The impact of socio-economic, demographic and medical factors on the morphological development of the fetus and the weight of the newborn

Relevance. The morphological development of the fetus and the weight of the newborn are key indicators of perinatal health, reflecting both the biological, socio-economic, demographic and medical characteristics of the mother. In the context of regional differences and the changing structure of motherhood, it is necessary to comprehensively study the influence of such factors as socio-economic status (income level, education, parity, and smoking status), maternal age, as well as the presence of diseases and anthropometric indicators (BMI) before pregnancy on the outcome of childbirth.
The objective of this study was to determine the cumulative effect of socio-economic, demographic and medical factors on the morphometric parameters of the fetus and the weight of the newborn in a regional analysis, as well as to identify optimal parameters for the formation of favorable intrauterine development.
Methods and materials. The study conducted a retrospective analysis of the data of 5,161 pregnant women who were observed at the Kirov Regional Clinical Perinatal Center. All data were divided into subgroups by maternal age (younger than 20, 20–30, 31–40, ≥41 years), socio-economic indicators (income level, education, parity, smoking status) and medical characteristics (presence of diseases: hypertension, preeclampsia, diabetes mellitus, SARS-CoV-2, fetoplacental insufficiency; BMI before pregnancy). Methods of descriptive statistics, univariate and multifactorial analysis of variance (ANOVA), post-hoc Tukey test, multiple linear regression and logistic regression were used for statistical processing. The software was SPSS (version 26.0) and R (version 4.0.2).
Results. Multifactorial analysis showed that all the studied factors have a statistically significant effect on the weight of the newborn (p<0.001). Optimal indicators were found in mothers aged 20–30 years with a high level of income and education, non–smokers, having a second pregnancy, a normal BMI (18.5–24.9 kg/m2) and the absence of concomitant diseases. Low BMI and the presence of diseases (hypertension, preeclampsia, diabetes mellitus, SARS-CoV-2, fetoplacental insufficiency) lead to a decrease in newborn weight by up to 20 % compared with the control group, while an increased BMI (25.0–29.9 kg/m2) partially compensates for the negative effects of diseases, increasing fetal weight by 8–10 %.
Conclusions. The obtained results emphasize the need for an integrated approach in perinatal medicine, taking into account socio-economic, demographic and medical factors. A personalized pregnancy management strategy, including monitoring the state of maternal health, optimizing anthropometric indicators, and correcting social factors, improves birth outcomes and reduces the risk of fetal hypotrophy. The results of the study are of practical importance for the development of programs to support pregnant women in regions with different social structures.

1. Ziyadinov A. A., Novikova V. A., Matejkovich E. A. et al. Struktura materinskix risk-faktorov nedostatochnogo rosta ploda // Lechenie i profilaktika. 2022;12(2):10–18. (In Russ.).

2. Yang Y., Le Ray I., Zhu J. et al. Preeclampsia Prevalence, Risk Factors, and Pregnancy Outcomes in Sweden and China // JAMA Netw Open. 2021;4(5):e218401. http://doi.org/10.1001/jamanetworkopen.2021.8401.

3. Yakovleva O. V., Rogozhina I. E., Glukhova T. N. Modern concepts of low birth weight fetus and fetal growth retardation // Kazan Medical Journal. 2021;102(3):347–354. (In Russ.).

4. Sun Y., Shen Z., Zhan Y. et al. Effects of pre-pregnancy body mass index and gestational weight gain on maternal and infant complications // BMC Pregnancy Childbirth. 2020;20(1):390. http://doi.org/10.1186/s12884-020-03071-y.

5. Belotserkovtseva L. D., Ivannikov S. E., Borisova T. D. The influence of maternal age on the course and outcomes of pregnancy at first birth // Russian Bulletin of Obstetrician-Gynecologist. 2021;21(4):48–53. (In Russ.).

6. Rani Balaji V. C., Saraswathi K., Manikandan S. Periodontal health in first trimester of pregnancy and birth weight outcomes // Indian J Dent Res. 2021;32(2):181–186. http://doi.org/10.4103/ijdr.ijdr_94_21.

7. Wahabi H., Elmorshedy H., Amer Y. S. et al. Neonatal Birthweight Spectrum: Maternal Risk Factors and Pregnancy Outcomes in Saudi Arabia // Medicina (Kaunas). 2024;60(2):193. http://doi.org/10.3390/medicina60020193.

8. Jeyaparam S., Agha-Jaffar R., Mullins E. et al. Retrospective cohort study of the association between socioeconomic deprivation and incidence of gestational diabetes and perinatal outcomes // BMC Public Health. 2024;24(1):184. http://doi.org/10.1186/s12889-023-17261-8.

9. Anikina V. O., Savenysheva S. S., Blokh M. E. et al. Stress associated with the COVID-19 pandemic in pregnant women // Bulletin of St. Petersburg University. Psychology. 2024;14(2):294–304. (In Russ.).

10. Derakhshan A., Peeters R. P., Taylor P. N. et al. Association of maternal thyroid function with birthweight: a systematic review and individual‐participant data meta‐analysis // Lancet Diabetes Endocrinol. 2020;8(6):501–510. http://doi.org/10.1016/S2213-8587(20)30061-9.

11. Li C., Cai Y., Li Y. et al. Well-controlled gestational diabetes mellitus without pharmacologic therapy decelerates weight gain in infancy // Front Endocrinol (Lausanne). 2022;(13):1063989. http://doi.org/10.3389/fendo.2022.1063989.

12. Liu W., Ren L., Fang F., Chen R. Maternal pre-pregnancy overweight or obesity and risk of birth defects in offspring: Population-based cohort study // Acta Obstet Gynecol Scand. 2024;103(5):862–872. http://doi.org/10.1111/aogs.14786.

13. Perumal N., Wang D., Darling A. M. et al. Associations between Gestational Weight Gain Adequacy and Neonatal Outcomes in Tanzania // Ann Nutr Metab. 2022;78(3):156–165. http://doi.org/10.1159/000522197.

14. Zefirova T. P., Mukhametova R. R. Why psychological stress is dangerous for pregnant women // Doctor.Ru. 2023;22(5):34–39. (In Russ.).

15. Simmons D., Immanuel J., Hague W. M. et al. Perinatal Outcomes in Early and Late Gestational Diabetes Mellitus After Treatment From 24–28 Weeks’ Gestation: A TOBOGM Secondary Analysis // Diabetes Care. 2024;47(12):2093–2101. http://doi.org/10.2337/dc23-1667.

16. Furse S., Koulman A., Ozanne S. E. et al. Altered Lipid Metabolism in Obese Women With Gestational Diabetes and Associations With Offspring Adiposity // J Clin Endocrinol Metab. 2022;107(7):e2825–e2832. http://doi.org/10.1210/clinem/dgac206.

17. Chen Y. H., Chen W. Y., Chang C. Y. et al. Association between maternal factors and fetal macrosomia in full-term singleton births // J Chin Med Assoc. 2023;86(3):324–329. http://doi.org/10.1097/JCMA.0000000000000871.

18. Martinez J. I., Figueroa M. I., Martínez-Carrión J. M. et al. Birth Size and Maternal, Social, and Environmental Factors in the Province of Jujuy, Argentina // Int J Environ Res Public Health. 2022;19(2):621. http://doi.org/10.3390/ijerph19020621.

19. Apostolopoulou A., Tranidou A., Chroni V. et al. Association of Maternal Diet with Infant Birthweight in Women with Gestational Diabetes Mellitus // Nutrients. 2023;15(21):4545. http://doi.org/10.3390/nu15214545.

20. Chen L. W., Aubert A. M., Shivappa N. et al. Associations of maternal dietary inflammatory potential and quality with offspring birth outcomes: An individual participant data pooled analysis of 7 European cohorts in the ALPHABET consortium // PLoS Med. 2021;18(1):e1003491. http://doi.org/10.1371/journal.pmed.1003491.

21. Zhang Y., Chen Z., Cao Z. et al. Associations of maternal glycemia and prepregnancy BMI with early childhood growth: a prospective cohort study // Ann N Y Acad Sci. 2020;1465(1):89– 98. http://doi.org/10.1111/nyas.14258.

22. Fritsche L., Hartkopf J., Hummel J. et al. Maternal Weight Gain during Pregnancy and the Developing Autonomic Nervous System—Possible Impact of GDM // Nutrients. 2022;14(24):5220. http://doi.org/10.3390/nu14245220.

23. Yuan Y., Zhu Q., Yao X. et al. Maternal circulating metabolic biomarkers and their prediction performance for gestational diabetes mellitus related macrosomia // BMC Pregnancy Childbirth. 2023;23(1):113. http://doi.org/10.1186/s12884-023-05440-9.

24. Hromadnikova I., Kotlabova K., Krofta L. First trimester prediction models for small-for-gestational age and fetal growth restricted fetuses without the presence of preeclampsia // Mol Cell Probes. 2023;(72):101941. http://doi.org/10.1016/j.mcp.2023.101941.

25. Robillard P. Y., Dekker G., Chaouat G. et al. Primipaternities and human birthweights // J Reprod Immunol. 2021;(147):103365. http://doi.org/10.1016/j.jri.2021.103365.