Searching for the Definition of Macrosomia through an
Outcome-Based Approach
Jiangfeng Ye
1.
, Lin Zhang
2.
, Yan Chen
1
, Fang Fang
1
, ZhongCheng Luo
1
, Jun Zhang
1
*
1MOE-Shanghai Key Laboratory of Children’s Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Department of
Obstetrics, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
Abstract
Background:
Macrosomia has been defined in various ways by obstetricians and researchers. The purpose of the present
study was to search for a definition of macrosomia through an outcome-based approach.
Methods:
In a study of 30,831,694 singleton term live births and 38,053 stillbirths in the U.S. Linked Birth-Infant Death
Cohort datasets (1995–2004), we compared the occurrence of stillbirth, neonatal death, and 5-min Apgar score less than
four in subgroups of birthweight (4000–4099 g, 4100–4199 g, 4200–4299 g, 4300–4399 g, 4400–4499 g, 4500–4999 g vs.
reference group 3500–4000 g) and birthweight percentile for gestational age (90
th
–94
th
percentile, 95
th
-96
th
, and $97
th
percentile, vs. reference group 75
th
–90
th
percentile).
Results:
There was no significant increase in adverse perinatal outcomes until birthweight exceeded the 97
th
percentile.
Weight-specific odds ratios (ORs) elevated substantially to 2 when birthweight exceeded 4500 g in Whites. In Blacks and
Hispanics, the aORs exceeded 2 for 5-min Apgar less than four when birthweight exceeded 4300 g. For vaginal deliveries,
the aORs of perinatal morbidity and mortality were larger for most of the subgroups, but the patterns remained the same.
Conclusions:
A birthweight greater than 4500 g in Whites, or 4300 g in Blacks and Hispanics regardless of gestational age is
the optimal threshold to define macrosomia. A birthweight greater than the 97
th
percentile for a given gestational age,
irrespective of race is also reasonable to define macrosomia. The former may be more clinically useful and simpler to apply.
Citation: Ye J, Zhang L, Chen Y, Fang F, Luo Z, et al. (2014) Searching for the Definition of Macrosomia through an Outcome-Based Approach. PLoS ONE 9(6):
e100192. doi:10.1371/journal.pone.0100192
Editor: Aimin Chen, University of Cincinnati, United States of America
Received January 3, 2014; Accepted May 23, 2014; Published June 18, 2014
Copyright: ß2014 Ye et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study was supported by a grant from the Shanghai Municipal Health Bureau, China (No. GWIII-26.2). The funder had no role in study design, data
collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: junjimzhang@gmail.com
.These authors contributed equally to this work.
Introduction
The term ‘‘macrosomia’’ is used to describe a very large fetus or
neonate. But there is no precise definition of macrosomia on which
all obstetricians and researchers agree. Common definitions use
either birthweight percentiles (e.g. P
90
or P
97
) or birthweight cut-
points (e.g. 4000g, 4500 g).[1–5] None however, were established
based on clear clinical evidence inclusive of a broad range of
perinatal outcomes.
Infant mortality decreases with increasing birthweight until
birthweight reaches a certain point after which the mortality rate
increases. This reverse J-shaped mortality curve has been well-
described for all races. It is well-known that the weight
corresponding to the lowest mortality is several hundred grams
heavier than the mean birthweight.[5–10] Bigger babies may have
survival advantages over smaller ones. But too big babies have
higher morbidities of asphyxia, birth trauma, neonatal seizures,
and meconium aspiration syndrome. [2,4,5] Macrosomic babies
may also have a higher risk of adult diseases such as obesity, type 2
diabetes and cardiovascular diseases. [11–13] So, how big is too
big? A consensus has not yet been reached to define macrosomia.
[14] Given that pregnant women are now older and heavier than
before, this may contribute to bigger babies. [15,16] An evidence-
based definition of macrosomia is needed.
In this study, we examined the frequently-used definitions of
macrosomia through an outcome-based approach using an index
of a broad range of hard-fact adverse perinatal outcomes. We
aimed to answer the following questions: (1) What is an
appropriate definition of macrosomia? Should it be defined based
on a birthweight percentile for a given gestational age (i.e., large-
for-gestational-age) or empirical birthweight cutpoints, irrespective
of gestational age? (2) Does one definition fit all races?
Materials and Methods
Study Design, Data Source and Population Studied
We carried out a retrospective cohort study. Infants were
categorized into subgroups by every 100 grams of birthweight
over 4000 g or by birthweight percentile for a given gestational
age at the cutoff points of the 10
th
,25
th
,50
th
,75
th
,90
th
,95
th
,
97
th
percentile. Perinatal mortality and morbidity were compared
between subgroups with the reference groups (3500–4000 g in
birthweight, or 75
th
–90
th
percentile). The cutoff points exceeded
PLOS ONE | www.plosone.org 1 June 2014 | Volume 9 | Issue 6 | e100192
which infants had significantly increased risks of mortality and
morbidity were considered as the threshold to defined macroso-
mia.
This study was based on the U.S. National Center for Health
Statistics (NCHS) Linked Birth-Infant Death Cohort datasets from
1995–2004. The datasets were compiled of birth and infant death
certificates registered in all states, the District of Columbia, Puerto
Rico, the Virgin Islands, and Guam. Each state provided to the
NCHS matching birth and death certificate numbers for each
infant less than one year of age occurring in a given calendar year.
NCHS used the matching certificate numbers to extract record
from the NCHS statistical files and link these data to establish the
linked record file. The methodological details of the linkage of
birth and death record were published in the Technical Notes of
National Vital Statistical Reports. [17] The data are coded
according to uniform specification and comply with uniform
quality control standard. The data are publicly accessible at the
Centers for Disease Control and Prevention Web site. Available
information in these files included demographic characteristics of
mothers, obstetric history, current pregnancy, labor and delivery
complications and birth outcomes.
For the purpose of this analysis, the study sample was restricted
to: 1) race of non-Hispanic White, non-Hispanic Black, and
Hispanic; 2) singleton pregnancies; 3) birthweight $500 grams;
and 4) term births (gestational age 37–42weeks). Infants had
missing birthweight or gestational age were excluded. Birthweight
.5500 grams was considered implausible and treated as missing
value. [18] Asian and other races were excluded due to the small
number of deaths.
Definition of Covariates
Race and ethnic origin were based on self-report. Maternal age
at delivery was grouped into: ,19, 20–34 and $35 years old.
Mother’s marital status was classified as: married, unmarried and
unknown. Education levels were recoded as: ,12 years (less than
high school), 12 years (high school), 13–16 years (college), $17
years (graduate school). Smoking during pregnancy was defined by
average number of cigarettes per day. We recoded this variable as
‘‘nonsmokers’’ (0 cigarettes per day), ‘‘light smokers’’ (1 to 10
cigarettes per day) and ‘‘heavy smokers’’ (more than 10 cigarettes
per day). Information describing ‘‘when the prenatal care started’’
was classified as: 1
st
trimester (1
st
-3
rd
month), 2
nd
trimester (4
th
-6
th
month), 3
rd
trimester (7
th
-9
th
month) and no prenatal care. Mode
of delivery was classified as vaginal or cesarean delivery.
Estimation of Gestational Age
Gestational age was recorded firstly based on self-reported last
menstrual period (LMP) and secondly by clinical estimate (CE).
Limitations of LMP-based estimate have been well documented.
[19,20] Several methods have been proposed to reduce misclas-
sifications of LMP-based gestational age. Qin and colleagues [21]
recently proposed that CE of gestational age substitutes for LMP-
based gestational age when the difference between the two
estimates was greater than two weeks. Compared to other
techniques, this method almost eliminated the aberrant second
mode of gestational age distribution, and was demonstrated to be
effective in correcting large errors in gestational age estimates. A
further benefit is that records are reclassified rather than excluded
altogether. Thus, we adopted LMP/CE method to estimate
gestational age.
Study Outcomes
The main outcomes included stillbirth, neonatal death and 5-
min Apgar score less than four. Stillbirth included all fetal deaths
with a birthweight of 500 g or more. Neonatal death included
infant deaths from 0 to 27 days after birth. As fetal and neonatal
mortality are rare outcomes, a composite perinatal mortality and
morbidity index (PMMI) including stillbirth, neonatal death and a
5-min Apgar score less than four was created. In the exploratory
analyses we observed that infants did not have significantly
increased risk of postnatal death even with a birthweight of 4500
or more. Therefore, postnatal mortality was not considered as one
of the outcome measures.
Ethics Statement
Data for this analysis were obtained from anonymized data
rendering ethical approval unnecessary by the Shanghai Xinhua
Hospital Research Ethics Board.
Statistical Analyses
Two types of definition of macrosomia were compared - based
on empirical birthweight or statistical distribution of birthweight.
The definitions were examined through an outcome-based
approach with the assumption that birthweight-specific infant
mortality curve follows a reversed J-shape. [6–10] Macrosomia is
defined as weights or weight percentiles that exceed the nadir of
the mortality curve. Infants were categorized into subgroups by
birthweight percentile cutoffs: 75
th
,90
th
,95
th
and 97
th
for each
gestational week. Birthweight percentiles by gestational age were
calculated according to the global reference for fetal-weight and
birthweight percentiles by race/ethnicity. [22] Table 1 contains
birthweight percentiles by gestational age for non-Hispanic White,
non-Hispanic Black and Hispanics. The risks of perinatal mortality
and morbidity were compared between subgroups. Exploratory
analyses observed that birthweight corresponding to the lowest
morbidity and mortality was several hundred grams heavier than
mean birthweight, as in previous studies.[6–10] Subgroups with
birthweight at 75
th
–90
th
percentiles or 3500–4000 g corresponded
to the nadir of birthweight-specific mortality curve and, therefore,
were used as the reference categories. Given that this study focuses
on macrosomia, we presented the main results for birthweight
greater than 3500 g or 75th percentile in separate analyses.
Multivariable logistic regression was used to estimate odds ratios
(ORs) of perinatal mortality and morbidity. We used OR = 2 as
the pre-defined criterion to identify clinically important macroso-
mia similar to the definition of fetal growth restriction by neonatal
death risk in Boulet’s study. [23] The analysis of risk of infant
mortality and morbidity was adjusted for maternal age, parity,
infant sex and gestational age, maternal diabetes, chronic
hypertension, pregnancy associated hypertension, eclampsia,
smoking and social economic status (marital status, education)
and prenatal care. The selection of the covariates included in the
models was based on findings in the literature. All variables were
retained in the model regardless of statistical significance as they
had a prior theoretical association with the outcomes. All analyses
were carried out using SAS version 9.2 (SAS Institute Inc, Cary,
NC).
Results
There were 39,956,864 live births and 539,915 stillbirths in the
linked dataset. A total of 30,831,694 live births and 38,053
stillbirths were included. There were large variations in the
birthweight distribution among infants of different races (Table 1).
About 12% of Whites, 6% of Blacks and 9% of Hispanics had a
birthweight greater than 4000 g. A total of 1.9% of Whites, 0.9%
of Blacks and 1.4% of Hispanics weighed heavier than 4500 g at
birth. The prevalence of birthweight greater than the 97
th
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 2 June 2014 | Volume 9 | Issue 6 | e100192
Table 1. Race-specific birthweight distributions in singleton term births, U.S. 1995–2004.
Gestational age (weeks) N
a
Birthweight (g) Birthweight percentile
Mean (SD) 4000–4499 (%) 4500–4999(%) $5000(%) 75
th
–89
th
(%) 90
th
–94
th
(%) 95
th
–96
th
(%) $97
th
(%)
White 19748437 3465(476) 10.6 1.7 0.2 15.4 5.5 2.5 6.0
37 1608614 3154(484) 3.7 0.6 0.1 16.9 7.5 3.6 12.4
38 3622784 3336(461) 6.3 0.9 0.1 16.4 7.2 3.3 9.6
39 5299598 3462(448) 9.4 1.4 0.1 16.1 5.7 2.5 6.3
40 6020734 3563(448) 13.2 2.1 0.2 15.0 4.5 2.2 3.7
41 2398201 3631(468) 16.7 3.2 0.3 12.1 3.8 1.3 2.7
42 798506 3571(490) 14.6 3.0 0.4 15.3 5.2 2.0 3.0
Black 4525824 3259(474) 5.1 0.8 0.1 14.8 5.7 2.6 7.2
37 486874 3004(481) 2.1 0.4 0.1 15.7 8.1 4.0 14.0
38 918529 3152(457) 3.1 0.5 0.1 16.8 7.0 3.2 10.1
39 1182564 3267(448) 4.5 0.7 0.1 14.8 5.9 2.6 7.0
40 1280923 3365(450) 6.6 0.9 0.1 13.9 4.7 1.9 4.9
41 474383 3420(473) 8.9 1.3 0.2 12.2 3.6 1.8 3.2
42 182551 3346(487) 7.2 1.1 0.1 15.3 5.0 2.0 3.0
Hispanic 6563032 3397(464) 8.0 1.2 0.2 14.9 6.2 2.5 6.9
37 577094 3152(484) 3.6 0.6 0.1 16.5 8.8 4.2 15.9
38 1242509 3290(453) 5.1 0.8 0.1 17.3 7.6 3.6 10.7
39 1779751 3398(441) 7.2 1.0 0.1 15.8 6.8 2.6 6.7
40 1905498 3483(443) 9.8 1.5 0.2 13.9 5.1 1.9 4.3
41 772771 3539(460) 12.5 2.1 0.2 10.9 3.8 1.3 2.9
42 285409 3489(474) 34.5 11.0 2.0 14.5 5.4 2.2 3.0
a
Number of live births.
doi:10.1371/journal.pone.0100192.t001
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 3 June 2014 | Volume 9 | Issue 6 | e100192
percentile was 6.0%, 7.2% and 6.9% for White, Black and
Hispanic, respectively.
Table 2 shows the prevalence of adverse perinatal outcomes.
Cesarean delivery rates were around 20% in all the three races,
and increased with higher birthweight. Prevalence of stillbirth,
neonatal death and 5-min Apgar score less than four decreased
with higher birthweight. Infants with birthweight of 3500–4000 g
had the lowest perinatal mortality and morbidity. When the
birthweight increased further, prevalence of perinatal mortality
and morbidity increased. Table 3 shows that the risk of perinatal
mortality increased slightly when birthweight exceeded the 95
th
in
all the three races. When birthweight exceeded the 97
th
percentile,
the risk increased further. The adjusted odds ratios (aORs) of
perinatal mortality were 1.39 (95%CI:1.28,1.50), 1.64
(95%CI:1.46,1.85) and 1.58 (95%CI: 1.39,1.80) in Whites, Blacks
and Hispanics, respectively. A similar trend was found in the risk
of 5-min Apagr score less than four and composite index of
morbidity and mortality.
When infants weighing between 4000–4500 g were further
classified into every 100 g subgroups, we found that the aORs
increased gradually with higher birthweight. When birthweight
exceeded 4500 g, the risk of perinatal mortality and morbidity
increased substantially in Whites (aOR 1.91 and 1.94, respectively)
(Table 4). However, in Blacks, the aORs of adverse outcomes
exceeded 2.0 when birthweight was heavier than 4300 g
(aOR = 2.04 for 5-min Apgar score less than four). In Hispanci,
the aOR exceeded 2.0 when birthweight was heavier than 4300 g
(aORs 2.03 for 5-min Apgar score less than four). The aORs of
composite index of mortality and morbidity exceeded 2.0 when
birthweight exceeded 4500 g in Blacks and Hispanics (aOR 3.09
and 2.71, respectively). We did two sensitive analyses by restricting
the analyses to vaginal deliveries (Table S1 and S2) and vaginal
deliveries excluding vaginal births after cesarean section (Table S3
and S4), the aORs of perinatal morbidity and mortality were
larger for most of the subgroups, but the patterns remained the
same.
Discussion
Our findings suggest that the term macrosomia should be
defined as a birthweight greater than 4500 g regardless of
gestational age in Whites, or as greater than the 97
th
percentile
in birthweight for gestational age for three races. In general, our
study supported the AJOG’s definition of macrosomia as 4500 g
or more for Whites. [3] However, in Blacks and Hispanics, the
optimal threshold to define macrosomia may be 200 g lower, at
4300 g based on the perinatal mortality and 5-min Apgar score.
The definition based on birthweight may be more clinically useful
and simpler to apply than that based on birthweight percentile.
We observed no significant increase in adverse perinatal
outcomes in the subgroup of 90
th
-94
th
and 95
th
-96
th
percentiles
in birthweight. Our finding doesn’t support the definition of
Table 2. Prevalence of perinatal and neonatal adverse outcomes in singleton birth cohort, U.S. 1995–2004.
Gestational age (weeks)
Cesarean
delivery (%)
Stillbirth
b
(per 1000)
Neonatal death
(per 1000)
5-min Apgar score less than four
(per 1000)
White (N
a
=19748437) 21.5 1.1 1.0 1.0
,2500 29.1 11.7 11.1 3.5
2500–2999 20.6 2.2 1.8 1.3
3000–3499 19.5 0.9 0.8 0.9
3500–3999 21.3 0.5 0.5 0.9
4000–4499 26.8 0.6 0.5 1.1
4500–4999 36.7 1.2 0.7 1.6
$5000 50.2 4.7 1.9 4.4
Black (N
a
=4525824) 22.9 1.7 1.3 1.8
,2500 24.9 9.9 7.2 4.7
2500–2999 19.6 1.9 1.6 1.9
3000–3499 21.0 1.0 0.9 1.4
3500–3999 25.9 1.0 0.8 1.5
4000–4499 35.3 1.8 0.9 2.3
4500–4999 48.6 5.4 1.5 4.5
$5000 62.2 18.5 5.0 12.9
Hispanic (N
a
=6563032) 21.5 1.3 1.0 1.0
,2500 26.7 13.7 10.8 2.8
2500–2999 18.8 2.0 1.5 1.1
3000–3499 19.1 0.9 0.7 0.9
3500–3999 22.6 0.7 0.5 0.9
4000–4499 30.4 1.0 0.5 1.2
4500–4999 42.9 2.8 0.9 2.7
$5000 58.3 9.9 2.5 6.3
a
Number of live births.
b
Based on live births plus stillbirths.
doi:10.1371/journal.pone.0100192.t002
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 4 June 2014 | Volume 9 | Issue 6 | e100192
Table 3. Risks of perinatal mortality and morbidity (the occurrence of stillbirth, neonatal death, or 5-min Apgar score ,4) by birthweight percentile (excluding deaths due to
congenital anomalies).
Birthweight
percentile Mortality
a
5-min Apgar score less than four Perinatal mortality and morbidity
c
Prevalence
(per 1000)
adjusted OR
(95% CI)
b
p value
Prevalence
(per 1000)
adjusted OR
(95% CI)
b
p value
Prevalence
(per 1000)
adjusted OR
(95% CI)
b
p value
White N = 16048878
P
75
–P
89
0.9 1.00 0.9 1.00 1.7 1.00
P
90
–P
94
0.9 1.03(0.94,1.13) 0.5134 1.0 1.06(0.98,1.15) 0.1532 1.8 1.04(0.97,1.11) 0.2430
P
95
–P
96
1.0 1.08(0.95,1.22) 0.2403 1.1 1.24(1.12,1.38) ,0.0001 1.9 1.15(1.06,1.26) 0.0009
$P
97
1.4 1.39(1.28,1.50) ,0.0001 1.3 1.40(1.30,1.50) ,0.0001 2.5 1.36(1.28,1.43) ,0.0001
Black N = 3758701
P
75
–P
89
1.3 1.00 1.5 1.00 2.7 1.00
P
90
–P
94
1.5 1.03(0.88,1.2) 0.7312 1.5 1.01(0.88,1.15) 0.9323 2.9 1.00(0.90,1.11) 0.9610
P
95
–P
96
1.9 1.24(1.03,1.51) 0.0263 1.7 1.14(0.95,1.35) 0.1503 3.3 1.13(0.98,1.29) 0.0853
$P
97
3.0 1.64(1.46,1.85) ,0.0001 2.5 1.64(1.47,1.82) ,0.0001 5.2 1.59(1.47,1.73) ,0.0001
Hispanic N = 6564283
P
75
–P
89
1.0 1.00 0.9 1.00 1.4 1.00
P
90
–P
94
1.0 0.96(0.81,1.13) 0.5827 0.9 1.04(0.86,1.27) 0.6562 1.4 1.03(0.91,1.16) 0.6888
P
95
–P
96
1.1 0.92(0.73,1.16) 0.4584 0.9 0.98(0.74,1.31) 0.9132 1.4 0.90(0.75,1.08) 0.2483
$P
97
2.1 1.58(1.39,1.80) ,0.0001 1.6 1.74(1.48,2.05) ,0.0001 2.8 1.65(1.49,1.82) ,0.0001
a
The occurrence of stillbirth or neonatal death.
b
Data are adjusted ORs estimated from multiple regression models adjusted for maternal age, gestational age, parity, infant sex, maternal diabetes, chronic hypertension, pregnancy associated hypertension, eclampsia, smoking,
social economic status (marital status, education) and month of prenatal care started.
c
The occurrence of stillbirth, neonatal death, or 5-min Apgar score less than four.
doi:10.1371/journal.pone.0100192.t003
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 5 June 2014 | Volume 9 | Issue 6 | e100192
Table 4. Risks of perinatal mortality and morbidity (stillbirth, neonatal death, or 5-min Apgar score ,4) by birthweight (excluding deaths due to congenital anomalies).
Birthweight Mortality
a
5-min Apgar score less than four Perinatal mortality and morbidity
c
Prevalence (per 1000) adjusted OR (95% CI)
b
p value
Prevalence (per
1000) adjusted OR (95% CI)
b
p value
Prevalence (per
1000) adjusted OR (95% CI)
b
p value
White N = 16048878
3500–3999 0.8 1.00 0.9 1.00 1.6 1.00
4000–4099 0.8 1.08(0.96,1.21) 0.2067 1.0 1.20(1.09,1.31) 0.0001 1.7 1.12(1.04,1.21) 0.0025
4100–4199 0.9 1.20(1.07,1.34) 0.0021 1.1 1.21(1.10,1.33) ,0.0001 1.8 1.22(1.13,1.31) ,0.0001
4200–4299 1.0 1.34(1.17,1.54) ,0.0001 1.0 1.14(1.01,1.29) 0.0393 1.8 1.21(1.1,1.33) 0.0001
4300–4399 1.0 1.43(1.24,1.65) ,0.0001 1.2 1.33(1.18,1.51) ,0.0001 2.1 1.37(1.24,1.5) ,0.0001
4400–4499 1.0 1.47(1.22,1.77) ,0.0001 1.2 1.36(1.16,1.60) 0.0001 2.1 1.38(1.21,1.57) ,0.0001
4500–4999 1.5 1.91(1.69,2.15) ,0.0001 1.6 1.77(1.60,1.96) ,0.0001 2.9 1.82(1.68,1.98) ,0.0001
$5000 6.0 7.23(5.98,8.76) ,0.0001 4.4 4.73(3.89,5.75) ,0.0001 9.5 5.61(4.86,6.48) ,0.0001
Black N = 3758701
3500–3999 1.4 1.00 1.5 1.00 2.8 1.00
4000–4099 1.6 1.10(0.86,1.41) 0.4391 1.8 1.16(0.94,1.41) 0.1612 3.2 1.10(0.94,1.29) 0.2454
4100–4199 2.0 1.27(1.00,1.62) 0.0484 2.3 1.55(1.29,1.87) ,0.0001 4.0 1.44(1.24,1.68) ,0.0001
4200–4299 2.0 1.16(0.84,1.60) 0.3715 2.7 1.80(1.44,2.25) ,0.0001 4.4 1.51(1.25,1.83) ,0.0001
4300–4399 2.6 1.67(1.24,2.23) 0.0006 3.0 1.94(1.54,2.45) ,0.0001 5.3 1.83(1.52,2.21) ,0.0001
4400–4499 3.9 2.35(1.69,3.27) ,0.0001 2.3 1.46(1.02,2.08) 0.0394 5.8 1.82(1.42,2.34) ,0.0001
4500–4999 5.8 3.49(2.86,4.27) ,0.0001 4.5 2.89(2.39,3.49) ,0.0001 9.5 3.09(2.68,3.57) ,0.0001
$5000 18.7 9.68(7.09,13.22) ,0.0001 12.9 7.63(5.52,10.53) ,0.0001 35.9 8.33(6.59,10.54) ,0.0001
Hispanic N = 6564283
3500–3999 0.9 1.00 0.9 1.00 1.3 1.00
4000–4099 1.1 1.27(1.03,1.56) 0.0258 0.9 1.07(0.83,1.39) 0.6056 1.4 1.19(1.01,1.4) 0.0403
4100–4199 1.1 1.10(0.87,1.39) 0.4158 1.3 1.57(1.25,1.98) 0.0001 1.7 1.36(1.15,1.6) 0.0002
4200–4299 1.8 1.94(1.54,2.45) ,0.0001 1.3 1.51(1.12,2.04) 0.0069 2.2 1.64(1.36,1.99) ,0.0001
4300–4399 1.7 1.68(1.29,2.18) 0.0001 1.6 1.81(1.35,2.43) ,0.0001 2.4 1.79(1.48,2.17) ,0.0001
4400–4499 1.6 1.44(1.00,2.09) 0.0519 1.1 1.25(0.78,2.00) 0.3493 2.1 1.42(1.06,1.88) 0.0173
4500–4999 3.4 2.69(2.19,3.29) ,0.0001 2.7 2.96(2.35,3.71) ,0.0001 4.4 2.71(2.33,3.17) ,0.0001
$5000 11.4 9.14(6.7,12.46) ,0.0001 6.3 7.09(4.62,10.88) ,0.0001 13.7 7.89(6.11,10.2) ,0.0001
a
The occurrence of stillbirth or neonatal death.
b
Data are adjusted ORs estimated from multiple regression models adjusted for maternal age, gestational age, parity, infant sex, maternal diabetes, chronic hypertension, pregnancy associated hypertension, eclampsia, smoking,
social economic status (marital status, education) and month of prenatal care started.
c
The occurrence of stillbirth, neonatal death, or 5-min Apgar score less than four.
doi:10.1371/journal.pone.0100192.t004
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 6 June 2014 | Volume 9 | Issue 6 | e100192
macrosomia as LGA. The 97
th
percentile for a given gestational
week may be a better cutoff point to define what is too big in birth
size. Based on the pre-defined criterion (OR = 2 as the cutoff
point) to identify clinically important macrosomia [23], even the
97
th
percentile could not meet this criterion.
Several studies using perinatal mortality and morbidity as
outcomes to examine the impact of macrosomia reported
somewhat similar conclusions. Boulet SL et al [2] used the NCHS
database from 1995–1997 and found that although a definition of
macrosomia as .4000 g may be useful for the identification of
increased risk of labor, .4500 g may be more predictive of
neonatal morbidity, and .5000 g may be a better indicator of
infant mortality risk. Although there is no general consensus on the
choice of optimal outcome indicators in defining clinically
significant macrosomia, stillbirth and neonatal death were the
most frequently used outcomes. [24–26] The 5-min Apgar score
less than four is strongly predictive of neonatal death. The
mortality of neonatal death in term infants with five-minute Apgar
score less than four was more than one in five (244 per 1000)
infants.
We found that risks of perinatal and infant mortality and
morbidity increased gradually in the infants weighted between
4000–4500 g in Whites. Once birthweight exceeded 4500 g, risks
elevated substantially. Our findings further are in general
agreement with previous study and support the American
Congress of Obstetricians and Gynecologists’ definition of
macrosomia as 4500 g or more. [3,5] However, our study also
showed that there was some variation among races/ethnicities.
Birthweight at 4500 g appears to be a good cutoff point for
Whites, but in Blacks and Hispanics, the cutoff seems about 200 g
lower.
Our study also found that the aORs for babies with birthweight
greater than 4500 g were substantially larger than those above the
97
th
percentile. This may be explained by the fact that before 40
weeks, 97
th
percentiles of birthweight correspond to birthweight
much lower than 4500 g. Thus, the .97
th
percentile group
included a substantial proportion of births that are reasonable in
size. Given this deficiency, a definition of macrosomia based on
4500 g for Whites, and 4300 g for Blacks and Hispanics is
recommended.
In Pasupathy’s study [27], neonatal outcomes of macrosomia
defined by customized centiles, population centiles and birth-
weight greater than 4000 g were compared in Whites. They
suggested customized standard as the better definition of LGA
than population centiles or a birthweight of 4000 g for its stronger
association with adverse neonatal outcomes. The macrosomia
infants defined by the combination of customized centile/
population centile or customized centile/empirical birhtweight of
4000 g in Pasupathy’s study had birthweight ranging from 4020 g
to 4475 g and from 4160 g to 4520 g, respectively, which were a
little lower than that defined by the birthweight of 4500 g or more.
The subgroup of infants defined as macrosomia in the current
study (birthweight 4500 or more) had twofold increased risk of
perinatal mortality and morbidity compared with the reference
group (3500–3999 g), which was similar to that of macrosomia
defined by the combined definition in Pasupathy’s study
(aOR = 1.8 and 1.9, respectively). For simplicity in clinical
application, we would suggest the definition of macrosomia as a
birthweight of 4500 g or more, irrespective of gestational age
among Whites.
Cesarean section is an effective intervention to reduce the risks
of neonatal adverse outcomes when it is medically justified. The
true risk of adverse perinatal outcomes in macrosomia may be
underestimated when medical necessary cesarean section was
available. [5,28] In our study, rates of cesarean delivery was
around 20% and increased significantly when birthweight was
higher than the 90
th
percentile or 4000 g. When we restricted the
analyses to vaginal deliveries, the aORs of adverse outcomes for
big babies were larger, but the cutoff point remained essentially
unchanged. Even after excluding vaginal births after cesarean
section, the risks of neonatal mortality and morbidity increased
with higher birthweight. The increase trends of adverse perinatal
outcomes in macrosomia infants may not be explained by the
confounding of mode of delivery.
Limitations
Our study has several potential limitations. First, the estimate of
gestational age may not be accurate in some babies, which might
have resulted in some misclassifications in birthweight percentiles,
and consequently, reduced the aORs for the extreme weight (.
90
th
or 97
th
) percentile groups. Secondly, high prepregnancy body
mass index (BMI) is known to be associated with both macrosomia
and adverse birth outcomes [29,30], but maternal prepregnancy
BMI was not available. We speculate that adjusting for prepreg-
nancy BMI may decrease the ORs, especially in races/ethnicities
where obesity is more prevalent. However, the trend should
remain the same, and thus, this deficiency should not materially
affect the main findings. Thirdly, cesarean delivery rate was
around 20% for all three races. Given that cesarean section is an
effective intervention to reduce maternal and neonatal mortality
when it is medically justified [28,31–33], the risk of macrosomia
without intervention may be underestimated. The NCHS files do
not include information on the timing or indication of cesarean
delivery. Thus, the impact of cesarean section on macrosomia is
unclear. We analyzed the data by including all births and, then,
vaginal deliveries only. We realize that this analytic approach may
not totally address the issue of confounding by indication, and the
risk of mortality in macrosomia might have been greater without
cesarean delivery. However, we found that the findings from
vaginal deliveries were consistent with those for all births.
Fourthly, the risks of adverse outcomes fluctuated among Hispanic
births with birthweight greater than 4200 g. Similar fluctuations
appeared in the vaginal births even after adjustment for maternal
age, gestational age, parity, infant sex, maternal diabetes, social
economic status, etc. The fluctuation in the risk of adverse
outcomes in Hispanic infants may be explained by the confound-
ing of maternal obesity. But there was no information of maternal
anthropometric indices in this dataset. The absence of information
on maternal height and weight prevented us from controlling for
the confounding of maternal obesity for the association between
macrosomia and adverse perinatal outcomes. Finally, babies with
macrosomia may have higher risk of adult diseases, such as
obesity, diabetes and cardiovascular diseases. [11–13] The reverse
J-shape relationship may also apply to the relationship birthweight
and adult diseases. The absence of information on long-term
outcomes in the NCHS files prevented us from consideration of
long-term effects of large birth size.
Implications
Birthweight at 4500 g may be the optimal cutoff point to define
macrosomia in Whites, but in Blacks and Hispanics, the cutoff
point seems to be 4300 g. The definition based on birthweight
irrespective of gestational age may be more clinically useful than
the one based on birth weight for gestational age. Application of
this pragmatic definition may be helpful to improve intrapartum
management.
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 7 June 2014 | Volume 9 | Issue 6 | e100192
Supporting Information
Table S1 Risks of perinatal morbidity and mortality (the
occurrence of stillbirth, neonatal death, or 5-min Apgar score ,
4) by birthweight percentile (excluding deaths due to congenital
anomalies) in vaginal deliveries.
(DOCX)
Table S2 Risks of perinatal morbidity and mortality (stillbirth,
neonatal death, or 5-min Apgar score ,4) by birthweight
(excluding deaths due to congenital anomalies) in vaginal
deliveries.
(DOCX)
Table S3 Risks of perinatal morbidity and mortality (the
occurrence of stillbirth, neonatal death, or 5-min Apgar score ,
4) by birthweight percentile (excluding deaths due to congenital
anomalies) in vaginal deliveries without previous cesarean section.
(DOCX)
Table S4 Risks of perinatal morbidity and mortality (stillbirth,
neonatal death, or 5-min Apgar score ,4) by birthweight
(excluding deaths due to congenital anomalies) in vaginal deliveries
without previous cesarean section.
(DOCX)
Author Contributions
Conceived and designed the experiments: JZ JFY ZCL. Analyzed the data:
JFY. Wrote the paper: JFY LZ. Critical revision of the paper for important
intellectual content: JFY LZ JZ ZCL YC FF.
References
1. Stotland NE, Caughey AB, Breed EM, Escobar GJ (2004) Risk factors and
obstetric complications associated with macrosomia. Int J Gynaecol Obstet 87:
220–226.
2. Boulet SL, Alexander GR, Salihu HM, Pass M (2003) Macrosomic births in the
united states: Determinants, outcomes, and proposed grades of risk. American
Journal of Obstetrics and Gynecology 188: 1372–1378.
3. ACOG practice bulletin no. 22. 2000 Washington, DC: American College of
Obstetricians and Gynecologists.
4. Koyanagi A, Zhang J, Dagvadorj A, Hirayama F, Shibuya K, et al. (2013)
Macrosomia in 23 developing countries: an analysis of a multicountry, facility-
based, cross-sectional survey. Lancet 381: 476–483.
5. Zhang X, Decker A, Platt RW, Kramer MS (2008) How big is too big? The
perinatal consequences of fetal macrosomia. Am J Obstet Gynecol 198: 517
e511–516.
6. Wilcox AJ, Russell IT (1983) Birthweight and perinatal mortality: II. On weight-
specific mortality. Int J Epidemiol 12: 319–325.
7. Vangen S, Stoltenberg C, Skjaerven R, Magnus P, Harris JR, et al. (2002) The
heavier the better? Birthweight and perinatal mortality in different ethnic
groups. Int J Epidemiol 31: 654–660.
8. Wilcox A, Skjaerven R, Buekens P, Kiely J (1995) Birth weight and perinatal
mortality. A comparison of the United States and Norway. Jama 273: 709–711.
9. Wilcox AJ, Russell IT (1986) Birthweight and perinatal mortality: III. Towards a
new method of analysis. Int J Epidemiol 15: 188–196.
10. Graafmans WC, Richardus JH, Borsboom GJ, Bakketeig L, Langhoff-Roos J, et
al. (2002) Birth weight and perinatal mortality: a comparison of ‘‘optimal’’ birth
weight in seven Western European countries. Epidemiology 13: 569–574.
11. Boney CM, Verma A, Tucker R, Vohr BR (2005) Metabolic syndrome in
childhood: association with birth weight, maternal obesity, and gestational
diabetesmellitus. Pediatrics. 115: e290–6.
12. Harder T, Roepke K, Diller N, Stechling Y, Dudenhausen JW, et al. (2009)
Birth weight, early weight gain, and subsequent risk of type 1 diabetes:
systematic review and meta-analysis. Am J Epidemiol. 169: 1428–36.
13. Schellong K, Schulz S, Harder T, Plagemann A (2012) Birth weight and long-
term overweight risk: systematic review and a meta-analysis including 643,902
persons from 66 studies and 26 countries globally. PLoS One. 7:e47776.
14. Haram K, Pirhonen J, Bergsjo P (2002) Suspected big baby: a difficult clinical
problem in obstetrics. Acta Obstet Gynecol Scand 81: 185–194.
15. Henriksen T (2008) The macrosomic fetus: a challenge in current obstetrics.
Acta Obstet Gynecol Scand 87: 134–145.
16. Dennedy MC, Dunne F (2013) Macrosomia: defining the problem worldwide.
Lancet 381: 435–436.
17. Mathews TJ, Curtin SC, MacDorman MF (2000) Infant mortality statistics from
the 1998 period linked birth/infant death data set. Natl Vital Stat Rep 48: 1–25.
18. Khashan AS, McNamee R, Abel KM, Pedersen MG, Webb RT, et al. (2008)
Reduced infant birthweight consequent upon maternal exposure to severe life
events. Psychosom Med. 70: 688–94.
19. Vahratian A, Buekens P, Alexander GR (2006) State-specific trends in preterm
delivery: are rates really declining among non-Hispanic African Americans
across the United States? Matern Child Health J 10: 27–32.
20. Dietz PM, England LJ, Callaghan WM, Pearl M, Wier ML, et al. (2007) A
comparison of LMP-based and ultrasound-based estimates of gestational age
using linked California livebirth and prenatal screening records. Paediatr Perinat
Epidemiol 21 Suppl 2: 62–71.
21. Qin C, Dietz PM, England LJ, Martin JA, Callaghan WM (2007) Effects of
different data-editing methods on trends in race-specific preterm delivery rates,
United States, 1990–2002. Paediatr Perinat Epidemiol 21 Suppl 2: 41–49.
22. Mikolajczyk RT, Zhang J, Betran AP, Souza JP, Mori R, et al. (2011) A global
reference for fetal-weight and birthweight percentiles. Lancet 377: 1855–1861.
23. Boulet SL, Alexander GR, Salihu HM, Kirby RS, Carlo WA (2006) Fetal
growth risk curves: defining levels of fetal growth restriction by neonatal death
risk. Am J Obstet Gynecol 195: 1571–1577.
24. Hannah ME, Hannah WJ, Hewson SA, Hodnett ED, Saigal S, et al. (2000)
Planned caesarean section versus planned vaginal birth for breech presentation
at term: a randomised multicentre trial. Term Breech Trial Collaborative
Group. Lancet 356: 1375–1383.
25. Hannah ME, Whyte H, Hannah WJ, Hewson S, Amankwah K, et al. (2004)
Maternal outcomes at 2 years after planned cesarean section versus planned
vaginal birth for breech presentation at term: the international randomized
Term Breech Trial. Am J Obstet Gynecol 191: 917–927.
26. Morris BH, Oh W, Tyson JE, Stevenson DK, Phelps DL, et al. (2008) Aggressive
vs. conservative phototherapy for infants with extremely low birth weight.
N Engl J Med 359: 1885–1896.
27. Pasupathy D, McCowan LM, Poston L, Kenny LC, Dekker GA, et al. (2012)
Perinatal outcomes in large infants using customised birthweight centiles and
conventional measures of high birthweight. Paediatr Perinat Epidemiol 26: 543–
552.
28. Scifres CM, Stamilio D, Allsworth J, Shanks A, Lewkowski B, et al. (2008)
Perinatal consequences of fetal macrosomia: Zhang et al. Am J Obstet Gynecol
198: 603–604; discussion e601–605.
29. Kristensen J, Vestergaard M, Wisborg K, Kesmodel U, Secher NJ (2005) Pre-
pregnancy weight and the risk of stillbirth and neonatal death. Bjog 112: 403–
408.
30. Yu CK, Teoh TG, Robinson S (2006) Obesity in pregnancy. Bjog 113: 1117–
1125.
31. Chauhan SP, Grobman WA, Gherman RA, Chauhan VB, Chang G, et al.
(2005) Suspicion and treatment of the macrosomic fetus: a review. Am J Obstet
Gynecol 193: 332–346.
32. Rouse DJ, Owen J, Goldenberg RL, Cliver SP (1996) The effectiveness and costs
of elective cesarean delivery for fetal macrosomia diagnosed by ultrasound. Jama
276: 1480–1486.
33. Souza JP, Gulmezoglu A, Lumbiganon P, Laopaiboon M, Carroli G, et al.
(2010) Caesarean section without medical indications is associated with an
increased risk of adverse short-term maternal outcomes: the 2004–2008 WHO
Global Survey on Maternal and Perinatal Health. BMC Med 8: 71.
Definition of Macrosomia Based on Perinatal Outcomes
PLOS ONE | www.plosone.org 8 June 2014 | Volume 9 | Issue 6 | e100192
