Post-neonatal Mortality, Morbidity, and Developmental
Outcome after Ultrasound-Dated Preterm Birth in Rural
Malawi: A Community-Based Cohort Study
Melissa Gladstone1*, Sarah White2, George Kafulafula{3, James P. Neilson1, Nynke van den Broek4
1 Department of Women’s & Children’s Health,Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom, 2 Malawi-Liverpool-Wellcome Trust
Clinical Research Programme, College of Medicine, University of Malawi, Malawi, 3 Department of Obstetrics & Gynaecology, College of Medicine, University of Malawi,
Blantyre, Malawi, 4 Liverpool School of Tropical Medicine, Liverpool, United Kingdom
Abstract
Background: Preterm birth is considered to be associated with an estimated 27% of neonatal deaths, the majority in
resource-poor countries where rates of prematurity are high. There is no information on medium term outcomes after
accurately determined preterm birth in such settings.
Methods and Findings: This community-based stratified cohort study conducted between May–December 2006 in
Southern Malawi followed up 840 post-neonatal infants born to mothers who had received antenatal antibiotic prophylaxis/
placebo in an attempt to reduce rates of preterm birth (APPLe trial ISRCTN84023116). Gestational age at delivery was based
on ultrasound measurement of fetal bi-parietal diameter in early-mid pregnancy. 247 infants born before 37 wk gestation
and 593 term infants were assessed at 12, 18, or 24 months. We assessed survival (death), morbidity (reported by carer,
admissions, out-patient attendance), growth (weight and height), and development (Ten Question Questionnaire [TQQ] and
Malawi Developmental Assessment Tool [MDAT]). Preterm infants were at significantly greater risk of death (hazard ratio
1.79, 95% CI 1.09–2.95). Surviving preterm infants were more likely to be underweight (weight-for-age z score; p,0.001) or
wasted (weight-for-length z score; p,0.01) with no effect of gestational age at delivery. Preterm infants more often
screened positively for disability on the Ten Question Questionnaire (p = 0.002). They also had higher rates of developmental
delay on the MDAT at 18 months (p = 0.009), with gestational age at delivery (p = 0.01) increasing this likelihood.
Morbidity—visits to a health centre (93%) and admissions to hospital (22%)—was similar for both groups.
Conclusions: During the first 2 years of life, infants who are born preterm in resource poor countries, continue to be at a
disadvantage in terms of mortality, growth, and development. In addition to interventions in the immediate neonatal
period, a refocus on early childhood is needed to improve outcomes for infants born preterm in low-income settings.
Please see later in the article for the Editors’ Summary.
Citation: Gladstone M, White S, Kafulafula G, Neilson JP, van den Broek N (2011) Post-neonatal Mortality, Morbidity, and Developmental Outcome after
Ultrasound-Dated Preterm Birth in Rural Malawi: A Community-Based Cohort Study. PLoS Med 8(11): e1001121. doi:10.1371/journal.pmed.1001121
Academic Editor: Gordon C. Smith, Cambridge University, United Kingdom
Received April 14, 2011; Accepted September 30, 2011; Published November 8, 2011
Copyright: ß 2011 Gladstone et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was funded by the Wellcome Trust (project grant 065810/Z/01/Z) http://www.wellcome.ac.uk/Funding/International/Global-health-research/
index.htm. No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Abbreviations: LAZ, length-for-age z score; MDAT, Malawi Developmental Assessment Tool; OR, odds ratio; SD, standard deviation; TQQ, Ten Question
Questionnaire; WAZ, weight-for-age z score; WLZ, weight-for-length z score
* E-mail: M.J.Gladstone@liverpool.ac.uk
{ Deceased.
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Outcomes of Preterm Infants in Malawi
breastfed and by 6–9 mo, 87% of infants are given complementary
foods [17].
Introduction
An estimated 3.6 million neonatal deaths occur each year,
accounting for 41% of deaths in children under 5 y old [1]. Over
three-quarters of these deaths occur in South Asia and subSaharan Africa, with causes of death often poorly documented.
Prematurity (birth at less than 37 completed wk gestation) is
considered to be associated with an estimated 27% of all neonatal deaths [2], but estimates are difficult because of uncertainties
about gestational age in many low-income countries. The very few
studies using accurate, prenatal ultrasound dating in Sub-Saharan
Africa, including our own, have reported a high incidence (15%–
22%) of preterm births [3–5].
There is good evidence that antenatal corticosteroids and
improved care in the immediate neonatal period, such as
Kangaroo Mother Care, and encouragement of early breastfeeding improve neonatal survival in the first month of life [6,7]. There
are recent estimates of post-neonatal mortality worldwide [8];
however, the information specifically about mortality and
morbidity of the surviving preterm infant in these settings is
largely unavailable.
Most previous studies come from high-resource countries and
have focused on babies born very preterm, before 32 weeks’
gestation. Almost three-quarters of preterm births occur however
between 32 and 36 wk [9,10], and these late preterm infants are
still at greater risk of infant mortality and morbidity compared to
infants born at term [11]. A comprehensive search of the literature
has identified few studies reporting medium or longer term
outcomes for babies born preterm in low-income settings. All these
studies have used proxy measures for gestational age (low birth
weight, Dubowitz scoring, or other) [12–15] with many of the
studies only reporting hospital-based births. None used prenatal
ultrasound—the most accurate method of assessing gestational
age.
The aim of our study was to assess four specific outcomes—postneonatal survival, morbidity, growth, and development—in a
community-based sample of infants born after spontaneous
preterm delivery in rural sub-Saharan Africa. All had gestational
age accurately determined using prenatal ultrasound scanning.
Study Setting and Population
We carried out a cohort study assessing mortality, morbidity,
development, and growth in post-neonatal infants who were
known to have been born preterm (,37 completed wk gestation
by ultrasound scan) (group 1) or at term (37–41 wk) (group 2). All
infants for this follow-up study were born during a placebocontrolled double blind antibiotic intervention study (APPLe trial
ISRCTN84023116) in southern Malawi. Birth weights were
recorded for those who delivered in a health facility (65.5%). In
the parent cohort population, low birth weight (,2.5 kg) was
recorded in 10.0% of babies. Serial ultrasound was not available
for this population, therefore making it impossible to diagnose
infants as being small for gestational age (due to intrauterine
growth restriction or other) during pregnancy. Nutritional status in
women was measured using BMI (kg/m2) with a mean (standard
deviation [SD]) BMI of 22.7 (2.7). More details of the APPLe
cohort can be found elsewhere [4].
Two strata were defined: babies born preterm and babies born
at term. We attempted to follow up babies who were known to
have survived the first 6 wk of life. The entire set of post-neonatal
surviving preterm babies born preterm from the APPLe trial
cohort of women was included. There were 295 preterm babies
identified for follow-up including 27 twin babies (14 pairs, one
died). 48 (16.3%) infants known to have been born preterm and to
have survived the neonatal period were lost to follow-up (moved
from area, could be not traced). For the comparison cohort, we
selected at least double the number of term-born post-neonatal
babies. This selection was done using a computer-generated
random list from the APPLe parent cohort. Following this method,
678 babies born at term were identified. 593 (87.5%) were found
at follow-up and included in the study. 85 infants known to be
born at term (12.6%) were lost to follow-up (moved from the area,
could be not traced) (Figure 1).
We aimed to assess all infants on at least one occasion at a
corrected age of 12 or 18 or 24 mo. We assessed them at this
precise age 61 wk. Corrected age was defined as chronological
age (time elapsed after birth) minus number of weeks born less
than 40 wk [19]. All assessments were carried out over a period of
7 mo from May 2006 until December 2006 using a team of six
research midwives. 16 infants (ten preterm and six term) were
assessed on two occasions 6 mo apart. These assessments are
included in the analyses of development. We present the analyses
below, with and without twins included.
Methods
Ethics Statement
We obtained written permission from each district health officer
for the four areas in which the study was conducted. The research
midwives explained the purpose of the study to each child’s parent
or carer and obtained written informed consent to participate in
the study. The study gained ethical approval from the College of
Medicine Research Ethics Committee in Malawi.
Data Collection
Socio-demographic characteristics were gathered for each
family by interviewing the mother at the time of assessment, using
a standard set of questions similar to those used in the Malawi
Demographic Health Survey [20] as recommended by the World
Bank [21].
To assess survival, we collected information on date of death,
cause of death, and place of death by interviewing the mother.
Cause of death was established using information gathered at
verbal autopsy and classified as recommended in recent studies
[22].
To assess morbidity, we collected data using a structured
questionnaire. This questionnaire included whether the child was
well at the time seen (as reported by the mother and observed by
the research nurse midwife), the number of episodes and reasons
for accessing care at a health facility, the number and reasons for
Malawi in Context
Malawi is considered to be one of the poorest countries in the
world with a per capita income of US$290 per year [16]. 80% of
the population live in rural areas and livelihoods are earned
mainly through subsistence farming. The estimated neonatal
mortality rate is 33/1,000 live births with just over 80% of births
delivered in a health facility [17]. More than 95% of women
attend for antenatal care in the community, mostly in communitybased health centres [18]. Antenatal steroids are not routinely
given to women in Malawi prior to preterm birth. Malawi has very
limited neonatal care with few units providing special care for
preterm infants. Those units that exist have oxygen, antibiotics,
and incubators and very little in the way of diagnostic facilities. In
recent surveys, 72% of children under 6 mo were exclusively
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Outcomes of Preterm Infants in Malawi
Figure 1. Flow chart of post-neonatal infants followed up in community cohort study.
doi:10.1371/journal.pmed.1001121.g001
assess for cerebral palsy, as this is a clinical diagnosis that without
further assessments and imaging was not able to be diagnosed in
this rural African setting.
being admitted to hospital in the past, and, specifically, whether
the child had ever had convulsions.
Growth was assessed for each child by measuring length and
nude weight. Weight was measured using electronic infant
weighing scales (SECA 735) with reading increments of 10 g.
Length was measured to the nearest 0.5 cm using standard locally
made length measurement boards based on blueprints for their
construction from the World Health Organization and the US
Centers for Disease Control (Atlanta, Georgia) [23]. All growth
data were collected by the research nurse midwives who had been
specifically trained prior to the start of the study. Training used the
‘‘my measure’’ formulas for anthropometeric standardisation as
recommended by the Anthropometric Indicators Measurement
Guide [24]. At recommended stages of training, ten children had
their height and weight measurements repeated on two occasions
by each research midwife. Training continued with the research
midwives until satisfactory accuracy was obtained. We asked each
mother whether the child was still breastfeeding at the time of
assessment.
Development and disability were assessed using the Ten
Question Questionnaire (TQQ) [25] and the Malawi Developmental Assessment Tool (MDAT), which we have described
previously [26]. The MDAT has demonstrated good reliability,
construct validity, and sensitivity in predicting moderate to severe
neurodisability and developmental delay in a Malawian population of malnourished children. We used the MDAT to assess
children in two ways: through a pass/fail scoring system and
through a numerical scoring system applied to each of four
domains of development [26]. Only eight of the ten questions in
the TQQ were used as the children were all under 2 y and
questions 8 and 9 regarding speech and language were not
appropriate for this age group. We were unable to specifically
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Statistical Analysis
All data were double entered and verified, hosted on a
password-protected SQL server with any discrepancies and
outlying results reviewed. Mothers and babies were identified
only by the mother’s identification number and in the case of
twins, the twin number. Data were analysed using SPSS for
Windows version 17 and Stata version 10. All available data were
included in the analyses.
Analyses compared data for infants and their mothers in the
preterm and term delivery groups. All infants were used in the
analysis, except where stated otherwise. Survival of infants in each
of these strata was estimated using Kaplan-Meier curves and
compared using a Cox’s proportional hazards model. Gender was
also included in the Cox’s proportional hazards analysis. When
date of death was not reported (six cases) it was assumed to have
been mid-way between birth and the assessment visit. For all other
analyses, when data required for an analysis was missing the
record was omitted from analysis. Socio-economic status was
measured using principal components analysis of multiple assets
following methods from the World Bank [21,27]. Socio-economic
quintiles for the two groups of mothers were analysed using logistic
regression with term/preterm as the binary outcome.
Weight-for-corrected-age (WAZ), height-for-corrected-age (HAZ),
and weight-for-height z (WHZ) scores were derived using Epi-info
version 3.2.2 with World Health Organization reference data
[28,29]. All analyses, except survival analyses, used corrected age
(defined above). Growth data and MDAT scores were each analysed
using linear regression models with gestational age at delivery as a
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Outcomes of Preterm Infants in Malawi
term-born infants died; Cox PH x2 = 5.05, p = 0.02. The
estimated hazard ratio (95% CI) for preterm compared with
term-born infants is 1.79 (1.09–2.95) (Figure 3). With twin
preterm-born infants excluded, Cox PH x2 = 2.76, p = 0.10 and
hazard ratio is 1.58 (0.93–2.69). The estimated mortality rates for
infants born preterm who had survived the neonatal period was
almost double that of infants born at term. At 1 y, there was an
estimated mortality rate of 7.7% (5.0–11.8) for preterm and 4.0%
(2.7–6.0) for term infants, and at 2 y (cumulative) a rate of 13.2%
(8.9–19.3%) and 7.6% (5.4–10.6), respectively (Table 1). Mortality rates were also significantly higher for boys compared with
girls. Cox PH x2 = 9.23, p = 0.002; the estimated hazard ratio
(95% CI) for male compared with female infants is 2.19 (1.30–
3.68).
There were very few babies born with a gestational age under
32 wk (very preterm) who survived the post-neonatal period in our
cohort (n = 10). Within this group, only one of these was found
dead on follow-up (Figure 2). The numbers are small, but when
analysed, we found no significant differences in mortality between
babies born less than 32 wk and those born between 32 and 37 wk
(Pearsons chi 0.439).
Information on cause of death was available for 23 of 27
(85.2%) infants born preterm and 37 of 37 (100%) infants born
at term (Table 2). We identified five main causes of death in
post-neonatal infants: gastroenteritis (36.7%), malaria (15%),
respiratory problems (15%), anaemia (15%), and fever (6.7%).
In the preterm group there were more reported deaths due to
respiratory problems (17.4% versus 13.5) and fewer due to
gastroenteritis (26.1% versus 43.2%) but the differences were
not statistically significant. By gender, more term males than
females died of gastroenteritis, malaria, and fever. In the
preterm group, more females died of respiratory illness (four
versus 0), but more males died of other conditions such as
malaria and fever. None of these differences were statistically
significant.
covariate in the model for both sets of scores; age at assessment was
an additional covariate in the analysis of MDAT scores. Stratified
Mantel-Haenszel tests were used to examine the association of each
of three indices of growth (WAZ and length-for-age [LAZ] and
weight-for-length [WLZ] z scores), and the number of times health
care was accessed with prematurity, stratified by age of assessment.
Other binary or categorical outcomes were analysed using Pearson
chi square tests unless otherwise stated.
Stratified Mantel-Haenszel tests were also used to examine
the association between being underweight (WAZ,22) and
identification of disability on the TQQ or severe developmental
delay on the MDAT. Stratification was by whether preterm or
not and by age of assessment to control for the influence of these
factors.
Results
Population Followed Up
A total of 840 post-neonatal infants were followed up, of whom
247 were born preterm and 593 were born at term (Figure 1).
Among these, 12 pairs of twins were born preterm (24 babies) and
one set of twins (two babies) were born at term. Among preterm
births, gestational age at birth (given in completed weeks of
gestation) was above 34 wk for 203/247 infants (82.2%), either 32
or 33 wk for 34/247 infants (13.8%), and between 28 to 31 wk for
9/247 (3.6%) with only one infant born below 28 wk. Figure 2
shows the distribution of gestational age at birth of the cohort
followed up. At time of assessment, the mean corrected ages for
the two groups were equal. Female babies were more prevalent in
the preterm group (58%) than in the term group (50%).
Survival
Post-neonatal infants born preterm were at significantly greater
risk of death (during the 6-wk to 24-mo follow-up period) than
those born at term: 27/247 (10.9%) preterm and 37/593 (6.2%)
Figure 2. Number of post-neonatal infants followed up by gestational age at birth.
doi:10.1371/journal.pmed.1001121.g002
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Outcomes of Preterm Infants in Malawi
Figure 3. Kaplan Meyer curves: survival of post-neonatal infants born preterm and at term (likelihood ratio X2 statistic: 5.05;
p = 0.02).
doi:10.1371/journal.pmed.1001121.g003
Haenszel M2 = 0.03, p = 0.86). Nonroutine reasons for attendance
to the health centre included malaria, respiratory problems,
diarrhoea, upper respiratory tract infections, skin rashes, and
fever. Only two mothers reported going to the health centre
because their child was malnourished. Visits for routine immunisations (97.4% [preterm] versus 98.9% [term]) and weighing
82.5% (preterm) versus 85.6% (term) were found to be similar.
There were no significant differences in the preterm versus term
group in the number of infants reported to have been admitted to
Morbidity
Mothers did not commonly report morbidity at the time of
assessment (12, 18, or 24 mo) with 98.7% (226/229) of the
preterm group and 97.9% (550/562) of the term group reported to
be well at the time of interview. Despite this, reported attendance
to the health centre was high in both infants born preterm (94.3%)
and those born at term (91.3%) with no significant difference
between the groups. The (median) numbers of times that health
care was accessed were 3, 3, and 4 times at 12, 18, and 24 mo of
age, and did not differ significantly between the groups (Mantel-
Table 2. Cause of death by verbal autopsy of babies born at
term and preterm (by gender).
Table 1. Mortality rates at 1 and 2 y for infants born preterm
or at term (by gender) with twins included in analysis.
Cause of Deatha
Age
Grouping
Preterm
Term
1y
Overall
7.7% (5.0%–11.8%)
4.0% (2.7%–6.0%)
By gender
2y
Preterm
Term
Boys
Boys
Girls
Girls
Total n infants who died
14
13
28
9
Gastroenteritis (diarrhoea and vomiting)
3
3
11
5
Boys
8.8% (4.7%–16.2%)
5.5% (3.4%–8.8%)
Respiratory problem
0
4
3
2
Girls
6.9% (3.8%–12.5%)
2.5% (1.0%–5.2%)
Anaemia
1
1
1
1
Overall
13.2% (8.9%–19.3%)a
7.6% (5.4%–10.6%)
Malaria
2
2
5
0
Fever
2
0
2
0
Boys
16.8% (9.9%–27.9%)
11.2% (7.7%–16.3%)
Other
4
1
6
1
Girls
10.5% (5.9%–18.3%)
3.8% (1.9%–7.6%)
Total n causes of death reported (by gender)
12
11
28
9
By gender
a
a
Without twins: 12% (7.8%–18.3%).
doi:10.1371/journal.pmed.1001121.t001
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Total n causes of death reported: preterm, 23; term, 37.
doi:10.1371/journal.pmed.1001121.t002
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a hospital (58/230; 25.2% versus 116/559; 20.8%). The median
number of admissions was 1.0 in each of the groups. Infants born
preterm were more likely to be admitted for cerebral malaria
(3.5% versus 1.8%) or anaemia (3.9% versus 2.1%), but this was
not statistically significant. Similar proportions were admitted for
simple malaria (9.2% versus 9.9%) and pneumonia (5.7% versus
5.0%). Other causes for admission were sepsis (reported only in
four cases), meningitis (one case), and malnutrition (five cases).
HIV/AIDS was not reported by parents as a cause of admission to
hospital. There were no significant differences in the number of
children experiencing convulsions, as reported by parents, preterm
compared to term-born children: 10.4% (22/211) versus 6.9%
(38/548) (p = 0.13).
10) (p = 0.005) were the items that were significantly more frequent
in infants.
In terms of overall pass/fail on the MDAT, more children in the
preterm group compared to the term group failed the MDAT at
each stage of assessment; at 12 mo this was 6.7% versus 2.9%
(p = 0.216), at 18 mo 22.8% versus 10.9% (p = 0.009), and at
24 mo 12.8% versus 10.7% (p = 0.274). Significant differences
were also found specifically at 18 mo for language development
(p = 0.033) (Table 5). When development was assessed on the
MDAT using numerical scores, there were significant changes
with gestational age (wk) at delivery in gross motor (0.15/wk;
p = 0.02), social development (0.24/wk; p = 0.004), and overall
development at 18 mo (0.79/wk; p = 0.01), and in social
development (0.21/wk; p = 0.02) at 24 mo (Table 6).
The number of children demonstrating severe delay on the
MDAT (delay greater than 2 SD from the mean expected score for
the age of the child) was the same across the two groups (9/230
preterm infants [3.9%] versus 23/562 term infants [4.1%]).
Growth
When assessing growth/nutritional parameters for the cohorts,
preterm infants were significantly more likely to be underweight
(p,0.001). Almost one-third (32.3%) of preterm infants were
moderately underweight (below 22 SD WAZ) and 11.1% severely
underweight (below 23 SD WAZ) (Table 3). Preterm infants were
also more likely to be moderately wasted (WLZ below 22 SD),
with a quarter (24.9%) of preterm infants moderately wasted
although the groups had similar levels of severe wasting (WLZ.3
SD below mean). In assessing for the effect of gestational age on
the growth parameters, the estimated increase in WAZ and WLZ
scores per additional week of gestational age was 0.08 (0.05–0.11)
and 0.07 (0.02–0.11), respectively. Stunting (below 22 SD for
LAZ) was common in both term- (38.3%) and preterm- (42.6%)
born children; the effect of each additional week of gestational age
at delivery (0.05 [20.005 to 0.10]) was not significant (p = 0.08).
Breastfeeding rates for preterm infants (100%) and term infants
(98.6%) at 12 mo were very similar (p = 1.0). There was a trend for
lower rates of breastfeeding in the preterm infants at 18 mo
(80.7%) versus term infants (89.6%) (p = 0.057) and also at 24 mo
for preterm (44.2%) versus term infants (48.3%) (p = 0.59), but
neither were significant.
Growth and Development
We analysed the association between growth and development
in this cohort. We used WAZ as these were the most robust of our
three measures. There was a significant association between being
underweight and positive on the disability screen (overall odds
ratio [OR], 95% CI 2.88 [1.81–4.61]), or having severe delay on
the MDAT (,22 SD) (overall OR, 95% CI 4.06 [1.98–8.32]).
The association was similar for both term and preterm infants
(Table 7).
Discussion
This study has clearly shown that infants who are born
prematurely in a rural community setting in sub-Saharan Africa,
who survive the first month of life, are still up to twice as likely to
die as term infants during the first 2 y of life with a cumulative
mortality rate of 132/1,000 in comparison with those born at
term (76/1,000). This cohort of preterm infants is unique because
gestational age was established by ultrasound dating. We have
shown that these infants are almost entirely a population of late
preterm infants, but despite this, are still more likely to have
higher rates of malnutrition and developmental delay than term
infants. As rates of prematurity are high in sub-Saharan African settings [3–5,30], this study provides evidence to show how
crucial it is to concentrate on improving outcomes within this
group.
Development
The post-neonatal infants born preterm were significantly more
likely than term-born infants to screen positive overall on the
TQQ (Table 4) (p = 0.002), with 32/230 (13.9%) of the preterm
infants and 38/562 (6.8%) of the term infants scoring positive on
one or more questions. Serious delay in walking, standing, or
sitting (question 1) (p = 0.049) or being slow in comparison to
children of the same age (neurodevelopmentally delayed; question
Table 3. Summary of WAZ, LAZ, and WLZ for preterm and term babies with estimated effects of gestational age at delivery from
linear regression.
Growth
Measurement
WAZ
WLZ
LAZ
Proportions Undernourished
Regression Analysis
12–23 mo
Children MDHS
Preterm
Term
Effect of Gestational
Age (wk) (95% CI)
,22 SD
28.8%
73/226 (32.3%)
122/556 (22.9%)
0.078 (0.045–0.111)
,0.001
,23 SD
7.4%
25/226 (11.1%)
25/556 (4.5%)
—
—
,22 SD
6.8%
56/225 (24.9%
91/551 (16.5%)
0.065 (0.016–0.114)
0.01
,23 SD
1.8%
16/225 (5.9%)
33/551 (6.0%)
—
—
,22 SD
60.7%
98/230 (42.6%)
213/556 (38.3%)
0.046 (20.005 to 0.097)
0.08
,23 SD
30.3%
45/230 (19.6%)
79/556 (14.2%)
—
—
Category
p-Value
MDHS, Malawi Demographic Health Survey [20].
doi:10.1371/journal.pmed.1001121.t003
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Table 4. Number and percentage of children positive on the TQQ for each question and overall scored positive in one or more
question.
Question Number
Reason for Being Positive on TQQ
n Preterm
(n = 230) (%)
n Term
(n = 562) (%)
Total n
(n = 792) (%)
p-Value
1
Serious delay in sitting, standing, or walking
20 (8.7)
28 (5)
48 (6)
0.049
2
Difficulty seeing (daytime or night)
1 (0.4)
5 (0.9)
6 (1)
0.34
3
Difficulty hearing
1 (0.4)
1 (0.2)
2 (0.2)
0.516
4
Problems understanding what you are saying
3 (1.5)
2 (0.4)
5 (0.6)
0.121
5
Difficulty walking or moving his/her arms or
weakness or stiffness in arms and legs
5 (2.2)
7 (1.3)
12 (1.5)
0.332
6
Child sometimes has fits, become rigid, or lose
consciousness
9 (3.9)
11 (2.0)
20 (2.5)
0.112
7
Child not learning to do things like others at his age?
9 (3.9)
13 (2.3)
22 (2.8)
0.221
10
Does the child appear mentally backward or
slow compared to others of same age?
11 (4.8)
8 (1.4)
19 (2.4)
0.005
Scored positive in one or
more of above questions
—
32 (13.9)
38 (6.8)
70 (8.8)
0.002
doi:10.1371/journal.pmed.1001121.t004
Recent studies from high-income countries have also demonstrated this relatively increased mortality in late preterm babies;
however, outcomes have mainly been measured only in the
neonatal period [11]. Studies have suggested that causative factors
may include thermal instability, hypoglycaemia, respiratory
distress, apnoea, jaundice, and feeding difficulties [31]. There is
a dearth of evidence from developing countries, but it could be
surmised that infants born in the late preterm period in rural
African settings are likely to be at increased risk for many of these
problems with high levels of poverty, poor post-natal care, and
high infection rates. Moreover, the population of infants in our
study were not exposed to antenatal steroids and will be more
likely to suffer from respiratory distress syndrome and related
respiratory disorders [32]. These late preterm infants may also be
malnourished due to feeding difficulties that cannot be augmented
through supplementary feeding methods present in high-income
settings. Poor nutrition will affect immune status and further lead
to an increased risk of infection. There is some limited evidence
that extra care of preterm-born infants in Asia, such as home care,
skin-to-skin contact, and additional support for breastfeeding, may
have some potential to prevent death in this group [7,33,34]. At
the time of this study, Kangaroo Mother Care was limited in the
Table 5. Comparisons of mean MDAT scores and percentage passing/failing for each domain of development, for preterm and
term babies, by age at assessment.
Domain of
Development
Statistic
Age of Assessment (mo)
12 mo
18 mo
24 mo
Preterm
n = 62a
Term
n = 143b
Percent fail
4.8%
Score
14.4
Fine motor
Percent fail
1.7%
Score
16.1
15.8
0.558
18.7
19.0
0.443
20.2
21.1
0.062
Language
Percent fail
1.6%
0.7%
0.552
2.2%
0%
0.033
2.6%
1.5%
0.554
Score
10.2
10.4
0.551
12.6
12.5
0.909
14.9
15.9
0.017
Social
Percent fail
0%
0%
—
6.8%
5.5%
0.655
3.8%
5.7%
0.513
Score
12.6
12.7
0.721
16.7
17.8
0.011
20.4
21.3
0.04
Percent fail
6.7%
2.9%
0.216
22.8%
10.9%
0.009
12.8%
10.7%
0.274
Score
53.1
52.9
0.93
66.3
68.3
0.04
75.5
77.7
0.081
Gross motor
Total
p-Value
Preterm
n = 89c
Term
n = 205d
p-Value
Preterm
n = 79e
Term
n = 215f
p-Value
3.5%
0.649
12.5%
14.7
0.433
18.5
8.3%
0.261
3.8%
3.3%
0.806
19.2
0.023
19.9
20.3
0.7%
0.535
3.5%
0.201
1.6%
0.300
9.1%
3.4%
0.053
a
For each domain up to two (3.3%) children were not assessed.
For each domain up to six (4%) children were not assessed.
For each domain up to four (4.5%) children were not assessed.
d
For each domain up to 13 (6.3%) children were not assessed.
e
For each domain up to two (2.5%) children were not assessed.
f
For each domain up to 19 (8.8%) children were not assessed.
doi:10.1371/journal.pmed.1001121.t005
b
c
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Outcomes of Preterm Infants in Malawi
Table 6. Summary of linear regression estimates of effect of gestational age at delivery and assessment age for MDAT scores.
Domain of
n 12 mo, 18 mo,
Development 24 mo
Estimate of Increase in MDAT Score per Additional Week of Gestational Age
12 mo
p-Value
18 mo
p-Value
Effect (95% CI)
24 mo
Effect (95% CI)
p-Value
Effect (95% CI)
0.10 (20.01 to 0.21)
Gross motor
205, 293, 294
0.74
20.02 (20.15 to 0.10)
0.02
0.15 (0.03–0.27)
0.08
Fine motor
200, 281, 280
0.12
20.15 (20.35 to 0.04)
0.57
0.05 (20.12 to 0.21)
0.20
0.11 (20.06 to 0.28)
Language
202, 289, 273
0.77
0.01 (20.07 to 0.10)
0.69
0.02 (20.07 to 0.11)
0.06
0.14 (20.01 to 0.28)
Social
204, 289, 289
0.89
20.01 (20.17 to 0.15)
0.004
0.24 (0.08–0.41)
0.02
0.21 (0.04–0.38)
Overall
205, 294, 295
0.42
20.17 (20.59 to 0.24)
0.01
0.79 (0.10–0.87)
0.09
0.41 (20.06 to 0.88)
Age at assessment was included as a covariate in these analyses.
doi:10.1371/journal.pmed.1001121.t006
morbidity in children is not available and further studies using
other approaches are very much warranted [38].
In our cohort, children born preterm were significantly more
likely to be underweight and wasted and did not demonstrate
catch-up growth in contrast to those born at term. Comparison
with studies from high-income settings is difficult as most have
studied very preterm or low birth weight infants [39,40]. We have
identified one other community cohort study from a middleincome country (Brazil) reporting a 3% rate for being underweight
with a comparison to terms of 0.8% [41]. Rates in our study were
much higher (32.3% for term infants and 22.9% for preterms),
suggesting a much higher overall level of malnutrition in this rural
sub-Saharan African population. Despite this level, only 0.5% of
children in our study were admitted for malnutrition despite
routine weighting of babies. This finding suggests that there must
be some difficulties for health care providers in either recognising
or referring these children with malnutrition. In our population,
weight was the indicator that most clearly showed demonstrable
differences between the two groups. Weight is often a more
sensitive measure of differences between groups and it is
recognised that length is consistently more difficult to measure
accurately than weight [23]; this may reflect why significant
differences between the groups were seen for WAZ and WLZ but
not LAZ. The higher-than-expected levels of low WLZs in our
population may also be a reflection of this. It may be that we were
observing more acute changes in malnutrition in our sample. We
did not have accurate birth weights on enough of the infants to be
able to measure change in weight over time between the two
groups. Therefore it is not clear from our study whether the
community and district health care settings in Malawi, but services
are now being scaled up and hopefully may improve rates of postneonatal mortality in these late preterm-born infants [35].
Male infants within our cohort of infants born at term were
more likely to die than female infants in the post-neonatal period.
There is limited evidence that gender does have an effect on
perinatal, neonatal [36], and under five death rates [37], but the
reasons for this are not clear.
There is little information on cause of death in infants in
resource-poor settings, particularly in early infancy. Verbal
autopsy tools in this population were found to be useful and we
documented more deaths in preterm infants associated with
respiratory problems compared to infants born at term. In the
absence of an agreed definition and framework for measuring
morbidity in community settings in children, we used reported
health-seeking behaviour as a proxy measure. Almost all mothers
reported their children as well at the time of the study taking place.
Almost all mothers had visited a health centre for routine weighing
and immunisation and almost one in four children had been
admitted as an inpatient in the first 2 y of life. There was no
difference in health-seeking behaviour between babies born
preterm and those born at term. The reports from the mothers
of their children being ‘‘well’’ at the time of the study was
surprising considering the morbidity we then encountered in terms
of malnutrition, developmental delay, and the high rates of
admission to the health centre. Our tools for assessing morbidity
were clearly not specific enough and highlight that parentreported morbidity is not a good measure of childhood morbidity.
Currently, an agreed framework or standard for measuring
Table 7. Associations between being underweight (WAZ,22) and developmental delay assessed by the TQQ and the MDAT for
all babies and by preterm or not status.
Assessment
Cohort
ORa
95% CI
p-Value
Positive score on TQQ
All
3.18
1.92–5.29
,0.001
Term babies
3.80
1.93–7.45
,0.0001
Preterm
2.59
1.19–5.63
0.013
,0.0001
MDAT score ,22 SD from the normal range.
All
4.06
1.98–8.32
Term babies
4.95
2.09–11.7
,0.001
Preterm
2.63
0.69–10.1
0.14
a
Stratified by age at assessment and, for all babies by whether premature or not.
doi:10.1371/journal.pmed.1001121.t007
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Outcomes of Preterm Infants in Malawi
significant differences in WAZs between the two groups may be
more innately related to preterm infants also being born small for
gestational age and never catching up. There were no significant
differences in breastfeeding rates at each of the ages assessed to
account for the differences in weight between the two groups. We
did not have information about supplementary feeding and age of
introduction. Considering our findings however, longitudinal
studies in this population using both ultrasound to measure
gestational age, birth weights, and serial growth measurements
with clearer assessments of breastfeeding and complementary feeds
could clarify some of these issues.
Infants born preterm were twice as likely to be identified as
having a disability using the TQQ as well as to fail the MDAT.
Studies from high-income countries have demonstrated educational difficulties in children born late preterm. As far as we are
aware, there are no similar studies on developmental outcomes in
cohorts of accurately gestationally dated late preterm-born infants
from a low-income setting. A study in Bangladesh measured
development using a variety of more complex assessment tools
adapted from those in high-income countries (Bayley II and
Stanford Binet) [12]. This study demonstrated significant differences in development, at a slightly higher level than ours, but the
babies were much more preterm (,33 wk gestation) and dated
using proxy measures. We have shown that a two-stage approach
[42] using the TQQ followed by a more detailed developmental
assessment using culturally appropriate assessment tools (such as
the MDAT) is feasible even in the most rural settings. Caution is
needed, however, when attributing importance to these early
assessments of mild impairment as found by using a developmental
assessment tool such as the MDAT. Follow-up of this cohort
beyond the preschool period would be extremely beneficial to
assess the actual amount of impairment, particularly as we found
no differences in severe delay between the preterm and the term
groups.
It is widely recognised that both nutrition and prematurity have
an impact on development. We confirmed that these associations
are present in this population from sub-Saharan Africa, but the
cross-sectional nature of this study did not allow us to evaluate this
relationship in more detail—this would clearly be an interesting
area for further research. We suggest that in the absence of more
sophisticated screening mechanisms, weight and development
could be used as ‘‘morbidity markers’’ and serve as an entry point
for identifying other health needs especially for babies born
preterm.
Conclusions
To date, interventions in low-income settings to reduce neonatal
morbidity and mortality have targeted the perinatal period. Our
data show that, for surviving preterm babies who survive the
immediate neonatal period, even in this mainly late preterm-born
surviving group, there is ongoing disadvantage with increased risk
of death, growth retardation, and developmental delay. Further
detailed qualitative and longitudinal studies to assess the causal
mechanisms for these problems would be extremely beneficial.
Along with these studies, post-neonatal interventions need to be
trialled that might improve outcomes in this group of pretermborn children.
Acknowledgments
We would like to acknowledge all the research midwives who collected data
for the study, particularly the Senior Research Midwives, Edith Kayira and
Chikondi Ntonya, and all carers and children from Southern Malawi who
took part in the study. We would also like to acknowledge Mark Turner
(senior lecturer in neonatology), James Bunn (senior lecturer in tropical
child health), and Marko Kerac (lecturer in child health) for their helpful
comments on the data and manuscript. We would also like to thank all the
carers and children who took part in the study. George Kafulafula, listed as
the final author of this paper, died before its publication. The
corresponding author, Melissa Gladstone, has therefore supplied the
information regarding his contribution to the manuscript and his
competing interests and it is correct to the best of her knowledge
Author Contributions
Conceived and designed the experiments: MG NvD GK JN SW. Analyzed
the data: MG SW NvDB. Contributed reagents/materials/analysis tools:
SW. Wrote the first draft of the manuscript: MG NvDB SW. Contributed
to the writing of the manuscript: MG NvDB SW JN. ICMJE criteria for
authorship read and met: MG SW GK JN NvDB. Agree with manuscript
results and conclusions: MG SW GK JN NvDB.
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Editors’ Summary
the babies born at term, the infants born preterm were
nearly twice as likely to die subsequently in the next two
years, were more likely to be underweight (a third were
moderately underweight), and to have higher rates of
developmental delay. The commonest causes of death
were gastroenteritis, respiratory problems, and malaria.
Visits to a health center and admissions to hospital were
similar in both groups.
Background Being born at term in Africa is not necessarily
straightforward. In Malawi, 33 of every 1,000 infants born die
in the first 28 days after birth; the lifetime risk for a mother
dying during or shortly after pregnancy is one in 36. The
comparable figures for the United Kingdom are three infants
dying per 1,000 births and a lifetime risk of maternal death of
one in 4,700. But for a baby, being born preterm is even
more risky and the gap between low- and high-income
countries widens still further. According to a World Health
Organization report in 2010, a baby born at 32 weeks of
gestation (weighing around 2,000 g) in Africa has little
chance of survival, while the chances of survival for a baby
born at 32 weeks in North America or Europe are similar to
one born at term. There are very few data on the longer term
outcomes of babies born preterm in Africa and there are
multiple challenges involved in gathering such information.
As prenatal ultrasound is not routinely available, gestational
age is often uncertain. There may be little routine follow-up
of preterm babies as is commonplace in high-income
countries. Data are needed from recent years that take into
account both improvements in perinatal care and adverse
factors such as a rising number of infants becoming HIV
positive around the time of birth.
What Do these Findings Mean? This study documents
longer term outcomes of babies born preterm in subSaharan Africa in detail for the first time. The strengths of the
study include prenatal ultrasound dating and correct
adjustment of follow-up age (which takes into account
being born before term). Because the researchers defined
morbidity using routine health center attendances and selfreport of illnesses by parents, this outcome does not seem to
have been as useful as the others in differentiating between
the preterm and term babies. Better means of measuring
morbidity are needed in this setting.
In the developed world, there is considerable investment
being made to improve care during pregnancy and in the
neonatal period. This investment in care may help by
predicting which mothers are more likely to give birth early
and preventing preterm birth through drug or other
treatments. It is to be hoped that some of the benefit will
be transferable to low-income countries. A baby born at 26
weeks’ gestation and admitted to a neonatal unit in the
United Kingdom has a 67% chance of survival; preterm
babies born in sub-Saharan Africa face a starkly contrasting
future.
Why Was This Study Done? We could improve outcomes
for babies born preterm in sub-Saharan Africa if we
understood more about what happens to them after birth.
We cannot assume that the progress of these babies will be
the same as those born preterm in a high-income country, as
the latter group will have received different care, both before
and after birth. If we can document the problems that these
preterm babies face in a low-income setting, we can consider
why they happen and what treatments can be realistically
tested in this setting. It is also helpful to establish baseline
data so that changes over time can be recorded.
The aim of this study was to document four specific
outcomes up to the age of two years, on which there were
few data previously from rural sub-Saharan Africa: how many
babies survived, visits to a health center and admissions to
the hospital, growth, and developmental delay.
Additional Information. Please access these Web sites via
the online version of this summary at http://dx.doi.org/10.
1371/journal.pmed.1001121.
N
N
What Did the Researchers Do and Find? The researchers
examined a group of babies that had been born to mothers
who had taken part in a randomized controlled trial of an
antibiotic to prevent preterm birth. The trial had previously
shown that the antibiotic (azithromycin) had no effect on
how many babies were born preterm or on other measures
of the infants’ wellbeing, and so the researchers followed up
babies from both arms of the trial to look at longer term
outcomes. From the original group of 2,297 women who
took part in the trial, they compared 247 infants born
preterm against 593 term infants randomly chosen as
controls, assessed at 12, 18, or 24 months. The majority of
the preterm babies who survived past a month of age (all
but ten) were born after 32 weeks of gestation. Compared to
PLoS Medicine | www.plosmedicine.org
N
N
N
11
UNICEF presents useful statistics on mother and child
outcomes
The World Health Organization has attempted to analyse
preterm birth rates worldwide, including mapping the
regional distribution and has also produced practical
guides on strategies such as Kangaroo Mother Care, which
can be used for the care of preterm infants in low resource
settings
Healthy Newborn Network has good information on
initiatives taking place to improve neonatal outcomes in
low income settings
The March of Dimes, a nonprofit organization for
pregnancy and baby health, provides information on
research being conducted into preterm birth
Tommy’s is a nonprofit organization that funds research
and provides information on the risks and causes of
premature birth
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