Pediatrics 2013 Parkinson e1240 63

8/12/2019 Pediatrics 2013 Parkinson e1240 63

1/27

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

http://pediatrics.aappublications.org/content/131/4/e1240.full.htmllocated on the World Wide Web at:

The online version of this article, along with updated information and services, is

of Pediatrics. All rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.Boulevard, Elk Grove Village, Illinois, 60007. Copyright 2013 by the American Academypublished, and trademarked by the American Academy of Pediatrics, 141 Northwest Point

publication, it has been published continuously since 1948. PEDIATRICS is owned,PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly

at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
http://pediatrics.aappublications.org/content/131/4/e1240.full.htmlhttp://pediatrics.aappublications.org/content/131/4/e1240.full.htmlhttp://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/content/131/4/e1240.full.html


2/27

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)

e1240 PARKINSON et al.at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/


3/27

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

REVIEW ARTICLE

PEDIATRICS Volume 131, Number 4, April 2013 e1241at Indonesia:AAP Sponsored on May 23, 2014pediatrics.aappublications.orgDownloaded from
http://www.ncbi.nlm.nih.gov/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://www.ncbi.nlm.nih.gov/


4/27

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

http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplemental


5/27

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.

REVIEW ARTICLE

http://-/?-http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://-/?-


6/27

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


PT:1.2

(0.7

)

TC:1.3

(1.2

)



7/27

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

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

)


PT:1.8

(0.8

)

TC:1.5

(0.7

)

REVIEW ARTICLE

http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/


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


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

)



9/27

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


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



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

)



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

)


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

)

REVIEW ARTICLE



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

)


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

)



13/27

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

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

)


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

)

REVIEW ARTICLE



14/27

TABLE

1

Continued

AuthorandYear

Populat

ionandStudyDetails

SampleNum

ber

GA(wk)[Mean6

SD

orMedian(Range)]

BirthWeight(g)

[Mean6

SDor

Median(Range)]

AdultAge6

SD

orMedian(Range)

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



15/27

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

)


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).

REVIEW ARTICLE



16/27

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.



17/27

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.

REVIEW ARTICLE

http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://-/?-http://-/?-http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


18/27

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.



19/27

FIGURE 3Forest plotsshowingthe unadjustedassociationbetweenpreterm birthand (Aand B)SBPand (Cand D)DBP in(A andC) adultmen and(B andD) adultwomen.

REVIEW ARTICLE



20/27

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.

http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/http://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplementalhttp://pediatrics.aappublications.org/lookup/suppl/doi:10.1542/peds.2012-2177/-/DCSupplemental


21/27

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

REVIEW ARTICLE



22/27

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



23/27

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.

REFERENCES

1. Hales CN, Barker DJ. The thrifty phenotype

hypothesis. Br Med Bull. 2001;60:520

2. Saigal S, Doyle LW. An overview of mortality

and sequelae of preterm birth from in-

fancy to adulthood. Lancet. 2008;371(9608):

261269

3. Doyle LW, Faber B, Callanan C, Morley R.

Blood pressure in late adolescence and

very low birth weight. Pediatrics. 2003;111

(2):252257

4. Johansson S, Iliadou A, Bergvall N, Tuvemo

T, Norman M, Cnattingius S. Risk of high

blood pressure among young men increaseswith the degree of immaturity at birth.

Circulation. 2005;112(22):34303436

5. Hack M, Schluchter M, Cartar L, Rahman M.

Blood pressure among very low birth

weight (,1.5 kg) young adults. Pediatr

Res. 2005;58(4):677684

6. de Jong F, Monuteaux MC, van Elburg RM,

Gillman MW, Belfort MB. Systematic review

and meta-analysis of preterm birth and

later systolic blood pressure. Hyperten-

sion. 2012;59(2):226234

7. Hovi P, Andersson S, Eriksson JG, et al.

Glucose regulation in young adults withvery low birth weight. N Engl J Med. 2007;

356(20):20

Pediatrics 2013 Parkinson e1240 63

Documents

Transcript of Pediatrics 2013 Parkinson e1240 63