Home Medicine Individualized sex-specific birth weight percentiles for gestational age based on maternal height and weight
Article
Licensed
Unlicensed Requires Authentication

Individualized sex-specific birth weight percentiles for gestational age based on maternal height and weight

  • Manfred Voigt , Niels Rochow EMAIL logo , Erin Landau-Crangle , Lena Marie Meyer-Kahrweg , Dirk M. Olbertz , Mirjam Kunze , Werner Nikischin , Ursula Wittwer-Backofen , Markus Rochow , Jan Däbritz and Roland Hentschel
Published/Copyright: August 31, 2020

Abstract

Objectives

The maternal body size affects birth weight. The impact on birth weight percentiles is unknown. The objective of the study was to develop birth weight percentiles based on maternal height and weight.

Methods

This observational study analyzed 2.2 million singletons from the German Perinatal Survey. Data were stratified into 18 maternal height and weight groups. Sex-specific birth weight percentiles were calculated from 31 to 42 weeks and compared to percentiles from the complete dataset using the GAMLSS package for R statistics.

Results

Birth weight percentiles not considering maternal size showed 22% incidence of small for gestational age (SGA) and 2% incidence of large for gestational age (LGA) for the subgroup of newborns from petite mothers, compared to a 4% SGA and 26% LGA newborns from big mothers. The novel percentiles based on 18 groups stratified by maternal height and weight for both sexes showed significant differences between identical original percentiles. The differences were up to almost 800 g between identical percentiles for petite and big mothers. The 97th and 50th percentile from the group of petite mothers almost overlap with the 50th and 3rd percentile from the group of big mothers.

Conclusions

There is a clinically significant difference in birth weight percentiles when stratified by maternal height and weight. It could be hypothesized that birth weight charts stratified by maternal anthropometry could provide higher specificity and more individual prediction of perinatal risks. The new percentiles may be used to evaluate estimated fetal as well as birth weight.


Corresponding author: Niels Rochow, MD, PhD, Department of Pediatrics, Paracelsus Medical University, General Hospital, Breslauer Str. 201, 90471Nuremberg, Germany; Department of Pediatrics, Rostock University Medical Center, 18057 Rostock, Germany; and Department of Pediatrics, McMaster University, Hamilton, ON L8S 4L8, Canada, Phone: +49 (911) 398 118903, Fax: +49 (911) 398 5107, E-mail:

Acknowledgments

We thank Tanja Pfitzenmaier for the editorial support.

  1. Research funding: None declared.

  2. Author contributions: MV: Data curation, conceptualization and study design, interpretation of the data; NR: Conceptualization and study design, statistical analysis, interpretation of the data, and wrote the manuscript; EL, LM: Drafted parts of the manuscript; JD, DO, WN, MK, UW: Conceptualization; RH, MR: Interpretation of the data, drafted parts of the manuscript. All co-authors reviewed the manuscript.

  3. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: The study was approved by the research ethics board of the University of Rostock (#A 2019-0108).

  6. Data sharing: Detailed percentile values for all maternal weight and height groups can be retrieved from www.growthcalcualtor.org [26].

References

1. Rochow, N, Voigt, M, Olbertz, DM, Straube, S. Birth weight percentiles: an international comparison. In: Zabransky, S, editor. Caring for children born small for gestational age. London: Springer Healthcare; 2013:pp. 45–53.10.1007/978-1-908517-90-6_5Search in Google Scholar

2. Rochow, N, AlSamnan, M, So, HY, Olbertz, D, Pelc, A, Dabritz, J, et al. Maternal body height is a stronger predictor of birth weight than ethnicity: analysis of birth weight percentile charts. J Perinat Med 2018;47:22–9. https://doi.org/10.1515/jpm-2017-0349.Search in Google Scholar

3. Battaglia, FC, Lubchenco, LO. A practical classification of newborn infants by weight and gestational age. J Pediatr 1967;71:159–63. https://doi.org/10.1016/s0022-3476(67)80066-0.Search in Google Scholar

4. Saenger, P, Czernichow, P, Hughes, I, Reiter, EO. Small for gestational age: short stature and beyond. Endocr Rev 2007;28:219–51. https://doi.org/10.1210/er.2006-0039.Search in Google Scholar

5. Zeve, D, Regelmann, MO, Holzman, IR, Rapaport, R. Small at birth, but how small? The definition of SGA revisited. Horm Res Paediatr 2016;86:357–60. https://doi.org/10.1159/000449275.Search in Google Scholar

6. Maxim, LD, Niebo, R, Utell, MJ. Screening tests: a review with examples. Inhal Toxicol 2014;26:811–28. https://doi.org/10.3109/08958378.2014.955932.Search in Google Scholar

7. Ay, L, Kruithof, CJ, Bakker, R, Steegers, EA, Witteman, JC, Moll, HA, et al. Maternal anthropometrics are associated with fetal size in different periods of pregnancy and at birth. The generation R study. BJOG 2009;116:953–63. https://doi.org/10.1111/j.1471-0528.2009.02143.x.Search in Google Scholar

8. Dunger, DB, Petry, CJ, Ong, KK. Genetics of size at birth. Diabetes Care 2007;30:S150–5. https://doi.org/10.2337/dc07-s208.Search in Google Scholar

9. Thame, M, Osmond, C, Trotman, H. Fetal growth and birth size is associated with maternal anthropometry and body composition. Matern Child Nutr 2015;11:574–82. https://doi.org/10.1111/mcn.12027.Search in Google Scholar

10. Romero, R, Tarca, AL. Fetal size standards to diagnose a small- or a large-for-gestational-age fetus. Am J Obstet Gynecol 2018;218:S605–7. https://doi.org/10.1016/j.ajog.2017.12.217.Search in Google Scholar

11. Gardosi, J, Francis, A, Turner, S, Williams, M. Customized growth charts: rationale, validation and clinical benefits. Am J Obstet Gynecol 2018;218:S609–18. https://doi.org/10.1016/j.ajog.2017.12.011.Search in Google Scholar

12. Tarca, AL, Romero, R, Gudicha, DW, Erez, O, Hernandez-Andrade, E, Yeo, L, et al. A new customized fetal growth standard for African-American women: the PRB/NICHD detroit study. Am J Obstet Gynecol 2018;218:S679–91.e4. https://doi.org/10.1016/j.ajog.2017.12.229.Search in Google Scholar

13. Grantz, KL, Hediger, ML, Liu, D, Buck Louis, GM. Fetal growth standards: the NICHD fetal growth study approach in context with INTERGROWTH-21st and the World Health Organization multicentre growth reference study. Am J Obstet Gynecol 2018;218:S641–55.e28. https://doi.org/10.1016/j.ajog.2017.11.593.Search in Google Scholar

14. Kiserud, T, Benachi, A, Hecher, K, Perez, RG, Carvalho, J, Piaggio, G, et al. The World Health Organization fetal growth charts: concept, findings, interpretation, and application. Am J Obstet Gynecol 2018;218:S619–29. https://doi.org/10.1016/j.ajog.2017.12.010.Search in Google Scholar

15. Voigt, M, Rochow, N, Guthmann, F, Hesse, V, Schneider, KT, Schnabel, D. Geburtsgewichtsperzentilwerte für Mädchen und Knaben unter Berücksichtigung der Körperhöhe der Mutter. Z Geburtshilfe Neonatol 2012;216:212–9. https://doi.org/10.1055/s-0032-1316324.Search in Google Scholar

16. Voigt, M, Rochow, N, Jahrig, K, Straube, S, Hufnagel, S, Jorch, G. Dependence of neonatal small and large for gestational age rates on maternal height and weight--an analysis of the German perinatal survey. J Perinat Med 2010;38:425–30. https://doi.org/10.1515/jpm.2010.059.Search in Google Scholar

17. Rigby, RA, Stasinopoulos, DM. Automatic smoothing parameter selection in GAMLSS with an application to centile estimation. Stat Methods Med Res 2014;23:318–32. https://doi.org/10.1177/0962280212473302.Search in Google Scholar

18. Rigby, RA, Stasinopoulos, DM. Generalized additive models for location, scale and shape. J R STAT SOC C-APPL 2005;54:507–54. https://doi.org/10.1111/j.1467-9876.2005.00510.x.Search in Google Scholar

19. R Development Core Team. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019. v3.6.2 (2019-12-12).Search in Google Scholar

20. Voigt, M, Rochow, N, Straube, S, Briese, V, Olbertz, D, Jorch, G. Birth weight percentile charts based on daily measurements for very preterm male and female infants at the age of 154–223 days. J Perinat Med 2010;38:289–95. https://doi.org/10.1515/jpm.2010.031.Search in Google Scholar

21. Voigt, M, Rochow, N, Schneider, KT, Hagenah, HP, Scholz, R, Hesse, V, et al. New percentile values for the anthropometric dimensions of singleton neonates: analysis of perinatal survey data of 2007–2011 from all 16 states of Germany. Z Geburtshilfe Neonatol 2014;218:210–7. https://doi.org/10.1055/s-0034-1385857.Search in Google Scholar

22. Landau-Crangle, E, Rochow, N, Fenton, TR, Liu, K, Ali, A, So, HY, et al. Individualized postnatal growth trajectories for preterm infants. J Parenter Enter Nutr 2018;42:1084–92. https://doi.org/10.1002/jpen.1138.Search in Google Scholar

23. Rochow, N, Raja, P, Liu, K, Fenton, T, Landau-Crangle, E, Göttler, S, et al. Physiological adjustment to postnatal growth trajectories in healthy preterm infants. Pediatr Res 2016;79:870–9. https://doi.org/10.1038/pr.2016.15.Search in Google Scholar

24. Rochow, N, Landau-Crangle, E, Thommandram, A, Fusch, C. Individualized postnatal growth trajectory for preterm infants – Online calculator; 2016. Available from: http://www.growthcalculator.org/ [Accessed 09 05 2019].Search in Google Scholar

25. Rochow, N, Landau-Crangle, E, So, HY, Pelc, A, Fusch, G, Dabritz, J, et al. Z-score differences based on cross-sectional growth charts do not reflect the growth rate of very low birth weight infants. PloS One 2019;14:e0216048. https://doi.org/10.1371/journal.pone.0216048.Search in Google Scholar

26. Rochow, N, Landau-Crangle, E, Thommandram, A, Fusch, C. Individualized postnatal growth trajectory for preterm infants – online calculator; 2020. Available from: http://www.growthcalculator.org/ [Accessed 30 03 2020].Search in Google Scholar


Supplementary Material

The online version of this article offers supplementary material https://doi.org/10.1515/jpm-2020-0119.


Received: 2020-03-17
Accepted: 2020-08-04
Published Online: 2020-08-31
Published in Print: 2021-01-26

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Global approach of the cesarean section rates
  4. Review
  5. Cesarean section one hundred years 1920–2020: the Good, the Bad and the Ugly
  6. Original Articles – Obstetrics
  7. Non-adherence to labor guidelines in cesarean sections done for failed induction and arrest of dilation
  8. Retrospective study of maternal and neonatal outcomes after induction compared to spontaneous start of labour in women with one previous birth in uncomplicated pregnancies ≥ 41+3
  9. Management of labor after external cephalic version
  10. Evaluation of the labour process with serial transperineal ultrasonography and prediction of the type of birth
  11. Comparative study regarding effect of pH on Misoprostol in induction of labor in full term primigravida pregnant women, a double blind randomized controlled trial
  12. Comparison of the rates of preterm birth and low birth weight of vanishing twin and primary pregnancies conceived with assisted reproductive technology
  13. Obstetric outcomes of pregnancy complicated by urolithiasis: a retrospective cohort study
  14. Serum kallistatin level is decreased in women with preeclampsia
  15. An observational study to assess Italian obstetrics providers’ knowledge about preventive practices and diagnosis of congenital cytomegalovirus
  16. Predictive values of clinical parameters and biophysical and biochemical markers in the first trimester for the detection of small-for-gestational age fetuses
  17. Original Articles – Newborns
  18. Antenatal and perinatal outcomes of refugees in high income countries
  19. Individualized sex-specific birth weight percentiles for gestational age based on maternal height and weight
  20. Inhaled nitric oxide (iNO) for preventing prematurity-related bronchopulmonary dysplasia (BPD): 7-year follow-up of the European Union Nitric Oxide (EUNO) trial
  21. Erratum
  22. Risk factors associated with adverse fetal outcomes in pregnancies affected by Coronavirus disease 2019 (COVID-19): a secondary analysis of the WAPM study on COVID-19
  23. Acknowledgment
  24. Acknowledgment
Downloaded on 31.12.2025 from https://www.degruyterbrill.com/document/doi/10.1515/jpm-2020-0119/html
Scroll to top button