American Journal of Epidemiology
Copyright © 2002 by the Johns Hopkins Bloomberg School of Public Health
All rights reserved
Vol. 156, No. 2
Printed in U.S.A.
DOI: 10.1093/aje/kwf002
Familial Aggregation of Fetal Growth Restriction in a French Cohort of 7,822 Term Births
between 1971 and 1985
Agnès La Batide-Alanore1, David-Alexandre Trégouët1, Delphine Jaquet2, Jean Bouyer3, and
Laurence Tiret1
1
INSERM U525, Paris, France.
INSERM U457, Paris, France.
3 INSERM U292, Villejuif, France.
2
Received for publication November 5, 2001; accepted for publication March 14, 2002.
An association between fetal growth restriction and increased rates of metabolic and cardiovascular diseases
in adulthood has been reported. This study evaluated familial aggregation of fetal growth restriction in term births.
The population consisted of 3,505 sibships comprised of 7,822 full-term singleton infants born between 1971 and
1985 in Haguenau, France, and selected from a regional register of births. Sib-sib odds ratios were estimated for
being born small for gestational age (SGA), defined as having a birth weight below the 10th percentile of the sexspecific curve of birth weight by week of gestation. SGA births were further stratified according to ponderal index
(birth weight/length3). After adjustment for maternal factors, the sib-sib odds ratios were 4.8 (95% confidence
interval (CI): 3.7, 6.3) for all SGA births, 7.7 (95% CI: 4.1, 14.7) for SGA births with a low ponderal index (<10th
percentile), and 4.4 (95% CI: 2.3, 8.2) for SGA births with a normal ponderal index (25th–75th percentile). None
of the maternal factors investigated significantly influenced the magnitude of these odds ratios. This strong
residual sib-sib aggregation suggests a role for genetic and/or shared environmental factors in the etiology of fetal
growth restriction, especially when associated with a low ponderal index. Am J Epidemiol 2002;156:180–7.
birth weight; family; fetal growth retardation; gestational age
Abbreviations: CI, confidence interval; EE, estimating equation; IUGR, intrauterine growth restriction; OR, odds ratio; SGA,
small for gestational age.
While considerable progress has been made during the
past decades in reducing perinatal mortality and morbidity,
the report about 10 years ago by Barker et al. (1) of an association between low birth weight and increased rates of
cardiovascular and metabolic disorders in adulthood casts
new light on the problem of consequences of intrauterine
growth restriction (IUGR). Although this association has
been largely confirmed since then (2–10), no definitive
explanation has been proposed. Although Barker et al.
initially interpreted this association as the consequence of
intrauterine programming of the fetus in response to
maternal undernutrition (3), McCance et al. (4), 1 year later,
rather favored a genetic contribution. Despite a large quantity of literature during the past 10 years, the environmental
versus genetic hypothesis is still a matter of debate. Several
recent reports support the role of genetic factors in influ-
encing the association between IUGR and complications in
later life (11–13). It was recently proposed that IUGR and
metabolic complications in adult life might be due to phenotypes of the same insulin-resistant genotype (14).
The hypothesis of a genetic contribution common to fetal
growth restriction and adult complications would imply
familial recurrence of IUGR. In epidemiologic studies,
IUGR is generally defined as low birth weight for gestational
age. Several studies have shown a tendency in mothers to
give birth to small-for-gestational-age (SGA) babies in
successive pregnancies (15–18) and a higher risk of low
birth weight among infants born to mothers of low birth
weight themselves (18–21). While extrinsic maternal
factors, such as pregnancy-associated hypertension and
smoking, are now well-recognized risk factors for SGA
Correspondence to Laurence Tiret, INSERM U525, Faculté de Médecine, 91 Bd de l’Hôpital, 75634 Paris Cedex 13, France (e-mail:
[email protected]).
180
Familial Aggregation of Fetal Growth Restriction 181
births, the role of genetic factors in controlling in utero
growth is less well established.
Knowledge of the extent of familial aggregation of IUGR
is a preliminary step in trying to identify genetic factors. We
evaluated familial aggregation of SGA births in a large
population-based register of live infants born at term, before
and after we adjusted for maternal characteristics. Since,
besides birth weight, body proportions at birth have been
shown to influence the risk of adult disease (3, 6, 8, 10, 22),
we also took into account ponderal index to refine the
familial risk.
MATERIALS AND METHODS
The study population was selected from a populationbased register including more than 20,000 pregnancies
recorded between 1971 and 1985 in the metropolitan area of
the city of Haguenau, France (23). The ascertainment rate of
the register was greater than 80 percent. For the present
study, the sample was restricted to European, singleton livebirths without evidence of intrauterine infection, chromosomal abnormalities, or other major malformations. To
exclude the effect of prematurity, only those infants born
after 37–42 weeks of gestation were selected. Since the study
focused on familial aggregation of SGA births, the sample
was restricted to infants belonging to sibships with at least
two siblings, linked by the mother’s identification number in
the register. The study sample included 7,822 siblings
belonging to 3,505 sibships.
Since growth standards for the population of Haguenau
were different from those for France in general because of
the large number of Germanic people living in the city, SGA
births were defined by using local standards for birth weight
derived from all livebirths over the 15-year period covered
by the register. Gestational age was determined from the date
of the mother’s last menstrual period and by physical examination during pregnancy, and it was confirmed by ultrasound measurements when available. Being SGA was
defined as having a birth weight below the 10th percentile of
the sex-specific curve of birth weight by week of gestation.
Ponderal index was calculated as birth weight/length3;
percentiles of ponderal index by week of gestation were
derived from all singleton livebirths recorded in the register.
Subgroups of SGA births with a low ponderal index (<10th
percentile) and a normal ponderal index (25th–75th percentiles) were defined further.
Maternal characteristics were recorded by using a standardized questionnaire. Data were taken from the medical
follow-up records of pregnancy, and mothers were identified
by a register number linking their different pregnancies. The
database did not include any personal identifier. Height and
educational level (university vs. others) were recorded at the
first pregnancy and were assumed to remain constant over
time. Maternal age was recorded at each delivery. Prepregnancy weight, cigarette smoking (yes or no) during pregnancy, marital status (unmarried or married), primiparity
(yes or no), and hypertension were defined for each pregnancy. Pregnancy-associated hypertension was defined as a
systolic/diastolic blood pressure of more than 140/90 mmHg
Am J Epidemiol
Vol. 156, No. 2, 2002
or by the use of an antihypertensive treatment during pregnancy.
Statistical analysis was performed by using SAS software
(SAS Institute, Inc., Cary, North Carolina). Since persons
within families are statistically not independent, conventional statistical methods could not be used; therefore, linear
regression analyses were performed by using the estimating
equation (EE) technique as implemented in the
SAS/GENMOD procedure. Familial aggregation of SGA
births was expressed in terms of odds ratios. The sib-sib odds
ratio was defined as the odds of a child being born SGA
given that his or her sibling was born SGA, divided by the
odds of a child being born SGA given that his or her sibling
was not born SGA. Sib-sib odds ratios were estimated by
using the EE technique extended to estimation of correlation
parameters (24), referred to as EE2. The EE2 approach estimates marginal odds ratios (eventually adjusted for relevant
factors) and their standard errors, estimations robust to a
misspecification of the dependency between the different
pairs of relatives in the same family. As is common in EE2
analysis, the dependencies between marginal odds ratios
were modeled by using a Gaussian correlation structure (25).
Because the marginal probability of being born SGA was
different between the firstborn child and subsequent siblings
and the odds ratios assume symmetry between siblings of the
pair, crude odds ratios were systematically adjusted for
primiparity. Odds ratios were further adjusted for maternal
covariates and were additionally adjusted for study period to
control for potential secular trends. For this purpose, the 15year study period was divided into three 5-year periods. For
analyses stratified according to low/normal ponderal index,
the reference group was composed of non-SGA newborns
whose ponderal index was normal (25th–75th percentile).
All EE2 analyses were performed by using a binary version
of the EE2 program developed by our group, described
previously (26, 27). Tests of hypothesis were conducted by
use of generalized Wald test statistics. A p value of 0.05 was
considered significant.
RESULTS
According to the definition adopted, 751 siblings (9.6
percent) were born SGA, of whom 231 (30.8 percent) had a
normal ponderal index (25th–75th percentile of the whole
population) and 299 (39.8 percent) had a low ponderal index
(<10th percentile of the whole population). Sibships that
included a single sibling born SGA accounted for 13.6
percent of the 3,505 sibships, and those that included at least
two siblings born SGA accounted for 3.6 percent (table 1).
The prevalence of SGA births decreased over time, but this
decrease was observed for multiparous mothers only,
whereas the prevalence remained constant over time for
primiparous mothers (table 2). The proportion of SGA births
in which the ponderal index was low or normal did not vary
significantly across the three study periods (table 2). Almost
all maternal characteristics changed over time (table 2).
However, at least for some variables, this change was mainly
the consequence of the selection scheme restricting the
sample to sibships with several siblings. This selection
implied that primiparous women who gave birth to no subse-
182 La Batide-Alanore et al.
TABLE 1. Distribution of sibships according to size and number of siblings being born small
for gestational age, Haguenau, France, 1971–1985
No. of sibships with k siblings being born SGA*
Sibship size
No. of sibships
k=0
k=1
k=2
k=3
k=4
2
2,811
2,355
368
88
3
597
478
88
19
12
4
81
57
18
3
1
2
5
11
7
3
0
1
0
6
5
3
1
0
1
0
3,505
2,900
478
110
15
2
Total
* SGA, small for gestational age.
TABLE 2. Prevalence of small-for-gestational-age births and maternal characteristics according to study period, Haguenau,
France, 1971–1985†
1971–1975
(n = 2,181)
1976–1980
(n = 2,956)
1981–1985
(n = 2,685)
p value
Prevalence of SGA‡ births
11.1
9.9
8.1
In primiparous mothers
12.2
10.3
11.2
In multiparous mothers
9.9
9.6
7.5
With a low ponderal index
43.2
38.2
38.2
NS
With a normal ponderal index
29.0
32.1
30.9
NS
**
NS‡
*
Percentage of SGA births
Maternal characteristics
Prepregnancy weight (kg)
Height (cm)
Age at delivery (years)
Unmarried
57.8 (0.3)
58.1 (0.2)
59.0 (0.3)
**
161.7 (0.2)
162.2 (0.1)
162.1 (0.1)
NS
23.9 (0.1)
25.0 (0.1)
29.0 (0.1)
**
7.0
6.9
7.2
NS
Primiparous
50.1
42.7
14.9
**
Smoker
10.7
16.8
19.2
**
Hypertension
19.5
14.2
8.5
**
4.6
8.8
8.6
**
High educational level
* p < 0.05; ** p < 0.001.
† Values are expressed as mean (standard error) or percentage; estimation and hypothesis testing were performed by using the
estimating equation technique.
‡ SGA, small for gestational age; NS, nonsignificant.
quent child during the study period were excluded from the
study sample (which explained the decrease in primiparity
over time) and that the same mothers could be surveyed at
different time periods for consecutive pregnancies
(explaining the increase in mothers’ age and weight). In
contrast, the decreasing prevalence of pregnancy-associated
hypertension and the increasing proportion of mothers who
smoked reflected true secular trends.
As expected, children born SGA were smaller regarding
all body measures than children born non-SGA (table 3).
Mothers in the SGA group weighed less and had a shorter
stature than mothers in the non-SGA group and were more
often unmarried, primiparous, and smokers (table 3). Educa-
tional level and hypertension were not significantly associated with SGA status. All variables associated with SGA
status in univariate analyses remained significant in multivariate analysis.
We further subdivided the SGA and non-SGA groups
according to the number of other SGA siblings in the sibship
that included the newborn under consideration (table 3). For
almost all variables, there was a marked trend indicating that
maternal risk factors and sibling characteristics became less
favorable as the number of SGA siblings increased. In particular, the proportion of mothers who smoked during pregnancy reached 41 percent in the group with multiple SGA
siblings compared with 14 percent in the group with no SGA
Am J Epidemiol
Vol. 156, No. 2, 2002
Familial Aggregation of Fetal Growth Restriction 183
TABLE 3. Comparison of maternal and child’s characteristics for children born small for gestational age and not small for
gestational age, Haguenau, France, 1971–1985†
All
Children born
non-SGA‡
(n = 7,071)
Children born non-SGA
Children born
SGA
(n = 751)
p
value
No SGA
sibling
(n = 6,425)
≥1 SGA
sibling
(n = 646)
Children born SGA
p
value
No SGA
sibling
(n = 478)
≥1 SGA
sibling
(n = 273)
p
value
Maternal characteristics
58.8 (0.2)
53.9 (0.3)
***
59.1 (0.1)
56.4 (0.5)
***
55.1 (0.4)
51.7 (0.6)
Height (cm)
Prepregnancy weight (kg)
162.2 (0.1)
160.1 (0.3)
***
162.4 (0.1)
160.6 (0.3)
***
160.6 (0.3)
159.2 (0.5)
*
Age (years)
25.4 (0.1)
25.1 (0.2)
NS‡
25.3 (0.1)
25.7 (0.2)
NS
24.9 (0.2)
25.4 (0.4)
NS
Unmarried
***
6.2
15.3
***
5.8
10.1
**
11.1
22.7
**
Primiparous
34.5
41.0
***
35.5
25.9
***
46.4
31.5
***
Smoker
14.7
28.0
***
13.9
21.8
***
20.3
41.4
***
Hypertension
13.7
13.4
NS
13.8
13.3
NS
16.1
8.8
**
7.8
6.0
NS
7.9
6.4
NS
6.3
5.5
NS
High educational level
Gestational age (weeks)
39.5 (0.0)
39.5 (0.1)
NS
39.5 (0.0)
39.2 (0.1)
**
39.5 (0.1)
39.3 (0.1)
NS
Child’s characteristics
Birth weight (g)
(6.1)
2,678 (12.0)
***
(6.4)
3,253 (15.4)
***
2,707 (12.8)
2,629 (23.3)
**
Birth length (cm)
3,474
50.6 (0.0)
47.9 (0.1)
***
3,497
50.7 (0.0)
49.9 (0.1)
***
48.1 (0.1)
47.5 (0.2)
**
Cranial perimeter (cm)
34.7 (0.0)
33.2 (0.1)
***
34.8 (0.0)
34.4 (0.1)
***
33.3 (0.1)
33.1 (0.1)
*
Thorax perimeter (cm)
33.8 (0.0)
31.3 (0.1)
***
33.9 (0.0)
33.1 (0.1)
***
31.4 (0.1)
31.1 (0.1)
*
Ponderal index (kg/m3)
26.7(0.0)
24.5 (0.1)
***
26.8 (0.6)
26.1 (0.1)
***
24.5 (0.2)
24.5 (0.2)
NS
* p < 0.05; ** p < 0.01; *** p < 0.001.
† Values are expressed as mean (standard error) or percentage; estimation and hypothesis testing were performed by using the estimating
equation technique.
‡ SGA, small for gestational age; NS, nonsignificant.
sibling, reflecting the strong impact of this factor on the
recurrence of IUGR. In the SGA group, the prevalence of
pregnancy-associated hypertension increased when the child
born SGA was the only one in the sibship. Since, in most
instances, he or she was the firstborn child, this finding
reflected the strong role of hypertension in the etiology of
IUGR in primiparous mothers.
Compared with children who had a normal ponderal index,
those born SGA and having a low ponderal index were characterized by a lower birth weight and a smaller thorax perimeter but a longer length (table 4). The maternal
characteristics most strongly associated with a low ponderal
index were primiparity and pregnancy-associated hypertension. On the other hand, mothers who smoked during pregnancy had small babies whose ponderal index was normal
(table 4). The mean ponderal index was 23.4 (standard deviation, 2.5) kg/m3 for SGA infants whose mothers were
hypertensive versus 24.7 (standard deviation, 2.3) kg/m3 for
those whose mothers smoked during pregnancy (p < 0.001).
We found a strong familial aggregation of SGA births, as
indicated by the odds ratios estimated for the 3,505 sibships
(table 5). The crude odds ratio for being born SGA was 6.6
(95 percent confidence interval (CI): 5.1, 8.6) and decreased
only slightly to 4.8 (95 percent CI: 3.7, 6.3) after adjustment
for maternal covariates and study period. Stratification
according to ponderal index appeared to only strengthen the
familial resemblance. The crude odds ratio for being born
Am J Epidemiol
Vol. 156, No. 2, 2002
SGA and having a low ponderal index was 8.0 (95 percent
CI: 4.5, 14.1), while the crude odds ratio for being born SGA
and having a normal ponderal index was 10.1 (95 percent CI:
4.9, 20.7). After adjustment for maternal factors and study
period, the odds ratio for being born SGA and having a low
ponderal index remained nearly unchanged, whereas the
odds ratio for being born SGA and having a normal ponderal
index decreased strongly (table 5). This result indicated that
the risk of recurrence of SGA births associated with a normal
ponderal index was influenced more strongly by maternal
factors than that of SGA births associated with a low
ponderal index. When we examined the impact of each
factor separately, smoking seemed to have the strongest
influence on the familial aggregation of SGA births in which
ponderal index was normal.
We further examined whether some factors might influence the degree of sib-sib aggregation (table 6). Neither the
delay between two consecutive pregnancies nor maternal
characteristics significantly modified the sib-sib odds ratio.
The only-borderline differences suggested that there was
less of a resemblance between the firstborn child and any
subsequent sibling than between two subsequent siblings
(odds ratio (OR) = 4.2 vs. OR = 6.0, p < 0.10) and that the
clustering was stronger in pairs in which the mother smoked
than in pairs in which the mother did not smoke (OR = 9.9
vs. OR = 4.0, p < 0.10).
184 La Batide-Alanore et al.
TABLE 4. Comparison of maternal and child’s characteristics for children born small for gestational age
and having a low or a normal ponderal index, Haguenau, France, 1971–1985†
Children born SGA,‡
ponderal index normal
(n = 231)
Children born SGA,
ponderal index low
(n = 299)
p value
Maternal characteristics
Prepregnancy weight (kg)
53.4 (0.6)
53.9 (0.5)
NS‡
Height (cm)
159.3 (0.5)
160.2 (0.3)
NS
Age (years)
25.0 (0.3)
24.8 (0.3)
NS
Unmarried
16.0
14.4
NS
Primiparous
34.2
49.2
**
Smoker
35.1
20.7
**
Hypertension
8.7
17.7
*
High educational level
7.6
5.3
NS
Gestational age (weeks)
39.6 (0.1)
39.5 (0.1)
NS
**
Child’s characteristics
Birth weight (g)
2,754 (16.1)
2,636 (18.6)
Birth length (cm)
47.2 (0.1)
49.0 (0.1)
**
Cranial perimeter (cm)
33.3 (0.1)
33.2 (0.1)
NS
Thorax perimeter (cm)
31.5 (0.1)
31.1 (0.1)
*
Ponderal index (kg/m3)
26.2 (0.1)
22.3 (0.1)
**
* p < 0.01; ** p < 0.001.
† Values are expressed as mean (standard error) or percentage; estimation and hypothesis testing were
performed by using the estimating equation technique.
‡ SGA, small for gestational age; NS, nonsignificant.
TABLE 5. Sib-sib odds ratios for being born small for gestational age, before and after adjustment for
maternal characteristics and according to ponderal index, Haguenau, France, 1971–1985
No. of sibships
All SGA* births
SGA births, normal
ponderal index
SGA births, low
ponderal index
3,505
1,042
1,070
167
26
28
No. of pairs†
Concordant for SGA
Discordant for SGA
683
107
129
4,423
1,152
1,152
Crude‡ (95% CI*)
6.61 (5.11, 8.56)
10.06 (4.90, 20.67)
7.98 (4.51, 14.12)
Adjusted§ (95% CI)
4.79 (3.65, 6.29)
4.35 (2.31, 8.19)
7.74 (4.08, 14.69)
Concordant for non-SGA
Sib-sib odds ratio
* SGA, small for gestational age, CI, confidence interval.
† The total number of pairs was higher than the number of sibships because sibships with more than two siblings
include more than one pair.
‡ The crude odds ratio was adjusted for primiparity only.
§ Maternal covariates were age at delivery, height, prepregnancy weight, marital status, primiparity, smoking,
and hypertension; odds ratios were additionally adjusted for study period.
Am J Epidemiol
Vol. 156, No. 2, 2002
Familial Aggregation of Fetal Growth Restriction 185
TABLE 6. Sib-sib odds ratios* for being born small for gestational age, according to different
factors, Haguenau, France, 1971–1985
Adjusted odds ratio†
95% confidence interval
Delay between two consecutive pregnancies
≤18 months
5.22
2.42, 11.26
>18 months
4.77
3.53, 6.44
Pairs including a firstborn child
Yes
4.21
3.11, 5.69
No
6.00
3.77, 9.56
Mother’s height
≤160 cm
3.94
2.77, 5.61
>160 cm
5.94
3.78, 9.35
≤55 kg
4.84
3.41, 6.86
>55 kg
4.72
2.88, 7.75
Married
4.55
3.36, 6.16
Unmarried
6.22
2.45, 15.7
Mother’s weight before the first pregnancy
Mother’s marital status‡
Mother’s educational level
Low
4.35
3.20, 5.92
High
5.80
1.15, 29.21
Mother’s smoking status‡
Nonsmoker
4.00
2.90, 5.52
Smoker
9.92
4.03, 24.41
* None of the p values was significant regarding homogeneity of the odds ratios.
† Maternal covariates were age at delivery, height, prepregnancy weight, marital status, primiparity,
smoking, and hypertension; odds ratios were additionally adjusted for study period.
‡ A few pairs for which this factor was different between the two pregnancies of the pair were excluded
from comparison.
Because smoking and hypertension are two major
extrinsic risk factors for SGA births, we reestimated the odds
ratios after exclusion of all pregnancies in which the mother
was either a smoker or hypertensive. In the remaining 2,194
sibships, the adjusted sib-sib odds ratio for being born SGA
was hardly modified compared with the initial value (OR =
4.6, 95 percent CI: 3.2, 6.6).
Finally, we estimated the sib-sib odds ratio when considering a more stringent definition of the SGA status by taking
into account a birth weight below the 5th percentile instead
of the 10th percentile. The crude odds ratio was 8.0 (95
percent CI: 5.4, 11.7), but, after adjustment for maternal
covariates and study period, it decreased to 4.9 (95 percent
CI: 3.2, 7.4), a value close to that obtained when the 10th
percentile was considered.
DISCUSSION
Our study provided an estimation of the familial aggregation of SGA births, further stratified according to body
proportionality, a factor shown to influence the risk of later
complications (3, 6, 8, 10, 22). Restriction of the study population to term births enabled us to rule out any confounding
Am J Epidemiol
Vol. 156, No. 2, 2002
effect of prematurity itself or prematurity-associated
morbidity. Major maternal factors influencing the risk of
SGA birth were height and weight, primiparity, smoking,
and unmarried status, as reported previously (28). Pregnancy-associated hypertension was not associated with
outcome in our population when we considered SGA births
as a whole. However, it was more frequent in primiparous
women, as already known (29), and it significantly distinguished the groups of proportionally (normal ponderal
index) and disproportionally (low ponderal index) SGA
births, being more frequent in the latter group of infants.
This result is in agreement with the fact that women with
pregnancy-related hypertension tend to have thinner infants
(28). The lack of association between hypertension and the
risk of SGA birth in the population as a whole might be
explained by the broad definition of hypertension we used in
this study, since fetal growth has been shown to be impaired
mostly by severe and early-onset pregnancy-induced hypertension (28, 30). Another reason might be that our study,
restricted to term births, did not focus on the most severe
forms of fetal growth restriction. Unfortunately, we could
not adjust our analyses for paternal factors because data were
missing for a large fraction of fathers. However, it has been
186 La Batide-Alanore et al.
shown that, after adjustment for maternal characteristics,
only paternal education and race significantly influence the
risk of low birth weight (31). Since our study was restricted
to a European population and we took into account maternal
education, which strongly correlates to paternal education,
we might expect that paternal factors would have only a
slight impact on our results.
Our findings indicate a strong familial aggregation of
IUGR. This aggregation was of a similar magnitude whether
we used the 10th percentile of birth weight to define IUGR,
therefore including a fraction of “almost normal” babies, or
a more stringent criterion, that is, a birth weight below the
5th percentile. Whatever the threshold used, after adjustment
for maternal factors, we found that a child’s risk of being
born SGA was more than fourfold higher when his or her
sibling was born SGA than when his or her sibling was not
born SGA. Moreover, subsequent siblings tended to have an
even higher risk when the child born SGA was not the firstborn of the sibship, although the difference did not reach
statistical significance because of a small number of pairs.
Indeed, the relative risk (approximating the odds ratio) of
being born SGA conditional on the status of that child’s
sibling reached 6.0 when the sibling born SGA was not the
firstborn; this value compared with 4.2 when the sibling born
SGA was the firstborn (table 6). This finding is important
from both a clinical and public health perspective, since it
implies that mothers who deliver a non-firstborn SGA baby
are at particularly high risk of giving birth to another SGA
child.
Our results are in accordance with previous studies
reporting a tendency to repeat SGA births in successive
pregnancies (15–18) and more generally with studies
showing a high familial correlation of birth weight (32, 33).
Familial aggregation of SGA births may be attributable to
genetic and/or shared environmental factors. However,
although adjustment for measurable maternal risk factors
cannot entirely control for a shared maternal environmental
influence, in particular an in utero influence (34), the strong
residual sib-sib aggregation suggests a role of genetic factors
in the etiology of IUGR. A possible role of genetic factors is
supported by several studies showing an association of low
infant birth weight with low maternal birth weight (18–21)
and, most important, with low paternal birth weight (35).
Unfortunately, information on paternal and maternal birth
weights was not available in the present study.
Interestingly, familial aggregation appeared to strengthen
when we stratified SGA births according to ponderal index,
suggesting that proportional and disproportional IUGR have
different etiologies. In support of this hypothesis, the sib-sib
odds ratio for proportionally SGA births decreased from
10.1 to 4.4 after adjustment for maternal characteristics,
indicating a strong impact of maternal factors, especially
smoking, on the risk of familial recurrence of this type of
fetal growth restriction. In contrast, for disproportionally
SGA births (accounting for 40 percent of all SGA births), the
sib-sib odds ratio was hardly modified after adjustment and
remained higher than 7.0, suggesting that, unlike proportionally SGA births, extrinsic maternal factors had little influence on this type of growth restriction. Disproportional
IUGR reflects a more important growth restriction in terms
of weight than height and is recognized as an indicator of the
severity of IUGR (36). This pattern of fetal growth restriction has been shown to predispose to insulin resistance and
to metabolic and cardiovascular diseases in adulthood (3, 6,
8, 10, 22). The strong familial clustering suggests that
common genetic factors might predispose to both impaired
fetal growth and adult disease. As proposed in the “fetal
insulin hypothesis” (14), fetal thinness and insulin resistance
might be two manifestations of the same insulin-resistant
genotype. This hypothesis is supported by the fact that
insulin secreted by the fetal pancreas in response to maternal
glucose concentrations is a key growth factor. The insulinresistant genotype might involve genes encoding for
angiogenic factors, metabolic factors, or growth factors.
One limitation of our study is that it relied on data
collected between 1971 and 1985, a time when ultrasound
examinations were not yet widely used; therefore, we had to
use birth weight as a surrogate variable for defining IUGR.
However, note that most of the epidemiologic studies
showing that IUGR is associated with morbid consequences
in adulthood have used birth weight to define IUGR (6, 8,
10). Another point deserving discussion is that, because of
improvements in the medical supervision of pregnancy, the
incidence of IUGR has decreased during the last few
decades. However, while factors such as smoking and hypertension can easily be modified by prevention, it is likely that
the fraction of IUGR cases due to genetic factors has
changed less.
A better characterization of the genetic determinants of
IUGR is of primary importance given its long-term consequences regarding metabolic and cardiovascular complications. It was recently shown that the risk of diabetes
associated with low birth weight in the offspring was
strongly related to the development of paternal diabetes,
suggesting a genetic link between low birth weight and
diabetes later in life (13). Similarly, the VNTR polymorphism of the insulin gene has been shown to be associated
with both birth weight and type 2 diabetes (12, 37). In
contrast, a polymorphism of the angiotensin-converting
enzyme gene was reported to be associated with insulin
response to a glucose load in young adults born SGA, but it
was not associated with SGA status itself (11). We are
currently performing a follow-up study of subjects born
SGA, as noted in the Haguenau register; this prospective
study should enable us to investigate the hypothesis of a
common genetic basis to IUGR and its later complications.
ACKNOWLEDGMENTS
The authors thank Professors P. Lazar and E. Papiernick
for initiating this study.
REFERENCES
1. Barker DJ, Osmond C, Golding J, et al. Growth in utero, blood
pressure in childhood and adult life, and mortality from cardiovascular disease. BMJ 1989;298:564–7.
Am J Epidemiol
Vol. 156, No. 2, 2002
Familial Aggregation of Fetal Growth Restriction 187
2. Hales CN, Barker DJ, Clark PM, et al. Fetal and infant growth
and impaired glucose tolerance at age 64. BMJ 1991;303:1019–
22.
3. Barker DJ, Hales CN, Fall CH, et al. Type 2 (non-insulindependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth.
Diabetologia 1993;36:62–7.
4. McCance DR, Pettitt DJ, Hanson RL, et al. Birth weight and
non-insulin dependent diabetes: thrifty genotype, thrifty phenotype, or surviving small baby genotype? BMJ 1994;308:942–5.
5. Valdez R, Athens MA, Thompson GH, et al. Birthweight and
adult health outcomes in a biethnic population in the USA. Diabetologia 1994;37:624–31.
6. Lithell HO, McKeigue PM, Berglund L, et al. Relation of size
at birth to non-insulin dependent diabetes and insulin concentrations in men aged 50–60 years. BMJ 1996;312:406–10.
7. Leger J, Levy-Marchal C, Bloch J, et al. Reduced final height
and indications for insulin resistance in 20 year olds born small
for gestational age: regional cohort study. BMJ 1997;315:341–
7.
8. Leon DA, Lithell HO, Vagero D, et al. Reduced fetal growth
rate and increased risk of death from ischaemic heart disease:
cohort study of 15 000 Swedish men and women born 1915–29.
BMJ 1998;317:241–5.
9. Leeson CP, Kattenhorn M, Morley R, et al. Impact of low birth
weight and cardiovascular risk factors on endothelial function
in early adult life. Circulation 2001;103:1264–8.
10. Eriksson JG, Forsen T, Tuomilehto J, et al. Early growth and
coronary heart disease in later life: longitudinal study. BMJ
2001;322:949–53.
11. Cambien F, Leger J, Mallet C, et al. Angiotensin I-converting
enzyme gene polymorphism modulates the consequences of in
utero growth retardation on plasma insulin in young adults.
Diabetes 1998;47:470–5.
12. Ong KK, Phillips DI, Fall C, et al. The insulin gene VNTR, type
2 diabetes and birth weight. Nat Genet 1999;21:262–3.
13. Lindsay RS, Dabelea D, Roumain J, et al. Type 2 diabetes and
low birth weight: the role of paternal inheritance in the association of low birth weight and diabetes. Diabetes 2000;49:445–9.
14. Hattersley AT, Tooke JE. The fetal insulin hypothesis: an alternative explanation of the association of low birthweight with
diabetes and vascular disease. Lancet 1999;353:1789–92.
15. Scott A, Moar V, Ounsted M. The relative contributions of different maternal factors in small-for-gestational-age pregnancies. Eur J Obstet Gynecol Reprod Biol 1981;12:157–65.
16. Bakketeig LS, Hoffman HJ. The tendency to repeat gestational
age and birth weight in successive births, related to perinatal
survival. Acta Obstet Gynecol Scand 1983;62:385–92.
17. Wolfe HM, Gross TL, Sokol RJ. Recurrent small for gestational
age birth: perinatal risks and outcomes. Am J Obstet Gynecol
1987;157:288–93.
18. Wang X, Zuckerman B, Coffman GA, et al. Familial aggregation of low birth weight among whites and blacks in the United
States. N Engl J Med 1995;333:1744–9.
Am J Epidemiol
Vol. 156, No. 2, 2002
19. Hackman E, Emanuel I, van Belle G, et al. Maternal birth
weight and subsequent pregnancy outcome. JAMA 1983;250:
2016–19.
20. Klebanoff MA, Graubard BI, Kessel SS, et al. Low birth weight
across generations. JAMA 1984;252:2423–7.
21. Klebanoff MA, Yip R. Influence of maternal birth weight on
rate of fetal growth and duration of gestation. J Pediatr
1987;111:287–92.
22. Barker DJ, Osmond C, Simmonds SJ, et al. The relation of
small head circumference and thinness at birth to death from
cardiovascular disease in adult life. BMJ 1993;306:422–6.
23. Papiernik E, Bouyer J, Dreyfus J, et al. Prevention of preterm
births: a perinatal study in Haguenau, France. Pediatrics 1985;
76:154–8.
24. Liang KY, Beaty TH. Measuring familial aggregation by using
odds-ratio regression models. Genet Epidemiol 1991;8:361–70.
25. Trégouët D, Tiret L. Applications of the estimating equations
theory to genetic epidemiology: a review. Ann Hum Genet
2000;64:1–14.
26. Trégouët DA, Herbeth B, Juhan-Vague I, et al. Bivariate familial correlation analysis of quantitative traits by use of estimating equations: application to a familial analysis of the insulin
resistance syndrome. Genet Epidemiol 1999;16:69–83.
27. Plancoulaine S, Abel L, van Beveren M, et al. Human herpesvirus 8 transmission from mother to child and between siblings in
an endemic population. Lancet 2000;356:1062–5.
28. Kramer MS, Olivier M, McLean FH, et al. Determinants of
fetal growth and body proportionality. Pediatrics 1990;86:18–
26.
29. Eskenazi B, Fenster L, Sidney S. A multivariate analysis of risk
factors for preeclampsia. JAMA 1991;266:237–41.
30. Odegard RA, Vatten LJ, Nilsen ST, et al. Preeclampsia and
fetal growth. Obstet Gynecol 2000;96:950–5.
31. Parker JD, Schoendorf KC. Influence of paternal characteristics
on the risk of low birth weight. Am J Epidemiol 1992;136:399–
407.
32. Beaty TH, Yang P, Munoz A, et al. Effect of maternal and
infant covariates on sibship correlation in birth weight. Genet
Epidemiol 1988;5:241–53.
33. Beaty TH, Skjaerven R, Breazeale DR, et al. Analyzing sibship
correlations in birth weight using large sibships from Norway.
Genet Epidemiol 1997;14:423–33.
34. Ounsted M, Scott A, Ounsted C. Transmission through the
female line of a mechanism constraining human fetal growth.
Ann Hum Biol 1986;13:143–51.
35. Magnus P, Bakketeig LS, Hoffman H. Birth weight of relatives
by maternal tendency to repeat small-for-gestational-age
(SGA) births in successive pregnancies. Acta Obstet Gynecol
Scand Suppl 1997;165:35–8.
36. Kramer M, McLean F, Olivier M, et al. Body proportionality
and head and length ‘sparing’ in growth-retarded neonates: a
critical reappraisal. Pediatrics 1989;84:717–23.
37. Dunger DB, Ong KK, Huxtable SJ, et al. Association of the INS
VNTR with size at birth. ALSPAC Study Team. Avon Longitudinal Study of Pregnancy and Childhood. Nat Genet 1998;
19:98–100.