1. Exploring the Cinderella myth: intrahousehold
differences in child wellbeing between orphans and
non-orphans in Amajuba District, South Africa
Anokhi Parikha, Mary Bachman DeSilvab, Mandisa Cakwea,
Tim Quinlana, Jonathon L. Simonb, Anne Skalickyb and
Tom Zhuwaua
Objective: To determine whether differences in wellbeing (defined by a variety of
education and health outcomes) exist between recent school-aged orphans and non-
orphans who live in the same household in a context of high HIV/AIDS mortality in
KwaZulu Natal, South Africa.
Design: The data come from the first 2 years (2004–2006) of an ongoing 3-year
longitudinal cohort study in a district in KwaZulu-Natal, the Amajuba Child Health
and Well-being Research Project. Using stratified cluster sampling based on school and
age, we constructed a cohort of 197 recent orphans and 528 non-orphans aged 9–16
years and their households and caregivers. Household heads, caregivers, and children
were interviewed regarding five domains of child wellbeing: demographic, economic,
educational, health/nutrition/lifestyle, and psychosocial status.
Methods: The analytical sample consists of 174 children (87 orphans and 87 com-
parable non-orphans who live together) at baseline and 124 children in round 2. We
estimated a linear regression model using household fixed effects for continuous
outcomes (grade adjusted for age, annual expenditure on schooling and body mass
index) and a logit model using household fixed effects for categorical variables
(malnutrition) to compare co-resident orphans and non-orphans.
Results: We found no statistically significant differences in most education, health and
labour outcomes between orphans and the non-orphans with whom they live. Paternal
orphans are more likely to be behind in school, and recent mobility has a positive effect
on schooling outcomes. ß 2007 Wolters Kluwer Health | Lippincott Williams & Wilkins
AIDS 2007, 21 (suppl 7):S95–S103
Keywords: caregivers, children, HIV, intrahousehold, mortality, orphans,
South Africa
Introduction currently 1.2 million AIDS orphans in South Africa [2],
and this number is expected to peak at a staggering 2.3
With an antenatal seroprevalence of 40.7% in 2005, million in 2015 [3]. As such, it is no surprise that the issue
KwaZulu-Natal has the highest HIV prevalence of any of orphaning has attracted significant attention.
province in South Africa, a country with 5.1 million
individuals infected [1,2]. AIDS-related mortality is high, Much of this attention has characterized orphans as
and the consequent impact on orphaning is likely to children who are growing up without the care and
be dramatic in the years to come, irrespective of the support of their families, who have poorer learning and
expansion of the antiretroviral programme. There are knowledge levels, and who are suffering from the
From the aHealth Economics and AIDS Research Division (HEARD), University of KwaZulu Natal, Durban, South Africa, and the
b
Boston University School of Public Health, Center for International Health and Development, Boston, Massachusetts, USA.
Correspondence to Anokhi Parikh, HEARD, Private Bag X 54001, Durban, 4000, South Africa.
E-mail: anokhip@gmail.com
ISSN 0269-9370 Q 2007 Wolters Kluwer Health | Lippincott Williams & Wilkins S95
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

2. S96 AIDS 2007, Vol 21 (suppl 7)
‘absence of adults in their socialization’ [4]. The data national 2003 General Household Survey, approximately
reveal that most orphans, defined in the AIDS literature as two-thirds of all orphans in KwaZulu-Natal live in such
having one or more parents dead, in sub-Saharan Africa households. These households are of particular interest
have at least one parent living and either live with their also because the co-resident non-orphans make a natural
surviving parent or are absorbed into other families where comparison group for orphans as they both share
they have some adult supervision. household characteristics (e.g. household income, literacy
of caregiver etc.).
Nevertheless, the death of a parent (and the potentially
long illness preceding it if the parent has died of AIDS) In one of the few studies to make intrahousehold
may have various impacts on a child’s wellbeing. comparisons, Case and Ardington [15] showed that in
Numerous studies have accordingly examined the impact Hlabisa district in KwaZulu-Natal, maternal orphans
of orphaning on children, but have focused primarily on were more likely to be behind in school and had less spent
educational outcomes (commonly defined by school on their schooling, but were equally likely to be enrolled
enrolment), with few studies looking at any other aspect as the non-orphans with whom they lived. Implicit in the
of wellbeing such as health or labour outcomes. finding that orphans are worse off when compared with
other children is the notion that caregivers may prioritize
Although the empirical evidence is mixed and depends their own children over the fostered child, a Cinderella
on the location, data sources, and methods used, two approach, so to speak. For example, when facing income
broad themes emerge in the literature: that the impact of constraints, a caregiver might spend less on the fostered
orphaning depends often on which parent dies and that child than on his/her own child (although perhaps with
income is often a greater predictor of outcomes than less malice than Cinderella’s stepmother). Gender bias in
orphan status. Case et al. [5] used the Demographic and educational expenditures has been well documented in
Health Survey data from 19 countries in Africa and found Asia; a similar bias could also apply to orphans, but very
systematic differences in school attendance between little research has examined the intrahousehold aspect of
orphans and non-orphans. The finding of difference in this question to date.
attendance and enrolment between orphans and non-
orphans has been supported by other studies in rural In summary, the research to date is limited in two ways.
Kenya through longitudinal studies [6,7], and in cross- First, few studies explicitly assess intrahousehold differ-
sectional studies elsewhere in sub-Saharan Africa [8]. ences between orphans and non-orphans. Second, both
Beegle et al. [9], using a panel that follows children for intra and interhousehold comparisons have used limited
13 years, showed that maternal orphanhood was indicators such as school enrolment, grade progression,
associated with lower educational attainment and health and height, and thus do not provide a comprehensive
(as measured by height) in the long term, and paternal picture of other important aspects of child wellbeing.
orphanhood was associated with lower educational
attainment for certain groups only. Using Demographic To respond to these shortcomings, this paper compares
and Health Survey data and other nationally representa- the differences in wellbeing between orphans and non-
tive household surveys from 51 countries in Africa, orphans who live with each other using longitudinal data
Ainsworth and Filmer [10] highlighted the variation in from 2004–2006 from Amajuba District in KwaZulu-
orphan/non-orphan differentials across countries and Natal. This paper addresses the question ‘do orphans and
found that income plays a greater role in determining non-orphans living within the same household fare
school enrolment than orphaning. differently in terms of wellbeing?’ We define ‘wellbeing’
to include education, health, and labour outcomes. We
A lack of statistically significant differences in enrolment conclude with potential explanations for the observed
have been found by other researchers conducting results and trends.
longitudinal studies in East Africa [11–13]. Chatterji
et al. [12], using longitudinal data from Rwanda, showed
no differences in school enrolment and food intake
between orphans and non-orphans. Adato et al. [14] Methods
found no statistically significant differences in schooling
indicators but qualitatively did find some cases of Study area
discrimination towards orphans within the household. The Amajuba district was chosen because it included a
broad cross-section of urban, peri-urban and rural areas.
Many of these studies consider orphans and non-orphans The district has approximately 470 000 inhabitants and is
in general, but do not distinguish between orphans who poor. The economy used to be driven by the coal mining
live with other orphans and orphans who live with non- industry, but the closure of coal mines has led to high
orphans in mixed households (with some exceptions) unemployment in the region and consequently high rates
[6,7,15]. Moreover, they are an important type of of migration. Additional details are provided elsewhere
household, as according to the Statistics South Africa’s (Bachman DeSilva et al., manuscript in preparation).
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

3. Wellbeing of co-resident orphans and non-orphans Parikh et al. S97
Data and sample selection a result of a change of caregiver, return to living with
The data come from the first 2 years of an ongoing 3-year parents, or move for family reasons. The movement of
cohort study that commenced in 2004. The study was one child led to the exclusion of the comparison child
designed, and the data collected by the Amajuba Child from the analysis.
Health and Well-being Research Project, a joint initiative
between the Health Economics and HIV/AIDS Analytical methods
Research Division (HEARD) at the University of This paper examines the education, health and labour
KwaZulu-Natal and the Center for International Health outcomes of orphans compared with the non-orphans
and Development at the Boston University School of with whom they live. For education, we assessed two
Public Health. The Institutional Review Board of Boston indicators: grade normalized for age, and annual
University Medical Center and the Ethics Committee of expenditures on schooling for the child. For physical
the University of KwaZulu-Natal provided ethical health, we examined body mass index (BMI), which was
approval for the study. calculated then translated into z-scores and percentiles
using the United States Centers for Disease Control and
The annual survey has four components: a household and Prevention age and sex-specific reference curves. As
demographic information questionnaire administered to malnutrition often manifests itself as obesity, analysing
the household; a questionnaire for the primary caregiver BMI as a continuous variable can be misleading. We
of the study child; and two questionnaires administered therefore looked at malnourishment as a categorical
to the study child, one on general wellbeing including variable in which malnourishment was defined, in
self-reported health, educational attainment, and the use accordance with Centers for Disease Control and
of time, and a second that assesses the self-reported Prevention definitions, as being in the bottom 5
psychosocial wellbeing of children. percentile or the top 5 percentile of the age and sex-
specific BMI distribution. For labour outcomes we
Sample selection took place using randomized stratified examined the categorical variables: whether the child had
cluster sampling from 60 of 252 schools in the district. worked outside the house in the last week and whether
The study population were predominantly Zulu-speak- the child had done chores within the house in the
ing children aged 9–16 years, resident in the district and last week.
attending school at the time of sampling. Only ‘recent
orphans’, defined as children who had lost one or both Bivariate relationships between child type and demo-
parents to any cause during a 6-month period between graphic variables were assessed using Mantel–Haenszel
March and August 2004 were included. This was done in chi-square tests for categorical variables and t-tests for
order to capture the incidence of orphaning and measure continuous outcomes. For the multivariate analysis, we
the exposure period of parent death. Three comparison estimated a linear regression model using household fixed
non-orphan children were randomly selected from the effects. The household fixed effect allows for the
same school, grade, and age as index-orphan children. In comparison of children (with different characteristics)
households in which there were both orphan and non- within households by controlling for all observed and
orphan children, a secondary comparison child was unobserved child invariant household characteristics such
selected in the same age range as that household’s primary as income, assets, household size, distance to school, etc.
study child. A cohort of secondary comparison children As co-resident orphans and non-orphans will have the
was thus also constructed in order to investigate same household characteristics, this method allows us to
intrahousehold differences in children’s wellbeing. identify the within-household differences between
orphans and non-orphans.
Study households were classified into three groups:
orphan-only, non-orphan-only, and mixed households. For continuous variables, we estimated the following
The overall baseline sample includes 50 orphans from the linear model:
50 orphan-only households, 377 non-orphans from 377
non-orphan-only households, and 298 children from the Yijt ¼ b1 maleij þ b2 ageijt þ b3 mobilityijt
210 mixed households (a total of 725 children). Of the
210 mixed households, 87 had non-orphans of com- þ b4 orphan typeijt þ b5 resident parentijt
parable age. The analytical sample used for the current þ Hj þ eijt
analysis thus consists of 174 children at baseline, 87
orphans and 87 non-orphans who live together in mixed
households; and 124 children, 62 orphans and 62 non- where Yijt represents the educational attainment/BMI for
orphans, in the second round. Of the 25 pairs that child i from household j at time t; male is an indicator
dropped out in round 2, six dropped out as the variable for whether child is male or not; age is the age of
comparison non-orphans were orphaned (therefore the the child; mobility is an array of categorical variables
household no longer remained mixed); the remaining 19 reflecting when the child moved into the house; orphan
pairs had at least one child moved to another household as type is the type of orphan (maternal orphan, paternal
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

4. S98 AIDS 2007, Vol 21 (suppl 7)
orphan, double orphan); resident parent is whether the mately half the sample had repeated a grade once. Average
surviving parent of the orphan or the parent of the non- body mass was within normal range and was comparable
orphan is living at home (father lives at home, mother for orphans and non-orphans. Approximately 10% of the
lives at home). Hj is the child invariant household fixed children work outside the house and 91% report assisting
effect; and eijt is the error term. Several models were with chores in the household (with no differences
estimated using the different independent variables in between orphans and non-orphans). Although mobility
different combinations, but results from only one such of the sample was high, it was equally high for orphans
model are presented in this paper. and non-orphans, with approximately 30% of the sample
having moved at least once and approximately 12% in the
For categorical variables, we estimated a logit model: past 2 years. Living arrangements were different, however,
with a parent being the primary caregiver for only 39% of
PðYijt ¼ 1Þ the non-orphans and 12% of the orphans. Grandparents
¼ Fðb1 maleij þ b2 ageijt þ b3 mobilityijt were primary caregivers for 56% of the orphans and
43% of non-orphans, although this difference was not
þ b4 orphan typeijt þ b5 resident parentijt statistically significant. These findings of non-difference
remained unchanged in round 2 (results not shown).
þ Hj þ eijt Þ Table 2 shows the demographic characteristics of the
where Yij represents whether child i from household j at time sample that was lost in round 2. None of the
t is malnourished or not/works at home or not/does chores characteristics listed were significant predictors of
at home or not; and the remaining variables are as defined attrition (results not shown).
above.
Of the orphans at baseline, 13 were maternal-only
The decision to include the variables on mobility and orphans, 30 were paternal-only orphans, 26 were double
resident parent was informed by the literature. This orphans, and 19 had missing information on which parent
literature shows that fostering and mobility are high even had died. This changed to nine maternal-only orphans,
for all kinds of children in South Africa because of high 21 paternal-only orphans, 21 double orphans, and 12
levels of adult migration and children born out of with missing data in the following year. Table 3
wedlock [14,16,17]. We thus feel it is important not only summarizes the demographic and socioeconomic charac-
to introduce these variables as controls. teristics of children by orphan type.
Examining children who are co-resident using household As mentioned in the methodology section, several
fixed effects allows us to control for common household models, each controlling for a different combination of
characteristics. It is impossible to know, however, with independent variables, were estimated to examine the
these data, whether the children being compared were orphan/non-orphan differentials across different out-
indeed comparable before the death of the parent because comes. Table 4 shows results from two such models. The
we do not have information on the orphan’s character- results were consistent across specifications: paternal
istics before being orphaned (which may have themselves orphans are more likely to be behind in school than non-
been affected by orphaning). We are also unable to orphans with whom they live, they are on average a third
consider the fixed and unobserved characteristics of the of a year behind in their grade. Maternal orphans are on
child him/herself, even though this is longitudinal data, as average half a year behind in schooling, but this effect is
most of the variables of interest have remained constant statistically insignificant. Mobility within the past 2 years
over time. As a result of this limitation of the data, this is seen to have a positive effect on grade progression.
paper does not try and isolate the impact of parental death Orphanhood does not seem to have any effect on
on children. Rather, it compares orphans and non- expenditures on schooling. Recent mobility is associated
orphans on a range of indicators and tries to identify some with a substantial negative effect on schooling expendi-
causal pathways for the results. ture. The impact of parents being present at home is
insignificant (results not shown).
Bivariate analysis demonstrates no significant differences
Results in nutrition, health proxy, and labour outcome indicators
such as going to bed hungry the previous night, being sick
At baseline, bivariate analysis of sociodemographic in the past 6 months, and working both within and
characteristics shows few differences between the 87 outside the house (see Table 1). Analysis of BMI,
orphans and 87 non-orphans in the analytical sample presented in Table 4, shows that BMI is lower for orphans.
(Table 1). There are no statistically significant differences This is also robust when controlling for mobility. As
between the demographic, educational, health, or labour malnutrition also manifests itself as obesity, however,
outcomes between orphans and co-resident non- lower BMI is not necessarily informative, especially in
orphans. Whereas attendance was near 100%, approxi- adolescents. Logistic analysis (Table 5) shows that
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

5. Wellbeing of co-resident orphans and non-orphans Parikh et al. S99
Table 1. Demographic characteristics of orphans and non-orphans at baseline (2004–2005).
Non-orphans (N ¼ 87) Orphans (N ¼ 87)
Characteristic % (N) Mean (SD) % (N) Mean (SD)
Sex (male) 55.2 (48) 55.2 (48)
Age (years) 12.3 (1.9) 12.2 (1.8)
Education
% of children attending school 98.8 (86) 100 (87)
Mean current grade 6.3 (2.0) 6.0 (2.0)
% of children who have repeated a grade at least once 53.5 (47) 51.7 (45)
Mean number of times grade has been repeated 1.1 (1.1) 1.3 (1.3)
Expenditures on schooling (SA Rand, per year) 392.7 (307.8) 357.5 (206.5)
Health
Mean body mass index 18.7 (3.6) 18.0 (3.1)
% of children who were sick in the past 6 months 28.7 (25) 32.2 (28)
% of children who ate breakfast this morning 86.2 (75) 81.6 (71)
Labour
% of children who worked outside the house last week 9.2 (8) 10.3 (9)
Mean number of hours worked last week 1.9 (0.6) 1.4 (0.5)
% of children who did chores in the house last week 93.1 (81) 89.5 (78)
Mean number of hours of chores last week 1.6 (0.5) 1.6 (0.5)
Mobility
% of children who have never changed residence 71.3 (62) 70.1 (61)
% of children who changed residence in the past 2 years 11.5 (10) 14.9 (13)
% of children who changed residence 2–5 years ago 6.9 (6) 4.6 (4)
% of children who changed residence over 5 years ago 10.3 (9) 10.3 (9)
Living arrangements
% of children whose primary caregiver is their parenta 39.0 (34) 12.6 (11)
% of children whose primary caregiver is their grandparent 43.7 (38) 56.3 (49)
% of children whose mother lives at homeb 67.5 (59) 50 (44)
% of children whose father lives at home 30.4 (26) 27.8 (24)
SA, South African.
a
Significant at 1%.
b
Significant at 5%.
Table 2. Characteristics of the 25 children lost to attrition in round 2.
Characteristics % (N) Mean (SD)
Sex (male) 62.5 (15)
Age (years) 12.9 (1.7)
Orphan status
Non-orphan 40 (10)
Maternal-only orphan 4 (1)
Paternal-only orphan 20 (5)
Double orphan 16 (4)
Orphans with missing parent death data 16 (4)
Education
% of children attending school 95.8 (23)
Mean current grade 6.7 (2.0)
% of children who have repeated a grade at least once 62.5 (15)
Mean number of times grade has been repeated 1.2 (0.4)
Expenditures on schooling (SA Rand, per year) 339.5 (174.0)
Health
Mean body mass index 18.4 (2.5)
Mobility and living arrangements
% of children who have never changed residence 58.3 (14)
% of children who changed residence in the past 2 years 25 (6)
% of children who changed residence 2–5 years ago 8.33 (2)
% of children who changed residence over 5 years ago 8.33 (2)
% of children whose primary caregiver is their parent 20.8 (5)
% of children whose primary caregiver is their grandparent 54.2 (13)
% of children whose mother lives at home 53.3 (13)
% of children whose father lives at home 27.3 (7)
SA, South African.
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6. S100
AIDS
Table 3. Demographic characteristics of maternal, paternal and double orphans at baseline (2004–2005).
2007, Vol 21 (suppl 7)
Maternal-only orphans (N ¼ 13) Paternal-only orphans (N ¼ 36) Double orphans (N ¼ 26)
% (N) Mean (SD) % (N) Mean (SD) % (N) Mean (SD)
Sex (male) 53.9 (7) 70 (25) 42.3 (11)
Age (years) 12.7 (2.0) 12.2 (1.7) 12.2 (1.9)
Education
% of children attending school 100 (13) 100 (36) 100 (26)
Mean current grade 5.7 (2.1) 6.2 (1.8) 6.1 (2.3)
% of children who have repeated a grade at least once 41.7 (5) 51.8 (19) 33.3 (9)
Expenditures on schooling (SA Rand, per year) 336.3 (127.8) 363.4 (158.7) 344.3 (309.2)
Health
Mean body mass index 19.3 (4.9) 17.7 (2.2) 17.8 (3.4)
% of children who were sick in the past 6 months 38.5 (5) 23.3 (8) 38.5 (10)
% of children who ate breakfast this morning 84.6 (11) 90 (32) 76.9 (20)
Labour
% of children who worked outside the house last week 7.7 (1) 3.3 (1) 7.7 (2)
% of children who did chores in the house last week 100 (13) 86.2 (31) 76.9 (20)
Mean number of hours of chores last week 1.5 (0.5) 1.6 (0.6) 1.6 (0.5)
Mobility and living arrangements
% of children who have never changed residence 61.5 (8) 86.7 (31) 69.2 (1.8)
% of children who changed residence in the past 2 years 7.7 (1) 5.5 (2) 26.9 (7)
% of children who changed residence over 2 years ago 23.1 (3) 5.5 (2) 3.8 (1)
% of children whose primary caregiver is their parent 0 (0) 1.7 (6)
% of children whose primary caregiver is their grandparent 69.2 (9) 43.3 (16) 65.4 (17)
% of children whose mother lives at home 50 (18)
% of children whose father lives at home 23.0 (3)
SA, South African.
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

7. Wellbeing of co-resident orphans and non-orphans Parikh et al. S101
Table 4. Educational and health outcomes for orphans and co-resident non-orphans (household fixed effects).
Grade normalized Grade normalized Annual expenditure Annual expenditure Body mass
for age for age on school on school index
Age (in years) À0.06b À0.07b À2.18 À1.59 0.77b
(0.01) (0.01) (38.25) (37.40) (0.10)
Sex (male) À0.02b À0.02b 23.19b 25.75b À3.11b
(0.00) (0.00) (8.74) (8.46) (0.45)
Changed residence in past 2 years 0.05b À170.11b
(0.02) (55.93)
Changed residence more than 2 years ago À0.03 106.43a
(0.02) (48.28)
Maternal-only orphan À0.04 À0.03 À11.14 À54.29 1.5a
(0.02) (0.02) (60.97) (60.74) (0.73)
Paternal-only orphan À0.04a À0.04b À5.15 6.53 À1.12a
(0.01) (0.01) (40.88) (40.25) (0.48)
Double orphan 0 À0.01 À61.42 À27.76 À1.71b
(0.01) (0.01) (42.74) (42.27) (0.50)
Constant 1.24b 1.25b 120.89 84.97 11.29b
(0.04) (0.04) (113.95) (110.35) (1.32)
Observations 296 296 298 298 298
Number of field code 87 87 87 87 87
R-squared 0.28 0.32 0.04 0.12 0.42
a
Significant at 5%.
b
Significant at 1%.
Standard errors in brackets.
Variable with missing orphan type included but not shown.
maternal and double orphans are at greater odds of being coefficient on the father being a resident within the
malnourished than non-orphans but this is not statistically household is insignificant (results not shown), suggesting
significant. Maternal and paternal orphans are at greater that the impact of paternal orphanhood may be caused by
odds of doing chores within the house and at lower the fact that the death of a father could be an economic
odds of working outside the house compared with co- shock that may have, at some point, resulted in children
resident non-orphans, but again these differences are not dropping out of school. We, unfortunately, have no way
statistically significant. to test this hypothesis and can only offer it as a
potential explanation.
What could explain the lack of overall differences
Discussion between orphans and non-orphans? First, temporal issues
may be driving the result. It is important to remember
The results show some statistical differences in edu- that we are merely looking at incident (recent) orphans,
cational outcomes and no differences for health and i.e. children that have lost at least one of their parents in
labour outcomes between orphans and non-orphans who the 6 months before the survey and in the same year the
live in the same households. survey was conducted. This may not be sufficient time to
see a large effect on children, or the households may have
Case and Ardington [15], in their intrahousehold analysis effective short-term coping mechanisms to mitigate the
also set in KwaZulu Natal (albeit in a poorer district), effect on children [9]. On the other hand, one can argue
found that maternal orphans are ‘on average, 0.12 of a that the critical period for an orphan child is the terminal
year behind in their schooling and have 7% less spent on illness period as a result of the trauma of seeing a parent
their education’ compared with the non-orphans with wasting away and sometimes having to miss school in
whom they live. Although the differences in expenditure order to attend to sick parent(s), and that the impacts may
are moderate, the magnitude of the difference between diminish over time.
orphans and non-orphans in terms of schooling is small:
0.12 of a year behind equates to orphans being behind by Second, Case and Ardington [15] have argued that
a little over a month. They found no difference for differences in outcomes between orphans and non-
paternal orphans. Our results, on the other hand, show orphans are driven by the tendency to live with distant or
that paternal orphans are behind in school. unrelated caregivers. All the orphans in the sample are
either living with close relatives (aunt or grandmother) or
Given the fact that a large proportion of South African their surviving parent, as in a study from the same
fathers are absent or not linked to the household [16], the province by Adato et al. [14]. Therefore, they are likely to
significant effect of paternal orphanhood is curious. The receive the same support as the non-orphans with whom
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8. S102 AIDS 2007, Vol 21 (suppl 7)
Table 5. Health and labour outcomes for orphans and co-resident non-orphans (logistic model with household fixed effects).
Child is malnourished Child works outside the house Child does household chores
Odds ratio 95% CI Odds ratio 95% CI Odds ratio 95% CI
Age (in years) À0.29 (À0.81–0.23) 0.01 (À0.31–0.32) À0.14 (À0.46–0.18)
Sex (male) 0.01 (À1.50–1.52) 0.11 (À1.37–1.59) À1.54 (À3.33–0.24)
Maternal-only orphan 0.48 (À1.88–2.83) À0.24 (À2.28–1.81) 0.69 (À1.77–3.15)
Paternal-only orphan À0.18 (À2.29–1.92) À0.03 (À1.41–1.35) 0.25 (À1.22–1.72)
Double orphan 0.56 (À1.13–2.24) À0.72 (À2.41–0.96) À0.95 (À2.61–0.72)
Observationsa 54 86 96
Number of groups 16 24 26
CI, Confidence interval. aMultiple positive/negative outcomes were encountered within groups and thus the groups were dropped from
the regression resulting in fewer numbers of observations. Standard errors in brackets. Variable with missing orphan type included but not
shown.
they live. With time, destination households may become moved houses in the preceding year, 13 orphans and 10
oversaturated and could struggle to absorb more children non-orphans. Moreover, in round 2, sample attrition was
and this may change. South Africa’s extensive social grants equally high for orphans and non-orphans. Therefore,
system potentially mitigates against this phenomenon and although there may be endogeneity in placement
assist families in coping. decisions, we do not believe it is disproportionately so
for orphans when compared with non-orphans. Child
Third, in Amajuba District’s context of high adult migration is a historical/cultural phenomenon, and
migration, having a parent alive does not equate to the fostering literature shows how children have lived away
presence of a parent at home, thus orphanhood itself may from their ‘nuclear’ families (although this may be
not be associated with lower educational or health exacerbated by AIDS mortality) [17].
outcomes. The majority of both orphans and non-
orphans live without parents present at home. Table 1 Fifth, it is possible that the indicators used may not be
indicates that only 38.64% of non-orphans have parents as sensitive to differences, particularly because the orphans
primary caregivers, and a large proportion of both were so recently orphaned. There may be some
orphans and non-orphans live with their grandparents. limitations of BMI, but in general it is difficult to
Even single parent orphans tend not to live with their identify good measures of health of older/school-aged
surviving parent. Migration for employment was the most children because this age group is generally very healthy
frequently cited reason for parents’ not living at home. (self-reported or otherwise). In terms of schooling, there
Furthermore, approximately a third of the fathers were maybe differences in performance within a grade that are
not living at home because they were not married to the not captured by these instruments. Whether an orphan
mother. This figure also calls into question the role of child is truly learning, as opposed to progressing, like
biological parents (especially fathers) in caregiving, and non-orphaned children, may not be fully captured by
supports other literature that shows that the absence of the data.
fathers is high in South Africa, with 55% of fathers being
absent in rural South Africa in 2002 [16]. Current The study has some limitations worth mentioning that
definitions of orphan inaccurately privilege the biological may bias the results towards the null. First, the tests have
parent in a context in which even non-orphans do not low power as a result of the relatively small sample size,
live with their parents. This calls into question our and this may contribute to not finding statistically
thinking on the category of orphan in South Africa. significant effects. The attrition in round 2 only further
reduced the sample. Comparisons with much larger
Fourth, when orphans have moved from their original studies should be made with this in mind.
households (i.e. they were fostered into the survey
household, which has non-orphans), there may be Second, the study sample was drawn from a random
endogeneity in placement decisions, in that orphans sample of schools in the district. Using schools as our sole
are strategically moved to better-off households and this recruitment source for study participants was both
may bias the results towards the null. The positive and methodological and practical. Drawing a sample of
significant coefficient on recent mobility (within the past school-going ‘recent’ orphans and non-orphans intro-
2 years) supports the idea that children are often moved duces a sampling bias that potentially biases the
for schooling. It is important to note, however, that intrahousehold results towards the null as worse-off
mobility is equally high for both orphans and non- orphans may have been excluded from the sample. What
orphans. Table 1 shows how there is no statistically is important to note is that school enrolment rates in
significant difference between orphans’ and non-orphans’ KwaZulu-Natal are extremely high. The national 2003
mobility. Of the 174 children at baseline, 23 children General Household Survey conducted by Statistics South
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

9. Wellbeing of co-resident orphans and non-orphans Parikh et al. S103
Africa showed school enrolment rates to be 97.5% for United States National Institutes of Health under its
non-orphans and 95% for orphans. Upon further analysis African Partnerships programme (grant R29
of this survey, we found orphans who are not enrolled HD43629).
neither worse off than the non-orphans with whom they
Conflicts of interest: None.
live nor are they are worse off compared with enrolled
orphans in terms of health and labour outcomes. Their
schooling outcomes do differ, however, and this may bias References
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