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DOI: 10.1542/peds.2012-2177; originally published online March 18, 2013;2013;131;e1240Pediatrics
Neena ModiJames R.C. Parkinson, Matthew J. Hyde, Chris Gale, Shalini Santhakumaran and
and Meta-analysisPreterm Birth and the Metabolic Syndrome in Adult Life: A Systematic Review
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Preterm Birth and the Metabolic Syndrome in Adult Life:
A Systematic Review and Meta-analysis
abstractBACKGROUND:Preterm birth is associated with features of the met-
abolic syndrome in later life. We performed a systematic review and
meta-analysis of studies reporting markers of the metabolic
syndrome in adults born preterm.
METHODS: Reports of metabolic syndromeassociated features in
adults ($18 years of age) born at ,37-week gestational age and
at term (37- to 42-week gestational age) were included. Outcomes
assessed were BMI, waist-hip ratio, percentage fat mass, systolic
(SBP) and diastolic (DBP) blood pressure, 24-hour ambulatory SBP
and DBP, ow-mediated dilatation, intima-media thickness, and fastingglucose, insulin, and lipid proles.
RESULTS:Twenty-seven studies, comprising a combined total of 17 030
preterm and 295 261 term-born adults, were included. In adults,
preterm birth was associated with signicantly higher SBP (mean
difference, 4.2 mm Hg; 95% condence interval [CI], 2.8 to 5.7; P,
.001), DBP (mean difference, 2.6 mm Hg; 95% CI, 1.2 to 4.0; P, .001),
24-hour ambulatory SBP (mean difference, 3.1 mm Hg; 95% CI, 0.3 to
6.0;P= .03), and low-density lipoprotein (mean difference, 0.14 mmol/L;
95% CI, 0.05 to 0.21; P = .01). The pretermterm differences for
women was greater than the pretermterm difference in men by
2.9 mm Hg for SBP (95% CI [1.1 to 4.6], P= .004) and 1.6 mm Hg forDBP (95% CI [0.3 to 2.9], P= .02).
CONCLUSIONS:For the majority of outcome measures associated with
the metabolic syndrome, we found no difference between preterm
and term-born adults. Increased plasma low-density lipoprotein in
young adults born preterm may represent a greater risk for
atherosclerosis and cardiovascular disease in later life. Preterm
birth is associated with higher blood pressure in adult life, with
women appearing to be at greater risk than men. Pediatrics
2013;131:e1240e1263
AUTHORS:James R.C. Parkinson, PhD, Matthew J. Hyde, PhD,Chris Gale, MBBS, Shalini Santhakumaran, MSc, and Neena
Modi, MD
Section of Neonatal Medicine, Department of Medicine, Imperial
College London, London SW10 9NH, United Kingdom
KEY WORDS
preterm, adult, blood pressure, meta-analysis
ABBREVIATIONS
aDBP24-hour ambulatory diastolic BP
aSBP24-hour ambulatory systolic BP
CIcondence interval
DBPdiastolic blood pressure
FMfat mass
FMDow-mediated dilatation
GAgestational age
HDLhigh-density lipoprotein
IMTintima-media thickness
LDLlow-density lipoprotein
PWVpulse wave velocity
SBPsystolic blood pressure
SESsocioeconomic status
WHRwaist-hip ratio
Dr Parkinson helped to design the study, extracted and veried
raw data from publications, carried out initial analysis, drafted
the initial manuscript, and approved the nal manuscript as
submitted. Dr Hyde independently veried raw data from
publications, assisted in the preparation of the manuscript, and
approved the nal manuscript as submitted. Dr Gale
independently veried raw data from publications, assisted inthe preparation of the manuscript, and approved the nal
manuscript as submitted. Ms Santhakumaran performed
statistical analysis, assisted in the preparation of the
manuscript, and approved the nal manuscript as submitted.
Dr Modi conceived and helped design the study, assisted in the
preparation of the manuscript, and approved the nal
manuscript as submitted.
Drs Parkinson, Hyde, and Modi are co-authors for the reference
Thomas et al 2011 included in this meta-analysis.
(Continued on last page)
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Metabolic and cardiovascular diseases
impose a substantial burden on pop-
ulation health. In addition to a sub-
optimal adult lifestyle, experiences in
early life are believed to contribute to
the development of these conditions.1
Preterm infants, born at,37 weeks ofgestation age (GA), are part of the low-
birth-weight spectrum, and their early
neonatal period, corresponding to the
third trimester of pregnancy, differs
from conditions in utero. Approxi-
mately 6% to 12% of births in the de-
veloped world are preterm, with the
absolute number rising globally. In the
United Kingdom, 70 000 babies are
born at ,37-week GA annually, and
.
99% survive, resulting in a growingadult preterm population.2
A number of studies have identied
pretermbirthasariskfactorforfeatures
of the metabolic syndrome in later life,
including higher blood pressure36 and
insulin resistance.7,8 However, additional
data indicate no negative impact of
preterm birth on atherosclerosis,9 sys-
tolic blood pressure (SBP),10 or insulin
sensitivity.11
Here, we conduct a systematic reviewand meta-analysis to address the as-
sociation between preterm birth and
key features of themetabolic syndrome
in adult life, including BMI, waist-hip
ratio (WHR), percentage fat mass
(percent FM), blood pressure, cardio-
vascular indices, and fasting glucose,
insulin, and plasma lipids. We aimed to
investigate the effect sizes, examine
potential sources of heterogeneity in
published data, and identify gender-
specic effects.
METHODS
A systematic review of studies com-
paring adults ($18 years of age) born
preterm (,37-week GA) and at term
(37- to 42-week GA) was undertaken in
accordance with Preferred Reporting
Items for Systematic Reviews and Meta-
Analyses guidelines.12 Two searches
were conducted separately in PubMed
(www.ncbi.nlm.nih.gov ) for studies
published before October 1, 2011, in
any language, and limited to human
studies.
Search A: Blood Pressure andCardiovascular Indices
The following medical subject heading
key words were used: ((Premature
Birth) OR (Low Birth weight) OR (Infant,
Premature)) AND ((Hypertension) OR
(Blood Pressure) OR (Diagnostic Tech-
niques, Cardiovascular)) AND ((Adult)
OR (Adolescence)).
Search B: Additional Markers of
the Metabolic Syndrome
The following medical subject heading
key words were used: ((Premature
Birth) OR (Low Birth weight) OR (Infant,
Premature)) AND ((Body Weights and
Measures) OR (Obesity) OR (Adipose
Tissue) OR (Dyslipidemia) OR (Insulin
Resistance) OR (Blood Chemical Anal-
ysis)) AND ((Adult) OR (Adolescence)).
Forward citations were traced, and
where multiple reports of the same
cohort existed, the study reporting the
largest sample number was used,
provided all studies received identical
quality assessment scores. Authors
were contacted where additional data
were required. Data on study design,
location, population, outcome, adjust-
ment variables, method of outcome
measurement, potential sources of
bias (including recruitment selection,
exclusion criteria, and blinding of
assessors to GA when evaluating adultoutcomes), and the mean and SD for
preterm and term groups were ex-
tracted for the following parameters:
(1) BMI; (2) WHR;(3) percent FM; (4) SBP
(mm Hg); (5) diastolic blood pressure
(DBP; mm Hg); (6) 24-hour ambulatory
SBP (aSBP; mm Hg); (7) 24-hour am-
bulatory DBP (aDBP; mm Hg); (8) ow-
mediated dilation (FMD) of the brachial
artery (%); (9) intima-media thickness
(IMT) of the carotid artery (mm); (10)
pulse wave velocity (PWV; m/s); (11)
fasting glucose (mmol/L); (12) fasting
insulin (mU/L); (13) fasting cholesterol
(mmol/L); (14) fasting high-density li-
poprotein (HDL; mmol/L); (15) fasting
low-density lipoprotein (LDL; mmol/L);and (16) fasting triglycerides (mmol/L).
Data were extracted by author J.R.C.P.
and independently veried by authors
M.J.H. and C.G. For inclusion, outcomes
were required to be presented un-
adjusted and performed at the same
age using the same technique for pre-
term and term groups.
Primary Analysis
A meta-analysis of studies was per-
formed for each outcome examining
differences between preterm and term
groups in Revman (Version 5.1; The
Cochrane Collaboration, 2011) using
the inverse variance method.14 SE
measurements were converted to SD
for inclusion in the meta-analysis.
Where studies presented analyses of
subgroups of adults born preterm,
pooled means and SDs were calculated
for the whole population. A numberof studies compared very-low-birth-
weight or extremely-low-birth-weight
and normal-birth-weight subjects;
these data were included if GA was
provided as the mean and SD, and the
mean GA 62 SD did not lie outside
,37-week GA for preterm and 37- to 42-
week GA for term subjects. Data on
small for GA and intrauterine growth
restricted infants were pooled with
that of appropriate for GA infants toobtain the outcome in the overall term-
born population, provided that re-
cruitment of small for GA or intrauterine
growthrestricted infants were not
oversampled (eg, through specic re-
cruitment), because this would result in
overrepresentation of low-birth-weight
babies in term-born populations.
Fasting insulin and plasma lipid data
were standardized across studies to SI
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units using established conversion
rates.13 Variables were examined for
skewness by checking whether the
mean was smaller than twice the SD.14
For skewed outcomes, we performed
a meta-analysis of log-transformed
data. Where the log values were notprovided, we converted published
summary measures (arithmetic and
geometric mean) to approximate log
values.15,16 The pooled mean difference
and 95% condence interval of log
values were transformed back and
represent the percentage difference
between term and preterm groups.
Gender-Specic Analysis
BMI, WHR, percent FM, SBP, and bloodpressure outcomes were analyzed
separately for men and women. In
pooled analysis,estimates of effect may
be biased and heterogeneity may be
increased if studies that provide data
exclusively for one gender are included.
Therefore, we excluded gender-specic
studies from our pooled analyses for
BMI, WHR, percent FM, and blood
pressure measurements.
Study Heterogeneity
Heterogeneity was assessed using the
x2
test for Cochranes Q statistic and by
calculating I2, the estimated proportion
of variance in the study outcome
caused by heterogeneity.17 Random ef-
fect models were used throughout be-
cause the assumption of a common
effect across studies (as required by
xed effect models) was not reason-
able as a result of the observationalnature of the studies. Random effects
models can give greater weight to
small studies, so if heterogeneity was
low (P. .05 from thex2
test and I2,
50%), a xed effects model was carried
out to check the sensitivity of con-
clusions. Because heterogeneity tests
have low power when study numbers
are small,18 a xed effects meta-analysis
was not carried out for analyses with
,5 studies. Results are shown as
pooled mean difference (95% CI) be-
tween preterm and term groups unless
otherwise stated and are illustrated
using forest plots. Funnel plots and
Eggers test19 were used to investigate
publication bias. Because Eggers test
has low power, a cutoff of 0.1 was used
for statistical signicance.19 If the test
was signicant, a trim and ll analysis
was performed to estimate the pooled
effect in the absence of publication
bias.20 Potential sources of study het-
erogeneity caused by differences in
population characteristics were exam-
ined by using meta-regression carried
out in Stata 11 (Statacorp, Houston, TX).
Factors included as continuous cova-riates were mean GA of the preterm
group and age at which outcomes were
measured. Meta-regressionwas used to
test whether the term-preterm differ-
ences varied with gender by treating
each gender-specic result as 1 study.
Robust variance estimation with hier-
archical weights was used to allow for
dependencies between gender-specic
results from the same study.21
Subgroup Analysis
The recruitment method was investi-
gated by comparing studies in which
adults were specically recruited on the
basis of GA, lowbirth weight, andstudies
of population-based cohorts. In addition,
we implemented a modied version of
the Newcastle-Ottawa scale22 to assess
the methodological quality of each study
included in the meta-analysis (Supple-
mental Fig 5). Authors J.R.C.P. and M.J.H.
independently assessed the quality of
each study. All differences were re-
solved by discussion. Sensitivity analysis
of pooled BMI, SBP, and DBP data were
performed for all studies that received
a$5-star rating.
RESULTS
Studies identied by the 2 separate
searches are depictedin Fig1. SearchA
identied 2142 publications; 14 addi-
tional papers were identied after
bibliographic review of retrieved
papers2336; 109 papers were reviewed
in full text; and 85 studies were ex-
cluded for the following reasons:
studies with participants ,18 years ofage (n = 10); multiple reports on the
same cohort (n= 9); studies with no GA
or outcome data (n= 27); no preterm
versus term analysis (n= 34); review
articles (n = 5). Twelve studies con-
tained raw data suitable for inclusion.
Attempts were made to contact the
authors of 12 publications for additional
data,11,24,28,3235,3741 and 8 replies were
received.24,28,32,35,3841
Search B identied 4824 publications; 4additional papers were identied
after bibliographic review of retrieved
papers.23,24,35,36 After screening of
abstracts to assess eligibility, 212
papers were reviewed in full text; and
181 studies were excluded for the fol-
lowing reasons: studies with partic-
ipants ,18 years of age (n = 12);
studies that did not compare a preterm
with a term-born group (n= 49); mul-
tiple reports on the same cohort (n=26); studies with no gestational age
information provided (n = 53); pop-
ulation studies in which data were not
analyzed based on GA or birth weight
(n = 33); review articles (n = 3); no
relevant outcome data provided (n=5).
Attempts were made to contact the
authors of 15 publications for addi-
tional data,11,23,24,28,3235,3740,4244 and 8
replies were received.24,28,32,35,3840,42
One author provided data from a singlecohort, pooled from 3 publications42,45,46;
for the sake of clarity, these data are
referred to as Leeson et al 2012.
Combining suitable studies from
both searches resulted in a total of 29
studies suitable for systematic review
(Table 1).35,2325,28,3032,35,36,3842,4455
Data from Oren et al23 and Pilgaard
et al44 were presented adjusted for
gender and age and therefore excluded
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from the meta-analysis. IMT data from
Bassareo et al28 were also excluded as
values were 10-fold higher in magnitude
than other reported results. Data on
plasma lipids from Cooper et al24 were
obtained from nonfasted volunteers
and not eligible for inclusion.
Overall, 27studies were suitableforinclusion
inthemeta-analysis.35,24,25,28,3032,35,36,3842,4555
Sixteen studies were longitudinal follow-
up comparisons of either low-birth-
weight3,5,31,39,41,4751,55 or preterm30,38,42,45,46
subjects and full-term cohorts matched
for age and gender. Fivestudies reported
retrospective analysis of low-birth-
weight28,52 or preterm36,53,54 cohorts.
There were 6 population cohort studies
with GA data.4,24,25,32,35,40
Primary Analyses
Overall, a total of 17 030 preterm and
295 261 term-born adults were eligible
for inclusion in the meta-analysis.
Combined, the mean GA at birth of
adults born preterm was 32.1 weeks,
and the mean age at outcome assess-
ment was 19.6 years (1845 years). The
results of the meta-analyses for each
primary outcome are shown inTable 2.
Numbers of studies and participants
varied considerably for each outcome
(Table 2). No signicant differences
between preterm and term-born adults
were observed in BMI, WHR, or percentFM (Table 2; Supplemental Fig 6). Per-
centage FM was estimated by bio-
electrical impedance,30 dual-energy
X-ray absorptiometry,31,47,53,54 and
whole body MRI.36 Only a single publi-
cation provided suitable data on pulse
wave velocity (PWV),42 so meta-analysis
was not possible. In comparison with
adults born at full term, adults born
preterm demonstrated signicantly
higher SBP (mean difference, 4.2 mmHg; 95% CI, 2.8 to 5.7; P, .001;Fig 2A),
DBP (mean difference, 2.6 mm Hg; 95%
CI, 1.2 to 4.0;P, .001;Fig 2B), and 24-
hour aSBP (mean difference, 3.1 mm
Hg; 95% CI, 0.3 to 6.0; P= .03); the dif-
ference in 24-hour aDBP did not reach
statistical signicance (Table 2).
No signicant differences between term
and preterm groups were identied
in fasting insulin or glucose (Table 2;
Supplemental Fig 6). A signicant in-
crease in fasting LDL in preterm sub-
jects was seen in both random effects
(mean difference, 0.15 mmol/L; 95% CI,
0.01 to 0.30;P= .04;I2: 47%;P= .11) and
xed effects models (Table 2; Supple-
mental Fig 7). There was a borderlinesignicant increase in cholesterol
(mean difference, 0.32 mmol/L; 95% CI,
20.01 to 0.65;P= .05;I2: 75%;P, .01)
in adults born preterm (Table nbsp;2).
No differences were found in fasting
HDL or triglycerides (Table 2; Supple-
mental Fig 7).
Gender-Specic Analysis
No differences between preterm and
term groups were observed in BMI,WHR, or percent FM when analyzed
separately in men or women (Table 3).
Gender-specic analysis revealed sig-
nicantly higher SBP and DBP in men
and women born preterm compared
with those born at term (men: SBP, 2.0
mm Hg; 95% CI, 0.5 to 3.5; P = .007;
Fig 3A; DBP, 1.3 mm Hg; 95% CI, 0.1 to 2.4;
P= .03;Fig 3C; women: SBP, 4.9 mm Hg;
95% CI, 3.3 to 6.6;P, .001;I2: 44%,P=
.05;Fig 3B; DBP, 2.9 mm Hg; 95% CI, 1.6
4.1; P, .00; I2: 44% P = .06; Fig 3D;
Table 3). Three papers included data on
24-hour aSBP and aDBP measurements
in women3,49,55 and 2 papers included
these data in men.3,48 Here, meta-
analysis revealed signicantly higher
24-hour ambulatory bloos pressure
in women born preterm (aSBP: 3.5
mm Hg; 95% CI, 1.4 to 5.6;P, .001;I2:
0%; P= .94; aDBP: 1.6 mm Hg; 95% CI,
0.04to 3.1;P
= .04;I2
:0%;P
= .06)butnotin men (aSBP: 2.9 mm Hg; 95% CI, 23.7
to 9.4; P= .39; I2
: 85%; P, .01; aDBP:
20.04 mm Hg; 95% CI,22.6to 2.7; P= .97;
I2: 48%; P= .17; Table 3; Supplemental
Fig 8).
Meta-Regression
Meta-regression was performed to
test whether the term-preterm differ-
ences varied with gender. For SBP, the
FIGURE 1Flowchartof thesearchstrategy used in the meta-analysis. Therelevant number of papersat each time
point is given.
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TABLE
1
StudiesIncludedinThisMeta-AnalysisExaminingtheAssociationBetweenPreterm
Birth(,37-weekGestation)andBloo
dPressureRelatedOutcomesinAdulthood($18years)
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Bassareoetal201031
Cagliari,Italy;retrospectivecohort
PT:25(4M)
PT:27.96
2.3
PT:8396
118
20.66
2.1
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:23.6
(3.1
)
PT:24.1
(3.0
)
TC:24.8
(2.6
)
TC:24.3
(3.0
)
TC:25(4M)
TC:39.66
2.2
TC:34506
263
FMD(%)
PT:2.2
1(0.9
8)
TC:3.2
7(0.4
5)
IMT(mm)
PT:3.4
0(0.5
8)
TC:3.4
8(0.5
1)
Cooperetal200927
Hertfordshire,
United
Kingdom;prospective
longitudinalfollow
-up
PT:319(166
M)
PT:34.96
1.6
PT:26806
580
44-45
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:27.7
(4.2
)
PT:27.7
(6.3
)
TC:27.8
(4.2
)
TC:26.9
(5.4
)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:134.2
(15.3
)
PT:125.5
(16.0
)
TC:132.9
(15.1
)
TC:120.1
(15.5
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:82.9
(11.0
)
PT:79.5
(11.1
)
TC:82.1
(10.5
)
TC:75.5
(10.2
)
TC:7647(3819M)
TC:39.96
1.4
TC:34006
490
Cholesterol(mmol/L)
PT:5.9
(1.2
)
TC:5.9
(1.1
)
HDL(mmol/L)
PT:1.5
(0.4
)
TC:1.6
(0.4
)
LDL(mmol/L)
PT:3.4
(0.9
)
TC:3.4
(0.9
)
Triglycerides(mmol/L)
PT:2.2
(1.8
)
TC:2.1
(1.6
)
Dalzieletal200740
Auckland,
New
Zealand;longitudinalprospective
follow-upofinfantsurvivorsofasteroidRCT
ofmothersexpect
edtodeliverprematurely
PT:310(153
M)
PT:34.1
(32
35)
PT:19586
487
306
0.0
SBP(mm
Hg)
PT:119.6
(13.7
)
TC:116.1
(11.8
)
TC:145(71M
)
TC:39.96
1.4
TC:31596
559
Triglycerides(mmol/L)
PT:1.2
(0.7
)
TC:1.3
(1.2
)
e1244 PARKINSON et al.at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
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TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Doyleetal20033
Melbourne,
Australia
;prospectivecohortof
infantsbornat,1500g
PT:155(72M
)
PT:28.06
2.0
PT:10986
235
19
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:128.9
(14.4
)
PT:121.2
(14.3
)
TC:120.3
(13.6
)
TC:111.7
(13.5
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:73.9
(9.5
)
PT:71.2
(9.6
)
TC:70.2
(7.1
)
TC:66.0
(6.9
)
TC:37(19M)
TC:40.06
1.1
TC:34936
494
24hSBP:Men(mm
Hg)
24hSB:Women(mm
Hg)
PT:125.8
(10.0
)
PT:118.9
(7.9
)
TC:119.5
(7.2
)
TC:115.1
(7.2
)
24hDBP:Men(mm
Hg)
24hDBP:Women(mm
Hg)
PT:68.8
(8.2
)
PT:69.5
(5.9
)
TC:67.3
(5.0
)
TC:68.8
(4.5
)
Evensenetal200943
Trondheim,
Norway;longitudinalprospective
follow-up
PT:37(20M)
PT:28(24
35)
PT:1245(800
1500
)
18.56
0.7
BMI(kg/m2)
PT:22.3
(3.0
)
TC:23.2
(3.2
)
TC:63(29M)
TC:40(37
42)
TC:3700(2670
514
0)
SBP(mm
Hg)
PT:129.7
(10.2
)
TC:123.2
(9.5
)
DBP(mm
Hg)
PT:63.9
(7.2
)
TC:61.7
(7.1
)
Fagerbergetal200442
Gothenburg,
Sweden
;menonly;prospective
follow-upofsubjectsfrom
Atherosclerosis
andInsulinResistanceStudy(AIR)
PT:30
PT:,37
PT:N/A
58
BMI(kg/m2)
PT:27.2
(3.6
)
TC:26.2
(3.2
)
SBP(mm
Hg)
PT:138.3
(15.4
)
TC:136.9
(19.3
)
DBP(mm
Hg)
PT:83.9
(9.1
)
TC:82.4
(10.0
)
TC:403
TC:N/A
TC:N/A
Cholesterol(mmol/L)
PT:6.5
(1.3
)
TC:5.9
(1.0
)
HDL(mmol/L)
PT:1.4
(0.5
)
TC:1.3
(0.3
)
Triglycerides(mmol/L)
PT:1.8
(0.8
)
TC:1.5
(0.7
)
REVIEW ARTICLE
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8/27
TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Hacketal20055
Ohio,
USA;longitudin
alprospectivefollow-up
ofVLBW
individuals
PT:195(103
M)
PT:29.86
2.2
PT:11906
214
20.16
0.4
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:22.9
(4.2
)
PT:24.7
(5.2
)
TC:25.5
(4.9
)
TC:25.4
(6.2
)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:117.5
(10.6
)
PT:110.4
(9.1
)
TC:208(101
M)
GA:$37
TC:3277
TC:116.9
(11.0
)
TC:107.2
(12.1
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:73.7
(8.6
)
PT:72.5
(8.5
)
TC:73.1
(8.6
)
TC:72.1
(8.9
)
Hovietal200949
Helsinki,Finland;lon
gitudinalprospective
follow-upofHelsin
kistudyofVLBW
adults
PT:144(60M
)
PT:29.36
2.2
PT:11276
218
22.66
2.2
FM
(%):Men
FM
(%):Women
TC:139(55M
)
TC:40.1
(1.1
)
TC:36006
471
PT:18.0
(6.4
)
PT:29.6
(6.1
)
TC:18.4
(5.7
)
TC:30.0
(5.5
)
Hovietal201050
Helsinki,Finland;lon
gitudinalprospective
follow-upofHelsin
kistudyofVLBW
adults
PT:118(49M
)
PT:29.26
2.2
PT:11386
224
23
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:21.6
(3.5
)
PT:22.3
(4.0
)
TC:23.5
(3.3
)
TC:23.0
(3.8
)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:128.2
(13.0
)
PT:116.7
(12.2
)
TC:126.4
(12.4
)
TC:111.4
(9.5
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
TC:120(48M
)
TC:40.16
1.0
TC:36236
479
PT:79.8
(8.0
)
PT:77.9
(9.1
)
TC:76.9
(8.1
)
TC:74.1
(8.0
)
24hSBP:Men(mm
Hg)
24hSB:Women(mm
Hg)
PT:121.7
(6.8
)
PT:117.1
(10.7
)
TC:122.1
(9.4
)
TC:114.0
(7.0
)
24hDB:Men(mm
Hg)
24hDBP:Womenmm
Hg)
PT:68.9
(6.1
)
PT:71.6
(7.8
)
TC:70.1
(6.4
)
TC:69.8
(5.0
)
e1246 PARKINSON et al.at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
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TABLE
1
Continued
AuthorandYear
PopulationandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Hovietal201151
Helsinki,Finland;longitudinalprospective
follow-upofHelsin
kistudyofVLBW
adults
PT:92(52M)
PT:29.56
2.4
PT:11386
210
23
FMD(%)
PT:6.9
(4.0
)
TC:5.8
(3.3
)
IMT(mm)
PT:0.4
4(0.0
5)
TC:0.4
3(0.0
4)
Cholesterol(mmol/L)
PT:4.6
(0.8
)
TC:4.6
(0.8
)
HDL(mmol/L)
PT:1.7
(0.4
)
TC:1.6
(0.4
)
TC:68(29M)
TC:40.26
1.1
TC:36486
470
LDL(mmol/L)
PT:2.5
(0.7
)
TC:2.5
(0.8
)
Triglycerides(mmol/L)(Geometricmean6
SD)
PT:1.0
(1.5
)
TC:1.1
(1.5
)
Glucose(mmol/L)(Geom
etricmean6
SD)
PT:4.7
(1.1
)
TC:4.6
(1.1
)
Insulin(mU/L)(Geometr
icmean6
SD)
PT:5.9
(1.6
)
TC:5.1
(1.3
)
Irvingetal200041
Edinburgh,
Scotland;
retrospective
follow-upofLBW(
,2000g)cohort
PT:19(9M)
PT:31.96
1.5
PT:16606
220
24.26
0.6
SBP(mm
Hg)
PT:123(9)
TC:115(9)
DBP(mm
Hg)
PT:80(7)
TC:73(7)
TC:27(11M)
TC:39.36
1.9
TC:31306
450
Glucose(mmol/L)
PT:5.6
(2.1
)
TC:4.9
(2.8
)
Insulin(mU/L)
PT:4.4
(0.4
)
TC:4.2
(0.4
)
Jrvelinetal200428
NorthernFinland;lon
gitudinalprospective
follow-upofaprospectivecohort
PT:273(132
M)
PT
PT:N/A
31
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:,37wk
PT:131.3
(13.8
)
PT:122.6
(14.1
)
TC:130.3
(12.5
)
TC:119.9
(12.3
)
TC:4356(2114M)
TC:37
42
TC:N/A
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:80.3
(13.1
)
PT:75.7
(10.4
)
TC:80.3
(11.3
)
TC:74.7
(10.9
)
REVIEW ARTICLE
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10/27
TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Johanssonetal20054
Sweden;menonly;lo
ngitudinalprospective
follow-upofpopul
ation-basedstudy
PT:14192
PT:24
36
PT:26396
498
18.26
0.4
BMI(kg/m2)
PT:22.3
(3.3
)
TC:22.3
(3.2
)
SBP(mm
Hg)
TC:275895
TC:GA37
41
TC:35906
484
PT:130(11)
TC:129(11)
DBP(mm
Hg)
PT:67(10)
TC:67(10)
Kerkhofetal200956
Rotterdam,
Netherlands;maleonlystudy;
subjectswererecruitedfrom
theprospective
PROGRAM/PREMSpreterm
cohort
PT:85
PT:32.06
2.1
PT:N/A
20.96
1.6
FM
(%)
TC:122
TC:39.36
1.6
TC:N/A
PT:16.8
(8.5
)
TC:16.3
(7.9
)
Kerkhofetal201055
Rotterdam,
Netherlands;femaleonlystudy;
subjectswererecruitedfrom
theprospective
PROGRAM/PREMSpreterm
cohort
PT:84
PT:32.06
2.3
PT:N/A
20.76
1.7
BMI(kg/m2)
PT:22.5
(3.9
)
TC:22.6
(4.0
)
TC:195
TC:39.16
1.7
TC:N/A
FM
(%)
PT:31.8
(7.9
)
TC:29.4
(8.6
)
Kistneretal200057
Stockholm,
Sweden;
womenonly;subjectswere
recruitedfrom
ap
rospectivecohortofLBW
infants
PT:15
PT:30.06
2.0
PT:12936
283
26.06
2.0
SBP(mm
Hg)
PT:123.0
(13.0
)
TC:110.0
(7.0
)
DBP(mm
Hg)
PT:69.0
(8.0
)
TC:64.0
(7.0
)
TC:17
TC:41.06
2.0
TC:37206
313
24hSBP(mm
Hg)
PT:120.0
(7.0
)
TC:116.0
(7.0
)
24hDBP(mm
Hg)
PT:72.0
(7.0
)
TC:69.0
(4.0
)
e1248 PARKINSON et al.at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
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11/27
TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Kistneretal200453
DetailsasinKistner
etal2000
PT:15
PT:30.06
2.0
PT:12936
283
26.06
2.0
BMI(kg/m2)
PT:23.4
(2.9
)
TC:23.9
(3.1
)
Glucose(mmol/L)
PT:4.3
(0.1
)
TC:4.3
(0.1
)
Insulin(mU/L)(Median
andrange)
PT:14(8-28)
TC:16(9-27)
Cholesterol(mmol/L)
TC:17
TC:41.06
2.0
TC:37206
313
PT:4.5
(0.7
)
TC:4.7
(0.9
)
HDL(mmol/L)
PT:1.4
(0.2
)
TC:1.4
(0.3
)
LDL(mmol/L)
PT:2.7
(0.8
)
TC:2.7
(0.7
)
Triglycerides(mmol/L)
PT:1.0
(0.3
)
TC:1.3
(0.5
)
Lazdam
etal201044
5UKcenters;PTgroup:prospectivefollow-up
from
RCTofpostnatalnutrition
PT:71(33M)
PT:30.36
2.5
PT:13036
281
25
SBP(mm
Hg)
PT:120.5
(10.8
)
TC:114.0
(11.0
)
DBP(mm
Hg)
PT:71.7
(6.8
)
TC:66.1
(7.1
)
IMT(mm)
PT:0.4
9(0.0
6)
TC:38(20M
)
TC:37
42
TC:N/A
TC:0.3
6(0.0
6)
FMD(%)
PT:6.1
(4.3
)
TC:6.9
(4.9
)
PWV(m/s)
PT:5.8
(0.7
)
TC:5.6
(1.1
)
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12/27
TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Leesonetal201244,4
7,4
8
Dataarepooledfrom
thesameprospective
cohortofindividualspresentedinthree
separatepublications(Lazdam
etal2010;
Lewandowskietal2011;Kellyetal2012)
PT:102(47M
)
PT:30.36
2.5
PT:12976
287
25.16
2.1
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:24.6
(4.0
)
PT:25.2
(6.4
)
TC:23.6
(2.8
)
TC:22.3
(3.2
)
WHR:Men
WHR:Women
PT:0.8
6(0.0
6)
PT:0.7
7(0.0
8)
TC:0.8
4(0.0
5)
TC:0.7
8(0.0
6)
Glucose(mmol/L)
PT:5.0
(0.4
)
TC:4.6
(0.3
)
Insulin(mU/L;convertedfrom
pmol/L)
PT:8.3
(5.5
)
TC:4.6
(2.1
)
TC:102(47M
)
TC:39.66
0.9
TC:34616
413
Cholesterol(mmol/L)
PT:4.9
(1.1
)
TC:4.2
(0.9
)
HDL(mmol/L)
PT:1.5
(0.4
)
TC:1.5
(0.4
)
LDL(mmol/L)
PT:2.8
(0.9
)
TC:2.4
(0.7
)
Triglycerides(mmol/L)
PT:1.1
(0.8
)
TC:0.9
(0.4
)
Leottaetal200735
Turin,
Italy;longitudinalfollow-upof
prospectivecohor
t
PT:26(14M)
PT:,37
PT:N/A
23.56
0.8
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:24.1
(3.1
)
PT:21.5
(2.5
)
TC:23.6
(3.9
)
TC:21.5
(3.3
)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:124.5
(13.0
)
PT:115.0
(9.9
)
TC:186(84M
)
TC:37
42
TC:N/A
TC:129.0
(14.0
)
TC:110.5
(10.8
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:72.0
(9.9
)
PT:72.1
(9.9
)
TC:73.4
(8.8
)
TC:69.2
(11.0
)
Orenetal200326
Utrecht,Netherlands
;follow-upofprospective
population-based
cohort:Atherosclerosis
RiskinYoungAdu
lts(ARYA)study
PT:26(11M)
PT:34.06
1.0
PT:26326
510
28.26
0.9
BMI(kg/m2)
PT:24.7
(4.1
)
TC:24.6
(3.9
)
TC:381(175
M)
TC:40.06
2.0
TC:34826
507
PWV(m/s)
PT:6.1
(1.5
)
TC:6.0
(2.0
)
e1250 PARKINSON et al.at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
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TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMe
an(SD)Result
Pilgaardetal201046
Denmark;randomsa
mpleofpopulation-based
study:TheInter99
study
PT:443(160
M)
PT:,37
PT:25556
403
30-60
BMI(kg/m2)
PT:25.8
(4.7
)
TC:26.2
(4.5
)
Glucose(mmol/L)
TC:4055(1928M)
TC:37
42
TC:35226
420
PT:5.5
(1.0
)
TC:5.5
(0.7
)
Insulin(pmol/L)(Medianandrange)
PT:33(23
49)
TC:35(23
49)
Rotteveeletal.200833
Netherlands;prospectivefollow-upofProjectof
PrematureandSm
allforGestationalAge
Infants(POPS)coh
ort
PT:57(28M)
PT:29.86
1.3
PT:12406
237
21.96
0.3
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:22.4
(3.2
)
PT:21.6
(2.6
)
TC:22.2
(2.0
)
TC:21.5
(2.2
)
FM
(%):Men
FM
(%):Women
PT:21.7
(6.2
)
PT:30.3
(4.6
)
TC:22.2
(4.0
)
TC:30.4
(4.0
)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:134.8
(13.3
)
PT:124.5
(13.1
)
TC:120.0
(10.0
)
TC:116.0
(9.0
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:70.7
(8.0
)
PT:72.5
(8.0
)
TC:64.0
(5.0
)
TC:66.0
(8.0
)
TC:30(15M)
TC:40.06
0.0
TC:35626
465
Glucose(mmol/L)
PT:5.1
(0.4
)
TC:5.0
(0.5
)
HDL(mmol/L)
PT:1.6
(0.4
)
TC:1.5
(0.3
)
Triglycerides(mmol/L)
PT:0.9
(0.4
)
TC:1.0
(0.4
)
Saigaletal200652
Ontario,
Canada;longitudinalprospective
follow-upofpopul
ationbasedcohortofELBW
individuals
PT:147(65M
)
PT:27.16
2.3
PT:8416
125
23.56
1.1
BMI:Men(kg/m2)
BMI:Women(kg/m2)
TC:131(59M
)
TC:37
42
TC:33806
475
PT:24.2
(4.6
)
PT:24.0
(5.6
)
TC:24.4
(4.4
)
TC:24.8
(5.3
)
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TABLE
1
Continued
AuthorandYear
Populat
ionandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMean(SD)Result
Skiltonetal201138
Finland;5cities;prospectivefollow-upofsubjectsfrom
theCardiovascula
rRiskinYoungFinnsStudy
PT:253(116
M)
PT:,37
PT:28146
602
32
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:25.7
(3.9
)
PT:24.9
(4.7
)
TC:25.9
(4.3
))
TC:24.6
(4.7
))
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:122.3
(12.6
)
PT:115.1
(12.1
)
TC:122.1
(12.4
)
TC:113.2
(12.6
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:72.8
(10.8
)
PT:71.2
(10.2
)
TC:73.8
(10.8
)
TC:69.6
(10.1
)
FMD(%)
PT:8.1
(4.1
)
TC:8.4
(4.6
)
IMT(mm)
TC:1042(480M)
TC:37
42
TC:36376
184
PT:0.5
9(0.0
9)
TC:0.5
8(0.0
9)
Glucose(mmol/L)(Geom
etricmean6
SD)
PT:5.1
(0.6
)
TC:5.0
(0.6
)
HDL(mmol/L)
PT:1.3
(0.3
)
TC:1.3
(0.3
)
LDL(mmol/L)
PT:3.3
(0.8
)
TC:3.2
(0.8
)
Triglycerides(mmol/L)(Geometricmean6
SD)
PT:1.2
(0.9
)
TC:1.3
(0.9
)
Szathmarietal200154
Budapest,Hungary;retrospectivecohortanalysisof
premature
PT:70(37M
)
PT:33(27
36)
PT:18146
386
20.36
0.8
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:22.0
(2.9
)
PT:24.9
(4.7
)
TC:21.7
(2.7
)
TC:24.6
(4.7
)
Glucose(mmol/L)
TC:30(16M
)
TC:40(38
41)
TC:32786
367
PT:4.66
0.5
TC:4.76
0.7
Insulin(logmU/mL)
PT:0.8
66
0.2
TC:0.8
56
0.1
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TABLE
1
Continued
AuthorandYear
PopulationandStudyDetails
SampleNum
ber
GA(wk)[Mean6
SD
orMedian(Range)]
BirthWeight(g)
[Mean6
SDor
Median(Range)]
AdultAge6
SD
orMedian(Range)
OutcomeMean(SD)Result
Thomasetal201110
London,
UnitedKingd
om;retrospectivecohortstudy
PT:23(13M
)
PT:29.46
2.6
PT:13666
425
23.76
2.6
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:24.2
(3.1
)
PT:21.4
(2.7
)
TC:23.8
(2.2
)
TC:22.0
(2.3
)
WHR:Men
WHR:Women
PT:0.8
8(0.0
4)
PT:0.7
7(0.0
6)
TC:0.8
4(0.0
4)
TC:0.7
7(0.0
4)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:122.3
(4.7
)
PT:118.9
(9.9
)
TC:116.4
(6.7
)
TC:112.0
(7.6
)
DBP:Men(mm
Hg)
DBP:Women(mm
Hg)
PT:78.3
(6.3
)
PT:74.4
(7.5
)
TC:71.9
(4.8
)
TC:69.0
(8.5
)
FM
(%):Men
FM
(%):Women
PT:21.8
(5.8
)
PT:31.9
(6.4
)
TC:17.5
(4.8
)
TC:30.8
(4.8
)
TC:25(10M
)
TC:40.16
1.6
TC:33396
441
Glucose(mmol/L)
PT:5.0
(0.3
)
TC:4.9
(0.4
)
Insulin(mU/L)
PT:5.9
(2.6
)
TC:6.1
(2.9
)
Cholesterol(mmol/L)
PT:4.5
(0.6
9)
TC:4.3
(0.8
4)
HDL(mmol/L)
PT:1.2
4(0.2
8)
TC:1.2
1(0.3
6)
LDL(mmol/L)
PT:2.7
(0.6
)
TC:2.5
(0.5
)
Triglycerides(mmol/L)
PT:1.1
1(0.4
)
TC:1.2
(0.6
)
Walkeret200234
Edinburgh,
Scotland;retrospectiveanalysisof
LBW
cohort,asin
Irvingetal2000
PT:19(9M)
PT:32.0
(1.5
)
PT:16666
228
24
BMI:Men(kg/m2)
BMI:Women(kg/m2)
PT:25.5
(3.3
)
PT:24.0
(3.4
)
TC:23.0
(1.8
)
TC:22.8
(3.6
)
WHR:Men
WHR:Women
PT:0.8
3(0.0
3)
PT:0.7
4(0.0
5)
TC:0.8
3(0.0
3)
TC:0.7
3(0.0
5)
TC:27(11M
)
TC:40.2
(1.8
)
TC:31286
441
FM
(%):Men
FM
(%):Women
PT:19.6
(3.8
)
PT:34.5
(8.2
)
TC:13.3
(6.0
)
TC:32.1
(9.7
)
SBP:Men(mm
Hg)
SBP:Women(mm
Hg)
PT:127(10)
PT:120(8)
TC:120(10)
TC:112(7)
AGA,
appropriateforGA;ELBW,
extremelylowbirthw
eight(,1000g);LBW,
lowbirthweight(,2500g);M,m
en;N/A,
notapplicable;PT,preterm;RCT,randomizedcon
trolledtrial;SGA,
smallforGA;TC,
term
control;VLWV,ve
rylowbirthweight(,1500g).
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TABLE
2
SummaryofMeta-analysis
Outcome
Numberof
Studies
Num
berof
Sub
jects
MeanAgeat
Outcome
PooledMean
Difference(95%
CI)
FE/REP
Heterogeneity(I2
,P)
Re
ferences
BMI
13
PT:1
388
39.4
RE:20.0
4kg/m2
(20.3
3to0.2
4)
RE:P
=.7
6
I2:66%,
P
,
.01
5,
10,
27,
31,
33
35,38,
43,
44,
47,
48,
50,
52,
54
TC:9
592
WHR
3
PT:1
44
24.7
RE:0.0
1(20.01to0.0
4)
RE:P
=.3
4
I2:72%,
P
=.0
3
10,
34,
44,
47,
48
TC:1
52
PercentFM
5
PT:4
12
22.1
RE:-0.0
6%
(2
0.7
4to0.6
3)
RE:P
=.8
7
I2:0%,
P
=.6
3
10,
34,
44,
47
49,
56
TC:5
38
FE:-0.0
6%
(2
0.7
4to0.6
3)
FE:P
=.8
7
SBP
13
PT:1
856
37.0
RE:4.2
mmHg(2.8
to5.7
)
RE:P
,
.001
I2:65%,
P
,
.001
3,
5,
10,
27,
28,
33,3
5,
38,
40,
41,
43,
44,
50
TC:1
3920
DBP
11
PT:1
546
37.1
RE:2.6
mmHg(1.2
to4.0
)
RE:P
,
.001
I2:78%,
P
,
.001
3,
5,
10,
27,
28,
33,3
5,
38,
41,
43,
44,
50
TC:1
3775
24-haSBP
2
PT:2
74
21.1
RE:3.1
mmHg(0.3
to6.0
)
RE:P
=.0
3
I2:61%,
P
=.1
1
3,
50
TC:1
58
24-haDBP
2
PT:2
74
21.1
RE:0.9
mmHg(20.4
to2.1
)
RE:P
=.1
7
I2:0%,
P
=.6
4
3,
50
TC:1
58
FMD
4
PT:4
50
29.3
RE:0.1
4%
(2
0.8
to1.0
)
RE:P
=.7
6
I2:47%,
P
=.1
3
38,
43,
44,
51
TC:1
197
IMT
3
PT:4
16
29.9
RE:0.0
5mm
(20.0
1to0.1
1)
RE:P
=.1
1
I2:98%,
P
,
.001
38,
43,
44
TC:1
148
Glucose
7
PT:5
35
29.6
RE:0.1
2mmo
l/L(20.0
3to0.2
8)
RE:P
=.1
2
I2:86%,
P
,
.01
10,
33,
38,
41,
44,
47,
48,
53,
54
TC:1
266
Insulina
5
PT:3
02
23.4
RE:8%
(22to18)
RE:P
=.1
2
I2:63%,
P
=.0
3
10,
41,
44,
47,
48,
51,
54
TC:2
45
Cholesterol
6
PT:2
77
38.0
RE:0.3
2mmo
l/L(20.0
1to0.6
5)
RE:P
=.0
5
I2:75%,
P
,
.01
10,
41,
42,
44,
47,
48,
51,
53
TC:6
32
PlasmaHDL
8
PT:5
85
34.2
RE:0.0
1mmo
l/L(20.0
2to0.0
5)
RE:P
=.4
8
I2:0%,
P
=.5
3
10,
33,
38,
41,
42,
44,
47,
48,
51,
53
TC:1
699
FE:0.0
1mmol/L(20.0
2to0.0
5)
FE:P
=.4
8
PlasmaLDL
5
PT:4
74
29.7
RE:0.1
5mmo
l/L(0.0
1to0.3
0)
RE:P
=.0
4
I2:47%,
P
=.1
1
10,
38,
44,
47,
48,
51,
53
TC:1
231
FE:0.1
4mmol/L(0.0
5to0.2
2)
FE:P
,
.01
Triglyceridesa
9
PT:8
89
34.0
RE:3%
(24to10)
RE:P
=.3
9
I2:43%,
P
=.0
8
10,
33,
38,
40
42,
44,
47,
48,
51,
53
TC:1
842
FE:4%
(21to
8)
FE:P
=.1
4
FE,
xedeffectmodel;PT,preterm;RE,
random
effec
tmodel;TC,
term
control.
a
Skewedvariableswerelogarithm
transformedbe
foremeta-analysis.
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preterm-term difference in womenwas
greater than the preterm-term differ-
encein men by 2.9 mm Hg (95%CI, 1.1 to
4.6;P= .004) and for DBP by 1.6 mm Hg
(95% CI, 0.3 to 2.9; P = .02). Meta-
regression did not reveal a signicant
gender difference with regard to the
preterm-term differences for BMI, WHR,
pecent FM, or ambulatory blood pres-sure in the small number of studies
available. Meta-regression revealed no
signicant relationship between term-
preterm differences for any outcome
with either mean GA or age at outcome.
Study Heterogeneity
In pooled analysis, funnel plots reveal
asymmetry for both SBP (Fig 4A) and
DBP (Fig 4D), and Eggers test showed
this to be signicant for both outcomes
(SBP:P= .003; DBP: P= .03). The trim
andll analysis gave a reduced pooled
effect for SBP (3.0 mm Hg; 95% CI, 1.4 to
4.5; P, .001) and a similar effect for
DBP (2.5 mm Hg; 95% CI, 1.2 to 3.8;P,
.001). In gender-specic analysis, there
was some visual evidence of asymme-try, particularly for DBP (Fig 4). Eggers
test only revealed signicant funnel
plot asymmetry in studies of SBP in
women and DBP in men (SBP: men,P=
.15; women,P= .002; DBP: men, P= .04;
women, P = .11; Fig 4). Trim and ll
analysis gave a reduced difference in
SBP in women (3.6 mm Hg; 95% CI, 1.8 to
5.4;P, .001) and no difference in DBP
in men (P= .9). Because heterogeneity
was low for the analysis of DBP in
women, a xed effects analysis was also
performed, yielding similar results (Ta-
ble 3). Funnel plots showed some visual
evidence of asymmetry for BMI, percent
FM, and glucose (Supplemental Figs 9
and 10). Eggers test was only statisti-
cally signicant for percent FM (pooled
genderand subgroup analysis in men, P= .013 andP= .063, respectively). Ad-
ditional xed effects analyses carried
out because of the absence of hetero-
geneity did not alter the conclusions in
pooled (Table 2) or gender-specic
analysis (Table 3).
Subgroup Analyses
Subgroup analyses using the re-
cruitmentmethod for BMI, SBP, andDBP
FIGURE 2Forest plots showing the unadjusted pooled gender association between premature birth and (A) SBP and (B) DBP in adulthood.
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TABLE
3
SummaryofGender-SpecicMe
ta-analysis
Outcome
Numberof
Studies
Numb
erof
Subj
ects
MeanAgeat
Outcome(y)
PooledMeanD
ifference(95%
CI)
FE/REP
H
eterogeneity(I2
,P)
References
Men B
MI
14
PT:14
872
18.7
RE:0.0
kg/m2(
20.0
6to0.0
5)
RE:P
=.5
9
I2:61%,
P
,
.01
4,
5,
10,
27,
31,
33-35,38,
42,
44,
47,
48,
50,
52,
54
TC:28
0969
FE:20.1
3kg/m
2
(20.6
0to0.3
4)
FE:P
=.8
7
WHR
3
PT:69
24.7
RE:0.0
(0.0
0to
0.0
4)
RE:P
=.0
8
I2:43%,
P
=.1
7
10,
34,
44,
47,
48
TC:68
FM
(%)
5
PT:19
5
21.8
RE:1.4
8%
(20.7
3to3.7
0)
RE:P
=.1
9
I2:62%,
P
=.0
3
10,
28,
38
40,
47,
50
TC:21
3
SBP
12
PT:14
924
18.7
RE:2.0
mm
Hg
(0.5
to3.5
)
RE:P
=.0
05
I2:60%,
P
,
.01
3
5,
10,
27,
28,
33
35,
38,
42,
50
TC:28
2999
24-haSBP
2
PT:12
1
21.0
RE:2.9
mm
Hg
(23.7
to9.4
)
RE:P
=.3
9
I2:85%,
P
,
.01
3,
50
TC:68
DBP
11
PT:14
915
18.7
RE:1.3
mm
Hg
(0.1
to2.4
)
RE:P
=.0
3
I2:65%,
P
,
.01
3-5,
10,
27,
28,
33,
35,38,
42,
50
TC:28
2988
24-haDBP
2
PT:12
1
21.0
RE:0.0
4mmHg(22.6
to2.7
)
RE:P
=.9
7
I2:48%,
P
=.1
7
3,
50
TC:68
Women
BMI
14
PT:80
0
38.4
RE:0.1
2kg/m2
(20.3
1to0.5
6)
RE:P
=.5
8
I2:18%,
P
=.2
6
6,
10,
24,
26,
28,
31,35
,38,
39,
41,
44
49
TC:50
70
FE:0.1
3kg/m2
(20.2
5to0.5
2)
FE:P
=.4
9
WHR
3
PT:75
24.7
RE:0.0
0(20.02to0.0
2)
RE:P
=.7
6
I2:0%,
P
=.7
0
10,
34,
44,
47,
48
TC:86
FM
(%)
5
PT:21
7
21.6
RE:0.7
7%
(20.5
7to2.1
1)
RE:P
=.2
6
I2:18%,
P
=.3
0
10,
34,
44,
47
49,
56
TC:325
FE:0.7
1%
(20.4
3to1.8
5)
FE:P
=.2
2
SBP
11
PT:75
0
37.2
RE:4.9
mm
Hg
(3.3
to6.6
)
RE:P
,
.001
I2:44%,
P
=.0
5
3,
5,
10,
27,
28,
33
35,
38,
50,
57
TC:69
89
24-haSBP
3
PT:16
7
21.8
RE:3.5
mm
Hg
(1.4
to5.6
)
RE:P
=.0
01
I2:0%,
P
=.9
4
3,
50,
57
TC:10
7
DBP
10
PT:74
0
37.2
RE:2.9
mm
Hg
(1.6
to4.1
)
RE:P
,
.001
I2:44%,
P
=.0
6
3,
5,
10,
27,
28,
33,
35,
38,
50,
57
TC:69
73
FE:2.6
mm
Hg
(1.7
to3.4
)
FE:P
,
.001
24-haDBP
3
PT:16
7
21.8
RE:1.6
mm
Hg
(0.0
4to3.1
)
RE:P
=.0
4
I2:0%,
P
=.6
0
3,
50,
57
TC:10
7
FE,
xedeffectmodel;PT,preterm;RE,
random
effec
tsmodel;TC,
term
control.
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FIGURE 3Forest plotsshowingthe unadjustedassociationbetweenpreterm birthand (Aand B)SBPand (Cand D)DBP in(A andC) adultmen and(B andD) adultwomen.
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are shown in Supplemental Fig 11.
With regard to BMI, meta-regression
showed the estimated term-preterm
difference to be larger in GA-based
studies than in those recruiting by
birth weight (1.42 kg/m2; 95% CI, 0.36 to
2.48; P = .02). The difference in BMI
between term and preterm adults was
also larger in population-based studies
than in those that recruited by birth
weight (0.99 kg/m2; 95% CI, 0.17 to 1.81;
P= .01). No signicant difference in BMI
was observed between population- and
GA-based studies (P= .29). The differ-
ence in blood pressure between stud-
ies in which adults were specicallyrecruited on the basis of GA30,36,38,42
was 4.4 mm Hg larger (95% CI, 0.3 to
8.4; P = .04) than population cohort
studies24,25,32,35 for SBP and 5.0 mm Hg
larger (95% CI, 2.0 to 8.0; P= .005) for
DBP. Studies in which recruitment
was specically on the basis of birth
weight3,5,39,48 showed a nonsignicant
increase in SBP and DBP compared
with studies in which recruitment
was population based (SBP: 2.7 mm
Hg; 95% CI,21.4 to 6.8;P= .17; DBP: 2.1
mm Hg; 95% CI, 20.4 to 4.6; P= .09).
Analysis of population-based stud-
ies24,25,32,35 revealed a signicantlyhigher SBP (2.1 mm Hg; 95% CI, 0.9 to
3.2;P, .001) and DBP in adults born
preterm (1.2 mm Hg; 95% CI, 20.03 to
2.4; P= .06; Supplemental Fig 8), al-
though the latter was not statistically
signicant.
Supplemental Fig 11 shows the as-
sessment of study quality for the 27
studies included in the meta-analysis.
Total scores ranged from 2 to 7 stars,
with 8 studies receiving a rating of$5stars. In comparison with the main
analysis, studies that received a .5
stars measurement demonstrated
a smaller, but still statistically signi-
cant, increase in SBP (2.8 mm Hg; 95%
CI, 1.6 to 4.0; P, .001) but no difference
in DBP (1.3 mm Hg; 95% CI, 20.3 to 2.9;
P= .12;Supplemental Fig 12). Gender-
specic analysis of high-quality studies
revealed signicantly higher SBP in
men (1.0 mm Hg; 95% CI, 0.8 to 1.2;P,
.001) and women (3.9 mm Hg; 95% CI,
2.3 to 5.6; P , .001) born preterm
compared with those born at term,
whereas DBP was only signicantly in-creased in women (2.5 mm Hg; 95% CI,
1.1 to 3.9; P , .001; Supplemental
Fig 12).
BMI was the only other outcome vari-
able with .5 studies with a $5* rat-
ing.4,24,31,32,35,40,48,50 Sensitivity analysis
of these studies revealed no difference
between term and preterm groups
(0.03 kg/m2; 95% CI, 20.33 to 0.39;P=
.86;I2: 57%;P= .04), and no signicant
difference was observed between high-quality studies compared with pooled
analysis. Additional details for each
paper are shown in Supplemental
Fig 13.
DISCUSSION
In this systematic review and meta-
analysis, we found no difference be-
tween adults born preterm and at term
FIGURE 4Funnel plotof mean difference in (AC) SBPand (DF) DBP between term and preterm born adults (A and D) overall, (B and E) in men, and (C and F) in women.
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for the majority of outcomes associated
with the metabolic syndrome. However,
preterm birth is associated with sig-
nicantly higher BP, including 24-hour
aBPinadultlife,aswellasanincreasein
plasma LDL. Hypertension is a major
risk factor for heart disease, stroke,and renal failure. Lowering blood
pressure by 2 mm Hg is reported to
reduce hypertension by 17%, heart
attacks by 6%, and stroke by 15%.56 The
clinically relevant and statistically sig-
nicant difference in blood pressure
and the apparently increased vulnera-
bility of women born preterm is
therefore of concern.
Adults born preterm remain shorter,
lighter, and have a lower BMI comparedwith their term-born peers throughout
infancy, childhood, and adolescence.2,57
This difference is attenuated during
mid-childhood and adolescence, with
women demonstrating faster catch-up
in growth than men.57,58 Our analyses
revealed no signicant difference in
BMI between preterm and term-born
adults in either pooled or gender
analysis. Heterogeneity was high in
the main analysis, and although someof this was explained by differences
in study quality and recruitment
method, a small effect could be ob-
scured by other differences between
studies. The signicant difference we
observes between low-birth-weight-
and GA-based recruitment would sug-
gest that selection based on birth
weight can lead to biased inferences
regarding the effects of preterm birth.
We would therefore recommend thatall future studies recruit solely on the
basis of GA.
Several publications indicate that the
reduced weight observed in children
and adolescents born preterm is as-
sociated with reduced FM rather than
reduced fat-free mass.59,60 Here, we
nd no difference in percent FM be-
tween adults born preterm and at
term. We observed low levels of study
heterogeneity in pooled analyses de-
spite combining percent FM data ac-
quired using a variety of different
techni ques. Ultimately, the lack of
differentiation provided by aggregate
whole body measurements com-
pared with direct evaluation of re-gional adipose tissue depots may not
be suitable to assess differences in
body composition between term and
preterm groups or to identify gender-
specic differences.
A recent smaller meta-analysisin which
SBP data from a range of outcome ages
were combined reported an increase in
SBP in preterm individuals comparable
to that identied here.6 Overall, there
is agreement with other systematicreviews indicating an increase of3 to
4 mm Hg in SBP in preterm compared
with term subjects.61,62 However, the
relationship between early life events
and adult blood pressure may be
overestimated. Bias arising from se-
lective publication of smaller studies
reporting larger effects63 and inap-
propriate statistical adjustment for
confounders that lie along the causal
pathway between birth weight andblood pressure are possible contrib-
uting factors.64 These phenomena ap-
pear to be reected in our analyses;
the funnel plot asymmetry present in
our primary analysis suggests evi-
dence of publication bias, indicating
that pooled results from the main
analysis may be an overestimation of
the true size of the association. Of note
is that high-quality studies revealed
a smaller but nonetheless statisticallysignicant and clinically relevant in-
crease in SBP in adults born preterm,
with reduced and nonsignicant het-
erogeneity in contrast to the pooled
analysis. The magnitude of these dif-
ferences is more likely to signify the
real long-term effects of preterm
birth on blood pressure in adult life.
It is also important to note that, given
the possibility of a dose-response
relationship between prematurity
and blood pressure, as suggested by
Johansson et al,4 the exclusion of
extremely preterm individuals may
result in an underestimation of the
association between preterm birth
and outcomes.
Ambulatory monitoring is considered
a more reliable approach to assessing
blood pressure, because it is less af-
fected by the anxiety response that
accompanies one-off measurements.65
Increased blood pressure reactivity
to psychosocial stressors has been
reported exclusively in preterm
women.66,67 Our analysis of aSBP only
revealed a signicant effect in women;
however, the number of studies wassmall, and a difference in men cannot
be dismissed. Gender differences in
biological outcomes are well recog-
nized; several studies have shown an
increased susceptibility to adverse
outcomes in preterm men compared
with preterm women, including aberrant
adiposity36 and neurodevelopment.68 In
contrast, a subgroup analysis of high-
quality studies performed here re-
vealed that a smaller, but signicantand clinically relevant, increase in DBP
only occurs in women born preterm.
Collectively, these data would suggest
gender-specic trajectories after pre-
term birth.
Disturbance of endothelial function is
considered key to the development of
vascular disease. Conicting data exist
on arterial stiffness and endothelial
dysfunctioninchildrenandadolescents
born preterm, with some studies in-dicating a positive association,9,69 and
others nding no association.10,70 We
found no signicant difference be-
tween preterm and term adults in FMD
or IMT, albeit there was a limited
number of studies. Insufcient data
were available to perform meta-
analysis on PWV; neither the un-
adjusted analysis of Lazdam et al,42 nor
the adjusted data presented by Oren
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etal26 identied a signicant difference
in PWV between adult term and pre-
term groups.
Increased blood pressure after pre-
term birth may also derive from
altered renal function, with data sug-
gesting accelerated maturation and
abnormal morphology in the preterm
neonatal kidney.71 The third trimester
represents a crucial period for kidney
development, with nephrogenesis com-
pleted by 36-week GA. However, the
limited number of studies of renal
function in children72 and adults55 born
pretermnd no consistent differences
with full-term counterparts.
Insulin resistanceis a keycomponent of
the metabolicsyndrome,but data on the
relationship with GA have been in-
conclusive to date. Several publications
reveal no association,73,74 whereas
other large cohort analyses demon-
strate a clear link between GA and de-
velopment of diabetes in childhood and
later life.75,76 We identied no differ-
ence in fasting glucose or insulin be-
tween adults born preterm and at
term. Meta-regression revealed no as-sociation between GA and fasting in-
sulin or glucose. However, the power to
detect such an association was small,
with only aggregate data available.
Future studies should provide data on
glucose homeostasis using a recog-
nized outcome measure such as Ho-
meostatic model assessment of insulin
resistance,77 which is sensitive and
combines both glucose and insulin
measurements. Although we foundsome evidence of increased LDL in
preterm subjects, an increase likely to
be responsible for the trend toward
increased total cholesterol, it should
be noted that because of the number of
statistical tests performed, these
results may have arisen by chance.
There was no indication of publication
bias from the funnel plot analysis of
these outcomes, although the small
number of studies made detection dif-
cult.
There are limitations to the conclusions
that may be drawn from observational
studies. However, the strengths of our
systematic review and meta-analysis
are the large number of studies and
subjects and the inclusion of additional
information provided by authors, in-
cluding data from several large
population-based cohorts.24,32,35 Only
a small number of studies were avail-
able for WHR, cardiovascular indices,
and 24-hour aBP measurements, limit-
ing power to detect an association
between preterm birth and these
parameters. The lack of individual pa-
tient data prevents ascertainingwhether degree of prematurity is as-
sociated with a greater impact on
outcomes such as adult blood pres-
sure, as suggested in large studies.4
In several studies, no adjustment was
made for potential confounders; where
thiswas done, adjustmentswere mainly
on the basis of genderand age. The lack
of uniformity in adjustment across
different studies limited meaningful
evaluation of the impact of potentialconfounders. Additionally, the justi-
cation for adjusting data for con-
founders that lie along the causal
pathway between prematurity and
adult outcomes is questionable64; BMI,
body weight, and gender differences
have all been noted to be associated
with preterm birth, and as such, it is
perhaps not appropriate to adjust for
these confounders. Exclusion criteria
were not standardized across allstudies, although in the majority of
studies, individuals with serious
chronic disease or neurologic impair-
ment were not included. A focus on low
birth weight as a risk factor for adult
blood pressure has complicated
efforts to dene the role of pre-
maturity, because this nomenclature
fails to disentangle the overlap with
intra-uterine growth restricted. Two
studies have attempted to address this
by comparing preterm appropriate for
GA and preterm small for GA adults;
neither reports signicant differences
in blood pressure between these pre-
term groups.30,41 Additional factors,
including growth rate in infancy andsocioeconomic status (SES), also con-
tribute to the development of an ad-
verse cardiovascular phenotype.78,79
Two studies in our meta-analysis in
which subjects were matched for SES
reported signicant increases in blood
pressure in adults born preterm.5,39 In
4 studies where adjustment was per-
formed, SES did not explain the differ-
ence in outcomes.4,25,38,41 Taken together,
these data suggest that at least part ofthe increase in adult blood pressure
observed in adults born preterm is
independent of SES.
We focused exclusively on adult out-
comes to avoid combining measures
of effect size with infancy, childhood,
and adolescence. Although meta-
regression revealed no signicant
relationship between term-preterm
differences for any outcome and age,
few studies in our meta-analysis pre-sented data on individuals .30 years.
The average age at outcome varied
across parameters (range, 2139 years),
and it would be unwise to suggest that
the data presented here represent
a clear adult phenotype for preterm
individuals. Differences in metabolic
markers in early adulthood are strongly
associated with cardiovascular disease
in later life, higher blood pressure in late
adolescence is associated with early in-cidence of coronary heart disease and
stroke,80 and cholesterol level in young
adulthood predicts all-cause mortality
and longevity.81 Evaluations of older
populations are essential to determine
if associations with preterm birth
emerge or become more pronounced
with aging. Ultimately, studies must be
undertaken to elucidate the physiologic
mechanisms and causal pathways that
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underpin divergence and identify new-
born care practices that either exacer-
bate or attenuate risk.
ACKNOWLEDGMENTS
We thank all the authors listed inTable 1
who kindly supplied additional data: Pier
Paolo Bassareo, Rachel Cooper, Stuart
Dalziel, Lex Doyle, Bjorn Fagerberg, Chris
Power, Franco Rabbia, and Michael Skilton.
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