The successful expansion of effective antiretroviral therapy (ART) has changed the pediatric HIV epidemic from a fatal disease to a chronic illness, with a growing perinatally HIV-infected population surviving to adolescence and beyond.1 In 2017, there were an estimated 1.8 million adolescents (10–19 years old) living with HIV (ALHIV) worldwide, of whom 150,000 were in the Asia-Pacific region.2 With many having taken ART and been in contact with the health care system since early childhood, their continued care and, where appropriate, their successful transition from pediatric to adult HIV care pose particular challenges.3,4
ALHIV have higher loss to follow-up rates than other age groups, with those aged 15–19 years at higher risk.5–7 ALHIV often have lower virologic suppression rates than adults, and worse treatment and clinical outcomes.8–10 Adherence in this cohort is often suboptimal, and has been found to be influenced by a number of sociodemographic, environmental, and behavioral factors including older age, living situation, disclosure, stigma, comorbid mental health conditions, and substance use.11–14 ALHIV are notable exceptions to declining AIDS-related deaths,15 and they remain underserved in HIV-epidemic responses.16
To better understand and address the challenges associated with the care of ALHIV in Asia, improved understanding of their HIV risk behaviors, ART adherence, and stigma and violence exposures are required. However, the data that are available tend to be cross-sectional, of limited geographical scope, or without comparison to uninfected controls. In addition, previous studies have raised concerns around the reliability of self-reported risk behaviors and adherence data from adolescents, and have highlighted the use of an audio computer-assisted self-interview (ACASI) tool to reduce social desirability bias.17–19 We, therefore, conducted a longitudinal study of adherence and behavioral risk factors among ALHIV and HIV-uninfected adolescents in Asia using an ACASI tool, and conducted an analysis of factors associated with poor virologic control in ALHIV.
Study Design and Study Population
We conducted a prospective, observational cohort study among ALHIV followed in the TREAT Asia Pediatric HIV Observational Database (TApHOD), a regional cohort study of IeDEA Asia-Pacific, and matched HIV-uninfected control adolescents. Nine HIV treatment sites participated in Malaysia (N = 3), Thailand (N = 4), and Vietnam (N = 2). HIV-uninfected controls were recruited from other clinics colocated at participating sites or through the sites' outreach services. ALHIV and uninfected adolescents between the ages of 12 and 18 years were eligible for enrollment, and ALHIV had to know their HIV status to participate. ALHIV were matched to the uninfected adolescents by sex and age in a ratio of 4:1. Study participants completed the study-specific ACASI questionnaire at week 0 (baseline), 48, 96, and 144 study visits. Enrolled participants who completed the ACASI week 0, 48, 96, and/or 144 questionnaires and had an available viral load (VL) within 6 months of that visit were included in the virologic control analysis. The undetectable VL by site cutoff was <40 copies/mL in Thailand and Malaysia and <300 copies/mL in Vietnam.
The study-specific ACASI was based on a version created for the US NIH Pediatric HIV/AIDS Cohort Study Adolescent Master Protocol, with permission,20 and previously piloted in Asian patients.21 The final ACASI included a maximum of 84 questions on general demographics (sex, age, education level, cohabitation and orphan status, and employment status), sexual behavior (access to sex education information, frequency of sex, number of sexual partners, condom use, status disclosure to sexual partner, and sexually transmitted infection symptoms or diagnosis), substance use (alcohol, cigarettes, and other substances), and violence (physical and sexual), with additional questions for ALHIV on adherence to ART, stigma, and disclosure of status beyond primary caregivers. Adherence to ART was self-reported on a 0–100 scale over the past month (0 = not taking any medicines and 100 = taking medicines every day). The ACASI was developed in English, and then translated into local languages (Malay, Thai, and Vietnamese). For ALHIV, data on their treatment history (ART regimen, duration on ART, and age at ART initiation) and other HIV clinical information (CD4 cell count/percentage and WHO stage) were collected from the primary TApHOD cohort study, for which the methods of data collection have previously been described.22
Participants completed the anonymous ACASI questionnaire on a tablet computer in a private area, and study staff were available to answer questions during the session. As part of the consent process, participants were informed that questions about violence would be included, which they had the option to refuse to answer. An automatic alert notification informed study staff if a participant responded that violence had been experienced. After completing the ACASI, the participant handed the tablet back to the study staff who checked for violence notifications before closing the individual session. This triggered a discussion between site staff and the individual adolescent after completion of the ACASI, to determine the nature and seriousness of the violence, and organize follow-up assessment and management, as needed and in line with the hospital's violence and abuse management protocols. ACASI response files were electronically transferred in real time or at regular intervals to the data team at the study management center for cleaning and analysis.23
The sample size of the control group was determined based on the pilot phase of the study, where 11% of ALHIV and 48% of HIV-uninfected adolescents had initiated sexual activity.21 Enrolling 60 HIV-uninfected controls for 250 ALHIV would provide over 95% power to detect this difference in risk behaviors between the 2 groups, at a 2-sided significance level of 5%. Demographic, substance use, violence, sexual behavior, and sexually transmitted infection data of ALHIV and uninfected adolescents at study visits were summarized by descriptive statistics. Continuous data were presented using medians, interquartile ranges (IQRs), and proportions as appropriate.
Changes in continuous and categorical variables over follow-up were compared within and between groups using generalized estimating equations. For the virologic control analysis, patient data were censored at the last available follow-up visit or if they met failure criteria (VL >1000 copies/mL). Generalized estimating equation using a logit link and an exchangeable correlation matrix were used to identify independent predictors for virologic failure (VF). Predictor covariates were adjusted for in a multivariate model if P was <0.2 in univariate models. A backward stepwise selection method with the likelihood ratio test was used for variable selection in the multivariate analysis, and at each step, the variable with the highest P value was deleted from the subsequent model until all remaining terms were significant at P <0.25. A P value of <0.05 was considered statistically significant. The linearity of continuous covariates (eg, age) against the logit was checked; in the case of nonlinearity, the covariate was modeled in quartiles.
Data management and statistical analyses were performed using SAS 9.4 (SAS Institute, Inc, Cary, NC) and Stata 14 (Stata Corp, College Station, TX), respectively.
All participating study sites and the study coordinating centers (HIV-NAT, Thai Red Cross AIDS Research Centre, Thailand; TREAT Asia, amfAR/The Foundation for AIDS Research, Thailand) obtained institutional review board (IRB) approvals for study participation. Caregivers for patients younger than 18 years and patients aged 18 years or older were asked to give consent; those younger than 18 years were asked to provide assent when this was required by the local site IRB.
Between July 2013 and March 2014, 250 ALHIV and 59 HIV-uninfected age and sex-matched controls were enrolled. Of the ALHIV, 59% were Thai, 24% Vietnamese, and 17% Malaysian; 49% were males and the median age was 14 years (IQR: 13–16) (Table 1). Patients were followed up until March 2017. The median ages of both groups by week 144 were 17 years.
The proportion of ALHIV and HIV-uninfected controls currently in school decreased over the course of the study from 93% to 75% (P < 0.01), and 95% to 91% (P = 0.49), respectively. The proportion of ALHIV currently studying was significantly lower than uninfected controls (P = 0.03). The proportion currently working to support themselves increased from 18% to 33% for ALHIV (P < 0.01), and 10% to 30% for controls (P = 0.02). The proportion of double or single orphans among ALHIV increased over time so that by week 144, 66% of ALHIV were orphans compared with 28% of HIV-uninfected controls (P < 0.01). By week 144, 23% of ALHIV lived with both biological parents compared with 47% of HIV-uninfected controls, and 33% of ALHIV lived with nonparent relatives compared with 12% of controls (P < 0.01).
The proportions of ALHIV and HIV-uninfected controls reporting ever having drunk alcohol increased from week 0 to 144 from 32% to 58% (P < 0.01) and 42% to 65% (P < 0.01), respectively (Table 2). The proportions reporting ever having smoked cigarettes increased from 10% to 28% (P < 0.01), and 17% to 30% (P = 0.02), respectively. The proportions reporting smoking cigarettes in the past 3 months increased from 4% to 12% (P < 0.01) and 8% to 16% (P = 0.05), respectively. There were no significant differences in alcohol or cigarette use between ALHIV participants and controls. Small proportions of both groups reported ever using other drugs.
The proportions of ALHIV and uninfected adolescents ever reporting receiving information on sex education increased from 74% to 91% (P < 0.01) and 75% to 91% (P < 0.01) from week 0 to 144 (Table 2). The most common sources of information on sexual education for both groups were school (particularly for uninfected adolescents), health care professionals (particularly for ALHIV), and other sources (eg, video, television, and Internet). The proportions of ALHIV receiving sexual education from school were significantly lower (P = 0.01) and from health care professionals significantly higher (P < 0.001), compared with uninfected adolescents. The proportions of ALHIV and uninfected adolescents reporting ever having sexual intercourse increased from 10% to 31% (P < 0.01) and 17% to 21% (P < 0.01), respectively. The proportions of sexually active ALHIV and uninfected adolescents reporting always using a condom during sexual activity increased from 27% to 42% (P = 0.62) and from 20% to 44% (P = 0.44), respectively, between week 0 and 144. Few participants reported same sex male relationships (<3%) or unsafe sex after using illegal drugs or alcohol (<3%). The proportion of ALHIV reporting the age at first sexual intercourse <15 years was significantly lower than controls (P < 0.01).
The proportion of ALHIV and uninfected adolescents reporting ever being physically hurt by family, friends, or teachers increased from 46% to 59% (P < 0.01) and 49% to 63% (P < 0.01), respectively, over the duration of the study (Table 2). The proportion of ALHIV reporting ever been physically hurt was significantly lower than controls (P < 0.01). The proportion of ALHIV reporting being physically hurt in the past 6 months fell from 24% at week 0 to 3% at week 144 (P = 0.04), and for uninfected adolescents, from 14% to 5% (P = 0.49). The proportion of either group reporting being forced to have some form of sexual interaction remained <3% throughout.
Clinical Characteristics of ALHIV
Almost all ALHIV (93%) acquired HIV through perinatal exposure, with 1% through blood products or sexual abuse, and 6% through unknown sources (see Table, Supplemental Digital Content 1, http://links.lww.com/QAI/B289, which describes the clinical characteristics of ALHIV study participants). The median age at ART initiation was 7 years (IQR 4–10). The median duration on ART was 10 years (IQR 8–13) at week 144. The median CD4 cell count was 217 cells/mm3 (IQR 77–548) at ART initiation, 676 cells/mm3 (IQR 484–884) at enrollment, and 600 cell/mm3 (IQR 482–795) at week 144 (P < 0.01). The proportion that had VL testing was 78% at week 0 and 73% at week 144. The median log VL was 1.60 (IQR 1.30–2.04) copies/mL at week 0 and 1.60 (IQR 1.30–1.70) copies/mL at week 144. The proportion of ALHIV with VL >1000 copies/mL was 14% at week 0 and 17% at week 144 (P = 0.41). The proportion with an undetectable VL by site cutoff was 72% at week 0 and 73% at week 144 (P = 0.36). The proportion with VL <400 copies/mL was 83% at week 0 and 81% at week 144 (P = 0.36).
By week 144, most ALHIV (73%) did not report telling anyone else about their HIV status; 25% informed their relatives, 12% told a relationship partner, and 10% told a friend (see Table, Supplemental Digital Content 2, http://links.lww.com/QAI/B289). Of those whose partner knew their status by week 144, 81% felt relieved or better after telling them. Although there was an increasing trend of people wanting to disclose to their partner over follow-up (P < 0.001), of those who had not disclosed their HIV status to their partner by week 144, only 38% still wanted to tell them.
Throughout the duration of the study, the proportion of ALHIV indicating that their body or appearance should be better, that they do not like themselves, or that they hate themselves remained relatively stable at around 18% (see Table, Supplemental Digital Content 2, http://links.lww.com/QAI/B289). The proportions of ALHIV reporting ever been teased by other people increased from 22% at week 0 to 36% at week 144 (P < 0.01). The proportions of ALHIV reporting perceiving problems living in their neighborhood (7% to 5%), going to school (9% to 8%), or living with their family (8% to 6%) because of their HIV infection remained stable.
The proportion of ALHIV reporting adherence ≥95% fell from 69% at week 0 to 60% at week 144 (P = 0.002) (see Table, Supplemental Digital Content 3, http://links.lww.com/QAI/B289). The proportion reporting difficulties taking antiretroviral medicines on a daily basis decreased from 38% at enrollment to 32% at week 144 (P = 0.16). Of those reporting difficulties, the most common reasons across the duration of the study were boredom (30%–42%), inconvenient time (29%–35%), number of pills (22%–30%), and size of pills (18%–27%). The most common reminder methods to take antiretroviral medications were to watch the clock (74%–79%), setting an alarm (48%–63%), and caregiver reminders (49%–55%).
Risk Factors for Poor Virologic Control
In multivariate analysis, the following were associated with increased odds of VF at all time points (Table 3): (1) living with nonparent relatives [odds ratio (OR) 2.20 vs. living with both parents; 95% confidence interval (CI): 1.03 to 4.71], (2) living with a partner (OR 5.55 vs. living with both parents; 95% CI: 1.00 to 30.85), (3) living on your own (OR 16.77 vs. living with both parents; 95% CI: 1.67 to 168.48), (4) ever smoking cigarettes (OR 2.26; 95% CI: 1.21 to 4.24), (5) having more than one sexual partner in the past 3 months (OR 5.08 vs. one sexual partner in the past 3 months; 95% CI: 1.39 to 18.61), and (6) reporting that the taste of antiretroviral medicines was a challenge to taking daily ART (OR 2.50; 95% CI: 1.08 to 5.81).
Factors associated with decreased odds of VF were: (1) higher CD4 counts [compared to those with CD4 count <500 cells/mm3, the OR (95% CI) for VF with CD4 counts of 500–650 cells/mm3, and ≥650 cells/mm3 were 0.24 (95% CI: 0.13 to 0.46) and 0.07 (95% CI: 0.04 to 0.15), respectively], and (2) nonnucleoside reverse transcriptase inhibitor–based ART (OR 0.21 vs. protease inhibitor–based ART; 95% CI: 0.10 to 0.43).
Across 3 years of longitudinal follow-up, we found minimal differences in risk behaviors between predominantly perinatally infected ALHIV and uninfected controls in this Southeast Asian cohort.
Although substance use rates were lower among ALHIV study participants, our findings are consistent with the limited number of studies comparing youth with and without HIV between 9 and 18 years old, which have reported that HIV infection was not by itself a risk factor for substance use.24–26 Smoking, alcohol, or illicit drug use rates among our ALHIV study population are consistent with other studies in the region but lower than rates reported among youth in Western cohorts.24,27,28 Our findings reflect those of other studies documenting equivalent or lower levels of sexual risk behavior among ALHIV compared with uninfected adolescents.11,29,30 In contrast to other studies in the region, we found infrequent reporting of sexual risk behavior associated with substance use.28,31 Given the risk of onward HIV transmission, the relatively low level of consistent condom use among our ALHIV study population is concerning and suggests that although ALHIV in our study had good access to sex education information, it has had a limited impact on risk reduction.
Our finding of lower violence exposure among ALHIV contrasts with lower levels of violence exposure reported among uninfected adolescent populations elsewhere.32–34 Violence exposure levels among ALHIV in our study are similar to those reported in other ALHIV populations.35 Early exposure to violence is of particular concern given the documented impacts among other populations living with HIV,36,37 further highlighting the need to promote awareness and engagement around the effects of violence, and the availability of support. Despite access to information and clinical care services, a high proportion of our ALHIV study population did not want to disclose their HIV status across the duration of the study. Many ALHIV reported feeling nervous about sharing this information with others, including among those in a relationship who feared that their partner would leave them after disclosing their status. Enhanced disclosure support should be part of routine HIV patient education from early adolescence onward to address these issues.
The proportion of ALHIV study participants reporting not liking themselves, or problems in their community or family because of their HIV status, suggests levels of internal stigma (the shame and expectation of discrimination that prevents people from talking about their experiences and stops them seeking help), and enacted stigma (the experience of unfair treatment by others),38 similar to those reported among ALHIV in other resource-limited settings.36 These responses did not decline substantially over time, highlighting the need for interventions that can increase their ability to combat negative societal influences,39 particularly given the associations between stigma, mental health, and service uptake and retention.40–42
Adherence levels in our cohort were consistent with those reported among ALHIV populations elsewhere,43,44 and the main barriers to adherence in our cohort (eg, boredom) complement those reported in other cohorts.45,46 The declining and suboptimal adherence levels in our cohort occurred despite ALHIV receiving care in relatively well-resourced tertiary care centers with the ability to provide individualized counseling and follow-up. As has been observed in high-income country settings, reasons behind adolescent treatment interruptions and defaults are complex. ALHIV are experiencing substantial maturational and neurocognitive development, and coping with the impact of stigma and chronic disease, often without parents or stable adult caregivers to guide them.47 ALHIV providers need more comprehensive tools, including mental health screening and treatment options, to better identify and address causes of poor adherence.
At the same time, with over 70% of the ALHIV tested having an undetectable VL at the start and end of our study, virologic suppression rates were comparable or higher than those reported in other ALHIV cohorts in Africa and North America.48–50 While somewhat surprising given increasing VF rates observed as similar cohorts aged,51 the stable VF rate in our cohort may be attributed to a combination of factors, including strong relationships between patients, caregivers, and families in our network. Because the median age at the end of follow-up was 17 years, we may have also missed a high-risk period in older adolescence when virologic suppression has been observed to decline. The stable viral suppression, despite decreasing adherence we observed, may be explained by the much steeper decline in adherence ≥95% among those without an available VL, than those with. Although the association between lower CD4 count and VF we observed has been consistently identified in previous pediatric studies,49,52 those related to cigarette smoking and sexual risk behavior are specific to older adolescent and adult populations.45,53–55
Our study found the odds of VF in ALHIV living with nonparent relatives was more than 2 times greater, more than 5 times greater in those living with a partner, and more than 16 times greater in those living on their own, compared with those living with both parents. In a prior study of our broader ALHIV cohort, having biological parents as the primary caregiver was associated with a reduced risk of postsuppression virologic rebound,56 and a study among ALHIV in Botswana found the absence of a parent from clinic visits was strongly associated with VF.57 The effect of caregiver status on virologic suppression is influenced by multiple factors, including caregiver sociodemographics, health status, substance use, and caregiving style.50,58–61 Much of this effect may be exerted through improved adherence to ART, with other studies reporting an association between high levels of adherence and a biological parent caregiver.12,14,62,63 The influence of caregiver status on adherence and virologic suppression highlights the importance of earlier education and intervention efforts, targeting children, caregivers, and families before adolescence, to reduce communication barriers and improve collaboration for ongoing health.64
We also examined data by VL availability and found no substantial differences in demographic, clinical, and risk behavior or exposure between those with VL testing and those without. Study findings should however be interpreted in the context of multiple limitations. Most cohort centers are urban referral centers, so our findings may not be generalizable to other adolescent HIV care settings in Asia. Although minimized through the use of ACASI, social desirability may still influence adolescent reporting of risk behaviors and adherence. Fear is another potential reason for intentional nonresponse about sensitive issues such as sex and violence. Notably, our definitions and measurement of violence and stigma experiences were not from standardized and validated tools, limiting the interpretation of those data. In addition, 28% of HIV-uninfected controls were lost to follow-up by week 144.
Overall, our study highlights a need for targeted interventions that focus on ALHIV's unique health needs and social circumstances that integrate prevention messages around sexual risk, substance use (including alcohol), and HIV transmission, and that address exposure to stigma and violence. There is a subset of ALHIV in Asia with substantial behavioral risk behaviors and poorer adherence who are at higher risk of VF, for whom efforts to improve adherence and retention must be enhanced. This may require support services that are beyond the usual scope of HIV care that can address mental health and social vulnerabilities related to HIV.
The authors are grateful to the study participants and all site staff for their commitment to the study.
The TREAT Asia Pediatric HIV Observational Database using an Audio Computer-Assisted Self-Interview (TApHOD ACASI) Study Group: W Prasitsuebsai, K Pruksakaew, S Kerr, and S Thammasala, The HIV Netherlands Australia Thailand Research Collaboration (HIV-NAT), The Thai Red Cross AIDS Research Centre, Bangkok, Thailand; P Lumbiganon, P Kosalaraksa, and P Tharnprisan, Faculty of Medicine, Srinagarind Hospital, Khon Kaen University, Khon Kaen, Thailand; R Hansudewechakul, S Denjanta, A Kongphonoi, and W Srisuk, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand; K Chokephaibulkit, S Sricharoenchai, Y Durier, and S Kanakool, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand; KH Truong, QT Du, and HD Tran, TKP Le Children's Hospital 1, Ho Chi Minh City, Vietnam; LV Nguyen, DTK Khu, GTT Thuy, and LT Nguyen, National Hospital of Pediatrics, Hanoi, Vietnam; KA Razali, TJ Mohamed, and NADR Mohammed, Pediatric Institute, Hospital Kuala Lumpur, Kuala Lumpur, Malaysia; Hospital Raja Perempuan Zainab II, Kelantan, Malaysia; SM Fong, KJ Wong, and F Daut, Hospital Likas, Kota Kinabalu, Malaysia; NK Nik Yusoff, and P Mohamad, AH Sohn, JL Ross, and C Sethaputra, TREAT Asia/amfAR—The Foundation for AIDS Research, Bangkok, Thailand.
1. Mofenson LM, Cotton MF. The challenges of success: adolescents
with perinatal HIV
infection. J Int AIDS Soc. 2013;16:18650.
2. UNAIDS. UNAIDS Indicators 2017. Available at: http://aidsinfo.unaids.org/
. Accessed September 20, 2018.
3. Bailey H, Cruz MLS, Songtaweesin WN, et al. Adolescents
and transition to adult care in the Caribbean, Central America and South America, Eastern Europe and Asia and Pacific regions. J Int AIDS Soc. 2017;20(suppl 3):21475.
4. Tepper V, Zaner S, Ryscavage P. HIV
healthcare transition outcomes among youth in North America and Europe: a review. J Int AIDS Soc. 2017;20(suppl 3):21490.
5. Kranzer K, Bradley J, Musaazi J, et al. Loss to follow-up among children and adolescents
growing up with HIV
infection: age really matters. J Int AIDS Soc. 2017;20:21737.
6. Hansudewechakul R, Pongprapass S, Kongphonoi A, et al. Transition of Thai HIV
to adult HIV
care. J Int AIDS Soc. 2015;18:20651.
7. Murray KR, Dulli LS, Ridgeway K, et al. Improving retention in HIV
care among adolescents
and adults in low- and middle-income countries: a systematic review of the literature. PLoS One. 2017;12:e0184879.
8. Ryscavage P, Anderson EJ, Sutton SH, et al. Clinical outcomes of adolescents
and young adults in adult HIV
care. J Acquir Immune Defic Syndr. 2011;58:193–197.
9. Agwu AL, Fairlie L. Antiretroviral treatment, management challenges and outcomes in perinatally HIV
. J Int AIDS Soc. 2013;16:18579.
10. Ferrand RA, Briggs D, Ferguson J, et al. Viral suppression in adolescents
on antiretroviral treatment: review of the literature and critical appraisal of methodological challenges. Trop Med Int Health. 2016;21:325–333.
11. Mellins CA, Tassiopoulos K, Malee K, et al. Behavioral health risks in perinatally HIV
-exposed youth: co-occurrence of sexual and drug use behavior, mental health problems, and nonadherence to antiretroviral treatment. AIDS Patient Care STDS. 2011;25:413–422.
12. Mutwa PR, Van Nuil JI, Asiimwe-Kateera B, et al. Living situation affects adherence
to combination antiretroviral therapy in HIV
in Rwanda: a qualitative study. PLoS One. 2013;8:e60073.
13. Calabrese SK, Martin S, Wolters PL, et al. Diagnosis disclosure, medication hiding, and medical functioning among perinatally infected, HIV
-positive children and adolescents
. AIDS Care. 2012;24:1092–1096.
14. Xu L, Munir K, Kanabkaew C, et al. Factors influencing antiretroviral treatment suboptimal adherence
among perinatally HIV
in Thailand. PLoS One. 2017;12:e0172392.
15. Progress for Children: Beyond Averages. Learning from the MDGs. New York, NY: UNICEF, Division of Communication; 2015.
16. Bernays S, Jarrett P, Kranzer K, et al. Children growing up with HIV
infection: the responsibility of success. Lancet. 2014;383:1355–1357.
17. Phillips AE, Gomez GB, Boily MC, et al. A systematic review and meta-analysis of quantitative interviewing tools to investigate self-reported HIV
and STI associated behaviours in low- and middle-income countries. Int J Epidemiol. 2010;39:1541–1555.
18. Dolezal C, Marhefka SL, Santamaria EK, et al. A comparison of audio computer-assisted self-interviews to face-to-face interviews of sexual behavior among perinatally HIV
-exposed youth. Arch Sex Behav. 2012;41:401–410.
19. Islam MM, Topp L, Conigrave KM, et al. The reliability of sensitive information provided by injecting drug users in a clinical setting: clinician-administered versus audio computer-assisted self-interviewing (ACASI). AIDS Care. 2012;24:1496–1503.
20. Mellins CA, Tassiopoulos K, Malee KM, et al. Risk behavior in perinatally HIV
-infected youth: co-morbidity of mental health problems, sexual and drug use behavior, and non-adherence
to antiretroviral therapy. XVIII International AIDS Conference, Vienna, Austria, July 18–23, 2010. Abstract no. WEAD0303.
21. Prasitsuebsai W, Pang J, Hansudewechakul R, et al. Risk behaviors and treatment adherence
in the TREAT Asia pediatric HIV
observational database. Presented at the International Workshop on HIV
Pediatrics, abstract P_18. 2012.
22. Kariminia A, Chokephaibulkit K, Pang J, et al. Cohort profile: the TREAT Asia pediatric HIV
observational database. Int J Epidemiol. 2011;40:15–24.
23. Prasitsuebsai W, Sethaputra C, Lumbiganon P, et al. Adherence
to antiretroviral therapy, stigma
and behavioral risk
factors in HIV
in Asia. AIDS Care. 2018;30:727–733.
24. Alperen J, Brummel S, Tassiopoulos K, et al. Prevalence of and risk factors for substance use among perinatally human immunodeficiency virus-infected and perinatally exposed but uninfected youth. J Adolesc Health. 2014;54:341–349.
25. Elkington KS, Bauermeister JA, Brackis-Cott E, et al. Substance use and sexual risk behaviors in perinatally human immunodeficiency virus-exposed youth: roles of caregivers, peers and HIV
status. J Adolesc Health. 2009;45:133–141.
26. Williams PL, Leister E, Chernoff M, et al. Substance use and its association with psychiatric symptoms in perinatally HIV
-infected and HIV
. AIDS Behav. 2010;14:1072–1082.
27. Lolekha R, Boon-Yasidhi V, Leowsrisook P, et al. Knowledge, attitudes, and practices regarding antiretroviral management, reproductive health, sexually transmitted infections, and sexual risk behavior among perinatally HIV
-infected youth in Thailand. AIDS Care. 2015;27:618–628.
28. Gamarel KE, Brown L, Kahler CW, et al. Prevalence and correlates of substance use among youth living with HIV
in clinical settings. Drug Alcohol Depend. 2016;169:11–18.
29. Elkington KS, Bauermeister JA, Robbins RN, et al. Individual and contextual factors of sexual risk behavior in youth perinatally infected with HIV
. AIDS Patient Care STDS. 2012;26:411–422.
30. Bauermeister JA, Elkington KS, Robbins RN, et al. A prospective study of the onset of sexual behavior and sexual risk in youth perinatally infected with HIV
. J Sex Res. 2012;49:413–422.
31. Duong CT, Nguyen TH, Hoang TT, et al. Sexual risk and bridging behaviors among young people in Hai Phong, Vietnam. AIDS Behav. 2008;12:643–651.
32. Nguyen HT, Dunne MP, Le AV. Multiple types of child maltreatment and adolescent mental health in Viet Nam. Bull World Health Organ. 2010;88:22–30.
33. Choo WY, Dunne MP, Marret MJ, et al. Victimization experiences of adolescents
in Malaysia. J Adolesc Health. 2011;49:627–634.
34. Meinck F, Cluver LD, Boyes ME, et al. Risk and protective factors for physical and sexual abuse of children and adolescents
in Africa: a review and implications for practice. Trauma Violence Abuse. 2015;16:81–107.
35. Martinez J, Hosek SG, Carleton RA. Screening and assessing violence and mental health disorders in a cohort of inner city HIV
-positive youth between 1998-2006. AIDS Patient Care STDS. 2009;23:469–475.
36. Pantelic M, Boyes M, Cluver L, et al. HIV
, violence, blame and shame: pathways of risk to internalized HIV stigma
among South African adolescents
living with HIV
. J Int AIDS Soc. 2017;20:21771.
37. Norman RE, Byambaa M, De R, et al. The long-term health consequences of child physical abuse, emotional abuse, and neglect: a systematic review and meta-analysis. PLoS Med. 2012;9:e1001349.
38. Gray AJ. Stigma
in psychiatry. J R Soc Med. 2002;95:72–76.
39. Harper GW, Lemos D, Hosek SG. Stigma
reduction in adolescents
and young adults newly diagnosed with HIV
: findings from the Project ACCEPT intervention. AIDS Patient Care STDS. 2014;28:543–554.
40. Tanney MR, Naar-King S, MacDonnel K. Depression and stigma
in high-risk youth living with HIV
: a multi-site study. J Pediatr Health Care. 2012;26:300–305.
41. Rueda S, Mitra S, Chen S, et al. Examining the associations between HIV
and health outcomes in people living with HIV
/AIDS: a series of meta-analyses. BMJ Open. 2016;6:e011453.
42. Stangl AL, Lloyd JK, Brady LM, et al. A systematic review of interventions to reduce HIV
and discrimination from 2002 to 2013: how far have we come? J Int AIDS Soc. 2013;16(3 suppl 2):18734.
43. Kim SH, Gerver SM, Fidler S, et al. Adherence
to antiretroviral therapy in adolescents
living with HIV
: systematic review and meta-analysis. AIDS. 2014;28:1945–1956.
44. Côté J, Delmas P, de Menezes Succi RC, et al. Predictors and evolution of antiretroviral therapy adherence
among perinatally HIV
in Brazil. J Adolesc Health. 2016;59:305–310.
45. MacDonell K, Naar-King S, Huszti H, et al. Barriers to medication adherence
in behaviorally and perinatally infected youth living with HIV
. AIDS Behav. 2013;17:86–93.
46. Kim MH, Mazenga AC, Yu X, et al. High self-reported non-adherence
to antiretroviral therapy amongst adolescents
living with HIV
in Malawi: barriers and associated factors. J Int AIDS Soc. 2017;20:21437.
47. Huy BV, Teeraananchai S, Oanh LN, et al. Impact of orphan status on HIV
treatment outcomes and retention in care of children and adolescents
in Asia. J Virus Erad. 2016;2:227–231.
48. Kahana SY, Fernandez MI, Wilson PA, et al. Rates and correlates of antiretroviral therapy use and virologic suppression among perinatally and behaviorally HIV
-infected youth linked to care in the United States. J Acquir Immune Defic Syndr. 2015;68:169–177.
49. Jobanputra K, Parker LA, Azih C, et al. Factors associated with virological failure and suppression after enhanced adherence
counselling, in children, adolescents
and adults on antiretroviral therapy for HIV
in Swaziland. PLoS One. 2015;10:e0116144.
50. Fokam J, Billong SC, Jogue F, et al. Immuno-virological response and associated factors amongst HIV
-1 vertically infected adolescents
in Yaoundé-Cameroon. PLoS One. 2017;12:e0187566.
51. Flynn PM, Rudy BJ, Lindsey JC, et al. Long-term observation of adolescents
initiating HAART therapy: three-year follow-up. AIDS Res Hum Retroviruses. 2007;23:1208–1214.
52. Chokephaibulkit K, Kariminia A, Oberdorfer P, et al. Characterizing HIV
manifestations and treatment outcomes of perinatally infected adolescents
in Asia. Pediatr Infect Dis J. 2014;33:291–294.
53. MacDonell KK, Jacques-Tiura AJ, Naar S, et al. Predictors of self-reported adherence
to antiretroviral medication in a multisite study of ethnic and racial minority HIV
-positive youth. J Pediatr Psychol. 2016;41:419–428.
54. Chandwani S, Koenig LJ, Sill AM, et al. Predictors of antiretroviral medication adherence
among a diverse cohort of adolescents
. J Adolesc Health. 2012;51:242–251.
55. Nguyen NT, Tran BX, Hwang LY, et al. Effects of cigarette smoking and nicotine dependence on adherence
to antiretroviral therapy among HIV
-positive patients in Vietnam. AIDS Care. 2016;28:359–364.
56. Sudjaritruk T, Aurpibul L, Ly PS, et al. Incidence of postsuppression virologic rebound in perinatally HIV
-infected Asian adolescents
on stable combination antiretroviral therapy. J Adolesc Health. 2017;61:91–98.
57. Lowenthal ED, Marukutira T, Tshume O, et al. Parental absence from clinic predicts human immunodeficiency virus treatment failure in adolescents
. JAMA Pediatr. 2015;169:498–500.
58. Skovdal M, Campbell C, Madanhire C, et al. Challenges faced by elderly guardians in sustaining the adherence
to antiretroviral therapy in HIV
-infected children in Zimbabwe. AIDS Care. 2011;23:957–964.
59. Cruz ML, Cardoso CA, Darmont MQ, et al. Viral suppression and adherence
-infected children and adolescents
on antiretroviral therapy: results of a multicenter study. J Pediatr (Rio J). 2014;90:563–571.
60. Mellins CA, Brackis-Cott E, Dolezal C, et al. The role of psychosocial and family factors in adherence
to antiretroviral treatment in human immunodeficiency virus-infected children. Pediatr Infect Dis J. 2004;23:1035–1041.
61. Williams PL, Storm D, Montepiedra G, et al. Predictors of adherence
to antiretroviral medications in children and adolescents
infection. Pediatrics. 2006;118:e1745–57.
62. Denison JA, Banda H, Dennis AC, et al. “The sky is the limit”: adhering to antiretroviral therapy and HIV
self-management from the perspectives of adolescents
living with HIV
and their adult caregivers. J Int AIDS Soc. 2015;18:19358.
63. Hudelson C, Cluver L. Factors associated with adherence
to antiretroviral therapy among adolescents
living with HIV
/AIDS in low- and middle-income countries: a systematic review. AIDS Care. 2015;27:805–816.
64. Puthanakit T, Aurpibul L, Louthrenoo O, et al. Poor cognitive functioning of school-aged children in Thailand with perinatally acquired HIV
infection taking antiretroviral therapy. AIDS Patient Care STDS. 2010;24:141–146.