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. 2012 Mar 21;27(6):1846–1856. doi: 10.1093/humrep/des090

Maternal HIV infection associated with small-for-gestational age infants but not preterm births: evidence from rural South Africa

James Ndirangu 1,*, Marie-Louise Newell 1,2, Ruth M Bland 1,3, Claire Thorne 2
PMCID: PMC3357196  PMID: 22442245

Abstract

BACKGROUND

 Human immunodeficiency virus (HIV) is prevalent in many countries where small-for-gestational age (SGA) and premature delivery are also common. However, the associations between maternal HIV, preterm delivery and SGA infants remain unclear. We estimate the prevalence of SGA and preterm (<37 weeks) births, their associations with antenatal maternal HIV infection and their contribution to infant mortality, in a high HIV prevalent, rural area in South Africa.

METHODS

Data were collected, in a non-randomized intervention cohort study, on all women attending antenatal clinics (2001–2004), before the availability of antiretroviral treatment. Newborns were weighed and gestational age was determined (based on last menstrual period plus midwife assessment antenatally). Poisson regression with robust variance assessed risk factors for preterm and SGA birth, while Cox regression assessed infant mortality and associated factors.

RESULTS

Of 2368 live born singletons, 16.6% were SGA and 21.4% were preterm. HIV-infected women (n= 1189) more commonly had SGA infants than uninfected women (18.1 versus 15.1%; P = 0.051), but percentages preterm were similar (21.8 versus 20.9%; P = 0.621). After adjustment for water source, delivery place, parity and maternal height, the SGA risk in HIV-infected women was higher [adjusted relative risk (aRR) 1.28, 95% confidence interval (CI): 1.06–1.53], but the association between maternal HIV infection and preterm delivery remained weak and not significant (aRR: 1.07, 95% CI: 0.91–1.26). In multivariable analyses, mortality under 1 year of age was significantly higher in SGA and severely SGA than in appropriate-for-gestational-age infants [adjusted hazard ratio (aHR): 2.12, 95% CI: 1.18–3.81 and 2.77, 95% CI: 1.56–4.91], but no difference in infant mortality was observed between the preterm and term infants (aHR: 1.18 95% CI: 0.79–1.79 for 34–36 weeks and 1.31, 95% CI: 0.58–2.94 for <34 weeks).

CONCLUSIONS

Maternal HIV infection increases the risk of SGA, but not preterm births, in this cohort.

Keywords: HIV, SGA, preterm, Africa, low birthweight

Introduction

Low birthweight (LBW) is a significant risk factor for infant mortality (Bhutta et al., 2005). LBW is commonly defined at a cut-off of 2500 g, and may be due to preterm delivery, growth restriction or both (Euser et al., 2008). In developed countries, LBW rates are low and caused mainly by prematurity while in developing countries, where the prevalence of LBW is >10% (Costello et al., 2001), LBW is often due to intrauterine growth restriction (IUGR) and often associated with small-for-gestational age (SGA) (Villar and Belizan, 1982; Kramer, 1987a,b). Prematurity SGA have heterogeneous etiologies (Rayco-Solon et al., 2005), and different outcomes for the infant (Verhoeff et al., 2001; Zeitlin et al., 2001; Rayco-Solon et al., 2005); SGA infants have poorer outcomes than appropriate-for-gestational age (AGA) infants, especially if they are preterm (Zeitlin et al., 2001). SGA is based on the percentile of the birthweight-for-gestational age and was not used to indicate IUGR in our study. Factors associated with SGA and preterm delivery include socio-economic status, short maternal stature and low parity (Kramer, 1987a,b; Verhoeff et al., 2001; Zeitlin et al., 2001). In developing country settings, it is important to understand factors associated with preterm births and SGA and their contribution to infant mortality, so that limited resources can be directed at those most at risk and so that the Millennium Development goal 4 aimed at reducing under-5 mortality by two-thirds between 1990 and 2015, can be achieved.

Human immunodeficiency virus (HIV) is highly prevalent in many of the countries where SGA and premature delivery are also common, and maternal HIV has been associated with adverse pregnancy outcomes such as spontaneous abortions, LBW and stillbirths (Langston et al., 1995; Rollins et al., 2007). However, the detail of associations between maternal HIV, preterm delivery and SGA infants remains unclear. In high HIV prevalence areas, some studies have reported a 70% increased risk of preterm delivery and a 40% increased risk of SGA associated with HIV (Bulterys et al., 1994; Taha et al., 1995), but this is not confirmed in other studies (Temmerman et al., 1994; Verhoeff et al., 2001). These inconsistent findings may be due to the lack of a standardized definition of SGA, difficulty in assessing gestational age or not adjusting for confounding factors (Brocklehurst and French, 1998; Verhoeff et al., 2001). The inability to obtain precise information on pregnancy duration in resource-limited settings has resulted in the use of birthweight as a proxy for gestational age in some studies (Temmerman et al., 1990; Taha et al., 1995). However, although birthweights are routinely recorded in health facilities, these are often not recorded in settings where a substantial number of births occur at home.

In this study, we estimate the prevalence of SGA and preterm births in a HIV prevalent, rural area in South Africa and evaluate the effect of maternal HIV infection on the risk of SGA or preterm births; we further quantify the contribution of SGA and preterm birth to infant mortality.

Materials and Methods

This vertical transmission study (VTS) enrolled HIV-infected and -uninfected pregnant women in nine antenatal clinics in two sites, the largest in rural Umkhanyakude district, northern KwaZulu-Natal and the other outside Durban, South Africa (Coovadia et al., 2007; Bland et al., 2010). Recruitment was from August 2001 to September 2004 with mothers and children followed for 2 years post-natally. Initially, all HIV-infected women and a systematic sample of uninfected women were enrolled in the study. However from July 2003, all women attending antenatal visits were offered enrolment before HIV testing. All pregnant women were tested for HIV and counselled at the antenatal clinic, by lay HIV counsellors, on infant feeding options according to the World Health Organization (WHO)/United Nations programme on AIDS recommendations current at that time (Bland et al., 2007). All HIV-infected women and their infants were offered single-dose nevirapine, but at the time of the study, antiretroviral treatment was not available through the public health services in South Africa. The study was approved by the Biomedical Research Ethics Committee of the University of KwaZulu-Natal.

Gestational age at delivery was determined on the basis of last menstrual period (collected at antenatal visits by trained study staff), unless adjusted by midwife assessment on the basis of a clinical assessment. Birthweight was measured by study staff or taken from clinic registers within 72 h of birth. For infants born at home, mothers brought their infant to the clinic the following day (or within 72 h) for immunization (BCG and polio), weighing and registration to obtain a road-to-health card (RTHC); this is the general practice in South Africa since without the RTHC, children cannot access public services such as clinics or school. These infants were weighed by the study staff. However, if women delivered in facilities outside the study area or study staff were not available, we used the weight documented by the Department of Health staff on the RTHC (Rollins et al., 2007).

Infants attended monthly clinic visits with a study nurse, scheduled from 6 weeks to 9 months of age, and thereafter quarterly to 24 months. All study clinic assistants who carried out anthropometric measurements at each visit received standardized anthropometry instructions with regular in-service training also given to ensure strict adherence to the techniques. The clinic manager conducted quality assurance checks of measurement techniques throughout the study. The same measuring equipment was used at all of the clinics with precision within 10 g for newborns while for older children, portable electronic weighing scales with taring capability and a precision to 100 g (UNICEF electronic scale 890) was used as recommended by WHO (de Onis et al., 2004). At approximately weekly intervals, the clinic manager checked calibration using standard metal weights. Further, each child had two weights recorded and if their difference was >100 g, a third measurement was taken and the two weights within 100 g were recorded; the mean value was calculated for this analysis (de Onis et al., 2004).

Dried blood spot (DBS) samples were collected from all HIV-exposed newborn infants within 72 h of birth, and then at each scheduled clinic visit to determine their HIV status. HIV status was established by quantitative HIV RNA assay with a sensitivity of 80 copies/ml (equivalent to 1600 copies per 50 µl DBS) (Bland et al., 2010). Infants were considered to be perinatally infected if the DBS sample taken at 4–8 weeks was positive, post-natally infected if the 4–8-week sample was negative and any subsequent sample was positive or infected with ‘timing unknown’ if the first sample was taken after 8 weeks and was positive.

In the antenatal period, socio-demographic and past and current pregnancy data were collected using structured questionnaires; post-natally, daily infant morbidity and feeding practices were documented at weekly intervals, and maternal weights, mid-upper arm circumference (MUAC) and height were measured (Bland et al., 2010). For these analyses, the weight and MUAC taken at 6 weeks post-delivery were used.

Definitions

Antenatal maternal HIV status was classified into HIV positive and negative; maternal CD4 count was measured in all HIV-positive women. LBW was defined as <2500 g (Kramer, 1987a,b). Infants were classified as preterm if the gestational age at birth was <37 completed weeks, and as SGA if below the 10th percentile of the birthweight-for-gestational age, as recommended by the WHO (WHO, 1995), with the US population-based reference used as the standard for comparability of the prevalence rates of SGA, and the potential effect of maternal HIV infection on SGA, with previous studies elsewhere in Africa (Alexander et al., 1996). To assess severely small-for-gestational-age infants, risk associations were further analyzed at a 3% cutoff (Oken et al., 2003). Size for gestational age was therefore categorized into three groups based on percentiles: AGA, ≥10%; SGA, 3 ≤ 10% and <3%, severely SGA. We only included singleton live births, given the increased risk of LBW and premature delivery for multiple birth; we also excluded stillbirths as four-fifths had missing birthweights. Place of delivery was classified into health facility and home. Parity was classified so as to compare primiparae with multiparae (Mansour et al., 2002) and was categorized as 0, 1–3 or ≥4. Based on the maternal enrollment clinic, residential area was classified as rural, peri-urban or urban, as most people in this setting are likely to attend their nearest clinic, with the median travel time of 81 min (Tanser, 2006). Neonatal mortality was defined as a death in the first 4 weeks of life (Lawn et al., 2005), while infant mortality was defined as the death by 12 months of age.

Statistical analysis

Data were analysed using Stata Version 11.2 (STATA Corps, College Station, TX, USA). Differences between HIV-infected and -uninfected women were assessed using t-test for continuous variables with normal distribution, χ2 test for categorical variables and Fisher's exact test if the numbers were small. Poisson regression, with a value of one attributed to each participant's follow-up time to obtain prevalence ratio estimates (done on all subjects and then separately among the HIV-positive and HIV-negative mothers), was used to assess factors associated with SGA and preterm delivery. To minimize overestimation of the relative risk when using Poisson regression for a categorical covariate of interest, a robust variance procedure was used (Lin and Wei, 1989). This method was considered to be a better alternative than the logistic regression for analysis of cross-sectional data, with the latter producing higher estimates than the former (Coutinho et al., 2008). For ease of comparison with other studies, we repeated our analyses using the conventional binary logistic regression and found essentially similar results to those presented here using Poisson regression. Variables were considered for inclusion in the multivariable model. Goodness-of-fit tests, assessed using the likelihood-based Akaike information criteria (AIC), were used to determine the variables that significantly improved the final Poisson models' fit (Bruin, 2006).

Mortality by maternal HIV status and SGA was assessed using Kaplan–Meier survival analysis. Follow-up time was computed as time from birth to withdrawal, loss to follow-up, migration or death if before the first year of life, whichever came first, allowing for child's HIV status as a time-varying variable for infant mortality analyses. Risk factors for infant mortality were assessed in univariable and multivariable Cox regression models with child HIV infection as a time-dependent variable; for the adjusted model, variables with a statistically significant association univariately were included in addition to three included (parity, maternal age and education) a priori (Ndirangu et al., 2010).

Results

There were 2811 live births in the cohort; 350 live births were excluded from the analysis: 76 (2.7%) had improbably high gestational age, 2 (0.1%) were missing birthweight and gestational age, 9 (0.3%) were missing gestational age only, 187 (6.7%) were missing birthweight data only and 76 (2.7%) had an improbable birthweight/gestational age combination (Fig. 1). A further 93 (3.3%) live births were excluded either because they were multiple births (86) or due to indeterminate maternal antenatal HIV status (7). A total of 2368 live born infants (1189 of HIV-infected and 1179 of HIV-uninfected women) were thus included in the analyses. HIV-uninfected women were significantly younger than infected women, more likely to be enrolled from rural clinics and less likely to have infants with LBW and SGA (Table I). HIV-infected women did not differ significantly from uninfected women with respect to place or type of delivery, gestational age or water source.

Figure 1.

Figure 1

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Study population. *Improbably high gestational age was >46 weeks.

Table I.

Maternal and infant characteristics by maternal HIV status.

Variable HIV infected (n= 1189) HIV uninfected (n= 1179) Total (n= 2368) P
Enrollment clinic
 Rural 513 (43.1%) 642 (54.5%) 1155 (48.8%) <0.001
 Peri-urban 448 (37.7%) 355 (30.1%) 803 (33.9%)
 Urban 228 (19.2%) 182 (15.6%) 410 (17.3%)
Place of delivery
 Home/othera 141 (11.8%) 139 (11.8%) 280 (11.8%) 0.959
 Hospital/clinic 1048 (88.1%) 1040 (88.2%) 2088 (88.2%)
Type of delivery
 Cesarean 166 (13.9%) 149 (12.6%) 315 (13.3%) 0.638
 Vaginal 1022 (86.0%) 1029 (87.3%) 2051 (86.6%)
 Missing 1 (0.1%) 1 (0.1%) 2 (0.1%)
Birthweight (g)
 ≥2500 1072 (90.2%) 1098 (93.1%) 2170 (91.6%) 0.009
 <2500 117 (9.8%) 81 (6.9%) 198 (8.4%)
Gestational age
 ≥37 weeks 930 (78.2%) 932 (79.1%) 1862 (78.6%) 0.963
 34 to <37 weeks 183 (15.4%) 173 (14.7%) 356 (15.0%)
 32 to <34 weeks 47 (4.0%) 45 (3.8%) 92 (3.9%)
 <32 weeks 29 (2.4%) 29 (2.4%) 58 (2.5%)
Size for gestation
 ≥10% 974 (81.9%) 1001 (84.9%) 1975 (83.4%) 0.051
 3 to <10% 121 (10.2%) 105 (8.9%) 226 (9.5%)
 <3% 94 (7.9%) 73 (6.2%) 167 (7.1%)
Maternal variables (median, IQR)
 Age (years) 25.1 (21.6–29.6) 21.8 (19.1–27.7) 23.6 (20.1–28.8) <0.001
 Weight 61.8 (55.7–69.5) 62.6 (56.3–70.4) 62.2 (56.0–69.8) 0.017
 Height 158.1 (154.2–162.6) 158.5 (154.9–163.0) 158.4 (154.5–162.8) 0.060
 BMI 24.9 (22.4–27.6) 24.6 (22.6–27.8) 24.7 (22.5–27.7) 0.951
 MUAC 27.1 (25.0–29.5) 27.1 (25.0–29.7) 27.1 (25.0–29.6) 0.243
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P indicates the statistical difference between HIV infected and HIV uninfected.

aOther place of delivery refers to deliveries on the way to hospital or clinic.

Prevalence of SGA and preterm deliveries

The median birthweight was 3100 g (inter-quartile range: 2850–3400) and 198 (8.4%) infants were LBW. Overall, 506 (21.4%) infants were born preterm, of these 188 (37%) were born at 36 weeks and nearly one-third were <34 weeks gestational age and 36 (7.1%) preterm infants were SGA. There were 393 (16.6%) infants were SGA; two-fifths of these were severely growth restricted and 36 (9.2%) of the SGA births were preterm. The percentage of SGA infants was higher for HIV-positive than for HIV-negative women (18.1 and 15.1% respectively, P = 0.051). Similarly, the proportion of preterm deliveries was slightly higher in HIV-positive than in HIV-negative women, although this was not statistically significant (21.8 and 20.9%, respectively, P = 0.621).

Stratifying by the child's HIV status: 26 (23.6%) of the perinatally infected, 9 (15.8%) of the post-natally infected and 318 (16.3%) of the uninfected children were SGA, P = 0.378, while 26 (23.6%), 13 (22.8%) and 417 (21.4%), respectively, were preterm, P = 0.722.

Risk factors for SGA and prematurity

Table II presents the overall risk factors for SGA and prematurity. The probability of an SGA infant significantly increased with maternal HIV-infection after adjusting for other factors, known to be associated with SGA risk. Additionally, compared with the relevant reference categories, infants residing in a household without piped water (a proxy indicator of lower socio-economic status) had a significantly higher probability of being SGA, as were first born, those born at home, and those whose mother's height at birth was below the study population mean.

Table II.

Risk factors for SGA and preterm birth (n= 2368).

Variable Overall live births [n (%)] SGA unadjusted RR (95% CI) P SGA adjusted RR (95% CI) P Preterm unadjusted RR (95% CI) P Preterm adjusted RR (95% CI) P
Infant gender
 Female 1188 (50.2) 1.00 1.00
 Male 1178 (49.8) 1.09 (0.91–1.31) 0.329 1.01 (0.86–1.18) 0.909
Area
 Rural 1161 (49.0) 1.00 1.00
 Peri-urban 807 (34.1) 0.92 (0.75–1.13) 0.424 0.90 (0.63–1.28) 0.552
 Urban 400 (16.9) 1.00 (0.78–1.28) 0.994 0.91 (0.58–1.42) 0.675
Water source
 Piped 1601 (67.6) 1.00 1.00 1.00
 Non-piped 706 (29.8) 1.29 (1.07–1.56) 0.008 1.26 (1.04–1.51) 0.017 1.85 (0.71–2.02) 0.077
 Missing data 61 (2.6) 0.73 (0.36–1.49) 0.392 0.71 (0.35–1.43) 0.337 1.31 (0.88–1.95) 0.186
Toilet type
 Flush 398 (16.8) 1.00 1.00
 Non-flush 1378 (58.2) 0.99 (0.76–1.27) 0.910 1.13 (0.90–1.41) 0.284
 None 531 (22.4) 1.36 (1.02–1.79) 0.032 1.15 (0.89–1.49) 0.276
 Missing data 61 (2.6) 0.72 (0.35–1.50) 0.387 1.52 (0.98–2.36) 0.058
Delivery place
 Hospital/clinic 2088 (88.2) 1.00 1.00 1.00 1.00
 Home/other 208 (11.8) 1.34 (1.05–1.72) 0.018 1.48 (1.16–1.90) 0.002 1.36 (1.11–1.67) 0.004 1.38 (1.12–1.69) 0.002
Parity
 1–3 1155 (48.8) 1.00 1.00 1.00
 0 1018 (43.0) 1.58 (1.30–1.91) <0.001 1.71 (1.41–2.07) <0.001 1.02 (0.87–1.19) 0.840
 ≥4 195 (8.2) 1.26 (0.88–1.78) 0.203 1.24 (0.87–1.77) 0.241 0.76 (0.54–1.06) 0.106
Maternal age
 >30 years 509 (21.5) 1.00 1.00 1.00
 20–30 years 1275 (53.8) 0.96 (0.76–1.22) 0.763 1.18 (0.95–1.45) 0.133 1.15 (0.92–1.43) 0.196
 <20 years 582 (24.6) 1.10 (0.85–1.43) 0.458 1.31 (1.03–1.65) 0.025 1.30 (1.02–1.66) 0.033
 Missing data 2 (0.1)
Maternal HIV
 HIV negative 1179 (49.8) 1.00 1.00 1.00 1.00
 HIV positive 1189 (50.2) 1.20 (1.00–1.44) 0.052 1.28 (1.06–1.53) 0.009 1.39 (0.89–1.21) 0.621 1.07 (0.91–1.26) 0.380
Maternal education
 No education 139 (5.9) 1.00 1.00
 Some primary 811 (34.2) 1.05 (0.58–1.93) 0.858 1.74 (0.76–3.97) 0.189
 Secondary and tertiary 1418 (59.9) 1.08 (0.60–1.94) 0.794 1.72 (0.77–3.85) 0.186
Maternal weight
 ≥Mean 823 (33.5) 1.00 1.00 1.00
 <Mean 1039 (42.3) 1.44 (1.15–1.79) 0.002 1.35 (1.13–1.62) 0.001 1.28 (1.07–1.54) 0.008
 Missing data 592 (24.1) 1.47 (1.15–1.89) 0.002 1.04 (0.83–1.29) 0.741 1.01 (0.81–1.27) 0.893
Maternal height
 ≥Mean 661 (26.9) 1.00 1.00 1.00
 <Mean 672 (27.4) 1.33 (1.02–1.74) 0.032 1.36 (1.05–1.77) 0.020 1.11 (0.91–1.37) 0.297
 Missing data 1121 (45.7) 1.43 (1.12–1.82) 0.003 1.41 (1.11–1.79) 0.005 0.95 (0.78–1.15) 0.591
Maternal MUAC
 ≥Mean 789 (32.2) 1.00 1.00
 <Mean 1039 (42.3) 1.33 (1.06–1.67) 0.013 1.38 (1.15–1.66) 0.001
 Missing data 626 (25.5) 1.39 (1.09–1.78) 0.009 1.10 (0.88–1.37) 0.418
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RR, relative risk.

Among HIV-positive mothers, those residing in a household without piped water (adjusted prevalence ratio (aRR): 1.34, 95% CI: 1.05–1.71), delivering at home (aRR: 1.59, 95% CI: 1.17–2.16), delivering for the first time (aRR: 1.59, 95% CI: 1.24–2.04) or of shorter stature (aRR: 1.81, 95% CI: 1.21–2.68) were at a significantly higher probability of having an SGA infant. Additionally, infants of HIV-positive mothers with CD4 counts below 200 cells/mm3 had a higher probability of being SGA (aRR: 1.43, 95% CI: 1.00–2.07, P = 0.053). In HIV-negative mothers, after adjusting for all other factors in Table II, parity was the only factor significantly associated with SGA, with first born infants having a higher probability of being SGA (aRR: 1.97, 95% CI: 1.42–2.73).

Additional analyses were carried out to assess the effect of maternal HIV infection on the risk of delivering severely growth-restricted infants (<3% birthweight-for-gestational age percentile). Adjusting for the risk factors in the final model, infants born to HIV-positive mothers had higher probability of severe growth restriction than those of HIV-negative mothers, although this did just not reach statistical significance due to lack of statistical power (aRR: 1.33, 95% CI: 0.98–1.79; P = 0.067).

In both univariate and multivariable analyses, the probability of preterm delivery was not significantly associated with maternal HIV infection (Table II). However, probability of preterm delivery was significantly higher in infants born at home, as well as in those born to mothers aged less than 20 years and mothers whose maternal weight at birth was less than the population mean. Among HIV-positive women, delivery place was the only statistically significant variable, with children born at home having significantly higher probability of being preterm (aRR: 1.46, 95% CI: 1.11–1.93). Among HIV-negative women, maternal weight at birth was the only significant variable, with children born to mothers whose weight was below the population mean having a significantly higher probability of being preterm (aRR: 1.31, 95% CI: 1.01–1.71).

Additional analyses showed that maternal HIV infection was not associated with severe prematurity (<34 weeks), after adjusting for other risk factors (aRR: 1.08, 95% CI: 0.78–1.50; P = 0.628).

Mortality

Overall, 5.8% (137/2368) infants died in the first year of life: 9.3% (111/1189) of infants of HIV-positive mothers and 2.2% (26/1179) of infants of HIV-negative mothers (P < 0.001). Infants born to HIV-positive women were at significantly higher risk of mortality compared with those of HIV-negative women (IMR, 93.4 and 22.1 per 1000 live births, P < 0.001). Additionally, HIV infected infants were also at a significantly higher mortality risk that uninfected infants (IMR 370.7 and 27.2 per 1000 live births, P < 0.001). Crude neonatal and infant mortality rates did not differ significantly between term and preterm births: 6.4 and 3.9 per 1000 live births, P = 0.522 for neonates and 56.4 and 63.2 per 1000 live births, P = 0.561 for infants respectively.

However, both crude neonatal and infant mortality rates differed significantly between AGA and SGA infants. SGA neonates had a mortality rate of 20.4 per 1000 live births, 6-fold higher than those AGA at 3.0 per 1000 live births, P < 0.001. Infant mortality rates among SGA infants was 101.8 per 1000 live births, double the rate among AGA infants at 49.1 per 1000 live births, P < 0.001. We estimated that at age 12 months, 16% of SGA and 10% of AGA infants (P = 0.008) of HIV-positive mothers will have died and 5% of SGA and 2.5% of AGA infants (P = 0.079) of negative mothers will have died (Fig. 2).

Figure 2.

Figure 2

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Estimated infant mortality by 12 months of age by maternal HIV status and size for gestational age.

Factors associated with infant mortality

Table III shows the risk factors for all children in the cohort irrespective of maternal HIV status. The CD4 count variable includes 1179 HIV-negative mothers classified as ‘missing’. The 2368 infants were followed up for a total of 25 305 child-months over their first year of life. Overall, compared with those AGA, SGA infants had a 2-fold significantly increased hazard of death; and severely growth-restricted infants (<3% percentile) had higher hazards of mortality than those with less severe growth restriction (Table III). Overall, preterm infants had a slightly increased risk of death; this did not reach statistical significance in either univariate or multivariate analyses. Lower maternal age was associated with a significantly increased hazard and women with some formal education had a reduced hazard of infant death.

Table III.

Risk factors for infant mortality (n= 2368).

Variable Overall live births [n (%)] Unadjusted HR (95% CI) P Adjusted HR (95% CI) P
Gestational age
 ≥37 weeks 1862 (78.6) 1.00 1.00
 34–36 weeks 356 (15.1) 1.10 (0.69–1.74) 0.688 1.18 (0.79–1.79) 0.423
 <34 weeks 150 (6.3) 1.17 (0.54–2.55) 0.685 1.31 (0.58–2.94) 0.509
Size for gestation
 ≥10% (AGA) 1975 (83.4) 1.00 1.00
 3 to <10% (SGA) 226 (9.5) 2.27 (1.29–4.02) 0.004 2.12 (1.18–3.81) 0.012
 <3% (SGA) 167 (7.1) 3.91 (2.31–6.63) <0.001 2.77 (1.56–4.91) <0.001
Area
 Rural 1161 (49.0) 1.00 1.00
 Peri-urban 807 (34.1) 0.86 (0.55–1.33) 0.496 0.73 (0.47–1.14) 0.172
 Urban 400 (16.9) 0.28 (0.11–0.69) 0.006 0.25 (0.10–0.67) 0.004
Parity
 1–3 1155 (48.8) 1.00 1.00
 0 1018 (43.0) 1.09 (0.72–1.67) 0.666 0.94 (0.57–1.57) 0.824
 ≥4 195 (8.2) 0.49 (0.17–1.36) 0.170 0.71 (0.23–2.22) 0.559
Maternal age
 >30 years 509 (21.5) 1.00 1.00
 20–30 years 1275 (53.8) 1.62 (0.90–2.92) 0.108 1.59 (0.81–3.12) 0.179
 <20 years 582 (24.6) 1.59 (0.83–3.06) 0.165 2.34 (1.01–5.43) 0.047
 Missing data 2 (0.1)
Maternal education
 No education 139 (5.9) 1.00 1.00
 Some primary 811 (34.2) 0.53 (0.25–1.12) 0.097 0.28 (0.13–0.61) 0.002
 Secondary and tertiary 1418 (59.9) 0.60 (0.30–1.21) 0.155 0.37 (0.17–0.80) 0.011
Child HIV infection status
 Uninfected 1945 (82.1) 1.00 1.00
 Perinatally infected 109 (4.6) 24.39 (15.10–39.39) <0.001 18.43 (10.40–32.65) <0.001
 Post-natally infected 57 (2.4) 5.42 (2.56–11.48) <0.001 5.06 (2.32–11.01) <0.001
 Infected, timing unknown 40 (1.7) 12.04 (4.32–33.53) <0.001 7.43 (2.56–21.60) <0.001
 Missing data 217 (9.2) 5.15 (2.42–10.91) <0.001 5.02 (2.35–10.73) <0.001
Maternal HIV status
 HIV negative 1179 (49.8) 1.00
 HIV positive 1189 (50.2) 3.02 (1.91–4.79) <0.001
Maternal antenatal CD4 count
 ≥500 cells/mm3 498 (21.0) 1.00 1.00
 200–499 cells/mm3 524 (22.1) 1.86 (1.06–3.25) 0.030 1.37 (0.77–2.46) 0.285
 <200 cells/mm3 129 (5.5) 2.47 (1.15–5.31) 0.021 1.87 (1.21–3.96) 0.009
 Missing dataa 1217 (51.4) 0.54 (0.29–0.96) 0.037 0.73 (0.41–1.27) 0.267
Open in a new tab

HR, hazard ratio. aHR were adjusted for the other variables in the table. Maternal HIV status was not adjusted for in the multivariable analysis as only HIV-positive women had an antenatal CD4 count. Note: toilet type, water source, child gender and delivery place were not significantly associated with infant mortality.

aMissing CD4 count category includes 1179 HIV-negative women.

Infants of HIV-positive mothers had a 3-fold significantly increased hazard of death; those whose mothers had antenatal CD4 counts <200 cells/mm3 had a 2-fold significantly increased hazard of death compared with those whose mothers had CD4 counts of at least 500 cells/mm3, when categorizing HIV-negative mothers as ‘missing’.

Overall, 8.7% (206/2368) of infants were HIV infected in the first year of life. Of the 109 perinatally infected infants, 24 (22.0%) were SGA and 27 (24.8%) were preterm (P = 0.562). The 206 HIV-infected infants were at a significantly increased risk of mortality compared with those who were HIV uninfected, allowing for child HIV status as a time-varying variable (Table III).

Discussion

This cohort study enrolled HIV-infected and -uninfected pregnant women between 2001 and 2004 (before the availability of antiretroviral treatment), in rural South Africa; almost all pregnant women in this setting present for antenatal visits (Hoque et al., 2008), and the study enrollment rate was >80% (Bland et al., 2010). In a recent systematic review, Northern and Western Africa had, respectively, an estimated rate of preterm births of 8.7 and 10.1%, considerably lower compared with that in Southern Africa, at 17.5% (Beck et al., 2010). Preterm births have multiple causes, and the design of this study allowed us to investigate the contribution of HIV, if any, given the enrolment of both HIV-infected and -uninfected women, in a setting with a very high antenatal HIV prevalence estimated at 39.5% (Department of Health, 2010a,b) and high preterm delivery rates. The prevalence of preterm deliveries was 21.4% while that of SGA was 16.6%, with limited overlap between the two, and the maternal HIV infection was associated with a 1.2-fold increased risk of SGA birth. This significant association was maintained after controlling for water source, delivery place, parity and maternal height, factors associated with SGA in other studies (Verhoeff et al., 2001; Bhutta et al., 2005).

SGA infants were at a significantly increased hazard of infant mortality compared with those who were AGA, but there was no difference in mortality between the term and preterm births. Our findings of increased infant mortality among SGA infants are consistent with another African study (Kasirye-Bainda and Musoke, 1992), with the risk increasing with severity of growth restriction, such that severely SGA infants had a 3-fold significantly increased hazard of death before and after adjusting for other confounders. A plausible mechanism for this may be the increased post-natal morbidity rates (Kasirye-Bainda and Musoke, 1992). As infant follow-up stopped at 2 years, we were not able to explore longer term implications of preterm delivery, such as developmental disabilities and cerebral palsy. Generally, there is limited service provision for children with such problems in this setting.

Knowledge of the independent effect of maternal HIV infection on birth outcomes such as preterm delivery and SGA infants is needed in order to understand the potential impact of antiretroviral treatment. Additionally, quantifying the burden of neonatal and infant morbidity and mortality associated with maternal HIV is important in similar settings with high antenatal HIV prevalence. Our study, conducted before antiretroviral treatment was available in this setting, shows that maternal HIV infection was not significantly associated with preterm delivery, consistent with other studies in Africa (Bulterys et al., 1994; Verhoeff et al., 2001). However, this contrast to earlier African studies which enrolled hospital-based deliveries only (Habib et al., 2008; Laar et al., 2010), while our study enrolled deliveries from both in and outside hospitals. Further, in one of the studies, 31% of pregnant women were lost prior to delivery, a large proportion of these were HIV negative, which may affect the strength of the association reported (Laar et al., 2010). Infants delivered at home had higher probabilities of being preterm, probably due to the fact that these women were unable to reach a health-care facility in time. Other independent factors associated with preterm delivery in this and previous studies were younger maternal age, consistent with greater perinatal risks due to social disadvantages or biological factors (da Silva et al., 2003) and low maternal weight (Ehrenberg et al., 2003).

The current prevention of mother-to-child transmission (PMTCT) guidelines in South Africa recommend zidovudine (AZT) from 14 weeks of pregnancy, single-dose nevirapine, 3-hourly AZT intrapartum and a single dose of tenofovir and emtracitabine post-partum, for women not eligible for lifelong antiretroviral treatment and antiretroviral treatment for those eligible starting as soon as possible in pregnancy (Department of Health, 2010a, b). Several studies in Europe and the USA have reported an increased risk of preterm delivery with antenatal highly active antiretroviral therapy (HAART), with associations of between 1.5- and 3.5-fold increased risk (Thorne et al., 2004; Cotter et al., 2006; Townsend et al., 2010a,b) and there are also preliminary indications from studies in sub-Saharan Africa (SSA) of the same association (Powis et al., 2011; van der Merwe et al., 2011). This has been hypothesized to be due to an immunological mechanism, with HAART in pregnancy associated with a reversal of the Th1 to Th2 switch that is an immunological feature of normal pregnancy (Fiore et al., 2006) rather than being caused by infant or placental factors. Given the enormous benefits of HAART for maternal health and PMTCT, and the fact that most of these preterm infants are born from gestations associated with relatively low morbidity and mortality risk, the benefits are considered to outweigh the risks in resource-rich settings (de Ruiter et al., 2008). In a UK study, the incremental risk–benefit ratio of HAART compared with monotherapy with respect to preterm delivery was modelled and it was found that each 10 infant infections prevented through the use of antenatal HAART would result in an additional 6 preterm births (Townsend et al., 2010a,b).

Despite the resource-limited setting, preterm infants in our study (37% of whom were born at 36 weeks) had good survival and we observed no difference in the crude neonatal and infant mortality rates comparing term and preterm deliveries. In the multivariable analysis, there was no statistically significant difference in infant mortality between the two groups, allowing for time-varying child infection status, although the hazard of death was slightly higher for preterm infants. The VTS was not designed to investigate the role of preterm delivery in infant mortality; furthermore, the implementation of ‘Kangaroo mother care (KMC’; continous skin-to-skin contact and support for exclusive breastfeeding or other appropriate feeding) in the first week of life within the study, shown to significantly reduce neonatal mortality and serious morbidity amongst preterm infants in low- and middle-income countries (Lawn et al., 2010), may have resulted in better outcomes than would be seen in other similar settings where KMC remains unavailable (Department of Health, 2008).

In the context of ongoing scale-up of antiretroviral treatment in SSA (Mutevedzi et al., 2010), a growing number of pregnant women with HIV will be using combination antiretroviral treatment throughout pregnancy (Townsend et al., 2008). The benefits of antenatal combination antiretroviral treatment in PMTCT in an African setting were illustrated in the Mma Bana trial in Botswana, with MTCT rates of 1.1% (Shapiro et al., 2010). Maternal initiation of HAART also has benefits of increased survival chances for the woman herself (Herbst et al., 2009) and indirectly that of her children (Ndirangu et al., 2010). Preliminary indications of the same association between HAART use and increased risk of preterm delivery in African populations as reported in resource-rich settings (Powis et al., 2011; van der Merwe et al., 2011) highlight the need for evaluation of the potential risks as well as the benefits of antenatal HAART.

Our finding of an increased risk of SGA in infants of HIV-positive mothers accords with previous studies elsewhere in Africa (Bulterys et al., 1994; Taha et al., 1995), as does our identification of primiparae and shorter maternal height as important contributors to SGA (Kramer, 1987a,b; Verhoeff et al., 2001; Watson-Jones et al., 2007), together with lower socio-economic status, included here with the use of a proxy measure (lack of piped water). Co-infections, for instance malaria and other medical conditions like tuberculosis and anaemia prior to or early in pregnancy have been shown to be important factors associated with SGA and preterm delivery (Verhoeff et al., 2001; Noble et al., 2005; Watson-Jones et al., 2007). In this study, such data were not available, although malaria is not an issue in KwaZulu-Natal. We were also unable to adjust for factors such as smoking, hypertension and anaemia.

In common with other studies reporting associations between advanced maternal HIV disease and adverse birth outcomes (Kuhn et al., 2005; Mehta et al., 2008), we found that HIV-positive women with severe immunodeficiency had higher risk of having a SGA infant. This raises the possibility that improving maternal health with the use of antiretroviral treatment might result in better fetal growth and fewer SGA infants. Although HAART regimens have been implicated in preterm delivery, this does not appear to be the case for IUGR according to a French study (Briand et al., 2009). However, recent evidence from Botswana suggesting that maternal antiretroviral treatment initiation before conception may be associated with very SGA infants (Parekh et al., 2011) needs confirmation, particularly given the potential for confounding by indication due to the limited ability to adjust for maternal disease status in this study.

In the current study of HIV-positive and -negative women, one in five deliveries occurred preterm, but this was not associated with maternal HIV status, nor was it a risk factor for infant mortality. However, one in six deliveries were of SGA infants and maternal HIV was one of the factors associated with this outcome. Furthermore, SGA infants, particularly those with HIV-positive mothers, were at increased risk of death in the first year of life. This has implications for clinical practice. Whereas preterm infants are usually routinely followed-up for several months post-delivery, SGA infants are not. Our findings suggest that SGA infants should also be included in careful clinical follow-up to minimize morbidity and mortality. Ongoing research and monitoring in SSA is needed to provide more information on the complex relationships between maternal health, antenatal ART and pregnancy outcomes in this setting where ∼90% of the world's HIV-infected pregnant women live. Future studies of preterm birth and SGA should include variables such as hypertension, anaemia and tuberculosis co-infections, although the feasibility of carrying out such a study on a large rural African population is questionable.

Authors' roles

J.N. was responsible for overall statistical analysis and writing of the first draft of the paper. M-L.N. and R.B. contributed to the vertical transmission study concept, design and data acquisition. C.T. and M-L.N. supervised the analyses approach and writing of the paper. All authors gave constructive comments during writing and interpretation of results and substantially contributed to, and approved, the final manuscript.

Funding

The Wellcome Trust supported this study (UK 063009/Z/00/2), and provides core funding to the Africa Centre. Dr Claire Thorne holds a Wellcome Trust Research Career Development Fellowship. Funding to pay the Open Access publication charges for this article was provided by Wellcome Trust.

Conflict of interest

None declared.

Acknowledgements

We would like to thank the mothers and children who participated in the VTS, the VTS staff for their dedication to this project and Colin Newell for assisting in data management. We also acknowledge the other VTS investigators: Hoosen M. Coovadia, Nigel C. Rollins and Anna Coutsoudis.

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