Predictors of adverse pregnancy outcomes in women infected with HIV in Latin America and the Caribbean: a cohort study




To examine maternal characteristics associated with adverse pregnancy outcomes among women infected with HIV.


Prospective cohort study.


Multiple sites in Latin America and the Caribbean.


Women infected with HIV enrolled in the Perinatal (2002–2007) and the Longitudinal Study in Latin American Countries (LILAC; 2008–2012) studies of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) International Site Development Initiative (NISDI).


Frequencies of adverse pregnancy outcomes assessed among pregnancies. Risk factors investigated by logistic regression analysis.

Main outcome measures

Adverse pregnancy outcomes, including preterm delivery (PT), low birthweight (LBW), small for gestational age (SGA), stillbirth (SB), and neonatal death.


Among 1512 women, 1.9% (95% confidence interval, 95% CI, 1.3–2.7) of singleton pregnancies resulted in a stillbirth and 32.9% (95% CI 30.6–35.4) had at least one adverse pregnancy outcome. Of 1483 singleton live births, 19.8% (95% CI 17.8–21.9) were PT, 14.2% (95% CI 12.5–16.1) were LBW, 12.6% (95% CI 10.9–14.4) were SGA, and 0.4% (95% CI 0.2–0.9) of infants died within 28 days of birth. Multivariable logistic regression modelling indicated that the following risk factors increased the probability of having one or more adverse pregnancy outcomes: lower maternal body mass index at delivery (odds ratio, OR, 2.2; 95% CI 1.4–3.5), hospitalisation during pregnancy (OR 3.3; 95% CI 2.0–5.3), hypertension during pregnancy (OR 2.7; 95% CI 1.5–4.8), antiretroviral use at conception (OR 1.4; 95% CI 1.0–1.9), and tobacco use during pregnancy (OR 1.7; 95% CI 1.3–2.2). The results of fitting multivariable logistic regression models for PT, LBW, SGA, and SB are also reported.


Women infected with HIV had a relatively high occurrence of adverse pregnancy outcomes, and some maternal risk factors were associated with these adverse pregnancy outcomes. Interventions targeting modifiable risk factors should be evaluated further.


The HIV epidemic has affected millions of women of childbearing age, worldwide. The mother-to-child transmission (MTCT) of HIV has been drastically reduced by means of universal testing for pregnant women, antiretroviral (ARV) treatment, use of elective caesarean delivery for women without viral suppression, and, in settings such as Latin America, the avoidance of breastfeeding.[1]

Besides HIV MTCT, other adverse pregnancy outcomes (APOs), such as preterm deliveries (PTs), low birthweight (LBW), small for gestational age (SGA), stillbirths, and neonatal deaths have been frequently reported among pregnancies complicated by HIV.[2-4]

It has been known that SGA, LBW, and PT are associated with increased neonatal mortality and significant long-term morbidity, including neurocognitive deficits, and chronic respiratory and metabolic problems.[5-8]

Some of the predictors for these outcomes have been described, but there is limited information from Latin America in the era of routine use of highly active ARV therapy (HAART).

Identifying the risk factors for APOs among women infected with HIV will help to allocate resources to interventions that may prevent these APOs in the future.


Study design and population

The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) International Site Development Initiative (NISDI) Perinatal Study (2002–2007) and the subsequent Longitudinal Study in Latin American Countries (LILAC; 2008–2012) are prospective cohort studies of pregnant women infected with HIV, and their infants, at participating clinical sites in Latin America and the Caribbean.[9] These protocols were designed to describe the characteristics of enrolled pregnant women and their infants, including the use of interventions to decrease the risk of HIV MTCT, use of ARV regimens, and maternal adverse events according to the use of ARVs. Women enrolled in the study were followed during pregnancy, through delivery, at hospital discharge, and 6–12 weeks postpartum. During each study visit, the participants' clinical, immunologic, and virologic characteristics were assessed through a physical examination, the evaluations of laboratory results, and a review of medical diagnoses made since the last visit. Prior to enrollment, all participants signed an approved informed consent for participation in the study.

Pregnant women who were enrolled in the NISDI Perinatal and LILAC protocols, and who met the following criteria, were included in the current analyses: first pregnancy after study enrollment, and either a live birth or a stillbirth. If a woman was enrolled in both protocols, the first pregnancy in the Perinatal protocol was chosen.

Outcome measures and risk factors

Gestational age (GA) was assessed by obstetricians using ultrasound, last menstrual period, and fundal height measurements. Adverse pregnancy outcomes of interest were derived using the following definitions: preterm delivery (PT), defined as a birth before 37 completed weeks of gestation; very preterm delivery, defined as a birth before 32 completed weeks of gestation; LBW, defined as a birthweight of <2500 g; very low birthweight (VLBW), defined as a birthweight of <1500 g; SGA, defined as a birthweight below the 10th percentile of a referent infant population at the same gestational age;[10] neonatal death, defined as the death of a liveborn infant in the first 28 days of life; and stillbirth, defined as a birth at 20 weeks of gestation or later with no signs of life. The composite variable APO was defined as the presence of one or more of the APOs described above.

Sociodemographic, clinical, and laboratory characteristics and obstetrical history, including previous preterm birth or stillbirth, among the recruited pregnant women were collected at enrollment. The HIV disease status was evaluated throughout the study, including the CD4 count, plasma HIV-1 RNA concentration, and CDC HIV clinical classification. Medications (ARV and non-ARV) taken by the participants were documented at each study visit, including drug names and start and stop dates. ARV use was categorised as: any ARV use; duration of ARV therapy during pregnancy; receipt of ARVs at conception; and reason for receiving ARVs during pregnancy (treatment versus prophylaxis according to local guidelines). For the purposes of analysis, ARV regimens were classified into three different time frames during pregnancy: most complex regimen received for ≥28 days during the entire pregnancy, and most complex regimen received for ≥28 days during the first or third trimester of pregnancy. The regimens were categorised as: HAART with a protease inhibitor (HAART PI), HAART without a PI (HAART not PI), and non-HAART regimens. Where relevant, participants were categorised as not receiving ARVs or not receiving a particular regimen for at least 28 days. HAART was defined as at least three different ARVs (except for ritonavir if used as a booster) from at least two distinct drug classes.

Prophylaxis for opportunistic infection during pregnancy was defined as receiving isoniazid (INH) during pregnancy in the absence of other drugs for tuberculosis (TB) infection or receiving TMP-SMX (trimethoprim-sulfamethoxazole) for at least 2 weeks during pregnancy for Pneumocystis pneumonia (PCP) prophylaxis.

Maternal substance abuse during pregnancy was recorded through maternal interview at enrollment. The presence of hypertension during pregnancy was defined on the basis of a diagnosis of eclampsia (seizures complicating hypertension during pregnancy), pre-eclampsia (hypertension after 20 weeks of gestation and proteinuria), pregnancy-induced hypertension (hypertension after 20 weeks of gestation without proteinuria), or chronic hypertension (hypertension preceding the current pregnancy or new onset before 20 weeks of gestation). Diabetes was defined on the basis of a new, continuing, or resolved diagnosis of type-I or -II diabetes mellitus, gestational diabetes, or pre-gestational diabetes, reported in the medical record.

Statistical methods

The prevalence of the defined APOs in the study population was computed with 95% confidence intervals (95% CIs) based on a binomial distribution. Contingency table analyses were used to examine associations of study outcomes with each of the risk factors; P values were calculated using the Fisher's exact or Fisher–Freeman–Halton exact test for categorical variables. The nonparametric Wilcoxon test was used to calculate P values for continuous variables. Missing values were excluded from the statistical tests.

Adjusted logistic regression analyses for each outcome started with a base model including all marginally significant candidate risk factors (P < 0.1) from the bivariate analyses. Among variables that were highly correlated, the one identified as the stronger predictor was included in the base model. Additional models fitted to the data to explore risk factor associations were compared using fit statistics [likelihood ratio test, Akaike's information criterion (AIC), c statistic, and goodness-of-fit test] to identify the best fitting model for the data.

All P values were two-sided with P < 0.05 being considered statistically significant. Analyses were performed using sas 9.2 (SAS Institute Inc., Cary, NC, USA).


Of the 1630 pregnant women enrolled, 1563 had first on-study pregnancies, including 1533 who had live-born infants and 30 who had stillbirths. Six out of the 1533 live births had no birthweight recorded, resulting in a total of 1527 mother–infant pairs being eligible for the initial analyses with birthweight-related study outcomes.

Among the 1483 participants who had live singleton births, 293 (19.8%) pregnancies resulted in preterm deliveries (95% CI 17.8–21.9), and 30 (2.0%) were very preterm deliveries (Table 1). Among the 1477 participants for whom birthweight was available, 210 (14.2%) live births were infants of low birthweight (95% CI 12.5–16.1), 19 (1.3%) were of very low birthweight, and 186 (12.6%) were SGA (95% CI 10.9–14.4). Six (0.4%) infants died within 28 days of birth (95% CI 0.2–0.9). Among the entire study population of singleton births, 29 (1.9%) pregnancies resulted in a stillbirth (95% CI 1.3–2.7). A total of 498 (32.9%) participants had at least one APO (95% CI 30.6–35.4). Table 1 also presents the prevalence of the study outcomes among all births and multiple births only; given the small number of multiple births and the difficulties this would pose for the analyses, models were not fitted for this group. As the numbers of outcomes of very preterm delivery, very low birthweight, and neonatal death were very small, no further analysis was performed for these outcomes either.

Table 1. Prevalence of adverse pregnancy outcomes and 95% confidence intervals in study population
Outcome variablesAll births n (prevalence; 95% CI)Multiple births n (prevalence; 95% CI)Singleton births n (prevalence; 95% CI)
  1. a

    Total population was 1527 for these outcomes because of missing values for birthweight.

  2. b

    Total population was 1477 for these outcomes because of missing values for birthweight.

Live births in study population n = 1533n = 50n = 1483
Preterm delivery324 (21.1; 19.1–23.3)31 (62.0; 47.2–75.4)293 (19.8; 17.8–21.9)
Very preterm delivery33 (2.2; 1.5–3.0)3 (6.0; 1.3–16.6)30 (2.0; 1.4–2.9)
Low birthweight246 (16.1; 14.3–18.0)a36 (72.0; 57.5–83.8)210 (14.2; 12.5–16.1)b
Very low birthweight23 (1.5; 0.9–2.3)a4 (8.0; 2.2–19.2)19 (1.3; 0.8–2.0)b
Small for gestational age204 (13.4; 11.7–15.1)a18 (36.0; 22.9–50.8)186 (12.6; 10.9–14.4)b
Neonatal death8 (0.5; 0.2–1.0)2 (4.0; 0.5–13.7)6 (0.4; 0.2–0.9)
Overall study population n = 1563n = 51n = 1512
Stillbirth30 (1.9; 1.3–2.7)1 (2.0; 0.05–10.5)29 (1.9; 1.3–2.7)
Any adverse pregnancy outcomes540 (34.5; 32.2–37.0)42 (82.4; 69.1–91.6)498 (32.9; 30.6–35.4)

Most participants were enrolled in Brazil (62.8%) and Argentina (24.5%), with smaller numbers in the Bahamas (2.8%), Jamaica (2.4%), Mexico (2.8%), and Peru (4.6%). The average age at delivery for these participants was 28.2 years (SD 5.9 years) and, on average, the duration of completed education was 8.0 years (SD 3.2 years). Among 815 participants who reported their ethnicity, 745 (91.4%) were Hispanic/Latino and 70 were either non-Hispanic/Latino or their ethnicity was unknown. Among 804 participants who reported their race, 58.0% were white, 20.4% were black, and 21.6% were of other races. A thorough description of the characteristics of the participants with singleton births, including an examination of the relationship of the characteristics with APOs, is provided in Table S1. In brief, the risk factors for APOs that were explored in bivariate analyses included maternal age, body mass index (BMI), history of stillbirths and preterm births, HIV disease characteristics (CD4+ lymphocyte count, plasma HIV RNA, ARV use during pregnancy, CDC clinical classification), substance use during pregnancy (alcohol, tobacco, marijuana, and crack/cocaine), hospitalisation during pregnancy, and maternal diagnoses during pregnancy (anaemia, urinary tract infection, upper and lower respiratory tract infections, syphilis, and hypertension during pregnancy).

Risk factors that were included in the final multiple logistic regression models for each of the APOs are summarised in Table 2. For the composite variable of any APO, a lower BMI at delivery (<18.5 kg/m2) increased the probability of APOs (OR 2.23, 95% CI 1.43–3.46), whereas a higher BMI (≥25 kg/m2) decreased the probability (OR 0.63, 95% CI 0.48–0.84). A similar relationship with BMI was also observed for LBW and SGA. Hospitalisation during pregnancy was associated with APOs (OR 3.25, 95% CI 1.98–5.34), as well as with PT and LBW. Hypertension during pregnancy was associated with a 2.7-fold increased risk of APOs, with similar increased risks observed for LBW and SGA. There was a 40% increased risk of APOs (primarily from PT) associated with the receipt of ARVs at conception. Tobacco use during pregnancy increased the risk of any APO by 71%, and by 78% specifically for SGA. Although not associated with risk of APOs, women diagnosed with a lower respiratory tract infection during pregnancy had a significantly increased risk of PT and SB (OR 2.34, 95% CI 1.03–5.31; OR 4.13, 95% CI 1.10–15.58, respectively).

Table 2. Risk factors in the final multiple logistic regression models for adverse pregnancy outcomesa
Risk factorPT OR (95% CI)LBW OR (95% CI)SGA OR (95% CI)SB OR (95% CI)APOs OR (95% CI)
  1. APOs, adverse pregnancy outcomes; CI, confidence interval; LBW, low birth weight; OR, adjusted odds ratio for the other risk factors in the models; PT, preterm delivery; SB, stillbirth; SGA, small for gestational age.

  2. a

    As none of the participants that had an SB used a non-HAART regimen during the third trimester, subjects that did not have an SB that used non-HAART during the third trimester were excluded from the model in order to fit this predictor.

Age of mother at delivery (years)
<25   0.95 (0.27–3.35) 
25–29   1.00 
>29   2.89 (1.05–7.90) 
BMI at or near delivery adjusted by GA (kg/m 2 )
Low (<18.5) 2.87 (1.72–4.79)3.25 (2.01–5.27) 2.23 (1.43–3.46)
Normal (18.5–24.9) 1.001.00 1.00
High (≥25) 0.60 (0.40–0.91)0.40 (0.26–0.64) 0.63 (0.48–0.84)
History of previous preterm birth
Yes1.92 (1.29–2.85)    
Hospitalisation during pregnancy
Yes3.56 (2.29–5.52)2.33 (1.27–4.26)  3.25 (1.98–5.34)
No1.001.00  1.00
Hypertension during pregnancy
Yes 3.73 (1.96–7.10)2.79 (1.36–5.74) 2.72 (1.54–4.80)
No 1.001.00 1.00
Lower respiratory tract infection (LRTI) during pregnancy
Yes2.34 (1.03–5.31)  4.13 (1.10–15.58) 
No1.00  1.00 
Most complex ARV regimen received at least 28 days during 3rd trimester
HAART with PI 0.59 (0.28–1.26) 0.14 (0.05–0.34) 
HAART w/o PI 0.33 (0.14–0.74) 0.11 (0.04–0.34) 
Non-HAART 0.40 (0.15–1.05)   
No ARVs or ARVs <28 days 1.00 1.00 
Receipt of ARVs at conception
Yes1.53 (1.11–2.09)   1.40 (1.04–1.87)
No1.00   1.00
Plasma HIV-1 RNA concentration at hospital discharge (copied/ml)
≥4001.47 (1.07–2.03)    
Reason for receiving ARVs during pregnancy
Treatment 1.80 (1.26–2.56)   
Prophylaxis 1.00   
Tobacco use during pregnancy
Yes  1.78 (1.24–2.54) 1.71 (1.30–2.24)
No  1.00 1.00


Main findings

We report the results of the largest study to date on APOs among women infected with HIV in Latin America. The findings indicate a substantial burden of APOs, with prevalences of PT, LBW, and SGA infants of 19.8, 14.2, and 12.6%, respectively, and prevalences of SB and neonatal death of 1.9 and 0.4%, respectively. The rates of these adverse outcomes among pregnant women infected with HIV, consistent with prior studies, are higher than those among women testing negative for HIV.[11, 12]

Strengths and limitations

The primary limitation of this study is the lack of a comparison group of pregnant women testing negative for HIV, which would have strengthened the study by enabling a more thorough investigation of risk factors associated with the study outcomes. The NISDI study was designed to characterise adverse events among women infected with HIV and their infants according to ARV exposure. Pregnant women testing negative for HIV were not included in the original study design, and budgetary constraints would not allow for a sample of these women to be enrolled at a later time for this investigation. Our analyses should therefore be interpreted as identifying risk factors for APOs among women infected with HIV.

The use of US-based data for defining SGA in this setting may have led to errors in our estimations; however, the exact extent and direction of these errors would be difficult to quantify given the relationship between birthweight and gestational age, according to ethnicity, found in US studies. When available in US studies, birthweight is generally found to be higher among Hispanics than among white, non-Hispanics up to about 37 weeks of gestation, after which it is higher for white, non-Hispanics.[9]

This study offers the advantage of having collected data on a large prospective cohort of women infected with HIV in Latin America from multiple participating sites, which provided high statistical power for the analyses of most study outcomes. Even so, small numbers of neonates with birthweights below 1500 g and small numbers born before 32 weeks of gestation limited our ability to evaluate these important outcomes further.

Data were collected using standardised case report forms, thereby ensuring better comparability of data collection across multiple sites, and across time as participants were enrolled and followed-up during the study. Unfortunately, detailed information was not collected on the reasons for hospitalisation in order to analyse this risk factor further.


The association of ARV exposure at the time of conception with APOs is similar to what has been previously described.[13-17] Previous studies of APOs related to the effect of HAART have reported conflicting results depending on the timing and type of ARV therapy, which may be confounded by other maternal risk factors in pregnancy.[15, 16, 18-23] Compared with ARV use for prophylaxis, the use of ARVs for treatment was associated with the occurrence of LBW, possibly as a proxy of the stage of maternal disease. The pathogenesis of preterm labour and the potential increased risk among women infected with HIV are not well understood. The inflammatory changes of immune reconstitution syndromes could play a role in women who started HAART at a low CD4 count, but other mechanisms may be involved in women with higher CD4 counts. Systemic or local genital tract immunology might be affected by ARVs and precipitate preterm labour, or induced changes in systemic cytokines could exacerbate hypertensive disorders and lead to preterm birth.[24, 25]

We also found that the use of ARVs during the third trimester of pregnancy reduced the occurrence of SB and LBW, compared with no ARV use or ARV therapy for <28 days. We should be cautious about interpreting the results of SB and LBW among women who did not receive ARVs during pregnancy, as these women may have had less access to antenatal care or may have delivered too early to have the opportunity to receive ARV therapy.

Our study indicates that hospitalisation during pregnancy is associated with having one or more APOs, particularly PT and LBW. Hospitalisations during pregnancy among HIV-infected individuals are mostly caused by acute infections and hypertensive conditions. Infections from the genitourinary tract, lung or gastrointestinal tract have been implicated in the occurrence of preterm delivery.[26] The mechanism by which these infections can promote preterm labour is thought to involve an acute inflammatory response. These conditions require early diagnosis and aggressive management to improve outcomes. An interesting finding of our study was the association between LRTI and APOs: although it is not impossible to rule out that LRTI might represent a marker of some other condition, it did not appear to simply represent a proxy for tobacco use or low CD4 count during pregnancy in our data. Pneumonia during pregnancy has been associated with LBW and an increased risk of preterm birth and serious maternal complications, including respiratory failure.[27] The incidence of bacterial pneumonia is higher than in non-HIV-infected populations, and pneumonia can occur at any stage of HIV disease and level of CD4 count. Individuals infected with HIV have an increased incidence of bacteraemia and mortality following pneumonia.[28] Pneumonia is frequently caused by Streptococcus pneumoniae, a pathogen that carries a high burden of disease, with enormous costs for treatment, including hospitalisations.[29] Most cases of pneumonia and subsequent hospitalisations could be prevented by increasing the coverage of pneumococcal vaccine for individuals infected with HIV, as recommended in practice guidelines.[29] Inactivated influenza vaccine should be administered annually to all patients infected with HIV prior to influenza season in order to prevent bacterial pneumonia as a complication of influenza illness. Both of these vaccines are suitable for pregnant women. Also, several therapies may decrease the risk for bacterial pneumonia, which include ARV use and TMP-SMX use as prophylaxis for PCP, when indicated.

Several potentially modifiable factors not directly related to HIV were also identified as increasing the risk of APOs. A history of preterm birth significantly increased the risk of having a preterm birth in a subsequent pregnancy, which has been widely reported.[30] While the management of women with previous preterm birth is beyond the scope of this discussion, women with such a history should have potential causes evaluated aggressively and be provided with any indicated treatment during subsequent pregnancies. We found that a low BMI (<18.5 kg/m2) at or near delivery was associated with an increased risk of APOs, particularly LBW and SGA. The association between being underweight and these outcomes has been previously described in both women infected with HIV and women testing negative for HIV.[14, 30-33] Women entering pregnancy with a low BMI should be counselled about appropriate weight gain and provided with nutritional supplementation, if needed. Our study also indicated that tobacco use during pregnancy was associated with APOs, even after adjusting for other risk factors. The literature has reported a dose-dependent association between smoking and SGA, PT, and SB.[18, 34, 35] Smoking during pregnancy has also been associated with poor adherence to ARV medications and to lower rates of virological suppression.[36, 37] Smoking cessation interventions should be offered to pregnant women who continue to smoke.

We also identified maternal hypertension during pregnancy as a risk factor for APOs. Hypertension during pregnancy may cause fetal growth restriction and increases the risk of pre-eclampsia, which could lead to medically indicated interruption of pregnancy and the risk of poor growth and stillbirth.[16, 38, 39] Older age at delivery (>29 years) in this cohort was associated with the occurrence of SB, which has also been observed among women testing negative for HIV.[40, 41] Although the biological mechanism for advanced maternal age increasing the probability of having an SB is unclear, a direct effect of aging on placental function, associated chronic diseases such as hypertension, and medical or obstetric complications are likely contributors.


This study demonstrates a high prevalence of APOs among women infected with HIV. Interventions to reduce risk factors identified in this analysis should be studied for their potential impact on reducing APOs. During pregnancy, underweight women may benefit from nutritional counselling, food or micronutrient supplementation, and closer monitoring.

Increasing the coverage of pneumococcal and influenza vaccines for women of childbearing age infected with HIV could potentially prevent LRTI and subsequent APOs. Behaviour modification for cigarette smoking, drug abuse, and alcohol consumption should also be encouraged.

Public health efforts should focus on supporting obstetrical and neonatal care for high-risk patients in developing countries, which will not only prevent MTCT of HIV, but also prevent the occurrence of stillbirths, neonatal death, and sequelae associated with prematurity.

As more women infected with HIV have intended or unintended pregnancies, additional effort is needed to identify women at high risk for APOs, which will allow the health support team to provide counselling to those at high risk and intensify support systems that address modifiable risk factors such as smoking, hypertension, lower respiratory tract infections, and low BMI.

Disclosure of interests

The authors have no interests to declare. The work described in this article was presented in part at the 17th Workshop on HIV Observational Databases, Cavtat, Croatia, 2013.

Contribution to authorship

SL carried out the statistical analysis, with support from RK, and drafted the article. RK, VHM, DFC, EJ, CMC, and JOA provided clinical management to study patients. HW, GKS, and all the previous mentioned authors contributed to the interpretation of the results, commented on all drafts of the article, and approved the final version.

Details of ethics approval

The protocols were approved by the ethical review board at each participating site, as well as by institutional review boards at the sponsoring institution (NICHD) and at the data management and statistical centre (Westat, Rockville, MD, USA).


The study was supported by NICHD contract no. N01-HD-3-3345 (2002–2007) and by NICHD contract no. HHSN267200800001C (NICHD control no. N01-HD-8-0001; 2007–2012).


Principal investigators, co-principal investigators, study coordinators, coordinating centre representatives, and NICHD staff include: Argentina, Buenos Aires, Marcelo H. Losso, Irene Foradori, Alejandro Hakim, Erica Stankievich, and Silvina Ivalo (Hospital General de Agudos José María Ramos Mejía); Brazil, Belo Horizonte, Jorge A. Pinto, Victor H. Melo, Fabiana Kakehasi, Beatriz M. Andrade (Universidade Federal de Minas Gerais); Caxias do Sul, Rosa Dea Sperhacke, Nicole Golin, Sílvia Mariani Costamilan (Universidade de Caxias do Sul/Serviço Municipal de Infectologia); Nova Iguaçu, Jose Pilotto, Luis Eduardo Fernandes, Gisely Falco (Hospital Geral Nova de Iguacu—HIV Family Care Clinic); Porto Alegre, Rosa Dea Sperhacke, Breno Riegel Santos, Rita de Cassia Alves Lira (Universidade de Caxias do Sul/Hospital Conceição); Rosa Dea Sperhacke, Mario Ferreira Peixoto, Elizabete Teles (Universidade de Caxias do Sul/Hospital Fêmina); Regis Kreitchmann, Luis Carlos Ribeiro, Fabrizio Motta, Debora Fernandes Coelho (Irmandade da Santa Casa de Misericordia de Porto Alegre); Ribeirão Preto, Marisa M. Mussi-Pinhata, Geraldo Duarte, Adriana A. Tiraboschi Bárbaro, Conrado Milani Coutinho, Fabiana Rezende Amaral, Anderson Sanches de Melo (Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo); Rio de Janeiro, Ricardo Hugo S. Oliveira, Elizabeth S. Machado, Maria C. Chermont Sapia (Instituto de Puericultura e Pediatria Martagão Gesteira); Esau Custodio Joao, Leon Claude Sidi, Maria Leticia Santos Cruz, Maria Isabel Gouvêa, Mariza Curto Saavedra, Clarisse Bressan, Fernanda Cavalcanti A. Jundi (Hospital Federal dos Servidores do Estado); São Paulo, Regina Celia de Menezes Succi, Prescilla Chow (Escola Paulista de Medicina- Universidade Federal de São Paulo); Peru, Lima, Jorge O. Alarcón Villaverde (Instituto de Medicina Tropical ‘Daniel Alcides Carrión’—Sección de Epidemiología, UNMSM), Carlos Velásquez Vásquez (Instituto Nacional Materno Perinatal), César Gutiérrez Villafuerte (Instituto de Medicina Tropical ‘Daniel Alcides Carrión’—Sección de Epidemiología, UNMSM); Data Management and Statistical Centre, Yolanda Bertucci, Rachel Cohen, Laura Freimanis Hance, René Gonin, D. Robert Harris, Roslyn Hennessey, James Korelitz, Margot Krauss, Sue Li, Karen Megazzini, Orlando Ortega, Sharon Sothern de Sanchez, Sonia K. Stoszek, Qilu Yu (Westat); NICHD, George K. Siberry, Rohan Hazra, Lynne M. Mofenson, Jennifer S. Read, D. Heather Watts (Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA).