Available via license: CC BY 4.0
Content may be subject to copyright.
International Journal of
Environmental Research
and Public Health
Article
The Economic Burden of Violence against Children in
South Africa
Xiangming Fang 1, 2,*, Xiaodong Zheng 1, Deborah A. Fry 3, Gary Ganz 4, Tabitha Casey 3,
Celia Hsiao 5and Catherine L. Ward 4ID
1College of Economics and Management, China Agricultural University, No. 17 Qinghuadong Road,
Haidian District, Beijing 100083, China; zhengxd@cau.edu.cn
2School of Public Health, Georgia State University, 140 Decatur Street, Atlanta, GA 30303, USA
3Moray House School of Education, St John’s Land, 2.02, Holyrood Road, Edinburgh EH8 8AQ, Scotland;
Debi.Fry@ed.ac.uk (D.A.F.); Tabitha.Casey@ed.ac.uk (T.C.)
4Department of Psychology and Safety and Violence Initiative, University of Cape Town,
Rondebosch 7701, South Africa; garyganz@gmail.com (G.G.); Catherine.Ward@uct.ac.za (C.L.W.)
5Save the Children South Africa, 2nd Floor SAQA House, 1067 Arcadia Street, Hatfield 0028, South Africa;
CHsiao@savethechildren.org.za
*Correspondence: xmfang@cau.edu.cn; Tel.: +86-10-6273-8705
Received: 6 September 2017; Accepted: 19 November 2017; Published: 22 November 2017
Abstract:
The purpose of this study was to estimate the economic burden of violence against children
in South Africa. We assembled summative estimates of lifetime prevalence, calculated the magnitude
of associations with negative outcomes, and thereby estimated the economic burden of violence
against children. According to our calculations, 2.3 million and 84,287 disability-adjusted life-years
(DALYs) lost in South Africa in 2015 were attributable to nonfatal and fatal violence against children,
respectively. The estimated economic value of DALYs lost to violence against children (including both
fatal and nonfatal) in South Africa in 2015 totalled ZAR173 billion (US $13.5 billion)—or 4.3% of
South Africa’s gross domestic product (GDP) in 2015. In addition, the reduced earnings attributable
to childhood physical violence and emotional violence in South Africa in 2015 were ZAR25.2 billion
(US $2.0 billion) and ZAR9.6 billion (US $750 million), respectively. In addition, South Africa spent
ZAR1.6 billion (US $124 million) on child care and protection in fiscal year 2015/2016, many of
which costs are directly related to violence against children. This study confirms the importance of
prioritising violence against children as a key social and economic concern for South Africa’s future.
Keywords:
economic burden; violence against child; South Africa; disability-adjusted life-year (DALY)
1. Introduction
Violence against children exists in every country in the world, cutting across culture,
class, education, income and ethnic origin. Sadly, South Africa is no exception. Childhood violence
can have lifelong adverse health, social and economic consequences for survivors and the society.
Given the high prevalence of violence against children and the many negative short- and long-term
consequences, the economic costs of violence against children may be substantial. Given such costs,
violence against children is not only a human rights and moral issue, but also an economic one.
Previous burden of violence against children studies have found significant impacts on children’s
and adults’ mental and physical health, employment and education, as well as increasing risk factors
for experiencing other forms of violence [
1
]. A burden study in the East Asia and Pacific region
found that violence against children costs the region 2% of their GDP [
2
]. Estimates of the economic
burden have also been published for a few countries individually such as the United States [
3
],
Australia [
4
], and China [
5
], but are lacking in most countries and regions of the world, including
Int. J. Environ. Res. Public Health 2017,14, 1431; doi:10.3390/ijerph14111431 www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2017,14, 1431 2 of 14
Africa. In the US, for instance, it was estimated that the average lifetime cost per victim of nonfatal
violence against children was US $210,012 in 2010; whereas the estimated average lifetime cost per
death was US $1,272,900. Together, the total lifetime economic burden resulting from new cases of
fatal and nonfatal violence against children in the US in 2008 alone was estimated to be approximately
US $124 billion [3].
No similar data exists for the economic burden of violence against children in Africa, making this
the first study to explore this burden on the continent. While studies of the prevalence and incidence
of violence against children provide authorities with information relevant to service planning—for
instance, how many staff members would be needed to deal with new reports of child maltreatment in
a year—this is often not a sufficient rationale for policymakers to develop services in contexts (like low-
and middle-income countries, such as South Africa) where there are competing urgent priorities for
the scarce resources within national budgets. Information on how much violence against children costs
the economy can provide that rationale, if costs of the violence outweigh the costs of prevention and
intervention services.
The purpose of this study, therefore, was to estimate the economic burden of violence against
children in South Africa. Through assembling summative estimates of lifetime prevalence and
calculating the strength of associations with negative outcomes, we estimated the economic burden
of violence against children. The data generated in this study is intended to advance the awareness
of policymakers of the economic impact of violence against children and therefore support budget
allocations and investments in this regard.
2. Materials and Methods
Three steps were used in the estimation of the economic burden of violence against children in
South Africa.
2.1. Step One—Systematic Review of Prevalence and Consequences
A systematic review was conducted to identify studies reporting on the prevalence and
consequences of violence against children in South Africa using the Africa-Wide Information,
MEDLINE, PsycINFO, CINAHL, ERIC, SocINDEX and Embase databases. Peer-reviewed and
non-peer-reviewed journal articles, research reports and other ‘grey’ literature reporting prevalence
and/or consequences of violence with a geographic focus in South Africa, that were published between
January 2000 and December 2015, were included. Key child protection researchers and organisations
in South Africa were also contacted to identify additional studies. The reference lists of key narrative
reviews on violence against children in South Africa and the region were also scanned for additional
studies, and a manual search of eight international and national journals was also conducted. The eight
journals include Child Abuse and Neglect,Child Maltreatment,Child Abuse Review,Journal of Interpersonal
Violence,South African Medical Journal,South African Journal of Psychology,African Journal of Psychiatry,
and Journal of Child and Adolescent Mental Health.
Studies were included if they reported the prevalence/incidence of sexual, physical or emotional
violence against children, neglect, witnessing family violence, community violence, bullying,
gang violence and other forms of violence affecting children in South Africa. For prevalence/incidence
studies additional inclusion criteria were: (i) Participants were recruited from a student or general
population; (ii) quantitative methods were used to estimate the prevalence/incidence of the violence
during childhood (e.g., younger than 18 years); (iii) the study reported the prevalence or incidence of
violence against children; and (iv) the recorded violence had been reported directly by the victims or
by parents. For the review of outcomes studies, additional inclusion criteria were: (i) primary research
that explored the relationship between at least one form of violence against children and its impact
on employment, education, mental health, physical health, health behaviours, aggression, violence,
criminality, exposure to further violence, formal and informal care and service use; (ii) included the
calculation of odds ratios (ORs) or relative risks (RRs) or marginal effects (MEs) disaggregated by the
Int. J. Environ. Res. Public Health 2017,14, 1431 3 of 14
type of violence; and (iii) did not sample on the basis of the presence of any specified outcome—since
this would invalidate the calculation of an OR or RR or MR for that outcome. The review utilised both
free text and controlled vocabulary of subject heading and keyword searches to identify articles and
grey literature via the electronic databases. To provide the broadest coverage of articles, the initial
search term consisted of: (1) population (e.g., children); (2) type of maltreatment (e.g., physical abuse);
and (3) South Africa. Five search strings were utilised in total. To ensure accuracy, the searches were
conducted by two researchers and results compared; papers were retained if there was consensus
between the two reviewers about inclusion, and any remaining questions were resolved by consultation
with the rest of the team if necessary. Relevant data from included articles was then extracted into an
Excel spreadsheet. The full details of the search strategy, search terms used, inclusion criteria, excluded
articles, a full description of all violence against children studies, and data extraction can be found
elsewhere [6].
Given that there were too few studies to yield reliable estimates on the consequences of witnessing
parental violence and exploitation, these forms of violence against children were not included in this
study. This study only focuses on four major types of violence against children: physical violence,
sexual violence, emotional violence, and neglect. We also did not distinguish violence perpetrated by
children from that perpetrated by adults: our definition of violence against children was based solely
on whether the victim was a child, in accord with the Optimus Study South Africa [
7
]. The systematic
review identified a total of 65 studies. For consequences, a total of 24 studies met the inclusion criteria:
10 measured the relationship between violence against children and interpersonal violence, 4 measured
anxiety, 3 measured self-harm, 3 measured alcohol abuse, 3 measured depression, 3 measured sexually
transmitted diseases, 2 measured drug abuse, 1 measured HIV, and 5 measured other types of outcomes
such as unwanted pregnancy or high school drop-out [
6
]. No studies reported odds ratios (ORs) or
relative risks (RRs) for the effects of violence against children on employment, formal and informal care,
or service use (e.g., health care services, criminal justice services). Given that the existing literature
mostly investigated the impacts of violence against children on health outcomes and health risk
behaviours, there is no sufficient information from the systematic review to estimate the economic
costs associated with the consequences of violence against children beyond health outcomes and
health risk behaviours. Thus, following the methods used by previous studies [
2
,
5
], we estimated
the economic burden of violence against children by first estimating the disability-adjusted life years
(DALYs) lost from health outcomes and health risk behaviours attributable to childhood violence and
then converting the DALY losses into a monetary value using a human capital approach, assuming that
one DALY is equal to the country’s per-capita GDP.
Following a systematic review of the prevalence literature, we began a meta-analysis to determine
the prevalence rates. However, at the same time, the results from the Optimus Study South Africa [
7
]
were released—these provide the first nationally representative figures of different forms of violence
against children in South Africa. Since nationally representative studies provide more accurate data
than those that can be pieced together through a meta-analysis, the Optimus Study data [
7
] were used
in subsequent analyses.
2.2. Step Two—Calculation of Population Attributable Fractions (PAFs)
Population Attributable Fractions (PAFs) were used to estimate the proportion of morbidity or
mortality attributable to a risk factor. All PAF formulas require: (1) Relative risk (RR) of a disease or
outcome (e.g., depression) given exposure to a risk factor (violence against children), or an odds ratio
(OR) which can be converted into an approximate estimate of the relative risk (RR); and (2) a measure
of prevalence. To calculate a population attributable fraction, it is necessary to know the prevalence
of a risk factor—e.g., violence against children—and the relative rate for the disease or outcome of
interest—e.g., depression—given exposure to that risk factor. In order to match the outcomes with the
available Global Burden of Disease categories, the outcomes were further limited to: alcohol abuse,
drug abuse, sexually transmitted diseases (STDs), HIV, interpersonal violence, self-harm and mental
Int. J. Environ. Res. Public Health 2017,14, 1431 4 of 14
disorder—including depression and anxiety. For each of these outcomes, we attempted to calculate a
population attributable fraction for each form of violence against children for which we had data.
Studies used to calculate ORs and RRs for violence against children in terms of a number
of outcome relationships are presented in Table A1. Table A2 in the Appendix Apresents the
ORs for health outcomes associated with childhood violence that were found from the systematic
review. In addition to the findings from the systematic review regarding the outcomes of violence,
we conducted additional data analyses to explore outcomes of violence against children based on the
Cape Area Panel Study (CAPS). The CAPS follows the lives of a large and representative sample of
adolescents in Cape Town as they undergo the multiple transitions from adolescence to adulthood.
The CAPS started in 2002 and ended in 2009, and includes five successive waves of survey. The study
investigated the multidimensional nature of the lives of the young men and women—educational,
psychological, familial, sociological, economic, and community.
Based on the data from the CAPS, generalised linear models (for binary outcome variables) or
linear regression (for continuous outcome variables) were used to estimate the associations between
the different types of violence against children (childhood emotional violence and physical violence)
and the related young adult consequences and risk behaviours: violence perpetration, wages earned,
alcohol use, drug use, obesity, and mental health. The Heckman two-stage method was used to
correct for the selection bias (i.e., people who work are selected non-randomly from the population)
and to estimate the marginal effect of violence against children on wages. All these regressions
were controlled for socio-demographic or biological confounding factors: sex, race, respondent’s
education, marital status, childhood family poverty, childhood family size, childhood family structure,
and mother’s education. The Stata software (prefix SVY) was used to control for the survey design
effects of individuals clustered in sampling units of enumeration areas (EAs) and stratification of major
population groups in Cape Town—black African, coloured, and white.
If only the unadjusted ORs for a study were available, we produced corresponding estimates of
adjusted ORs using the ratios between adjusted and unadjusted ORs reported for other studies [
8
].
As most studies included in the systematic review reported ORs but not RRs, RRs had to be estimated
from the ORs using a simple formula [
9
]. The secondary data analyses based on the CAPS generated
RRs directly, using generalised linear models (See Table A3 in the Appendix A).
Finally, for each type of violence, the estimated RRs were grouped according to outcomes and
then combined using meta-analysis with sample size weighting.
2.3. Step Three—Estimating the Costs to South Africa of Violence against Its Children
In the final step, we estimated the costs to the economy of violence against South African Children
using a prevalence-based approach. Cost categories available from the existing data were estimated
as follows:
•
Disability-Adjusted life years (DALYs) lost were calculated for both fatal violence, and for the
physical and mental health outcomes, and health risk behaviours, that could be attributed to
nonfatal violence against children;
•Reductions in earnings attributable to physical and emotional violence against children;
•Costs to the government child protection system.
2.3.1. Monetary Value of DALY Loss
Based on the findings from the literature review and data analyses, we first estimated monetary
value of DALY loss attributable to nonfatal violence against children. Following the work of the World
Health Organization (WHO) [
10
] and Brown [
11
], we estimated the DALYs lost—due to violence
against children-attributable physical and mental health outcomes and health-risk behaviours—and
then estimated the monetary value of those DALYs in 2015 South African Rand (ZAR).
Int. J. Environ. Res. Public Health 2017,14, 1431 5 of 14
For each of the main types of violence against children that we considered, a population
attributable fraction for an outcome of interest was multiplied by the estimate of the number of the
DALYs expected to be lost because of that outcome. Population attributable fractions of our selected
health and behavioural outcomes (alcohol abuse, drug abuse, sexually transmitted diseases (STDs),
HIV, interpersonal violence, self-harm, serious mental illness, depression and anxiety) were matched
to definitions of “alcohol use”, “drug use”, “STDs excluding HIV“, “HIV/AIDS”, “interpersonal
violence”, “self-harm”, “mental disorders”, “depressive disorders”, and “anxiety disorders” from
the Global Burden of Disease Study 2015 (GBD 2015) (Available at http://ghdx.healthdata.org/gbd-
results-tool [12]).
Given the possible co-morbidity between childhood violence and other health outcomes, DALY
data was only used for those aged 15+ to estimate disease-induced DALY losses. This was to avoid
the possibility of diseases preceding the occurrence of childhood violence. To avoid double counting,
the contribution of the cause categories (e.g., self-harm, HIV/AIDS) to DALY loss under a given risk
factor (e.g., drug use) was removed, if PAFs for these cause categories (e.g., self-harm, HIV/AIDS)
were available separately.
Second, the DALYs lost from fatal cases of violence against children were calculated as the number
of child deaths multiplied by a loss function specifying the years lost for deaths as a function of the
age at which death occurs [
13
]. Since the loss function is intended to represent the maximum life
span of an individual in good health, who is not exposed to avoidable health risks, or severe injuries,
and receives appropriate health services, the 2015 Global Burden of Disease study chose to base this
on the frontier national life expectancy projected for the year 2050 by the World Population Prospects
2012 [14]; we follow this approach here.
To convert the DALY losses into a monetary value, a method employed by WHO [
10
] and
Brown [
11
] was used. This method assumes that one DALY is equal to the country’s per-capita GDP.
In other words, it is assumed that a year lost due to either disability or mortality (one year lived with
disability or one year of life lost) is a year lost from the productive capacity of a country’s economy
and can therefore, on average, be approximated by the per capita GDP; the “human capital” approach
to valuing DALYs. Data on 2015 population, GDP, and GDP per capita for South Africa were obtained
from Statistics South Africa (Available at http://cs2016.statssa.gov.za/ [15]).
2.3.2. Reductions in Earnings
The Cape Area Panel Study is a panel study of young people in Cape Town, South Africa.
It includes data on physical and emotional violence against the participants, as well as their earnings
in adulthood. Using this, we were able to estimate the percentage reduction in adulthood earnings that
might be attributable to these two forms of violence against children. Using data from the Optimus
Study South Africa [
7
], we estimated how many people in the labour force had sufferance of physical
or emotional violence in their lifetimes. These two pieces of data were then combined to estimate
the total productivity loss in South Africa in 2015 attributable to physical and emotional violence
against children.
2.3.3. Child Welfare Costs
Services provided to child victims of violence also have a cost associated with them. In South
Africa, costs of welfare services are reported in documents available from the National Treasury;
we used these data to estimate the costs of providing these necessary services (see Table 1).
Int. J. Environ. Res. Public Health 2017,14, 1431 6 of 14
Table 1. Cost of child care and protection.
Province Revised Estimate of Child Care and Protection (2015/2016)—ZAR Thousand
Eastern Cape 216,512
Free State 78,284
Western Cape 175,376
North West 55,023
Gauteng 507,563
KZN 324,436
Northern Cape 36,687
Mpumalanga 54,092
Limpopo 133,190
National total 1,581,163
Source: National Treasury: http://www.treasury.gov.za/documents/provincial%20budget/2016/7.%20EPRE%
20standardised%20tables%20in%20Excel%20format/Default.aspx [16].
This cost under-estimates the direct costs, for several reasons: (1) It only includes what is currently
spent on services, not what would be spent if all children who were victims of violence actually
received services; and (2) It only includes welfare services, and no other services that child victims
may need (for instance, costs of policing violence against children, taking cases through the courts,
or physical or mental health services).
3. Results
3.1. Monetary Value of DALYs Lost from Nonfatal Violence against Children
Prevalence of each type of nonfatal violence against children (see Table 2), and the relative risks
and population-attributable fractions (Table 3), were used together to calculate the DALYs lost to each
type of violence, and hence the economic cost associated with the DALYs (Table 4).
Table 2. Prevalence of violence against children.
Type of Violence against Children Prevalence Rate (%)
Contact sexual violence 7.2%
Males 6.1%
Females 8.5%
Physical violence 26.1%
Males 24.0%
Females 28.7%
Emotional violence 12.6%
Males 9.7%
Females 16.2%
Neglect 12.2%
Males 9.8%
Females 15.1%
Source: Artz, L. et al., (2016). Optimus Study South Africa: Technical Report [7].
Int. J. Environ. Res. Public Health 2017,14, 1431 7 of 14
Table 3. Population attributable fractions (PAFs) and relative risks (RRs) for health outcomes associated with violence against children.
Type of VAC SMI Depression Anxiety Alcohol Abuse Drug Abuse STDs HIV Interpersonal Violence Self-Harm
RR PAF RR PAF RR PAF RR PAF RR PAF RR PAF RR PAF RR PAF RR PAF
Sexual violence
Total - - - - 1.83 0.06 - - 3.23 0.14 1.4 0.03 - - - - 2.84 0.12
Males - - - - - - 2.2 0.07 - - - - - - 1.5 0.0296 - -
Females - - 1.73 0.06 - - 2.25 0.1 - - 2 0.08 1.6 0.05 1.94 0.074 - -
Physical violence
Total 1.41 0.1 - - 1.57 0.13 1.55 0.13 1.46 0.11 - - - - 1.18 0.0449 2.13 0.23
Males - - - - - - - - - - - - - - 1.35 0.0775 - -
Females - - - - - - - - - - - - 1.97 0.22 1.48 0.1211 - -
Emotional violence
Total 1.38 0.05 - - 1.86 0.1 1.35 0.04 1.41 0.05 - - - - 1.27 0.0329 2.35 0.15
Males - - - - - - 1.33 0.03 - - - - - - - - - -
Females - - - - - - - - - - - - 1.86 0.12 - - - -
Neglect
Total - - - - 1.73 0.08 - - - - - - - - - - - -
Males - - 2.9 0.16 - - - - 1.45 0.04 - - - - - - - -
Females - - 1.66 0.09 - - 2.12 0.14 - - 1.39 0.06 - - - - - -
Witnessing family violence
Total - - - - 1.59 0.13 - - - - - - - - - - - -
Males - - - - - - - - - - - - - - 1.86 0.1591 - -
Females - - - - - - - - - - - - - - 1.71 0.1648 - -
Notes: SMI, serious mental illness; STD, sexually transmitted disease; - indicates not applicable.
Table 4. Estimated disability-adjusted life-years (DALYs) and economic value lost to childhood violence in 2015.
Health Outcomes
Sexual Violence Physical Violence Emotional Violence Neglect Aggregate Costs
DALY Loss Economic Value
(Million Rand) DALY Loss Economic Value
(Million Rand) DALY Loss Economic Value
(Million Rand) DALY Loss Economic Value
(Million Rand) DALY Loss Economic Value
(Million Rand)
Serious mental illness 90,597 6619 42,824 3129 133,420 9748
Depression 14,127 1032 48,008 3507 62,135 4540
Anxiety 7941 580 18,236 1332 13,767 1006 11,515 841 51,459 3760
Alcohol abuse 70,520 5152 119,261 8713 40,128 2932 29,717 2171 25,9626 18,969
Drug abuse 18,122 1324 14,041 1026 6434 470 3604 263 42,201 3083
STDs 1106 81 960 70 2066 151
HIV 181,841 13,285 816,045 59,621 45,8238 33,479 1,456,124 106,386
Interpersonal violence 36,764 2686 45403 3317 33,290 2432 115,457 8435
Self-harm 44,677 3264 86984 6355 55,520 4056 187,180 13,676
Total 375,097 27,405 1,172,331 85,652 636,434 46,499 93,804 6853 2,277,666 166,409
Int. J. Environ. Res. Public Health 2017,14, 1431 8 of 14
Although only a limited number of health outcomes were considered, an estimated 375,097,
1,172,331, 636,434, and 93,804 of DALYs lost in South Africa in 2015 were attributable to childhood
sexual violence, physical violence, emotional violence, and neglect, respectively. The estimated
economic value of these lost DALYs was 27.4, 85.7, 46.5, and 6.9 billion South Africa Rand (0.7%, 2.1%,
1.2%, and 0.17% of GDP), respectively.
Adding up the economic value of DALY loss across different types of violence against children,
2.3 million DALYs lost in South Africa in 2015 were attributable to violence against children, a full 32%
of those attributed to HIV/AIDS in 2015. The estimated economic value of DALYs lost to violence
against children in South Africa in 2015 totalled ZAR166 billion (4.2% of the 2015 GDP in South Africa).
3.2. Economic Cost of Fatal Violence against Children
An estimated 1018 child homicides occurred in 2009 in South Africa, broken down by age group
as follows: 405 cases in the 0–4 years age group, 87 in the 5–9 years age group, 110 in 10–14 years age
group, and 416 in 15–17 years age group [
17
]. This was the only study of child homicides that we could
identify, and we therefore assumed that the number of child homicides in 2015 equalled to that in 2009.
In order to estimate DALYs, we needed the mean ages of the children who had died; to estimate this,
we used the median age of the age group as the mean age of victims. Thus we estimated the mean age
of the 405 child victims in the 0–4 age group to be 2, the mean age in the 5–9 age group to be 7, 12 for
the 10–14 age group, and 16 for the 15–17 age group.
The WHO standard life table for years of life lost [
13
] provides standards for the expected
years of life lost for a death at a particular age. We used this to estimate years of life lost
at ages 2, 7, 12 and 16 to be 90.01, 85.02, 80.03, and 76.04, respectively. DALYs lost from the
1018 child deaths was then estimated to be 84,287, by multiplying the number of deaths in each
age group by the corresponding years of life lost for the deaths at the mean age of the age group
(
90.01 ×405 + 85.02 ×87 + 80.03 ×110 + 76.04 ×416
). The estimated economic value of these lost
DALYs was 6.2 billion South Africa Rand (0.16% of South Africa’s GDP).
3.3. Reduced Earnings
Our analyses of the Cape Area Panel Study data allowed us to estimate that physical and
emotional violence against children on average reduce victim monthly earnings by 11.7% and 9.2%,
respectively. According to Statistics South Africa [
18
], the median monthly earnings for South Africa
for 2014 (including employees, employers and own-account workers) was ZAR3120. We then used the
Consumer Price Index to adjust this figure 2015 Rand values, yielding an estimated median monthly
earning figure of ZAR3262. Combining these two pieces of data, physical and emotional violence
against children on average therefore reduce victim monthly earnings by ZAR382 (3262
×
11.7%) and
ZAR300 (3262 ×9.2%), respectively.
According to the weighted data from the self-administered questionnaire in household surveys
that formed part of the Optimus Study South Africa [
7
], 26.1% of the respondents reported lifetime
experience of physical violence, and 12.6% reported some experience of emotional violence in their
lifetimes. In 2015, the average size of the labour force was 21,084,500 in South Africa (Available at
http://cs2016.statssa.gov.za/ [
15
]). We then calculated how many people in the labour force in 2015
were lifetime victims of childhood physical violence (5,503,055; 21,084,500
×
26.1%) and lifetime
victims of childhood emotional violence (2,656,647; 21,084,500 ×12.6%).
The total monthly productivity loss attributable to physical and to emotional violence against
children in South Africa in 2015 could thus be estimated at ZAR2,100,262,762 (5,503,055
×
382) and
ZAR797,270,391 (2,656,647
×
300), respectively. The corresponding annual figures could be achieved
by multiplying these estimates by 12, so that the total productivity loss in South Africa for the year of
2015 attributable to physical and emotional violence against children were ZAR25.2 (0.63% of GDP)
and ZAR9.6 billion (0.24% of GDP), respectively.
Int. J. Environ. Res. Public Health 2017,14, 1431 9 of 14
3.4. Child Welfare Costs
Together, the nine South African provinces in South Africa spent ZAR1.58 billion (0.04% of GDP)
on child care and protection in fiscal year 2015/2016.
4. Discussion
This is the first study to estimate the economic cost of violence against children in South Africa.
Data from previous studies, and in particular the Optimus Study South Africa [
7
], shows that violence is
a common experience for South African children; our work shows that this violence is not only a human
rights issue, but an economic one: violence against children costs South African society in terms of both
DALYS and money. According to our calculations, 2.3 million and 84,287 DALYs lost in South Africa
in 2015 were attributable to nonfatal and to fatal violence against children, respectively. Our estimates
of DALYs lost to nonfatal violence against children are greater than the corresponding South African
estimates for diabetes mellitus (1.1 million DALYs lost) and cardiovascular diseases (2.1 million DALYs
lost) (Available at http://ghdx.healthdata.org/gbd-results-tool). HIV/AIDS was the leading cause
of DALYs lost in 2015 in South Africa (Available at http://ghdx.healthdata.org/gbd-results-tool):
our figures for DALYs lost to non-fatal violence against children led to the loss of 32% of the DALYs lost
to HIV/AIDS. The estimated economic value of DALYs lost to violence against children (including both
fatal and nonfatal) in South Africa in 2015 totalled ZAR173 billion (US $13.5 billion)—or 4.3% of South
Africa’s GDP in 2015. These were not the only costs. The reduced earnings attributable to physical and
emotional violence against children in South Africa in 2015 were ZAR25.2 billion (US $2.0 billion) and
ZAR9.6 billion (US $750 million), respectively. Despite these high costs to the economy, South Africa
spent only ZAR1.6 billion (US $124 million) on child care and protection in fiscal year 2015/2016.
There are of course limitations in our work. In particular, these estimates suffer from several
major gaps in the evidence base and data available in South Africa. PAFs may be sensitive to small
changes in prevalence and RR, and most of the studies used for calculating PAF did not have
representative samples, used different samples and approaches to sampling, different definitions
of violence against children, and different measures. The implications of these differences can be
significant when multiplied by an aggregate outcome. Although we carefully reviewed all input data
to select appropriate studies, our results are inevitably based on what data is available. This problem is
not limited to research into violence against children; such challenges generally emerge in any research
that draws on a variety of secondary data sources.
Although the DALYs measure has made a central contribution to the comparative assessment of
disease burden, it is important to note that the measure has been the subject of some debate [
19
–
21
].
For instance, the validity and universality of the disability weights [
20
,
21
] have been questioned,
and standard life expectancy figures may overestimate DALYs saved when actual or local life
expectancy is shorter [
22
]. Furthermore, DALYs are a global generic disability index, but the relative
weights for each health state/condition may be substantially different in any single country and lead
to quite different results. Thus, the DALY results should be interpreted with caution.
Ideally, studies of this nature would account for poly-victimisation, or repeat victimisation—a
common phenomenon in violence against children, and one which may provide the greater part of
the association between victimisation and consequences [
23
]. Unfortunately, based on the studies
available to us, we were not able to take this into account, which may have led to over-estimation of
the aggregate economic burden of violence against children.
Other factors known to confound the association between exposure to violence and later
outcomes (for instance, genetic and other family factors) [
2
,
24
] were also not taken into account
in the studies available to us, which again could have resulted in an over-estimation of the PAFs.
In addition, most of the studies of consequences that we used measured both violence exposure and
the consequences by self-report in cross sectional studies, and retrospectively, and this too may lead
to either over- or under-estimation. Further, because the studies used self-report, they only reported
ORs. Approximate RRs needed for PAF were calculated with from ORs with a simple formula [
9
],
Int. J. Environ. Res. Public Health 2017,14, 1431 10 of 14
but because the majority of studies were based on small sample sizes, the RRs generated from these
studies may not be generalisable to the entire population and the resultant PAFs could be biased up or
down. We used meta-analysis with sample size weighting to alleviate these problems, but it cannot
fully eliminate this bias.
Considering all these limitations together, we suggest that the burden estimates derived from our
work are likely to under-estimate the true situation. The studies of health outcomes available to us for
estimating the burden of violence against children only addressed a small number of health outcomes,
and our work therefore does not include other serious effects of violence against children (for instance,
its association with obesity, itself associated with increased morbidity and mortality) [
25
]. Costs that
we were not able to include in our models included the costs of poor educational outcomes; increased
formal and informal care; higher levels of healthcare utilisation; criminal behaviour; reproductive
health problems; and chronic diseases such as diabetes, heart disease and cancer.
5. Conclusions
This study reveals that the economic burden of violence against children in South Africa is
substantial, and thus confirms the importance of prioritising violence against children as a key social
and economic concern for South Africa’s future development. Policy-makers are urged to consider the
huge economic cost, as well as the human cost, of the lifetime impacts of violence against children in
their budget allocations. It provides a strong indication that resources directed towards preventing
violence against children are a vital investment that could save lives, could prevent much agony for
children, and increase the economic dividend that lies latent in the country’s children.
Acknowledgments: This work was funded from the resources of Save the Children South Africa.
Author Contributions:
This study was designed by Xiangming Fang, Deborah A. Fry, and Catherine L. Ward.
Systematic reviews were conducted by Gary Ganz and Tabitha Casey. Meta-analysis and secondary data analysis
were conducted by Xiangming Fang and Xiaodong Zheng. The manuscript was written and revised by all authors.
Conflicts of Interest: The authors declare no conflict of interest.
Appendix A
Table A1.
Studies used to calculate relative risks (RRs) for violence against children (VAC)—outcomes.
Study Reference VAC—Outcomes Relationship
[26]Sexual Violence—Self-harm
Physical Violence—Self-harm
[27] Physical Violence—Anxiety
[28]
Sexual Violence—Anxiety
Physical Violence—Anxiety
Emotional Violence—Anxiety
Neglect—Anxiety
[29] Sexual Violence—Interpersonal Violence
[30] Physical Violence—Interpersonal Violence
[31]Sexual Violence—Drug Abuse
Sexual Violence—Interpersonal Violence
Int. J. Environ. Res. Public Health 2017,14, 1431 11 of 14
Table A1. Cont.
Study Reference VAC—Outcomes Relationship
[32]
Sexual Violence—Depression
Sexual Violence—Alcohol Abuse
Sexual Violence—HIV
Physical Violence—HIV
Emotional Violence—Alcohol Abuse
Emotional Violence—HIV
Neglect—Depression
Neglect—Alcohol Abuse
Neglect—Drug Abuse
Neglect—STDs
[33] Physical Violence—Interpersonal Violence
[34] Physical Violence—Anxiety
[35] Sexual Violence—STD
[36]Sexual Violence—Interpersonal Violence
Physical Violence—Interpersonal Violence
[37] Sexual violence—Depression
[38] Sexual violence—STD
[39] Emotional Violence—Self-harm
[40]Sexual Violence—Interpersonal Violence
Physical Violence—Interpersonal Violence
[41]Sexual Violence—Substance use disorders
Physical Violence—Anxiety
[42] Physical Violence—Alcohol Abuse
Int. J. Environ. Res. Public Health 2017,14, 1431 12 of 14
Table A2. Odd ratios (ORs) for health outcomes associated with childhood violence based on the systematic review.
Type of VAC SMI Depression Anxiety Alcohol Abuse Drug Abuse STDs HIV Interpersonal Violence Self-Harm
Sexual abuse
Total - - 2.8 - 4.9 1.4 - - 9.3
Males - - - 3.7 - - - 2.1 -
Females - 2.2, 1.5 - 3.9 - 2.2 1.7 3.4, 2.4, 2.3, 2 -
Physical abuse
Total - - 1.9 2, 2.2 - - - - 2.2
Males - - - - - - - 2.2, 1.4 -
Females - - - - - - 2.1 1.6, 2.2 -
Emotional abuse
Total - - 2.9 - - - - - 2.4
Males - - - 1.5 - - - - -
Females - - - - - - 2.0 - -
Neglect
Total - - 2.5 - - - - - -
Males - 3.4 - - 2.0 - - - -
Females - 1.8 - 2.2 - 1.6 - - -
Witnessing family violence
Total - - 2.1 - - - - - -
Males - - - - - - - 1.5, 1.7, 2.0, 2.3 -
Females - - - - - - - 1.6, 1.8, 1.7 -
Table A3. Relative risks (RRs) for health outcomes associated with childhood violence based on the secondary analysis of the Cape Area Panel Study.
Type of VAC SMI Obesity Perpetrating Violence Smoking Problem Drinking Illicit Drug Use
Physical abuse 1.409 ** 1.348 ** 1.184 * 1.103 ** 1.124 1.460 **
(1.065, 1.863) (1.045, 1.740) (0.992, 1.414) (1.009, 1.206) (0.739, 1.709) (1.050, 2.031)
Emotional abuse 1.382 ** 1.309 ** 1.273 ** 1.045 1.349 * 1.410 **
(1.007, 1.896) (1.045, 1.708) (1.046, 1.549) (0.954, 1.146) (0.891, 2.043) (1.027, 1.935)
*p< 0.10; ** p< 0.05.
Int. J. Environ. Res. Public Health 2017,14, 1431 13 of 14
References
1.
Fry, D.; Blight, S. How prevention of violence in childhood builds healthier economies and smarter children
in the Asia and Pacific region. BMJ Glob. Health 2016,1, i3–i11. [CrossRef] [PubMed]
2.
Fang, X.; Fry, D.A.; Brown, D.S.; Mercy, J.A.; Dunne, M.P.; Butchart, A.R.; Corso, P.S.; Maynzyuk, K.;
Dzhygyr, Y.; Chen, Y.; et al. The burden of child maltreatment in the East Asia and Pacific region.
Child Abuse Negl. 2015,42, 146–162. [CrossRef] [PubMed]
3.
Fang, X.; Brown, D.S.; Florence, C.S.; Mercy, J.A. The economic burden of child maltreatment in the United
States and implications for prevention. Child Abuse Negl. 2012,36, 156–165. [CrossRef] [PubMed]
4.
Australian Institute of Family Studies (AIFS). The Economic Costs of Child Abuse and Neglect;
Australian Institute of Family Studies: Melbourne, Australia, 2016.
5.
Fang, X.; Fry, D.A.; Ji, K.; Finkelhor, D.; Chen, J.; Lannen, P.; Dunne, M.P. The burden of child maltreatment
in China: A systematic review. Bull. World Health Organ. 2015,93, 176C–185C. [CrossRef] [PubMed]
6.
Casey, T.; Ganz, G.; Fry, D.; Zheng, X.; Fang, X.; Hsiao, C.; Ward, C. The Consequences of Violence against
Children in South Africa: A Systematic Review and Meta-Analysis. Child Abuse Rev. 2017. under review.
7.
Artz, L.; Burton, P.; Ward, C.L.; Leoschut, L.; Phyfer, J.; Lloyd, S. Optimus Study South Africa, Technical Report;
UBS Optimus Foundation: Zurich, Switzerland, 2016.
8.
Andrews, G.; Corry, J.; Slade, T.; Issakadis, C.; Swanston, H. Child sexual abuse. In Comparative Quantification
of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors; Ezzati, M.,
Lopez, A.D., Rodgers, A., Murray, C., Eds.; World Health Organization: Geneva, Switzerland, 2004.
9.
Zhang, J.; Yu, K.F. What’s the relative risk? A method of correcting the odds ratio in cohort studies of
common outcomes. JAMA 1998,280, 1690–1691. [CrossRef] [PubMed]
10.
World Health Organization. Macroeconomics and Health. Investing in Health for Economic Development;
WHO: Geneva, Switzerland, 2001.
11.
Brown, D.W. Economic value of disability-adjusted life years lost to violence, estimates for WHO Member
States. Revista Panamerica de Salud Pública 2008,4, 203–209. [CrossRef]
12.
Global Burden of Disease (GBD) Results Tool. GHDx. Available online: http://ghdx.healthdata.org/gbd-
results-tool (accessed on 4 July 2017).
13.
World Health Organization. WHO Methods and Data Sources for Global Burden of Disease Estimates
2000–2011. Available online: http://www.who.int/healthinfo/statistics/GlobalDALYmethods2000_2011.pdf
(accessed on 4 July 2017).
14.
United Nations Population Division. World Population Prospects; 2012 Revision; United Nations:
New York, NY, USA, 2013.
15. Statistics South Africa. Available online: http://cs2016.statssa.gov.za/ (accessed on 8 July 2017).
16.
National Treasury. Available online: http://www.treasury.gov.za/documents/provincial%20budget/2016/
7.%20EPRE%20standardised%20tables%20in%20Excel%20format/Default.aspx (accessed on 8 July 2017).
17.
Mathews, S.; Abrahams, N.; Jewkes, R.; Martin, L.J.; Lombard, C. The epidemiology of child homicides in
South Africa. Bull. World Health Organ. 2013,91, 562–568. [CrossRef] [PubMed]
18.
Statistics South Africa. Gross Domestic Product, Fourth Quarter 2015 (P0441); Statistics South Africa:
Pretoria, South Africa, 2016.
19.
Anand, S.; Hanson, K. Disability-adjusted life years, a critical review. J. Health Econ.
1997
,16, 685–702.
[CrossRef]
20.
Arnesen, T.; Nord, E. The value of DALY life, problems with ethics and validity of disability adjusted life
years. BMJ 1999,319, 1423–1425. [CrossRef] [PubMed]
21. James, K.; Foster, S. Are disability weights universal? Lancet 1999,354, 1306.
22.
Sassi, F. Calculating QALYs, comparing QALY and DALY calculations. Health Policy Plan.
2006
,21, 402–408.
[CrossRef] [PubMed]
23.
Finkelhor, D.; Ormrod, R.K.; Turner, H.A. Poly-victimization: A neglected component in child victimization.
Child Abuse Negl. 2007,31, 7–26. [CrossRef] [PubMed]
24.
Coates, D. Impact of childhood abuse: Biopsychosocial pathways through which adult mental health is
compromised. Aust. Soc. Work 2010,63, 391–403. [CrossRef]
25.
Greenfield, E.A.; Marks, N.F. Violence from parents in childhood and obesity in adulthood: Using food in
response to stress as a mediator of risk. Soc. Sci. Med. 2009,68, 791–798. [CrossRef] [PubMed]
Int. J. Environ. Res. Public Health 2017,14, 1431 14 of 14
26.
Bruwer, B.; Govender, R.; Bishop, M.; Williams, D.R.; Stein, D.J.; Seedat, S. Association between childhood
adversities and long-term suicidality among South Africans from the results of the South African Stress and
Health study: A cross-sectional study. BMJ Open 2014,4, e004644. [CrossRef] [PubMed]
27.
Collings, S.J. Childhood exposure to community and domestic violence: Prevalence, risk factors and
posttraumatic outcomes in a South African student sample. J. Psychol. Afr. 2011,21, 535–539. [CrossRef]
28.
Collings, S.J.; Penning, S.L.; Valjee, S.R. Lifetime poly-victimization and posttraumatic stress disorder among
school-going adolescents in Durban, South Africa. J. Psychiatry Open Access 2014,17. [CrossRef]
29.
Dunkle, K.L.; Jewkes, R.K.; Brown, H.C.; Yoshihama, M.; Gray, G.E.; McIntyre, J.A.; Harlow, S.D.
Prevalence and patterns of gender-based violence and revictimization among women attending antenatal
clinics in Soweto, South Africa. Am. J. Epidemiol. 2004,160, 230–239. [CrossRef] [PubMed]
30.
Gass, J.D.; Stein, D.J.; Williams, D.R.; Seedat, S. Gender differences in risk for intimate partner violence
among South African adults. J. Interpers. Violence 2011,26, 2764–2789. [CrossRef] [PubMed]
31.
Heusser, S.; Elkonin, D. Childhood sexual abuse and HIV sexual-risk behaviour among men who have sex
with men in South Africa. S. Afr. J. Psychol. 2014,44, 83–96. [CrossRef]
32.
Jewkes, R.; Dunkle, K.; Nduna, M.; Jama, P.N.; Puren, A. Associations between childhood adversity
and depression, substance abuse and HIV and HSV2 incident infections in rural South African youth.
Child Abuse Negl. 2010,34, 833–841. [CrossRef] [PubMed]
33.
Jewkes, R.; Levin, J.; Penn-Kekana, L. Risk factors for domestic violence: Findings from a South African
cross-sectional study. Soc. Sci. Med. 2002,55, 1603–1617. [CrossRef]
34.
Kaminer, D.; Grimsrud, A.; Myer, L.; Stein, D.J.; Williams, D.R. Risk for post-traumatic stress disorder
associated with different forms of interpersonal violence in South Africa. Soc. Sci. Med.
2008
,67, 1589–1595.
[CrossRef] [PubMed]
35.
Maharaj, P.; Munthree, C. Coerced first sexual intercourse and selected reproductive health outcomes among
young women in KwaZulu-Natal, South Africa. J. Biosoc. Sci. 2007,39, 231–244. [CrossRef] [PubMed]
36.
Meinck, F.; Cluver, L.D.; Boyes, M.E. Longitudinal predictors of child sexual abuse in a large
community-based sample of South African youth. J. Interpers. Violence 2015, 1–33. [CrossRef] [PubMed]
37.
Nduna, M.; Jewkes, R.K.; Dunkle, K.L.; JamaShai, N.P.; Colman, I. Prevalence and factors associated with
depressive symptoms among young women and men in the Eastern Cape Province, South Africa. J. Child
Adolesc. Ment. Health 2013,25, 43–54. [CrossRef] [PubMed]
38.
O‘Leary, A.; Jemmott, J.B., 3rd; Jemmott, L.S.; Teitelman, A.; Heeren, G.A.; Ngwane, Z.; Icard, L.; Lewis, D.A.
Associations between psychosocial factors and incidence of sexually transmitted disease among South
African adolescents. Sex. Transm. Dis. 2015,42, 135–139. [CrossRef]
39.
Penning, S.L.; Collings, S.J. Perpetration, revictimization, and self-injury: Traumatic reenactments of child
sexual abuse in a nonclinical sample of South African adolescents. J. Child Sex. Abuse
2014
,23, 708–726.
[CrossRef] [PubMed]
40.
Shamu, S.; Gevers, A.; Mahlangu, B.P.; JamaShai, P.N.; Chirwa, E.D.; Jewkes, R.K. Prevalence and risk factors
for intimate partner violence among Grade 8 learners in urban South Africa: Baseline analysis from the
Skhokho Supporting Success cluster randomised controlled trial. Int. Health
2015
,8, 18–26. [CrossRef]
[PubMed]
41.
Slopen, N.; Williams, D.R.; Seedat, S.; Moomal, H.; Herman, A.; Stein, D.J. Adversities in childhood and
adult psychopathology in the South Africa Stress and Health Study: Associations with first-onset DSM-IV
disorders. Soc. Sci. Med. 2010,71, 1847–1854. [CrossRef] [PubMed]
42.
Sorsdahl, K.; Stein, D.J.; Williams, D.R.; Anthony, J.; Myers, B. Childhood punishment and risk for alcohol
use disorders: Data from South Africa. Int. J. Ment. Health Addict. 2015,13, 103–114. [CrossRef]
©
2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).