Original Research
Obstetrics
Customized vs INTERGROWTH-21st standards for the assessment of birthweight and stillbirth risk at term

https://doi.org/10.1016/j.ajog.2017.12.013Get rights and content

Background

Fetal growth abnormalities are linked to stillbirth and other adverse pregnancy outcomes, and use of the correct birthweight standard is essential for accurate assessment of growth status and perinatal risk.

Objective

Two competing, conceptually opposite birthweight standards are currently being implemented internationally: customized gestation-related optimal weight (GROW) and INTERGROWTH-21st. We wanted to compare their performance when applied to a multiethnic international cohort, and evaluate their usefulness in the assessment of stillbirth risk at term.

Study Design

We analyzed routinely collected maternity data from 10 countries with a total of 1.25 million term pregnancies in their respective main ethnic groups. The 2 standards were applied to determine small for gestational age (SGA) and large for gestational age (LGA) rates, with associated relative risk and population-attributable risk of stillbirth. The customized standard (GROW) was based on the term optimal weight adjusted for maternal height, weight, parity, and ethnic origin, while INTERGROWTH-21st was a fixed standard derived from a multiethnic cohort of low-risk pregnancies.

Results

The customized standard showed an average SGA rate of 10.5% (range 10.1-12.7) and LGA rate of 9.5% (range 7.3-9.9) for the set of cohorts. In contrast, there was a wide variation in SGA and LGA rates with INTERGROWTH-21st, with an average SGA rate of 4.4% (range 3.1-16.8) and LGA rate of 20.6% (range 5.1-27.5). This variation in INTERGROWTH-21st SGA and LGA rates was correlated closely (R = ±0.98) to the birthweights predicted for the 10 country cohorts by the customized method to derive term optimal weight, suggesting that they were mostly due to physiological variation in birthweight. Of the 10.5% of cases defined as SGA according to the customized standard, 4.3% were also SGA by INTERGROWTH-21st and had a relative risk of 3.5 (95% confidence interval, 3.1–4.1) for stillbirth. A further 6.3% (60% of the whole customized SGA) were not SGA by INTERGROWTH-21st, and had a relative risk of 1.9 (95% confidence interval, 3.1–4.1) for stillbirth. An additional 0.2% of cases were SGA by INTERGROWTH-21st only, and had no increased risk of stillbirth. At the other end, customized assessment classified 9.5% of births as large for gestational age, most of which (9.0%) were also LGA by the INTERGROWTH-21st standard. INTERGROWTH-21st identified a further 11.6% as LGA, which, however, had a reduced risk of stillbirth (relative risk, 0.6; 95% confidence interval, 0.5–0.7).

Conclusion

Customized assessment resulted in increased identification of small for gestational age and stillbirth risk, while the wide variation in SGA rates using the INTERGROWTH-21st standard appeared to mostly reflect differences in physiological pregnancy characteristics in the 10 maternity populations.

Introduction

Fetal growth restriction and low birthweight are closely linked to risk of stillbirth and other indicators of adverse perinatal outcome. As these associations have become ever clearer, the focus has shifted to prevention, which requires adequate tools and standards.

Many reference curves and tables have been produced in various settings for the assessment of fetal growth and birthweight. They can vary because of the methods used, the quality of the data they originated from, and whether they were based on longitudinal or cross-sectional, fetal, or neonatal data. They also vary with the physiological and pathological characteristics of the population. Therefore, an approach that has gained traction in recent years is not to base reference curves on the whole population, but to set a standard that seeks to represent the optimal growth and birthweight that can be achieved in the absence of any complications, and that therefore should be better able to detect abnormalities in fetal growth.

Such a standard has been developed as the computer-generated customized GROW chart, which uses coefficients derived from large birthweight databases to predict optimal growth for each mother in each pregnancy.1, 2 Physiological variables such as ethnic origin, maternal size, and parity are adjusted for, and the standard is set at a level that is free from pathology, so that the effect adverse influences such as smoking, hypertension, or diabetes, are better recognized. Because the construction of the standard combines a term optimal weight (TOW) with a proportionality fetal weight curve for all gestations, the same chart can be used for the assessment of fetal growth as well as birthweight. Customized charts have been shown to be internationally applicable,3, 4, 5, 6, 7, 8 are recommended by the Royal College of Obstetricians and Gynecologists,9 and are now increasingly in clinical and international research use. The GROW (Gestation Related Optimal Weight) application has recently been updated with additional coefficients to represent over 100 ethnic or country-of-origin groups.

An alternative approach to derive a standard is that taken by the INTERGROWTH-21st (IG21) project, which selected low-risk, well-nourished mothers with uncomplicated pregnancies. Data were combined from cohorts in 8 countries to produce a single, prescriptive, multiethnic standard for birthweight10, 11 and fetal growth12, 13 to be used universally. The recently published World Health Organization fetal growth project,14 based on data from 10 countries, used similar methodology, but concluded that there were significant differences between populations in maternal characteristics that affected growth. Similarly, the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies15 and other studies16, 17, 18 demonstrated ethnic differences in fetal growth in low-risk pregnancies. Nevertheless, the IG21 standards are being actively promoted and have begun to be implemented in many settings.

We therefore set out to compare the IG21 birthweight standard with the individually customized (GROW) standard in an international cohort based on maternity datasets from 10 countries, to assess how well they were able to associate birthweight with stillbirth risk. We focused our analysis on term data, as preterm birthweight ought to be assessed with a fetal rather than a neonatal weight standard in light of the known associations between prematurity and fetal growth restriction.19, 20, 21

Section snippets

Data source

The Perinatal Institute administers the Gestation Network (www.gestation.net), which is a portal for provision of free software tools including customized centile calculators for local, national, and international use. The applications contain coefficients for adjustment of the growth and weight standard according to maternal characteristics, derived from anonymized databases submitted from clinicians and researchers who wish to have an application suitable for their own local population. To

Results

Details of the 10 datasets are listed in Table 2. Averages with measures of dispersion are provided to illustrate the wide variation in maternal characteristics between country cohorts. Maternal height ranged from 155-170 cm, early pregnancy weight from 54-69 kg, median gestational age at delivery from 273-282 days, and median birthweight from 3040-3610 g.

Also shown is the ethnic group-based TOW predicted for a standard size mother in her first pregnancy at 280 days (TOW1), and the predicted

Comment

This is, to our knowledge, the first multinational comparison of the IG21 and customized birthweight standards. It shows firstly that using IG21, there are wide differences in SGA and LGA rates across the 10 cohorts studied, ranging from 3.1-16.8% for SGA and 5.1-27.5% for LGA rates. As Figures 2 and 3 show, these values are strongly correlated with the TOW calculated by GROW for each cohort, suggesting that IG21 SGA and LGA rates vary mostly due to physiological differences between different

Acknowledgment

We would like to thank the collaborators and their organizations for supplying data for this multinational cohort study: Prof Phurb Dorji and A. Yangden, Jigme Dorji Wangchuck National Referral Hospital, Thimphu, Bhutan; Prof Jun Jim Zhang, Jiao Tong University, Shanghai, China; Prof Birgit Arabin and Dr Bjoern Misselwitz, Geschaeftstelle Qualitaetsicherung Hessen, Eschborn, Germany; Dr Suseela Vavilala and Dr Nuzhat Aziz, Fernandez Hospital, Hyderabad, India; Prof Fergal Malone, Perinatal

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    Disclosure: All authors are employees of the Perinatal Institute, a not-for-profit organization that derives income from the provision of support services to health care organizations, which may include the GROW software for customized growth charts mentioned in this article.

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