Correlation Between Birth Weight and
Maternal Body Composition
Etaoin Kent, MRCOG, MRCPI, Vicky O’Dwyer, MRCPI, Chro Fattah,
Clare O’Connor, MRCPI, and Michael J. Turner, FRCOG, FRCPI
OBJECTIVE: To estimate which maternal body composition parameters measured using multifrequency segmental bioelectric impedance analysis in the first
trimester of pregnancy are predictors of increased birth
weight.
METHODS: Nondiabetic women were recruited after
ultrasonographic confirmation of an ongoing singleton
pregnancy in the first trimester. Maternal body composition was measured using bioelectric impedance analysis.
Multivariable linear regression analysis was performed to
identify the strongest predictors of birth weight, with
multiple logistic regression analysis performed to assess
predictors of birth weight greater than 4 kg.
RESULTS: Data were analyzed for 2,618 women, of
whom 49.6% (n51,075) were primigravid and 16.5%
(n5432) were obese based on a body mass index (BMI)
of 30 or higher. In univariable analysis, maternal age,
BMI, parity, gestational age at delivery, smoking, fat mass,
and fat-free mass all correlated significantly with birth
weight. In multivariable regression analysis, fat-free mass
remained a significant predictor of birth weight (model
R250.254, standardized b50.237; P,.001), but no relationship was found between maternal fat mass and birth
weight. After adjustment for confounding variables,
women in the highest fat-free mass quartile had an
adjusted odds ratio of 3.64 (95% confidence interval
2.34–5.68) for a birth weight more than 4 kg compared
with those in the lowest quartile.
CONCLUSIONS: Based on direct measurements of body
composition, birth weight correlated positively with
From the UCD Centre for Human Reproduction, Coombe Women and Infants
University Hospital, Dublin, Ireland.
Corresponding author: Dr. Etaoin Kent, MRCOG, MRCPI, UCD Centre for
Human Reproduction, Coombe Women and Infants University Hospital, Dublin
8, Ireland; e-mail: [email protected].
Financial Disclosure
The authors did not report any potential conflicts of interest.
© 2012 by The American College of Obstetricians and Gynecologists. Published
by Lippincott Williams & Wilkins.
ISSN: 0029-7844/13
46
VOL. 121, NO. 1, JANUARY 2013
MD,
Nadine Farah,
MD,
maternal fat-free mass and not adiposity. These findings
suggest that, in nondiabetic women, interventions
intended to reduce fat mass during pregnancy may not
prevent large-for-gestational-age neonates and revised
guidelines for gestational weight gain in obese women
may not prevent large-for-gestational-age neonates.
(Obstet Gynecol 2013;121:46–50)
DOI: http://10.1097/AOG.0b013e31827a0052
LEVEL OF EVIDENCE: III
B
irth weight is an important obstetric outcome. Both
low and high birth weight are associated with
increased obstetric and neonatal complications in the
short-term, and with an increased risk of cardiovascular
disease and metabolic syndrome later in life.1,2
Epidemiologic studies have linked birth weight
with the mother’s body composition with maternal
obesity reportedly associated with an increased risk
of fetal macrosomia and neonatal adiposity.2,3 In
a report from the Institute of Medicine, gestational
weight gain was associated with both restricted and
excessive intrauterine fetal growth.4 Concerns about
the affect of rising levels of maternal obesity on intrauterine fetal growth led the Institute in 2009 to publish
revised guidelines recommending lower levels of gestational weight gain for obese women.5
However, the evidence linking maternal obesity
and birth weight is problematic. Maternal obesity is
usually classified on the basis of a body mass index
(BMI, calculated as weight (kg)/[height (m)]2) of 30 or
higher. Most epidemiologic studies are retrospective
and based on self-reporting of weight and height to
calculate BMI, which under-reports obesity levels and
often lead to BMI miscategorization.6–8 Furthermore,
BMI does not measure fat directly but acts as a surrogate marker of adiposity.
Fat mass and fat-free mass in adults can be
measured directly using bioelectric impedance analysis, which is a safe, noninvasive, and convenient
method to determine body composition.9–12 Recent
OBSTETRICS & GYNECOLOGY
technical advances with eight-electrode multifrequency
bioelectric impedance analysis (multifrequency bioelectric impedance analysis) mean that bioelectric
impedance analysis can be applied in large numbers
of patients to analyze body composition and also to
analyze the distribution of fat and fat-free mass without
recourse to the supine position.10–12 We have demonstrated previously that in early pregnancy the use of
multifrequency bioelectric impedance analysis is feasible and reproducible, and that it correlates strongly
with clinical and endocrine markers of maternal adiposity.11,12 The purpose of this prospective observational study was to estimate whether maternal fat
mass measured in the first trimester correlated better
with birth weight than did fat-free mass, and to identify
which maternal body composition parameters correlated best with birth weight.
PATIENTS AND METHODS
The study was performed prospectively between July
2008 and December 2011, in a large university
teaching hospital. The study was approved by the
Ethics Committee of the Coombe Women and Infants
University Hospital and all participants gave written
informed consent. It is hospital policy to offer a dating
ultrasound scan to all women in early pregnancy.
Women were recruited after ultrasonographic confirmation of a viable, singleton pregnancy in the first
trimester. To avoid ethnic confounding variables, the
study was confined to Caucasian women. Women
who were younger than age 18 years or who were
unable to give informed consent were excluded.
Women were also excluded if they had pre-existing
diabetes mellitus.
Height was measured using a wall-mounted digital
meter stick to the nearest 0.1 cm with the woman
standing erect in her bare feet. Weight was measured
digitally to the nearest 0.1 kg with the woman in light
clothing. An allowance of 0.5 kg was made for clothing
and the BMI was calculated. Bioelectric impedance
analysis was performed using the Tanita MF-180CA
with the woman in her bare feet and wearing light
clothing. Segmental bioelectric impedance analysis of
the trunk and individual limbs, along with whole-body
analysis, were performed on each patient.
Clinical and sociodemographic details were
recorded and the women were discharged back to
their own obstetric team for the management of the
pregnancy and delivery. The hospital has a policy of
selective and not universal screening for gestational
diabetes mellitus.13 The antenatal and delivery details
were obtained postpartum from the hospital’s computerized database.
VOL. 121, NO. 1, JANUARY 2013
To identify predictors of birth weight, univariable
correlations of birth weight with maternal demographic, anthropometric, and clinical variables, bioelectric impedance analysis measures of fat mass and
fat-free mass, and gestational age at delivery were
assessed by Pearson or Spearman correlation coefficients according to distribution. Variables thus
identified as having a statistically significant relationship with birth weight were incorporated into a multivariable linear regression model, with birth weight as
the dependent variable.
Multiple logistic regression analysis was then
performed to generate odds ratios for birth weight
greater than 4 kg per bioelectric impedance analysis–
measured fat-free mass quartile, with the lowest
quartile serving as the reference group. Models
incorporated maternal demographic and clinical variables, along with gestational age at delivery and
bioelectric impedance analysis–measured fat mass. A
similar analysis was performed to estimate the effect
of fat mass on odds of birth weight greater than 4 kg,
this time adjusted for fat-free mass.
Statistical analyses were performed using SPSS
18.0 statistical software. P,.05 was considered statistically significant.
RESULTS
Of the 3,000 women recruited in the first trimester,
320 delivered before 37 weeks of gestation and 62
(2.1%) had gestational diabetes mellitus diagnosed on
targeted screening. Because gestational age and gestational diabetes mellitus are both strong and independent determinants of birth weight, these women
were excluded from further analysis. The characteristics of the remaining 2,618 women are shown in
Table 1. The mean BMI of the study population was
25.4 (standard deviation 5.1), with 43.9% of patients
classified as overweight or obese.
The association between birth weight and maternal
BMI, fat-free mass, fat mass, and visceral fat level was
evaluated, and in a univariable analysis all four
variables were significant predictors of birth weight
(Table 2). The variable that showed the strongest correlation with birth weight was maternal fat-free mass.
The analysis was repeated for fat mass and fat-free mass
of arms, legs, and trunk, and in all cases both parameters were associated with birth weight (P,.001).
A multiple linear regression model was built using
variables with significant univariable relationships with
birth weight. After adjustment for age, parity, gestational
age at delivery, smoking status, and fat mass, fat-free
mass remained a significant predictor of birth weight
(model R250.254, standardized b50.237; P,.001)
Kent et al
Birth Weight and Maternal Body Composition
47
Table 1. Characteristics of Study Population
N
Age (y)
Primparous
Current smoker
Former smoker
BMI (kg/m2)
Fat mass (kg)
Fat-free mass (kg)
Visceral fat (level)
BMI category (kg/m2)
Underweight (less than 18.5)
Normal (18.5–24.9)
Overweight (25.0–29.9)
Obese (30 or higher)
Delivery gestation (wk)
Mode of delivery
Spontaneous vaginal delivery
Instrumental
Emergency cesarean delivery
Elective cesarean delivery
Birth weight (kg)
2,618
28.3 (15–44)
49.6
22.0
18.9
25.4 (15–55)
22.1 (4.6–72.3)
46.2 (29.9–79.2)
3.79 (1–18)
2.3
53.8
27.4
16.5
39.7 (37–42)
60.4
19.0
12.2
8.4
3.51 (1.9–5.1)
BMI, body mass index.
Data are mean (range) or % unless otherwise specified.
(Table 3). In contrast, no relationship was found
between fat mass and birth weight using this model.
Compared with women in the first fat-free mass
quartile, the unadjusted odds ratios for birth weight
more than 4 kg for women in the second, third, and
fourth fat-free mass quartiles were 1.87 (95% confidence
interval [CI] 1.26–2.76), 2.38 (95% CI 1.63–3.48), and
4.89 (95% CI 3.43–6.98), respectively (P,.001) (Table 4).
After adjustment for age, parity, gestational age at delivery, and maternal fat mass, fat-free mass remained a predictor of birth weight more than 4 kg, with women in
the highest fat-free mass quartile having an odds ratio of
3.64 (95% CI 2.34–5.68) for birth weight greater than 4
kg. In contrast, no relationship was seen between odds
of birth weight more than 4 kg and maternal fat mass
after adjustment for fat-free mass (Table 4).
DISCUSSION
In a large, prospective, observational study of women
who delivered singleton neonates at term, we found
Table 2. Univariate Correlations With Birth Weight
(N52,618)
P
Correlation Coefficient
Age
Body mass index
Fat mass
Fat-free mass
Smoking
Parity
48
Kent et al
0.08
0.169
0.214
0.261
-0.193
0.131
,.001
,.001
,.001
,.001
,.001
,.001
Table 3. Multivariate Regression Analysis of
Predictors of Birth Weight
Variable
Gestational age at
delivery (wk)
Fat-free mass
Smoking
Parity
Age (y)
Fat mass
Regression Coefficient
(95% CI)
143.0 (129.6–156.4)
19.8
2219.0
124.7
3.3
0.7
P
,.001
(17.0–22.7)
,.001
(2248.0 to 170.0) ,.001
(90.4–159.0)
,.001
(0.3–6.3)
.032
(21.9 to 3.3)
.621
CI, confidence interval.
R250.245.
Dependent variable: birth weight.
Independent variables: age, parity, gestational age at delivery,
smoking, fat mass, and fat-free mass.
that birth weight correlated positively with measurement of maternal fat-free mass, and not fat mass, in the
first trimester of pregnancy. The relationship between
birth weight and different biological and psychosocial
variables is complex. However, recent studies have
often focused on the increased risk of fetal macrosomia with maternal obesity.14 Concerns about aberrant fetal growth, albeit based on limited evidence,
influenced the Institute of Medicine’s decision to
revise downwards the recommendations on gestational weight gain for obese women.5
Although BMI, measured accurately, is an excellent surrogate marker of adiposity, it provides no
information on the distribution of either fat or fat-free
mass. This study has used bioelectric impedance
analysis to directly measure maternal body composition, which means fat and fat-free mass have been
measured and also their distributions in early pregnancy have been measured. Strengths of this study
include the accurate dating of all pregnancies by firsttrimester ultrasonography; although gestational age at
delivery is a strong predictor of birth weight, few
studies confirm the dates with an early ultrasound
scan.15 Also, all patients had BMI calculated after digital measurement of height and weight. This contrasts
with other studies in which BMI often was calculated
using self-reporting of weight and height, which is
epidemiologically misleading.8 Confining the study
to Caucasian women without gestational diabetes mellitus and with a singleton pregnancy who delivered at
term removes other important confounding variables
for birth weight.
A potential weakness in our study is that recruitment was by convenience and was not consecutive.
The analysis is also based on proprietary formulae,
which were calculated for American and European
women. In view of ethnic differences in adiposity, the
Birth Weight and Maternal Body Composition
OBSTETRICS & GYNECOLOGY
Table 4. Crude and Adjusted Odds Ratios of Fat-Free Mass and Fat Mass Quartiles as Predictors of Birth
Weight Greater Than 4 kg
Quartile
Fat-free mass
Model 1
Model 2
Model 3a
Fat mass
Model 1
Model 2
Model 3b
1
2 Odds Ratio (95% CI)
3 Odds Ratio (95% CI)
4 Odds Ratio (95% CI)
P
1.00
1.00
1.00
1.87 (1.26–2.76)
1.55 (1.04–2.31)
1.49 (1.00–2.24)
2.38 (1.63–3.48)
2.06 (1.40–3.04)
1.89 (1.26–2.84)
4.89 (3.43–6.98)
4.42 (3.07–6.37)
3.64 (2.34–5.68)
,.001
,.001
,.001
1.00
1.00
1.00
1.92 (1.31–2.81)
1.65 (1.11–2.43)
1.47 (0.98–2.19)
2.72 (1.88–3.92)
2.31 (1.58–3.37)
1.62 (1.08–2.44)
3.73 (2.61–5.32)
3.28 (2.27–4.74)
1.42 (0.91–2.23)
,.001
,.001
.13
CI, confidence interval.
Model 1: unadjusted.
Model 2: adjusted for age, parity, gestational age, and smoking history.
Model 3a: adjusted as per model 2 and fat mass.
Model 3b: adjusted as per model 2 and fat-free mass.
findings from this study may not be applicable to
other ethnic groups.16
Our findings are consistent with those of previous
smaller studies using bioelectric impedance analysis in
pregnant women. In an Italian longitudinal study,
single-frequency tetrapolar bioelectric impedance analysis evaluation was first conducted at 15–17 weeks of
gestation and repeated at 20–22 weeks, 25–27 weeks,
30–32 weeks, and 35–37 weeks of gestation.17 Body
water in the second trimester, but not in the third trimester, was predictive of birth weight. In a smaller
study of 29 women near term using single-frequency
bioelectric impedance analysis after 36 weeks of gestation, fat-free mass was the most important maternal
body component correlating with birth weight.18 In
a study of 169 women who delivered a singleton pregnancy at term, maternal body composition was measured postpartum using bioelectric impedance analysis.
Fat-free mass and total body water explained the major
proportion of the birth weight.19
In a prospective study of 200 healthy women in
New York who delivered at term, body fat was
determined by a complex multicompartment model
between 12 and 16 weeks of gestation, and again after
36 weeks of gestation.20 After regression modeling,
maternal body water, but not body fat, correlated positively with birth weight.
These scientific observations are supported by
larger epidemiologic reports. Despite increasing levels
of maternal obesity in recent years, there has been no
increase in the incidence of fetal macrosomia (birth
weight more than 4.5 kg) in our own hospital,21 nationally,22 or in other countries such as the United States.23
It is notable that in our study maternal adiposity
was measured in the first trimester and that women
with pre-existing diabetes mellitus were excluded.
VOL. 121, NO. 1, JANUARY 2013
Maternal obesity is an important risk factor for the
development of gestational diabetes mellitus, particularly moderate to severe obesity. Thus, any epidemiologic association between maternal obesity and
increased fetal growth may be the result of metabolic
abnormalities associated with gestational diabetes
mellitus, such as hyperglycemia and hypertriglyceridemia, rather than maternal obesity itself.
Our findings have important clinical implications.
The Institute of Medicine in 2009 produced revised
guidelines that lowered the recommended gestational
weight gain for obese women to 5–9 kg.4 The number of
obese women with a gestational weight gain exceeding
the recommendations is high, but obese women still gain
less weight during pregnancy than nonobese women.24
There is a potential risk that overzealous attempts
to reduce gestational weight gain in obese women
may cause complications by reducing calorie intake or
micronutrients. This reduction may be detrimental to
the fetus and, in the absence of gestational diabetes
mellitus, our results suggest minimizing maternal
weight gain may not prevent fetal macrosomia and
could potentially increase the risk of intrauterine
growth restriction.
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