Post on 15-May-2023
Original article 1871
Birth weight, weight change, a
nd blood pressure duringchildhood and adolescence: a school-based multiplecohort studyArnaud Chioleroa,b, Gilles Paradisa,c,d, George Madeleinee, James A. Hanleya,Fred Paccaudb and Pascal Bovetb,eObjective We assessed the association between birth
weight, weight change, and current blood pressure (BP)
across the entire age-span of childhood and adolescence in
large school-based cohorts in the Seychelles, an island
state in the African region.
Methods Three cohorts were analyzed: 1004 children
examined at age 5.5 and 9.1 years, 1886 children at 9.1 and
12.5, and 1575 children at 12.5 and 15.5, respectively. Birth
and 1-year anthropometric data were gathered from
medical files. The outcome was BP at age 5.5, 9.1, 12.5 or
15.5 years, respectively. Conditional linear regression
analysis was used to estimate the relative contribution
of changes in weight (expressed in z-score) during
different age periods on BP. All analyses were adjusted for
height.
Results At all ages, current BP was strongly associated with
current weight. Birth weight was not significantly associated
with current BP. Upon adjustment for current weight, the
association between birth weight and current BP tended to
become negative. Conditional linear regression analyses
indicated that changes in weight during successive age
periods since birth contributed substantially to current BP at
all ages. The strength of the association between weight
Copyright © Lippincott Williams & Wilkins. Unaut
0263-6352 � 2011 Wolters Kluwer Health | Lippincott Williams & Wilkins
change and current BP increased throughout successive
age periods.
Conclusion Weight changes during any age period since
birth have substantial impact on BP during childhood and
adolescence, with BP being more responsive to recent than
earlier weight changes. J Hypertens 29:1871–1879 Q 2011
Wolters Kluwer Health | Lippincott Williams & Wilkins.
Journal of Hypertension 2011, 29:1871–1879
Keywords: birth weight, blood pressure, children, growth, life course
Abbreviation: BP, blood pressure
aDepartment of Epidemiology, Biostatistics, and Occupational Health, McGillUniversity, Montreal, Canada, bInstitute of Social and Preventive Medicine(IUMSP), University Hospital Center and University of Lausanne, Switzerland,cMcGill University Health Center Research Institute, dPublic Health Institute ofQuebec, Montreal, Canada and eMinistry of Health, Victoria, Republic ofSeychelles
Correspondence to Dr Pascal Bovet, MD, MPH, Institute of Social and PreventiveMedicine, University of Lausanne, 17 rue du Bugnon, 1005 Lausanne,SwitzerlandTel: +41 21 314 72 72; fax: +41 21 314 73 73; e-mail: bovet.pascal@gmail.com
Received 9 February 2011 Revised 5 April 2011Accepted 13 July 2011
IntroductionBlood pressure (BP) tracks across the life course [1] and
may be determined early in life, particularly during
fetal development [2]. Alterations in the intra-uterine
environment and in fetal growth could be associated with
adaptive processes that program increased susceptibility
to hypertension [3]. This hypothesis is supported by
numerous studies which have shown an inverse associ-
ation between birth weight – used as a proxy for fetal
growth – and BP [2,4]. However, some studies found no
association or a positive association between birth weight
and BP [5,6] and doubts have been raised about the
causality of this association [7]. In addition, the inverse
association between birth weight and BP may reflect
the impact of postnatal rather than fetal growth because
the reported inverse association is magnified or appears
only upon adjustment for body size measured at the time
of BP measurement [5,8,9].
Whereas rapid postnatal growth during the first 1 or
2 years of life may be critical for the determination of
future BP [10–12], studies also suggest that changes in
body weight during later years, that is in childhood and
adolescence, are of greater importance on BP in adoles-
cents [6] or young adults [13]. Singhal and Lucas [11]
hypothesized that rapid growth – for example, an upward
centile crossing or an increase in z-score of weight – early
in life (in infancy) but also during childhood could have a
detrimental effect on cardiovascular disease risk factors.
Still, the relative contribution of body weight change at
different ages on the level of current BP during childhood
and adolescence remains unclear [4]. This is due to the
paucity of large longitudinal studies with repeated
anthropometric and BP measurements at different ages
and to related statistical analytic challenges [9,14].
Previous studies analyzed one cohort at a time with
limited age ranges at which body weight or BP were
measured [6,10–13]. Since we collected several weight
measurements between birth and school age in a large
number of children from an ongoing school-based sur-
veillance program, we assessed the association between
birth weight, weight change at different ages, and current
horized reproduction of this article is prohibited.
DOI:10.1097/HJH.0b013e32834ae396
C
1872 Journal of Hypertension 2011, Vol 29 No 10
BP across the entire age-span of childhood and adoles-
cence.
MethodsThe research took place in the Republic of Seychelles, a
middle-income island state in the Indian Ocean (African
region), approximately 1000 km east of Kenya. A large
majority of the population is of African descent. In the
Seychelles, child and maternal undernutrition is uncom-
mon and a high prevalence of cardiovascular disease risk
factors (e.g. hypertension and obesity) has been docu-
mented in adults [15,16] and in children [17,18].
As part of a surveillance system, data were collected
during routine medical visits at school carried out by a
dozen trained school nurses. The surveillance system has
been routinely conducted in all schools for more than a
decade and was approved by the Ministry of Health after
technical and ethical reviews. Parents or guardians pro-
vided informed consent and children were free to parti-
cipate. The Institutional Review Boards at McGill
University approved the study protocol. Nearly 100% of
children attend school up to the fourth secondary level.
Data were collected between 1998 and 2006 in children
and adolescents attending all schools in four selected
grades: kindergarten, fourth, seventh and 10th year of
obligatory school [17,18]. Children were surveyed more
than once as they moved across the four selected grades
over time. For the present study, we analyzed three cohorts
of children who had been examined twice in kindergarten
and grade 4, grade 4 and grade 7, or grade 7 and grade 10
and for whom birth data and 1-year body weight and height
were available (Fig. 1). Some of the children that were
examined on three separate occasions (at 3–4-year inter-
vals) are included in two different cohorts.
opyright © Lippincott Williams & Wilkins. Unauth
Fig. 1
G4
Cohort G4-G71yBirth
Cohort G7-G10
Cohort K-G4
5
Age
G4
0
K
1yBirth
1yBirth
BPBP
Three cohorts of children were analyzed. In the cohort K-G4, we assessed(kindergarten), and age 9.1 (grade 4) and blood pressure (BP) at age 5.5association between weight measurements at birth, age 1, age 9.2 (grade 4we assessed the association between weight measurements at birth, age 1
School nurses followed a standard measurement pro-
cedure and were regularly trained by one of the inves-
tigators (G.M.). The equipment was checked annually
for accuracy. Equipment and methods for BP and anthro-
pometry measurements were kept identical throughout
the study period. BP was measured according to a stan-
dardized protocol with oscillometric automated devices
(Omron M5; Omron), which met the international vali-
dation protocol criteria for BP measurement [19]. BP was
measured on the right arm, in the sitting position, after a
5-min rest, and using a cuff of appropriate size according
to the arm circumference. Two readings were obtained at
a 1-min interval and averaged. Elevated BP was defined
as SBP and/or DBP equal to or above the US reference
sex, age, and height-specific 95th percentile [20].
Weight was measured using precision electronic scales
(Seca 870; Seca, Hamburg, Germany) and height was
measured with fixed stadiometers (Seca 208; Seca, Ham-
burg, Germany). Overweight and obesity were defined
using the sex and age-specific BMI criteria of the CDC,
that is, body mass index (BMI) percentile at least 85th
and at least 95th, respectively [21]. Early life anthropo-
metric data (birth weight, gestational age at birth, and
body weight at 1 year) were gathered retrospectively from
medical records [22]. Gestational age was estimated from
the date of the first day of the mother’s last menstrual
period reported in medical records. Internal sex and age-
specific z-scores (i.e. standard deviation scores) for weight
and height (or length) at each age were generated.
Statistical analysesTracking of body weight z-scores was assessed by
Pearson’s correlation coefficient between two measure-
ments from the same children [1,23].
orized reproduction of this article is prohibited.
G7 G10
(years)
G7
10 15
K: kindergartenG4: grade 4G7: grade 7G10: grade 10BP
BP
the association between weight measurements at birth, age 1, age 5.5and at age 9.1, respectively. In the cohort G4–G7, we assessed the), and age 12.5 (grade 7) and BP at age 12.5. In the cohort G7–G10,, age 12.5 (grade 7), and age 15.5 (grade 10) and BP at age 15.5.
Weight change and blood pressure in children Chiolero et al. 1873
We assessed the association between birth and current
body weight z-scores, changes in body weight z-scores,
and current BP measured at 5.5 and 9.1 years in the
kindergarten–grade 4 cohort, at 12.5 years in the grade
4–7 cohort, and at 15.5 years in the grade 7–10 cohort,
respectively (Fig. 1), using standard and conditional
linear regression analyses [8,14,24]. We fitted models
within each cohort, for each sex, and for SBP and DBP
separately. We conducted sex-specific analyses because
the pattern of growth differs between boys and girls and
because the relationship between weight z-scores and BP
could differ between boys and girls. Exploratory analyses
indeed showed interactions between current weight
z-scores and sex to be significantly associated with
SBP. However, because the differences between boys
and girls were modest (see results below), we do not
emphasize the sex difference.
Standard linear regression analysesTo assess the association between birth and current body
weight z-scores and current BP, models of standard linear
regression models were fitted, following the recommen-
dations of Lucas et al. [8]. First, two models were fitted
with birth weight and current weight body z-score con-
sidered separately, that is, current BP¼aþb1�birth
weight z-score, corresponding to the ‘early’ model in
Lucas et al.’ terminology [8]; current BP¼aþb2� cur-
current body weight z-score, corresponding to the ‘late’
model. Second, a model was fitted with both body weight
z-scores considered simultaneously, that is, current
BP¼aþb1�birth weight z-scoreþb2� current body
weight z-score, corresponding to the ‘combined’ model
[8]. Furthermore, because individuals born small for
gestational age (SGA) tend to have a greater upward
body weight postnatal centile crossing (i.e. catch-up
growth) and their BP may be more sensitive to weight
change compared to individuals with normal birth weight
[25], we fitted additional models with an interaction term
between birth and current weight z-scores, that is, current
BP¼aþb1�birth weight z-scoreþb2� current body
weight z-scoreþb3� [birth weight z-score� current
body weight z-score], corresponding to the ‘interaction’
model [8]. If the interaction term turns out to be signifi-
cantly associated with BP, this means that postnatal
weight change has a differential effect on BP in SGA
and normal birth weight individuals [8]. To account for
the potential effect of height on BP, all these models
were fitted with an adjustment for birth length or/and
current height.
Conditional linear regression analysesWe fitted conditional linear regression (also called un-
explained residual regression [24]) models to assess the
relative contribution of changes in body weight z-score
during different periods on BP level. With such model,
the effect of weight change during each period is assessed
independently from the effect of weight change during
Copyright © Lippincott Williams & Wilkins. Unaut
other periods [13,24,26]. This method allows estimation
of the specific contribution of weight changes on BP at
different age periods during childhood and the identifi-
cation of sensitive periods for the effect these changes
have on BP [26].
For each age of the children after birth, we first fitted
separate linear regression models of body weight z-score at
each exam on previous weight(s) and calculated residuals
of body weight z-scores at each age. These residuals
express how many units of body weight z-score was gained
or lost above the expected z-score over the prior interval.
The following conditional regression model was then
fitted: BP¼aþb0�birth weight z-scoreþb1� residual
of one year body weight z-scoreþb2� residual of inter-
mediate body weight z-scoreþb3� residual of current
body weight z-score.
For each residual, and at each age period, the regression
coefficient can be interpreted as the effect on current BP
of change in body weight during a given age period, given
past body weight history [13]. The coefficient expresses
the difference in BP between a child who has gained one
standard deviation of weight during a given age period to
a child with an identical past weight history who did not
gain weight during this period [13]. Each coefficient for
different age periods can be interpreted independently
from the other because residuals are statistically unre-
lated to each other. To account for the potential effect of
height on BP, these models were fitted with an adjust-
ment for birth length and change in height during the
considered age periods (using residuals of 1 year, inter-
mediate, and current body height z-scores, respectively).
Adjustment for patients’ age at each exam and for birth
year was made in all models.
Analyses were carried out with Stata 10.0 (StataCorpLP,
College Station, Texas, USA).
ResultsSome 2743 children were included in this study, that is,
1004 in the kindergarten–grade 4 cohort, 1886 in grade
4–7, and 1575 in grade 7–10, respectively. Table 1 shows
the characteristics of the children in each cohort. The
average time between two exams was 3.6 years (SD 0.3)
in cohort kindergarten–grade 4, 3.4 years (0.3) in cohort
grade 4–7, and 3.0 years (0.3) in cohort grade 7–10, respec-
tively.
Tracking of body weight z-score was relatively weak
between weight at birth or weight at 1 year of age and
weight later in life (Table 2). Tracking was much stronger
between successive body weight measurements in child-
hood and adolescence.
Using standard linear regression analyses, neither SBP
(Table 3) nor DBP (Table 4) was associated with birth
weight z-score. In each cohort, a strong association
was found between current body weight and BP. The
horized reproduction of this article is prohibited.
C
1874 Journal of Hypertension 2011, Vol 29 No 10
Table 1 Characteristics of the participants in the three cohorts
Cohort K–G4 (N¼1004) Cohort G4–G7 (N¼1886) Cohort G7–G10 (N¼1575)
K G4 G4 G7 G7 G10
BoysN 522 930 738Birth weight (kg) 3.1 (0.5) 3.2 (0.5) 3.2 (0.5)Gestational age (week) 39.2 (1.6) 39.4 (1.5) 39.4 (1.5)One year weight (kg) 10.0 (1.2) 10.0 (1.1) 10.0 (1.1)Age (year) 5.5 (0.4) 9.1 (0.4) 9.1 (0.4) 12.5 (0.4) 12.5 (0.4) 15.5 (0.4)Weight (kg) 19.5 (3.4) 29.6 (7.3) 29.0 (6.2) 42.7 (10.7) 41.6 (10.1) 57.7 (11.2)Height (cm) 113.4 (5.6) 134.0 (6.5) 134.0 (6.3) 152.3 (8.3) 151.2 (8.1) 169.8 (7.3)BMI (kg/m2) 15.1 (1.9) 16.4 (3.1) 16.1 (2.7) 18.3 (3.6) 18.1 (3.4) 20.0 (3.4)Overweight (%) 10.3 14.7 11.4 16.1 14.1 9.9Obesity (%) 5.6 7.9 5.7 6.5 5.7 4.1SBP (mmHg) 95.1 (10.0) 100.6 (11.2) 101.0 (11.0) 104.0 (11.3) 104.4 (10.8) 115.6 (12.2)DBP (mmHg) 58.4 (9.5) 62.3 (9.8) 61.9 (9.7) 64.0 (8.4) 64.8 (8.8) 68.5 (8.6)Elevated BP (%) 6.7 9.0 8.5 4.8 5.0 10.3
GirlsN 482 956 837Birth weight (kg) 3.1 (0.5) 3.1 (0.5) 3.1 (0.5)Gestational age (week) 39.3 (1.6) 39.4 (1.5) 39.2 (1.6)One year weight (kg) 9.5 (1.2) 9.5 (1.2) 9.4 (1.2)Age (year) 5.5 (0.3) 9.1 (0.3) 9.1 (0.3) 12.5 (0.4) 12.5 (0.4) 15.5 (0.4)Weight (kg) 19.2 (3.4) 30.2 (7.3) 29.8 (7.1) 47.0 (11.6) 45.7 (11.4) 54.9 (11.4)Height (cm) 112.7 (5.3) 134.3 (6.6) 134.1 (6.5) 155.0 (7.1) 153.8 (7.1) 161.1 (6.1)BMI (kg/m2) 15.1 (2.0) 16.6 (3.3) 16.4 (3.1) 19.5 (4.2) 19.2 (4.1) 21.2 (4.2)Overweight (%) 10.4 16.4 14.6 21.5 19.6 18.3Obesity (%) 4.8 7.7 5.9 9.1 7.9 5.7SBP (mmHg) 94.9 (10.7) 101.2 (11.6) 101.1 (10.9) 105.8 (11.0) 106.1 (10.6) 109.1 (10.5)DBP (mmHg) 58.6 (9.6) 63.7 (9.5) 63.0 (9.4) 66.9 (8.6) 67.1 (8.8) 69.5 (7.8)Elevated BP (%) 9.5 11.2 11.0 8.8 9.1 7.9
Values are mean (SD) or proportion. BP, blood pressure; G, grade; K, kindergarten. Overweight and obesity were defined using the sex- and age-specific BMI criteria of theCDC, that is, BMI percentile at least 85th and at least 95th, respectively [21]. Elevated BP was defined as SBP and/or DBP equal to or above the US reference sex, age, andheight-specific 95th percentile [20].
association between current weight z-score and SBP was
slightly weaker at younger (5.5 or 9.1 years) than at later
ages (12.5 or 15.5 years) (Table 3). The association
between current weight z-score and BP was generally
weaker for DBP than for SBP. For DBP, the strength of
the association with current body weight z-score was
similar at all ages (Table 4). These patterns were similar
in both sexes.
In standard linear regression analyses considering simul-
taneously birth and current body weight measurements,
the association between birth weight z-score and BP
tended to decrease and, in some cases, become negative.
In these models, current weight remained strongly associ-
ated with BP. In each cohort, the interaction term
between birth weight z-score and current weight z-score
opyright © Lippincott Williams & Wilkins. Unauth
Table 2 Tracking correlation coefficient of body weight z-scorebetween successive visits
Boys Girls
Age(years) 1 5.5 9.1 12.5 15.5 1 5.5 9.1 12.5 15.5
0 0.28 0.19 0.15 0.12 0.09 0.27 0.22 0.18 0.15 0.181 0.52 0.42 0.33 0.29 0.60 0.42 0.39 0.375.5 0.84 0.77 0.81 0.739.1 0.87 0.76 0.87 0.7812.5 0.81 0.84
was not statistically significantly associated with SBP or
DBP (P-values for interaction term 0.11–0.98).
Conditional regression analyses showed that both SBP
and DBP were positively associated with body weight z-
score change in all the considered age periods after birth
(Figs 2 and 3, Online supplement Table S1 and S2, http://
links.lww.com/HJH/A113) but the strength of the associ-
ation between weight gain and current BP tended to
increase throughout successive age periods in all cohorts.
The strength of the association was generally weaker for
weight change between birth and 1 year of age than for
later weight change. These findings were similar for boys
and girls and for SBP (Fig. 2) and DBP (Fig. 3), albeit the
strength of the associations was generally weaker for DBP
than SBP.
DiscussionThe major finding of our study is that weight changes
during successive age periods since birth contributed
substantially to current BP during childhood and adoles-
cence and that this association was stronger for weight
changes in recent than earlier years of children’s growth.
Weight change in the first year of life had a significant but
relatively small impact on current BP. No significant
association was observed between birth weight and cur-
rent BP although there was a trend toward negative
orized reproduction of this article is prohibited.
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Weight change and blood pressure in children Chiolero et al. 1875
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C
1876 Journal of Hypertension 2011, Vol 29 No 10
Fig. 2
-2-101234567
Con
ditio
nal r
egre
ssio
n co
effi
cein
t(m
mH
g/un
it z-
scor
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Boys
Girls
at 12.5 years
Age period (year)
Systolic BP at 9.1 yearsat 5.5 years at 15.5 years
Regression coefficient estimates (and 95% confidence interval) from regression of current SBP on each specific residual of body weight z-score.
association upon adjustment for current weight. There
was no evidence that the effect of postnatal weight
change on current BP differed between individuals born
small for gestational age and individuals born with normal
birth weight.
Few studies have assessed the association between cur-
rent BP and growth taking place after infancy or after
early childhood [4,6,13]. For example, using standard
multiple regression analysis, Horta et al. [6] reported that
rapid weight gain before and after the age of 4 was
associated with high SBP at 15 years of age. Only weight
gain after the age of 4 years was associated with DBP. In
young adults, using various statistical methods, a change
in BMI z-scores after – but not before – the age of
11–13 years was shown to be a strong determinant of BP
opyright © Lippincott Williams & Wilkins. Unauth
Fig. 3
−2
−1
0
1
2
3
4
5
6
7
Co
nd
itio
nal
reg
ress
ion
co
effi
cein
t(m
mH
g/u
nit
z-s
core
)
aDiastolic BP at 9.1 yearsat 5.5 years
Regression coefficient estimates (and 95% confidence interval) from regres
at 30–40 years of age [13]. Limitations of these studies
include the relatively long interval of time between
weight measurements before BP determination and
the relatively small sample sizes. These studies may
indicate critical periods with respect of the effect of
growth on BP, but they also suggest that weight gain
that immediately precedes BP measurement is most
strongly associated with BP, that is, recent weight gain
has more effect on BP than earlier weight change, which
is consistent with our findings.
Although the effect was relatively small in our study,
weight gain during the first year of life contributed to BP
independently of later weight gain. This may be due to
tracking of body weight [23] as well as ‘programming’
of BP early in life. Whereas experimental studies in
orized reproduction of this article is prohibited.
Boys
Girls
t 12.5 years
Age period(year)
at 15.5 years
sion of current DBP on each specific residual of body weight z-score.
Weight change and blood pressure in children Chiolero et al. 1877
newborns have suggested that BP may be ‘programmed’
by faster weight gain in the first months of life [11,27],
observational studies assessing the effect of growth early
in postnatal life on later BP have provided contrasting
results [10,12,28–30]. Some studies suggest that weight
gain in the first months of life is associated with elevated
BP in young adults [12,30]. For example, it was reported
that rapid weight gain during infancy (0–6 months) – but
not during early childhood (3–6 years) – predicted risk
factors clustering associated with the metabolic syn-
drome, including elevated BP, in adolescents aged
17 years [31]. However, other studies did not find that
early weight gain was critical for later BP [10,28,29]. For
example, Law et al. [10] found that weight gain during
infancy (0–1 year) was not associated with SBP at 22 years
of age although they did find an association with weight
gain during early childhood (1–5 years). Similarly, in
children aged 3 in Britain [28] and in children aged 6
in Australia [29], BP was not associated with weight gain
during the first year of life once birth weight or current
body weight was taken into account. Overall, it remains
difficult to ascertain with confidence whether weight
gain in the first years of life is critical for later BP or
not, and our study suggests that it may be less critical than
weight gain later in life. Long-term follow-up of partici-
pants randomized to interventions potentially affecting
early growth and excessive weight gain (e.g. breastfeed-
ing vs. formula feeding) may shed light on this issue
[8,11].
We found that the association between birth weight and
current BP was null or only modest without adjustment
for current body weight and tended to become negative
upon adjustment for current weight. With regards to the
unadjusted association, other studies reported mixed
results, that is, positive, negative or no association
[5,6,32]. In a systematic review pooling data from more
than 350 000 children and adults, the (unadjusted) associ-
ation between birth weight and later BP was weakly
negative [5]. Our finding of a tendency toward a negative
association between birth weight and current BP upon
adjustment for current body weight, is consistent with
most studies showing that, after adjustment for current
body size, a negative association between birth weight
and later BP emerges or, if already present in the unad-
justed analysis, is magnified [5,9,32]. This suggests that
among children who attained the same weight at a given
age, those who were of lower birth weight have, on
average, higher BP, that is, that growth trajectories since
from conception to childhood or adolescence may be
determinants for the level of BP [33].
Blood pressure seems to be increasingly responsive to
weight changes throughout successive age periods during
childhood and adolescence. This may be due to the effect
of weight changes on attained weight and corresponding
amount of adiposity. Biologically, a large weight gain
during childhood reflects in part an accumulation of
Copyright © Lippincott Williams & Wilkins. Unaut
adipose tissue. Excess adiposity is associated with inflam-
mation, production of adipocytokines, sympathetic
hyperactivity, and insulin resistance, which all may
increase BP in children and adolescents [34]. In adults,
studies suggest that BP is more sensitive to recent than
past weight decrease, and this effect has been linked to
water and salt losses and, perhaps, reduced sympathetic
activity and insulin resistance [35]. Changes in diet or
in physical activity that are concomitant with recent
body weight changes may also influence BP. Postnatal
‘programming’ of BP may also be involved. It implies the
modification or impaired development of permanent
somatic structures or the resetting of physiological sys-
tems by a given stimulus at a sensitive time period,
resulting in long-term consequences on BP [3]. For
instance, the kidneys play a major role in the long-term
regulation of BP and biological mechanisms for a
hypothetical postnatal programming of BP could involve
alterations in renal function [36]. Thus, excess weight
gain during successive age period may be associated
with the progressive development of subtle renal
deterioration due to adiposity-related factor such as
an increased intrarenal pressure or hyperuricemia [36].
Progressive increase in arterial stiffness could also be
implicated [37] and could explain that the strength of
the association between current body weight and BP
increased with age.
Our study has limitations. Our analyses are conditioned
on the age at which data were collected and we could
analyze a limited numbers of defined periods of growth.
Birth weight, gestational age and body weight at the age
of 1 year were gathered retrospectively. We did not take
into account several potential explanatory or confounding
factors (e.g. physical activity, diet, pubertal development/
sexual maturation, socio-economic factors, or parents’
characteristics), which limits causal inferences. We did
not have data on metabolic or cardiovascular character-
istics which could have provided further insight on the
cardiovascular consequences of weight change during
childhood and adolescence. Detailed information on
body composition and fat distribution would have also
helped understand biological mechanisms underlying the
association between weight change and BP [38]. Findings
in one population may not directly apply to all popu-
lations since the ideal growth trajectory for cardiovascular
health may differ among different populations [32]. Our
study also has unique strengths. We studied three large
population-based cohorts and used identical and standar-
dized measurement methods allowing a comprehensive
study of growth and BP across the entire age range of
childhood and adolescence. Our statistical methods allow
the direct comparison of the effect on current BP of
weight change during successive age periods.
Our findings have important clinical and public health
significance for the prevention and control of elevated
BP. On one hand, because BP is more responsive to
horized reproduction of this article is prohibited.
C
1878 Journal of Hypertension 2011, Vol 29 No 10
recent than earlier weight change, prevention of exces-
sive weight gain even relatively late in childhood
or adolescence may be important strategies to address
elevated BP or prevent its occurrence. On the contrary,
because weight gain at all ages is associated with
both increased weight and increased BP later in life,
maintenance of a healthy weight at all ages will
help prevent hypertension in childhood or adolescence
[20]. Nonetheless, it remains unclear whether interven-
tions to prevent weight gain are more efficient at younger
than at later age [39]. Further studies are required to
determine modalities and best timing for weight control
interventions during childhood as a mean to prevent
elevated BP.
AcknowledgmentsData for this study were collected within the routine
operation of an ongoing School Health Program con-
ducted by the Ministry of Health of the Republic of
Seychelles. Equipment for this program was partially
funded by the World Health Organization and some
other nonprofit organizations. We thank all the nurses
and other health officers involved with the School Health
Program and we are grateful to the Ministry of Health for
continued support to epidemiological research related to
non communicable diseases. Arnaud Chiolero is sup-
ported by the Canadian Institutes of Health Research
(CIHR). Gilles Paradis holds a CIHR Applied Public
Health Research Chair. The views expressed by the
authors of this paper do not reflect necessarily those of
their institutions.
Conflicts of interestThere are no conflicts of interest.
References1 Chen X, Wang Y. Tracking of blood pressure from childhood to adulthood:
a systematic review and meta-regression analysis. Circulation 2008;117:3171–3180.
2 Barker DJP, Bull AR, Osmmond C, Simmonds SJ. Fetal and placental sizeand risk of hypertension later in life. BMJ 1990; 301:259–262.
3 McMillen IC, Robinson JS. Developmental origins of the metabolicsyndrome: prediction, plasticity, and programming. Physiol Rev 2005;85:571–633.
4 Lawlor DA, Smith GD. Early life determinants of adult blood pressure. CurrOpin Nephrol Hypertens 2005; 14:259–264.
5 Huxley R, Neil A, Collins R. Unravelling the fetal origins hypothesis: is therereally an inverse association between birthweight and subsequent bloodpressure? Lancet 2002; 360:659–665.
6 Horta BL, Barros FC, Victora CG, Cole TJ. Early and late growth and bloodpressure in adolescence. J Epidemiol Community Health 2003; 57:226–230.
7 Kramer MS. Invited commentary: association between restricted fetalgrowth and adult chronic disease: is it causal? Is it important? Am JEpidemiol 2000; 152:605–608.
8 Lucas A, Fewtrell MS, Cole TJ. Fetal origins of adult disease-the hypothesisrevisited. BMJ 1999; 319:245–249.
9 Tu YK, West R, Ellison GT, Gilthorpe MS. Why evidence for the fetal originsof adult disease might be a statistical artifact: the ‘reversal paradox’ for therelation between birth weight and blood pressure in later life. Am JEpidemiol 2005; 161:27–32.
10 Law CM, Shiell AW, Newsome CA, Syddall HE, Shinebourne EA, FayersPM, et al. Fetal, infant, and childhood growth and adult blood pressure: alongitudinal study from birth to 22 years of age. Circulation 2002;105:1088–1092.
opyright © Lippincott Williams & Wilkins. Unauth
11 Singhal A, Lucas A. Early origins of cardiovascular disease: is there aunifying hypothesis? Lancet 2004; 363:1642–1645.
12 Ben-Shlomo Y, McCarthy A, Hughes R, Tilling K, Davies D, Smith GD.Immediate postnatal growth is associated with blood pressure in youngadulthood: theBarryCaerphilly GrowthStudy. Hypertension2008;52:638–644.
13 Gamborg M, Andersen PK, Baker JL, Budtz-Jørgensen E, Jørgensen T,Jensen G, Sørensen TI. Life course path analysis of birth weight, childhoodgrowth, and adult systolic blood pressure. Am J Epidemiol 2009;169:1167–1178.
14 De Stavola BL, Nitsch D, dos Santos Silva I, McCormack V, Hardy R, MannV, et al. Statistical issues in life course epidemiology. Am J Epidemiol 2006;163:84–96.
15 Danon-Hersch N, Chiolero A, Shamlaye C, Paccaud F, Bovet P.Decreasing association between body mass index and blood pressure overtime. Epidemiology 2007; 18:493–500.
16 Bovet P, Romain S, Shamlaye C, Mendis S, Darioli R, Riesen W, et al.Divergent fifteen-year trends in traditional and cardiometabolic risk factorsof cardiovascular diseases in the Seychelles. Cardiovasc Diabetol 2009;8:34.
17 Chiolero A, Madeleine G, Gabriel A, Burnier M, Paccaud F, Bovet P.Prevalence of elevated blood pressure and association with overweight inchildren of a rapidly developing country. J Hum Hypertens 2007; 21:120–127.
18 Chiolero A, Paradis G, Madeleine G, Hanley JA, Paccaud F, Bovet P.Discordant secular trends in elevated blood pressure and obesity inchildren and adolescents in a rapidly developing country. Circulation 2009;119:558–565.
19 El Assaad MA, Topouchian JA, Asmar RG. Evaluation of two devices forself-measurement of blood pressure according to the internationalprotocol: the Omron M5-I and the Omron 705IT. Blood Press Monit 2003;8:127–133.
20 National High BP Education Program Working Group on High BloodPressure in Children and Adolescents. The fourth report on the diagnosis,evaluation, and treatment of high blood pressure in children andadolescents. Pediatrics 2004; 114 (2 Suppl 4th Report):S555–S576.
21 Kuczmarski RJ, Ogden CL, Grummer-Strawn LM, Flegal KM, Guo SS,Wei R, et al. CDC growth charts: United States. Adv Data 2000; 314:1–27.
22 Stettler N, Bovet P, Shamlaye H, Zemel BS, Stallings VA, Paccaud F.Prevalence and risk factors for overweight and obesity in children fromSeychelles, a country in rapid transition: the importance of early growth. IntJ Obes Relat Metab Disord 2002; 26:214–219.
23 Singh AS, Mulder C, Twisk JW, van Mechelen W, Chinapaw MJ. Trackingof childhood overweight into adulthood: a systematic review of theliterature. Obes Rev 2008; 9:474–488.
24 Keijzer-Veen MG, Euser AM, van Montfoort N, Dekker FW, VandenbrouckeJP, Van Houwelingen HC. A regression model with unexplained residualswas preferred in the analysis of the fetal origins of adult diseaseshypothesis. J Clin Epidemiol 2005; 58:1320–1324.
25 Adair LS, Cole TJ. Rapid child growth raises blood pressure in adolescentboys who were thin at birth. Hypertension 2003; 41:451–456.
26 Adair LS, Martorell R, Stein AD, Hallal PC, Sachdev HS, Prabhakaran D,et al. Size at birth, weight gain in infancy and childhood, and adult bloodpressure in 5 low- and middle-income-country cohorts: when does weightgain matter? Am J Clin Nutr 2009; 89:1383–1392.
27 Singhal A, Cole TJ, Lucas A. Early nutrition in preterm infants and later bloodpressure: two cohorts after randomised trials. Lancet 2001; 357:413–419.
28 Whincup PH, Bredow M, Payne F, Sadler S, Golding J. Size at birth andblood pressure at 3 years of age. The Avon Longitudinal Study ofPregnancy and Childhood (ALSPAC). Am J Epidemiol 1999; 149:730–739.
29 Blake KV, Gurrin LC, Evans SF, Beilin LJ, Stanley FJ, Landau LI, NewnhamJP. Adjustment for current weight and the relationship between birthweight and blood pressure in childhood. J Hypertens 2000; 18:1007–1012.
30 Jarvelin MR, Sovio U, King V, Lauren L, Xu B, McCarthy MI, et al. Early lifefactors and blood pressure at age 31 years in the 1966 northern Finlandbirth cohort. Hypertension 2004; 44:838–846.
31 Ekelund U, Ong KK, Linne Y, Neovius M, Brage S, Dunger DB, et al.Association of weight gain in infancy and early childhood withmetabolic risk in young adults. J Clin Endocrinol Metab 2007;92:98–103.
32 Victora CG, Adair L, Fall C, Hallal PC, Martorell R, Richter L, et al. Maternaland child undernutrition: consequences for adult health and human capital.Lancet 2008; 371:340–357.
orized reproduction of this article is prohibited.
Weight change and blood pressure in children Chiolero et al. 1879
33 Lawlor DA, Leon DA, Rasmussen F. Growth trajectory matters: interpretingthe associations among birth weight, concurrent body size, and systolicblood pressure in a cohort study of 378,707 Swedish men. Am J Epidemiol2007; 165:1405–1412.
34 Lambert M, O’Loughlin J, Delvin EE, Levy E, Chiolero A, Paradis G.Association between insulin, leptin, adiponectin and blood pressure inyouth. J Hypertens 2009; 27:1025–1032.
35 Kuller LH. Weight loss and reduction of blood pressure and hypertension.Hypertension 2009; 54:700–701.
36 Johnson RJ, Rodriguez-Iturbe B, Kang DH, Feig DI, Herrera-Acosta J. Aunifying pathway for essential hypertension. Am J Hypertens 2005;18:431–440.
Copyright © Lippincott Williams & Wilkins. Unaut
37 Sakuragi S, Abhayaratna K, Gravenmaker KJ, O’Reilly C, Srikusalanukul W,Budge MM, et al. Influence of adiposity and physical activity on arterialstiffness in healthy children: the lifestyle of our kids study. Hypertension2009; 53:611–616.
38 Lawlor DA, Benfield L, Logue J, Tilling K, Howe LD, Fraser A,et al. Association between general and central adiposity inchildhood, and change in these, with cardiovascular riskfactors in adolescence: prospective cohort study. BMJ 2010;341:c6224.
39 Gidding SS. Assembling evidence to justify prevention of atherosclerosisbeginning in youth. Circulation 2010; 122:2493–2494.
horized reproduction of this article is prohibited.