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. 2020 Jan 24;3:1533. Originally published 2019 Sep 4. [Version 2] doi: 10.12688/gatesopenres.13046.2

Adverse birth outcomes and their clinical phenotypes in an urban Zambian cohort

Joan T Price 1,2,3,a, Bellington Vwalika 2, Katelyn J Rittenhouse 1, Humphrey Mwape 3, Jennifer Winston 1, Bethany L Freeman 1, Ntazana Sindano 3, Elizabeth M Stringer 1, Margaret P Kasaro 3, Benjamin H Chi 1, Jeffrey SA Stringer 1
PMCID: PMC7047437  PMID: 32161903

Version Changes

Revised. Amendments from Version 1

In this version, we have expanded the discussion to address the reviewers' concerns around definitions of preterm birth and stillbirth used as well as to add global context to our estimates of the frequencies of adverse birth outcomes. We have updated Figure 2 to illustrate the co-occurrence of very preterm birth, very small-for-gestational-age, and stillbirth. We present an additional linear regression analysis of continuous exposures and continuous outcomes and note that maternal height is not associated with either preterm birth or small-for-gestational-age.

Abstract

Background: Few cohort studies of pregnancy in sub-Saharan Africa use rigorous gestational age dating and clinical phenotyping. As a result, incidence and risk factors of adverse birth outcomes are inadequately characterized.

Methods: The Zambian Preterm Birth Prevention Study (ZAPPS) is a prospective observational cohort established to investigate adverse birth outcomes at a referral hospital in urban Lusaka. This report describes ZAPPS phase I, enrolled August 2015 to September 2017. Women were followed through pregnancy and 42 days postpartum. At delivery, study staff assessed neonatal vital status, birthweight, and sex, and assigned a delivery phenotype. Primary outcomes were: (1) preterm birth (PTB; delivery <37 weeks), (2) small-for-gestational-age (SGA; <10 th percentile weight-for-age at birth), and (3) stillbirth (SB; delivery of an infant without signs of life).

Results: ZAPPS phase I enrolled 1450 women with median age 27 years (IQR 23–32). Most participants (68%) were multiparous, of whom 41% reported a prior PTB and 14% reported a prior stillbirth. Twins were present in 3% of pregnancies, 3% of women had short cervix (<25mm), 24% of women were HIV seropositive, and 5% were syphilis seropositive. Of 1216 (84%) retained at delivery, 15% were preterm, 18% small-for-gestational-age, and 4% stillborn. PTB risk was higher with prior PTB (aRR 1.88; 95%CI 1.32–2.68), short cervix (aRR 2.62; 95%CI 1.68–4.09), twins (aRR 5.22; 95%CI 3.67–7.43), and antenatal hypertension (aRR 2.04; 95%CI 1.43–2.91). SGA risk was higher with twins (aRR 2.75; 95%CI 1.81–4.18) and antenatal hypertension (aRR 1.62; 95%CI 1.16–2.26). SB risk was higher with short cervix (aRR 6.42; 95%CI 2.56–16.1).

Conclusio ns: This study confirms high rates of PTB, SGA, and SB among pregnant women in Lusaka, Zambia. Accurate gestational age dating and careful ascertainment of delivery data are critical to understanding the scope of adverse birth outcomes in low-resource settings.

Keywords: adverse birth outcomes, pregnancy, preterm birth, small for gestational age, stillbirth, sub-Saharan Africa, Zambia

Introduction

The often overlapping outcomes of preterm birth (PTB), small for gestational age (SGA), and stillbirth (SB), collectively called ‘adverse birth outcomes’, are responsible for most perinatal morbidity and mortality worldwide. 1, 2 Low- and middle-income countries bear the overwhelming burden of global PTB, SB, and SGA. 35 However, reliable classification and estimation of adverse birth outcomes in low-resources settings is challenging because of a number of interrelated factors, including (1) uncertain gestational age dating, 6 (2) conflation of fetal growth restriction and PTB into the less useful metric of ‘low birthweight’, 3, 5 (3) inconsistent thresholds for fetal viability, 7 and (4) misclassification of stillbirth and neonatal death. 8, 9 In many countries, including Zambia, data sources that adequately address these methodological challenges are lacking to the extent that national estimates of adverse birth outcomes must be modeled. 3, 6, 10, 11

In sub-Saharan Africa, cohort studies in pregnancy rarely use reliable gestational age dating or clinical phenotyping to classify outcomes. Deliberate clinical phenotyping that characterizes the events that incite parturition (i.e., spontaneous vs. provider-initiated), quantifies maternal and fetal co-morbid conditions, and reliably distinguishes the timing of perinatal death is essential for rigorous classification of adverse birth outcomes. 12, 13 Accurate estimation of gestational age with fetal ultrasound is also critical. Other dating methods, such as maternal recall of last menstrual period (LMP), 1417 symphisial-fundal height measurement, 18 or newborn physical exam 19, 20 introduce error (and in some cases, bias 21).

We established a cohort of 1450 pregnant women and their infants at a tertiary care institution in Lusaka, Zambia, with the goal of better understanding the epidemiological factors and biological mechanisms leading to adverse birth outcomes. This report presents the outcomes of the first phase of this cohort.

Methods

The Zambian Preterm Birth Prevention Study (ZAPPS) is an ongoing prospective observational cohort study at the Women and Newborn Hospital of the University Teaching Hospitals (UTH-WNH), the primary referral hospital in Lusaka. Phase 1 of ZAPPS, the subject of this report, recruited and enrolled participants beginning in August 2015 and completed follow-up in June 2018. The sample size for this observational study was initially set at 2000 women, with a target of 250 preterm birth events based on published regional population estimates. 4 For budgetary reasons and because the prematurity rate was higher than initially expected, enrollment was stopped in September 2017 after 1450 women had been enrolled. The ZAPPS protocol was developed to align with the Guidelines for Strengthening The Reporting of Observational Studies in Epidemiology (STROBE). 22

Study population

Pregnant women meeting the following criteria were eligible for enrollment in Phase 1 of the ZAPPS cohort: (1) 18 years of age or older; (2) viable intrauterine singleton or twin gestation; (3) presentation to antenatal care prior to 20 weeks of gestation if HIV-uninfected or 24 weeks if HIV-infected; (4) residing within Lusaka with no plans to relocate during the study follow-up period; (4) willing to provide written, informed consent; (5) willing to allow participation of their infant(s) in the study; (6) willing to be contacted and followed up at home if necessary.

The ZAPPS protocol was approved prior to study initiation and is subjected to annual review by the University of Zambia School of Medicine Biomedical Research Ethics Committee (reference number: 016-04-14) and the University of North Carolina School of Medicine Institutional Review Board (study number: 14-2113). The study also received approval from the Zambian Ministry of Health National Health Research Authority. Each participant provided written informed consent before enrollment.

Procedures

Full study procedures are described in detail elsewhere. 23 Community educators identified potential participants at antenatal care clinics of UTH-WNH and five surrounding clinics in Lusaka, assessing basic eligibility criteria such as age and approximate gestational age. Interested volunteers underwent ultrasound examination per standard of care to determine pregnancy location, fetal viability, number of fetuses, and gestational age by standard biometry (Sonosite M-Turbo, Fuji Sonosite, Bothell, WA). Gestational age was calculated at enrollment by crown-rump length if <14 gestational weeks or by head circumference and femur length if ≥14 weeks. Fetal biometry structures were each measured twice and then averaged to calculate gestational age using INTERGROWTH-21st equations. 24, 25 Pregnancies below the lower threshold for INTERGROWTH-21st equations were dated by the Hadlock formula. 26 Interested women who met preliminary ultrasound eligibility criteria completed an informed consent process in their preferred language of English, Nyanja, or Bemba.

At enrollment, study nurses collected demographic and behavioral information through medical record review and participant interview, and documented a thorough health history including prior pregnancy outcomes. As part of standard antenatal care, participants underwent a physical exam and rapid testing for hemoglobin, urinalysis, syphilis (SD Bioline Syphilis 3.0, Abbott Diagnostics), and HIV (SD Bioline 3.0, Abbott Diagnostics).

After enrollment, participants received routine antenatal care at follow-up visits scheduled at approximately 24 weeks, 32 weeks, and 36 weeks. All participants underwent cervical length measurement in the second trimester (i.e., 14–28 weeks) and fetal growth assessment by biometry in the third trimester. 27, 28 Cervical length measurements were performed by sonographers with certification in the Cervical Length Education and Review (CLEAR) program. Study nurses staffed the UTH-WNH labor ward full-time and collected detailed information about the clinical course and perinatal outcomes of participants and their infants, including gestational age at birth, neonatal vital status, birthweight, and sex, and assigned a delivery phenotype. For participants who did not deliver at UTH-WNH or were not captured by study staff during their delivery admission, study staff collected perinatal outcomes either in person or by phone. Cohort retention in this analysis was defined as ascertainment of date of delivery.

Exposures

Primary exposures evaluated included maternal age (years), height (cm), and body mass index (BMI, kg/m 2); reported prior preterm birth (nulliparous, parous with no prior PTB, or parous with one or more prior PTB); cervical length (mm) and short cervix (<25mm); gestation (single or twin); hypertension during pregnancy (≥140 systolic or ≥90mmHg diastolic at any antepartum study visit); anemia at enrollment (<10.5g/dL); bacteriuria during pregnancy (1+ leukocyte esterase and/or nitrites at any antepartum study visit); syphilis seropositivity (reactive at enrollment); and HIV seropositivity (reactive at enrollment).

Outcomes

Primary outcomes of this analysis were: PTB, defined as birth between 16 0/ 7 and 36 6/ 7 gestational weeks, SGA (newborn weight-for-age <10th percentile by INTERGROWTH-21st norms), 29 and SB (delivery of an infant without signs of life ≥16 0/ 7 weeks). Secondary outcomes included very PTB (birth before 34 0/ 7 weeks), very SGA (newborn weight-for-age <3rd percentile), gestational duration (days), and birthweight centile for gestational age at delivery. Both PTB and very PTB were further characterized as either spontaneous (spontaneous labor or membrane rupture prior to labor) or provider-initiated (induction of labor or pre-labor cesarean). We differentiated antepartum stillbirth (i.e., fetal heart tones absent on admission or, if not assessed, maceration skin changes present at delivery) from intrapartum stillbirth (i.e., fetal heart tones present on admission or, if not assessed, absence of maceration skin changes at delivery).

Statistical analysis

We performed descriptive analyses of baseline characteristics and exposures of the cohort, reporting median and interquartile range (IQR) for continuous variables, and frequency and percent for categorical variables. Differences in baseline characteristics between women retained at delivery and those lost to follow-up were evaluated by univariate tests of association.

We summarized parturition phenotype among our retained participants by preterm versus term and spontaneous versus provider-initiated following a standard rubric. 12 Among spontaneous PTB, we identified primary maternal, fetal, and/or placental conditions present at the time of delivery. Among provider-initiated PTB, we reported the primary indication for delivery as recorded by the provider. Finally, key individual conditions present and phenotypic clusters were used to classify all PTB, spontaneous PTB, and provider-initiated PTB.

We calculated the incidence of adverse birth outcomes: PTB, spontaneous PTB, very PTB, spontaneous very PTB, SGA, very SGA, and SB among all participants retained at delivery. Twin deliveries in which at least one neonate was SGA or stillborn were classified as having met the respective outcome. Crude associations between key exposures and outcomes were analyzed as risk ratios estimated using Poisson regression analyses with a robust variance. 30 Adjusted risk ratios were also estimated using Poisson regression accounting for other key exposures plus maternal age, BMI, estimated gestational age at enrollment, and HIV serostatus at enrollment. We then analyzed the association between continuous exposure variables and outcomes (gestational duration and birthweight centile by gestational age at birth) using linear regression.

Kaplan-Meier curves were plotted for time to delivery for participants with and without a history of prior PTB, short cervix, and twin gestation. We accounted for loss to follow-up by right censoring women at their last study visit (if before delivery) and compared survival between exposure groups by log-rank tests. We also used Cox regression to calculate the hazard of delivery between participants with and without prior PTB, short cervix, and twin gestation, adjusting for maternal age. The proportional-hazards assumption was tested based on Schoenfeld residuals. 31 Because of the inherent converging of survival curves in pregnancy at term, we restricted our models to the preterm period by administratively censoring all participants at 37 gestational weeks. 32, 33

All statistical analyses were performed with Stata version 14 (College Station, TX, USA) and SAS version 9.4 (Cary, NC, USA).

Results

From August 2015 to September 2017, 1784 pregnant women were screened and 1450 (81%) enrolled ( Figure 1). 23 The median age of enrolled participants was 27 (IQR: 23–32) ( Table 1). 34 Median estimated gestational age (EGA) at enrollment was 16 weeks; 30% (n=427/1450) were enrolled before 14 completed gestational weeks. Of 1042 (72%) participants who had been pregnant at least once in the past; 19% (n=194/1042) reported a prior miscarriage. Of 992 (68%) with a prior delivery, 41% (n=411) reported a prior PTB. On ultrasound exam, 3% (n=35/1175) had short cervix <25mm, and 3% (n=38/1450) had twin gestation. The prevalence of HIV seropositivity at enrollment was 24% (n=350/1447). Syphilis seropositivity was detected in 5% (70/1342).

Figure 1. ZAPPS cohort participant flowchart.

Figure 1.

ANC, antenatal care; UTH-WNH, Women and Newborn Hospital of University Teaching Hospital.

Table 1. Baseline characteristics of ZAPPS cohort, N=1450.

Characteristic Total enrolled
N=1450
Retained at delivery visit
N=1216 (83.9%)
Lost to follow-up
N=234 (16.1%)
p
N Value
% or Median (IQR) *
N Value
% or Median (IQR) *
N Value
% or Median (IQR) *
Maternal age, years 1409 27 (23–32) 1192 27 (23–32) 217 24 (20–29) <.001
   <20 111 7.9 72 6.0 39 18.0
   20–34 1116 79.2 956 80.2 160 73.7
   ≥35 182 12.9 164 13.8 18 8.3
   Missing 41 24 17
Maternal education, years 1435 12 (9–12) 1204 12 (9–12) 231 9 (7–12) <.001
   None 26 1.8 19 1.6 7 3.0
   0–12 years 1225 85.4 1018 84.6 207 89.6
   ≥12 years 184 12.8 167 13.9 17 7.4
   Missing 15 12 3
Married or cohabiting 1202 83.7 1014 84.1 188 81.4 0.310
   Missing 13 10 3
Electricity in home 1302 90.6 1105 91.6 197 85.3 0.002
   Missing 13 10 3
Piped drinking water in home 1340 93.3 1123 93.2 217 93.9 0.678
   Missing 14 11 3
Toilet facilities in home <.001
   Flush or Pour 762 53.0 667 55.3 95 41.1
   Pit / Latrine / Other 675 47.0 539 44.7 136 58.9
   Missing 13 10 3
Floor material in home 0.438
   Natural / rudimentary 138 9.6 119 9.9 19 8.2
   Finished 1299 90.4 1087 90.1 212 91.8
   Missing 13 10 3
Domestic violence in past year 71 5.0 58 4.9 13 5.6 0.641
   Missing 28 26 2
Smoking in pregnancy 8 0.6 7 0.6 1 0.4 0.768
   Missing 24 23 1
Alcohol use in pregnancy 124 8.7 106 8.9 18 7.7 0.563
   Missing 25 24 1
Maternal height at enrollment, cm 1368 156 (160–164) 1151 156 (160–165) 217 156 (160–164) 0.263
BMI at enrollment, kg/m 2 1366 23.6 (21.2–27.2) 1149 23.9 (21.4–27.6) 217 22.7 (20.7–25.5) <.001
   <18.5 71 5.2 56 4.9 15 6.9
   18.5–30.0 1103 80.8 919 80.0 184 84.8
   >30.0 192 14.1 174 15.1 18 8.3
   Missing 84 67 17
Gravidity 1450 2 (1–4) 1042 2 (1–4) 408 2 (1–3) 0.003
   Primigravida 408 28.1 321 26.4 87 37.2 0.001
   Multigravida 1042 71.9 895 73.6 147 62.8
Prior miscarriage, n=1042 0.933
   Multigravida, no prior miscarriage 848 81.4 728 81.3 120 81.6
   Multigravida, ≥1 prior miscarriage 194 18.6 167 18.7 27 18.4
Parity 1450 1 (0–2) 1216 1 (0–2) 234 1 (0–2) 0.004
   Nulliparous 458 31.6 365 30.0 93 39.7 0.003
   Parous 992 68.4 851 70.0 141 60.3
Prior PTB, n=992 0.224
   Parous, no prior PTB 581 58.6 505 59.3 76 53.9
   Parous, ≥1 prior PTB 411 41.4 346 40.7 65 46.1
Prior stillbirth, n=992 0.401
   Parous, no prior SB 780 86.1 672 86.5 108 83.7
   Parous, ≥1 prior SB 126 13.9 105 13.5 21 16.3
   Missing 86 74 12
Short cervix < 2.5 cm 35 3.0 32 3.0 3 3.2 0.899
   Missing 275 135 140
Twin gestation 38 2.6 31 2.6 7 3.0 0.698
HIV positive at enrollment 350 24.2 304 25.0 46 19.7 0.084
   Missing 3 2 1
Syphilis reactive 70 5.2 63 5.6 7 3.1 0.142
   Missing 108 93 15
Hypertensive at enrollment ^ 52 3.7 46 3.9 6 2.7 0.392
   Missing 31 21 10
Hemoglobin at enrollment, g/dL 1025 12 (11–13) 854 12 (11–13) 171 12 (11–13) 0.274
   <10.5 140 13.7 123 14.4 17 9.9
   Missing 425 362 63
Abnormal UA at enrollment 69 5.0 55 4.8 14 6.3 0.343
   Missing 79 67 12
EGA at enrollment, weeks 1450 16.1 (13.3–18.3) 1216 16.0 (13.3–18.3) 234 16.3 (13.3–18.6) 0.421
   <14 427 29.4 362 29.8 65 27.8

BMI, body mass index; PTB, preterm birth; SB, stillbirth; UA, urinalysis; EGA, estimated gestational age; IQR, interquartile range.

* Not all columns sum to 100% due to rounding.

^ Defined as systolic blood pressure ≥ 140 and/or diastolic blood pressure ≥ 90.

Defined as 1+ leukocyte esterase and/or + nitrites.

p values calculated by Wilcoxon rank sum or chi-square for continuous and categorical comparisons, respectively.

Of enrolled participants, 1216 (84%) were retained with delivery date ascertained. Compared to participants lost to follow-up, those retained at delivery were older (median: 27 versus 24 years, p<.001), had more years of education (median: 12 versus 9 years, p<.001), were more likely to have electricity (91% versus 85%, p=.002) and flush or pour toilet facilities at home (55% versus 41%, p<.001), had higher body mass index (23.9 versus 22.7 kg/m 2, p<.001), and had higher gravidity (74% versus 63% multigravid, p=.001) and parity (70% versus 60% parous, p=.004).

Frequencies of our outcomes were as follows: 15% PTB (n=181/1216), 8% very PTB (n=92/1216), 18% SGA (n=207/1159), 7% very SGA (n=80/1159), and 4% SB (n=53/1209). Three participants (0.3%) experienced miscarriages before 16 weeks of gestation. Of the pregnancies that ended in SB, 44 (83%) were antepartum and 9 (17%) occurred intrapartum. Among 1159 deliveries within the EGA range for SGA calculation and with birthweight recorded, 35 150 (13%) were PTB, 65 (6%) were very PTB, 207 (18%) were SGA, 80 (7%) were very SGA, and 32 (3%) were stillborn ( Figure 2).

Figure 2. Preterm birth, very preterm birth, small for gestational age, very small for gestational age, and stillbirth among participants retained at delivery in ZAPPS cohort.

Figure 2.

Among ZAPPS cohort participants retained at delivery, 15% (181/1216) were preterm (PTB), 8% (92/1216) were very PTB, 18% (207/1159) were small for gestational age (SGA), 7% (80/1159) were very SGA, and 4% (53/1209) were stillborn (SB). *11 preterm births (^9 of which were very preterm), one term stillbirth, and 20 preterm stillbirths (^18 of which were very preterm) were either outside the gestational age threshold for INTERGROWTH-21 st calculation of SGA, 28 or were missing birthweight at delivery. Figures created with: EulerAPE. 36

Of 181 total PTB, 120 (66%) occurred spontaneously, 56 (31%) were provider-initiated, and 5 (3%) could not be definitively classified ( Figure 3). The most common key conditions present in women with spontaneous PTB (n=120) were HIV infection (n=42, 35%), SB (n=26, 23%), hypertension alone (n=22; 18%), and twin gestation (n=18, 15%); 33 (28%) had no key condition identified. Most provider-initiated preterm deliveries were indicated for SB (n=16, 29%), preeclampsia or eclampsia (n=15, 27%) or hypertension alone (n=4, 7%), or both SB and preeclampsia (n=4, 7%). We identified major phenotypic clusters of PTB, spontaneous PTB, and provider-initiated PTB by presence of maternal, fetal, and/or placental conditions ( Table 2).

Figure 3. Parturition phenotypes among ZAPPS participants with preterm delivery.

Figure 3.

Of participants who underwent preterm delivery (n=181) in the ZAPPS cohort, 120 of them were spontaneous and 56 were indicated. This figure presents the frequencies of primary conditions present in spontaneous preterm deliveries, primary indications for indicated preterm deliveries, and the overall frequency with 95% confidence intervals of key conditions in each group. Gray bars represent missing values. APH, antepartum hemorrhage; OB HX, obstetrical history.

Table 2. Phenotypes of preterm birth in ZAPPS cohort, N=181.

All preterm birth
N (%) *
Spontaneous
N (%)
Provider-initiated
N (%)
All preterm 181 100 120 68 56 32
Phenotypic clusters
   No significant clinical conditions 41 23 33 87 5 13
   Maternal condition(s) only 60 33 40 67 20 33
   Fetal condition(s) only 27 15 21 81 5 19
   Placental condition(s) only 4 2 1 25 3 75
   Maternal and fetal conditions 37 20 17 47 19 53
   Maternal and placental conditions 6 3 3 50 3 50
   Fetal and placental conditions 1 1 1 100 0 0
   Maternal, fetal, and placental conditions 5 3 4 80 1 20
Significant maternal conditions 108 60 64 60 43 40
   HIV infection 53 29 42 81 10 19
   Urinary tract infection, n=41 9 22 7 78 2 22
   Clinical chorioamnionitis, n=120 1 1 1 100 0 0
   Diabetes (mellitus or gestational), n=179 5 3 1 20 4 80
   Hypertension 34 19 19 56 15 44
   Preeclampsia, n=107 23 21 6 26 17 74
   Eclampsia, n=125 5 4 0 0 5 100
Significant fetal conditions 70 39 43 63 25 37
   Twin gestation 21 12 18 90 2 10
   Stillbirth, n=176 48 27 26 55 21 45
   Fetal growth restriction 2 1 0 0 2 100
   Fetal distress 1 1 0 0 1 100
   Polyhydramnios 1 1 0 0 1 100
   Oligohydramnios 1 1 0 0 1 100
Significant placental conditions 16 9 9 56 7 44
   Placental abruption 15 8 9 60 6 40
   Placenta previa 4 2 0 0 4 100

* column percent.

† row percent.

Maternal age ≥35, prior PTB, short cervix, twin gestation, antenatal hypertension, and EGA at enrollment <14 weeks were associated with PTB ( Table 3). Overall, these associations were stable or strengthened when restricting the outcome to spontaneous PTB and to very PTB ( Table 4). Although associated with PTB, antenatal hypertension did not significantly predict spontaneous phenotypes of PTB. Maternal height was not significantly associated with PTB or very PTB in univariate analyses. In multivariable regression models adjusting for maternal age, BMI, EGA at enrollment, and HIV status at enrollment, participants with prior PTB (aRR 1.88; 95% CI 1.32–2.68), short cervix (aRR 2.62; 95% CI 1.68–4.09), twin gestation (aRR 5.22; 95% CI 3.67–7.43), and antenatal hypertension (aRR 2.04; 95% CI 1.43–2.91) had increased risk of PTB ( Table 2). The associations between the exposures of prior PTB, short cervix, and twin gestation with PTB were stable or strengthened when restricting the outcome to spontaneous phenotypes and very PTB ( Table 4). The risk of PTB decreased with increasing cervical length (RR 0.58 per cm; 95% CI 0.46–0.73) ( Figure 4). In multiple linear regression of continuous exposure variables, gestational duration was associated with number of prior PTB (coeff -5.11 days; 95% CI -6.42 to -3.79), cervical length (coeff 6.49 days; 95% CI 4.18–8.81), and EGA at enrollment (0.70 days; 0.28–1.12) ( Table 6).

Table 3. Risk of adverse birth outcomes among ZAPPS participants retained at delivery, n=1213.

Exposure Preterm birth 16 to <37 weeks Spontaneous preterm birth 16 to <37 weeks Small for gestational age Stillbirth
n events % RR 95%
CI
aRR * 95%
CI
n events % RR 95%
CI
aRR * 95%
CI
n events % RR 95%
CI
aRR 95%
CI
n events % RR 95%
CI
aRR 95%
CI
Age at enrollment, years
   <20 72 5 6.9 1.00 70 3 4.3 1.00 70 13 18.6 1.00 72 0 0.0 -
   20–34 953 144 15.1 2.18 0.92–
5.14
950 103 10.8 2.53 0.82–
7.77
911 157 17.2 0.93 0.56–
1.55
954 39 4.1 1.00
   ≥35 164 31 18.9 2.72 1.10–
6.72
164 13 7.9 1.85 0.54–
6.29
155 33 21.3 1.15 0.64–
2.04
159 14 8.8 2.15 1.20–
3.88
BMI at enrollment, kg/m 2
   <18.5 56 12 21.4 1.00 56 10 17.9 1.00 53 10 18.9 1.00 55 1 1.8 1.00
   18.5–30.0 916 136 14.9 0.69 0.41–
1.17
912 90 9.9 0.55 0.30–
1.00
876 172 19.6 1.04 0.59–
1.85
913 41 4.5 2.47 0.35–
17.6
   >30.0 174 20 11.5 0.54 0.28–
1.03
173 10 5.8 0.32 0.14–
0.74
168 18 10.7 0.57 0.28–
1.15
173 7 4.1 2.23 0.28–
17.7
Prior PTB
   Nulliparous 364 40 11.0 1.13 0.76–
1.68
0.93 0.60–
1.43
363 25 6.9 1.23 0.73–
2.08
0.86 0.47–
1.55
345 73 21.2 1.42 1.06–
1.91
1.36 0.98–
1.87
363 8 2.2 0.62 0.27–
1.40
0.95 0.36–
2.50
   Parous, no prior
PTB
504 49 9.7 1.00 1.00 502 28 5.6 1.00 1.00 491 73 14.9 1.00 1.00 503 18 3.6 1.00 1.00
   Parous, ≥1 prior
PTB
345 92 26.7 2.74 1.99–
3.77
1.88 1.32–
2.68
343 67 19.5 3.5 2.30–
5.33
2.62 1.69–
4.06
323 61 18.9 1.27 0.93–
1.73
1.12 0.82–
1.54
343 27 7.9 2.20 1.23–
3.93
1.63 0.78–
3.40
Cervical length
   ≥2.5cm 1049 137 13.1 1.00 1.00 1045 91 8.7 1.00 1.00 1021 181 17.7 1.00 1046 35 3.4 1.00 1.00
   <2.5cm 32 16 50.0 3.83 2.62–
5.60
2.62 1.68–
4.09
32 9 28.1 3.23 1.79–
5.81
1.95 1.01–
3.77
31 9 29.0 1.64 0.93–
2.89
32 6 18.8 5.60 2.54–
12.4
6.42 2.56–
16.1
Gestation
   Single 1182 160 13.5 1.00 1.00 1178 102 8.7 1.00 1.00 1128 191 16.9 1.00 1.00 1177 51 4.3 1.00
   Twin 31 21 67.7 5.00 3.77–
6.64
5.22 3.67–
7.43
30 18 60.0 6.93 4.90–
9.80
7.86 5.37–
11.5
31 16 51.6 3.05 2.12–
4.39
2.75 1.81–
4.18
31 2 6.5 1.49 0.38–
5.85
HIV serostatus at
enrollment
   Negative 908 128 14.1 1.00 1.00 904 78 8.6 1.00 1.00 871 152 17.5 1.00 1.00 906 37 4.1 1.00 1.00
   Positive 303 53 17.5 1.24 0.93–
1.66
1.17 0.85–
1.62
302 42 13.9 1.61 1.13–
2.29
1.36 0.91–
2.03
286 55 19.2 1.10 0.83–
1.46
1.09 0.80–
1.47
301 16 5.3 1.30 0.73–
2.31
1.29 0.65–
2.56
Syphilis
   Non-reactive 1057 159 15.0 1.00 1053 109 10.4 1.00 1006 184 18.3 1.00 1053 41 3.9 1.00 1.00
   Reactive 63 9 14.3 0.95 0.51–
1.77
63 3 4.8 0.46 0.15–
1.41
63 13 20.6 1.13 0.68–
1.86
63 6 9.5 2.45 1.08–
5.55
2.34 0.91–
6.04
Blood pressure
during pregnancy
   Normotensive 1072 145 13.5 1.00 1.00 1067 106 9.9 1.00 1025 173 16.9 1.00 1.00 1068 42 3.9 1.00 1.00
   Hypertensive 141 36 25.5 1.89 1.37–
2.60
2.04 1.43–
2.91
141 14 9.9 1.00 0.59–
1.70
134 34 25.4 1.50 1.09–
2.07
1.62 1.16–
2.26
141 11 7.8 1.98 1.05–
3.76
1.83 0.84–
3.96
Hemoglobin at
enrollment
   ≥10.5 g/dL 730 111 15.2 1.00 727 70 9.6 1.00 700 125 17.9 1.00 726 30 4.1 1.19 0.51–
2.80
   <10.5 g/dL 121 21 17.4 1.14 0.75–
1.75
121 15 12.4 1.29 0.76–
2.17
113 20 17.7 0.99 0.65–
1.52
122 6 4.9 1.00
UA during
pregnancy
   Normal 907 125 13.8 1.00 903 82 9.1 1.00 880 168 19.1 1.00 903 32 3.5 1.00
   Abnormal ^ 189 31 16.4 1.19 0.83–
1.71
189 20 10.6 1.17 0.73–
1.85
182 26 14.3 0.75 0.51–
1.10
191 6 3.1 0.89 0.38–
2.09
EGA at
enrollment, weeks
   <14 360 72 20.0 1.00 358 45 12.6 1.00 333 62 18.6 1.00 357 20 5.6 1.00
   ≥14 853 109 12.8 0.64 0.49–
0.84
850 75 8.8 0.70 0.50–
0.99
826 145 17.6 0.94 0.72–
1.23
851 33 3.9 0.69 0.40–
1.19

BMI, body mass index; PTB, preterm birth; UA, urinalysis; EGA, estimated gestational age; RR, relative risk; CI, confidence interval; aRR, adjusted risk ratio

* Risk ratios calculated via Poisson regression with robust error variance. Multivariable model estimates of adjusted risk ratios include other exposure variables listed and all models adjusted for: maternal age, maternal BMI, and EGA at enrollment as continuous variables.

‡ Defined as systolic blood pressure ≥ 140 and/or diastolic blood pressure ≥ 90 at enrollment or at any follow-up ANC visit.

^ Defined as 1+ leukocyte esterase and/or + nitrites.

Table 4. Risk of severe adverse birth outcomes in ZAPPS participants retained at delivery, n=1213.

Exposure Very preterm birth 16 to <34 weeks Spontaneous very preterm birth 16 to <34 weeks Very small for gestational age
n events % RR 95% CI aRR * 95% CI n events % RR 95% CI aRR * 95% CI n events % RR 95% CI aRR * 95% CI
Age at enrollment,
years
   <20 72 3 4.2 1.00 71 2 2.8 1.00 70 7 10.0 1.00
   20–34 953 75 7.9 1.89 0.61–5.84 950 50 5.3 1.87 0.46–7.53 913 55 6.0 1.66 0.79–3.51
   ≥35 164 13 7.9 1.90 0.56–6.48 164 6 3.7 1.30 0.27–6.28 155 17 11.0 1.82 1.09–3.05
BMI at enrollment,
kg/m 2
   <18.5 56 4 7.1 1.00 56 3 5.4 1.00 53 8 15.1 1.00
   18.5–30.0 916 72 7.9 1.10 0.42–2.90 913 46 5.0 0.94 0.30–2.93 879 60 6.8 0.45 0.23–0.90
   >30.0 174 9 5.2 0.72 0.23–2.27 173 5 2.9 0.54 0.13–2.19 167 10 6.0 0.40 0.17–0.95
Prior PTB
   Nulliparous 364 22 6.0 1.45 0.81–2.60 1.10 0.55–2.21 364 14 3.9 1.61 0.75–3.44 0.88 0.34–2.31 345 32 9.3 1.98 1.18–3.32 1.92 1.12–3.32
   Parous, no prior
PTB
504 21 4.2 1.00 1.00 502 12 2.4 1.00 1.00 491 23 4.7 1.00 1.00
   Parous, ≥1 prior
PTB
345 49 14.2 3.41 2.08–5.58 2.27 1.28–4.04 343 33 9.6 4.02 2.11–7.68 2.89 1.39–5.98 323 25 7.7 1.65 0.95–2.86 1.39 0.76–2.53
Cervical length
   ≥2.5cm 1049 63 6.0 1.00 1.00 1046 39 3.7 1.00 1.00 1022 68 6.7 1.00 1.00
   <2.5cm 32 12 37.5 6.24 3.76–10.4 3.97 2.15–7.33 32 7 21.9 5.87 2.84–12.1 3.19 1.35–7.55 31 5 16.1 2.42 1.05–5.59 2.06 0.88–4.82
Gestation
   Single 1182 81 6.9 1.00 1.00 1179 51 4.3 1.00 1.00 1130 74 6.6 1.00 1.00
   Twin 31 11 35.5 5.18 3.08–8.70 5.18 2.75–9.77 30 8 26.7 6.16 3.21–11.8 7.53 3.58–15.9 31 6 19.4 2.96 1.39–6.27 2.71 1.12–6.57
HIV serostatus at
enrollment
   Negative 908 67 7.4 1.00 1.00 905 41 4.5 1.00 1.00 871 61 7.0 1.00 1.00
   Positive 303 25 8.3 1.12 0.72–1.74 1.20 0.71–2.01 302 18 6.0 1.32 0.77–2.26 1.35 0.68–2.66 286 19 6.6 0.95 0.58–1.56 0.86 0.48–1.53
Syphilis
   Non-reactive 1057 81 7.7 1.00 1054 53 5.0 1.00 1009 71 7.0 1.00
   Reactive 63 5 7.9 1.04 0.44–2.46 63 2 3.2 0.63 0.16–2.53 63 6 9.5 1.35 0.61–2.99
Blood pressure
during pregnancy
   Normotensive 1072 78 7.3 1.00 1068 55 5.2 1.00 1025 65 6.3 1.00 1.00
   Hypertensive 141 14 9.9 1.36 0.79–2.34 141 4 2.8 0.55 0.20–1.50 134 15 11.2 1.77 1.04–3.00 1.68 0.92–3.06
Hemoglobin at
enrollment
   ≥10.5 g/dL 730 60 8.2 1.00 727 35 4.8 1.00 703 46 6.5 1.00
   <10.5 g/dL 121 7 5.8 0.70 0.33–1.50 121 5 4.1 0.86 0.34–2.15 113 5 4.4 0.68 0.27–1.67
UA during
pregnancy
   Normal 907 59 6.5 1.00 904 37 4.1 1.00 881 68 7.7 1.00
   Abnormal ^ 189 14 7.4 1.14 0.65–2.00 189 7 3.7 0.81 0.41–2.00 183 10 5.5 0.71 0.37–1.35
EGA at
enrollment, weeks
   <14 360 39 10.8 1.00 358 26 7.3 1.00 333 25 7.5 1.00
   ≥14 853 53 6.2 0.57 0.39–0.85 851 33 3.9 0.92 0.86–0.99 828 55 6.6 0.88 0.56–1.40

BMI, body mass index; PTB, preterm birth; UA, urinalysis; EGA, estimated gestational age; RR, relative risk; CI, confidence interval; aRR, adjusted risk ratio

* Risk ratios calculated via Poisson regression with robust error variance. Multivariable models include other exposure variables listed and adjusted for: maternal age, maternal BMI, and EGA at enrollment.

‡ Defined as systolic blood pressure ≥ 140 and/or diastolic blood pressure ≥ 90 at enrollment or at any follow-up visit.

^ Defined as 1+ leukocyte esterase and/or + nitrites.

Figure 4. Predicted probability of preterm birth <37 weeks by mid-trimester cervical length.

Figure 4.

Among ZAPPS cohort participants with a cervical length measured by ultrasound in the second trimester (n=1081), the probability of preterm birth <37 weeks decreased with increasing cervical length. PTB, preterm birth; RR, relative risk; CI, confidence interval.

Nulliparity, twin gestation, and antenatal hypertension were each associated with SGA in univariate analysis, and older age, low BMI, nulliparity, short cervix, twin gestation, and antenatal hypertension were associated with very SGA. In multivariable analysis, twin gestation (aRR 2.75; 95% CI 1.81–4.18) and antenatal hypertension (aRR 1.62; 95% CI 1.16–2.26) were associated with an increased risk of SGA; nulliparity was marginally associated with SGA (aRR 1.36; 95% CI 0.98–1.87). Nulliparity (aRR 1.92; 95% CI 1.12–3.32) and twin gestation (aRR 2.71, 95% CI 1.12–6.57) were associated with very SGA. Maternal height was not associated with SGA or very SGA in univariate analyses of categorical outcomes, but was associated with mean centile of birthweight in adjusted linear regression (coeff 0.32; 95% CI 0.04,0.59), along with maternal weight (coeff 0.34; 95% CI 0.21,0.47), and EGA at enrollment (coeff -0.75; 95% CI -1.25 to -0.25) ( Table 6).

Finally, older maternal age, prior PTB, short cervix, syphilis seropositivity, and antenatal hypertension were individually associated with an elevated risk of SB ( Table 3). In multivariable analysis, short cervix predicted SB (aRR 6.42; 95% CI 2.56–16.1), while syphilis was only marginally associated (aRR 2.34; 95% CI 0.91–6.04).

Elevated risks of PTB among women with prior PTB, short cervix, and twin gestation were supported by survival analyses, with log-rank tests of association demonstrating significant differences between groups of each variable ( Figure 5; Table 5). In proportional hazards models adjusted for maternal age at enrollment, participants with prior PTB, short cervix, and twin gestation had significantly higher hazards of delivering before 37 gestational weeks compared to parous women with no prior PTB, women with cervical lengths ≥25mm, or with single gestations. Participants with increasing numbers of prior preterm births demonstrated increasing hazard ratios of delivering preterm.

Figure 5.

Figure 5.

Kaplan-Meier survival curves by ( a) prior preterm birth, ( b) short cervix (<25mm), and ( c) twin gestation. Survival curves are presented for participants with increasing numbers of prior preterm birth, those with cervical length <25mm compared to ≥25 mm, and those with twin compared to singleton gestation. The dashed vertical line represents a gestational age of 37 weeks, the threshold for preterm versus term delivery. EGA, estimated gestational age; PTB, preterm birth.

Table 5. Log-rank and Cox proportional hazards regression with test of proportionality assumption for prior preterm birth, short cervical length, and twin gestation.

Log-rank Cox proportional
hazards
Schoenfeld
residual test
p HR * 95% CI p rho Χ 2 p
Prior preterm birth global 3.23 0.66
   Parous, no prior <.001 ^ ref ref
   Parous, 1 prior 2.21 1.47– 3.33 <.001 -0.01 0.01 0.92
   Parous, 2 prior 2.79 1.70– 4.58 <.001 0.00 0.00 0.95
   Parous, 3+ prior 4.70 2.94– 7.53 <.001 -0.11 2.33 0.13
   Nulliparous - 1.16 0.75– 1.78 0.51 -0.06 0.80 0.37
Cervical length global 4.42 0.11
   ≥ 25mm <.001 ref ref
   <25mm 5.19 3.09– 8.74 <.001 -0.15 3.26 0.07
Gestation global 3.19 0.20
   Singleton <.001 ref ref
   Twin 6.70 4.25– 10.60 <.001 0.13 3.19 0.07

HR, hazards ratio; CI, confidence interval.

* Each proportional hazards model adjusted for maternal age at enrollment.

^ log-rank of trend, excluding nulliparas.

Table 6. Association between continuous exposures by gestational duration and birthweight centile.

Exposure Gestational duration, days Birthweight centile for gestational age
coeff 95% CI adjusted 95% CI coeff 95% CI adjusted 95% CI
Age at enrollment, years -0.18 -0.44,0.08 0.30 0.01,0.60 -0.02 -0.32,0.29
Maternal height at enrollment, m -0.05 -0.28,0.17 0.63 0.37,0.88 0.32 0.04,0.59
Maternal weight at enrollment, kg -0.01 -0.11,0.09 0.41 0.30,0.53 0.34 0.21,0.47
BMI at enrollment, kg/m 2 0.09 -0.20,0.37 0.84 0.51,1.17
Number of prior PTB -6.54 -8.07,-5.00 -5.11 -6.42,-3.79 -1.94 -3.80,-0.07
Cervical length 6.93 5.05,8.82 6.49 4.18,8.81 0.87 -1.84,3.58
Systolic blood pressure at
enrollment
-0.11 -0.22,0.01 -0.05 -0.18,0.08
Diastolic blood pressure at
enrollment
-0.17 -0.32,-0.02 -0.01 -0.18,0.17
Hemoglobin at enrollment 0.45 -0.59,1.48 1.17 -0.01,2.34
EGA at enrollment, weeks 1.12 0.70,1.54 0.70 0.28,1.12 -0.77 -1.26,-0.29 -0.75 -1.25,-0.25

Coefficients and confidence intervals calculated by linear regression. Adjusted coefficients calculated in multivariable models that included other exposure variables with estimates shown.

PTB, preterm birth; EGA, estimated gestational age; coeff, coefficient; CI, confidence interval.

Discussion

We present the primary results of the ZAPPS pregnancy cohort, established to evaluate the risk factors associated with adverse birth outcomes in Lusaka, Zambia. This study was notable for enrollment of pregnant women at early presentation to antenatal care, gestational age determination by early ultrasound, universal cervical length screening, comprehensive and uniform antenatal and postpartum care, and clinical phenotyping of birth outcomes. Our analyses revealed strong risks of prior preterm birth, short mid-trimester cervical length, and twin gestation on incident preterm birth, and these risks were supported by analyses of pregnancy ‘survival’ to term. We also report increased risks of small-for-gestational-age infants among nulliparous women and women with twin gestation, and of stillbirth among those with short cervix.

The proportion of gravidas who deliver before term varies significantly across individual studies and national estimates in sub-Saharan Africa. The most recent global report estimated a PTB rate of 8% in Europe and 11% in North America, compared to 12% across sub-Saharan Africa and 12% in Zambia specifically, where the rate was based on modeled regional estimates instead of national data. 6 In contrast, a census accounting of 237,219 public sector births over 6 years in Lusaka — where the vast majority of pregnancies are dated by last menstrual period — classified 46% of singleton deliveries as preterm. 37, 38 In Zambia, obstetrical ultrasound is rare and the reliance on maternal recall of LMP alone substantially over-estimates preterm birth rates, 17, 39 an inaccuracy that worsens with later presentation to care. 21 We report PTB based on ultrasound gestational age dating and prospectively ascertained delivery outcomes such that our data are likely more accurate than reports that rely on LMP recall or regional models.

Inconsistent global PTB definitions hinder inter-regional comparisons of rates and risk factors, and we acknowledge that gestational age boundaries are somewhat arbitrary. We chose a lower gestational age limit of 16 weeks because of evidence of similar etiological risk factors between preterm births occurring as early as 16 weeks and those that occur later in pregnancy 12, 40. In addition, we included preterm stillbirths in our definition of PTB since excluding stillbirths that occur in the process of parturition would falsely lower the rate of PTB. In a sensitivity analysis that excluded all stillbirths from PTB outcomes, the PTB incidence was modestly reduced. However, risk estimates calculated in regression models remained stable, which supports evidence that risk factors for live and stillborn PTB demonstrate substantial overlap 40.

The distinction of preterm parturition as spontaneously occurring versus provider-initiated is important but rarely reported from national surveillance or clinical research data in low-resource settings. Deliveries that are preceded by spontaneous labor or membrane rupture are phenotypically distinct from those that are induced medically or surgically for complications such as preeclampsia, antepartum fetal demise, or other maternal or fetal conditions. 12, 4144 Further classification based on primary conditions present in spontaneous PTB and the primary indications for provider-initiated PTB is based on a standardized rubric proposed to elucidate phenotypic clusters of PTB 12. An understanding of prevailing phenotypes can direct research, policy, and preventive interventions towards regional and population-specific needs. 13, 45, 46 While our cohort is limited by a small number of PTB events (n=181), we were able to classify nearly all (i.e., 97%) as either spontaneous or provider-initiated, and to identify the primary complications and phenotypic characteristics of each. Further granularity and generalizability of PTB classification requires a larger sample size, signaling a need for future high-quality obstetrical research on a greater scale.

As with PTB classification, identifying infants born SGA requires accurate gestational age estimation, which can be at best imprecise, and at worst biased, when based solely on LMP. 21 The incidence of SGA in our cohort (18%) was modestly higher than regional estimates of SGA in sub-Saharan Africa of 16%, 5 and compared to a recent estimate in Zambia of 13%, which was modeled from published rates in other neighboring countries because of scarcity of data from Zambia itself. 5 In comparison to the ZAPPS cohort, in which older maternal age, low BMI, nulliparity, twin gestation, and antenatal hypertension predicted either SGA or very SGA, a study among over 19,000 singletons in Tanzania identified younger maternal age, height, and nulliparity as strong risk factors for SGA. 47 The WHO Multi-country Survey on Maternal and Newborn Health found nulliparity and hypertensive disorders to indicate higher risk of preterm SGA and hypertensive disorders, sociodemographic factors, and anemia to predict term SGA. 48 With a much smaller sample size and fewer outcomes compared to these two studies, we were not able to differentiate our outcome by preterm vs. term SGA due to low statistical precision for stratified associations with key risk factors. Due to this low precision, we are not able to discern whether or not SGA outcomes were modified by gestational age at delivery. However, both of these studies relied on reported LMP to estimate gestational age at delivery, which itself may have introduced error. Whether growth restriction is a distinct pathological process before 37 weeks compared to after 37 weeks is unclear. Finally, while the INTERGROWTH-21 st Project 49 intended to define universal fetal growth and newborn weight standards derived from an extensive multi-ethnic sample of women with adequate antenatal care and nutrition, its widespread use over ethnicity-specific or customized standards has been disputed. 43, 5056 Despite this, we chose to define SGA in our cohort based on INTERGROWTH-21 st standards since local standards that include all pregnancies affected by undernutrition and/or pregnancy comorbidities tend to identify only the severest 10% of cases by definition.

Stillbirth, a composite outcome comprising antepartum and intrapartum fetal death, is particularly understudied in low-resource settings. Compared to developed regions with a stillbirth rate of 3.4 per 1000 total births, the rate in sub-Saharan Africa is estimated as 28.7 per 1000, while 4% of our cohort delivered stillbirths. 3 The true global burden of stillbirth and its underlying causes are poorly classified due to inconsistent fetal viability limits and imperfect classification of neonatal death versus stillbirth, limited resources for case investigations, under-reporting of home births that result in perinatal death, and inadequate national and regional reporting of identified cases. 3 Indeed, recent global and regional estimates of stillbirth included just 17% of its datapoints from sub-Saharan Africa and south Asia, regions that bear 77% of the global burden. 3 Data from the recent Zambia Demographic and Health Survey reported a rate of stillbirth, defined as fetal death over 7 months’ gestation, as 1.3% among 13,563 births reported, with equal rates outside Lusaka province as within. 57 This is similar to estimates from a Global Network study in Zambia, in which 2% of women enrolled delivered stillbirths. 9 The higher proportion of deliveries that resulted in stillbirth in the ZAPPS cohort, at least partly attributable to a broader gestational age range, was reflected in the ZEPRS database, in which 6% of 66,395 deliveries at UTH resulted in stillbirth. 38 However, over half of stillbirths in ZEPRS and 67% in a Global Network study in Zambia were classified as intrapartum, compared to less than 20% in the ZAPPS cohort. These disparities may result from differential classification; it is standard practice outside of our study to classify stillbirths solely by neonatal skin maceration at delivery, particularly in the absence of but even despite the presence of documented fetal heart activity during labor. 9 Indeed, previous studies have demonstrated that reliance on observed skin maceration alone can over-estimate stillbirth proportions attributable to the intrapartum period. 58

This study has several limitations, many of which have been noted previously. 23 First, 16% of participants were lost to follow-up. While this is commensurate with other longitudinal pregnancy cohort studies in the region, 59, 60 error may be introduced if outcomes are not missing at random. 61 Women lost to follow-up were younger, more likely to be primigravida and nulliparous, had lower BMIs, and had multiple lower measures of socioeconomic status; many of these characteristics were risk factors for at least one adverse outcome. Further, 250 (21%) of the retained participants either did not deliver at the study hospital or delivered at a time when ZAPPS staff were not present, requiring delivery outcomes to be ascertained by record review and/or participant report (it is worth noting that we found no difference in frequencies of outcomes between deliveries attended by ZAPPS staff versus those that were not; see Underlying data). Second, our data have noted missingness of key antenatal test results at baseline (i.e., hemoglobin, syphilis, and urinalysis) because tests were not routinely repeated nor results recorded in our database if performed at the recruitment clinic before enrollment. Of these test results, only syphilis was associated with an outcome (stillbirth), but we cannot determine with certainty whether missingness introduced bias or simply reduced statistical power. Third, while the ZAPPS study recruits from several surrounding primary clinics, it is based at a tertiary referral hospital and many of our participants were drawn from this higher-risk pool. We note high prevalence of prior PTB, miscarriage, and stillbirth, and high HIV and syphilis seropositivity, which may have resulted from self-selection of high-risk women into a cohort study investigating adverse birth outcomes. It is likely that this resulted in an over-representation of outcomes, but less likely to have also introduced a biased association with identified risk factors.

In summary, the ZAPPS cohort study demonstrates high prevalence of antenatal comorbidities and identifies a number of factors associated with increased risks of preterm birth, small-for-gestational-age infants, and stillbirth. This is the first study of its kind to be conducted in Zambia, and one of the largest on the African continent. An understanding of the true global scope of adverse birth outcomes will require consistent definitions, meticulous ascertainment, and systematic reporting that has eluded those settings where the burden of these outcomes is highest. In the absence of sophisticated registry infrastructure, large pregnancy cohort studies may be able to approximate regional incidence estimates and can provide important data to stratify and direct care for pregnancies at highest risk. Future sub-studies using data and stored biological specimens from the ZAPPS cohort will aim to identify underlying biological mechanisms, causal pathways, and appropriate interventions for the accurate prediction and prevention of adverse birth outcomes in Zambia and worldwide.

Data availability

Underlying data

Open Science Framework: Zambian Preterm Birth Prevention Study (ZAPPS) – Outcomes. https://doi.org/10.17605/OSF.IO/WT6Q8 34

This project contains the following underlying data:

  • -

    Z1A minimum dataset 2019-06-30.csv (underlying data for all participants)

  • -

    Z1A Codebook 2019-06-30.rtf (codebook for the variables within the dataset)

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Acknowledgments

The authors acknowledge the invaluable contributions to the study design and conduct by Eve Lackritz, James Litch, Marcela Castillo, Nancy Hancock, and Nurain Fuseini. The study protocol is registered at ClinicalTrials.gov, identifier: NCT02738892.

Funding Statement

This study was supported by the Bill and Melinda Gates Foundation [OPP1033514] through a grant to the Global Alliance to Prevent Prematurity and Stillbirth. Additional support was provided by the US National Institutes of Health through the UNC Center for AIDS Research [P30 AI50410] and trainee / mentor support: [T32 HD075731] (JTP), [K01 TW010857] (JTP), [D43 TW009340] (KJR), and [K24 AI120796] (BHC).

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

[version 2; peer review: 2 approved]

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Gates Open Res. 2020 Feb 26. doi: 10.21956/gatesopenres.14236.r28503

Reviewer response for version 2

Shinjini Bhatnagar 1, Ramachandran Thiruvengadam 2

I have no further comments to make.

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Gates Open Res. 2019 Nov 6. doi: 10.21956/gatesopenres.14168.r28082

Reviewer response for version 1

Shinjini Bhatnagar 1

In this manuscript, the authors report the rates of adverse birth outcomes such as preterm birth, stillbirth and small for gestational age from a well-characterized cohort of 1450 pregnant women from Zambia. This is a very important article, providing robust data from a low-middle income country like Zambia in the domain of maternal and child health. 

The emphasis on accuracy and precision of gestational age estimation which is a cornerstone in preterm birth research is praise-worthy. The data is well represented and the statistical analyses are appropriate.

Comments:

  1. Preterm birth has been defined as birth between 16 0/7 and 36 6/7 gestational weeks in this study. The definition seems to include stillbirths (the proportion of stillbirth among PTB is reported in paragraph 4 of the results section), which is in variance with the convention of reporting preterm birth among live-born babies. What is the rationale behind this choice? Does such a change in definition influence the preterm birth rate in this study population? If so, how much? 

  2. The lower limit of gestational age for defining preterm birth is taken as 16 0/7 weeks in this study. What was the rationale behind considering 16 weeks as the lower cut-off of preterm birth? Further, one of the inclusion criteria is  “presentation to antenatal care prior to 20 weeks of gestation if HIV-uninfected or 24 weeks if HIV-infected”. Nearly 50% of the women first present to antenatal care after 16 weeks in this population and 25% above 18.3w (median EGA at enrolment is 16.1 (IQR: 13.3–18.3)w). This means there would be some pregnant women in the population who delivered preterm (between 16 & 24w) who couldn’t be a part of the cohort because of the delay in seeking antenatal care. Would that create a bias? If so, how much would this influence the study’s estimate of the preterm birth rate in the population? Reporting preterm birth rate among the participants enrolled less than 16 weeks of gestation will add further information in this aspect. 

 

The manuscript can be accepted for indexing after the resolution of the comments made above.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Gates Open Res. 2019 Nov 14.
Joan Price 1

We chose to include preterm stillbirths in our definition of preterm birth and demonstrate the overlapping adverse outcomes of preterm birth, stillbirth, and small for gestational age in Figure 2. We acknowledge significant limitations in differentiating intrapartum stillbirth from preterm birth with immediate neonatal death in our setting. We believe that to exclude stillbirths that occur in the process of parturition from spontaneous preterm birth would falsely lower the rate of spontaneous preterm delivery. As we note in the discussion, the categorization of antepartum vs. intrapartum stillbirth is also imperfect. Of 181 preterm deliveries in our cohort, 48 (27%) were stillborn. Excluding stillbirths from our preterm delivery definition reduced preterm delivery from 15% to 11% and spontaneous preterm delivery from 10% to 8%. Despite this overall reduction, excluding stillbirths from our regression models did not significantly alter our estimates of risk, which supports evidence that risk factors for live and stillborn preterm births demonstrate substantial overlap (Kramer 2012). Finally, our cohort was designed to evaluate the risk factors associated with adverse birth outcomes, and not necessarily to estimate population-level rates of these outcomes. We note in the discussion that our study population likely over-represents high-risk women and therefore overestimates the true population incidence of adverse birth outcomes. 

Both lower and upper EGA boundaries for defining preterm birth vary widely in research and national statistics worldwide. Participants at the International Conference on Prematurity and Stillbirth of the Global Alliance to Prevent Prematurity and Stillbirth (GAPPS) have argued for including births occurring 16 weeks onward in the definition of preterm birth, citing studies that show similar etiological risk factors for births occurring as early as 16 weeks and those that occur later in the 2 nd and 3 rd trimester (Kramer 2012; Villar 2012). We acknowledge that the risk of preterm birth in any cohort increases with earlier gestational age at presentation for precisely the reason explained by the reviewer. There is a strong relationship between EGA at presentation and EGA at delivery, which therefore produces this effect regardless of relatively arbitrary EGA boundaries used to define outcomes. Indeed, the preterm birth rate among participants who enrolled <16 weeks was 18% in our cohort compared to 12% among those enrolled ≥16 weeks. Because of this, we include EGA at enrollment in all multivariable analyses. We also repeated analyses of preterm delivery outcomes restricting our sample to those participants who presented <20 weeks and again to those who presented <16 weeks to evaluate the potential for bias. These restricted analyses had no effect on our results (with the exception of short cervix as an exposure since it was only performed beyond 16 weeks).

Gates Open Res. 2019 Nov 4. doi: 10.21956/gatesopenres.14168.r28081

Reviewer response for version 1

Ge Zhang 1

This is an important study and the data presented adds new knowledge about the adverse birth outcomes and their risk factors in low-income countries in sub-Saharan Africa. The advantages of the study include:

  1. Well-designed and well-conducted cohort study;

  2. Reliable gestational age dating and clinical phenotyping;

  3. Well-defined primary exposures and birth outcomes;

  4. Distinction between spontaneous and provider-initiated PTB;

  5. Comprehensive and reliable data analysis;

  6. Results were well-organized clearly presented;

  7. Limitations were well noted and discussed.

Minor comments:

  1. The reviewer recognized that the authors tried to avoid using p-values in this report according to recent guidelines and recommendations. However, sometimes it could be helpful to the readers to comprehend the “substantiality” of the statistical evidence. The reviewer therefore would suggest including p-values in Figure 3, Table 2, etc. (as Table 1).

  2. EGA at enrollment (<14) was shown to be associated with PTB. The authors might compare the baseline characteristics between the samples enrolled before and after 14wks to identify the possible reasons underlying this association (similar to the comparisons made in Table 1). In addition, as the gestational age was calculated differently in the samples enrolled before and after 14wks, the authors might also compare outcomes (e.g. gestation duration) between these two groups to examine whether the two methods could potentially cause systematical difference in the estimation of gestational age.

  3. The authors presented the co-occurrence among PTB, SGA and SB using a Venn diagram (Figure 2). It is also interesting to learn whether the frequencies of the co-occurrence of these outcomes were higher than expected especially between the very PTB and very SGA group.

  4. The authors dichotomized continuous exposures (e.g. maternal age, BMI) as well as the outcomes (e.g. PTB, SGA) in the association analysis (Table 3). It would be more informative if the authors could also show the results based on association tests of continuous variables.

  5. Maternal height has been shown to be associated with gestational duration and birth weight (gestational age adjusted) in previous studies mainly in high-income countries. It is not known whether maternal height is associated with gestational duration (and PTB) in this study or not.

  6. In the discussion section, the authors should compare the risk factors (e.g. their occurrence, frequencies and estimated effect sizes) and the frequencies of adverse birth outcomes reported in this study with those reported in high-income countries.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Gates Open Res. 2020 Feb 7.
Joan Price 1

The authors thank the reviewer for the thoughtful and constructive comments. Please find a point-by-point response to each comment here. 

  1. We have elected not to include p values in our tables beyond Table 1 because the we think point estimates and their 95% confidence intervals are the best estimates of association. (see Harrington et al NEJM 2019 https://www.nejm.org/doi/full/10.1056/NEJMe1906559).  

  2. Thank you for this suggestion. In response to the other reviewer’s comment regarding the increased risk of PTB with EGA at enrollment, we have repeated analyses of preterm delivery outcomes restricting our sample to those participants who presented <20 weeks and again those who presented <16 weeks to evaluate the potential for bias and our results proved stable. We also include EGA at enrollment in all multivariable analyses. We think that additional reporting of which baseline characteristics differ by EGA at enrollment and investigation of the effect of ultrasound algorithms used for EGA calculation is beyond the scope (and page limit) of this analysis but may be explored in future analyses. 

  3. Thank you for this suggestion. We have added a second Euler diagram to Figure 2 to illustrate the co-occurrence of very PTB, very SGA, and stillbirth.

  4. We have added linear regression of continuous exposures and continuous outcomes (Table 6). 

  5. We have noted in the results section that maternal height was not associated with either PTB or SGA. It was similarly not associated with gestational duration.

  6. We have added additional global context to our estimates of the frequencies of adverse birth outcomes in the discussion section. However, we acknowledge significant limitations to direct comparisons of risk estimates due to inconsistent definitions. Furthermore, as there is still no undisputed global standard by which to identify small for gestational age neonates, we have not directly compared the incidence of SGA in our cohort to estimates from high-income countries.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Stringer JSA: Zambian Preterm Birth Prevention Study (ZAPPS) - Outcomes.2019. 10.17605/OSF.IO/WT6Q8 [DOI]

    Data Availability Statement

    Underlying data

    Open Science Framework: Zambian Preterm Birth Prevention Study (ZAPPS) – Outcomes. https://doi.org/10.17605/OSF.IO/WT6Q8 34

    This project contains the following underlying data:

    • -

      Z1A minimum dataset 2019-06-30.csv (underlying data for all participants)

    • -

      Z1A Codebook 2019-06-30.rtf (codebook for the variables within the dataset)

    Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).


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