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. Author manuscript; available in PMC: 2010 Oct 1.
Published in final edited form as: J Acquir Immune Defic Syndr. 2009 Oct;52(2):280. doi: 10.1097/QAI.0b013e3181ab6eab

Late disease stage at presentation to an HIV clinic in the era of free antiretroviral therapy in sub-Saharan Africa

Isaac M Kigozi 1, Loren M Dobkin 2, Jeffrey N Martin 3, Elvin H Geng 2, Winnie Muyindike 4, Nneka I Emenyonu 5, David R Bangsberg 5, Judith A Hahn 2
PMCID: PMC2815238  NIHMSID: NIHMS139783  PMID: 19521248

Abstract

Background

Access to free antiretroviral therapy (ART) in sub-Saharan Africa has been steadily increasing, and the success of large-scale ART programs depends on early initiation of HIV care. However, little is known about the stage at which those infected with HIV present for treatment in sub-Saharan Africa.

Methods

We conducted a cross-sectional analysis of initial visits to the Immune Suppression Syndrome Clinic of the Mbarara University Teaching Hospital, including patients who had their initial visit between February 2007 and February 2008 (N=2311).

Results

Median age was 33 years (range 16–81). 64% were female. Over one-third (40%) were categorized as late presenters, that is World Health Organization disease stage 3 or 4. Male gender, age 46 to 60 (versus younger), lower education level, being unemployed, living in a household with others, being unmarried, and lack of spousal HIV status disclosure were independently associated with late presentation, while being pregnant, having young children, and consuming alcohol in the prior year were associated with early presentation.

Conclusions

Targeted public health interventions to facilitate earlier entry into HIV care are needed, as well as additional study to determine whether late presentation is due to delays in testing versus delays in accessing care.

Keywords: Antiretroviral therapy, access, sub-Saharan Africa, late presentation

Introduction

Sub-Saharan Africa remains the most affected region in the global AIDS epidemic, with an estimated 22.5 million people living with HIV in 2007. Increasing numbers of patients are receiving free HIV antiretroviral therapy (ART) in this region, with 1.7 million treated under the President’s Emergency Plan for AIDS Relief.1 Approximately 39% of HIV positives in Uganda who meet eligibility criteria for HIV antiretroviral therapy (ART), based on either CD4 count ≤ 200 cells/mL or clinical diagnosis of World Health Organization (WHO) stage 3 or 4,2 are currently receiving ART.3

The health status of patients at the time of ART initiation plays a crucial role in the success of treatment. Patients with advanced HIV disease at the time of ART initiation are less likely to respond to treatment, more likely to place financial strain on health services, and have a higher mortality rate compared to those who initiate earlier.4–12 In addition, late presentation poses a higher cumulative risk of HIV transmission to others, considering that earlier presentation and HIV-suppressing treatment might otherwise reduce viral load and risk of transmission.12–16

A large proportion of HIV-infected individuals in the developed world, roughly 15–43%, present at clinics for care with advanced or severe disease (WHO stage 3 or 4, CDC Category B or C, or CD4 ≤200 cells/ml).5,7,17–26 Characteristics associated with late presentation in the developed world include older age, male sex, risk behavior (including injection drug and alcohol use), lower income, as well as low degree of education.27–35 However, little is known in low income countries, particularly those in sub-Saharan Africa, about the proportion or characteristics of HIV-infected individuals who present late for care at clinics. One study of 31 patients in Haiti reported that 65% presented with a CD4 count less than 350 cells/ml.36 Several studies from sub-Saharan Africa have shown that a large number of patients have low CD4 cell counts at ART initiation;37–40 however it is not possible to determine how much of this is attributable to the sickest patients being prioritized for treatment. We are unaware of any other published studies that have examined HIV stage at presentation for care in low income countries.

Quantifying the proportion of HIV-positive patients who present at clinics at WHO HIV disease stage 3 or 4 and identifying correlates of late presentation in sub-Saharan Africa may assist health professionals in allocating resources to different types of HIV care services, and in designing interventions to overcome barriers to early HIV care. We therefore conducted an analysis of medical records from patients’ initial visit to the HIV clinic of a large referral hospital in southwestern Uganda to estimate the proportion of patients presenting at WHO stage 3 or 4, and to identify demographic, psychosocial, and behavioral correlates of late presentation. We also examined whether correlates of late presentation vary by sex.

Methods

Subjects

Our sample included all patients who attended the Mbarara University Teaching Hospital (MUTH) Immune Suppression Syndrome (ISS) clinic for the first time between February 1st, 2007 and February 29th, 2008 and were accessing HIV care for the first time. The MUTH is the regional referral hospital for a population of 1.2 million in southwestern Uganda. As of February 29th, 2008 the ISS Clinic had 6,381 active HIV-positive patients, 3,939 of whom were receiving ART.

Data collection

Data for this study was the patient information that is routinely collected at initial clinic visit on a standard form that was adapted from the Open Medical Record System, an electronic medical records system framework developed by Moi University and Indiana University for use in developing countries. The ISS initial visit form includes socio-demographic, behavioral and clinical information, including physical examination findings, medication history, symptoms, WHO stage, and HIV treatment plan. The socio-demographic and behavioral data are collected by counselors while the clinical data are collected by physicians. The data from this form is entered into the OpenMRS data management system (www.openmrs.org). Quality control checks are performed on 5% of entered records, through which electronic records are compared variable by variable with the original source document; entry errors occur in less than 1% of the data.

Measurements

Outcome variable

We used WHO stage at initial clinic visit as the outcome variable for these analyses. The WHO HIV staging system41 applies clinical conditions to measure disease progression and is widely used in resource limited settings including sub-Saharan Africa, where laboratory values of disease stage (i.e. CD4+ T cell counts and plasma HIV RNA levels) are not always readily available. This staging system has been shown to reliably predict survival time and subsequent disease progression.42–46 We categorized WHO stage dichotomously, as not severe (stages 1 and 2) or severe (stages 3 and 4), and clinic presentation as early or late, respectively.

Independent variables

Independent variables included socio-demographic information recorded on the ISS initial visit form such as gender, pregnancy, age, tribe, religion, socioeconomic status (i.e. education level, occupation, monthly income, in-house running water), household composition (i.e. number of children and adults), and marital status. We also examined variables directly related to HIV care, such as the time required to travel to the ISS clinic, the number of HIV-infected household members, the number of those receiving HIV care, and among the married patients, whether they had disclosed their HIV status to their spouse, whether the spouse was HIV-infected, and whether the spouse was identified as the primary treatment supporter. We assessed alcohol use in the prior year using the Alcohol Use Disorders Identification Test-C (AUDIT-C),47 a shortened and validated version of the WHO-developed AUDIT.48

Statistical Analysis

We calculated summary statistics to describe the general socio-demographic, medical, and behavioral features of the population. Where more than 2.5% of the data were missing for any independent variable, we created a separate category for the missing values. We used chi-square tests of association for nominal variables and chi-square trend tests for ordinal variables to compare patients missing WHO stage to those with WHO stage data. We similarly conducted unadjusted analyses, and performed multivariable logistic regression to identify independent correlates of late presentation. Given our large sample size and the exploratory nature of the study, we included all variables in the model, except the number of HIV-infected household members and the number of household members in HIV care, because these variables were collinear with the total number of household members.

We also conducted multivariable analyses stratified by sex because we hypothesized that the psychosocial correlates of late presentation might differ by sex. Several variables were relevant to only the married participants, so we conducted additional analyses among the married participants only. In those analyses, we were unable to include whether the participants’ spouses were identified as their HIV treatment supporters in the model due to collinearity with whether the participants had disclosed their HIV status to their spouses.

Ethical considerations

The study was approved by the ISS Clinic data sharing committee and the Institutional Review Boards of Mbarara University of Science and Technology and the University of California, San Francisco.

Results

Of the 2,584 unique patients who presented to the ISS Clinic between February 1st, 2007 and February 29th, 2008, we excluded 58 who had received prior HIV care elsewhere. For 216 patient records, no WHO stage or specific clinical condition was checked on the ISS initial visit form to indicate WHO stage. We compared patients who had WHO stage information (n=2,311) with those who had none (n=216) and found the two groups to be similar (p> 0.05) in all analyzed characteristics: gender, age, tribe, religion, level of education, occupation, income, household water source, alcohol use, time required to travel to ISS clinic, number of children under 5 years, number of household members, number of HIV positive household members and number receiving HIV care, marital status, treatment supporter, HIV status of spouse, as well as disclosure of HIV status to spouse.

We therefore analyzed the records with WHO stage of 2,311 unique patients. The median age was 33 years (range 16–81) (Table 1). The sample was 64% female, including 4% who were pregnant. Fifty-five percent of the total sample reported being married. Twenty-two percent (22%) reported having had some secondary school education, and 7% reported at least some college education. The majority (80%) reported a monthly income that is the equivalent of US $60 or less and 38% were farmers. Over one-third (40%) presented at the ISS Clinic late, that is at a severe WHO disease stage (35% stage 3 and 5% stage 4), while 60% were presented early (23% stage 1 and 37% stage 2).

Table 1.

Demographic and behavioral characteristics and bivariate associations with late HIV disease stage (i.e. WHO stages 3 and 4) at initial clinic visit at the ISS Clinic in Mbarara, Uganda, February 2007–March 2008

Characteristics Total
N=2,311		 (Col%) Late Stage
n=928		 (Row%) Odds Ratio (95% CI) P-value
WHO stage at presentation
    Stage 1 525 (23)
    Stage 2 858 (37)
    Stage 3 811 (35)
    Stage 4 117 (5)
Gender
    Female (Not pregnant) 1387 (60) 505 (36) 1
    Female (Pregnant) 100 (4) 15 (15) 0.31ψ (0.18 – 0.54) < 0.01
    Male 824 (36) 408 (50) 1.71ψ (1.44 – 2.04) < 0.01
Age
    16–30 years 869 (38) 302 (35) 1
    31–45 years 1127 (49) 463 (41) 1.31ψ (1.09 – 1.57) < 0.01
    46–60 years 250 (11) 131 (52) 2.07ψ (1.55 – 2.75) < 0.01
    > 60 years 40 (2) 18 (45) 1.53 (0.81 – 2.91) 0.18
Tribe
    Other 684 (30) 255 (37) 1
    Munyankole 1519 (66) 630 (41) 1.19 (0.99 – 1.44) 0.06
    Missing 108 (5) 43 (40) 1.11 (0.73 – 1.69) 0.61
Religion
    Catholic 571 (25) 237 (42) 1
    Protestant 1084 (47) 429 (40) 0.92 (0.75 – 1.13) 0.45
    Muslim 218 (9) 88 (40) 0.95 (0.69 – 1.31) 0.77
    Other 133 (6) 55 (41) 0.99 (0.67 – 1.46) 0.97
    Missing 305 (13) 119 (39) 0.90 (0.68 – 1.20) 0.48
Education
    Some Secondary School 556 (24) 182 (33) 1
    No Secondary School 1665 (72) 706 (42) 1.51ψ (1.24 – 1.85) < 0.01
    Missing 90 (4) 40 (44) 1.64* (1.05 – 2.58) 0.03
Occupation
    Business 425 (18) 142 (33) 1
    Unemployed 276 (12) 119 (43) 1.51ψ (1.11 – 2.06) < 0.01
    Agriculture 802 (35) 339 (42) 1.46ψ (1.14 – 1.87) < 0.01
    Other (Student, Government, Army) 597 (26) 242 (40) 1.36* (1.05 – 1.76) 0.02
    Missing 211 (9) 86 (41) 1.37 (0.98 – 1.93) 0.07
Monthly Income (Ugandan shillings)
    ≥ 100,000 (≥ $60 USD) 361 (16) 138 (38) 1
    < 100,000 (< $60 USD) 1457 (63) 585 (40) 1.08 (0.86 – 1.37) 0.50
    Missing 493 (21) 205 (42) 1.15 (0.87 – 1.52) 0.32
Piped Water in the Household
    Yes 766 (33) 281 (37) 1
    No 1153 (50) 484 (42) 1.25* (1.03 – 1.51) 0.02
    Missing 392 (17) 163 (42) 1.23 (0.96 – 1.58) 0.09
Travel time to clinic
    <30 minutes 365 (16) 127 (35) 1
    30 – 60 minutes 648 (28) 268 (41) 1.32* (1.01 – 1.72) 0.04
    1 – 2 hours 538 (23) 216 (40) 1.26 (0.95 – 1.66) 0.10
    >2 hours 480 (21) 212 (44) 1.48ψ (1.12– 1.96) < 0.01
    Missing 280 (12) 105 (38) 1.12 (0.81 – 1.55) 0.48
Number children < 5 yrs in house
    1 or more 961 (42) 344 (36) 1
    0 249 (11) 114 (46) 1.51ψ (1.14 – 2.01) < 0.01
    Missing 1101 (48) 470 (43) 1.34ψ (1.12 – 1.60) < 0.01
Number of people in household
    1 (respondent) 137 (6) 56 (41) 1
    2–4 983 (43) 378 (38) 0.90 (0.63 – 1.30) 0.59
    5–16 1141 (49) 468 (41) 1.01 (0.70 – 1.44) 0.97
    Missing 50 (2) 26 (52) 1.57 (0.82 – 3.00) 0.18
Number HIV+s in household (among those
not living alone, N=2,124)
    1 or more 1676 (79) 651 (39) 1
    0 21 (1) 13 (62) 2.56* (1.05 – 6.21) 0.03
    Missing 427 (20) 182 (43) 1.17 (0.94 – 1.45) 0.15
Alcohol use in the last year
    None 1392 (60) 582 (42) 1
    Moderate 123 (5) 39 (32) 0.65* (0.44 – 0.96) 0.03
    Heavy (Audit C Test Positive) 360 (16) 130 (36) 0.79* (0.61 – 1.00) 0.05
    Missing 436 (19) 177 (41) 0.95 (0.76 – 1.18) 0.65
Number HIV+s in household receiving
HIV care (among those with ≥1 HIV+
household member N=1,676)
    1 or more 953 (57) 381 (40) 1
    0 58 (3) 17 (29) 0.62 (0.35 – 1.11) 0.11
    Missing data 665 (40) 253 (40) 0.92 (0.75 – 1.13) 0.43
Marital Status
    Married 1218 (53) 431 (35) 1
    Single 192 (8) 77 (40) 1.22 (0.90 – 1.67) 0.21
    Separated/Divorced 414 (18) 203 (49) 1.76ψ (1.40 – 2.20) < 0.01
    Widowed 391 (17) 170 (43) 1.40ψ (1.11 – 1.77) < 0.01
    Missing 96 (4) 47 (49) 1.75ψ (1.15 – 2.66) < 0.01
Characteristics: Married Persons Only Total
N=1,218		 (Col%) Late Stage
n=431		 (Row%) Odds Ratio (95% CI) P-value
Proposed treatment supporter
    Spouse 820 (67) 280 (33)       1
    Other 195 (16) 450 (45)   1.64ψ (1.35 – 1.98) < 0.01
    Missing 203 (17) 198 (44)   1.58ψ (1.25 – 1.99) < 0.01
HIV status of spouse
    Positive 515 (42) 184 (36) 1
    Negative/Unknown 584 (48) 211 (36) 1.02 (0.79 – 1.30) 0.89
    Missing 119 (10) 36 (30) 0.76 (0.49 – 1.16) 0.20
HIV disclosure to spouse
    Told spouse 678 (56) 231 (34) 1
    Told other person, not spouse 246 (246) 105 (43) 1.44* (1.07 – 1.94) 0.02
    Missing 294 (24) 95 (32) 0.91 (0.68 – 1.21) 0.51
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*

P-value < 0.05

ψ

P-value < 0.01

Bivariate results

Demographic factors

Several factors demographic factors were associated with late presentation on bivariate analyses, including male gender (50% of males presented late versus 36% of non-pregnant females), non-pregnancy (36% of non-pregnant women presented late versus 15% of pregnant women), and older age (52%, 41%, and 35% of those 46–50, 31–45, and 16–25 years old respectively presented late).

Socioeconomic factors

Socioeconomic factors associated with late presentation were lesser education (42% of those with no secondary education presented late versus 33% of those with some secondary education or more), non-business occupation (43% of those unemployed, 42% of farmers and 40% of those with other occupations versus 33% of those with business employment presented late), no household water source (42% of those without piped water presented late versus 37% of those with piped water), and more time required to travel to the ISS clinic (44%, 41%, and 35% of those traveling >2 hours, 30–60 minutes, and less than 30 minutes to clinic respectively presented late).

Household and family related factors

Household-related factors that were associated with late presentation included no children under age 5 in the household (46% of those with no children under age 5 presented late versus 36% of those with 1 or more), no other HIV-infected household members (62% of those with no HIV-infected household members presented late versus 39% of those with 1 or more), and unmarried status (43% of those who were widowed, 49% of those who were separated/divorced versus 35% of those who were married presented late). Among married patients (n=1,218), factors associated with late presentation in bivariate analyses included proposed non-spousal HIV treatment supporter (45% of those who listed someone other than the patient’s spouse versus 33% of those who listed their spouse presented late), and HIV non-disclosure to spouse (43% of those who disclosed to another person who was not their spouse presented late versus 34% of those who disclosed to their spouse).

Behavioral factors

Alcohol consumption in the past year was associated with HIV stage at presentation, with more non-drinkers presenting late (42%, 36%, and 32% of those who reported no alcohol use, moderate alcohol use, and heavy alcohol use respectively presented late).

Multivariate results

We also conducted multivariate analyses (Table 2) using all of the variables studied except the number of HIV-infected household members and the number of household members in HIV care, due to collinearity with the total number of household members. We found that male gender, older age, local tribal identity (Munyankole), having no secondary school education, being unemployed, having no children under age 5, not reporting living alone, and being unmarried or missing marital status were independently associated with presenting late at WHO stage 3 or 4, while being pregnant and reporting some alcohol use in the past year were independently associated with presenting early at WHO stage 1 or 2.

Table 2.

Adjusted odds ratios and 95% confidence intervals for late HIV disease stage (i.e. WHO stages 3 and 4) at clinic presentation for all new patients and stratified by patient gender, Mbarara, Uganda, February 2007–March 2008

Correlates All (N=2,311) Women (n=1,487) Men (n=824)
ORAdj 95% CI ORAdj 95% CI ORAdj 95% CI
Gender and pregnancy
    Male (vs. non-pregnant female) 2.23ψ (1.80 – 2.76) ------- --------------- ------- ---------------
    Pregnant female (vs. non–pregnant female) 0.42ψ (0.24 – 0.75) 0.45ψ (0.25 – 0.80) ------- ---------------
Age
    31–45years   (vs. 16–30 years) 1.13 (0.91 – 1.39) 1.05 (0.81 – 1.35) 1.24 (0.81 – 1.90)
     46–60years   (vs. 16–30 years) 1.55ψ (1.13 – 2.14) 1.79ψ (1.16 – 2.77) 1.49 (0.86 – 2.60)
    Older than 60 (vs. 16–30 years) 0.84 (0.43 – 1.66) 0.91 (0.30 – 2.80) 0.90 (0.36 – 2.27)
Tribe
    Munyankole (vs. other) 1.23* (1.00 – 1.51) 1.15 (0.89 – 1.49) 1.54* (1.07 – 2.22)
    Missing   (vs. other) 1.03 (0.66 – 1.61) 1.20 (0.69 – 2.07) 0.80 (0.36 – 1.77)
Religion
    Protestant   (vs. Catholic) 0.87 (0.70 – 1.09) 0.93 (0.70 – 1.23) 0.77 (0.53 – 1.12)
    Muslim (vs. Catholic) 0.96 (0.67 – 1.35) 1.08 (0.70 – 1.66) 0.75 (0.40 – 1.39)
    Other (vs. Catholic) 0.87 (0.58 – 1.31) 0.77 (0.46 – 1.31) 1.08 (0.54 – 2.17)
    Missing     (vs. Catholic) 0.87 (0.64 – 1.18) 1.03 (0.70 – 1.52) 0.67 (0.40 – 1.13)
Education
    No secondary school (vs. some secondary) 1.48ψ (1.17 – 1.86) 1.28 (0.93 – 1.76) 1.79ψ (1.27– 2.54)
    Missing (vs. some secondary) 1.46 (0.90 – 2.37) 1.53 (0.82 – 2.86) 1.39 (0.63– 3.07)
Occupation
    Unemployed   (vs. business) 1.44* (1.02 – 2.03) 1.29 (0.85 – 1.96) 1.92 (0.97 – 3.80)
    Agriculture    (vs. business) 1.25 (0.95 – 1.65) 1.19 (0.83 – 1.69) 1.43 (0.90 – 2.26)
    Other (vs. business) 1.21 (0.92 – 1.60) 1.03 (0.71 – 1.51) 1.48 (0.97 – 2.26)
    Missing (vs. business) 1.32 (0.92 – 1.91) 1.52 (0.96 – 2.43) 1.03 (0.56 – 1.89)
Monthly income
    ≤ 100,000 UGX [$60] (vs. >100,000 UGX) 0.99 (0.75 – 1.31) 0.78 (0.51 – 1.20) 1.20 (0.82 – 1.76)
    Missing (vs. >100,000 UGX) 1.12 (0.81 – 1.56) 0.90 (0.56 – 1.44) 1.22 (0.74 – 2.02)
Piped tap water in home
    No piped tap water   (vs. piped tap water) 1.09 (0.88 – 1.36) 1.43* (1.09 – 1.88) 0.68* (0.47 – 0.97)
    Missing (vs. piped tap water) 1.16 (0.88 – 1.52) 1.24 (0.87 – 1.77) 1.03 (0.67 – 1.60)
Travel time to clinic
    30–60 minutes   (vs. < 30 minutes) 1.18 (0.88 – 1.57) 1.18 (0.80 – 1.72) 1.17 (0.73 – 1.88)
    1–2 hours    (vs. < 30 minutes) 1.09 (0.80 – 1.48) 1.19 (0.79 – 1.77) 0.94 (0.57 – 1.54)
    > 2hours    (vs. < 30 minutes) 1.27 (0.93 – 1.75) 1.23 (0.82 – 1.85) 1.29 (0.76 – 2.18)
    Missing (vs. < 30 minutes) 1.05 (0.74 – 1.48) 1.07 (0.69 – 1.66) 0.94 (0.51 – 1.54)
Number of children < 5 years in household
    None (vs. ≥ 1) 1.83ψ (1.21 – 2.78) 1.80* (1.06 – 3.05) 2.10* (1.02 – 4.33)
    Missing    (vs. ≥ 1) 1.19 (0.97 – 1.44) 1.26 (0.98 – 1.63) 1.16 (0.82 – 1.62)
Number of people in household
    2–4   (vs. 1) 1.80* (1.04 – 3.10) 1.66 (0.81 – 3.37) 2.10 (0.84 – 5.22)
    5–16    (vs. 1) 1.90* (1.09 – 3.28) 1.86 (0.92 – 3.80) 2.03 (0.81 – 5.09)
    Missing (vs. 1) 2.48* (1.11 – 5.54) 2.88 (0.96 – 8.62) 2.14 (0.61 – 7.49)
Marital status
    Single (vs. married) 1.43* (1.00 – 2.03) 1.70* (1.07 – 2.69) 1.20 (0.66 – 2.17)
    Separated/divorced   (vs. married) 1.94ψ (1.51 – 2.49) 2.39ψ (1.77 – 3.23) 1.34 (0.83 – 2.14)
    Widowed (vs. married) 1.47ψ (1.13 – 1.91) 1.56ψ (1.15 – 2.14) 1.23 (0.69 – 2.17)
    Missing (vs. married) 1.81ψ (1.16 – 2.83) 1.33 (0.73 – 2.44) 3.18ψ (1.47 – 6.85)
Alcohol use in the last year
    Heavy– Audit C test positive (vs. none) 0.60ψ (0.46 – 0.78) 0.55ψ (0.37 – 0.80) 0.57ψ (0.38 – 0.84)
    Moderate (vs. none) 0.49ψ (0.33 – 0.78) 0.56 (0.29 – 1.07) 0.47ψ (0.27 – 0.84)
     Missing (vs. none) 0.80 (0.64 – 1.02) 0.84 (0.61 – 1.14) 0.80 (0.55 – 1.18)
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*

P-value < 0.05

ψ

P-value < 0.01

In multivariate analyses stratified by sex (Table 2), we found that among women, older age, having no children under age 5 and being unmarried remained independently associated with late presentation, and being pregnant and reporting hazardous alcohol use in the past year remained independently associated with early presentation. Among men, local tribal identity (Munyankole), having no secondary education, having no children less than 5 years, and missing marital status remained independently associated with late presentation, while moderate or hazardous alcohol use in the past year remained independently associated with early presentation. Having no piped tap water at home was independently associated with late presentation among women, whereas it was associated with early presentation among men.

When we conducted analyses among the married participants only (Table 3), we included all variables used in the multivariate analyses listed above, as well as HIV status of spouse and HIV disclosure to spouse. We found that compared to patients who disclosed their HIV status to their spouses, patients who did not disclose to their spouses were significantly more likely to present late, after controlling for all other variables. Other multivariate odds ratios among married patients were similar to those for the whole sample.

Table 3.

Adjusted odds ratios and 95% confidence intervals for late HIV disease stage (i.e. WHO stages 3 and 4) at clinic presentation for all married patients and stratified by patient gender, Mbarara, Uganda, February 2007-March 2008

Correlates Among Married Patients All Married (N=1,205) Married Women (n=669) Married Men (n=536)
ORAdj 95% CI ORAdj 95% CI ORAdj 95% CI
Gender and pregnancy
    Male (vs. non-pregnant female) 2.39ψ (1.77 – 3.24) ------- --------------- ------- ---------------
    Pregnant female (vs. non-pregnant female) 0.37ψ (0.18 – 0.77) 0.37ψ (0.18 – 0.80) ------- ---------------
Age
    31–45 years   (vs. 16–30 years) 1.28 (0.94 – 1.76) 1.34 (0.90 – 2.02) 1.21 (0.68 – 2.14)
    46–60years   (vs. 16–30 years) 1.40 (0.85 – 2.30) 1.06 (0.40 – 2.79) 1.76 (0.86 – 3.58)
    Older than 60 (vs. 16–30 years) 0.66 (0.22 – 1.97) ------- --------------- 0.67 (0.19 – 2.35)
Tribe
    Munyankole (vs. other) 1.21 (0.90 – 1.62) 1.16 (0.77 – 1.74) 1.38 (0.86 – 2.20)
    Missing   (vs. other) 0.90 (0.59 – 1.39) 1.14 (0.43 – 3.03) 0.47 (0.17 – 1.31)
Religion
    Protestant   (vs. Catholic) 0.99 (0.72 – 1.37) 1.39 (0.86 – 2.24) 0.75 (0.47 – 1.20)
    Muslim    (vs. Catholic) 0.86 (0.52 – 1.42) 1.02 (0.51 – 2.12) 0.78 (0.36 – 1.68)
    Other (vs. Catholic) 1.57 (0.89 – 2.79) 1.68 (0.75 – 3.80) 1.68 (0.67 – 4.20)
    Missing    (vs. Catholic) 0.90 (0.59 – 1.39) 1.38 (0.74 – 2.59) 0.62 (0.33 – 1.18)
Education
    No secondary school (vs. some secondary) 1.36 (0.99 – 1.86) 1.30 (0.79 – 2.14) 1.45 (0.95 – 2.24)
    Missing (vs. some secondary) 1.59 (0.81 – 3.13) 2.18 (0.83 – 5.66) 1.13 (0.41 – 3.13)
Occupation
    Unemployed  (vs. business) 1.39 (0.83 – 2.33) 1.16 (0.56 – 2.39) 2.42 (0.97 – 6.06)
    Agriculture   (vs. business) 1.24 (0.84 – 1.83) 1.44 (0.81 – 2.57) 1.09 (0.62 – 1.90)
    Other (vs. business) 1.43 (0.98 – 2.09) 1.53 (0.83 – 2.83) 1.34 (0.80 – 2.23)
    Missing (vs. business) 1.26 (0.75 – 2.13) 1.95 (0.95 – 4.03) 0.78 (0.35 – 1.75)
Monthly income
    ≤ 100,000 UGX [$60] (vs. >100,000 UGX) 1.17 (0.82 – 1.67) 0.82 (0.45 – 1.49) 1.28 (0.80 – 2.05)
    Missing (vs. >100,000 UGX) 1.30 (0.84 – 2.02) 0.78 (0.39 – 1.56) 1.65 (0.87 – 3.14)
Piped tap water in home
    No piped tap water   (vs. piped tap water) 0.97 (0.71 – 1.32) 1.44 (0.92 – 2.24) 0.63* (0.40 – 0.99)
    Missing (vs. piped tap water) 1.08 (0.74 – 1.59) 1.01 (0.56 – 1.83) 1.07 (0.61 – 1.86)
Travel time to clinic
    30–60 minutes (vs. < 30 minutes) 1.18 (0.78 – 1.78) 1.07 (0.59 – 1.93) 1.40 (0.76 – 2.57)
    1–2hours     (vs. < 30 minutes) 1.08 (0.70 – 1.66) 1.04 (0.55 – 1.93) 1.15 (0.61 – 2.17)
    > 2hours     (vs. < 30 minutes) 1.55 (0.98 – 2.43) 1.40 (0.73 – 2.67) 1.74 (0.88 – 3.44)
    Missing (vs. < 30 minutes) 0.97 (0.58 – 1.62) 0.99 (0.49 – 1.98) 0.84 (0.38 – 1.85)
Number of children < 5 years in household
    None    (vs. ≥ 1) 1.53 (0.85 – 2.77) 1.32 (0.55 – 3.17) 1.50 (0.62 – 3.63)
    Missing   (vs. ≥ 1) 1.12 (0.85 – 1.48) 1.17 (0.79 – 1.73) 1.11 (0.74 – 1.68)
Number of people in household
    2–4 (vs. 1) 1.52 (0.42 – 5.49) 0.77 (0.14 – 4.26) 3.34 (0.43 – 26.06)
    5–16 (vs. 1) 1.53 (0.43 – 5.52) 0.91 (0.17 – 5.03) 2.96 (0.38 – 22.90)
    Missing (vs. 1) 1.82 (0.39 – 8.48) 0.65 (0.06 – 6.80) 4.54 (0.44 – 46.32)
HIV status of spouse
    Negative/Unknown (vs. positive) 0.92 (0.69 – 1.23) 1.12 (0.73 – 1.71) 0.92 (0.69 – 1.23)
    Missing (vs. positive) 0.75 (0.47 – 1.20) 0.99 (0.51 – 1.94) 0.83 (0.54 – 1.28)
HIV disclosure to spouse
    Told other person (vs. told spouse) 1.50* (1.06 – 2.12) 1.32 (0.82 – 2.14) 1.73* (1.06 – 2.12)
    Missing (vs. told spouse) 0.99 (0.71 – 1.38) 0.83 (0.51 – 1.34) 1.25 (0.77 – 2.04)
Alcohol use in the last year
    Heavy- Audit C test positive (vs. none) 0.65* (0.44 – 0.95) 0.72 (0.35 – 1.46) 0.58* (0.35 – 0.95)
    Moderate (vs. none) 0.46* (0.25 – 0.84) 0.22* (0.05 – 1.00) 0.59 (0.29 – 1.22)
    Missing (vs. none) 0.81 (0.58 – 1.15) 1.00 (0.61 – 1.65) 0.72 (0.44 – 1.17)
Open in a new tab
*

P-value < 0.05

ψ

P-value < 0.01

Discussion

In an era when HAART is not only free but also widely available in Uganda, we found that 40% of new patients in a large HIV clinic had late-stage HIV disease at their initial clinic visit. This figure may represent a lower bound for late-stage presentation, because the HIV stage was based on observable clinical signs and may have missed asymptomatic patients with advanced immunological disease. In a study in rural Uganda, 19% of those classified as at stage 1 or 2 HIV disease actually had CD4 counts of below 200 cells/mL.49 In addition, low detection of opportunistic infections, a plausible scenario in a busy clinical setting, may also have caused us to under-estimate the proportion presenting with late-stage disease. We found that 50% of the men presented with severe disease compared to 36% of the non-pregnant women and 15% of the pregnant women. This suggests that current programs to routinely offer HIV testing and treatment for the prevention of mother-to-child transmission (PMTC) in antenatal clinics in Mbarara are successfully linking most HIV-infected women with HIV care. Prior HIV testing and counseling in PMTC might also explain the lower rate of late presentation in non-pregnant women compared to men. However, other gender-related factors may be at play, as outpatient health service utilization in Uganda is generally higher among women as compared to men.50 Gender and pregnancy differences in stage at presentation have also been observed in Haiti, Canada, and several countries in Europe.21,26,51–53

Older age was also associated with late-stage presentation, which may be explained in part by the unavailability of HIV treatment in years past. Older people, on average, may have become infected longer ago and may have been more likely to suspend their clinic attendance for lack of treatment options. Another explanation for this finding could be that older people, like other low- risk groups, have a low self-perceived HIV risk, and therefore HIV test later than younger people, though this has not been shown in Africa.10,15,54–56 Other studies conducted in the United States,57 Europe,58–63 Australia64 and Venezuela65 have shown similar associations of age with stage of HIV disease at presentation. Older age has been shown to compound the negative impact of late presentation on treatment outcomes both in Africa66 and in the western world.67,68

Several socioeconomic factors were associated with late presentation to the ISS clinic. We found that patients with some secondary education had significantly lower odds of presenting with late-stage disease, compared to those with none; this has also been noted in the United States as well as in Venezuela65,69,70 Similarly, those who were employed were less likely to present late than those who were unemployed. Travel time to clinic was associated with late presentation on bivariate analysis, but not on multivariate analyses that controlled for other indicators of economic status and family responsibilities. These findings suggest that there may be structural barriers to seeking care in a rural setting where the travel to the only public hospital may require a substantial investment of time and money.

Several variables related to household and marriage were associated with HIV stage at presentation. Being married was associated with earlier presentation as compared with being single, separated or widowed, particularly among the women. Patients who had any children less than 5 years old in their household were also less likely to present late. Patients with young children, like pregnant women, may have more contact with the healthcare system and thus initiate HIV care earlier in the course of their disease. Among the married people, those who did not disclose their HIV status to their spouses were more likely to present late compared to those who disclosed, particularly among men. This suggests that the desire to hide one’s HIV-positive status from a spouse may inhibit HIV care-seeking. Studies have shown that the rates of sero-status disclosure among sexual partners in Africa are low 71,72 and our findings suggest that this may discourage participation in HIV treatment programs.

Surprisingly, patients who reported hazardous or moderate alcohol use in the previous year had lower odds of presenting late compared to those who abstained from alcohol for at least one year. There may be several explanations for this, including that those who are the most ill, i.e. those who are presenting with severe disease, are unlikely to feel healthy enough to consume alcohol. Another explanation could be that alcohol users have a heightened risk perception, a phenomenon similar to that observed among injecting drug users and men who have sex with men in the United States.73 A last possibility is that there is a high mortality rate among HIV-positives who consume alcohol, which caused the absence of many would-be late presenters from our sample of alcohol users. Further research is needed to determine the effect of alcohol on access to and receipt of HIV care and treatment.

The biggest limitations of this study are its cross-sectional design and selection bias. Because we did not follow HIV-positives prospectively from time of diagnosis and instead drew our sample from a snapshot of clinic attendees, our analyses of delayed presentation do not represent the proportion or characteristics of HIV-positives in the catchment area who never attended clinic. In addition, secular trends in the AIDS epidemic could also cause a variety of apparent associations. Lastly, under-diagnosis of late presentation may have caused bias to the null. However, these data serve as a preliminary examination of the amount of late presentation and factors associated with late presentation in the African setting where it is difficult to conduct large longitudinal studies.

The data we used came solely from information routinely collected during clinical encounters and as a result were lacking several potentially important variables. In particular, the ISS initial visit form did not include any questions regarding perceived or experienced HIV stigma, which has been shown to discourage HIV testing and counseling in sub-Saharan Africa.74,75 Nor did we capture patients’ HIV care attitudes and beliefs, for example, perceived eligibility requirements for ART. Because we did not know the date of first positive HIV test, we were unable to determine whether late clinic presentation was attributable to a delay in HIV testing or in accessing treatment upon diagnosis. Therefore, we are limited in our ability to recommend appropriate interventions to hasten the initiation of HIV care.

The level of missing data was higher than in typical analytic studies. However, we felt that it was important to disseminate the findings if the missing data were unlikely to cause significant bias. We created separate categories for missing data and found that these categories were not associated with the outcome, except in two instances concerning household composition; it appears that the data were likely missing at random.

Despite these limitations, our study includes a large number of HIV-positive patients in a developing country, providing a preliminary investigation into demographic, psychosocial, and behavioral correlates of late clinic presentation in this context. The associations we observed may provide a framework upon which to build a conceptual model of late presentation.

The large percentage of patients with late-stage HIV disease at their initial clinic visit suggests that barriers to HIV care are considerable in Uganda. Delays in HIV care have serious public health implications because opportunities to prevent further transmission through effective treatment with antiretroviral drugs are lost, and because initiating treatment for HIV disease at an advanced stage leads to worse treatment outcomes than treatment started earlier. This study reveals a need to develop interventions that facilitate earlier entry into HIV care.

This study also suggests that low CD4 count at ART initiation, as observed in several studies in sub-Saharan Africa, may be due to the high frequency of late-stage presentation among new HIV-positive patients, rather than to selective treatment of patients with late-stage disease. Late presentation poses a significant threat to the success of large scale ART. More research is needed to determine whether late presentation is due to delayed HIV diagnosis or a delay after diagnosis. Our findings suggest that in southwestern Uganda potential interventions, whether designed to promote HIV testing or early entry into care, should target men, un-married and older women, and those of lower socioeconomic status. In addition, we speculate that HIV testing programs may help accelerate initiation of HIV care by encouraging HIV sero-status disclosure to partners upon positive diagnosis.

Acknowledgments

Funding: This work was supported by the US National Institutes of Health grants R25 MH064712, P30 MH062246, U01 AI069911, P30 AI027763, and R01 MH054907, the Starr Foundation AIDS International Scholarship Fund, the International AIDS Society HIV Research Trust, the East Africa International Epidemiologic Databases to Evaluate AIDS (IeDEA) Consortium, the Antiretroviral Treatment in Lower Income Countries (ARTLINC) Collaboration, and Mark and Lisa Schwartz. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Government of the United States; The Power of Partnerships: Latest PEPFAR Results (June 2008) 2008
  • 2.Uganda National Antiretroviral Treatment And Care Guidelines For dults And Children. (1st Edition) 2003 [Google Scholar]
  • 3.UNGASS Uganda Report to UNAIDS (January 2006 – December 2007) 2008
  • 4.Badri M, Lawn SD, Wood R. Short-term risk of AIDS or death in people infected with HIV-1 before antiretroviral therapy in South Africa: a longitudinal study. Lancet. 2006;368(9543):1254–1259. doi: 10.1016/S0140-6736(06)69117-4. [DOI] [PubMed] [Google Scholar]
  • 5.Castilla Jab, Sobrino Pb, de la Fuente Lab, Noguer Ia, Guerra La, Parras Fa. Late diagnosis of HIV infection in the era of highly active antiretroviral therapy: consequences for AIDS incidence. AIDS. 2002;16(14):1945–1951. doi: 10.1097/00002030-200209270-00012. [DOI] [PubMed] [Google Scholar]
  • 6.Chadborn TRa, Baster Ka, Delpech VCa, Sabin CAb, Sinka Ka, Rice BDa, Evans BGa. No time to wait: how many HIV-infected homosexual men are diagnosed late and consequently die? (England and Wales, 1993–2002) AIDS. 2005;19(5):513–520. doi: 10.1097/01.aids.0000162340.43310.08. [DOI] [PubMed] [Google Scholar]
  • 7.Chadborn TRa, Delpech VCa, Sabin CAb, Sinka Ka, Evans BGa. The late diagnosis and consequent short-term mortality of HIV-infected heterosexuals (England and Wales, 2000–2004) AIDS. 2006;20(18):2371–2379. doi: 10.1097/QAD.0b013e32801138f7. [DOI] [PubMed] [Google Scholar]
  • 8.Egger M, May M, Chene G, Phillips AN, Ledergerber B, Dabis F. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet. 2002;360(9327):119–129. doi: 10.1016/s0140-6736(02)09411-4. [DOI] [PubMed] [Google Scholar]
  • 9.Hocking JS, Rodger AJ, Rhodes DG, Crofts N. Late presentation of HIV infection associated with prolonged survival following AIDS diagnosis-characteristics of individuals. International Journal of STD & AIDS. 2000;11:503–508. doi: 10.1258/0956462001916407. [DOI] [PubMed] [Google Scholar]
  • 10.Krentz HB, Auld MC, Gill MJ. The high cost of medical care for patients who present late (CD4<200 cells/µL) with HIV infection. HIV Medicine. 2004;5(2):93–98. doi: 10.1111/j.1468-1293.2004.00193.x. [DOI] [PubMed] [Google Scholar]
  • 11.Lawn SD, Myer L, Harling G, Orrell C, Bekker LG, Wood R. Determinants of mortality and nondeath losses from an antiretroviral treatment service in South Africa: implications for program evaluation. Clin Infect Dis. 2006;43(6):770–776. doi: 10.1086/507095. [DOI] [PubMed] [Google Scholar]
  • 12.Sabin CA, Smith CJ, Gumley H, Murphy G, Lampe FC, Phillips AN, Prinz B, Youle Mb, Johnson MA. Late presenters in the era of highly active antiretroviral therapy: uptake of and responses to antiretroviral therapy. AIDS. 2004;18(16):2145–2151. doi: 10.1097/00002030-200411050-00006. [DOI] [PubMed] [Google Scholar]
  • 13.Bunnell R, Mermin J, De Cock KM. HIV Prevention for a threatened continent: Implementing positive prevention in Africa. JAMA. 2006;296(7):855–858. doi: 10.1001/jama.296.7.855. [DOI] [PubMed] [Google Scholar]
  • 14.Castilla J, Del Romero J, Hernando V, Marincovich B, García S, Rodríguez C. Effectiveness of highly active antiretroviral therapy in reducing heterosexual transmission of HIV. Journal of Acquired Immune Deficiency Syndromes 2005. 2005 September 1;Volume 40(1):96–101. doi: 10.1097/01.qai.0000157389.78374.45. [DOI] [PubMed] [Google Scholar]
  • 15.Girardi EMD, Sabin CAP, Monforte AdAMD. Late diagnosis of HIV infection: Epidemiological features, consequences and strategies to encourage earlier testing. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2007;46(1) Suppl:S3–S8. doi: 10.1097/01.qai.0000286597.57066.2b. [DOI] [PubMed] [Google Scholar]
  • 16.Lima VD, Johnston K, Hogg RS, Levy AR, Harrigan PR, Anema A, Montaner JSG. Expanded access to highly active antiretroviral therapy: A potentially powerful strategy to curb the growth of the HIV epidemic. The Journal of Infectious Diseases. 2008;198(1):59–67. doi: 10.1086/588673. [DOI] [PubMed] [Google Scholar]
  • 17.Gay CL, Napravnik S, Eron JJ., Jr Advanced immunosuppression at entry to HIV care in the southeastern United States and associated risk factors. AIDS. 2006;20(5):775–778. doi: 10.1097/01.aids.0000216380.30055.4a. [DOI] [PubMed] [Google Scholar]
  • 18.Gupta SB, Gilbert RL, Brady AR, Livingstone SJ, Evans BG. on behalf of the CDSSAG. CD4 cell counts in adults with newly diagnosed HIV infection: results of surveillance in England and Wales, 1990–1998. AIDS. 2000;14(7):853–861. doi: 10.1097/00002030-200005050-00012. [DOI] [PubMed] [Google Scholar]
  • 19.Girardi EMD, Aloisi MSB, Arici CMD, Pezzotti PP, Serraino DMD, Balzano RB, Vigevani GMD, Alberici FMD, Ursitti MMD, D'Alessandro MMD, Monforte AdAMD, Ippolito GMD for the IBESG. Delayed presentation and late testing for HIV: Demographic and behavioral risk factors in a multicenter study in Italy. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2004;36(4):951–959. doi: 10.1097/00126334-200408010-00009. [DOI] [PubMed] [Google Scholar]
  • 20.Couturier E, Schwoebel V, Michon C, Hubert JB, Delmas MC, Morlat P, Boue F, Simonpoli AM, Dabis F, Brunet JB. Determinants of delayed diagnosis of HIV infection in France, 1993–1995. AIDS. 1998;12(7):795–800. doi: 10.1097/00002030-199807000-00016. [DOI] [PubMed] [Google Scholar]
  • 21.Samet JH, Retondo MJ, Freedberg KA, Stein MD, Heeren T, Libman H. Factors associated with initiation of primary medical care for HIV-infected persons. The American Journal of Medicine. 1994;97(4):347–353. doi: 10.1016/0002-9343(94)90301-8. [DOI] [PubMed] [Google Scholar]
  • 22.Girardi E, Sampaolesi A, Gentile M, Nurra G, Ippolito G. Increasing proportion of late diagnosis of HIV infection among patients with AIDS in Italy following introduction of combination antiretroviral therapy. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2000;25(1):71–76. doi: 10.1097/00042560-200009010-00010. [DOI] [PubMed] [Google Scholar]
  • 23.Mugavero MJ, Castellano C, Edelman D, Hicks C. Late diagnosis of HIV infection: The Role of Age and Sex. The American Journal of Medicine. 2007;120(4):370–373. doi: 10.1016/j.amjmed.2006.05.050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Schwarcz S, Hsu L, Dilley JW, Loeb L, Nelson K, Boyd S. Late diagnosis of HIV infection: trends, prevalence, and characteristics of persons whose HIV diagnosis occurred within 12 months of developing AIDS. J Acquir Immune Defic Syndr. 2006;43(4):491–494. doi: 10.1097/01.qai.0000243114.37035.de. [DOI] [PubMed] [Google Scholar]
  • 25.McDonald AM, Li Y, Dore GJ, Ree H, Kaldor JM. Late HIV presentation among AIDS cases in Australia, 1992–2001. Australian and New Zealand Journal of Public Health. 2003;27(6):608–613. doi: 10.1111/j.1467-842x.2003.tb00607.x. [DOI] [PubMed] [Google Scholar]
  • 26.Samet JH, Freedberg KA, Stein MD, Lewis R, Savetsky J, Sullivan L, Levenson SM, Hingson R. Trillion Virion Delay: Time from testing positive for HIV to presentation for primary care. Arch Intern Med. 1998;158(7):734–740. doi: 10.1001/archinte.158.7.734. [DOI] [PubMed] [Google Scholar]
  • 27.Chow KY, Ang LW, Verghesse I, Chew SK, Leo YS. Measurable predictive factors for progression to AIDS among HIV-infected patients in Singapore. Ann Acad Med Singapore. 2005;34(1):84–89. [PubMed] [Google Scholar]
  • 28.Gardner LI, Jr., Brundage JF, McNeil JG, Milazzo MJ, Redfield RR, Aronson NE, Craig DB, Davis C, Gates RH, Levin LI, et al. Predictors of HIV-1 disease progression in early-and late-stage patients: the U.S. Army Natural History Cohort. Military Medical Consortium for Applied Retrovirology. J Acquir Immune Defic Syndr. 1992;5(8):782–793. [PubMed] [Google Scholar]
  • 29.Gay CL, Napravnik S, Eron JJ., Jr Advanced immunosuppression at entry to HIV care in the southeastern United States and associated risk factors. AIDS. 2006;20(5):775–778. doi: 10.1097/01.aids.0000216380.30055.4a. [DOI] [PubMed] [Google Scholar]
  • 30.Girardi E, Sabin CA, Monforte AD. Late diagnosis of HIV infection: epidemiological features, consequences and strategies to encourage earlier testing. J Acquir Immune Defic Syndr. 2007;46 Suppl 1:S3–S8. doi: 10.1097/01.qai.0000286597.57066.2b. [DOI] [PubMed] [Google Scholar]
  • 31.Hocking JS, Rodger AJ, Rhodes DG, Crofts N. Late presentation of HIV infection associated with prolonged survival following AIDS diagnosis--characteristics of individuals. Int J STD AIDS. 2000;11(8):503–508. doi: 10.1258/0956462001916407. [DOI] [PubMed] [Google Scholar]
  • 32.Lanoy E, Mary-Krause M, Tattevin P, Perbost I, Poizot-Martin I, Dupont C, Costagliola D. Frequency, determinants and consequences of delayed access to care for HIV infection in France. Antivir Ther. 2007;12(1):89–96. doi: 10.1177/135965350701200111. [DOI] [PubMed] [Google Scholar]
  • 33.Masson CL, Sorensen JL, Phibbs CS, Okin RL. Predictors of medical service utilization among individuals with co-occurring HIV infection and substance abuse disorders. AIDS Care. 2004;16(6):744–755. doi: 10.1080/09540120412331269585. [DOI] [PubMed] [Google Scholar]
  • 34.Mugavero MJ, Castellano C, Edelman D, Hicks C. Late diagnosis of HIV infection: the role of age and sex. Am J Med. 2007;120(4):370–373. doi: 10.1016/j.amjmed.2006.05.050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Samet JH, Freedberg KA, Savetsky JB, Sullivan LM, Stein MD. Understanding delay to medical care for HIV infection: the long-term non-presenter. AIDS. 2001;15(1):77–85. doi: 10.1097/00002030-200101050-00012. [DOI] [PubMed] [Google Scholar]
  • 36.Louis C, Ivers LC, Smith Fawzi MC, Freedberg KA, Castro A. Late presentation for HIV care in central Haiti: factors limiting access to care. AIDS Care. 2007;19(4):487–491. doi: 10.1080/09540120701203246. [DOI] [PubMed] [Google Scholar]
  • 37.Braitstein P, Brinkhof MW, Dabis F, Schechter M, Boulle A, Miotti P, Wood R, Laurent C, Sprinz E, Seyler C, Bangsberg DR, Balestre E, Sterne JA, May M, Egger M. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet. 2006;367(9513):817–824. doi: 10.1016/S0140-6736(06)68337-2. [DOI] [PubMed] [Google Scholar]
  • 38.Calmy A, Pinoges L, Szumilin E, Zachariah R, Ford N, Ferradini L. Generic fixed-dose combination antiretroviral treatment in resource-poor settings: multicentric observational cohort. AIDS. 2006;20(8):1163–1169. doi: 10.1097/01.aids.0000226957.79847.d6. [DOI] [PubMed] [Google Scholar]
  • 39.Ferradini L, Jeannin A, Pinoges L, Izopet J, Odhiambo D, Mankhambo L, Karungi G, Szumilin E, Balandine S, Fedida G, Carrieri MP, Spire B, Ford N, Tassie JM, Guerin PJ, Brasher C. Scaling up of highly active antiretroviral therapy in a rural district of Malawi: an effectiveness assessment. Lancet. 2006;367(9519):1335–1342. doi: 10.1016/S0140-6736(06)68580-2. [DOI] [PubMed] [Google Scholar]
  • 40.Stringer JSA, Zulu I, Levy J, Stringer EM, Mwango A, Chi BH, Mtonga V, Reid S, Cantrell RA, Bulterys M, Saag MS, Marlink RG, Mwinga A, Ellerbrock TV, Sinkala M. Rapid scale-up of antiretroviral therapy at primary care sites in Zambia: Feasibility and early outcomes. JAMA. 2006;296(7):782–793. doi: 10.1001/jama.296.7.782. [DOI] [PubMed] [Google Scholar]
  • 41.WHO. Interim WHO Clinical Staging of HIV/AIDS and HIV/AIDS Case Definitions for Surveillance. 2005
  • 42.Vandenbruaene M, Colebunders R, Goeman J, Alary M, Farber CM, Kestens L, van Ham G, Van den Ende J, Van Gompel A, Van den Enden E, et al. Evaluation of two staging systems for HIV infection for use in developing countries. AIDS. 1993;7(12):1613–1615. doi: 10.1097/00002030-199312000-00011. [DOI] [PubMed] [Google Scholar]
  • 43.Kassa E, Rinke de Wit TF, Hailu E, Girma M, Messele T, Mariam HG, Yohannes S, Jurriaans S, Yeneneh H, Coutinho RA, Fontanet AL. Evaluation of the World Health Organization staging system for HIV infection and disease in Ethiopia: association between clinical stages and laboratory markers. AIDS. 1999;13(3):381–389. doi: 10.1097/00002030-199902250-00011. [DOI] [PubMed] [Google Scholar]
  • 44.Malamba SS, Morgan D, Clayton T, Mayanja B, Okongo M, Whitworth J. The prognostic value of the World Health Organisation staging system for HIV infection and disease in rural Uganda. AIDS. 1999;13(8):2555–2562. doi: 10.1097/00002030-199912240-00009. [DOI] [PubMed] [Google Scholar]
  • 45.Ghate MV, Mehendale SM, Mahajan BA, Yadav R, Brahme RG, Divekar AD, Paranjape RS. Relationship between clinical conditions and CD4 counts in HIV-infected persons in Pune, Maharashtra, India. Natl Med J India. 2000;13(4):183–187. [PubMed] [Google Scholar]
  • 46.Teck R, Ascurra O, Gomani P, Manzi M, Pasulani O, Kusamale J, Salaniponi FML, Humblet P, Nunn P, Scano F, Harries AD, Zachariah R. WHO clinical staging of HIV infection and disease, tuberculosis and eligibility for antiretroviral treatment: relationship to CD4 lymphocyte counts. The International Journal of Tuberculosis and Lung Disease. 2005;9:258–262. [PubMed] [Google Scholar]
  • 47.Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA for the Ambulatory Care Quality Improvement P. The AUDIT Alcohol Consumption Questions (AUDIT-C): An Effective Brief Screening Test for Problem Drinking. Arch Intern Med. 1998;158(16):1789–1795. doi: 10.1001/archinte.158.16.1789. [DOI] [PubMed] [Google Scholar]
  • 48.Saunders JB, Aasland OG, Babor TF, Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption-II. Addiction. 1993;88(6):791–804. doi: 10.1111/j.1360-0443.1993.tb02093.x. [DOI] [PubMed] [Google Scholar]
  • 49.Kagaayi J, Makumbi F, Nakigozi G, et al. WHO HIV clinical staging or CD4 cell counts for antiretroviral therapy eligibility assessment? An evaluation in rural Rakai district, Uganda. Aids. 2007 May 31;21(9):1208–1210. doi: 10.1097/QAD.0b013e32810c8dce. [DOI] [PubMed] [Google Scholar]
  • 50.Nabyonga J, Desmet M, Karamagi H, Kadama PY, Omaswa FG, Walker O. Abolition of cost-sharing is pro-poor: evidence from Uganda. Health Policy Plan. 2005;20(2):100–108. doi: 10.1093/heapol/czi012. [DOI] [PubMed] [Google Scholar]
  • 51.Biber CL, Jaker MA, Kloser P, Auerbach SB, Rhoads GG. A study of sex differences in presentation for care of HIV. AIDS Patient Care STDS. 1999;13(2):103–110. doi: 10.1089/apc.1999.13.103. [DOI] [PubMed] [Google Scholar]
  • 52.Guenter CD, Gill MJ, Samet JH, Freedberg KA, Stein MD. A population with short delay from diagnosis of Human Immunodeficiency Virus to medical care. Arch Intern Med. 1999;159(7):758–759. doi: 10.1001/archinte.159.7.758. [DOI] [PubMed] [Google Scholar]
  • 53.Klein H, Elifson KW, Sterk CE. "At risk" women who think that they have no chance of getting HIV: self-assessed perceived risks. Women Health. 2003;38(2):47–63. doi: 10.1300/J013v38n02_04. [DOI] [PubMed] [Google Scholar]
  • 54.Del Pierre C, Cuzin L, Lauwes-Cances V, Marchou B, Lang T. High-risk groups for late diagnosis of HIV infection: A need for rethinking testing policy in the general population. AIDS Patient Care and STDs. 2006;Volume 20(Number 12Number 12):838–847. doi: 10.1089/apc.2006.20.838. [DOI] [PubMed] [Google Scholar]
  • 55.Manavi K, McMillan A, Ogilvie M, Scott G. Heterosexual men and women with HIV test positive at a later stage of infection than homo- or bisexual men. International Journal of STD & AIDS. 2004;15:811–814. doi: 10.1258/0956462042563585. [DOI] [PubMed] [Google Scholar]
  • 56.Samet JH, Retondo MJ, Freedberg KA, Stein MD, Heeren T, Libman H. Factors associated with initiation of primary medical care for HIV-infected persons. Am J Med. 1994;97(4):347–353. doi: 10.1016/0002-9343(94)90301-8. [DOI] [PubMed] [Google Scholar]
  • 57.Samet JHa, Freedberg KAa, Savetsky JBa, Sullivan LMc, Stein MDd. Understanding delay to medical care for HIV infection: the long-term non-presenter. AIDS. 2001;15(1):77–85. doi: 10.1097/00002030-200101050-00012. [DOI] [PubMed] [Google Scholar]
  • 58.Castilla J, Sobrino P, De La Fuente L, Noguer I, Guerra L, Parras F. Late diagnosis of HIV infection in the era of highly active antiretroviral therapy: consequences for AIDS incidence. AIDS. 2002;16(14):1945–1951. doi: 10.1097/00002030-200209270-00012. [DOI] [PubMed] [Google Scholar]
  • 59.Couturier E, Schwoebel V, Michon C, Hubert JB, Delmas MC, Morlat P, Boue F, Simonpoli AM, Dabis F, Brunet JB. Determinants of delayed diagnosis of HIV infection in France, 1993–1995. AIDS. 1998;12(7):795–800. doi: 10.1097/00002030-199807000-00016. [DOI] [PubMed] [Google Scholar]
  • 60.Girardi E, Sampaolesi A, Gentile M, Nurra G, Ippolito G. Increasing proportion of late diagnosis of HIV infection among patients with AIDS in Italy following introduction of combination antiretroviral therapy. J Acquir Immune Defic Syndr. 2000;25(1):71–76. doi: 10.1097/00042560-200009010-00010. [DOI] [PubMed] [Google Scholar]
  • 61.Gupta SB, Gilbert RL, Brady AR, Livingstone SJ, Evans BG CD4 Surveillance Scheme Advisory Group. CD4 cell counts in adults with newly diagnosed HIV infection: results of surveillance in England and Wales, 1990–1998. AIDS. 2000;14(7):853–861. doi: 10.1097/00002030-200005050-00012. [DOI] [PubMed] [Google Scholar]
  • 62.Porter K, Wall PG, Evans BG. Factors associated with lack of awareness of HIV infection before diagnosis of AIDS. BMJ. 1993;307(6895):20–23. doi: 10.1136/bmj.307.6895.20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Sabin CA, Smith CJ, Gumley H, Murphy G, Lampe FC, Phillips AN, Prinz B, Youle M, Johnson MA. Late presenters in the era of highly active antiretroviral therapy: uptake of and responses to antiretroviral therapy. AIDS. 2004;18(16):2145–2151. doi: 10.1097/00002030-200411050-00006. [DOI] [PubMed] [Google Scholar]
  • 64.Gillieatt SJ, Mallal SA, French MA, Dawkins RL. Epidemiology of late presentation of HIV infection in Western Australia. Med J Aust. 1992;157(2):117–118. [PubMed] [Google Scholar]
  • 65.Bonjour M, Montagne M, Zambrano M, Molina G, Lippuner C, Wadskier F, Castrillo M, Incani R, Tami A. Determinants of late disease-stage presentation at diagnosis of HIV infection in Venezuela: A case-case comparison. AIDS Research and Therapy. 2008;5(1):6. doi: 10.1186/1742-6405-5-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Toure S, Kouadio B, Seyler C, Traore M, Dakoury-Dogbo N, Duvignac J, Diakite N, Karcher S, Grundmann C, Marlink R, Dabis F, Anglaret X. Rapid scaling-up of antiretroviral therapy in 10,000 adults in Cote d'Ivoire: 2-year outcomes and determinants. AIDS. 2008;22(7):873–882. doi: 10.1097/QAD.0b013e3282f768f8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Egger M, May M, Chêne G, Phillips AN, Ledergerber B, Dabis F, Costagliola D, Monforte ADA, de Wolf F, Reiss P, Lundgren JD, Justice AC, Staszewski S, Leport C, Hogg RS, Sabin CA, Gill MJ, Salzberger B, Sterne JAC. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. The Lancet. 2002;360(9327):119–129. doi: 10.1016/s0140-6736(02)09411-4. [DOI] [PubMed] [Google Scholar]
  • 68.The Antiretroviral Therapy Cohort C. Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies. AIDS. 2007;21(9):1185–1197. doi: 10.1097/QAD.0b013e328133f285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.CDC. Late versus early testing of HIV--16 Sites, United States, 2000–2003. MMWR Morb Mortal Wkly Rep. 2003;Vol. 52:581–586. [PubMed] [Google Scholar]
  • 70.Schoenborn CA, Marsh SL, Hardy AM. AIDS knowledge and attitudes for 1992. Data from the National Health Interview Survey. Adv Data. 1994;(243):1–16. doi: 10.1037/e608982007-001. [DOI] [PubMed] [Google Scholar]
  • 71.Antelman G, Smith Fawzi MC, Kaaya S, Mbwambo J, Msamanga GI, Hunter DJ, Fawzi WW. Predictors of HIV-1 serostatus disclosure: a prospective study among HIV-infected pregnant women in Dar es Salaam, Tanzania. Aids. 2001;15(14):1865–1874. doi: 10.1097/00002030-200109280-00017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 72.Medley A, Garcia-Moreno C, McGill S, Maman S. Rates, barriers and outcomes of HIV serostatus disclosure among women in developing countries: implications for prevention of mother-to-child transmission programmes. Bull World Health Organ. 2004;82(4):299–307. [PMC free article] [PubMed] [Google Scholar]
  • 73.Late versus early testing of HIV--16 Sites, United States, 2000–2003. MMWR Morb Mortal Wkly Rep. 2003;52(25):581–586. [PubMed] [Google Scholar]
  • 74.Kalichman SC, Simbayi LC. HIV testing attitudes, AIDS stigma, and voluntary HIV counselling and testing in a black township in Cape Town, South Africa. Sex Transm Infect. 2003;79(6):442–447. doi: 10.1136/sti.79.6.442. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75.Weiser SD, Heisler M, Leiter K, Percy-de Korte F, Tlou S, DeMonner S, Phaladze N, Bangsberg DR, Iacopino V. Routine HIV testing in Botswana: a population-based study on attitudes, practices, and human rights concerns. PLoS Med. 2006;3(7):e261. doi: 10.1371/journal.pmed.0030261. [DOI] [PMC free article] [PubMed] [Google Scholar]

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