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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Am J Clin Nutr. Author manuscript; available in PMC Jun 1, 2009.
Published in final edited form as:
PMCID: PMC2474657
NIHMSID: NIHMS55089
Nutritional indicators of adverse pregnancy outcomes and mother-to-child transmission of HIV among HIV-infected women2
Saurabh Mehta, Karim P Manji, Alicia M Young, Elizabeth R Brown, Charles Chasela, Taha E Taha, Jennifer S Read, Robert L Goldenberg, and Wafaie W Fawzi
Departments of Nutrition and Epidemiology, Harvard School of Public Health, Boston, MA (SM and WWF); the Department of Pediatrics, Muhimbili University College of Health Sciences, Dar es Salaam, Tanzania (KPM); the Statistical Center for HIV/AIDS Research and Prevention, Fred Hutchinson Cancer Research Center, Seattle, WA (AMY and ERB); the University of North Carolina Project, Lilongwe, Malawi (CC); the Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD (TET); the Pediatric, Adolescent, and Maternal AIDS Branch, NICHD, NIH, DHHS, Bethesda, MD (JSR); and the Department of Obstetrics and Gynecology, Drexel University College of Medicine, Philadelphia, PA (RLG).
Address reprint requests and correspondence to S Mehta, Department of Nutrition, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115. E-mail: smehta/at/hsph.harvard.edu.
Background
Poor nutrition may be associated with mother-to-child transmission (MTCT) of HIV and other adverse pregnancy outcomes.
Objective
The objective was to examine the relation of nutritional indicators with adverse pregnancy outcomes among HIV-infected women in Tanzania, Zambia, and Malawi.
Design
Body mass index (BMI; in kg/m2) and hemoglobin concentrations at enrollment and weight change during pregnancy were prospectively related to fetal loss, neonatal death, low birth weight, preterm birth, and MTCT of HIV.
Results
In a multivariate analysis, having a BMI < 21.8 was significantly associated with preterm birth [odds ratio (OR): 1.82; 95% CI: 1.34, 2.46] and low birth weight (OR: 2.09; 95% CI: 1.41, 3.08). A U-shaped relation between weight change during pregnancy and preterm birth was observed. Severe anemia was significantly associated with fetal loss or stillbirth (OR: 3.67; 95% CI: 1.16, 11.66), preterm birth (OR: 2.08; 95% CI: 1.39, 3.10), low birth weight (OR: 1.76; 95% CI: 1.07, 2.90), and MTCT of HIV by the time of birth (OR: 2.26; 95% CI: 1.18, 4.34) and by 4−6 wk among those negative at birth (OR: 2.33; 95% CI: 1.15, 4.73).
Conclusions
Anemia, poor weight gain during pregnancy, and low BMI in HIV-infected pregnant women are associated with increased risks of adverse infant outcomes and MTCT of HIV. Interventions that reduce the risk of wasting or anemia during pregnancy should be evaluated to determine their possible effect on the incidence of adverse pregnancy outcomes and MTCT of HIV.
The interplay between nutrition and infection is well established (1); poor nutrition predisposes to disease acquisition and progression, and disease leads to worsening of nutritional status. In the context of pregnancy and HIV infection, poor nutritional status, preexistent or as a result of HIV-induced wasting or weight loss, is likely to increase the risk of mother-to-child transmission (MTCT) of HIV (2). Additionally, poor nutrition as reflected by short stature, low body mass index (BMI), poor weight gain during pregnancy, and a low hemoglobin concentration is an established risk factor for adverse pregnancy outcomes such as low birth weight, fetal loss, preterm birth, and intrauterine growth retardation among HIV-uninfected women (39). Wasting, defined as involuntary weight loss (10), is one of the hallmarks of HIV disease. Furthermore, anemia is known to be the most frequent hematologic abnormality of HIV disease (11). Hence, we expect HIV infection to lead to a greater risk of adverse pregnancy outcomes in infected women, as has been suggested in some studies (2, 12). However, these studies were conducted in an era when no interventions for the prevention of MTCT of HIV, such as nevirapine (NVP) prophylaxis, were available. Thus, the association between poor nutritional status and MTCT of HIV and adverse pregnancy outcomes is unknown in HIV-infected women who receive such interventions.
We analyzed data from the HIVNET 024 trial (13), a randomized controlled trial of antepartum and peripartum antibiotics to prevent chorioamnionitis-associated MTCT and preterm birth, and examined the associations between maternal BMI and hemoglobin at enrollment and subsequent weight gain or loss during pregnancy and adverse pregnancy outcomes and MTCT of HIV.
HPTN 024 trial
The study design and population of the HPTN 024 trial were described in detail elsewhere (13). Briefly, this trial was conducted from July 2001 to August 2003 at 4 sites in 3 African countries: Blantyre and Lilongwe, Malawi; Dar es Salaam, Tanzania; and Lusaka, Zambia. The study protocol was approved by each of the US and foreign collaborating Institutional Review Boards. HIV-infected women were randomly assigned at 20−24 wk of gestation to receive either antibiotics (metronidazole plus erythromycin antenatally and metronidazole plus ampicillin intrapartum) or placebo. All women self-administered 200 mg NVP at the onset of labor, and the infants were given a 2-mg/kg dose of NVP syrup within the first 72 h of life in accordance with the HIVNET 012 antiretroviral prophylaxis regimen (14). After enrollment, women were followed through the remainder of the pregnancy, through delivery, and 1 y postpartum.
Information was collected on sociodemographic characteristics, such as years of education; anthropometric measures, including weight and height; and laboratory variables, namely, CD4 cell counts, plasma HIV RNA concentrations (viral loads), and hemoglobin concentrations on enrollment into the study (20−24 wk of gestational age). Additionally, information on weight also was collected during the second (26−30 wk of gestational age) and third (36 wk of gestational age) prenatal visits. The infant's gestational age in weeks, birth weight in grams, and occurrence of adverse events such as neonatal mortality (death before 29 d of age) were recorded. Gestational age was determined by using 3 methods: 1) fundal height (uterine size in centimeters measured from the pubic symphysis to the uterine fundus), 2) the modified Ballard examination (15) performed at delivery or within 48 h of birth, and 3) the calculation of expected date of delivery from the date of last menstrual period as recalled by the participant.
The infant's HIV infection status was determined by testing blood samples collected as dried blood spots via heel stick at birth and at 6 wk and 12 mo of age. These dried blood spots were tested by RNA polymerase chain reaction (PCR) from whole blood. Organon-Teknika NucliSens (Organon-Teknika, Durham, NC) was used for the Malawi and Zambia sites; whereas Roche Amplicor v1.5 (Roche Diagnostics, Branchburg, NJ) was used for samples from the Tanzania sites. All tests were performed at a reference laboratory (University of North Carolina, Chapel Hill, NC).
Study population and variables for this analysis
For the analyses reported in this article, we included all HIV-infected women enrolled in the HIVNET 024 study for whom delivery information was available. We identified 3 main markers of maternal nutritional status, namely BMI and hemoglobin (both assessed at study enrollment) and weight change during pregnancy. BMI was calculated by dividing the weight (in kg) by the square of height (in m). Because there are no standard cutoffs for BMI for pregnant women at 20−24 wk of gestation, and because the conventional cutoffs from the US Centers for Disease Control and Prevention (16) for nonpregnant adults are more applicable to populations in developed countries, BMI was categorized on the basis of tertiles of BMI in the study population. Furthermore, BMI is expected to vary by week of gestation at the first visit, and hence an arbitrary cutoff point may not be applicable. Hemoglobin concentrations were categorized into 3 groups: severe anemia (<8.5 g/dL), mild-to-moderate anemia (8.5−10.9 g/dL), and no anemia (≥11 g/dL), based on cutoffs used for referral to district hospitals in Tanzania (17).
Because weight was measured at 3 time points before delivery, we performed 2 additional sets of analyses to estimate the associations between weight change and birth outcome. The first subset included all births after 30 wk, and the rate of weight change was calculated as the difference between the weights at enrollment and the second visit divided by the time between the visits. The second subset included only births after 36 wk, and the rate of weight change was estimated for each woman using least squares based on all 3 measurements (or only 2 if a measurement was missing). Associations between weight change and the outcomes were assessed with weight change as a continuous as well as a categorical covariate. Weight loss was defined as a rate of weight change ≤0 kg/wk. Low, normal, and high weight gain were defined as ≤25th percentile, >25th percentile to ≤75th percentile, and >75th percentile of the positive weight gain distribution.
The primary outcomes of interest were adverse pregnancy outcomes, including fetal loss or stillbirth, neonatal mortality (defined as death of the infant before 29 d of age), preterm birth (defined as delivery before 37 wk of gestation determined by fundal height), and low birth weight (defined as birth weight <2500 g). MTCT of HIV was assessed at 2 time points: 1) at birth and 2) at 4−6 wk after birth. Transmission was assumed to have occurred in utero if the birth RNA PCR assay result was positive. If the birth specimen RNA PCR assay result was negative but the test at week 6 was positive, the infection was classified as having occurred in the intrapartum/early postnatal period (18).
Statistical analyses
Chi-square tests were performed to test for associations between categorical variables. One-way analysis of variance tests were performed to compare the means of continuous characteristics by the levels of categorical variables. To explore the overall shape of the relation between each nutritional measure and each adverse birth outcome, generalized additive models were fit and plots of the nutritional measures against the predicted probability of the outcome were generated. Logistic regression models were fit to assess the associations between adverse birth outcomes and the nutritional markers. Censored multinomial models (19) were fit to assess the associations between MTCT of HIV and the nutritional markers. The multivariate models included the nutritional measures and were adjusted for age, CD4 count and viral load at enrollment, and site. Additionally, when a quadratic relation was suggested by the generalized additive models, a squared term for that predictor was included in the model. Pearson correlation coefficients between maternal weight and infant birth weight were also calculated, and exploratory scatterplots were created. All analyses were conducted by using SAS version 9.1 (SAS Institute Inc, Cary, NC) (20).
A total of 2294 eligible HIV-infected women were randomly assigned in the parent HIVNET 024 trial described above. Seven women died before delivery, and 160 women were lost to follow-up. Of 2127 women who were known to have delivered, delivery information was available for 2126 (ie, 92.7% of eligible women). Therefore, the study population comprised 2126 HIV-infected women and their infants.
The baseline maternal characteristics of the study population of 2126 mothers, overall and according to BMI and hemoglobin at enrollment and weight change during pregnancy, are summarized in Table 1. BMI (kg/m2) was categorized into the following groups based on tertiles: <21.8, 21.8−23.9, and ≥24.0. A higher BMI was significantly associated with older age, higher hemoglobin, and lower cervical and plasma viral load. A higher hemoglobin concentration was significantly associated with younger age, lower gestational age at enrollment, higher weight, higher BMI, higher CD4 cell count, and lower cervical and plasma viral loads at enrollment. Weight change was categorized into the following groups: ≤0 kg/wk, 0.01−0.18 kg/wk (≤25th percentile), 0.19−0.41 kg/wk (>25th percentile to ≤75th percentile), and ≥0.42 kg/wk (>75th percentile of the positive weight gain distribution). Weight change was associated with age, gestational age, weight, BMI, hemoglobin, and cervical and plasma viral loads.
TABLE 1
TABLE 1
Maternal characteristics by BMI and hemoglobin at enrollment and weight change during pregnancy
Infant outcomes, overall and according to maternal BMI and hemoglobin at enrollment and weight change during pregnancy, are shown in Table 2. Lower maternal BMI was associated with preterm birth and low birth weight. Lower maternal hemoglobin concentrations were associated with preterm birth, low birth weight, fetal loss or stillbirth, and neonatal death. Weight change during pregnancy was associated with preterm birth, low birth weight, and fetal loss or stillbirth. The associations of BMI, maternal hemoglobin, and weight change during pregnancy with preterm birth remained the same regardless of the measure of gestational age used (Ballard examination and last menstrual period–based numbers not shown).
TABLE 2
TABLE 2
Infant outcomes by maternal BMI and hemoglobin at enrollment and weight change during pregnancy
Lower maternal BMI and hemoglobin also were associated with an increased risk of MTCT of HIV (Table 3). When assessed at birth, MTCT of HIV was significantly higher in women who were severely anemic (hemoglobin <8.5 g/dL) at baseline (13%; 95% CI: 9%, 17%) compared with women with hemoglobin ≥11 g/dL at baseline (5%; 95% CI: 3%, 7%). The overall risk of HIV infection at 4−6 wk (including those testing positive at birth) was 28% (95% CI: 22%, 34%) in women who had severe anemia: 16% (95% CI: 14%, 18%) in women with moderate anemia (8.5≤hemoglobin <11 g/dL), and 9% (95% CI: 7%, 12%) in women with hemoglobin ≥11 g/dL at baseline. The corresponding numbers by maternal BMI at enrollment were 17% (95% CI: 14%, 20%) in women in the lowest tertile of BMI, 17% (95% CI: 15%, 19%) in women in the middle tertile of BMI, and 12% (95% CI: 9%, 14%) in women in the highest tertile of BMI.
TABLE 3
TABLE 3
Mother-to-child transmission of HIV by maternal BMI and hemoglobin at enrollment and weight change during pregnancy1
We had information on weight change between 2 visits only on the women who delivered after 30 wk. Hence, we excluded the 67 women who delivered before 30 wk of gestational age from further analysis. Furthermore, the results for deliveries after 30 wk and for deliveries after 36 wk were similar, except for some outcomes, which are noted below. Therefore, the results presented in Tables 4, ,5,5, and 66 and in the figures refer to deliveries after 30 wk (n = 2059) unless otherwise specified.
TABLE 4
TABLE 4
Multivariate analysis of preterm birth
TABLE 5
TABLE 5
Multivariate analysis of low birth weight (<2500 g)
TABLE 6
TABLE 6
Multivariate analysis of fetal loss/stillbirth, neonatal death, and HIV infection
In multivariate analysis (Table 4), women with BMI in the lowest tertile had 1.82 times greater odds of delivering a preterm infant compared with women with BMI in the highest tertile (95% CI: 1.34, 2.46; P < 0.01). In models with continuous predictors, a decrease in 1 kg/m2 in BMI was associated with a 1.10 times greater odds of preterm birth [95% CI: 1.06, 1.16; P < 0.01; adjusted for age, CD4 count, plasma viral load (log), and site]. Women with severe anemia had a 2.08 times greater odds of delivering a preterm infant than did women with a hemoglobin concentration ≥11 g/dL (95% CI: 1.39, 3.10; P < 0.01). In models with continuous predictors, a 1 g/dL decrease in hemoglobin was associated with 1.14 times greater odds of preterm birth [95% CI: 1.05, 1.25; P < 0.01; adjusted for age, CD4 count, plasma viral load (log), and site].
Because the generalized additive models suggested a quadratic relation between weight change and preterm birth and between weight change and low birth weight, a squared weight change term was included in the model. The log odds ratios (ORs) of preterm birth for women losing 0.1−0.7 kg/wk or gaining 0.1−1 kg/wk, compared with women with no weight change (0 kg/wk), are shown in Figure 1. The values corresponding to the ORs and CIs shown in the plots are provided in Table 4. These plots indicate that women losing weight had a higher odds of preterm birth than did women remaining at the same weight, and the odds of preterm birth increased as weight loss increased. Gaining >0.9 kg/wk also was associated with an increased odds of preterm birth compared with not gaining or losing any weight.
FIGURE 1
FIGURE 1
Log odds ratios of preterm birth (deliveries after 30 wk) for weight change compared with no weight change (0 kg/wk). Values are estimates from an adjusted model with continuous nutritional predictors.
When adjusted for maternal age, CD4 count, plasma viral load, and site, both BMI and hemoglobin were significantly associated with low birth weight (Table 5); women with a BMI in the lowest tertile had a 2.09 times greater odds of delivering an infant with low birth weight compared with women with BMI in the highest tertile (95% CI: 1.41, 3.08; P < 0.01). In models with continuous predictors, a 1-kg/m2 decrease in BMI was associated with a 1.13 times greater odds of having an infant with a low birth weight [95% CI: 1.06, 1.20; P < 0.01; adjusted for age, CD4 count, plasma viral load (log), and site]. Similarly, women with severe anemia had a 1.76 times greater odds of delivering a low-birth-weight infant compared with women with a hemoglobin concentration ≥11 g/dL (95% CI: 1.07, 2.90; P = 0.03). When the analysis was restricted to deliveries after 36 wk (data not shown), the magnitude of the ORs of low birth weight for the covariates was similar, although the relation with hemoglobin became nonsignificant (P = 0.06); these results suggest that the effect of BMI and hemoglobin on low birth weight is independent of their effect on preterm birth.
As with preterm birth, a quadratic relation between weight change and low birth weight was indicated in generalized additive models. Hence, a weight change squared term was included in the multivariate model. The results suggest that women losing weight had a higher odds of low birth weight than did women remaining at the same weight, and the odds of low birth weight increased as weight loss increased (Figure 2). Women gaining between 0.1 and 0.6 kg/wk had a lower odds of low birth weight than did women whose weight remains the same. Similar results were obtained when the analysis was restricted to deliveries after 36 wk (data not shown).
FIGURE 2
FIGURE 2
Log odds ratios of low birth weight (deliveries after 30 wk) for weight change compared with no weight change (0 kg/wk). Values are estimates from an adjusted model with continuous nutritional predictors.
Although BMI was not a significant predictor of fetal loss or stillbirth (Table 6), both weight change and hemoglobin were significant predictors of fetal loss or stillbirth in the unadjusted and adjusted models. In models with continuous predictors, a 1-g/dL decrease in hemoglobin was associated with a 1.5 times greater odds of fetal loss or stillbirth [95% CI: 1.19, 1.89; P < 0.01; adjusted for age, CD4 count, plasma viral load (log), and site]. Women with severe anemia (hemoglobin < 8.5 g/dL) had a 3.67 times greater odds of fetal loss or stillbirth compared with women with hemoglobin ≥ 11 g/dL after adjustment for age, CD4 cell count, viral load, and site. A one kilogram per week decrease in weight change was associated with lower odds of fetal loss or stillbirth [OR: 0.28; 95% CI: 0.09, 0.91; P = 0.03; adjusted for age, CD4 counts, plasma viral load (log), and site]. When the analysis was restricted to women delivering after 36 wk, the magnitude of the ORs with severe anemia was similar; however, the associations became non-significant (data not shown).
In the adjusted model, only weight change was a significant predictor of neonatal death (Table 6). A 1-kg/wk decrease in weight change was associated with a 4.36-fold increase in the odds of neonatal death [95% CI: 1.57, 12.11; P < 0.01; adjusted for age, CD4 count, plasma viral load (log), and site]. However, none of the nutritional markers were significantly associated with neonatal death when the analysis was limited to deliveries after 36 wk (data not shown).
BMI was not significantly associated with MTCT at birth (Table 6); however, women with severe anemia had a 2.26 times higher odds of MTCT of HIV compared with women with hemoglobin ≥11 g/dL. In models with continuous predictors, a 1-g/dL decrease in hemoglobin was associated with a 1.17 times greater odds of MTCT at birth [95% CI: 1.02, 1.34; P = 0.03; adjusted for age, CD4 count, plasma viral load (log) and site]. Only severe anemia was a significant predictor of MTCT at birth in the analyses restricted to deliveries after 36 wk (OR: 2.48; 95% CI: 1.17, 5.26; P = 0.02; data not shown).
Neither BMI nor weight change was a significant predictor of MTCT of HIV at 4−6 wk among those negative at birth (Table 6). However, women with severe anemia had a 2.33 times greater odds of MTCT of HIV compared with women with hemoglobin ≥11 g/dL. A similar relation was observed between severe anemia and risk of MTCT when the analyses were restricted to deliveries after 36 wk (data not shown).
In this prospective study of HIV-infected women, we found that poor nutritional status as characterized by low BMI at the first prenatal visit was associated with preterm birth and low birth weight. The risk of preterm birth increased with increasing weight loss or excessive weight gain. Weight loss during pregnancy also was associated with a significantly increased risk of neonatal death. In this study, maternal anemia was associated with increased risks of fetal loss or stillbirth, preterm birth, low birth weight, and MTCT of HIV at birth and at 4−6 wk among those negative at birth.
These findings are consistent with those of studies in HIV-uninfected populations. For example, in a review of 46 national surveys from 36 developing countries, low maternal BMI was associated with low birth weight and neonatal mortality (21). Poor weight gain during pregnancy also is known to be associated with risk of preterm birth (5, 22), low birth weight (3, 23), and fetal loss (24, 25). On the other hand, maternal overweight and obesity also are known to increase the risk of adverse obstetric and neonatal outcomes (26, 27), whereas excessive maternal weight gain is associated with macrosomia (23) and large-for-gestational age infants and pre-eclampsia (28).
Similar associations have been reported between maternal anthropometric measures and MTCT of HIV. Low maternal midupper arm circumference was found to be associated with intrapartum and early postnatal transmission in Zimbabwe (29). In Tanzania, maternal weight loss during pregnancy was strongly associated with the risk of MTCT of HIV, independent of maternal CD4 cell count and plasma viral load (2). In Malawi, no association was reported between BMI at first prenatal visit, which occurred during the second or third trimester, and MTCT; however, this study assessed HIV infection status at 1 y after birth (30).
Low baseline BMI is a marker of minimal maternal nutrient reserves. Severe protein-energy malnutrition could be responsible for adverse pregnancy outcomes (2), as suggested by studies in which protein-energy supplementation of HIV-uninfected pregnant women improved maternal weight gain and fetal growth and decreased the risks of stillbirth and low birth weight (3133). Suboptimal intakes of micronutrients such as calcium, vitamins B-6 and B-12, and folate also may play a role (3437). This may be especially true for HIV-infected women, as suggested by results from micronutrient supplementation trials in Tanzania, in which supplementation of HIV-infected pregnant women with vitamins B, C, and E lowered the risks of low birth weight, preterm birth, and fetal loss by almost 40% (38).
Poor weight gain again may partly be due to a lack of protein-energy availability to the fetus, although the exact biological mechanism is unknown (39). Weight loss during pregnancy is likely to occur at the expense of maternal rather than fetal tissues and may therefore constitute an indicator of maternal wasting in the course of HIV disease. Wasting, defined as involuntary weight loss, is one of the hallmarks of HIV disease. Metabolic disturbances that lead to wasting appear to represent an adaptive response to a generalized inflammatory state and are mediated by an increased secretion of pro-inflammatory cytokines, including tumor necrosis factor-α, interferon-γ, and interleukins-1 and -6 (40). The increase in these cytokines (41) could lead to an increase in placental inflammation, which could lead to increased susceptibility of the placenta to viral infection and replication (42) and a loss of integrity of the placental barrier. Wasting is also a strong predictor of adverse outcomes among HIV-infected individuals independent of other markers of disease progression (4346). This is supported by studies that have shown that wasting increased viral shedding in genital secretions and was significantly related to an increased rate of adverse birth outcomes, including fetal loss, low birth weight, and preterm delivery (12).
We noted that a low level weight gain during pregnancy appeared to be protective against fetal loss. The mechanism for such an effect is not clear; it might be that such low weight gain is associated with improved care provided to women with more advanced HIV disease, thus resulting in a lower risk of fetal loss. These surviving infants, however, might be at a higher risk of dying in the neonatal period, which may explain the adverse association observed between weight change and neonatal mortality. Furthermore, mothers who have a relatively better health status are more likely to carry into term, which is likely to explain the absence of this adverse association in deliveries after 36 wk.
We also found that anemia was very common in this population; 73% of the women had hemoglobin concentrations <11 g/dL. Severe anemia, defined as a hemoglobin concentration <8.5 g/dL, was present in 12% of the population. This is similar to the prevalence of anemia observed in other studies in HIV-infected pregnant women in developing countries (4749). Anemia is an established risk factor for higher maternal mortality and morbidity and adverse perinatal outcomes in HIV-uninfected women (5053). Many women, particularly in developing countries, enter pregnancy with little or no iron reserves, mainly because of poor nutrition but also because of closely spaced pregnancies, prolonged periods of lactation, and blood loss from postpartum hemorrhage (54). Also, an increased incidence of low birth weight in infants of anemic mothers has been observed in several studies (50, 5557). Given that maternal hemoglobin is required for oxygen transportation across the placenta, anemia may compromise oxygen delivery to the growing fetus, which potentially leads to intrauterine growth retardation and low birth weight (58).
Anemia is also a common hematologic abnormality in HIV disease (11) and is an independent predictor of mortality (59, 60), progression to AIDS (61, 62), and decreased quality of life (63) among HIV-infected individuals. An explanation for our results could be that anemia is a marker of advanced HIV disease and hence is associated with adverse pregnancy outcomes and MTCT of HIV.
The major limitation of this study is its observational design; lower BMI, more severe anemia, or poorer weight gain during pregnancy may be a consequence of advanced HIV disease, which is more likely to be associated with increased risk of adverse pregnancy outcomes and MTCT of HIV. However, we adjusted for most known confounders such as CD4 cell counts and viral load, which are determinants of HIV disease stage.
Our findings have important implications for the prevention of adverse pregnancy outcomes and MTCT of HIV. The women in this study received NVP prophylaxis to prevent MTCT of HIV; however, poor nutritional status remained a marker of increased risk of MTCT of HIV. Interventions that lower the risk of wasting during HIV disease and treat and prevent anemia could be potentially efficacious adjunct modalities to strategies such as antiretroviral prophylaxis to decrease the risk of MTCT of HIV, and trials that randomly assign women to these interventions are warranted. Such interventions could include protein-energy and micronutrient supplementation and the treatment of infections such as malaria, intestinal parasitic infections, and other opportunistic infections (64, 65)—all cofactors in the etiology of malnutrition among HIV-infected women.
Acknowledgments
We are grateful to the mothers and children who participated in this study and to the entire study team at each site for their dedication and excellent collaboration.
The authors’ responsibilities were as follows—SM, KPM, WWF, and AMY: contributed to the plans for data analysis; SM: interpreted the data and wrote the initial draft of the manuscript; AMY: analyzed and assisted with the data interpretation; ERB: provided statistical guidance and helped interpret the data; and TET, RLG, WWF, JSR, KPM, and CC (trial investigators): contributed to the study design and implementation. All coauthors participated in the manuscript preparation. None of the authors had a personal or financial conflict of interest.
The HPTN 024 team consisted of the following persons—Protocol Cochairs: Taha E Taha (Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD) and Robert Goldenberg (University of Alabama at Birmingham). In-Country Cochairs/Investigators of Record: Newton Kumwenda and George Kafulafula (Blantyre, Malawi), Francis Martinson (Lilongwe, Malawi), Gernard Msamanga (Dar es Salaam, Tanzania), and Moses Sinkala and Jeffrey Stringer (Lusaka, Zambia). US Cochairs: Irving Hoffman (University of North Carolina, Chapel Hill, NC) and Wafaie Fawzi (Harvard School of Public Health, Boston, MA). In-Country Investigators, Consultants, and Key Site Personnel: Robin Broadhead, George Liomba, Johnstone Kumwenda, Tsedal Mebrahtu, Pauline Katunda, and Maysoon Dahab (Blantyre, Malawi); Peter Kazembe, David Chilongozi, Charles Chasela, George Joaki Willard Dzinyemba, and Sam Kamanga (Lilongwe, Malawi); Elgius Lyamuya, Charles Kilewo, Karim Manji, Sylvia Kaaya, Said Aboud, Muhsin Sheriff, Elmar Saathoff, Priya Satow, Iluminata Ballonzi, Gretchen Antelman, and Edgar Basheka (Dar es Salaam, Tanzania); Victor Mudenda, Christine Kaseba, Maureen Njobvu, Makungu Kabaso, Muzala Kapina, Anthony Yeta, Seraphine Kaminsa, Constantine Malama, Dara Potter, Maclean Ukwimi, Alison Taylor, Patrick Chipaila, and Bernice Mwale (Lusaka, Zambia). US Investigators, Consultants, and Key Site Personnel: Priya Joshi, Ada Cachafeiro, Shermalyn Greene, Marker Turner, Melissa Kerkau, Paul Alabanza, Amy James, Som Siharath, and Tiffany Tribull (University of North Carolina, Chapel Hill, NC); Saidi Kapiga and George Seage (Harvard School of Public Health, Boston, MA); Sten Vermund, William Andrews, and Deedee Lyon (University of Alabama at Birmingham). National Institute of Allergy and Infectious Diseases Medical Officer: Samuel Adeniyi-Jones. National Institute of Child Health and Human Development Medical Officer: Jennifer S Read. Protocol Pharmacologist: Scharla Estep. Protocol Statisticians: Elizabeth R Brown, Thomas R Fleming, Anthony Mwatha, Lei Wang, and Ying Q Chen. Protocol Virologist: Susan Fiscus. Protocol Operations Coordinator: Lynda Emel. Data Coordinators: Debra J Lands and Ceceilia J Dominique. Systems Analyst Programmers: Alice H Fisher and Martha Doyle. Protocol Specialist: Megan Valentine.
Footnotes
2Supported by the HIV Network for Prevention Trials and sponsored by the US National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, through contract N01-AI-035173 with Family Health International; contract N01-AI-045200 with Fred Hutchinson Cancer Research Center; and subcontract N01-AI-035173-117/412 with Johns Hopkins University. Also supported by the HIV Prevention Trials Network and sponsored by the National Institute of Child Health and Human Development, National Institute on Drug Abuse, National Institute of Mental Health, and Office of AIDS Research of the National Institutes of Health, US Department of Health and Human Services, Harvard University (U01-AI-048006), Johns Hopkins University (U01-AI-048005), and the University of Alabama at Birmingham (U01-AI-047972). Nevirapine (Viramune, Boehringer Ingelheim GmbH, Ingelheim, Germany) was provided by Boehringer Ingelheim Pharmaceuticals, Inc.
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