educated individuals. This was found at the population level in data from Rakai,
Uganda in 1990 and 1992 (Kirunga & Ntozi, 1997; Smith et al., 1999); from Mwanza,
Tanzania in 1991-1996 (Grosskurth et al., 1995; Quigley et al., 1997; Senkoro et al.,
2000) and amongst women attending ante-natal clinics in Fort Portal, Uganda in
1991-4 (Kilian et al., 1999) and in Zambia in 1994 and 1998 (Fylkesnes et al., 2001;
Fylkesnes, Ndhlovu, Kasumba, Musonda, & Sichone, 1998). In all cases, the
relationship was adjusted for age, sex and setting (urban or rural). Five population
based studies found the opposite trend. Education had a protective effect against HIV
among young women of Manicaland, Zimbabwe from 1998-2000 (Simon Gregson
et al., 2001), among men and women in Masaka district in Uganda in 2000 but not in
1990 (De Walque, 2002), among women in Youndé, Cameroon and men in Cotonou,
Benin (Glynn et al., 2004) and against HIV-2 infection in the Gambia (Wilkins et al.,
1991). Two Ethiopian studies focusing on sub-populations found opposing trends.
Education was related to lower HIV prevalence amongst sugar estate workers
5
(Fontanet et al., 2000), but higher HIV prevalence in male army recruits in rural areas
(Abebe et al., 2003). Several large studies of HIV prevalence among 21-year old Thai
army recruits found that those with more years of education had lower levels of HIV
infection (Carr et al., 1994; Mason et al., 1998; Mason et al., 1995; Nelson et al.,
1993; Sirisopana et al., 1996) although no relationship between HIV and education
was found in studies from Northern Thailand where the prevalence is highest
(Celentano et al., 1996; Dobbins et al., 1999; Nopkesorn et al., 1993). Several other
studies found that HIV prevalence and education were not statistically related,
including studies in Zimbabwe (S. Gregson et al., 2001), in Ndola, Zambia and
Kisumu, Kenya (Glynn et al., 2004) and in 7 of the 27 studies reported in a review
(Hargreaves & Glynn, 2002).
There is no consistent pattern in these results. This inconsistency may represent the
combination of two opposing trends in the data: the initial increased vulnerability of
educated individuals to HIV infection followed by their more rapid behavioural
change once informed about the epidemic. The studies reported do allow us several
opportunities to try and pick apart these two trends from their data by analyzing the
evolution of these trends with epidemic maturity.
Changing relationship between HIV and education with epidemic maturity
It is notable that the majority of studies conducted in Africa until the mid 1990s found
higher HIV prevalence among the more educated whereas later studies were more
likely to find the opposite. This is consistent with the view that educated Africans
were more at risk of HIV infection initially and were only equipped with the
information required to mount a response to the epidemic years later. In Thailand the
picture is different. The HIV epidemic was monitored by existing mechanisms and
was initially confined to high-risk groups. This allowed the spread of information
about the epidemic before the spread of the disease to the general population. This is
perhaps why the most educated individuals are protected from HIV from the early
1990s.
More direct evidence addresses the hypothesis that the relationship between HIV and
education evolves as the epidemic matures. The clearest evidence comes from a serial
6
cross-sectional survey in the rural areas of Masaka district, Uganda (De Walque,
2002). The national prevalence of HIV in the adult population declined from its peak
of 14% in the early 1990s to around 5%, largely due to a strong prevention campaign
(Stoneburner & Low-Beer, 2004). As illustrated in Figure 2, the rate of decline in
prevalence was greater for those with secondary education and those with primary
education showed faster decline in prevalence than those with no education. The
chances of contracting HIV infection during this period was reduced by 6.7% for each
year spent in education (De Walque, 2002) and those with no education were 2.2
times more likely to become infected than those who had completed primary
education. These analyses were restricted to those born after 1971 most of whom
would have become sexually active after the beginning of the information campaigns
(in 1986). For older Ugandans, the more educated were actually more likely than less
educated people to become infected during the period of the study, suggesting that
population behaviour change is driven by young people. On the basis of these figures,
the Global Campaign for Education argue that less educated young adults will
experience a disproportionately large number of new infections. They estimate that
the 36% of young adults in low-income countries without a complete primary
education will experience 55% of new infections – 1.3 million of the total of 5 million
new infections in the whole population every year. The estimates imply that achieving
Universal Primary Education could reduce the number of new infections in this group
by 700,000 a year (GCE, 2004).
The data from Uganda demonstrate the importance of schooling in an individual’s
response to a prevention campaign. It also demonstrates the evolving nature of the
relationship between HIV and education. In 1990 there was no relationship between
HIV prevalence and education. In 2000, having completed primary education was
associated with a 5.1% reduction in the risk of HIV infection and secondary education
was associated with an 8.8% reduction in risk. This relationship between HIV and
education was found for women but not men. Similarly, in Rakai, Uganda, HIV
infection was associated with increased levels of education in 1990 and 1992 but not
by 1994 (Kelly et al., 1999; Smith et al., 1999).
These finding supports the thesis that more educated individuals are better able to
mount a response to the HIV epidemic. However, the reversal of the epidemic in
Uganda is not typical of African countries. What evidence is there that education
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protects against HIV in the absence of a successful national prevention campaign? In
fact, data from a number of countries show a similar evolution in the relationship
between HIV and education. In the following studies, this evolution is evident in
comparisons between younger and older age groups at one time point, and in
comparisons between similar populations over time. In a population-based study in
Zimbabwe, men and women aged 17-19 were at a lower risk of HIV infection if they
had secondary education. The benefit of education was less for those aged 20-24 and
there was little or no protective benefit for those aged 25 and over (Simon Gregson
et al., 2001). In Fort Portal, HIV prevalence amongst women aged 15-49 attending an
antenatal clinic was highest for those with secondary education in 1991-1994 but by
1995-97 older illiterate women had the highest prevalence (Kilian et al., 1999).
Prevalence reduced to the greatest extent amongst women with secondary education
and among young women. Similarly, there was a positive association between
education and HIV infection amongst women attending an antenatal clinic in 1994 but
not by 1998 (Fylkesnes et al., 1997; Fylkesnes et al., 2001). Again, largest
reductions were seen amongst younger more educated women. Similar patterns were
seen in northern Malawi (Crampin et al., 2003) but there was no evidence of a
changing association between HIV and education in Blantyre, Malawi (Taha et al.,
1998) or in Kagera, Tanzania (Kwesigabo et al., 1998).
The data presented so far have been concerned with the static relationship between
HIV and education. An important policy question concerns the impact of increasing
levels of education on the epidemic. There is no experimental evidence addressing
this issue, but one study has estimated this relationship by analysing longitudinal data
from 20 regions in Tanzania over 8 years (Brent, 2005). This study estimated that an
increase of 1% in female primary school enrolment would be responsible for a 0.15%
reduction in HIV prevalence in this group, corresponding to 1,408 infections in the
period 1994-2001. A further analysis of these data suggest that the investment in
increased school enrolment is justified by the averted cases of HIV and the earning
potential of these individuals, with a cost-benefit ratio of between 1.3 and 2.9.
Urban-rural differences in the HIV-education relationship
8
Three studies have collected comparable data from urban and rural areas on the
relationship between HIV infection and education. The finding from all three is that
education is a greater risk factor for infection in rural areas compared to urban areas.
In Kagera, Tanzania (Kwesigabo et al., 1998), secondary educated individuals were
3.3 times more likely than those with no education to be infected with HIV in rural
areas. Conversely, in urban areas secondary education was associated with a reduction
in HIV risk. In Zambia in 1994 (Fylkesnes et al., 1997), having more than 10 years
of education was associated with an increased risk of being HIV infection, compared
to those with less than 4 years of education, in both rural and urban areas. However,
the increased risk was greater in rural areas (odds ratio of 4.2) than in urban areas
(odd ratio of 2.5). By 1999 figures from Zambia (Fylkesnes et al., 2001) showed that
education was now associated with a decrease in HIV prevalence in urban areas but
there was no relationship between education and infection in rural areas. A similar
pattern of results was found in Rakai, Uganda, in 1990 (Smith et al., 1999). Increased
education was associated with an increased risk of HIV in rural villages but there was
no relationship in roadside trading centres or in trading villages. Similarly, in
Mwanza, Tanzania, in 1991-2, HIV infection was positively associated with education
levels in rural villages and in roadside trading villages but not in urban centres.
All studies show a stronger relationship between HIV infection and education in rural
areas compared to urban areas. This should be considered with the finding that urban
residence is associated with a higher risk of HIV infection overall (Barongo et al.,
1992; Boerma et al., 1999; Fylkesnes et al., 1997; Serwadda et al., 1992). Taken
together these findings suggest that, at least in the early stages of the epidemic,
educated individuals were similarly at risk of infection in urban and rural areas. The
less educated were at a lower risk of HIV infection in urban areas and to a greater
extent in rural areas (Fylkesnes et al., 1997).
Sex differences in the HIV-education relationship
Data on sex differences are limited by the common use of infection rates in women
visiting ante-natal clinics as a proxy for population infection rates. Nevertheless, four
studies have looked at gender differences in the HIV-education relationship (Barongo
et al., 1992; Fylkesnes et al., 2001; Grosskurth et al., 1995; Smith et al., 1999). In all
four studies the increased risk of HIV infection associated with education was very
9
similar for men and women, suggesting there are no sex differences in the relationship
between HIV and education.
Sex differences in the HIV-education relationship are complicated by consideration of
the partner’s education. Evidence shows that a women’s risk of HIV infection is
increased with higher levels of education in their partner (Allen et al., 1991;
Dallabetta et al., 1993).
Considering evidence from education interventions, where sex differences are found
they consistently suggest that HIV-related knowledge is more strongly associated with
sexual behaviour in women, compared to men (Jukes, in preparation). Therefore,
although there is no evidence of sex differences in the HIV-education association at
present, we might expect more educated women to change their behaviour more
rapidly than men in response to the HIV epidemic.
Education and social capital
Studies in Uganda show how more educated people are more likely to change their
behaviour in response to an HIV prevention education campaign. One study in
Manicaland, Zimbabwe shows how more educated women are also able to benefit
more from other protective measures. This study looked at membership of social
groups related to, among others, churches or political parties. Women who were
members of a well-functioning social group were 1.3 times more likely to avoid HIV
infection than those who were not in such groups or who were in groups with which
they were dissatisfied. Education played a key role in the protective effect of the
social groups. Women with secondary education were more likely to belong to such
groups and among women with secondary education, those who were members of
well functioning groups were 1.5 times less likely to be infected with HIV, whereas
women with no education received no such benefits from group membership (S.
Gregson, Terceira, Mushati, Nyamukapa, & Campbell, 2004).
Explaining the relationship between HIV and education
In trying to understand the relationship between HIV and education two questions are
of interest. What is it about educated people that enables them to change their
behaviour in response to the epidemic? And, what aspects of behaviour change are
10
responsible for the reduction in HIV prevalence in this group? Few studies have
addressed these questions directly. In response to the first question, analyses from
Uganda (De Walque, 2002) and elsewhere (Vandemoortele & Delamonica, 2000)
suggest that parental and individual income are not explanatory factors. This supports
the view that the increased knowledge, understanding or self-efficacy that comes with
education is responsible for behaviour change.
One study in Zimbabwe addresses the question of which behaviours change amongst
educated individuals. The finding was that the secondary educated women acquired
HIV infection at a slower rate and have both a later sexual debut and less unprotected
casual sex (Simon Gregson et al., 2001). Subsequent analyses suggest that the
delayed age of sexual debut is primarily responsible for the relationship between
education and HIV infection (James Lewis, pers. comm.). This relationship may result
from the impact of sexual behaviour on girls’ education (through pregnant young
women dropping out of school) as well as the impact of education on sexual
behaviour.
Conclusion
Overall there is convincing evidence that education better equips individuals to
respond to the HIV epidemic. Although education is associated with higher HIV
prevalence in the early stages of an epidemic, in the later stages more educated
individuals have less risky sexual behaviour and are less likely to be HIV positive.
This is true in many settings but is particularly evident in Uganda, where a national
prevention campaign has successfully reduced HIV prevalence. There have been few
estimates of the likely impact of increasing primary school completion on the HIV
epidemic. One analysis based on the Uganda data suggests that universal primary
education could save 700,000 young adults from HIV infection. Another analysis
from Tanzania suggests that investments in expanded school enrolment for girls is
cost effective purely in terms of the effect this increased enrolment will have on the
HIV epidemic. Taken together, there is a strong case for making expanded primary
education and improved literacy a central part of the global response to the HIV/AIDS
epidemic.
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Section 3. Education and Antiretroviral Therapy
Treatment adherence is a critical issue in the promotion of antiretroviral therapy in
developing countries. Poor adherence is associated with reduced viral suppression
(Bangsberg et al., 2000; McNabb et al., 2001; Paterson et al., 2000), progression to
AIDS (Bangsberg et al., 2001), the development of multidrug resistance and death
(Hogg et al., 2002; Stephenson, 1999). Adherence is perceived as a significant barrier
to the delivery of ART in sub-Saharan Africa in particular (Harries, Nyangulu,
Hargreaves, Kaluwa, & Salaniponi, 2001). Poor education is often implied as a reason
why adherence is unlikely to be high in sub-Saharan Africa. A spokesman for USAID
is quoted as saying ‘Ask Africans to take their drugs at a certain time of day and they
do not know what you are talking about’ (cited in Orrell, Bangsberg, Badri, & Wood,
2003). Here we review the evidence that education and literacy are related to
treatment adherence.
Treatment adherence in Africa.
Initial studies of treatment adherence in Africa have allayed some fears of poor
adherence on the continent. A study in South Africa looked at adherence in a poor
HIV-positive cohort receiving ART through a public sector hospital (Orrell et al.,
2003). Adherence of the cohort was 93.5%. A composite measure of socioeconomic
status, including education and income, was not related to adherence. Those speaking
English at home were more than twice as likely to adhere to the treatment regimen.
Older patients and those required to take fewer doses were also more likely to adhere
to their regimen.
One study in Uganda looked at adherence in 304 HIV-infected individuals on a selffinanced regimen of antiretroviral therapy. The study population was relatively well
educated and wealthy. Monthly income was greater than $250 for 87.8% of the
sample and 63.2% had post-secondary education. Those with a monthly income of
less than $50 were 2.8 times more likely to miss 5% or more of doses. Seventy five
percent gave lack of money to buy drugs as a reason for lapses in adherence. Those
who were single (never married) were 2.9 times as likely to miss 5% or more of
doses. There was no significant relationship between adherence and post-secondary
12
education. An analysis by years of education was not reported (Byakika-Tusiime et
al., 2005).
A relationship between education and adherence was found in a study of 109 patients
attending private clinics in Botswana (Weiser et al., 2003). However, the relationship
was in the unexpected direction. Those who had not completed secondary education
were 3.9 times as likely to adhere to their treatment as those with higher education. In
this study, those who perceived cost or side effects as a barrier to treatment were less
likely to adhere to treatment; those who had disclosed their HIV status to others were
more likely to adhere to their treatment.
Treatment adherence in resource rich settings.
Studies in the West show that more educated individuals are more likely to adhere to
treatment with combination ART (Chesney, 2000; Chesney, Ickovics, Hecht, Sikipa,
& Rabkin, 1999). For example, in one study in America, high school completion was
associated with a 5.5% increase in adherence to a regimen of combined anti-retroviral
therapy (Golin et al., 2002). However, education does not emerge as a major
determinant of treatment adherence in the West. Alcohol and drug abuse are the key
patient characteristics affecting adherence. Other factors include depression, anxiety,
extreme pain, low self-efficacy and being young, male, or from an ethnic minority
(Chesney, 2000).
In a review of adherence to highly active antiretroviral therapy (HAART) similar
factors emerged as key determinants of adherence. In 14 studies that assessed the
relationship between education and adherence, 10 found no relationship and 4 found
higher levels of adherence amongst the more educated. This relationship disappeared
when controlling for other demographic factors in all 4 studies (Ammassari et al.,
2002).
Other studies show a relationship between adherence and knowledge, beliefs and
other cognitive factors of the patient that may be related to their level of education. A
patient's beliefs about their illness and the effectiveness of medication are predictive
of adherence. A patient's level of knowledge about HIV disease (Eldred, Wu,
Chaisson, & Moore, 1995; Eraker, Kirscht, & Becker, 1984; Morse, Simon, &
13
Walker, 1995) a belief that HAART is effective (Klosinski & Brooks, 1998;
Wenger, Gifford, Liu, Chesney, & Golin, 1999) and prolongs life (Stone et al.,
1998), and a recognition that poor adherence may equal viral resistance and treatment
failure (Wenger et al., 1999) all impact favourably upon a patients ability to adhere.
Conversely, a lack of interest in becoming knowledgeable about HIV (Kammann,
Williams, Chesney, & Currier, 1999) and a belief that HAART may in fact cause
harm, impede adherence (Brigido et al., 1998; Horne, Pearson, Leake, Fisher, &
Weinman, 1999; Johnston, Ahmad, Smith, & Rose, 1998).
Conclusion
There is insufficient evidence to make strong conclusions about the relationship
between education and ART treatment adherence in low-income countries. Of the
three studies conducted so far, only one was with relatively poor patients in a public
hospital. This found that those speaking English at home were more likely to adhere
to their treatment. It is possible this relationship was mediated through improved
education or literacy of those receiving treatment. The other two studies were
conducted with more wealthy individuals paying for their own treatment. These
studies found either no associated between adherence and education or found that
more education was associated with poorer adherence. However, these studies
compared those with or without complete secondary education and their findings may
not be relevant to questions of basic education and literacy. Findings from the West
suggest that there is a link between education and literacy. It seems that improving
education levels in developing countries is likely only to improve ART treatment
adherence and, perhaps more importantly, greater education levels may serve to allay
widespread fears amongst policy makers about the problems of adherence in Africa.
14
15
Adult HIV Prevalence %, 1999 (UNAIDS, 2000)
40
y = 0.2483x - 4.7922
2
R = 0.3509
30
20
10
0
0
Figure 1:
10
20
70
60
50
40
30
Adult Literacy %, 1998 (UNESCO, 2000)
80
90
100
HIV prevalence in adults aged 15-49 years by level of adult literacy for
40 countries in sub-Saharan Africa. (From Simon Gregson et al., 2001)
16
Figure 2. HIV prevalence by education category, Rural Uganda,
1990-2001. Individuals aged 18-29. (De Walque 2002).
17