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RESEARCH ARTICLE
The World Health Organization Fetal Growth
Charts: A Multinational Longitudinal Study of
Ultrasound Biometric Measurements and
Estimated Fetal Weight
Torvid Kiserud
1,2
*, Gilda Piaggio
3,4
*, Guillermo Carroli
5
, Mariana Widmer
6
*,
Jose
´Carvalho
4
, Lisa Neerup Jensen
7
, Daniel Giordano
5
, Jose
´Guilherme Cecatti
8
,
Hany Abdel Aleem
9
, Sameera A. Talegawkar
10
, Alexandra Benachi
11
, Anke Diemert
12
,
Antoinette Tshefu Kitoto
13
, Jadsada Thinkhamrop
14
, Pisake Lumbiganon
14
, Ann Tabor
7
,
Alka Kriplani
15
, Rogelio Gonzalez Perez
16
, Kurt Hecher
12
, Mark A. Hanson
17
, A.
Metin Gu
¨lmezoglu
6
, Lawrence D. Platt
18,19
1Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway, 2Department
of Clinical Science, University of Bergen, Bergen, Norway, 3Medical Statistics Department, London School
of Hygiene &Tropical Medicine, London, United Kingdom, 4Statistika Consultoria, São Paulo, Brazil,
5Centro Rosarino de Estudios Perinatales, Rosario, Argentina, 6Department of Reproductive Health
and Research, UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development
and Research Training in Human Reproduction, World Health Organization, Geneva, Switzerland,
7Center of Fetal Medicine, Department of Obstetrics, Rigshospitalet, Copenhagen University, Copenhagen,
Denmark, 8Department of Obstetrics and Gynecology, School of Medical Sciences, University of Campinas,
Campinas, Brazil, 9Department of Obstetrics and Gynecology, Faculty of Medicine, Assiut University,
Assiut, Egypt, 10 Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health,
George Washington University, Washington, District of Columbia, United States of America, 11 Service
de Gynecologie Obstetrique, Ho
ˆpital Antoine-Be
´cle
`re, AP-HP, Universite
´Paris Sud, Clamart, France,
12 Department for Obstetrics and Fetal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg,
Germany, 13 E
´cole de Sante
´Publique, Faculte
´de Medecine, Universite
´de Kinshasa, Kinshasa, Democratic
Republic of the Congo, 14 Department of Obstetrics and Gynecology, Faculty of Medicine, Khon Kaen
University, Khon Kaen, Thailand, 15 Department of Obstetrics and Gynecology, All India Institute of Medical
Sciences, New Delhi, India, 16 Divisio
´n de Obstetricia y Ginecologı
´a, Escuela de Medicina, Pontificia
Universidad Cato
´lica de Chile, Santiago, Chile, 17 Institute of Developmental Sciences, University of
Southampton, Southampton, United Kingdom, 18 David Geffen School of Medicine, University of California,
Los Angeles, Los Angeles, California, United States of America, 19 Center for Fetal Medicine and Women’s
Ultrasound, Los Angeles, California, United States of America
*torvid.kiserud@uib.no (TK); gilda.piaggio@gmail.com (GP); widmerm@who.int (MW)
Abstract
Background
Perinatal mortality and morbidity continue to be major global health challenges strongly
associated with prematurity and reduced fetal growth, an issue of further interest given the
mounting evidence that fetal growth in general is linked to degrees of risk of common non-
communicable diseases in adulthood. Against this background, WHO made it a high priority
to provide the present fetal growth charts for estimated fetal weight (EFW) and common
ultrasound biometric measurements intended for worldwide use.
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 1 / 36
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OPEN ACCESS
Citation: Kiserud T, Piaggio G, Carroli G, Widmer
M, Carvalho J, Neerup Jensen L, et al. (2017) The
World Health Organization Fetal Growth Charts: A
Multinational Longitudinal Study of Ultrasound
Biometric Measurements and Estimated Fetal
Weight. PLoS Med 14(1): e1002220. doi:10.1371/
journal.pmed.1002220
Academic Editor: Jenny E. Myers, University of
Manchester, UNITED KINGDOM
Received: April 21, 2016
Accepted: December 13, 2016
Published: January 24, 2017
Copyright: ©2017 Kiserud 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.
Data Availability Statement: Data are available
upon request from Ms. Catherine Hamill
(hamillc@who.int).
Funding: UNDP/UNFPA/UNICEF/WHO/World Bank
Special Programme of Research, Development and
Research Training in Human Reproduction,
Department of Reproductive Health and Research,
World Health Organization. The funders had no role
in study design, data collection and analysis,
Methods and Findings
We conducted a multinational prospective observational longitudinal study of fetal growth in
low-risk singleton pregnancies of women of high or middle socioeconomic status and with-
out known environmental constraints on fetal growth. Centers in ten countries (Argentina,
Brazil, Democratic Republic of the Congo, Denmark, Egypt, France, Germany, India, Nor-
way, and Thailand) recruited participants who had reliable information on last menstrual
period and gestational age confirmed by crown–rump length measured at 8–13 wk of gesta-
tion. Participants had anthropometric and nutritional assessments and seven scheduled
ultrasound examinations during pregnancy. Fifty-two participants withdrew consent, and
1,387 participated in the study.
At study entry, median maternal age was 28 y (interquartile range [IQR] 25–31), median
height was 162 cm (IQR 157–168), median weight was 61 kg (IQR 55–68), 58% of the
women were nulliparous, and median daily caloric intake was 1,840 cal (IQR 1,487–2,222).
The median pregnancy duration was 39 wk (IQR 38–40) although there were significant
differences between countries, the largest difference being 12 d (95% CI 8–16). The median
birthweight was 3,300 g (IQR 2,980–3,615). There were differences in birthweight between
countries, e.g., India had significantly smaller neonates than the other countries, even after
adjusting for gestational age. Thirty-one women had a miscarriage, and three fetuses had
intrauterine death.
The 8,203 sets of ultrasound measurements were scrutinized for outliers and leverage
points, and those measurements taken at 14 to 40 wk were selected for analysis. A total of
7,924 sets of ultrasound measurements were analyzed by quantile regression to establish
longitudinal reference intervals for fetal head circumference, biparietal diameter, humerus
length, abdominal circumference, femur length and its ratio with head circumference and
with biparietal diameter, and EFW. There was asymmetric distribution of growth of EFW: a
slightly wider distribution among the lower percentiles during early weeks shifted to a notably
expanded distribution of the higher percentiles in late pregnancy.
Male fetuses were larger than female fetuses as measured by EFW, but the disparity
was smaller in the lower quantiles of the distribution (3.5%) and larger in the upper quantiles
(4.5%). Maternal age and maternal height were associated with a positive effect on EFW,
particularly in the lower tail of the distribution, of the order of 2% to 3% for each additional 10
y of age of the mother and 1% to 2% for each additional 10 cm of height. Maternal weight
was associated with a small positive effect on EFW, especially in the higher tail of the distri-
bution, of the order of 1.0% to 1.5% for each additional 10 kg of bodyweight of the mother.
Parous women had heavier fetuses than nulliparous women, with the disparity being greater
in the lower quantiles of the distribution, of the order of 1% to 1.5%, and diminishing in the
upper quantiles. There were also significant differences in growth of EFW between coun-
tries. In spite of the multinational nature of the study, sample size is a limiting factor for gen-
eralization of the charts.
Conclusions
This study provides WHO fetal growth charts for EFW and common ultrasound biometric
measurements, and shows variation between different parts of the world.
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 2 / 36
decision to publish, or preparation of the
manuscript.
Competing Interests: I have read the journal’s
policy and the authors of this manuscript have the
following competing interests: GP is a WHO
statistical consultant and has a contract to give
statistical support to the Fetal Growth Study. GP
has worked with WHO for 15 years and has a
relationship with WHO, both paid (contracts) and
unpaid. GP is also a good friend of many of the
investigators involved in this study. LDP is a Board
Member of the Perinatal Quality Foundation, a
nonprofit organization related to the Society for
Maternal Fetal Medicine. LDP has received
research support from General Electric Medical
Systems unrelated to fetal growth. LDP also
lectures 1 or 2 times per year at an educational
meeting supported by General Electric Medical
Systems unrelated to fetal growth.
Abbreviations: AC, abdominal circumference; BMI,
body mass index; BPD, biparietal diameter; D. R.
Congo, Democratic Republic of the Congo; EFW,
estimated fetal weight; FL, femur length; HC, head
circumference; HL, humerus length; IQR,
interquartile range; LMP, last menstrual period; TI,
thermal index.
Author Summary
Why Was This Study Done?
• Small size at birth is associated with perinatal mortality, child morbidity, and adult
health risks, all major global health challenges prioritized by the World Health
Organization.
• Ultrasound estimation of fetal weight before birth is today very widely used in clinical
practice, and, while essential for the identification and management of high-risk preg-
nancies, the current reference ranges used worldwide are largely based on single popula-
tions from a few high-income countries and are therefore of uncertain general
applicability.
• WHO therefore requested new fetal growth charts based on multiple populations to be
made available for general use and at the same time provide a foundation for the grow-
ing initiative to prevent noncommunicable diseases and promote a healthy life course
starting before birth.
What Did the Researchers Do and Find?
• In all, 1,387 healthy women with low-risk pregnancies and unconstrained nutritional
and social background from ten countries in Africa, Asia, Europe, and South America
were included in a longitudinal study of fetal growth.
• During pregnancy, repeated ultrasound measurements were used to establish interna-
tional fetal growth charts for head and abdominal circumference, length of the thigh
bone, and fetal weight, estimated using a combination of the three measurements.
• Fetal growth showed considerable natural variation, differing significantly between
countries. Growth was to a small extent influenced by maternal age, height, weight, and
parity, and by fetal sex.
• Similarly, birthweight varied significantly between countries, even after adjustment for
differences in the length of pregnancy.
What Do These Findings Mean?
• We suggest that these WHO charts for growth in estimated fetal weight are more suit-
able for international use than those commonly applied today. However, the differences
between countries, with maternal factors, and with fetal sex mean that these growth
charts may need to be adjusted for local clinical use to increase their diagnostic and pre-
dictive performance.
• The considerable variation in fetal growth and birthweight which occurs even under
optimal conditions, and which is not explicable in terms of maternal and population fac-
tors, may suggest, first, that such natural variation in offspring size is a collective adap-
tive strategy that has proved extremely successful from an evolutionary point of view
and, second, that major determinants of variation in human development before birth
are still to be determined.
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 3 / 36
• Although the present study encompasses ten countries, it still represents only a small
selection when the substantial anthropometric variations existing even within conti-
nents are taken into account.
Introduction
Global mortality for infants under age 5 y halved from 90 to 43 deaths per 1,000 live births
between 1990 and 2015. This is the result of a tremendous global effort to achieve the UN Mil-
lennium Development Goals [1] and the goals of the UN Secretary-General’s Every Woman
Every Child initiative [2]. Neonatal mortality in the first 28 d declined (by 47%) from 5.0 to 2.6
million deaths annually over this period. Unfortunately, inequality between countries persists,
with 98% of neonatal deaths occurring in low- and middle-income countries [3]. Importantly,
more than 60% of such deaths are associated with low birthweight due to intrauterine growth
restriction or preterm birth or both [4,5]. Ultrasound imaging has become an essential tool for
assuring correct gestational age and for fetal size assessment, increasingly so even in societies
with restricted resources. Correspondingly, evidence is emerging at the population level that
use of ultrasound biometry increases the rate of detection of fetal growth restriction and the
identification of those at increased risk of neonatal morbidity [6].
Birthweight, closely linked to fetal growth, is also a marker of risks for noncommunicable
diseases in adult life, with cardiovascular diseases, type II diabetes, and obesity being the most
prominent [7,8]. While the birthweight gradient across the entire population reflects the distri-
bution of degrees of such risk, it is increasingly evident that it is the developing physiology
associated with fetal growth, rather than birthweight per se, that conditions cardiovascular,
metabolic, endocrine, and neural functions for the life course, and thus long-term health and
disease risks [9]. For this reason, fetal growth data and aspects of intrauterine development
need to be included as an important part of an early-life noncommunicable disease prevention
initiative, as this targets the time when the effect of an intervention is greatest [10].
Ameeting of experts convened by WHO in 2002 reviewed current knowledge on birth-
weight as a health outcome and identified a need for research to develop fetal growth charts for
international use [11]. In 2006, WHO published the multicenter WHO Child Growth Standards
[12] using a prescriptive concept that assumes that, under optimal socioeconomic and nutri-
tional conditions, all children follow one growth standard, regardless of ethnic background.
Some support for this concept was drawn from previous studies [13,14]. Although widely
adopted, the applicability of these child growth standards has been questioned on the grounds
of lack of fit to some populations [15,16], especially for the head circumference standards [17].
Recently, a large multicenter study, the Fetal Growth Longitudinal Study of the Intergrowth-
21st Project [18], applied the same concept and approach to fetal growth. The study presented
growth standards using ultrasound biometric measurements but did not estimate fetal weight
(EFW), even though this is the single most widely used clinical assessment of fetal growth today.
Another large recent study, the NICHD Fetal Growth Studies, showed significant differences in
fetal growth with ethnicity, and established ethnic-specific growth charts [19]. This contradicts
the prescriptive concept that one standard fits all. The study was, however, restricted to four
self-reported ethnic groups of Asian, Hispanic, black, and white women in the US.
The present study is the fetal component of the WHO Multicentre Growth Reference
Study, which aimed to establish growth charts for clinical use based on populations recruited
from multiple countries [20].
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 4 / 36
Methods
Design
This was a multinational observational study approved by the WHO Research Project Review
Panel (RP2) and the WHO Research Ethics Review Committee, secondarily approved by the
national or local ethics review committee for each study center, and correspondingly carried
out according to the Helsinki declaration on ethical principles for medical research in humans
[20,21]. All women were recruited specifically for this study, gave written informed consent at
inclusion, and otherwise followed their conventional antenatal care program separately from
study sessions. Study measurements were revealed to the clinician when the information was
thought to be of importance for the management of the pregnancy. The study protocol was
published previously [20], so here we present a condensed account of the methods. The study
selected participating centers from a range of ethnic and geographical settings, and intended
to recruit 1,400 participants. The sample size calculation procedure was published previously
[20].
Setting
The following centers participated in the study based on the proficient use of ultrasonography:
Centro Rosarino de Estudios Perinatales, Rosario, Argentina; University of Campinas, Campi-
nas, Brazil; University of Kinshasa, Kinshasa, Democratic Republic of the Congo (D. R.
Congo); Rigshospitalet, Copenhagen University, Copenhagen, Denmark; Assiut University,
Assiut, Egypt; Ho
ˆpital Antoine Be
´clère, Paris, France; University Medical Center, Hamburg-
Eppendorf, Germany; All India Institute of Medical Sciences, New Delhi, India; Haukeland
University Hospital, Bergen, Norway; and Khon Kaen University, Khon Kaen, Thailand.
Participants
Participants without known health, environmental, and/or socioeconomic constraints were
invited to participate in the study. Further inclusion criteria were used: living at an altitude
lower than 1,500 m and near the study area (intended to promote compliance for the duration
of the study and any possible follow-up studies); age 18 y and 40 y; body mass index
(BMI) 18–30 kg/m
2
; singleton pregnancy; gestational age at entry between gestational week
8+0 d and 12+6 d according to reliable information on last menstrual period (LMP) and
confirmed by ultrasound measurement of fetal crown–rump length; no history of chronic
health problems; no long-term medication (including fertility treatment); no environmental
or economic constraints likely to impede fetal growth; not smoking currently or in the previ-
ous 6 mo; no history of recurrent miscarriages; no previous preterm delivery (<37 wk) or
birthweight <2,500 g; and no evidence in the present pregnancy of congenital disease or fetal
anomaly at study entry. Fetal anomalies detected during pregnancy or at birth were noted and
verified postnatally. Pregnancies in which small-for-gestation-age fetuses were observed or
intrauterine growth restriction was suspected were also noted. All mothers recruited were fol-
lowed up until the end of the study, apart from those withdrawing consent.
Study Procedures
Women in the first trimester (before week 12+6 d of gestation) attending antenatal care clinics
were approached by members of the study team and asked to participate. They were informed
about the study objectives and procedures. Those who signed the consent form were enrolled
in the study. After the ultrasound scan to assess agreement between gestational age based on
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 5 / 36
LMP and that based on crown–rump length, they were scheduled for fetal biometry scans at
monthly intervals.
All infants had an anthropometric assessment after delivery, including measurement of
birthweight. All pregnant women in the study were asked for a 24-h dietary recall at entry into
the study (and at 28 and 36 wk of gestation) [22]. Clinically relevant conditions (e.g., hyperten-
sion, preeclampsia, and diabetes) occurring during pregnancy and childbirth were noted. Oth-
erwise, no further procedures were added to the routine antenatal care provided at the study
centers.
Gestational Age Assessment
Gestational age was confirmed by measuring the crown–rump length between gestational
week 8 + 0 d and 12 + 6 d based on LMP and recorded as the average of three measurements.
To acquire the crown–rump length, the midline sagittal section of the whole fetus was visual-
ized with the fetus horizontal on the screen at 90 degrees to the angle of insonation. Gestational
age was assessed by using the reference charts published by Robinson and Fleming [23]. The
woman was eligible for the study provided that gestational age by crown–rump length con-
firmed LMP-based age within 7 d. The LMP-based age was used for the analyses.
Ultrasound Measurements
The first visit (dating scan) was between 8 + 0 and 12 + 6 wk, and subsequent visits for fetal
biometry were scheduled at approximately 4-wk (±1 wk) intervals at 14, 18, 24, 28, 32, 36, and
40 wk. All scanning appointments were arranged at the time of the dating scan and study
enrollment. All participants were scanned in the lateral recumbent position.
The compulsory ultrasound measurements obtained at all visits included the following
biometric parameters: biparietal diameter (BPD), head circumference (HC), abdominal cir-
cumference (AC), femur length (FL), and humerus length (HL). At each examination, all mea-
surements were obtained three times from three separately generated ultrasound images and
uploaded electronically (with the associated images) to the data management system. The
median of the three measurements of each parameter was used in the analyses.
In addition, a full morphological evaluation (anomaly scan) was conducted at 18–24 wk fol-
lowing standard practice at each center. Fetuses diagnosed with any anomaly were managed
according to local clinical guidelines. Their ultrasound measurements were included in the
study, and the possible effect on the percentiles derived was evaluated. The following measure-
ment techniques were used. BPD was measured as the outer–inner distance of the parietal
bones in a cross-sectional view of the fetal head at the level of the thalami and cavum septi pel-
lucidi or cerebral peduncles. The cerebellum was not included in the section. The measure-
ment was obtained from an image with the midline echo as close as possible to the horizontal
plane, 90 degrees to the ultrasound beam. HC was obtained from the same image as BPD as
follows: calipers were placed on the outer borders of the occipital and frontal edges of the bone
at the point of the midline of the skull, and the ellipse facility was used to follow the outer
perimeter of the skull to calculate HC. AC was measured in the transverse section of the fetal
abdomen that was as close as possible to circular and that included the stomach and the junc-
tion of the umbilical vein and portal sinus. The anteroposterior and transverse diameters were
then measured with calipers placed on the outer borders of the body outline. The anteroposter-
ior diameter was measured from the spine to the anterior abdominal wall, and the transverse
diameter at a right angle to the anteroposterior diameter. The ellipse facility was used to
calculate AC as outlined above. FL was measured from an image of the full femoral shaft in a
plane close to 90 degrees to the ultrasound beam. The distal femoral epiphysis was excluded.
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 6 / 36
Similarly, HL was measured from an image of the full humeral shaft in a plane close to 90
degrees to the ultrasound beam.
The participating centers used identical ultrasound machines during the project (Voluson
Expert E8, General Electric, Kretz Ultrasound, Zipf, Austria) equipped with two curvilinear
transabdominal transducers (4–8 MHz and 1–5 MHz) and a transvaginal transducer (6–12
MHz), observing that the energy output was set so that thermal index (TI) was <1.0. The TI
was automatically recorded and transmitted to the web-based data management system by the
ultrasound machine.
Measurement results were stored electronically, with the images together with all informa-
tion collected from the mother and the perinatal outcomes. EFW was calculated by including
HC, AC, and FL in Hadlock et al.’s third formula [24]. To facilitate assessment of relative fetal
head size and growth, the ratios FL/HC and FL/BPD were established.
Training and Quality Assurance
The choice of participating centers was based on their proficient use of ultrasound by experi-
enced sonographers. The sonographers participating in the study received specific training
for the study and were certified as proficient under the supervision of a qualified instructor,
according to a standard protocol. All the ultrasound operators had their scans assessed for
quality during their early period in the project. Instruments and techniques used in all centers
were standardized, i.e., equipment and training were provided to each of the measurement
teams.
Maternal Anthropometric and Nutritional Assessment and Birthweight
Weight wearing light clothing was measured using a beam balance with nondetachable weights
and recorded to the nearest 0.1 kg. Height of the mother was measured in the standing posi-
tion using a stadiometer and recorded to the nearest millimeter. If the reading fell between two
values, the lower was recorded.
The 24-h diet recall assessment was carried out by a specifically trained nutritionist or
nurse who asked the study participant about food and beverages consumed during the previ-
ous 24 h [22]. Further details are available elsewhere [20]. Birthweight was assessed at delivery,
and neonatal morphometry carried out within 24 h according to the protocol [20].
Data Management
Data were collected via a web-based data management system developed by Centro Rosarino
de Estudios Perinatales, Rosario, Argentina. All data (clinical, anthropometric, nutritional,
and fetal biometry measurements plus 2-D/3-D images) were stored in a central server compli-
ant with good clinical practice. Data transmission was encrypted to assure data integrity and
patient confidentiality. Access to the web system was password protected, and only authorized
users had access. Data changes were documented by a complete audit trail record kept auto-
matically by the web system (recording when, by whom, and why data were changed). Data
entered into the web system were checked by the coordinating unit at Centro Rosarino de
Estudios Perinatales for completeness, accuracy, reliability, and consistent intended perfor-
mance. Different kinds of validation procedures were carried out (checking missing values
and outliers, cross-checks, cross-time verifications among scanning appointments, and proto-
col compliance). Measurements and 2-D/3-D images corresponding to fetal biometry had
special processing. In collaboration with General Electric Healthcare, Germany, ViewPoint
software was installed at all participating centers, allowing a standard interface/procedure for
scans and an automatic transfer of fetal biometry measurements/images to the web-based
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 7 / 36
system. Thus, all fetal biometry measurements considered by the protocol were automatically
transferred instead of being entered manually (except for D. R. Congo; there, a complete
checking of values was done by the comparison of images and values entered into the web-
based system). The above mentioned web-based system and procedures have been used in five
previous HRP (UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research,
Development and Research Training in Human Reproduction)/WHO multicenter studies and
are proven to be efficient and compliant with HRP/WHO Standard Operating Procedures as
well as with Title 21 CFR Part 11 of the Code of Federal Regulations, which deals with United
States Food and Drug Administration guidelines on electronic records.
Adjustments of Analyses Compared with the Protocol and Justifications
Compared with the original protocol [20], the following aspects of the study were adjusted.
Reliable information on LMP (confirmed by a measurement of crown–rump length), rather
than ultrasound measured crown–rump length alone, was used as the basis for gestational age
calculation for the following reasons: there is no evidence that ultrasound dating more accu-
rately determines gestational age than a reliable LMP confirmed by crown–rump length; reli-
able LMP is the basis for establishing crown–rump length charts for dating; crown–rump
length dating translates natural variation of size into variation of gestational age, which is not
desirable for a study of growth; and LMP, not crown–rump length, is the accessible, low-cost
method for gestational age assessment for all women in the world, and for the low-income
areas usually the only one.
The sample size calculation was based on the assumption of normality for the distribution
of ultrasound measurements. However, we used quantile regression, which calculates quantiles
(i.e., percentiles) directly from the observed measurements without making assumptions
about the distribution.
Maternal and fetal conditions occurring during pregnancy were not excluded from the
analysis. The rationale for this was that the reference intervals of this study are intended pri-
marily for clinical use and therefore should reflect the population for which they are intended
as closely as possible. The pregnancy conditions (e.g., complications) that the study population
experienced are those common to low-risk pregnancies around the world. Likewise, excluding
all neonates below the 10th percentile of birthweight, as suggested in the protocol [20], would
by definition remove the 10% of the participants at the bottom of the range (the vast majority
being healthy in this low-risk cohort) and cause a corresponding distortion of the new growth
charts, i.e., a substantial upward shift of all the lowest percentiles (10, 5, 2.5, and 1) in the direc-
tion of supernormal.
Given the plethora of measurements, we prioritized clinical usefulness in the analyses and
results presented here (e.g., EFW and common biometric measurements) and left the follow-
ing for secondary studies and publications: transverse cerebellar diameter, fetal foot length,
3-D ultrasound acquisitions, maternal anthropometric measurements except height and
weight, the second and third sets of dietary 24-h-recall data (at 28 and 36 wk of gestation), and
newborn anthropometric measurements except birthweight.
Data Analysis and Statistical Methods
Descriptive statistics were calculated for the women’s characteristics at study entry, for mode
of delivery, for birth events, and for fetal, neonatal, and maternal conditions, by country and
overall. Protocol compliance was evaluated by comparing the dates of the windows of gesta-
tional age defined in the protocol with the dates of actual measurements.
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 8 / 36
The ultrasound measurements were used to estimate reference curves for individual param-
eters (BPD, HC, AC, FL, HL, FL/HC, FL/BPD) and EFW based on Hadlock et al.’s formula 3
[24]. Reference curves were fitted using quantile regression for reference models, as described
by Wei et al. [25] from the work of Koenker [26,27].
The development of reference curves has up to now in general used parametric models,
based on assumptions about distribution and on transformation of the observations to normal
distributions. Advances brought by computer power and by the work of Koenker and others
have made it possible to estimate the distributions directly by estimating their quantiles. Quan-
tile regression is now a well-established technique [26,27], and statistical software is available
to fit quantile regression models. Quantile regression fits a function to each chosen quantile
using linear programming and has the advantage of not imposing any distributional assump-
tions. The asymmetry and kurtosis of the fitted distributions may thus assume any form dic-
tated by the data, even changing with gestational age. In addition, quantile regression is more
robust against the influence of outliers in the data. The flexibility of the fitting and the fact that
any inference drawn is entirely data-driven led us to choose quantile regression as the method
for the construction of reference curves.
The estimated quantiles were smoothed by polynomial functions of gestational age. Full
models fitted a polynomial on gestational age for each country by including interaction terms
between gestational age polynomial and country. Additive terms were included for other
covariates.
The models were checked by the residual analysis produced by the software. Hypotheses on
the overall importance of covariates were formally tested using likelihood ratio or Wald chi-
square tests. In addition, visual inspection of quantile profilers was used to assess the relevance
of each covariate in explaining the variation. To compare the distributions of the different
countries with the overall distribution, we used quantile–quantile plots. We calculated 95%
confidence intervals for the difference between country and global EFW percentiles for partic-
ular gestational ages, using the result that the parameter estimates from quantile regression
were asymptotically normally distributed [28].
Logarithms of ultrasound parameters and EFW were used for the fitting. This was done
only to achieve better numerical accuracy and faster convergence of the fitting algorithm.
After the fitting, the results were retransformed to the original scale. To describe growth asym-
metry, we used the Bowley coefficient of asymmetry [29], based on differences of semi-quartile
ranges relative to the quartile range, for the gestational ages 15 and 40 wk.
Data were analyzed using SAS Software version 9.4 (SAS Institute, Cary, North Carolina,
US) and JMP Pro 12 (SAS Institute, Cary, North Carolina, US).
Results
Participants
A total of 1,439 women were enrolled between October 2009 and September 2014, with data
collection being completed with the last childbirth in April 2015. Of these, 52 (3.6%) withdrew
consent, leaving 1,387 women and their fetuses participating in the study. Table 1 shows the
numbers of women recruited, those withdrawing consent, those lost to follow-up, and those
having miscarriages or intrauterine deaths, by country. Among women lost to follow-up and
with miscarriage or intrauterine death, 10 and 15, respectively, did not contribute ultrasound
information. All women other than those withdrawing consent were included in the growth
curve analyses if they contributed ultrasound information, with the number in this analysis
being 1,362.
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 9 / 36
Population Characteristics
Statistics for participating women’s characteristics, their daily caloric intake, and ethnicity are
presented in Table 2. Median age at study entry was 28 y but varied between 24 y (Argentina
and Egypt) and 32 y (France). Median maternal height ranged from 155 cm (India) to 169 cm
(Germany), and weight from 54 kg (Thailand) to 66 kg (Germany). While overall median BMI
was 23.1 kg/m
2
, the median by country ranged from 21.6 kg/m
2
in Thailand to 25.9 kg/m
2
in
Egypt. Median daily caloric intake in the study group was 1,848 calories according to the 24-h
dietary recall assessment, with Thailand having the lowest median, 1,232 calories, and Egypt
having the highest median, 2,094 calories. The ethnic distribution of the study group was
roughly 20% African (including the peri-Mediterranean Egypt), 20% Asian, and 60% white.
Perinatal Outcomes
Table 3 shows delivery information. The overall rate of spontaneous onset of birth was 67.3%,
with a wide range by country: 28.5% in Brazil to 94.5% in D. R. Congo. There was an overall
cesarean section rate of 32.1%, with a considerable range from 5.5% in D. R. Congo to 70.1%
in Brazil. The occurrence of Apgar score <7 at 5 min was similar in all countries, i.e., 0%–
2.2%. Most of the countries had a similar distribution between female and male neonates
except for Egypt, Germany, and Norway, where about 40% of neonates were female. The inci-
dence of preterm birth varied from 3.6% in Germany to 14.7% in Egypt (p= 0.03 for differ-
ences among countries). It was lowest in D. R. Congo, Denmark, Germany, and Norway and
highest in Egypt and India.
Gestational Age at Birth and Birthweight
Gestational age at birth varied between countries from a median of 38 wk 4 d in India to 40 wk
3 d in Norway (p<0.001 for differences among countries) (Table 3). Norway had the highest
median birthweight (3,575 g), and Denmark and Germany had birthweights approximately
100 g less, while Argentina, Brazil, and France had birthweights 200 g less. There is a group
Table 1. Number of women recruited to the study by country, with withdrawals and discontinuations.
Country Number of Women Recruited Consent Withdrawal Discontinuation
Lost to Follow-Up Miscarriage/Intrauterine
Death*
nPercent nPercent nPercent
Argentina 143 0 0.0 2 1.4 1 0.7
Brazil 157 4 2.5 2 1.3 3 1.9
D. R. Congo 157 15 9.6 6 3.8 10 6.4
Denmark 142 2 1.4 3 2.1 1 0.7
Egypt 180 25 13.9 11 6.1 9 5.0
France 109 1 0.9 9 8.3 2 1.8
Germany 141 0 0.0 2 1.4 0 0.0
India 146 0 0.0 7 4.8 3 2.1
Norway 140 2 1.4 1 0.7 1 0.7
Thailand 124 3 2.4 3 2.4 4 3.2
Total 1,439 52 3.6 46 3.2 34 2.4
*Two medical abortions, 29 miscarriages, and three intrauterine deaths.
D. R. Congo, Democratic Republic of the Congo.
doi:10.1371/journal.pmed.1002220.t001
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 10 / 36
Table 2. Characteristics of the participating women by country at study entry.
Characteristic Statistic Argentina
(N= 143)
Brazil
(N= 153)
D. R.
Congo
(N= 142)
Denmark
(N= 140)
Egypt
(N= 155)
France
(N= 108)
Germany
(N= 141)
India
(N= 146)
Norway
(N= 138)
Thailand
(N= 121)
Total
(N= 1,387)
Age (y) Missing 0 0 0 0 0 0 0 0 0 0 0
Q1 20 27 24 28 22 28 28 25 26 26 25
Median 24 30 27 30 24 32 31 27 28 29 28
Q3 28 33 31 32.5 28 34 33 30 30 32 31
Weight (kg) Missing 0 0 0 1 8 0 0 0 1 1 11
Q1 52 57 53 58 57 57 60 50 59 50 55
Median 58 63 60 62 65 63 66 57 63 54 61
Q3 64 69 66 67 75 69 72 62 71 59.5 68
Height (cm) Missing 0 0 0 1 8 0 0 0 1 1 11
Q1 153 160 157 164 155 162 165 152 165 155 157
Median 157 163 162 168 159 165 169 155 168 157 163
Q3 162 167 165 171 163 170 174 160 173 161 168
BMI (kg/m
2
) Missing 0 0 0 1 8 0 0 0 1 1 11
Q1 21.2 21.6 20.8 20.8 23.5 21.1 21.1 20.0 20.5 20.0 21.0
Median 23.3 23.5 22.9 22.2 25.9 22.9 23.2 23.0 22.2 21.6 23.1
Q3 26.3 25.8 25.6 24.1 29.0 24.5 24.9 25.3 24.9 23.9 25.4
Total calories in
24-h dietary recall
Missing 0 0 0 0 4 10 0 28 1 6 49
Q1 1,666 1,441 1,460 1,584 1,747 1,489 1,674 1,514 1,558 1,004 1,487
Median 1,928 1,709 2,063 1,820 2,094 1,736 1,978 1,831 1,890 1,232 1,848
Q3 2,189 2,148 2,605 2,053 2,525 2,053 2,285 2,194 2,314 1,534 2,222
Ethnicity, n
(percent)
White 143 (100.0) 146 (95.4) 0 (0.0) 140 (100.0) 0 (0.0) 100 (92.6) 136 (96.5) 0 (0.0) 137 (99.3) 0 (0.0) 802 (57.8)
Asian 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 2 (1.4) 146
(100.0)
1 (0.7) 121 (100.0) 270 (19.5)
African 0 (0.0) 7 (4.6) 142 (100.0) 0 (0.0) 133 (85.8) 8 (7.4) 3 (2.1) 0 (0.0) 0 (0.0) 0 (0.0) 293 (21.1)
Other 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 22 (14.2) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 22 (1.6)
Parity
(nulliparous n)
N137 153 142 139 57 108 141 138 138 121 1,274
Missing 6 0 0 1 98 0 0 8 0 0 113
n
(percent)
64 (46.7) 108 (70.6) 51 (35.9) 86 (61.9) 21 (36.8) 51 (47.2) 104 (73.8) 115 (83.3) 67 (48.6) 72 (59.5) 739 (58.0)
BMI, body mass index; D. R. Congo, Democratic Republic of the Congo; Q1, first quartile; Q3, third quartile.
doi:10.1371/journal.pmed.1002220.t002
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 11 / 36
Table 3. Mode of delivery, gestational age at birth and outcomes.
Characteristic Statistic Argentina
(N= 140)
Brazil
(N= 150)
D. R.
Congo
(N= 127)
Denmark
(N= 137)
Egypt
(N= 140)
France
(N= 97)
Germany
(N= 139)
India
(N= 139)
Norway
(N= 136)
Thailand
(N= 114)
All
(N= 1,319)
Neonatal sex (n
female)
N140 148 127 136 132 97 139 137 131 112 1,299
n(percent) 68 (48.6) 70 (47.3) 67 (52.8) 75 (55.1) 54 (40.9) 45 (46.4) 56 (40.3) 67 (48.9) 52 (39.7) 54 (48.2) 608 (46.8)
Apgar <7 at 5
min
N140 147 127 135 136 97 139 138 136 113 1,308
n(percent) 1 (0.7) 1 (0.7) 1 (0.8) 1 (0.7) 3 (2.2) 0 (0.0) 1 (0.7) 1 (0.7) 2 (1.5) 0 (0.0) 11 (0.8)
Preterm
(gestational
age <37 wk)
N140 148 127 137 136 97 139 138 136 114 1,312
n(percent) 12 (8.6) 11 (7.4) 6 (4.7) 8 (5.8) 20 (14.7) 7 (7.2) 5 (3.6) 15 (10.9) 6 (4.4) 9 (7.9) 99 (7.5)
Birthweight (g) N140 148 127 136 117 97 139 137 136 113 1,290
Q1 2,990 2,910 2,850 3,133 3,000 2,965 3,100 2,656 3,348 2,980 2,980
Median 3,328 3,290 3,170 3,462 3,100 3,370 3,480 2,975 3,575 3,130 3,300
Q3 3,620 3,608 3,500 3,790 3,500 3,600 3,820 3,200 3,900 3,400 3,615
Gestational age
(days)
N140 148 127 137 139 97 139 138 136 114 1,315
Q1 270 268 270 272 262 273 273 265 276 267 269
Median 276 273 277 282 271 279 279 270 283 271 276
Q3 281 278 283 287 280 284 285 277 288 278 282
Mode of delivery,
n(percent)
Spontaneous 91 (67.9) 41 (28.5) 120 (94.5) 105 (83.3) 64 (45.7) 80 (85.1) 82 (73.2) 84 (64.1) 113 (91.1) 58 (50.9) 838 (67.3)
Intrapartum
CS
30 (22.4) 33 (22.9) 6 (4.7) 7 (5.6) 16 (11.4) 8 (8.5) 24 (21.4) 20 (15.3) 9 (7.3) 26 (22.8) 179 (14.4)
Elective CS 13 (9.7) 68 (47.2) 1 (0.8) 13 (10.3) 54 (38.6) 6 (6.4) 6 (5.4) 27 (20.6) 2 (1.6) 30 (26.3) 220 (17.7)
Vacuum 0 (0.0) 0 (0.0) 0 (0.0) 11 (8.7) 0 (0.0) 0 (0.0) 25 (22.3) 5 (3.8) 1 (0.8) 0 (0.0) 42 (3.4)
Forceps 6 (4.5) 6 (4.2) 0 (0.0) 0 (0.0) 0 (0.0) 3 (3.2) 2 (1.8) 3 (2.3) 11 (8.9) 0 (0.0) 31 (2.5)
Unknown 0 (0.0) 2 (1.4) 0 (0.0) 1 (0.8) 6 (4.3) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0) 9 (0.7)
CS, cesarean section; D. R. Congo, Democratic Republic of the Congo; Q1, first quartile; Q3, third quartile.
doi:10.1371/journal.pmed.1002220.t003
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 12 / 36
of countries (D. R. Congo, Egypt, and Thailand) with birthweight a median 400 g less than
that of Norway, and lastly India, with birthweight 500 g less. The differences in birthweight
between countries were highly significant for all percentiles (p<0.001 for all). When adjusted
for gestational age at birth, the differences were still significant for all the percentiles (p=
0.0018 for the 5th percentile and p<0.001 for the 10th, 25th, 50th, 75th, 90th, and 95th per-
centiles). The estimated birthweight according to neonatal sex and gestational age is shown in
Table 4.
Maternal Complications and Perinatal Conditions
Conditions occurring in the mother during pregnancy are shown in Table 5, together with
fetal malformations and neonatal conditions. In addition to globally experienced maternal
complications such as preeclampsia, pregnancy-induced hypertension, gestational diabetes,
and anemia, 42 had identified malaria. There was no maternal death. Four small-for-gesta-
tional-age fetuses were identified clinically, of which two were examined using Doppler ultra-
sound; none had abnormal recordings in the umbilical artery or middle cerebral artery, and all
were kept in the analysis. It was registered when neonates needed transmission to the neonatal
intensive care unit, commonly due to prematurity, respiratory distress syndrome, infections,
Table 4. Estimated birthweight percentiles for female and male neonates according to completed ges-
tational week.
Percentile Birthweight (g) by Gestational Age (wk)
Female Male
37 38 39 40 41 42 37 38 39 40 41 42
51,968 2,315 2,575 2,748 2,835 2,834 2,062 2,451 2,723 2,880 2,921 2,845
25 2,493 2,698 2,891 3,072 3,241 3,398 2,705 2,890 3,061 3,218 3,362 3,491
50 2,786 2,990 3,173 3,336 3,479 3,601 2,919 3,153 3,354 3,519 3,650 3,747
75 2,951 3,217 3,443 3,631 3,779 3,888 3,143 3,387 3,608 3,806 3,982 4,134
90 3,181 3,451 3,682 3,871 4,021 4,130 3,450 3,666 3,871 4,067 4,253 4,428
95 3,238 3,593 3,867 4,060 4,171 4,200 3,584 3,813 4,036 4,251 4,459 4,659
doi:10.1371/journal.pmed.1002220.t004
Table 5. Maternal complications, fetal malformations, and neonatal conditions by country.
Condition Argentina
(N= 143)
Brazil
(N= 153)
D. R.
Congo
(N= 142)
Denmark
(N= 140)
Egypt
(N= 155)
France
(N= 108)
Germany
(N= 141)
India
(N= 146)
Norway
(N= 138)
Thailand
(N= 121)
All
(N= 1,387)
Fetal
malformation
§
4 (2.8) 0 (0.0) 0 (0.0) 0 (0.0) 1 (0.6) 1 (0.9) 1 (0.7) 0 (0.0) 1 (0.7) 0 (0.0) 8 (0.6)
Neonatal
condition
19 (13.3) 12 (7.8) 7 (4.9) 10 (7.1) 4 (2.6) 2 (1.9) 9 (6.4) 8 (5.5) 3 (2.2) 9 (7.4) 83 (6.0)
Maternal
complication*
24 (16.8) 10 (6.5) 42 (29.6) 4 (2.9) 3 (1.9) 8 (7.4) 7 (5.0) 23 (15.8) 6 (4.3) 10 (8.3) 137 (9.9)
Data are given as n(percent).
§
One malformation was discovered at birth, here counted as fetal malformation. Sacrococcygeal cyst (1), Jarcho-Levin syndrome (1), clubfoot (1),
polycystic kidneys (1), cardiac malformations (3), cleft palate (1).
*Preeclampsia (22), hypertension (16), gestational diabetes (32), malaria (42), anemia (19), and other (16); some participants had more than one
diagnosis.
D. R. Congo, Democratic Republic of the Congo.
doi:10.1371/journal.pmed.1002220.t005
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 13 / 36
or jaundice. There were three intrauterine deaths and three neonatal deaths, representing a
perinatal mortality of 0.4%.
Compliance with Ultrasound Scans
The median number of ultrasound scans (excluding the study entry screening scan) in all
women was 6 (range 0–7). Compliance by gestational age window as defined in the protocol
is presented in S1 Table, by country and for all countries combined (“Total”). Compliance for
all countries combined in each gestational age window was between 89.1% and 100%; 72%
of the participants had a complete set of all the scheduled scans. In addition, for each of the
measurements BPD, HC, AC, FL, and HL, scans were obtained 2 times for at least 95% of
participants.
Thermal Index
Of the 8,372 scan sessions in the project, 115 had no scans stored and 54 belonged to women
who withdrew consent, leaving 8,203 for the statistics. The median TI was 0.2, and none had
TI 1.0.
Reference Intervals for Biometric Parameters and Estimated Fetal
Weight
Fig 1 presents the overall growth curves for BPD, HC, AC, FL, HL, and EFW, and for the ratios
FL/HC and FL/BPD, based on quantile regression. The corresponding reference values are
shown in Tables 6–13 and in csv format in S1 File.
The distribution of EFW starts with a slight asymmetry to the left (i.e., lower percentiles) in
early pregnancy and ends with a very noticeable right asymmetry (i.e., higher percentiles) in
later pregnancy. The Bowley coefficient of asymmetry [29], based on differences of semi-quar-
tile ranges relative to the quartile range, was −0.016 for gestational age 15 wk and +0.111 for
40 wk.
Influence of Covariates on Growth Percentiles
Fetal sex. Male fetuses were larger than female fetuses as measured by EFW, but the dis-
parity was smaller in the lower quantiles of the distribution (3.5%) and larger in the upper
quantiles (4.5%) (Fig 2and S2 Table, without adjustment for country differences). This differ-
ence in size by fetal sex was significant at the 5% level for all percentiles. EFW reference values
were also established for female and male fetuses separately (Tables 14 and 15) to allow assess-
ment customized according to fetal sex. For example, at gestational week 37, the median EFW
of female fetuses is 84 g lower than that of male fetuses.
Country. Countries differed in EFW (Fig 3). Using country as a covariate in a quantile
regression model, including interaction terms with gestational age, showed significance at the
5% level for all percentiles 5th, 10th, 25th, 50th, 75th, 90th, and 95th (S2 and S3 Tables). This
variation due to country was adjusted for maternal characteristics (mother’s age, parity, height,
and weight, or with BMI substituting the latter two) and sex of the fetus. To assess the relative
contribution of these variables to the variation in EFW, the Wald chi-square statistics in S2
and S3 Tables are informative, e.g., for the 5th percentile (quantile 0.05, first table in S2 Table),
as expected, most of the variation (Wald chi-square = 1,797, 1 df) is due to gestational age (lin-
ear) as the fetus grows, and there is significant curvature (Wald chi-square = 207, 1 df). Coun-
try variation gives Wald chi-square = 36 (9 df); sex of the fetus, 29 (1 df); mother’s height, 26
(1 df); and mother’s age, 22 (1 df), while the Wald chi-square value for weight is negligible. In
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 14 / 36
the same table, the level of significance is listed for these variables, e.g., p<0.001 for country,
highly significant. It is clear that variation due to country also occurs independently of
Fig 1. Percentiles for biparietal (outer–inner) diameter, head circumference, abdominal circumference,
femur length, humerus length, estimated fetal weight, femur length/head circumference ratio, and
femur length/biparietal diameter ratio during gestational weeks 14–40. The percentiles (percent) 1st, 5th,
10th, 50th, 90th, 95th, and 99th (smoothed lines) are based on quantile regression and are shown with the
observed values (grey dots).
doi:10.1371/journal.pmed.1002220.g001
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 15 / 36
maternal characteristics and the sex of the fetus. Fig 3 offers a visualization of country variation
for the 10th, 50th, and 90th percentiles for EFW. Country variation in the other ultrasound
parameters for the 10th, 50th, and 90th percentiles is presented in S2–S6 Figs. Country differ-
ences in EFW percentiles and overall EFW percentiles are presented in S4 Table.
The clinical relevance of the differences between the country quantiles and the global quan-
tiles can be assessed in quantile–quantile plots (Fig 4). These plots are intended to enable the
reader to derive the magnitude of difference in grams for any size and country and percentile.
For example, consider the quantile–quantile plot for the individual country 0.05 quantile (i.e.,
the 5th percentile) for EFW versus the global 0.05 quantile: the 5th percentiles at low values of
EFW cannot be differentiated because of the relative smallness of EFW at early pregnancy (Fig
4). However, at the end of gestation (high values of EFW), the 5th percentile for Norway is
3,200 g, while the overall 5th percentile is 2,800 g; for France it is 2,800 g, and for Egypt, 2,700
g. Similarly, it can be seen that while the 10th percentile for EFW at the end of gestation for
Norway is 3,400 g, it is 2,700 g for India (versus about 3,100 g for the global 10th percentile),
showing that a fetus weighing 3,200 g would be below the 10th percentile for Norway but well
above it for India. The magnitude of the differences among countries can also be appreciated
Table 6. Growth chart for fetal outer–inner biparietal diameter.
Gestational Age (Weeks) Biparietal Diameter (mm) by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 23 24 24 26 27 28 29 30 31
15 26 27 27 29 30 31 32 33 34
16 29 30 30 32 33 35 36 37 38
17 32 33 33 35 36 38 39 40 41
18 35 36 37 38 40 41 43 44 45
19 38 39 40 42 43 45 46 47 48
20 41 42 43 45 47 48 50 51 52
21 44 45 46 48 50 52 53 54 55
22 47 48 50 51 53 55 57 58 59
23 50 52 53 55 57 59 60 61 62
24 53 55 56 58 60 62 64 65 66
25 56 58 59 61 63 65 67 68 69
26 59 60 62 64 66 68 70 71 72
27 62 63 65 67 69 71 73 74 75
28 64 66 67 69 72 74 76 77 78
29 67 68 70 72 74 76 78 80 81
30 69 71 72 74 77 79 81 82 83
31 71 73 74 76 79 81 83 85 86
32 73 75 76 79 81 83 86 87 88
33 75 77 78 81 83 86 88 89 90
34 77 79 80 83 85 88 90 91 92
35 79 80 82 84 87 89 92 93 94
36 80 82 84 86 89 91 93 95 96
37 82 84 85 88 90 93 95 96 97
38 84 85 87 90 92 95 97 98 99
39 85 87 89 92 94 96 99 100 101
40 87 88 90 93 96 98 100 101 102
doi:10.1371/journal.pmed.1002220.t006
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 16 / 36
in Fig 5, where selected country percentiles are shown with the corresponding global percentile
curve.
Maternal age and maternal height. Maternal age and height seem to be associated
with a positive effect on EFW, especially in the lower tail of the distribution, significant at
the 5% level, of the order of 2% to 3% for each additional 10 y of age of the mother and 1%
to 2% for each additional 10 cm of height (S1D and S1F Fig, without adjusting for country
differences).
Maternal weight. Maternal weight seems to be associated with a small positive effect on
EFW, especially in the higher tail of the distribution, significant at the 5% level, of the order of
1% to 1.5% for each additional 10 kg of weight of the mother (S1E Fig, without adjusting for
country differences).
Parity (0 versus 1). Parous women had heavier fetuses than nulliparous women, with
the disparity being much higher in the lower quantiles of the distribution, of the order of 1% to
3%, significant at the 5% level, and subsiding in the upper quantiles (S1C Fig, without adjust-
ing for country differences).
Table 7. Growth chart for fetal head circumference.
Gestational Age (Weeks) Head Circumference (mm) by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 86 88 91 95 100 104 107 110 112
15 97 99 102 106 111 115 119 122 124
16 108 111 114 118 123 128 132 134 137
17 120 123 126 130 135 140 144 147 149
18 132 135 138 143 148 153 157 160 162
19 145 147 150 155 161 166 170 173 175
20 157 159 163 168 173 179 183 186 188
21 169 172 175 180 186 191 196 199 201
22 181 184 187 193 198 204 209 212 214
23 193 196 199 205 210 216 221 224 227
24 204 207 211 216 222 228 233 236 239
25 215 218 222 227 233 239 245 248 251
26 225 228 232 238 244 250 256 259 262
27 234 238 242 248 254 261 267 270 273
28 243 247 251 257 264 270 277 280 283
29 251 256 260 266 273 280 286 290 293
30 259 264 268 274 281 288 295 299 302
31 266 271 275 282 289 296 303 307 311
32 273 278 282 289 296 304 311 315 318
33 279 284 289 295 303 311 318 322 326
34 285 290 295 302 309 317 324 328 332
35 291 296 300 307 315 323 330 335 338
36 296 301 306 313 321 329 336 340 344
37 302 306 311 318 326 334 341 345 349
38 307 311 315 324 332 339 347 350 354
39 313 316 320 329 337 344 352 355 359
40 319 321 325 334 342 350 357 360 363
doi:10.1371/journal.pmed.1002220.t007
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 17 / 36
Influence of Clinical Conditions on Growth Percentiles
Participants for whom clinical conditions occurred during pregnancy and childbirth were
retained in the study. We then assessed the effect of excluding them on the parameter estimates
of the quantiles. We excluded successively maternal conditions, fetal malformations, and neo-
natal conditions and assessed the fit for the global EFW percentiles. The parameter estimates
obtained were indistinguishable.
In order to illustrate variation of the clinically relevant 10th and 90th percentiles for EFW,
we compiled the values (without any formal comparison) for 24, 28, 32, and 36 wk of gestation
from the present study, the NICHD Fetal Growth Studies [19], a study from D. R. Congo [30],
and another study from Norway [31] (Table 16). Since the other existing multinational study,
the Fetal Growth Longitudinal Study of the Intergrowth-21st Project, did not publish EFW but
rather AC, which is a major determinant for EFW, we also compiled 10th and 90th percentiles
for AC from relevant studies [18,19,30,32–34] (Table 17).
Discussion
In this paper we present the WHO fetal growth charts for EFW and common ultrasound bio-
metric measurements intended for international use. They reveal a wide range of variation in
Table 8. Growth chart for fetal abdominal circumference.
Gestational Age (Weeks) Abdominal Circumference (mm) by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 69 71 73 77 81 86 89 92 95
15 79 81 83 87 92 96 100 103 106
16 89 91 93 98 103 108 112 115 118
17 99 102 104 109 114 119 124 127 130
18 110 113 116 121 126 131 136 139 142
19 121 124 127 132 138 143 148 152 155
20 132 136 139 144 150 155 161 164 167
21 143 147 150 156 162 168 173 177 180
22 154 159 162 167 173 180 186 189 193
23 165 170 173 179 185 192 198 202 205
24 176 181 184 190 197 203 210 214 217
25 186 191 195 201 208 215 222 226 229
26 196 201 205 212 219 226 233 238 241
27 206 211 215 222 230 237 245 249 253
28 215 220 225 232 240 248 256 260 264
29 224 229 234 242 250 258 266 271 276
30 233 238 243 251 260 269 277 282 287
31 241 246 252 260 269 279 287 292 298
32 249 254 260 269 279 288 298 303 308
33 257 262 269 278 288 298 308 313 319
34 265 270 277 287 298 308 318 324 330
35 273 279 286 297 307 318 329 335 342
36 282 287 294 306 317 329 340 346 353
37 290 296 304 316 328 340 352 358 365
38 299 306 313 326 338 351 364 371 378
39 309 316 324 337 350 363 377 384 392
40 319 327 335 349 363 377 391 399 406
doi:10.1371/journal.pmed.1002220.t008
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 18 / 36
human fetal growth across different parts of the world. Significant differences in fetal growth
between countries are confirmed by differences in birthweight. Furthermore, the study shows
that intrauterine growth is influenced by fetal sex and by maternal age, height, weight, and
parity, although these influences explain only partially the differences in growth between
countries.
The primary motivation for this study, the fetal component of the WHO Multicentre
Growth Reference Study [11], was the need for clinical reference intervals applicable interna-
tionally, including for areas of the world where perinatal morbidity and mortality are high,
hence the multinational design. Driven by the same motivation, we prioritized ultrasound
measurements in common clinical use worldwide, the most prominent being EFW (Fig 1;
Table 11). The use of estimated weight in grams is simple and intelligible, which enhances clin-
ical management, facilitates communication within the health care system, and is valuable
when counselling patients. In addition to the other common measurements in daily use (BPD,
HC, AC, and FL) (Fig 1; Tables 6–9), we established reference intervals for the ratios FL/HC
and FL/BPD aimed at facilitating the identification and monitoring of disproportionate fetal
head development, e.g., hydrocephaly or microcephaly (Fig 1; Tables 12 and 13). The diagnosis
in pregnancies complicated by such conditions is often hampered by uncertainty about
gestational age since head size (BPD and HC) is also commonly used for the dating of the
Table 9. Growth chart for fetal femur length.
Gestational Age (Weeks) Femur Length (mm) by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 10 10 11 12 13 14 15 16 17
15 12 13 14 15 16 17 18 19 20
16 15 16 17 18 19 20 22 22 23
17 19 19 20 21 22 24 25 26 26
18 22 22 23 24 26 27 28 29 30
19 25 26 26 28 29 30 31 32 33
20 28 29 30 31 32 33 35 35 36
21 31 32 33 34 35 36 38 38 39
22 34 35 35 37 38 39 40 41 42
23 36 37 38 39 41 42 43 44 45
24 39 40 41 42 43 45 46 47 47
25 41 42 43 44 46 47 48 49 50
26 43 44 45 46 48 49 51 51 52
27 46 46 47 49 50 52 53 54 55
28 48 48 49 51 52 54 55 56 57
29 50 50 51 53 54 56 57 58 59
30 51 52 53 55 56 58 60 60 61
31 53 54 55 57 59 60 62 63 64
32 55 56 57 59 61 62 64 65 66
33 57 58 60 61 63 65 66 67 68
34 59 60 61 63 65 67 68 69 70
35 61 62 63 65 67 69 70 71 73
36 63 64 65 67 69 70 72 73 75
37 65 66 67 68 70 72 74 75 76
38 66 67 68 70 72 74 75 77 78
39 67 68 69 70 73 75 76 78 79
40 68 68 69 70 73 75 77 78 79
doi:10.1371/journal.pmed.1002220.t009
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 19 / 36
pregnancy. FL/HC and particularly FL/BPD are less dependent on gestational age after 20 wk
of gestation (Fig 1) and may therefore have diagnostic utility.
A strength of the new growth charts provided by the study (Tables 6–15) is that they are
based on multinational data, i.e., ten countries, and therefore are more likely to be applicable
internationally than previously published reference intervals for EFW based on single coun-
tries. A recent sizeable study found significant variation in fetal growth between Asian, black,
Hispanic, and white ethnic groups, with Asian fetuses being the smallest and white fetuses the
largest, justifying ethnic-specific growth charts [19]. However, that study was confined to the
US. Table 16 demonstrates the relation between studies for the clinically important 10th and
90th percentiles for EFW. The WHO growth chart for all countries lies in the middle of them.
Although the present study was not designed to investigate ethnic differences, a limited record
of participants’ ethnicity showed a distribution largely according to country (Table 2). Interest-
ingly, there was a significant difference in the growth of EFW between countries that was not
explained by maternal factors (Fig 3;S2 Table). While ethnic differences may play a role in this
variation, as for the US-based study [19], variation could also be due to differences in diet and
cultural and socioeconomic factors commonly associated with particular ethnic groups. These
may also have played a role in the US-based study.
Table 10. Growth chart for fetal humerus length.
Gestational Age (Weeks) Humerus Length (mm) by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 10 11 11 12 14 15 16 16 17
15 13 13 14 15 16 18 19 19 20
16 16 16 17 18 19 21 22 22 23
17 19 19 20 21 23 24 25 25 26
18 22 22 23 24 26 27 28 28 29
19 25 25 26 27 28 30 31 31 32
20 27 28 29 30 31 32 33 34 35
21 30 31 31 33 34 35 36 37 38
22 32 33 34 35 36 37 39 39 40
23 34 35 36 37 38 40 41 42 42
24 36 37 38 39 41 42 43 44 45
25 38 39 40 41 42 44 45 46 47
26 40 41 42 43 44 46 47 48 49
27 42 43 43 45 46 47 49 50 51
28 43 44 45 46 48 49 51 52 52
29 45 46 47 48 49 51 52 53 54
30 46 47 48 50 51 53 54 55 56
31 48 49 50 51 53 54 56 57 58
32 49 50 51 53 54 56 57 59 59
33 51 52 53 54 56 58 59 60 61
34 53 53 54 56 58 59 61 62 63
35 54 55 56 57 59 61 62 63 64
36 55 56 57 59 61 62 64 65 66
37 56 57 58 60 62 64 65 66 67
38 57 58 59 61 63 65 66 67 68
39 58 59 60 62 64 65 67 68 69
40 57 58 60 62 64 66 68 69 69
doi:10.1371/journal.pmed.1002220.t010
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 20 / 36
Another recently published multinational study by the Intergrowth-21st Project presented
biometric growth but not EFW data [18]. We therefore present variation in AC, which is
closely linked to EFW and is an important predictor of perinatal outcome [6], for the com-
monly used cutoffs, the 10th and 90th percentiles (Table 17). Interestingly, the 10th percentile
for the Intergrowth-21st Project results seems to fall below that of the WHO study, even
though the Intergrowth-21st Project study was carried out according to a strictly “prescriptive”
concept to establish so-called optimal fetal growth (low-risk pregnancies with no environmen-
tal and nutritional constraints, and excluding all conditions during pregnancy and childbirth
that may be associated with effects on fetal growth). The WHO study had a similar recruitment
but retained in the analysis pregnancies with maternal, fetal, and neonatal clinical conditions,
based on the principle that reference intervals should reflect as closely as possible the popula-
tion to which they will be applied. Furthermore, we assessed the effect of removing such preg-
nancies from the dataset and found no identifiable effect on the percentiles. As seen from
Table 17, it is as if rigorous selection and exclusions have limited effect, and other uncontrolled
factors are responsible for the variation between studies and countries. Apart from random
error, systematic error due to differences in ultrasound measurement techniques could influ-
ence the differences between the studies. However, these studies had well-trained ultrasound
Table 11. Growth chart for estimated fetal weight regardless of fetal sex.
Gestational Age (Weeks) Estimated Fetal Weight (g) by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 70 73 78 83 90 98 104 109 113
15 89 93 99 106 114 124 132 138 144
16 113 117 124 133 144 155 166 174 181
17 141 146 155 166 179 193 207 217 225
18 174 181 192 206 222 239 255 268 278
19 214 223 235 252 272 292 313 328 340
20 260 271 286 307 330 355 380 399 413
21 314 327 345 370 398 428 458 481 497
22 375 392 412 443 476 512 548 575 595
23 445 465 489 525 565 608 650 682 705
24 523 548 576 618 665 715 765 803 830
25 611 641 673 723 778 836 894 938 970
26 707 743 780 838 902 971 1,038 1,087 1,125
27 813 855 898 964 1,039 1,118 1,196 1,251 1,295
28 929 977 1,026 1,102 1,189 1,279 1,368 1,429 1,481
29 1,053 1,108 1,165 1,251 1,350 1,453 1,554 1,622 1,682
30 1,185 1,247 1,313 1,410 1,523 1,640 1,753 1,828 1,897
31 1,326 1,394 1,470 1,579 1,707 1,838 1,964 2,046 2,126
32 1,473 1,548 1,635 1,757 1,901 2,047 2,187 2,276 2,367
33 1,626 1,708 1,807 1,942 2,103 2,266 2,419 2,516 2,619
34 1,785 1,872 1,985 2,134 2,312 2,492 2,659 2,764 2,880
35 1,948 2,038 2,167 2,330 2,527 2,723 2,904 3,018 3,148
36 2,113 2,205 2,352 2,531 2,745 2,959 3,153 3,277 3,422
37 2,280 2,372 2,537 2,733 2,966 3,195 3,403 3,538 3,697
38 2,446 2,536 2,723 2,935 3,186 3,432 3,652 3,799 3,973
39 2,612 2,696 2,905 3,135 3,403 3,664 3,897 4,058 4,247
40 2,775 2,849 3,084 3,333 3,617 3,892 4,135 4,312 4,515
doi:10.1371/journal.pmed.1002220.t011
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 21 / 36
operators specifically instructed for the research procedure using internationally accepted
techniques, and this should minimize such error.
Another strength of the present WHO study is the use of quantile regression to establish
the reference intervals. Quantile regression makes an inference about regression coefficients
for the conditional quantiles of a variable without making assumptions about its distribution:
there is no need to assume a particular distribution and to estimate its moments. In conse-
quence, it provides a more direct representation of the observed measurements. This is nicely
demonstrated in a recent large study establishing population-specific fetal growth charts [35].
The technique is especially useful when the quantiles vary differently with a covariate such as,
in the present study, gestational age. In addition, the method is robust against the effect of out-
liers and can capture important features of the data that might be missed by models that aver-
age across the conditional distribution [25].
Quantile regression is particularly useful in studying distribution changes, and shows in the
present study that fetal growth in the population is not symmetrical with gestation. Starting
with a higher distribution towards the lower percentiles, EFW shifts to an expanded distribu-
tion among the higher percentiles and ends with a noticeable asymmetry near term. The Bow-
ley coefficient for asymmetry changed from −0.016 to +0.111 during that period. We are not
sure of the nature of the small negative asymmetry in early pregnancy, but speculate that
Table 12. Growth chart for fetal femur length/head circumference ratio.
Gestational Age (Weeks) Femur Length/Head Circumference Ratio by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 0.50 0.52 0.53 0.54 0.56 0.57 0.59 0.59 0.60
15 0.54 0.55 0.56 0.57 0.59 0.60 0.61 0.62 0.62
16 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.64
17 0.60 0.60 0.61 0.62 0.63 0.64 0.65 0.65 0.66
18 0.62 0.62 0.63 0.64 0.65 0.66 0.66 0.67 0.67
19 0.64 0.64 0.65 0.65 0.66 0.67 0.68 0.68 0.68
20 0.65 0.66 0.66 0.67 0.67 0.68 0.69 0.69 0.69
21 0.66 0.67 0.67 0.68 0.68 0.69 0.69 0.70 0.70
22 0.67 0.67 0.68 0.68 0.69 0.69 0.70 0.70 0.71
23 0.68 0.68 0.68 0.69 0.69 0.70 0.70 0.71 0.71
24 0.68 0.69 0.69 0.69 0.70 0.70 0.71 0.71 0.71
25 0.69 0.69 0.69 0.70 0.70 0.71 0.71 0.71 0.72
26 0.69 0.69 0.69 0.70 0.70 0.71 0.71 0.72 0.72
27 0.69 0.69 0.70 0.70 0.71 0.71 0.72 0.72 0.72
28 0.69 0.70 0.70 0.70 0.71 0.71 0.72 0.72 0.72
29 0.70 0.70 0.70 0.71 0.71 0.72 0.72 0.72 0.73
30 0.70 0.70 0.70 0.71 0.71 0.72 0.72 0.73 0.73
31 0.70 0.70 0.71 0.71 0.72 0.72 0.73 0.73 0.73
32 0.70 0.71 0.71 0.72 0.72 0.73 0.73 0.73 0.74
33 0.71 0.71 0.71 0.72 0.72 0.73 0.73 0.74 0.74
34 0.71 0.71 0.72 0.72 0.73 0.73 0.74 0.74 0.74
35 0.71 0.72 0.72 0.73 0.73 0.74 0.74 0.74 0.75
36 0.72 0.72 0.72 0.73 0.73 0.74 0.74 0.75 0.75
37 0.72 0.72 0.73 0.73 0.74 0.74 0.74 0.75 0.75
38 0.72 0.72 0.73 0.73 0.74 0.74 0.75 0.75 0.75
39 0.72 0.72 0.73 0.73 0.74 0.74 0.75 0.75 0.75
40 0.71 0.72 0.72 0.73 0.73 0.74 0.75 0.75 0.75
doi:10.1371/journal.pmed.1002220.t012
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 22 / 36
regulatory functions, such as the process of maternal constraint of fetal growth, change
through gestation, i.e., fetuses in the higher percentiles may be exposed to greater influences,
which vary with maternal characteristics. This corroborates the differential effects of covariates
across the percentiles shown in S1 Fig. We believe that studying distribution dynamics may
yield more information on the control of fetal growth.
The study confirmed the biologically interesting facts that fetal sex and maternal height,
weight, parity, and age significantly influence fetal growth [31,36,37]. Together with the coun-
try differences, the ethnic differences shown in the US population [19], and, not least, the sub-
stantial variation in birthweight among carefully selected low-risk pregnancies, these findings
document a diversity and plasticity in human prenatal growth dynamics that is only partially
understood. There is increasing evidence linking fetal development, and proxies of develop-
ment such as birthweight, to postnatal health and life course risk of disease [7,9]. This issue is
prioritized by the UN and WHO at a time when noncommunicable diseases are becoming
global epidemics [10,38]. For example, in our study, birthweights in India were significantly
lower than in the other countries, and Indian participants also had the lowest fetal growth and
were the shortest mothers. It is known that body composition in Indian newborns contains
relatively more fat [39], a pattern that passes across generations [40] and that is linked to
Table 13. Growth chart for fetal femur length/biparietal diameter.
Gestational Age (Weeks) Femur Length/Biparietal Diameter Ratio by Percentile
2.5 5 10 25 50 75 90 95 97.5
14 0.71 0.72 0.74 0.76 0.78 0.80 0.82 0.83 0.84
15 0.75 0.76 0.77 0.79 0.81 0.83 0.84 0.85 0.86
16 0.79 0.80 0.81 0.82 0.84 0.85 0.87 0.88 0.88
17 0.82 0.82 0.83 0.85 0.86 0.87 0.89 0.89 0.90
18 0.84 0.85 0.85 0.87 0.88 0.89 0.90 0.91 0.91
19 0.86 0.86 0.87 0.88 0.89 0.90 0.91 0.92 0.92
20 0.87 0.88 0.88 0.89 0.90 0.91 0.92 0.93 0.93
21 0.88 0.89 0.89 0.90 0.91 0.92 0.93 0.93 0.94
22 0.89 0.89 0.90 0.91 0.92 0.92 0.93 0.94 0.94
23 0.89 0.90 0.90 0.91 0.92 0.93 0.94 0.94 0.95
24 0.90 0.90 0.91 0.91 0.92 0.93 0.94 0.94 0.95
25 0.90 0.90 0.91 0.92 0.92 0.93 0.94 0.94 0.95
26 0.90 0.91 0.91 0.92 0.93 0.93 0.94 0.95 0.95
27 0.90 0.91 0.91 0.92 0.93 0.93 0.94 0.95 0.95
28 0.90 0.91 0.91 0.92 0.93 0.94 0.94 0.95 0.95
29 0.90 0.91 0.91 0.92 0.93 0.94 0.94 0.95 0.95
30 0.91 0.91 0.91 0.92 0.93 0.94 0.94 0.95 0.95
31 0.91 0.91 0.92 0.92 0.93 0.94 0.95 0.95 0.95
32 0.91 0.91 0.92 0.93 0.93 0.94 0.95 0.95 0.96
33 0.91 0.92 0.92 0.93 0.94 0.94 0.95 0.96 0.96
34 0.92 0.92 0.92 0.93 0.94 0.95 0.95 0.96 0.96
35 0.92 0.92 0.93 0.93 0.94 0.95 0.95 0.96 0.96
36 0.92 0.93 0.93 0.94 0.94 0.95 0.96 0.96 0.97
37 0.92 0.93 0.93 0.94 0.94 0.95 0.96 0.96 0.97
38 0.92 0.93 0.93 0.94 0.95 0.95 0.96 0.96 0.97
39 0.92 0.92 0.93 0.94 0.94 0.95 0.96 0.96 0.97
40 0.91 0.92 0.92 0.93 0.94 0.95 0.96 0.96 0.97
doi:10.1371/journal.pmed.1002220.t013
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 23 / 36
increased risk of subsequent type 2 diabetes [41]. It seems clear that the understanding of
“optimal” fetal growth needs to incorporate more than birthweight.
To have a single fetal growth chart that fits all pregnancies across the world would require
that all fetuses had the same genetic background for growth, that this genetic background
was reliably expressed in the mother, and that influences such as nutrition, physical activity,
stress, toxicants, and other environmental conditions had similar effects on the genotype in
all embryos and fetuses. This is very unlikely: recent research has revealed a range of interac-
tions between the developmental environment and genetic and epigenetic processes [9]. Even
influences on fetal growth classically thought to be primarily genetic, such as maternal and
paternal height, are complicated by environmental factors. Altitude, climate, geography, other
environmental conditions, and the challenges of daily life and nutrition vary around the
world. Humans adapt across generations to local conditions, and fetal development adds an
important adaptive refinement for the next generation. Secular changes in birthweight and
child growth patterns have been shown to accompany social changes [42,43]. Fetal growth
charts may thus need to be adjusted to fit the diversity of individuals and populations if they
are to be of the greatest clinical utility.
Fig 2. Female and male growth of estimated fetal weight during gestational weeks 14–40. The difference in growth for female (F; red)
and male (M; blue) fetuses is shown by the 5th, 50th, and 95th percentiles for EFW growth. The smoothed lines are based on quantile
regression that includes data from all the participating countries.
doi:10.1371/journal.pmed.1002220.g002
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 24 / 36
While including ten countries in the present WHO study was a strength compared to previ-
ous studies, it still has limitations. The ten population samples, including two in South-East
Asia and two in Africa, were included to increase generalizability, but they are still a very lim-
ited sample of the global human population. Africa alone has a greater genetic diversity than
has the rest of the world [44], and anthropometric variation on that continent is substantial.
The present study showed population differences within the pooled dataset, and so the extent
to which the results can be extrapolated to other populations, which possibly have other
growth dynamics, is at present unknown.
A limitation of the study is that ultrasound measurements were accompanied by a corre-
sponding gestational age exposed on the screen, which could have led to undue changes in the
management of the pregnancy and pregnancy duration. However, it was common practice
among the sonographers and midwives doing the examination not to pay attention to this ges-
tational age because the department was using other reference values than the one on the
screen. On the other hand, part of the ethical commitment of the study was actually to let the
mother be informed of any abnormality or deviation of importance discovered, so that it could
be taken into account for the management of the pregnancy, and to refer the case to the man-
aging clinician. However, the reported referrals were few and were found not to influence the
statistics.
Table 14. Growth chart for estimated fetal weight for female fetuses.
Gestational Age (Weeks) Female Estimated Fetal Weight (g) by Percentile
5 10 25 50 75 90 95
14 73 77 82 89 96 102 107
15 92 97 104 113 121 129 135
16 116 122 131 141 152 162 170
17 145 152 164 176 189 202 211
18 180 188 202 217 233 248 261
19 221 231 248 266 285 304 319
20 269 281 302 322 346 369 387
21 324 339 364 388 417 444 466
22 388 405 435 464 499 530 557
23 461 481 516 551 592 629 660
24 542 567 608 649 697 740 776
25 634 663 710 758 815 865 907
26 735 769 823 880 946 1,003 1,051
27 846 886 948 1,014 1,090 1,156 1,210
28 967 1,013 1,083 1,160 1,247 1,323 1,383
29 1,096 1,150 1,230 1,319 1,418 1,505 1,570
30 1,234 1,296 1,386 1,489 1,601 1,699 1,770
31 1,379 1,451 1,553 1,670 1,796 1,907 1,984
32 1,530 1,614 1,728 1,861 2,002 2,127 2,209
33 1,687 1,783 1,911 2,060 2,217 2,358 2,445
34 1,847 1,957 2,101 2,268 2,440 2,598 2,690
35 2,008 2,135 2,296 2,481 2,669 2,846 2,943
36 2,169 2,314 2,494 2,698 2,902 3,099 3,201
37 2,329 2,493 2,695 2,917 3,138 3,357 3,462
38 2,484 2,670 2,896 3,136 3,373 3,616 3,725
39 2,633 2,843 3,096 3,354 3,605 3,875 3,988
40 2,775 3,010 3,294 3,567 3,832 4,131 4,247
doi:10.1371/journal.pmed.1002220.t014
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 25 / 36
Pooling data is not ideal in the presence of variation among populations, and a single over-
all growth chart will only partially reflect the individual populations included. Figs 4and 5
show the variation of country-specific percentiles compared with the corresponding overall
percentiles of the study and provide an opportunity to assess the magnitude and clinical rele-
vance of the observed variation. Tables 16 and 17 illustrate a similar pattern when compiling
the 10th and 90th percentiles for EFW and AC from various relevant high-quality studies avail-
able for clinical use. Although no formal statistical comparison was undertaken, the results of
these studies illustrate the distribution that can be found around the world. This gives an im-
pression of a wider spread for the 90th percentile than for the 10th. A similar pattern is found
within the WHO study itself: a more obvious diversity between the countries for the 90th per-
centile than for the 10th percentile (Fig 3). As seen from these figures, variation between coun-
tries may increase to several hundred grams towards the end of pregnancy, and may cause
misclassifications when the overall percentile is used. Secondly, it seems that population varia-
tion in growth is more reflected in the 90th percentile than in the lowest percentiles. Thus, it is
possible that the 10th, 5th, and 2.5th percentiles of a pooled study are more universally applica-
ble, while the upper percentiles—90th, 95th, and 97.5th—vary more according to population
Table 15. Growth chart for estimated fetal weight (EFW) for male fetuses.
Gestational Age (Weeks) Male Estimated Fetal Weight (g) by Percentile
5 10 25 50 75 90 95
14 75 79 84 92 99 105 109
15 96 100 107 116 126 134 139
16 121 127 136 146 158 169 175
17 152 158 170 183 197 210 219
18 188 196 210 226 243 260 271
19 232 241 258 277 298 320 333
20 282 293 314 337 362 389 405
21 341 354 380 407 436 469 489
22 408 424 454 487 522 561 586
23 484 503 539 578 619 666 695
24 570 592 635 681 730 785 818
25 666 692 742 795 853 917 956
26 772 803 860 923 990 1,063 1,109
27 888 924 989 1,063 1,141 1,224 1,276
28 1,014 1,055 1,129 1,215 1,305 1,399 1,458
29 1,149 1,197 1,281 1,379 1,482 1,587 1,654
30 1,293 1,349 1,442 1,555 1,672 1,788 1,863
31 1,445 1,509 1,613 1,741 1,874 2,000 2,085
32 1,605 1,677 1,793 1,937 2,085 2,224 2,319
33 1,770 1,852 1,980 2,140 2,306 2,456 2,562
34 1,941 2,032 2,174 2,350 2,534 2,694 2,814
35 2,114 2,217 2,372 2,565 2,767 2,938 3,072
36 2,290 2,404 2,574 2,783 3,002 3,185 3,334
37 2,466 2,591 2,777 3,001 3,238 3,432 3,598
38 2,641 2,778 2,981 3,218 3,472 3,676 3,863
39 2,813 2,962 3,183 3,432 3,701 3,916 4,125
40 2,981 3,142 3,382 3,639 3,923 4,149 4,383
doi:10.1371/journal.pmed.1002220.t015
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 26 / 36
Fig 3. Influence of country on estimated fetal weight. The 10th, 50th, and 90th percentiles for estimated
fetal weight in grams for the ten participating countries, with variation due to country becoming more obvious
towards the end of gestation. Congo, Democratic Republic of the Congo.
doi:10.1371/journal.pmed.1002220.g003
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 27 / 36
Fig 4. Quantile–quantile plots comparing countries’ distributions with the global distribution of
estimated fetal weight. The 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles (Q05, Q10, Q25, Q50,
Q75, and Q90, respectively) for the distribution of each country are plotted versus the same percentiles of the
global distribution (global Q05, global Q10, global Q25, global Q50, global Q75, global Q90, respectively).
Congo, Democratic Republic of the Congo.
doi:10.1371/journal.pmed.1002220.g004
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 28 / 36
characteristics and accordingly will be more in need of adjustment, i.e., customization, for use
at the population level [37].
It follows that whenever the WHO growth charts, or any reference intervals, are applied to
a population, their performance should be checked or tested in order to ensure appropriate
use. It is possible to adjust them by changing cutoffs (e.g., from 10th to 5th percentile) to fit
clinical needs better, and it is possible to customize the percentiles to country, maternal char-
acteristics, and fetal sex to improve diagnostic performance [45]. A further refinement would
be to introduce conditioning terms when using repeated ultrasound measurements for moni-
toring growth [46,47], i.e., narrowing the expected reference interval for an assessment by con-
ditioning it using a previous measurement. WHO is working on these methods to make them
generally available with the growth chart.
Fig 5. Country differences in estimated fetal weight. Selected percentiles for estimated fetal weight (EFW)
for the ten participating countries, showing the magnitude of differences (red, 5th percentile; blue, 50th
percentile; green, 95th percentile; each dot denotes a country).
doi:10.1371/journal.pmed.1002220.g005
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 29 / 36
If such adjustments and refinements do not suffice to make the growth charts fit clinical
needs appropriately, then it may be necessary to establish new high-quality reference intervals
for a population. For example, the WHO growth charts and many others are based on popula-
tions living at altitudes <1,500 m. However, millions of people live at higher altitudes, and
their physiological adaptations include pregnancy and fetal development. It might be that spe-
cific charts will be needed for such populations.
The concept of a “standard,” whether international or national, is often used for instru-
ments and methods to make procedures uniform and to reduce random and systematic error,
rather than to set a standard for a biological parameter such as height or bodyweight for the
population globally. We are inclined to the view that, while the methodology to define refer-
ence ranges or charts for fetal growth needs to be standardized, fetal growth itself is a biological
parameter expected to reflect adaptive processes and to change with development, time, loca-
tion, and environmental conditions. Variation in fetal growth within and between populations
should therefore not be ignored.
To apply any growth chart sensibly requires insight, critical attitude, and pragmatism. We
believe that the present WHO fetal growth charts can be used internationally, particularly
where no local data exist. However, once they are in use, it will be prudent to test the perfor-
mance of the charts in a particular setting in case adjustments, customization, or replacement
with population-specific high-quality reference intervals is needed. With the currently varying
degrees of resources, health, and needs around the world, health care professionals have the
Table 16. The 10th and 90th percentile for estimated fetal weight in relation to other relevant reference
values.
Reference Chart Gestational Week
20 24 28 32 36
10th percentile of EFW (g)
US, white
¶
289 583 1,045 1,686 2,432
D. R. Congo
#
288 576 1,023 1,624 2,310
WHO 286 576 1,026 1,635 2,352
US, black
¶
286 559 985 1,579 2,264
Norway*283 610 1,102 1,730 2,411
US, Hispanic
¶
279 555 987 1,595 2,298
US, Asian
¶
275 546 978 1,574 2,262
90th percentile of EFW (g)
Norway*408 833 1,472 2,304 3,230
US, white
¶
381 771 1,391 2,276 3,368
WHO 380 765 1,368 2,187 3,153
US, Hispanic
¶
379 755 1,353 2,209 3,245
US, black
¶
376 742 1,317 2,135 3,115
US, Asian
¶
373 737 1,318 2,129 3,111
D. R. Congo
#
345 700 1,277 2,083 3,032
Percentiles from the present multinational study (bold), a recent multiethnic national study in the US [19], a
study from D. R. Congo [30], and another study from Norway [31] are listed according to descending values
at 20 wk, but are not formally compared or ranked.
¶
Buck Louis et al. [19].
#
Landis et al. [30].
*Johnsen et al. [31].
D. R., Congo, Democratic Republic of the Congo; EFW, estimated fetal weight.
doi:10.1371/journal.pmed.1002220.t016
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 30 / 36
responsibility of fitting and refining the use of the fetal growth charts to best serve the popula-
tion in their care.
Supporting Information
S1 Fig. Influence of covariates on estimated fetal weight quantiles. (A) Intercept; (B) fetal
sex; (C) parity; (D) maternal age; (E) maternal weight; (F) maternal height; (G) gestational age
linear component; (H) gestational age quadratic component; (I) gestational age cubic compo-
nent. Output of quantile profilers from quantile multivariate regression in the logarithmic
scale, presented as the effect of covariates with 95% confidence bands. For binary variables (sex
of the fetus and parity), the relative change is between the two categories; for continuous vari-
ables, the relative change refers to the increment in EFW resulting from a unit increment of
the independent variable (year for maternal age, kilogram for maternal weight, and centimeter
for maternal height). Gestational age was included in the model with polynomial terms (linear,
quadratic, and cubic).
(DOCX)
Table 17. The 10th and 90th percentile for fetal abdominal circumference in relation to relevant refer-
ence values.
Reference Chart Gestational Week
20 24 28 32 36
10th percentile AC (mm)
US, white
¶
141 185 227 268 306
WHO 139 184 225 260 294
Norway*139 182 223 262 299
US, Asian
¶
139 182 221 260 295
US, Hispanic
¶
138 181 221 262 299
Intergrowth-21st Project
§
138 179 219 257 291
US, black
¶
137 179 217 267 293
Thailand
#
135 177 217 254 290
UK
&
135 175 213 249 283
90th percentile AC (mm)
Norway*165 213 259 303 346
US, white
¶
164 212 258 306 353
US, Hispanic
¶
163 210 255 303 349
WHO 161 210 256 298 340
US, Asian
¶
161 208 252 299 343
Thailand
#
159 208 256 301 339
US, black
¶
159 205 249 295 340
UK
&
158 204 248 290 330
Intergrowth-21st Project
§
158 203 248 291 335
Percentiles from the present multinational study (bold), a recent multinational study (Intergrowth-21st
Project), a recent multiethnic study in the US, and three studies from Norway, Thailand, and the United
Kingdom are listed according to descending values at 20 wk, but are not formally compared or ranked.
¶
Buck Louis et al. [19].
*Johnsen et al. [33].
§
Papageorghiou et al. [18].
#
Sunsaneevithayakul et al. [34].
&
Chitty et al. [32].
AC, abdominal circumference; D. R., Congo, Democratic Republic of the Congo.
doi:10.1371/journal.pmed.1002220.t017
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 31 / 36
S2 Fig. Influence of country on fetal growth expressed as the ultrasound measure biparietal
diameter. Graphs of the 10th, 50th, and 90th percentiles for the ultrasound measure BPD in
millimeters for the ten participating countries.
(TIF)
S3 Fig. Influence of country on fetal growth expressed as the ultrasound measure head cir-
cumference. Graphs of the 10th, 50th, and 90th percentiles for the ultrasound measure HC in
millimeters for the ten participating countries.
(TIF)
S4 Fig. Influence of country on fetal growth expressed as the ultrasound measure abdomi-
nal circumference. Graphs of the 10th, 50th, and 90th percentiles for the ultrasound measure
AC in millimeters for the ten participating countries.
(TIF)
S5 Fig. Influence of country on fetal growth expressed as the ultrasound measure femur
length. Graphs of the 10th, 50th, and 90th percentiles for the ultrasound measure FL in milli-
meters for the ten participating countries.
(TIF)
S6 Fig. Influence of country on fetal growth expressed as the ultrasound measure humerus
length. Graphs of the 10th, 50th, and 90th percentiles for the ultrasound measure HL in milli-
meters for the ten participating countries.
(TIF)
S1 File. Growth charts for the fetal ultrasound measurements biparietal diameter, head
circumference, abdominal circumference, femur length, and humerus length; for esti-
mated fetal weight; and for the ratios femur length/head circumference and femur length/
biparietal diameter in one Excel file.
(XLSX)
S1 Table. Compliance of ultrasound visits with protocol, measured by observed versus
expected.
(DOCX)
S2 Table. Variation of estimated fetal weight quantiles due to country, maternal character-
istics (age, height, weight, and parity), and sex of the fetus. Output from quantile multivari-
ate regression showing Wald chi-square tests for gestational age; country; the interaction of
gestational age and country; sex of the fetus; and maternal characteristics.
(DOCX)
S3 Table. Variation of estimated fetal weight quantiles due to country, maternal character-
istics (age, BMI, and parity), and sex of the fetus. Output from quantile multivariate regres-
sion showing Wald chi-square tests for gestational age; country; the interaction of gestational
age and country; sex of the fetus; and maternal characteristics.
(DOCX)
S4 Table. Comparison of country percentiles with overall percentiles. The 10th, 50th, and
90th percentiles for overall EFW, and the 95% confidence intervals for the difference between
each country’s percentiles and the overall percentiles at 20, 24, 28, 32, and 36 wk of gestational
age. The results should be interpreted with caution (the study was not powered for this analy-
sis; multiplicity of inferences implies that the confidence is much lower than 95%).
(DOCX)
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 32 / 36
Acknowledgments
We thank Mario Merialdi and George Bega for their contributions during the first stages of
the study. We thank General Electric for loaning the ultrasound machines and for providing
technical assistance during the study. We thank Jose
´de Souza Ramos for his contributions to
the programming of descriptive tables and creation of analysis files. The Argentina team
would like to acknowledge ultrasonographers: Sergio Ricci, De
´bora Montoya, Pablo Caño
´n,
Mario Marchetti; nutritionists: Silvina Tosticarelli, Silvia del Cerro; physicians at the primary
care health centers: Malvina Giuliani, Marisa Menighini, Karina Martı
´nez, Virginia Dı
´az, Ana
Paula Bogino, Paola Salina, Fernanda Candio, Duilio Filiberto, Marı
´a Belen Bosch, Eliana
Juan, Guadalupe Moro
´n, Mariela Giraudo, Natalia Blanco, Berenise Macagno; neonatologists
at Maternidad Martin: Ofelia Casas, Gabriela Puig, Lorna Andreuzzi, Marcelo Rodrı
´guez, Sus-
ana Morales, Silvia Carazzone, Andrea Bobatto, Marina Duarte; obstetricians at Maternidad
Martin: Daniel Crosta, Silvia Carbognani; and staff at the Centro Rosarino de Estudios Perina-
tales: Edgardo Abalos, Liana Campodonico, Cristina Cuesta, Hugo Gamerro, Lucia Darder,
Carla Salas, Renata Zanello, Fernando Burgueño. The Brazil team would like to acknowledge
Maria Laura Costa, Carla Silveira, Kleber Cursino Andrade, Cristiane Martins Almeida, Ana
Gabriela Bortoleto, and Daiane Sofia Paulino. The D. R. Congo team would like to acknowl-
edge sonographers Luyeye M. Mandiangu Godefroid and Lokomba Bolamba Victor, site phy-
sicians Kiumbu Nzita and Modeste Luzingu Kinko Joy, study coordinator Bidashimwa
Nzabonimpa Dieudonne
´, nurses Omba Dihandjo Betty and Matondo Lutonadio He
´lène, and
nutritionists Diba Tshilenge Solange and Bauma Juhudi Mamy. The Egypt team would like to
acknowledge Elwany Elsonosy, Mostafa Hussein, Mahmoud A. Abdel-Aleem, and Dina
Habib. The France team would like to acknowledge ultrasonographer Catherine Egoroff. The
Germany team would like to acknowledge study nurse Gudula Hansen. The India team would
like to acknowledge Vatsla Dadhwal. The Norway team would like to acknowledge the local
coordinating physician Synnøve Lian Johnsen; midwives Ine Hildershavn Moen, Guro Kyte
Børsheim, and Jeanette Aasland; and dietitians Gro Trae and Hilde Mollestad Tveit. The Thai-
land team would like to acknowledge site physician and ultrasonographer Kiattisak Kongwat-
tanakul and nutritionist Benja Muktabhant.
Author Contributions
Conceptualization: TK GC JGC HAA SAT AB AD ATK PL AT AK RG KH LDP MAH.
Formal analysis: JC GP DG.
Investigation: TK GC JGC HAA AB AD ATK PL AT AK LNJ JT.
Methodology: TK GC JGC HAA SAT AB AD ATK PL AT AK RG KH LDP JC GP MG MW.
Project administration: MW MG.
Resources: MW MG TK GC JGC HAA AB AD ATK PL AT AK LNJ JT.
Software: DG GP JC.
Supervision: TK.
Visualization: GP JC TK.
Writing – original draft: TK GP GC MW JC LNJ DG JGC HAA SAT AB AD ATK JT PL AT
AK RG KH MAH MG LDP.
WHO Fetal Growth Charts
PLOS Medicine | DOI:10.1371/journal.pmed.1002220 January 24, 2017 33 / 36
Writing – review & editing: TK GP GC MW JC LNJ DG JGC HAA SAT AB AD ATK JT PL
AT AK RG KH MAH MG LDP.
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