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.
Acknowledgments
We thank Tanja Pfitzenmaier for the editorial support.
Research funding: None declared.
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.
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.
Informed consent: Informed consent was obtained from all individuals included in this study.
Ethical approval: The study was approved by the research ethics board of the University of Rostock (#A 2019-0108).
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.
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