Abstract
Background
Adolescents living with HIV (ALHIV) have poorer adherence and clinical outcomes than adults. We conducted a study to assess behavioral risks and antiretroviral therapy (ART) outcomes among ALHIV in Asia.
Methods
A prospective cohort study among ALHIV and matched HIV-uninfected controls aged 12 to 18 years was conducted at nine sites in Malaysia, Thailand and Vietnam from July 2013-March 2017. Participants completed an audio computer-assisted self-interview at weeks 0, 48, 96 and 144. Virologic failure (VF) was defined as ≥1 viral load (VL) measurement >1000 copies/mL. Generalized estimating equations were used to identify predictors for VF.
Results
Of 250 ALHIV and 59 HIV-uninfected controls, 58% were Thai and 51% female. Median age was 14 years at enrollment; 93% of ALHIV were perinatally infected. At week 144, 66% of ALHIV were orphans vs. 28% of controls (p <0.01); similar proportions of ALHIV and controls drank alcohol (58% vs. 65%), used inhalants (1% vs. 2%), had been sexually active (31% vs. 21%) and consistently used condoms (42% vs. 44%). Of the 73% of ALHIV with week 144 VL testing, median log VL was 1.60 (IQR 1.30-1.70) and 19% had VF. Over 70% of ALHIV had not disclosed their HIV status. Self-reported adherence ≥95% was 60% at week 144. Smoking cigarettes, >1 sexual partner, and living with non-parent relatives, a partner or alone, were associated with VF at any time.
Conclusions
The subset of ALHIV with poorer adherence and VF require comprehensive interventions that address sexual risk, substance use, and HIV-status disclosure.
Keywords: Adolescents, HIV, adherence, behavioral risk, stigma, viral load
Introduction
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 (PHIV) 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 15–19 years of age 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 the notable exception to declining AIDS-related deaths [15], and they remain underserved in HIV epidemic responses [16].
In order 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 tends 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.
Methods
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 co-located at participating sites or through the sites’ outreach services. ALHIV and uninfected adolescents aged between 12 to 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 cut-off was <40 copies/mL in Thailand and Malaysia and <300 copies/mL in Vietnam.
Data collection
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, employment status), sexual behavior (access to sex education information, frequency of sex, number of sexual partners, condom use, status disclosure to sexual partner, STI symptoms or diagnosis), substance use (alcohol, cigarettes, other substances), and violence (physical, 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 last month (0 = not taking any medicines, 100 = taking medicines every day). The ACASI was developed in English, and then translated into local languages (Malay, Thai, Vietnamese). For ALHIV, data on their treatment history (ART regimen, duration on ART, age at ART initiation), and other HIV clinical information (CD4 cell count/percentage, 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 prior to 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].
Statistical considerations
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 two groups, at a two-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 (IQR) and proportions as appropriate.
Changes in continuous and categorical variables over follow-up were compared within and between groups using generalized estimating equations (GEE). 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). GEE using a logit link and an exchangeable correlation matrix were used to identify independent predictors for virologic failure. Predictor covariates were adjusted for in a multivariate model if p was <0.2 in univariate models. A backward stepwise selection method with 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 (e.g., age) against the logit was checked; in the case of non-linearity, the covariate was modelled in quartiles.
Data management and statistical analyses were performed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA) and Stata 14 (Stata Corp, College Station, TX, USA), respectively.
Ethical considerations
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 under 18 years and patients 18 or more years of age were asked to give consent; those under 18 were asked to provide assent when this was required by the local site IRB.
Results
Socio-demographics
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 male and the median age was 14 years (IQR: 13–16) (Table 1). Patients were followed until March 2017. The median ages of both groups by week 144 was 17 years old.
Table 1:
Sociodemographic characteristics of adolescents with and without HIV at weeks 0, 48, 96 and 144
| Arm | ALHIV | HIV-uninfected adolescents | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ACASI visit | Week 0 |
Week 48 |
Week 96 |
Week 144 |
P | Week 0 |
Week 48 |
Week 96 |
Week 144 |
P | PAll |
| N | 250 | 248 | 240 | 231 | 59 | 51 | 46 | 43 | |||
| Country | |||||||||||
| Thailand | 147 (59) | 147 (59) | 140 (58) | 131 (57) | 31 (53) | 24 (47) | 20 (43) | 19 (44) | |||
| Malaysia | 42 (17) | 41 (17) | 40 (17) | 42 (18) | 12 (20) | 11 (22) | 11 (24) | 11 (26) | |||
| Vietnam | 61 (24) | 60 (24) | 60 (25) | 58 (25) | 16 (27) | 16 (31) | 15 (33) | 13 (30) | |||
| Median (IQR) Age at test | 14 (13 - 16) | 16 (14 - 17) | 16 (15 - 18) | 17 (16 - 18) | <0.01 | 14 (13 - 16) | 15 (13 - 17) | 16 (14 - 18) | 17 (15 - 18) | <0.01 | 0.59 |
| Female sex, N (%) | 129 (52) | 129 (52) | 123 (51) | 115 (50) | 0.97 | 29 (49) | 24 (47) | 21 (46) | 20 (47) | 0.97 | 0.07 |
| Education | |||||||||||
| Primary (grades 1-12) | 222 (89) | 194 (78) | 166 (69) | 128 (55) | <0.01 | 52 (88) | 44 (86) | 33 (72) | 29 (67) | <0.01 | 0.26 |
| Vocational/Pre-university | 7 (3) | 18 (7) | 28 (12) | 28 (12) | 4 (7) | 3 (6) | 5 (11) | 4 (9) | |||
| University | 3 (1) | 9 (4) | 10 (4) | 17 (7) | 0 (0) | 3 (6) | 5 (11) | 6 (14) | |||
| Non-school education | 5 (2) | 5 (2) | 3 (1) | 2 (1) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | |||
| Not in school | 13 (5) | 22 (9) | 33 (14) | 56 (24) | 3 (5) | 1 (2) | 3 (7) | 4 (9) | |||
| Currently studying (vs. not) | 232 (93) | 221 (89) | 204 (85) | 173 (75) | <0.01 | 56 (95) | 50 (98) | 43 (93) | 39 (91) | 0.49 | 0.03 |
| Currently working | 46 (18) | 47 (19) | 59 (25) | 77 (33) | <0.01 | 6 (10) | 7 (14) | 5 (11) | 13 (30) | 0.02 | 0.08 |
| Parent status | |||||||||||
| Both alive | 64 (26) | 61 (25) | 61 (25) | 56 (24) | 0.95 | 39 (66) | 30 (59) | 28 (61) | 27 (63) | 0.39 | <0.01 |
| One parent alive* | 99 (40) | 97 (39) | 92 (38) | 92 (40) | 12 (20) | 12 (24) | 10 (22) | 12 (28) | |||
| Both of them died | 54 (22) | 63 (25) | 62 (26) | 61 (26) | 0 (0) | 3 (6) | 4 (9) | 0 (0) | |||
| Unknown | 33 (13) | 27 (11) | 25 (10) | 22 (10) | 8 (14) | 6 (12) | 4 (9) | 4 (9) | |||
| Who do you live with? | 0.21 | 0.18 | <0.01 | ||||||||
| Mother and father | 61 (24) | 64 (26) | 57 (24) | 54 (23) | 35 (59) | 28 (55) | 26 (57) | 20 (47) | |||
| Mother or father | 61 (24) | 66 (27) | 59 (25) | 60 (26) | 8 (14) | 7 (14) | 6 (13) | 11 (26) | |||
| Relatives, not parents | 93 (37) | 80 (32) | 83 (35) | 77 (33) | 7 (12) | 7 (14) | 6 (13) | 5 (12) | |||
| Foster family | 10 (4) | 9 (4) | 13 (5) | 12 (5) | 3 (5) | 1 (2) | 2 (4) | 1 (2) | |||
| Shelter home | 24 (10) | 23 (9) | 19 (8) | 18 (8) | 5 (8) | 6 (12) | 4 (9) | 3 (7) | |||
| Partner | 1 (0) | 3 (1) | 6 (3) | 7 (3) | 1 (2) | 1 (2) | 2 (4) | 2 (5) | |||
| On my own | 0 (0) | 3 (1) | 3 (1) | 3 (1) | 0 (0) | 1 (2) | 0 (0) | 1 (2) | |||
ALHIV: Adolescents living with HIV; ACASI: audio computer-assisted self-interview; Pall: p-value between HIV-positive and HIV-negative; P: p-value within group; IQR: interquartile range;
one parent alive and the other dead or unknown
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 to 28% of HIV-uninfected controls (p<0.01). By week 144, 23% of ALHIV lived with both biological parents compared to 47% of HIV-uninfected controls, and 33% of ALHIV lived with non-parent relatives compared to 12% of controls (p<0.01).
Substance use.
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.
Table 2:
Substance use, sexual behavior and violence exposure characteristics of adolescents with and without HIV at weeks 0, 48, 96 and 144
| Arm | ALHIV | HIV-uninfected controls | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ACASI visit week | Week 0 |
Week 48 |
Week 96 |
Week 144 |
P | Week 0 |
Week 48 |
Week 96 |
Week 144 |
P | PAll |
| N | 250 | 248 | 240 | 231 | 59 | 51 | 46 | 43 | |||
| Substance use | |||||||||||
| Ever drank alcohol | 80 (32) | 109 (44) | 121 (50) | 133 (58) | <0.01 | 25 (42) | 24 (47) | 26 (57) | 28 (65) | <0.01 | 0.12 |
| Drank alcohol in the past 3 months | 31 (12) | 42 (17) | 50 (21) | 55 (24) | 0.84 | 12 (20) | 14 (27) | 9 (20) | 13 (30) | 0.40 | 0.46 |
| Ever smoked cigarettes | 24 (10) | 46 (19) | 58 (24) | 65 (28) | <0.01 | 10 (17) | 9 (18) | 10 (22) | 13 (30) | 0.02 | 0.20 |
| Smoked cigarettes in the past 3 months | 11 (4) | 22 (9) | 24 (10) | 27 (12) | <0.01 | 5 (8) | 7 (14) | 5 (11) | 7 (16) | 0.05 | 0.19 |
| Ever used marijuana or hash | 8 (3) | 13 (5) | 14 (6) | 13 (6) | 0.17 | 5 (8) | 1 (2) | 3 (7) | 7 (16) | 0.08 | 0.10 |
| Ever used inhalants | 3 (1) | 2 (1) | 3 (1) | 3 (1) | 0.95 | 1 (2) | 1 (2) | 3 (7) | 1 (2) | 0.53 | 0.16 |
| Ever used other substances | 1 (0) | 5 (2) | 5 (2) | 5 (2) | 0.19 | 2 (3) | 1 (2) | 1 (2) | 1 (2) | 0.51 | 0.52 |
| Ever shot up drugs into a vein | 0 (0) | 1 (0) | 1 (0) | 0 (0) | 0.98 | 0 (0) | 1 (2) | 0 (0) | 0 (0) | NA | 0.46 |
| Sexual behavior | |||||||||||
| Ever received information on sexual education | 185 (74) | 211 (85) | 211 (88) | 211 (91) | <0.01 | 44 (75) | 41 (80) | 41 (89) | 39 (91) | <0.01 | 0.78 |
| Source of information on sexual education (multiple answers) | |||||||||||
| From school | 164 (89) | 175 (89) | 178 (90) | 177 (88) | 0.77 | 43 (98) | 41 (100) | 39 (95) | 36 (97) | 0.78 | 0.01 |
| From public information | 37 (20) | 68 (35) | 81 (41) | 97 (48) | <0.001 | 12 (27) | 12 (29) | 19 (46) | 21 (57) | 0.007 | 0.33 |
| From friends | 46 (25) | 52 (27) | 69 (35) | 72 (36) | 0.004 | 15 (34) | 9 (22) | 18 (44) | 13 (35) | 0.09 | 0.59 |
| From other sources e.g., video, television, internet | 71 (39) | 87 (44) | 97 (49) | 100 (50) | 0.01 | 18 (41) | 13 (32) | 18 (44) | 20 (54) | 0.094 | 0.90 |
| From health-care professionals | 125 (68) | 137 (70) | 135 (69) | 129 (64) | 0.92 | 18 (41) | 14 (34) | 15 (37) | 18 (49) | 0.34 | <0.001 |
| Ever had sexual intercourse | 26 (10) | 42 (17) | 57 (24) | 71 (31) | <0.01 | 10 (17) | 5 (10) | 6 (13) | 9 (21) | <0.01 | 0.09 |
| Never had sexual intercourse | 224 (90) | 206 (83) | 183 (76) | 160 (69) | 49 (83) | 46 (90) | 40 (87) | 34 (79) | |||
| Age at first sexual intercourse < 15 years | 7 (27) | 8 (19) | 8 (14) | 8 (11) | 0.09 | 3 (30) | 1 (20) | 1 (17) | 1 (11) | 0.86 | <0.01 |
| Type of sexual relationships ever had | 26 | 35 | 51 | 71 | 10 | 5 | 6 | 9 | |||
| Female-male | 26 (100) | 35 (100) | 46 (98) | 61 (98) | 9 (90) | 3 (100) | 5 (83) | 8 (100) | |||
| Male-male | 0 (0) | 0 (0) | 0 (0) | 2 (3) | 0 (0) | 0 (0) | 0 (0) | 0 (0) | |||
| Female-female | 4 (15) | 3 (9) | 4 (9) | 3 (5) | 1 (10) | 0 (0) | 1 (17) | 0 (0) | |||
| Number of sexual partners in the past 3 months | 26 | 35 | 51 | 71 | 10 | 5 | 6 | 9 | |||
| 1 person | 17 (65) | 17 (40) | 29 (51) | 39 (55) | 0.06 | 5 (50) | 2 (40) | 4 (67) | 6 (67) | 0.74 | 0.91 |
| More than 1 person | 6 (23) | 8 (19) | 7 (12) | 5 (7) | 3 (30) | 0 (0) | 0 (0) | 0 (0) | |||
| No sexual intercourse within 3 months | 3 (12) | 17 (40) | 21 (37) | 27 (38) | 2 (20) | 3 (60) | 2 (33) | 3 (33) | |||
| Frequency of sex in the past 3 months | 26 | 35 | 51 | 71 | 10 | 5 | 6 | 9 | |||
| 1-5 times | 18 (69) | 23 (55) | 33 (58) | 47 (66) | <0.01 | 4 (40) | 0 (0) | 3 (50) | 5 (56) | 0.03 | 0.66 |
| > 5 times | 3 (12) | 6 (14) | 10 (18) | 11 (15) | 4 (40) | 2 (40) | 2 (33) | 2 (22) | |||
| Condom used | 26 | 35 | 51 | 71 | 10 | 5 | 6 | 9 | |||
| Yes, always | 7 (27) | 15 (43) | 20 (39) | 30 (42) | 0.62 | 2 (20) | 1 (20) | 1 (17) | 4 (44) | 0.44 | 0.45 |
| Yes, sometimes | 18 (69) | 21 (60) | 28 (55) | 32 (45) | 8 (80) | 2 (40) | 5 (83) | 4 (44) | |||
| No, never | 1 (4) | 6 (17) | 9 (18) | 9 (16) | 0 (0) | 2 (40) | 0 (0) | 1 (22) | |||
| Every had unsafe sex after using illegal drugs or alcohol | 8 (3) | 7 (3) | 5 (3) | 8 (2) | 0.71 | 1 (2) | 0 (2) | 1 (0) | 1 (2) | 0.97 | 0.42 |
| Ever had STD symptoms | 4 (2) | 7 (3) | 9 (4) | 9 (4) | <0.01 | 0 (0) | 0 (0) | 0 (0) | 0 (0) | NA | NA |
| Violence | |||||||||||
| Have ever been physically hurt by friends/teachers/families | 114 (46) | 141 (57) | 143 (60) | 137 (59) | <0.01 | 29 (49) | 31 (61) | 29 (63) | 27 (63) | <0.01 | <0.01 |
| Have been physically hurt by friends/teachers/families in the past 6 months | |||||||||||
| Yes | 59 (24) | 39 (16) | 22 (9) | 8 (3) | 0.04 | 8 (14) | 8 (16) | 3 (7) | 2 (5) | 0.49 | 0.06 |
| No | 2 (1) | 1 (0) | 3 (1) | 1 (0) | 3 (5) | 1 (2) | 4 (9) | 4 (9) | |||
| Unknown | 53 (21) | 101 (41) | 118 (49) | 128 (55) | 18 (31) | 22 (43) | 22 (48) | 21 (49) | |||
| Never | 136 (54) | 107 (43) | 97 (40) | 94 (41) | 30 (51) | 20 (39) | 17 (37) | 16 (37) | |||
| Have ever been forced to have any sexual act/interaction that you did not want to have | 8 (3) | 7 (3) | 4 (2) | 4 (2) | 0.55 | 0 (0) | 0 (0) | 0 (0) | 0 (0) | NA | NA |
ALHIV: Adolescents living with HIV; ACASI: audio computer-assisted self-interview; Pall: p-value between HIV-positive and HIV-negative; P: p-value within group; STD: sexually transmitted disease
Sexual behavior.
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 (e.g., video, television, 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 to 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 to 144. Few participants reported same sex male relationships (<3%) or unsafe sex after using illegal drugs or alcohol (<3%). The proportion of ALHIV reporting age at first sexual intercourse <15 years was significantly lower than controls (p <0.01).
Violence.
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, which describes the clinical characteristics of ALHIV study participants). The median age at ART initiation was 7 (IQR 4–10). 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 enrolment, 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 viral load by site cut-off 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).
Disclosure.
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). 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.
Stigma.
Throughout the duration of the study, the proportion of ALHIV indicating that their body or appearance should be better, that they don’t like themselves or that they hate themselves remained relatively stable at around 18% (see Table, Supplemental Digital Content 2). 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.
Adherence.
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). The proportion reporting difficulties taking antiretroviral medicines on a daily basis decreased from 38% at enrolment, 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 virologic failure at all time points (Table 3): 1) living with non-parent relatives (OR 2.20 versus living with both parents; 95% CI 1.03 – 4.71), 2) living with a partner (OR 5.55 versus living with both parents; 95% CI 1.00 – 30.85), 3) living on your own (OR 16.77 versus living with both parents; 95% CI 1.67 – 168.48), 4) ever smoking cigarettes (OR 2.26; 95% CI 1.21 – 4.24), 5) having more than one sexual partner in the past 3 months (OR 5.08 versus one sexual partner in the past 3 months; 95% CI 1.39 – 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 – 5.81).
Table 3:
Factors associated with virologic failure among adolescents with HIV
| Covariate | Univariate | P | Multivariate | P |
|---|---|---|---|---|
| OR (95% CI) | aOR (95% CI) | |||
| Female | 1.56 (0.87-2.8) | 0.13 | 1.54 (0.81-2.94) | 0.071 |
| Parent status | 0.17 | |||
| Both of them alive | ref | |||
| One of them alive | 1.33 (0.67-2.64) | |||
| Both of them died | 2.35 (1.12-4.94) | |||
| Unknown | 1.32 (0.51-3.42) | |||
| Current caregiver or living situation | 0.03 | 0.031 | ||
| Both father and mother | ref | ref | ||
| Mother / father | 1.67 (0.83-3.36) | 1.76 (0.77-4.04) | ||
| Relatives, not parents | 1.93 (1.01-3.70) | 2.20 (1.03-4.71) | ||
| Foster family / Shelter home | 1.22 (0.52-2.87) | 1.04 (0.40-2.71) | ||
| Partner | 6.49 (1.88-22.38) | 5.55 (1.00-30.85) | ||
| On my own | 5.00 (0.89-28.02) | 16.77 (1.67-168.48) | ||
| Currently working | 1.40 (0.92-2.12) | 0.11 | ||
| Age at ART initiation (years) | 0.09 | |||
| <4 | ref | |||
| 4-<7 | 0.50 (0.24-1.06) | |||
| 7-<10 | 0.38 (0.16-0.88) | |||
| ≥10 | 0.51 (0.23-1.13) | |||
| Current CD4 count (cells/mm3) | <0.001 | |||
| <500 | ref | ref | <0.001 | |
| 500 - 650 | 0.29 (0.17-0.49) | 0.24 (0.13-0.46) | ||
| ≥650 | 0.09 (0.05-0.17) | 0.07 (0.04-0.15) | ||
| Duration on ART (years) | 0.44 | |||
| <6 | 1.24 (0.65-2.38) | |||
| 6-<9 | 0.92 (0.5-1.71) | |||
| 9-<12 | 0.74 (0.42-1.3) | |||
| ≥12 | ref | |||
| Current regimen | <0.001 | <0.001 | ||
| NNRTI-based ART | 0.24 (0.12-0.49) | 0.21 (0.10-0.43) | ||
| PI-based ART | ref | ref | ||
| Third-line ART | 1.07 (0.36-3.20) | 0.88 (0.29-2.64) | ||
| Others | 0.21 (0.06-0.75) | 0.32 (0.10-1.09) | ||
| Adherence | <0.001 | |||
| ≥95 | ref | |||
| <95 | 2.18 (1.49-3.19) | |||
| Problems taking ART | ||||
| Difficult to take anti-HIV medicine | 0.61 (0.41-0.92) | 0.02 | ||
| Time to take anti-HIV medicine | 0.58 (0.32-1.03) | 0.01 | ||
| Number of times to take anti-HIV medicine each day | 0.60 (0.28-1.28) | 0.04 | ||
| Number of pills | 1.95 (1.09-3.50) | 0.01 | ||
| Size of pills | 1.75 (0.96-3.20) | 0.02 | ||
| Taste of anti-HIV medicine | 1.89 (0.96-3.73) | 0.01 | 2.50 (1.08-5.81) | 0.002 |
| Substance use | ||||
| Ever drank alcohol | 1.17 (0.76-1.80) | 0.47 | ||
| Drank alcohol within 3 months | 0.51 | |||
| Yes | 1.34 (0.80-2.26) | |||
| No | 1.06 (0.65-1.72) | |||
| Never | ref | |||
| Ever smoked cigarettes | 2.20 (1.40-3.45) | 0.001 | 2.26 (1.21-4.24) | 0.001 |
| Cigarette smoking within 3 months | 0.002 | |||
| Yes | 1.93 (1.04-3.58) | |||
| No | 2.39 (1.44-3.99) | |||
| Never | ref | |||
| Ever tried marijuana or hashish | 1.91 (0.92-3.95) | 0.08 | ||
| Ever used inhalants | 2.67 (0.70-10.16) | 0.15 | ||
| Ever used other substances | 2.78 (0.80-9.70) | 0.11 | ||
| Sexual risk behavior | ||||
| Ever had sexual intercourse | 1.72 (1.07-2.77) | 0.02 | ||
| Number of sexual partners in the past 3 months | 0.03 | 0.07 | ||
| 1 person | ref | ref | ||
| More than 1 person | 2.33 (0.96-5.62) | 5.08 (1.39-18.61) | ||
| No sexual intercourse within 3 months | 1.30 (0.61-2.78) | 2.04 (0.71-5.86) | ||
| Never had sexual intercourse | 0.72 (0.40-1.30) | 1.65 (0.73-3.74) | ||
| STD symptoms | 0.07 | |||
| Yes | 1.33 (0.46-3.90) | |||
| No | ref | |||
| Never had sexual intercourse | 0.60 (0.37-10.00) | |||
| Stigma | ||||
| Ever been teased by people | 1.25 (0.74-2.13) | 0.40 | ||
| Teased by people in the past 3 months | 0.93 | |||
| Yes, sometimes | 0.70 (0.30-1.64) | |||
| Yes, most of the time | 0.84 (0.15-4.66) | |||
| Yes, everyday | 1.01 (0.26-3.99) | |||
| No | ref | |||
| Unknown | 0.81 (0.38-1.70) | |||
| Does your boyfriend/girlfriend know about your HIV infection? | 1.13 (0.66-1.96) | 0.65 | ||
| Violence | ||||
| Ever experienced violence from friends/teachers/families | 0.98 (0.60-1.59) | 0.96 | ||
| Experienced violence in the past 6 months | ||||
| Yes | 1.24 (0.66-2.31) | 0.62 | ||
| No | ref | |||
| Unknown | 0.95 (0.57-1.57) |
OR: odds ratio; aOR: adjusted odds ratio; CI: confidence interval; P: p-value within group; ART: antiretroviral therapy; NNRTI: non-nucleoside reverse transcriptase inhibitor; PI: protease inhibitor; STD: sexually transmitted disease
Factors associated with decreased odds of virologic failure were: 1) higher CD4 counts (compared to those with CD4 count <500 cells/mm3, the OR [95%CI] for virologic failure with CD4 counts of 500–650 cells/mm3 and ≥650 cells/mm3 were 0.24 [95% CI 0.13 – 0.46] and 0.07 [95% CI 0.04 – 0.15], respectively), and 2) non-nucleoside reverse transcriptase inhibitor-based ART (OR 0.21 versus protease inhibitor-based ART; 95% CI 0.10 – 0.43).
Discussion
Across three 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 to 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 onwards 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 (e.g., 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, in order 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]. Whilst somewhat surprising given increasing virologic failure rates observed as similar cohorts aged [51], the stable virologic failure rate in our cohort may be attributed to a combination of factors, including strong relationships between patients, caregivers, and families in our network. Because 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, might be explained by the much steeper decline in adherence ≥95% amongst those without an available viral load, than those with. While the association between lower CD4 count and virologic failure 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 virologic failure in ALHIV living with non-parent relatives was over 2 times greater, over 5 times greater in those living with a partner, and over 16 times greater in those living on their own, compared to 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 post-suppression virologic rebound [56], and a study among ALHIV in Botswana found absence of a parent from clinic visits was strongly associated with virologic failure [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 prior to adolescence, in order to reduce communication barriers, and improve collaboration for ongoing health [64].
We also examined data by viral load availability and found no substantial differences in demographic, clinical, and risk behavior or exposure between those with viral load 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 non-response 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 virologic failure, 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.
Supplementary Material
Acknowledgements
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.
Funding support was provided through a grant to amfAR, The Foundation for AIDS Research from the U.S. National Institutes of Health’s National Institute of Allergy and Infectious Diseases, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Cancer Institute, National Institute of Mental Health, and National Institute on Drug Abuse as part of the International Epidemiology Databases to Evaluate AIDS (IeDEA; U01AI069907), and additional support from LIFE+, Austria. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions mentioned above.
Footnotes
Conflicts of Interest and Source of Funding
The authors declare no conflicts of interest related to this study.
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