Risk and Protective Factors for Whoonga use among adolescents in South Africa

Abstract

Background
Antiretroviral therapy (ART) is publicly available in South Africa in response to the urgent need to address HIV and AIDS. Off-label use of ARV medication alone or in combination with other substances is known as “whoonga” and “nyaope” in South Africa. Diversion of ARVs for whoonga use is not well understood, especially among adolescents. This secondary analysis explores risk and protective factors for adolescent whoonga use in a community-based HIV endemic setting.

Methods
Data on whoonga use were derived from the baseline survey of N=200 adolescents recruited for participation in a randomized controlled trail to reduce adolescent HIV risk behaviors and depression. Risk and protective factors for adolescent whoonga use were explored using an ecological systems framework using one-way ANOVAs, chi-squared tests and hierarchical regressions.

Results
Individual level factors increased the odds of whoonga use or known use such child age OR:1.22 (95% CI, 1.03-1.43), hazardous drug use OR:1.62 (95% CI, 1.02-2.59), and hazardous alcohol OR:1.80 (95% CI, 1.05-3.09). Food insecurity appears to have a slightly protective effect on the odds of whoonga use or reports of use among people adolescents knew OR:0.649 (95% CI, 0.541-0.779).

Conclusions
Larger epidemiological studies should expand the surveillance of hazardous alcohol use and illicit drug use, specifically for recreational use of prescription medication. Granular data is warranted to characterize the patters of use, especially among highly vulnerable populations such as adolescents. Future surveillance studies that explore these multi-level relationships are warranted to further understand this phenomenon among teens in South Africa.

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Risk and Protective Factors for Whoonga use among adolescents in South Af‐
rica
Teresa DeAtley, Catherine Mathews, Dan J. Stein, David Grelotti, Larry K.
Brown, Danielle Giovenco, Millicent Atujuna, William Beardslee, Caroline
Kuo
PII: S2352-8532(19)30237-8
DOI: https://doi.org/10.1016/j.abrep.2020.100277
Reference: ABREP 100277
To appear in: Addictive Behaviors Reports
Received Date: 29 November 2019
Revised Date: 8 April 2020
Accepted Date: 17 April 2020
Please cite this article as: T. DeAtley, C. Mathews, D.J. Stein, D. Grelotti, L.K. Brown, D. Giovenco, M.
Atujuna, W. Beardslee, C. Kuo, Risk and Protective Factors for Whoonga use among adolescents in South Africa,
Addictive Behaviors Reports (2020), doi: https://doi.org/10.1016/j.abrep.2020.100277
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1
Title: Risk and Protective Factors for Whoonga use among adolescents in South Africa
Authors and Affiliations: Teresa DeAtley,1 Catherine Mathews,2 Dan J. Stein,2, David Grelotti,3
Larry K. Brown,4,5 Danielle Giovenco, 6 Millicent Atujuna,7 William Beardslee,8 Caroline
Kuo1,2,5
1Brown University School of Public Health, Department of Behavioral and Social Sciences
Brown University School of Public Health, 121 S Main St, Providence, Rhode Island 02903,
USA
2University of Cape Town, Department of Psychiatry and Mental Health & South African
Medical Research Council, Unit on Risk & Resilience in Mental Disorders, Groote Schuur
Hospital, Anzio Road, Observatory, Cape Town, 7925, South Africa
3University of California San Diego, Department of Psychiatry, 220 Dickinson Street, Suite B,
San Diego, California 92103, USA
4Alpert Medical School of Brown University, Department of Psychiatry and Human Behavior,
222 Richmond St, Providence, Rhode Island 02903, USA
5Providence/Boston Center for AIDS Research, 164 Summit Avenue CFAR Building, Room
134, Providence, Rhode Island, 02906, USA
6University of North Carolina at Chapel Hill, Department of Epidemiology, 135 Dauer Drive,
2101 McGavran-Greenberg Hall, CB #7435, Chapel Hill, NC 27599-7435, USA
7Desmond Tutu HIV Foundation, P.O. Box 13801, Mowbray, 7705 Cape Town, South Africa
8Boston Children’s Hospital & Judge Baker Children’s Center & Harvard Medical School,
Department of Psychiatry, 53 Parker Hill Ave, Roxbury Crossing, Massachusetts 02120, USA
Corresponding author:
Teresa DeAtley, MPH
Department of Behavioral and Social Sciences
Brown University School of Public Health
121 South Main Street, Providence, Rhode Island 02912, USA
Email: Teresa_DeAtley@brown.edu Phone: +1 571 345 6680
Abstract
Background: Antiretroviral therapy (ART) is publicly available in South Africa in response to
the urgent need to address HIV and AIDS. Off-label use of ARV medication alone or in
combination with other substances is known as "whoonga" and "nyaope" in South Africa.
Diversion of ARVs for whoonga use is not well understood, especially among adolescents. This

2
secondary analysis explores risk and protective factors for adolescent whoonga use in a
community-based HIV endemic setting.
Methods: Data on whoonga use were derived from the baseline survey of N=200 adolescents
recruited for participation in a randomized controlled trail to reduce adolescent HIV risk
behaviors and depression. Risk and protective factors for adolescent whoonga use were explored
using an ecological systems framework using one-way ANOVAs, chi-squared tests and
hierarchical regressions.
Results: Individual level factors increased the odds of whoonga use or known use such child age
OR:1.22 (95% CI, 1.03-1.43), hazardous drug use OR:1.62 (95% CI, 1.02-2.59), and hazardous
alcohol OR:1.80 (95% CI, 1.05-3.09). Food insecurity appears to have a slightly protective effect
on the odds of whoonga use or reports of use among people adolescents knew OR:0.649 (95%
CI, 0.541-0.779).
Conclusions: Larger epidemiological studies should expand the surveillance of hazardous
alcohol use and illicit drug use, specifically for recreational use of prescription medication.
Granular data is warranted to characterize the patters of use, especially among highly vulnerable
populations such as adolescents. Future surveillance studies that explore these multi-level
relationships are warranted to further understand this phenomenon among teens in South Africa.
1 Introduction
South Africa has the largest country population of individuals living with HIV (UNAIDS,
2014). Antiretroviral therapy (ART) medication is widely available through large public sector
roll out (Jain and Zorzi, 2017; Chin et al., 2015). ART was initially being used for treatment but
now is increasingly being used as pre-exposure prophylaxis (PrEP) for HIV prevention. In
parallel with efforts to increase the availability of HIV prescription medication in South Africa
for treatment and prevention, there has been an emergence of a new substance use phenomenon
with a drug known as whoonga (or wunga/nyaope). Diversion of ART for recreational use has
also been documented in the United States (Eban, 2005; Grelotti et al., 2013).

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There is limited consensus on the chemical composition of whoonga. The chemical
composition is likely to vary by context and change over time. It is thought that whoonga
contains ART medication mixed with detergent, rat poison, marijuana, and/or methamphetamine.
While not all ART has neuropsychiatric effects, efavirenz has documented neuropsychiatric
effects including hallucinations, psychosis and mania (Grelotti et al., 2014; Mimiaga et al., 2015;
Rough et al., 2014), likely a result of agonism of the 5-HT(2A) receptor, the serotonin receptor
implicated in mediating the psychoactive effects of lysergic acid diethylamine (LSD) (Gatch et
al., 2013).
Diversion of ART for recreational substance use is especially concerning for adolescents.
The 2011 Youth Risk Behavior Survey reported that adolescent illicit drug use was highest for
cannabis/daga (12.5%) followed by prescription drugs (11.5%) and inhalants (11.5%). Mandrax,
heroin, club drugs, tik and whoonga self-reported ever use ranged from 4.5 to 5.5% (Reddy et
al., 2013). Early experimentation with drugs can intensify use and place adolescents at increased
risk for substance use dependence in adulthood (Grant and Dawson, 1998; Van Ryzin and
Dishion, 2014; Wang et al., 2014).
Of the reports, we identified on this emergent phenomenon, only one reported whoonga
use among adolescents (Grelotti et al., 2014). Much remains unknown on the patterns and risk
factors for whoonga among adolescents (Rough et al., 2014). In this paper, we report on one of
few studies to examine this phenomenon in a community-based sample of adolescents from a
community with high prevalence of HIV. We utilized ecological systems theory to understand
how multiple environments influence adolescent whoonga use (Bronfenbrenner, 1979) and to
examine risk and protective factors in three levels of the adolescent ecosystem, 1) individual, 2)

4
interpersonal, and 3) community. This approach has been previously used to understand
adolescent substance use among Zambian street youth (Tyler et al., 2016).
2 Methods
This paper utilizes data from Our Family Our Future, a pilot randomized controlled trial
(RCT) designed to explore the acceptability and feasibility of an intervention to reduce
adolescent HIV risk behaviors and depression. Data on whoonga use were derived from the
baseline survey of N=200 adolescents recruited for participation in the RCT.
The RCT took place during 2015-2017 in a community in Cape Town, South Africa. An
institutional review board approved all study protocols. Adolescents were recruited house-to-
house within randomly selected enumeration areas. Adolescents were eligible to participate if
they were between the ages of 13-15 years, lived in the household at least four days a week,
confirmed that the adult was either a primary caregiver or parent, and met a threshold for
elevated depressive symptoms. After gaining parent or guardian and adolescents provided
written informed assent. Adolescents completed a survey in English or isiXhosa using
smartphones. Surveys occurred in participant’s homes. Interviewers administered non-sensitive
behavioral questions by reading questions and answer options off a smartphone and entering
answers. Sensitive questions including questions on recreational ARV use were administered
through Audio Computer-Assisted Self-Interviewing (ACASI). In this process participants were
given headphones attached to the smartphone. Participants were provided pre-recorded audio of
questions and answer options and provided answers in complete privacy.
2.2 Measures & Analysis

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Since whoonga is an emergent drug phenomenon there were no previously validated
measures to pull from. Whoonga use was captured using the following question: “Have you or
someone you know ever used antiretroviral medication (ARVs) to get high OR another mixture
of substances that you suspect may have contained ARVs to get high (this mix is sometimes
called nyaope or whoonga)?” Response options were: 1) you, 2) someone you know or 3) neither
I nor someone I know has done this.
In addition to whoonga use, administration modality was captured using the following
question: “How have you or someone you know used ARVs or mixtures of substances that you
suspect may have contained ARVS to get high?” Possible response options were: 1) smoked, 2)
snorted, 3) injected, 4) inserted/absorbed, and 5) swallowed.
Risk and protective factors were organized into three levels using the ecological systems theory
framework informed by current scientific evidence base on adolescent substance abuse and
analyzed using hierarchical regression.
2.2.1 Individual level measures
The Alcohol Use Disorders Identification Test (AUDIT-C)
The AUDIT-C is 3-item version of the longer AUDIT scale (Bush et al., 1998). Studies have
found high comparability between the AUDIT-C and the full AUDIT (Reinert & Allen, 2007).
AUDIT-C identifies frequency and quantity of hazardous drinking. A cutoff score of three or
more drinks for girls and four or more drinks for boys was used per standardized scoring
convention for the scale (Morojele et al., 2016).
Drug Use Disorders Identification Test (DUDIT)

6
The 11-item Drug Use Disorders Identification Test (DUDIT) was used to assess current
substance use among adolescents. This scale focused on frequency of drug use, physical and
psychological problems and symptoms of dependency (A. Berman et al., 2003; A.H. Berman et
al., 2005). We followed the standard scoring which identifies men with drug-related problems at
a cut-off score of 6 or more and women with at a cut-off score of 2 points or more. In our sample
these scores were dichotomized for hazardous drug use yes or no, following previous studies (A.
Berman et al., 2003). This scale has been validated for use among adolescents (Matuszka et al.,
2014).
2.2.2 Relational level measure
Parent Monitoring Questionnaire
The Parent Monitoring Questionnaire (PMQ) is a 15-item questionnaire that assesses three
sources of parental knowledge about adolescents’ routine activities (child disclosure, parental
solicitation, and parental control) (Kerr and Stattin, 2000). Of the three subscales, the PMQ
disclosure subscale was included into our hierarchical regression based on Table 1.
The Parent Adolescent Communication Scale
The Parent Adolescent Communication Scale (PACS) (Olson, 1985) is at 20 item questionnaire
that assesses communication quality between adolescents and parents. For this study, the
adolescent filled out the questionnaire in relation to one parent or guardian. This scale has two
subscales which were uses in this study, Open Family Communication and Problems in Family
Communication. Following the existing approach, raw scores are were used because out analysis

7
included subscale data (Houck et al., 2007). Of the two subscales, the OFC subscale was
included in our hierarchical regression (Table 1).
Lifetime sex exposure
Adolescents were asked to self-report sexual history including oral, anal and vaginal sex (if
applicable). A composite measure was created using these three questions and a summary
frequency was derived for each individual. These questions were derived from questions used by
the Adolescent Medicine Trials Network for HIV/AIDS Interventions (National Institutes of
Health Office of AIDS Research, 2019).
2.2.3 Community level measure
Food insecurity index
A food insecurity index was created using the following four questions. An aggregate sum of all
questions was coded, summary scores ranged from 0-4 for each parent. Respondents were
categorized as low (summary value of 0), moderate (summary values of 1, 2, or 3) or high
(summary value of 4) on the food insecurity scale.
2.3 Analysis
We tested every scale or index using one-way ANOVAs and chi-squared tests for association to
describe the relationship with baseline adolescent whoonga use as the outcome (with the three
levels as described above). Based on the results in Table 1, the following six measures were
included in the hierarchical regression, AUDIT-C, DUDIT, Parental Monitoring Disclosure
Subscale, Parent Adolescent Communication Scale (OFC subscale), any lifetime sex and the
Food Security Index based on a p-value of less than .05 for statistical significance. Hierarchical

8
variables were coded to align to the ecosystem model. All beta coefficients and 95% confidence
intervals were exponentiated so that results could be reported in odds.
3 Results
3.1 Patterns of Whoonga Use
Adolescent participants were an average age of 14.1 years. All identified as Black
African with isiXhosa as their primary language, with 56% female and 43% male. Three percent
of adolescents (n=6) reported use of off-label ART for recreational use. Adolescent’s reports of
whoonga use among others were notable higher (14.1%). Among those who reported recreational
ART use, either themselves or by others, it was most commonly smoked (71%) followed by
snorting (15%), injecting (15%), ingesting (15%), and inserting (3%).
3.2 Hierarchical regression
Results from the hierarchical regression are shown in Table 2. The R squared value did
improve as levels of the ecological systems theory were added but we were less concerned with
model fit, as this analysis is exploratory. A number of meaningful relationships held between the
tests for association and hierarchical regressions. Namely, child age, hazardous drug use,
hazardous alcohol use and food insecurity.
Individual level factors increased the odds of whoonga use such child age, hazardous
drug use, and hazardous alcohol. The reported odds of self-reported whoonga use or known use
were OR:1.22 (95% CI, 1.03 - 1.43) among adolescents that were older. The odds of whoonga
use were OR: 1.80 (95% CI, 1.05 - 3.09) higher among adolescents that reported hazardous
alcohol use and were OR:1.62 (95% CI, 1.02 - 2.59) higher among adolescents that reported
hazardous drug use. Food insecurity appears to have a slightly protective effect on whoonga use

9
or reports of use among people adolescents knew OR: 0.649 (95% CI, 0.541 - 0.779). Ideally, in
other studies we could see if these relationships are more pronounced and if the directionality
holds within a data set with a larger sample of whoonga users.
4 Discussion
Our findings highlight that there are multilevel factors that influence whoonga use among
adolescents in South Africa. Individual level risk behaviors such as drug and alcohol use slightly
increased the odds of whoonga use or reports of use among people adolescents knew. This makes
sense as risk for behaviors like substance use or other illicit drug use may be associated with
more risk for whoonga use which adolescents tend to experiment with growing age. These
factors may be suited as targets for future intervention should these relationships be found more
pronounced in larger surveillance studies. Food insecurity as a protective factor for whoonga was
difficult to interpret and would need to be explored further; it is possible that this may relate to
poverty, and the lack of disposable income to purchase whoonga.
With more people starting treatment for HIV and the introduction of PrEP using
emtricitabine-tenofovir disoproxil fumarate, the undeniable growth in ART use highlights the
urgency to determine the magnitude of the public health problem posed by whoonga. Should this
drug phenomenon continue to emerge it may gain traction given the widespread availability of
ARVs in South Africa. Future surveillance studies are needed to track whoonga use. Specifically,
we need to more effectively characterize this emerging illicit drug phenomenon by developing
psychometrically validated measures to capture frequency of use and administration modality.
Second, we need to develop methods to examine the chemical composition of whoonga. Third,
this phenomenon needs to be tracked starting early in the life course during adolescence to
determine if and how it may affect an ART referral, use and adherence, and to support

10
prevention efforts for substance use among adolescents. Use of ART as a lifesaving drug should
not waver. However, our results indicate that further study of this emerging substance of abuse is
vital as countries transition for the use of ART for treatment to ART for prevention in regards to
drug supply as well as risk for drug resistance.
These findings have a few notable limitations. This sample may be less representative of
the overall adolescent population in South Africa given the elevated levels of depression that
adolescents were recruited in this study. Overall, our sample size for whoonga use was small, as
such our r-squared measures should only be interpreted as pseudo R-squared. Nonetheless, we
feel this data is of value in identifying emergent trends in adolescent substance use.
5 Conclusion
Larger epidemiologic studies should expand upon the surveillance of substance use,
specifically for recreational use of prescription medication. Granular data is warranted to
characterize the patters of use, especially among highly vulnerable populations like adolescents.
Expanding surveillance on this category of drug will allow us to track patterns of use for
whoonga and other meaningful proxies that may not typically be captured in surveillance studies
beyond food insecurity, hazardous drinking such as social/familial support. Surveillance studies
that are powered to further explore these multi-level relationships are warranted to further
understand this phenomenon among teens in South Africa.
Role of Funding Sources:
This research was supported by the National Institutes of Health, award number
(K01MH096646) of which Caroline Kuo is the lead investigator . This publication was
additionally supported by the Population Studies and Training Center at Brown University
through the Eunice Kennedy Shriver National Institute of Child Health and Human
Development, award number (P2C HD041020 and T32 HD007338). There are no other
disclosures to report.

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Contributors:
Teresa DeAtley was the lead writer on this publication and was responsible for the analysis. Dr.
Caroline Kuo is the senior author and supervised all steps of the analysis and writing. Drs.
Catherine Mathews, Dan J. Stein, David Grelotti, Larry K. Brown, Millicent Atujuna, William
Beardslee and Ms. Danielle Giovenco, were coauthors that provided meaningful input and
revisions throughout the publication preparation.
Conflict of Interest:
All authors report no conflicts of interest.
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Table 1
Anova and chi-squared test for associations
DV
IV
P-value
Baseline Child Whoonga use
Child age
0.007*
AUDIT
0.000*
DUDIT
0.000*
CESDD
0.100
CONDUCT
0.255
Parental Monitoring subscale
0.469
Parental Monitoring Solicitation subscale
0.280
Parental Monitoring Control subscale
0.899
Parental Monitoring Disclosure subscale
0.028*
Connor Davidson-Resilience Scale
0.728
Parent Adolescent Communication Scale – Problems
0.302
Parent Adolescent Communication Scale – Openness
0.019*
Any lifetime sex
0.000*
Exposure to community violence
0.320
Food Insecurity Index
0.000*
*p value less than .05

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Table 2
Hierarchical Regression for Adolescent Whoonga use
Variables
Model 1
Model 2
Model 3
β
95 % CI
P value
β
95% CI
P value
β
95% CI
P value
Individual Level
Low
High
Low
High
Low
High
Child Age
1.19
1.01
1.40
.039*
1.12
1.01
1.42
0.037*
1.22
1.03
1.43
0.019*
AUDIT
1.87
1.06
3.27
.029*
1.77
1.01
3.11
0.046*
1.80
1.05
3.09
0.032*
DUDIT
1.70
1.07
2.70
.025*
1.61
0.99
2.63
0.053
1.62
1.02
2.58
0.040*
Relational Level
PMQ
(Disclosure subscale)
.999
.980
1.02
0.935
.999
.981
1.02
0.999
PACS
(Openness subscale)
.805
.660
.982
0.032*
.842
.696
2.76
0.075
Any lifetime sex
.997
.966
1.03
0.874
.997
.967
1.03
0.838
Community Level
Food Insecurity
.649
.541
.779
0.000*
Adjusted R squared
.105
.131
.226
*p value less than .05

15
Highlights
Adolescents are reporting exposure and use of off label use of ARV medication in
combination with other substances in South Africa
Individual level risk factors increase risk for Whoonga use or known use among
adolescents
Food insecurity has a slightly protective effect on Whoonga use or known use among
adolescents
Surveillance studies are warranted to explore the multilevel factors that influence
Whoonga use among adolescents

16
Author Contributions:
Teresa DeAtley: Formal Analysis, Conceptualization, Methodology, Writing–Original Draft; Dr.
Caroline Kuo: Funding acquisition, Conceptualization, Methodology, Supervision, Writing –
Review & Editing, Resources, Validation. Catherine Mathews: Writing –Review & Editing, Dan
J. Stein: Writing –Review & Editing; David Grelotti: Writing –Review & Editing; Larry K.
Brown: Writing –Review & Editing; Danielle Giovenco: Writing –Review & Editing; Millicent
Atujuna: Writing –Review & Editing; William Beardslee: Writing –Review & Editing.