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. Author manuscript; available in PMC: 2023 Dec 1.
Published in final edited form as: Am J Obstet Gynecol. 2022 Aug 2;227(6):916–922.e1. doi: 10.1016/j.ajog.2022.07.045

Unified standard for fetal growth velocity: the Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies

Katherine L Grantz 1, Jagteshwar Grewal 2, Sungduk Kim 3, William A Grobman 4, Roger B Newman 5, John Owen 6, Anthony Sciscione 7, Daniel Skupski 8, Edward K Chien 9, Deborah A Wing 10, Ronald J Wapner 11, Angela C Ranzini 12, Michael P Nageotte 13, Sabrina Craigo 14, Stefanie N Hinkle 15, Mary E D’Alton 16, Dian He 17, Fasil Tekola-Ayele 18, Mary L Hediger 19, Germaine M Buck Louis 20, Cuilin Zhang 21, Paul S Albert 22
PMCID: PMC9729377  NIHMSID: NIHMS1838785  PMID: 35926648

OBJECTIVE:

Fetal growth velocity has the potential to improve the identification of fetuses who are failing or who are exceeding their expected rate of growth compared with a single measure of fetal size.1,2 The Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies – Singletons developed a calculator to compute fetal growth velocity standard percentiles for any given set of gestational week intervals in a contemporary, low-risk, and racially or ethnically diverse multisite population in the United States.1 The calculator has the ability to compute velocity percentiles by maternal self-reported race and ethnicity, including non-Hispanic White (NHW), non-Hispanic Black (NHB), Hispanic, and Asian or Pacific Islander (Asian) women, that can be used in concert with race- or ethnic-specific fetal growth standards.3,4 Subsequently, we have provided a unified fetal growth standard to provide a complementary option to the race- or ethnic-specific fetal growth standard.5-7 In the current analysis, we provided a fetal growth velocity standard and calculator to complement our previous work on unified fetal growth size standards.7

STUDY DESIGN:

The cohort included 1737 pregnant individuals without obesity with low-risk prepregnancy and antenatal profiles who delivered at ≥37 weeks of gestation at 12 US clinical sites (2009–2013).3,7,8 The analysis was limited to 1732 eligible individuals (99.7%) with ultrasound measurements, of whom 27.7% identified as NHW, 24.4% identified as NHB, 28.1% identified as Hispanic, and 19.8% identified as Asian. To address the original oversampling by race and ethnicity, the sample was weighted back to the US population distribution of pregnant women using natality statistics, employing the same methods as the unified fetal growth standard for size.7,9 Human subjects’ approval was obtained from all participating sites, and all women provided informed consent before any data collection.

Research ultrasounds were performed at up to 6 visits where fetal biparietal diameter, head circumference (HC), abdominal circumference (AC), humerus, and femur length (FL) were measured following a standardized protocol. Estimated fetal weight (EFW) was calculated from HC, AC, and FL.10 The individual biometrics and EFW were log-transformed to stabilize variances across gestational ages (GAs) and improve normal approximations for error structures. Using GAs 11 to 41 weeks, we fitted a weighted linear mixed model with cubic splines for the fixed effects and a cubic polynomial for the random effects for each biometric measurement and EFW. Weights were chosen in the linear mixed model estimation so that inferences reflected a US-based population concerning race and ethnicity. Of note, 3-knot points (25th, 50th, and 75th percentiles) were chosen at GAs that evenly split the distributions. Velocity was computed and presented in 2 ways: (1) the difference between 2 consecutive weekly measurements and (2) the difference between any 2 measurements divided by the difference between the 2 measurements in weeks. In both cases, percentiles were derived from the fitted linear mixed model. Estimated 50th percentile velocity curves were defined as the mean change in each biometric measurement and EFW per gestational week. For detailed equations for the velocity calculation, see the Appendix. All analyses were implemented using SAS (version 9.4; SAS Institute, Cary, NC) or R (version 4.1.2; http://www.R-project.org).

RESULTS:

After weighting, the racial or ethnic representation of women in the analytical sample was 55.0% for NHW, 12.4% for NHB, 24.5% for Hispanic, and 8.1% for Asian, which is a distribution similar to all 2011 US births. Additional demographic details for the weighted cohort are as previously published.7 Average EFW growth velocity increased from 29 g/wk at 16 weeks, to 59 g/wk at 20 weeks, to 175 g/wk at 30 weeks, reaching a peak of 215 g/wk at 34 to 35 weeks. The 50th percentile for the unified weekly EFW velocity curve was lower than that of the NHW group, similar to the Hispanic group, and higher than the Asian and NHB groups through the peak EFW velocity at 35 weeks (comparative statistical testing not performed) (Figure). Data for weekly growth velocity percentiles for EFW and individual biometrics from weeks 11 to 41 (5th, 10th, 50th, 90th, and 95th percentiles) are presented in the Table.

FIGURE. EFW velocity (g/wk) in the NICHD Fetal Growth Studies – Singletons.

FIGURE

Velocity for the EFW by a unified multiracial or ethnic group, individual maternal self-reported race and ethnicities, and GA. Estimated 10th, 50th, and 90th percentiles for velocity were calculated using parameters from the linear mixed model as discussed in the methods. The unified velocity curve for the entire cohort was weighted for race and ethnicity using the 2011 natality data.9

EFW, estimated fetal weight; GA, gestational age; NICHD, Eunice Kennedy Shriver National Institute of Child Health and Human Development.

TABLE.

Percentiles for fetal growth velocity of anthropometric measurements by GA, Eunice Kennedy Shriver National Institute of Child Health and Human Development Fetal Growth Studies – Singletons

GA (wk) Percentile
5th 10th 50th 90th 95th
Biparietal diameter (mm)
11 2.4 2.6 3.4 4.2 4.4
12 2.4 2.6 3.6 4.6 4.9
13 2.3 2.6 3.7 4.9 5.3
14 2.0 2.4 3.7 5.1 5.5
15 1.7 2.1 3.6 5.2 5.7
16 1.3 1.7 3.4 5.2 5.7
17 0.9 1.4 3.3 5.2 5.8
18 0.6 1.1 3.1 5.2 5.9
19 0.3 0.9 3.1 5.4 6.0
20 0.1 0.8 3.1 5.6 6.3
21 0.0 0.6 3.1 5.7 6.5
22 −0.2 0.5 3.1 5.9 6.7
23 −0.4 0.3 3.1 6.1 6.9
24 −0.7 0.1 3.1 6.2 7.1
25 −0.9 −0.1 3.1 6.3 7.3
26 −1.2 −0.3 3.0 6.4 7.4
27 −1.4 −0.5 2.9 6.5 7.6
28 −1.7 −0.7 2.9 6.6 7.7
29 −1.9 −0.9 2.8 6.6 7.8
30 −2.2 −1.2 2.7 6.7 7.9
31 −2.5 −1.4 2.5 6.7 7.9
32 −2.8 −1.7 2.4 6.6 7.9
33 −3.1 −2.0 2.2 6.6 7.9
34 −3.5 −2.3 2.0 6.5 7.8
35 −3.8 −2.6 1.7 6.3 7.7
36 −4.2 −2.9 1.5 6.2 7.5
37 −4.4 −3.2 1.3 6.0 7.4
38 −4.7 −3.4 1.1 5.9 7.3
39 −4.9 −3.6 1.0 5.9 7.3
40 −5.0 −3.7 0.9 5.8 7.3
41 −5.1 −3.8 0.9 5.8 7.3
Head circumference (mm)
11 8.8 9.5 11.9 14.5 15.3
12 8.9 9.8 12.8 15.9 16.8
13 8.7 9.7 13.2 17.0 18.0
14 8.1 9.2 13.3 17.6 18.9
15 7.1 8.4 13.1 18.0 19.4
16 6.1 7.5 12.7 18.1 19.7
17 4.9 6.5 12.3 18.2 20.0
18 3.9 5.7 11.9 18.4 20.3
19 3.2 5.0 11.8 18.8 20.8
20 2.6 4.6 11.8 19.4 21.6
21 2.0 4.1 11.8 19.9 22.2
22 1.3 3.6 11.8 20.3 22.8
23 0.5 2.9 11.6 20.7 23.4
24 −0.3 2.3 11.4 21.0 23.8
25 −1.1 1.5 11.2 21.2 24.2
26 −2.0 0.7 10.9 21.4 24.5
27 −3.0 −0.1 10.5 21.5 24.7
28 −3.9 −0.9 10.1 21.5 24.9
29 −4.9 −1.7 9.6 21.5 25.0
30 −5.9 −2.6 9.1 21.4 25.0
31 −6.9 −3.5 8.6 21.2 24.9
32 −7.9 −4.5 7.9 20.9 24.7
33 −9.0 −5.5 7.3 20.6 24.4
34 −10.1 −6.5 6.5 20.1 24.1
35 −11.2 −7.5 5.7 19.5 23.6
36 −12.2 −8.5 4.9 19.0 23.1
37 −13.1 −9.4 4.3 18.5 22.6
38 −13.9 −10.1 3.7 18.1 22.3
39 −14.6 −10.7 3.2 17.7 22.0
40 −15.1 −11.2 2.8 17.5 21.8
41 −15.5 −11.6 2.6 17.4 21.7
Abdominal circumference (mm)
11 6.0 6.7 9.4 12.2 13.1
12 6.2 7.1 10.4 13.9 14.9
13 6.1 7.2 11.1 15.3 16.6
14 5.7 7.0 11.6 16.6 18.1
15 5.1 6.6 11.9 17.7 19.3
16 4.3 6.0 12.0 18.5 20.4
17 3.4 5.2 12.0 19.2 21.4
18 2.4 4.4 11.9 19.9 22.3
19 1.4 3.6 11.9 20.6 23.2
20 0.5 2.9 11.8 21.3 24.1
21 −0.6 2.1 11.7 21.9 24.9
22 −1.6 1.2 11.5 22.4 25.6
23 −2.7 0.3 11.2 22.9 26.3
24 −3.8 −0.6 11.0 23.3 27.0
25 −4.8 −1.4 10.8 23.8 27.6
26 −5.7 −2.2 10.6 24.3 28.3
27 −6.6 −2.9 10.5 24.9 29.1
28 −7.4 −3.5 10.6 25.6 30.0
29 −8.0 −4.0 10.7 26.4 31.0
30 −8.7 −4.5 10.9 27.3 32.1
31 −9.5 −5.1 11.0 28.0 33.1
32 −10.3 −5.8 10.9 28.7 33.9
33 −11.3 −6.6 10.8 29.2 34.6
34 −12.4 −7.5 10.5 29.6 35.2
35 −13.6 −8.5 10.0 29.8 35.6
36 −14.8 −9.6 9.5 29.9 35.9
37 −16.0 −10.6 9.0 29.9 36.1
38 −17.1 −11.6 8.6 30.0 36.3
39 −18.1 −12.5 8.1 30.1 36.6
40 −19.1 −13.4 7.8 30.2 36.8
41 −20.1 −14.2 7.4 30.4 37.2
Femur length (mm)
11 1.2 1.3 1.7 2.1 2.3
12 1.5 1.7 2.3 3.0 3.2
13 1.7 1.9 2.9 3.9 4.2
14 1.7 2.0 3.3 4.7 5.1
15 1.4 1.9 3.5 5.2 5.8
16 1.0 1.5 3.5 5.6 6.3
17 0.4 1.0 3.3 5.8 6.6
18 −0.2 0.5 3.1 6.0 6.9
19 −0.7 0.1 3.0 6.2 7.1
20 −1.1 −0.3 2.9 6.5 7.5
21 −1.5 −0.6 2.9 6.7 7.9
22 −2.0 −1.0 2.8 7.0 8.2
23 −2.4 −1.3 2.7 7.2 8.5
24 −2.8 −1.7 2.6 7.4 8.8
25 −3.3 −2.1 2.5 7.5 9.0
26 −3.7 −2.4 2.4 7.7 9.3
27 −4.1 −2.7 2.3 7.8 9.5
28 −4.4 −3.0 2.2 8.0 9.8
29 −4.7 −3.3 2.1 8.2 10.0
30 −5.0 −3.5 2.1 8.4 10.3
31 −5.3 −3.8 2.1 8.6 10.6
32 −5.6 −4.0 2.0 8.8 10.8
33 −6.0 −4.3 2.0 8.9 11.0
34 −6.3 −4.6 1.9 9.0 11.2
35 −6.6 −4.8 1.8 9.1 11.4
36 −6.9 −5.1 1.7 9.2 11.5
37 −7.3 −5.4 1.5 9.2 11.5
38 −7.6 −5.8 1.3 9.2 11.5
39 −8.0 −6.1 1.1 9.0 11.5
40 −8.4 −6.5 0.8 8.9 11.3
41 −8.8 −6.8 0.5 8.6 11.1
Humerus length (mm)
11 1.3 1.4 1.8 2.2 2.4
12 1.6 1.8 2.4 3.1 3.4
13 1.8 2.1 3.0 4.0 4.3
14 1.8 2.1 3.3 4.7 5.1
15 1.5 1.9 3.4 5.2 5.7
16 0.9 1.4 3.3 5.4 6.1
17 0.3 0.9 3.1 5.5 6.2
18 −0.3 0.3 2.8 5.5 6.3
19 −0.8 −0.1 2.6 5.6 6.5
20 −1.2 −0.4 2.5 5.8 6.8
21 −1.6 −0.7 2.5 6.0 7.0
22 −1.9 −1.0 2.4 6.1 7.3
23 −2.3 −1.4 2.3 6.3 7.5
24 −2.7 −1.7 2.2 6.4 7.7
25 −3.0 −2.0 2.0 6.5 7.8
26 −3.4 −2.3 1.9 6.6 8.0
27 −3.7 −2.5 1.8 6.7 8.1
28 −4.0 −2.8 1.7 6.8 8.3
29 −4.3 −3.0 1.7 6.9 8.5
30 −4.5 −3.2 1.6 7.0 8.6
31 −4.8 −3.4 1.6 7.1 8.8
32 −5.0 −3.6 1.5 7.2 9.0
33 −5.2 −3.8 1.5 7.3 9.1
34 −5.5 −4.0 1.4 7.5 9.3
35 −5.7 −4.2 1.4 7.6 9.4
36 −5.9 −4.4 1.3 7.6 9.5
37 −6.2 −4.6 1.2 7.6 9.6
38 −6.5 −4.9 1.0 7.5 9.5
39 −6.8 −5.2 0.8 7.4 9.4
40 −7.2 −5.6 0.5 7.2 9.2
41 −7.5 −5.9 0.1 6.8 8.9
EFW (g)
11 4 5 9 13 14
12 5 6 11 16 18
13 6 8 14 21 23
14 8 10 18 27 29
15 10 13 23 34 37
16 13 16 29 42 47
17 16 20 35 53 58
18 18 23 43 64 71
19 20 27 51 77 85
20 22 30 59 91 101
21 23 32 68 107 118
22 23 34 77 124 138
23 23 36 87 142 159
24 22 38 97 162 181
25 21 39 108 183 206
26 19 40 120 207 233
27 16 41 132 232 263
28 13 41 145 260 295
29 10 41 160 291 330
30 4 40 175 323 368
31 −3 37 189 356 406
32 −14 31 201 388 444
33 −29 21 210 418 480
34 −49 7 215 444 513
35 −73 −12 215 466 541
36 −101 −35 212 484 566
37 −129 −58 208 500 588
38 −158 −82 202 514 608
39 −187 −107 195 527 627
40 −216 −131 189 540 645
41 −244 −154 182 552 664

Week corresponds to exact week (eg, 11 weeks = 11.0 weeks). EFW was calculated using the Hadlock formula.10

EFW, estimated fetal weight; GA, gestational age.

CONCLUSION:

We have provided a unified, multiethnic fetal growth velocity standard to supplement our previous work.3,4,7 This unified EFW velocity curve, which is weighted by race and ethnicity to represent the distribution of US pregnant women in 2011, generally fell below that for the fetuses of NHW women and above those for the fetuses of Asian and NHB women with peak velocity approximately 34 to 35 weeks of gestation. Our findings were generally consistent with other studies of fetal growth velocity, although the magnitude of change and patterns of the timing of accelerated growth and peak velocities for individual biometrics varied by population.11-13 Fetal growth velocity indicates how a fetus arrived at a given EFW (ie, fast or slow growth), which provides additional information beyond that provided by a cross-sectional assessment of EFW at a single time point.1 The week-specific velocity (change per week) is useful for understanding the expected amount of fetal growth between any 2 points during gestation and comparing it across groups. From a clinical perspective, we would not recommend performing sonograms 1 week apart to identify abnormal fetal velocity given that this is not sufficient time to allow actual differences in growth to be disentangled from random variation in fetal growth. However, as in the original velocity article, we presented a calculator that allows for the estimation of relative growth velocity based on any clinically appropriate interval between sonograms.1 The optimal interval for estimating fetal growth velocity and using it to inform clinical practice is currently unknown and is complicated as it reflects the time between measurements and error in the biometric measurement. The interval may also vary based on the outcome of interest. Evidence suggests that fetal growth velocity might better distinguish fetuses that are failing to meet their growth potential from constitutionally small-for-gestational-age fetuses below the 10th percentile for EFW.2 In summary, we provided a multiethnic, unified fetal growth velocity standard and calculator for fetal growth velocity. Future work is needed to determine whether adding growth velocity to traditional fetal size measures improves perinatal outcomes in terms of morbidity and mortality and, if so, whether racial- or ethnic-specific or a unified velocity standard is superior in improving outcomes.

Supplementary Material

supplement

ACKNOWLEDGMENTS

The authors acknowledge the research teams at all participating clinical centers, including ChristinaCare Health Systems; University of California, Irvine; Long Beach Memorial Medical Center; Northwestern University; Medical University of South Carolina; Columbia University; NewYork-Presbyterian Queens; Saint Peters’ University Hospital; the University of Alabama at Birmingham; Women and Infants Hospital of Rhode Island; Fountain Valley Regional Hospital and Medical Center; and Tufts University. The authors also acknowledge Clinical Trials & Surveys Corp and the Emmes Corporation for providing data and imaging support for this multisite study. This work would not have been possible without the assistance of GE Healthcare Women’s Health Ultrasound for their support and training on the Voluson and ViewPoint products during the study.

This research was supported, in part, by the Division of Population Health, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, and, in part, with Federal funds for the NICHD Fetal Growth Studies – Singletons (contract numbers HHSN275200800013C, HHSN275200800002I, HHSN27500006, HHSN275200800003IC, HHSN275200800014C, HHSN275200800012C, HHSN275200800028C, and HHSN275201000009C). P.S.A., K.L.G., J.G., S.K., and F.T.A. have contributed to this work as part of their official duties as employees of the US federal government.

APPENDIX

For a single longitudinal ultrasound measurement, we built a mixed-effects model with cubic spline based on 3-knot points for fixed effects and cubic function for random effects as follow:

Yij=θ0+θ1tij+θ2tij2+θ3tij3+θ4(tijδ1)+3+θ5(tijδ2)+3+θ6(tijδ3)+3+bi0+bi1tij+bi2tij2+bi3tij3+εij (1)

where Yij denotes a log-transformed ultrasound measurement, tij3 is the j th gestational age for i th women, (tijδk)+3=max(0,(tijδk)3), δ = (δ1, δ2, δ3)′, is the knot sequence with δ1 < δ2 < δ3, (1, tij, tij2, tij3, (tijδ1)+3, (tijδ2)+3, (tijδ3)+3) ′ is a truncated polynomial basis functions of degree 3, θ = (θ0, θ1, θ2, θ3, θ4, θ5, θ6)′ is a corresponding vector of parameter, bi = (bio, bi1, bi2, bi3)′ denotes the random effects, for j = 1, 2, …, ni, i = 1, 2, …, I, ni denotes the number of repeated time points for i th women, and I denotes the number of women. Furthermore, we assumed that the residual errors εij are distributed with independent normal distributions with mean 0 and variance. The random effects are assumed to follow the multivariate normal distribution with mean zero and unstructured variance-covariance matrix Ω. The random effects are interpreted as individual departures in an individual’s growth curve relative to the average fetal growth curve in the population. From the model in Eq. (1), the ratio and velocity of 2 ultrasound measurements can be computed, respectively, as follows:

ri,jj=exp(Yij^Yij^)andvi,jj=(ri,jj1)Yijtijtij

where Yij is an original scaled ultrasound measurement at time tij, Yij^ is an estimated log-transformed ultrasound measurement at time tij, ri,jj′ is a ratio of 2 ultrasound measurements, and vi,jj′ is a velocity of 2 ultrasound measurements. We incorporated weights in the linear mixed model where each individual’s component of the likelihood is weighted by the proportion of the US population reference for that individual’s race or ethnic group divided by the corresponding proportion in the Eunice Kennedy Shriver National Institute of Child Health and Human Development fetal growth twin study population.

Footnotes

D.A.W. has been a consultant for Parsagen, for which she received no compensation. The other authors report no conflict of interest.

This study was registered on ClinicalTrials.gov (ClinicalTrials.gov identifier: NCT00912132).

Contributor Information

Katherine L. Grantz, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.

Jagteshwar Grewal, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.

Sungduk Kim, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.

William A. Grobman, Feinberg School of Medicine, Northwestern University, Chicago, IL.

Roger B. Newman, Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC.

John Owen, University of Alabama at Birmingham, Birmingham, AL.

Anthony Sciscione, Department of Obstetrics and Gynecology, ChristianaCare Health System, Newark, DE.

Daniel Skupski, NewYork-Presbyterian Queens, Flushing, NY.

Edward K. Chien, Women and Infants Hospital of Rhode Island, Providence, RI; Cleveland Clinic, Cleveland, OH.

Deborah A. Wing, University of California, Irvine, Orange, CA; Fountain Valley Regional Hospital and Medical Center, Fountain Valley, CA.

Ronald J. Wapner, Columbia University Medical Center, New York, NY.

Angela C. Ranzini, Saint Peter’s University Hospital, New Brunswick, NJ; The MetroHealth System, Cleveland, OH.

Michael P. Nageotte, Miller Children’s and Women’s Hospital Long Beach/Long Beach, Memorial Medical Center, Long Beach, CA.

Sabrina Craigo, Department of Obstetrics and Gynecology, Tufts Medical Center, Boston, MA.

Stefanie N. Hinkle, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA.

Mary E. D’Alton, Columbia University Medical Center, New York, NY.

Dian He, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD; The Prospective Group, Inc, Fairfax, VA.

Fasil Tekola-Ayele, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.

Mary L. Hediger, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD.

Germaine M. Buck Louis, College of Health and Human Services, George Mason University, Fairfax, VA.

Cuilin Zhang, Division of Population Health Research, Division of Intramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD; Bia-Echo Asia Centre for Reproductive Longevity & Equality, Yong Loo Lin School of Medicine, National University of Singapore, Queenstown, Singapore; Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Queenstown, Singapore.

Paul S. Albert, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.

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