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        Antiretroviral Therapy Enrollment Characteristics and Outcomes Among HIV-Infected Adolescents and Young Adults Compared with Older Adults — Seven African Countries, 2004–2013

        Andrew F. Auld, MBChB1, Simon G. Agolory, MD1, Ray W. Shiraishi, PhD1, Fred Wabwire-Mangen, MD, PhD2, Gideon Kwesigabo, MD, PhD3, Modest Mulenga, MD4, Sebastian Hachizovu, MBChB4, Emeka Asadu, MD5, Moise Zanga Tuho, MD6, Virginie Ettiegne-Traore, MD6, Francisco Mbofana, MD7, Velephi Okello, MD8, Charles Azih, MD8, Julie A. Denison, PhD9, Sharon Tsui, MPH9, Olivier Koole, MD10, Harrison Kamiru, DrPH11, Harriet Nuwagaba-Biribonwoha, MBChB, PhD11, Charity Alfredo, MD12, Kebba Jobarteh, MD12, Solomon Odafe, MD13, Dennis Onotu, MD13, Kunomboa A. Ekra, MD14, Joseph S. Kouakou, MD14, Peter Ehrenkranz, MD15, George Bicego, PhD15, Kwasi Torpey, PhD16, Ya Diul Mukadi, MD17, Eric van Praag, MD18, Joris Menten, MSc10, Timothy Mastro, MD19, Carol Dukes Hamilton, MD19, Mahesh Swaminathan, MD1, E. Kainne Dokubo, MD1, Andrew L. Baughman, PhD1, Thomas Spira, MD1, Robert Colebunders, MD, PhD10, David Bangsberg, MD20, Richard Marlink, MD21, Aaron Zee, MPH1, Jonathan Kaplan, MD1, Tedd V. Ellerbrock, MD1 (Author affiliations at end of text)

        Although scale-up of antiretroviral therapy (ART) since 2005 has contributed to declines of about 30% in the global annual number of human immunodeficiency (HIV)-related deaths and declines in global HIV incidence,* estimated annual HIV-related deaths among adolescents have increased by about 50% (1) and estimated adolescent HIV incidence has been relatively stable. In 2012, an estimated 2,500 (40%) of all 6,300 daily new HIV infections occurred among persons aged 15–24 years.§ Difficulty enrolling adolescents and young adults in ART and high rates of loss to follow-up (LTFU) after ART initiation might be contributing to mortality and HIV incidence in this age group, but data are limited (2). To evaluate age-related ART retention challenges, data from retrospective cohort studies conducted in seven African countries among 16,421 patients, aged ≥15 years at enrollment, who initiated ART during 2004–2012 were analyzed. ART enrollment and outcome data were compared among three groups defined by age at enrollment: adolescents and young adults (aged 15–24 years), middle-aged adults (aged 25–49 years), and older adults (aged ≥50 years). Enrollees aged 15–24 years were predominantly female (81%–92%), commonly pregnant (3%–32% of females), unmarried (54%–73%), and, in four countries with employment data, unemployed (53%–86%). In comparison, older adults were more likely to be male (p<0.001), employed (p<0.001), and married, (p<0.05 in five countries). Compared with older adults, adolescents and young adults had higher LTFU rates in all seven countries, reaching statistical significance in three countries in crude and multivariable analyses. Evidence-based interventions to reduce LTFU for adolescent and young adult ART enrollees could help reduce mortality and HIV incidence in this age group.

        In each of seven countries (C?te d'Ivoire, Nigeria, Swaziland, Mozambique, Zambia, Uganda, and Tanzania), a representative sample of ART facilities was selected using either probability-proportional-to-size sampling or purposeful (nonrandom) sampling (Table 1). At each selected facility, a sample frame of study-eligible ART patients was created, and simple random sampling used to select the desired sample size. Eligibility criteria included having started ART during 2004–2012 and ≥6 months before data abstraction. Data were abstracted from ART medical records onto standard forms.

        Mortality and LTFU were the primary outcomes of interest. A patient was considered LTFU if he/she had not attended the facility in the 90 days preceding data abstraction for a medication refill, a laboratory visit, or a clinician visit. Mortality ascertainment occurred largely through passive reporting to the health facility by family or friends, and to a lesser extent, through country-specific tracing activities to locate patients late for clinic appointments.

        Study design was controlled for during analysis. Age at ART initiation was divided into three age categories (3): 15–24 years, 25–49 years, and ≥50 years. Differences in demographic and clinical characteristics across age groups were assessed using chi-square tests for categorical variables and unadjusted linear regression models for continuous variables.

        To estimate the association between age group and rates of death and LTFU, Cox proportional hazards regression models were used to estimate unadjusted and adjusted hazard ratios for each outcome separately. For the multivariable analysis, to best manage missing baseline demographic or clinical data, multiple imputation with chained equations was used to impute missing data included in the model (4). Twenty imputed datasets were created for each outcome: death and LTFU (4). The imputation model included the event indicator, all study variables, and the Nelson-Aalen estimate of cumulative hazard (4). The proportional hazards assumption was assessed using visual methods and the Grambsch and Therneu test.

        Demographic and clinical characteristics of adults at ART initiation were compared across age groups by country (Table 2). Age distribution was relatively constant across countries, with 5%–16% aged 15–24 years, 70%–86% aged 25–49 years, and 8%–14% aged ≥50 years. In all seven countries, the youngest age group was almost exclusively female (81%–92%), and the middle-age group mostly female (60%–68%); in contrast, the oldest age group was mostly male in all countries, except Nigeria. In the six countries with data on pregnancy at ART enrollment, pregnancy prevalence was highest in the youngest age group in five countries, where it ranged from 16% to 32%. In all seven countries, being married or in a civil union was least common in the youngest age group (27%–46%), reaching statistical significance in five countries. In the four countries with data on employment status, the youngest age group was least likely to be employed at the time of ART enrollment (14%–47%) (p<0.05).

        In all seven countries, median baseline weight was lowest in the youngest age group (48.2–58.0 kg), reaching statistical significance in six countries. In three countries (Nigeria, Swaziland, and Tanzania), prevalence of World Health Organization clinical stage 4 at ART initiation differed across age groups, tending to be lowest in the youngest and highest in the oldest age group (p<0.05). Median baseline CD4 count was similar across age groups in all countries, except Nigeria, where the median was highest in the youngest age group (p=0.004). Median baseline hemoglobin was significantly lower in the youngest age group in four countries (9.4–10.7 g/dL).

        Compared with older adults, rates of LTFU were higher in the youngest age group in all seven countries, reaching statistical significance in unadjusted analyses in three countries (C?te d'Ivoire (p=0.005), Mozambique (p<0.001), and Tanzania (p=0.005)) (Table 3). Even after adjusting for baseline demographic and clinical characteristics, rates of LTFU were 1.66–2.45 times as high in the youngest compared with the oldest age group in these three countries (C?te d'Ivoire [p=0.001], Mozambique [p=0.002], and Tanzania [p<0.001]).

        In two countries (Swaziland and Uganda), the oldest age group had significantly higher rates of documented mortality than younger age groups (Table 3), and older age remained a significant predictor of mortality even in multivariable analyses.

        Discussion

        The three main findings based on the experience of the seven African countries are as follows: 1) adolescents and young adults differed significantly from older adults in ART enrollment characteristics; 2) adolescents and young adults tended to have higher LTFU rates; and 3) in two countries (Uganda and Swaziland), adults ≥50 years had higher documented mortality rates.

        Adolescent and young adult ART enrollees were almost exclusively female, commonly pregnant, unmarried, and unemployed. The observation that median weight was lowest among adolescents and young adults could be explained by expected weight-for-age growth, sex differences in weight, or undernutrition. Similarly, the observation that median hemoglobin tended to be lowest in the youngest age group might reflect predominantly female sex or higher prevalence of undernutrition.

        Available data suggest that this group of predominantly female adolescent and young adult ART enrollees represents a socially vulnerable population (2). Although rates of HIV-related mortality and HIV incidence have declined globally since 2005, mortality has increased and HIV incidence remained relatively stable among adolescents, with the majority of adolescent deaths and new HIV infections occurring in sub-Saharan Africa (2). In African countries with generalized epidemics, being young, female, and unemployed increases the risk for voluntary or coerced sexual contact with older, HIV-infected men (2); this might partly explain HIV infection at a young age among some of the female adolescent and young adult ART enrollees described in this report. Factors that possibly explain high LTFU rates among adolescent and young adult ART enrollees might include stigma (2), lack of money for transport (5), child care responsibilities, and migration for work (6). LTFU from ART is associated with significant increases in mortality risk (7). A recent meta-analysis suggests that 20%–60% of patients lost to follow-up die, with most of these deaths occurring after default from ART (7). Therefore, difficulties in preventing LTFU among adolescent and young adults on ART might be a contributor to HIV-related mortality in this age group. Suboptimal ART adherence among adolescents might also be contributing to adolescent mortality (1).

        High rates of LTFU among adolescent and young adult ART enrollees is also concerning from a prevention perspective, because LTFU patients are at risk for transmitting HIV to seronegative partners once ART is discontinued and viral load no longer suppressed (8). High rates of LTFU among young women, among whom the prevalence of pregnancy is high, also increases the likelihood of mother-to-child HIV transmission.

        Adult ART enrollees aged ≥50 years were mostly male, commonly married, and employed. In two countries, this age group had higher documented mortality, similar to findings in other studies (9). Higher mortality in this oldest age group should probably be expected because of higher background rates of mortality in the older general population. However, HIV-related reasons for higher mortality in the oldest age group might include slower ART-induced CD4 restoration among older patients (3) or incidence of HIV-associated noncommunicable diseases, especially atherosclerotic disease (10).

        The findings in this report are subject to at least four limitations. First, missing data might have introduced nondifferential measurement error. Second, because of differences in cohort size, there was greater power to detect covariate effect sizes in C?te d'Ivoire, Nigeria, Swaziland, and Mozambique than in Zambia, Uganda, and Tanzania. Third, in Zambia, Uganda, and Tanzania, clinics were purposefully selected, limiting generalizability of findings. Finally, limited active tracing for defaulting patients might have resulted in overestimates of LTFU and underestimates of mortality.

        The main finding of this report is that adolescent and young adult ART enrollees differ significantly from older adults in demographic and clinical characteristics and are at higher risk for LTFU. Effective interventions to reduce LTFU for adolescent and young adult ART enrollees could help reduce mortality and HIV incidence in this age group.

        1Division of Global HIV/AIDS, Center for Global Health, CDC; 2Infectious Diseases Institute, Makerere University College of Health Sciences, Uganda; 3Muhimbili University of Health and Allied Sciences, Tanzania; 4Tropical Diseases Research Center, Zambia; 5Ministry of Health, Nigeria; 6Ministry of Health, C?te d'Ivoire; 7National Institute of Health, Mozambique; 8Ministry of Health, Swaziland; 9Social and Behavioral Health Sciences, FHI 360, Washington, DC; 10Institute of Tropical Medicine, Department of Clinical Sciences, Belgium; 11International Center for AIDS Care and Treatment Programs-Columbia University, New York, NY; 12Division of Global HIV/AIDS, Center for Global Health, CDC, Mozambique; 13Division of Global HIV/AIDS, Center for Global Health, CDC, Nigeria; 14Division of Global HIV/AIDS, Center for Global Health, CDC, C?te d'Ivoire; 15Division of Global HIV/AIDS, Center for Global Health, CDC, Swaziland; 16FHI 360, Zambia; 17FHI 360, Haiti; 18FHI 360, Tanzania; 19Global Health, Population and Nutrition, FHI 360, Durham, NC; 20Massachusetts General Hospital, Boston, MA; 21Harvard School of Public Health, Boston, MA (Corresponding author: Andrew F. Auld, aauld@cdc.gov, 404-639-8997)

        References

        1. Idele P, Gillespie A, Porth T, et al. Epidemiology of HIV and AIDS among adolescents: current status, inequities, and data gaps. J Acquir Immune Defic Syndr 2014;66(Suppl 2):S144–53.
        2. Kasedde S, Luo C, McClure C, Chandan U. Reducing HIV and AIDS in adolescents: opportunities and challenges. Curr HIV/AIDS Rep 2013;10:159–68.
        3. Grabar S, Kousignian I, Sobel A, et al. Immunologic and clinical responses to highly active antiretroviral therapy over 50 years of age. Results from the French Hospital Database on HIV. AIDS 2004;18:2029–38.
        4. White IR, Royston P. Imputing missing covariate values for the Cox model. Stat Med 2009;28:1982–98.
        5. Geng EH, Bangsberg DR, Musinguzi N, et al. Understanding reasons for and outcomes of patients lost to follow-up in antiretroviral therapy programs in Africa through a sampling-based approach. J Acquir Immune Defic Syndr 2009;53:405–11.
        6. CDC. Differences between HIV-infected men and women in antiretroviral therapy outcomes—six African countries, 2004–2012. MMWR Morb Mortal Wkly Rep 2013;62:946–52.
        7. Brinkhof MW, Pujades-Rodriguez M, Egger M. Mortality of patients lost to follow-up in antiretroviral treatment programmes in resource-limited settings: systematic review and meta-analysis. PLoS One 2009;4:e5790.
        8. Cohen MS, Chen YQ, McCauley M, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med 2011;365:493–505.
        9. May M, Sterne JA, Sabin C, et al. Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies. AIDS 2007;21:1185–97.
        10. Bloomfield GS, Khazanie P, Morris A, et al. HIV and noncommunicable cardiovascular and pulmonary diseases in low- and middle-income countries in the ART era: what we know and best directions for future research. J Acquir Immune Defic Syndr 2014;67(Suppl 1):S40–53.

        * Information available at http://www.unaids.org/en/media/unaids/contentassets/documents/epidemiology/2013/gr2013/UNAIDS_Global_Report_2013_en.pdf.

        Sources: Kasedde S, Luo C, McClure C, Chandan U. Reducing HIV and AIDS in adolescents: opportunities and challenges. Curr HIV/AIDS Rep 2013;10:159–68; and UNAIDS. Report on the Global AIDS Epidemic, 2012, unpublished estimates; Spectrum 2012.

        § Information available at http://www.unaids.org/sites/default/files/en/media/unaids/contentassets/documents/epidemiology/2012/gr2012/JC2434_WorldAIDSday_results_en.pdf.


        What is already known on this topic?

        Although scale-up of antiretroviral therapy (ART) since 2005 has contributed to a decline of about 30% in the global annual number of human immunodeficiency (HIV)–related deaths and declines in global HIV incidence, estimated annual HIV-related deaths among adolescents have increased by about 50%, and estimated adolescent HIV incidence has been relatively stable. In 2012, an estimated 2,500 (40%) of all 6,300 daily new HIV infections occurred among persons aged 15–24 years. Difficulty enrolling adolescents and young adults in ART and high rates of loss to follow-up (LTFU) after ART initiation might be contributing to mortality and HIV incidence in this age group, but data are limited.

        What is added by this report?

        Age-related differences in enrollment characteristics and outcomes were analyzed among 16,421 patients aged ≥15 years starting ART in seven African countries (C?te d'Ivoire, Nigeria, Swaziland, Mozambique, Zambia, Uganda, and Tanzania) during 2004–2012. Patient characteristics and outcomes were compared across three age groups: adolescents and young adults (15–24 years), middle-aged adults (25–49 years), and older adults (≥50 years). Compared with older adults, adolescents and young adults had higher LTFU rates in all seven countries, reaching statistical significance in three countries (C?te d'Ivoire, Mozambique, and Tanzania) in both crude and multivariable analyses.

        What are the implications for public health practice?

        The higher risk for LTFU among adolescent and young adult ART enrollees, compared with older adults, increases their risk for death and increases the risk they will transmit HIV to seronegative sex partners. Effective interventions to reduce LTFU for adolescent and young adult ART enrollees could help reduce mortality and lower HIV incidence in this age group.


        TABLE 1. Summary of sampling strategies to select cohorts of enrollees for antiretroviral therapy (ART) — seven African countries, 2004–2013

        Region and country

        Stage 1: Selection of study facilities

        Stage 2: Selection of study patients

        No. of ART clinics

        No. of
        ART enrollees at
        ART clinics

        Clinic eligibility criteria
        for
        study

        No. of study-eligible clinics

        Estimated no. of study-eligible adult ART enrollees at study-eligible clinics

        Site sampling technique

        No. of clinics selected

        Age-eligibility criteria (age at
        ART initiation)

        ART enrollment years

        Patient sampling technique at
        selected study clinics

        Planned sample size

        No. of eligible patient charts abstracted

        Date of data collection

        West Africa

        C?te d'Ivoire

        124 by Dec 2007

        36,943

        Enrolled ≥50 adults by Dec 2007

        78

        36,110

        PPS

        34

        Adults aged
        ≥15 yrs

        2004–2007

        SRS

        4,000

        3,682

        Nov 2009–March 2010

        Nigeria

        178 by Dec 2009

        168,335

        Enrolled ≥50 adults by Dec 2009

        139

        167,438

        PPS

        35

        Adults aged
        ≥15 yrs

        2004–2012

        SRS

        3,500

        3,496

        Dec 2012–Aug 2013

        Southern Africa

        Swaziland

        31 by Dec 2009

        50,767

        All ART initiation sites eligible

        31

        50,767

        PPS

        16

        Adults aged
        ≥15 yrs

        2004–2010

        SRS

        2,500

        2,510

        Nov 2011– Feb 2012

        Mozambique

        152 by Dec 2006

        43,295

        Enrolled ≥50 adults by Dec 2006

        94

        42,234

        PPS

        30

        Adults aged
        ≥15 yrs

        2004–2007

        SRS

        2,600

        2,596

        Sept–Nov 2008

        Zambia

        322 by Dec 2007

        65,383

        Enrolled ≥300 adults by Dec 2007

        129*

        58,845*

        Purposeful

        6

        Adults aged
        ≥15 yrs

        2004–2009

        SRS

        1,500

        1,214

        April–July 2010

        East Africa

        Uganda

        286 by Dec 2007

        45,946

        Enrolled ≥300 adults by Dec 2007

        114*

        41,351*

        Purposeful

        6

        Adults aged
        ≥15 yrs

        2004–2009

        SRS

        1,500

        1,466§

        April–July 2010

        Tanzania

        210 by Dec 2007

        41,920

        Enrolled ≥300 adults by Dec 2007

        85

        37,728*

        Purposeful

        6

        Adults aged
        ≥18 yrs

        2004–2009

        SRS

        1,500

        1,457

        April–July 2010

        Total

         

        452,589 

        670

        434,473

        133

        17,100

        16,421

        Abbreviations: PPS = probability-proportional-to-size; SRS = simple random sampling.

        * Estimates based on available published data.

        In Zambia, from 1,457 records sampled, 243 were excluded because of noncompliance with simple random sampling procedures at one site.

        § In Uganda, from 1,472 records samples, six patients were excluded because of absence of age data at ART initiation.

        In Tanzania, from 1,458 records samples, one patient was excluded because of absence of age data at ART initiation.


        TABLE 2. Demographic and clinical characteristics of patients at initiation of antiretroviral therapy (ART) — seven African countries, 2004–2012*

        Characteristic and
        age group (yrs) 

        C?te d'Ivoire

        (N = 3,682)

        Nigeria

        (N = 3,496)

        Swaziland

        (N = 2,510)

        Mozambique

        (N = 2,596)

        Zambia

        (N = 1,214)

        Tanzania

        (N = 1,457 )

        Uganda

        (N = 1,466)

        Age at ART initiation (No. and %)

        15–24

        188

        5%

        399

        11%

        398

        16%

        284

        12%

        95

        8%

        83

        6%

        95

        6%

        25–49

        3,087

        83%

        2,805

        81%

        1,759

        70%

        2,069

        79%

        1,000

        82%

        1,198

        82%

        1,261

        86%

        ≥50

        407

        12%

        292

        9%

        353

        14%

        243

        10%

        119

        10%

        176

        12%

        110

        8%

        Female (No. and %)

        15–24

        166

        87%

        366

        92%

        326

        82%

        45

        86%

        82

        86%

        73

        88%

        77

        81%

        25–49

        2,077

        68%

        1,808

        64%

        1,120

        64%

        838

        60%

        599

        60%

        813

        68%

        837

        66%

        ≥50

        179

        46%

        146

        51%

        175

        49%

        137

        48%

        45

        38%

        87

        49%

        50

        45%

        p–value

        <0.001§

        <0.001

        <0.001

        <0.001

        <0.001

        <0.001

        <0.001

        Among females, pregnant (No. and %)

        15–24

        4

        3%

        56

        16%

        82

        26%

        61

        30%

        15

        32%

        25

        18%

        25–49

        64

        4%

        188

        10%

        117

        11%

        138

        14%

        56

        12%

        102

        9%

        ≥50

        0

        0%

        0

        0%

        2

        1%

        0

        0%

        0

        0%

        0

        0%

        p-value

        0.567

        <0.001

        <0.001

        0.002

        0.003

        <0.001

        Married/Civil union (No. and %)

        15–24

        41

        27%

        177

        43%

        85

        28%

        99

        41%

        38

        46%

        28

        41%

        21

        34%

        25–49

        1,393

        50%

        1,795

        64%

        725

        47%

        999

        55%

        520

        60%

        505

        53%

        431

        43%

        ≥50

        202

        54%

        200

        67%

        190

        65%

        113

        55%

        67

        64%

        71

        49%

        40

        43%

        Missing

        414

        11%

        86

        2%

        384

        15%

        233

        9%

        166

        14%

        299

        21%

        313

        21%

        p-value

        <0.001

        <0.001

        <0.001

        0.001

        0.022

        0.115

        0.354

        Employed (No. and %)

        15–24

        59

        47%

        91

        30%

        68

        31%

        28

        14%

        25–49

        1,394

        63%

        1,541

        66%

        551

        48%

        860

        49%

        ≥50

        148

        53%

        165

        70%

        73

        32%

        104

        56%

        Missing

        1,081

        29%

        420

        12%

        925

        37%

        328

        13%

         

         

         

         

         

         

        p-value

        <0.001

        <0.001

        <0.001

        <0.001

         

         

         

        Baseline weight (No. and median [kg])

        15–24

        162

        49.0

        371

        52.0

        356

        58.0

        223

        50.0

        83

        49.0

        80

        48.2

        86

        52.7

        25–49

        2,743

        53.0

        2589

        57.0

        1575

        60.0

        1,658

        54.5

        882

        53.0

        1,163

        51.1

        1,145

        55.0

        ≥50

        351

        54.0

        274

        57.0

        301

        59.9

        180

        52.5

        108

        55.0

        172

        50.2

        101

        56.0

        Missing

        426

        12%

        262

        7%

        278

        11%

        535

        21%

        141

        12%

        42

        3%

        134

        9%

        p-value

        0.005

        <0.001

        0.024

        0.015

        0.001

        0.296

        0.001

        WHO clinical stage 4 (No. and %)

        15–24

        25

        18%

        25

        5%

        22

        6%

        32

        20%

        11

        13%

        20

        29%

        12

        14%

        25–49

        462

        22%

        197

        8%

        218

        13%

        205

        15%

        96

        11%

        257

        27%

        137

        12%

        ≥50

        67

        25%

        24

        11%

        53

        16%

        22

        15%

        5

        5%

        48

        35%

        11

        12%

        Missing

        1,101

        30%

        232

        7%

        290

        12%

        979

        38%

        157

        13%

        293

        20%

        164

        11%

        p-value

        0.468

        0.012

        <0.001

        0.066

        0.100

        <0.001

        0.551

        Baseline CD4 count (No. and median [cells/μL])

        15–24

        165

        122

        320

        192

        359

        158

        249

        175

        69

        147

        50

        175

        76

        161

        25–49

        2,811

        136

        2321

        157

        1618

        141

        1,794

        157

        701

        128

        933

        126

        1,011

        133

        ≥50

        367

        132

        244

        142

        319

        160

        211

        133

        79

        158

        137

        160

        79

        147

        Missing

        339

        9%

        611

        17%

        214

        9%

        342

        13%

        365

        30%

        337

        23%

        300

        20%

        p-value

        0.216

        0.004

        0.139

        0.077

        0.704

        0.243

        0.501

        Baseline hemoglobin (No. and median [g/dL])

        15–24

        156

        10.0

        190

        10.3

        229

        10.7

        211

        9.4

        52

        10.1

        37

        9.6

        55

        11.5

        25–49

        2,646

        9.9

        1,365

        10.3

        1165

        11.2

        1,515

        10.2

        582

        10.6

        648

        10.2

        748

        11.9

        ≥50

        347

        9.9

        145

        10.8

        218

        11.6

        173

        10.6

        70

        11.6

        90

        10.9

        62

        12.1

        Missing

        533

        14%

        1,796

        51%

        898

        36%

        697

        27%

        510

        42%

        682

        47%

        601

        41%

        p-value

        0.524

        0.690

        <0.001

        <0.001

        0.002

        0.028

        0.306

        Abbreviation: WHO = World Health Organization.

        * Although the study captured patient follow-up time through 2013, all patients started ART during the period 2004–2012.

        Proportions from C?te d'Ivoire, Nigeria, Swaziland, and Mozambique are weighted to account for sampling design.

        Bold-typed p-values are statistically significant (p<0.05).


        TABLE 3. Association between age group at initiation of antiretroviral therapy and rates of loss to follow-up and death — seven African countries, 2004–2013

        Country 

         Age group (yrs) 

        No. 

        Lost to follow-up

        Died

        Rate
        (per 100) 

        Crude

        Adjusted 

        Rate
        (per 100) 

        Crude

        Adjusted

        HR

        (95% CI)

        p-value

        AHR*

        (95% CI)

        p-value

        HR

        (95% CI)

        p-value

        AHR*

        (95% CI)

        p-value

        C?te d'Ivoire 

         

        ≥50

        407

        14.5

        1.00

        1.00

        4.2

        1.00

        1.00

         

        25–49

        3,087

        17.5

        1.21

        (0.92–1.59)

        0.171

        1.33

        (1.00–1.77)

        0.052

        2.9

        0.68

        (0.45–1.05)

        0.077

        0.76

        (0.51–1.12)

        0.155

         

        15–24

        188

        23.0

        1.54

        (1.15–2.04)

        0.005

        1.66

        (1.24–2.22)

        0.001

        3.8

        0.87

        (0.37–2.03)

        0.732

        0.97

        (0.43–2.18)

        0.935

        Nigeria 

         

        ≥50

        399

        15.3

        1.00

        1.00

        1.5

        1.00

        1.00

         

        25–49

        2,805

        13.7

        0.91

        (0.70–1.18)

        0.446

        0.94

        (0.73–1.22)

        0.640

        1.1

        0.79

        (0.43–1.46)

        0.441

        0.89

        (0.47–1.68)

        0.714

         

        15–24

        292

        16.5

        1.09

        (0.79–1.50)

        0.604

        1.04

        (0.75–1.44)

        0.818

        0.8

        0.51

        (0.20–1.34)

        0.166

        0.74

        (0.30–1.86)

        0.514

        Swaziland§

        ≥50

        353

        11.0

        1.00

        1.00

        3.0

        1.00

        1.00

         

        25–49

        1,759

        11.4

        1.06

        (0.91–1.23)

        0.452

        0.99

        (0.81–1.20)

        0.887

        1.9

        0.66

        (0.46–0.93)

        0.021

        0.56

        (0.39–0.81)

        0.006

         

        15–24

        398

        13.2

        1.26

        (0.94–1.70)

        0.113

        1.22

        (0.89–1.68)

        0.198

        1.9

        0.65

        (0.46–0.92)

        0.018

        0.58

        (0.38–0.90)

        0.019

        Mozambique  

         

        ≥50

        243

        16.4

        1.00

        1.00

        3.8

        1.00

        1.00

         

        25–49

        2,069

        14.4

        0.96

        (0.78–1.18)

        0.686

        1.02

        (0.79–1.32)

        0.872

        3.2

        0.94

        (0.55–1.59)

        0.805

        1.10

        (0.62–1.96)

        0.733

         

        15–24

        284

        28.4

        1.80

        (1.46–2.21)

        <0.001

        1.76

        (1.27–2.43)

        0.002

        5.0

        1.40

        (0.72–2.71)

        0.296

        1.33

        (0.72–2.45)

        0.339

        Zambia 

         

        ≥50

        95

        21.4

        1.00

        1.00

        3.6

        1.00

        1.00

         

        25–49

        1,000

        21.7

        1.01

        (0.75–1.37)

        0.928

        0.94

        (0.69–1.29)

        0.722

        2.3

        0.63

        (0.29–1.33)

        0.223

        0.66

        (0.30–1.47)

        0.312

         

        15–24

        119

        25.6

        1.14

        (0.75–1.74)

        0.539

        1.21

        (0.78–1.89)

        0.393

        5.1

        1.32

        (0.49–3.51)

        0.582

        1.26

        (0.43–3.71)

        0.679

        Tanzania

         

        ≥50

        83

        13.0

        1.00

        1.00

        8.0

        1.00

        1.00

         

        25–49

        1,198

        17.8

        1.36

        (0.98–1.90)

        0.067

        1.47

        (1.05–2.06)

        0.024

        6.4

        0.80

        (0.52–1.23)

        0.309

        0.90

        (0.58–1.42)

        0.661

         

        15–24

        176

        30.1

        2.01

        (1.24–3.25)

        0.005

        2.45

        (1.50–4.01)

        <0.001

        13.5

        1.37

        (0.70–2.70)

        0.358

        1.40

        (0.69–2.82)

        0.354

        Uganda

         

        ≥50

        95

        6.0

        1.00

        1.00

        2.8

        1.00

        1.00

         

        25–49

        1,261

        7.6

        1.29

        (0.76–2.17)

        0.346

        1.37

        (0.81–2.34)

        0.240

        1.0

        0.35

        (0.15–0.80)

        0.013

        0.31

        (0.13–0.76)

        0.010

         

        15–24

        110

        7.1

        1.18

        (0.57–2.44)

        0.664

        1.19

        (0.56–2.51)

        0.647

        1.0

        0.34

        (0.07–1.66)

        0.184

        0.25

        (0.05–1.29)

        0.098

        Abbreviations: HR = hazard ratio; CI = confidence interval; AHR = adjusted hazard ratio.

        * All variables presented in the table were included in the multivariable model for each country.

        Bold-typed p-values are statistically significant (p<0.05) or borderline significant (p=0.05–0.10).

        § In Swaziland, the study was designed to assess the effect of interfacility transfer of stable patients (down-referral) on risk for loss to follow-up, and this time-varying covariate was included in the multivariable model in addition to variables presented in the table.



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