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Amini P, Moghimbeigi A, Zayeri F, et al. Evaluating The Impact of Risk Factors on Birth Weight and Gestational Age: A Multilevel Joint Modeling Approach. Int J Fertil Steril. 2018;12(2):106-113doi: 10.22074/ijfs.2018.5330.
Amini, P., Moghimbeigi, A., Zayeri, F., Mahjub, H., Maroufizadeh, S., & Omani-Samani, R. (2018). Evaluating The Impact of Risk Factors on Birth Weight and Gestational Age: A Multilevel Joint Modeling Approach. International journal of fertility & sterility, 12(2), 106-113. https://doi.org/10.22074/ijfs.2018.5330
Amini, Payam, et al. "Evaluating The Impact of Risk Factors on Birth Weight and Gestational Age: A Multilevel Joint Modeling Approach." International journal of fertility & sterility vol. 12,2 (2018): 106-113. doi: https://doi.org/10.22074/ijfs.2018.5330
Amini P, Moghimbeigi A, Zayeri F, Mahjub H, Maroufizadeh S, Omani-Samani R. Evaluating The Impact of Risk Factors on Birth Weight and Gestational Age: A Multilevel Joint Modeling Approach. Int J Fertil Steril. 2018 Jul;12(2):106-113. doi: 10.22074/ijfs.2018.5330. Epub 2018 Mar 18. PMID: 29707925; PMCID: PMC5936606.
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Int J Fertil Steril. 2018 Jul;12(2):106-113. doi: 10.22074/ijfs.2018.5330. Epub 2018 Mar 18.

Evaluating The Impact of Risk Factors on Birth Weight and Gestational Age: A Multilevel Joint Modeling Approach.

International journal of fertility & sterility

Payam Amini, Abbas Moghimbeigi, Farid Zayeri, Hossein Mahjub, Saman Maroufizadeh, Reza Omani-Samani

Affiliations

  1. Department of Biostatistics and Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
  2. Modeling of Noncomunicable Disease Research Center, Department of Biostatistics, Faculty of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.Electronic Address: [email protected].
  3. Department of Biostatistics, Proteomics Research Center, School of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
  4. Research Center for Health Sciences, Department of Biostatistics, Faculty of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
  5. Department of Epidemiology and Reproductive Health, Reproductive Epidemiology Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran.
  6. Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.

PMID: 29707925 PMCID: PMC5936606 DOI: 10.22074/ijfs.2018.5330

Abstract

BACKGROUND: Abnormalities in birth weight and gestational age cause several adverse maternal and infant outcomes. Our study aims to determine the potential factors that affect birth weight and gestational age, and their association.

MATERIALS AND METHODS: We conducted this cross-sectional study of 4415 pregnant women in Tehran, Iran, from July 6-21, 2015. Joint multilevel multiple logistic regression was used in the analysis with demographic and obstetrical variables at the first level, and the hospitals at the second level.

RESULTS: We observed the following prevalence rates: preterm (5.5%), term (94%), and postterm (0.5%). Low birth weight (LBW) had a prevalence rate of 4.8%, whereas the prevalence rate for normal weight was 92.4, and 2.8% for macrosomia. Compared to term, older mother's age [odds ratio (OR)=1.04, 95% confidence interval (CI): 1.02-1.07], preeclampsia (OR=4.14, 95% CI: 2.71-6.31), multiple pregnancy (OR=18.04, 95% CI: 9.75- 33.38), and use of assisted reproductive technology (ART) (OR=2.47, 95% CI: 1.64-33.73) were associated with preterm birth. Better socioeconomic status (SES) was responsible for decreased odds for postterm birth compared to term birth (OR=0.53, 95% CI: 0.37-0.74). Cases with higher maternal body mass index (BMI) were 1.02 times more likely for macrosomia (95% CI: 1.01-1.04), and male infant sex (OR=1.78, 95% CI: 1.21-2.60). LBW was related to multiparity (OR=0.59, 95% CI: 0.42-0.82), multiple pregnancy (OR=17.35, 95% CI: 9.73-30.94), and preeclampsia (OR=3.36, 95% CI: 2.15-5.24).

CONCLUSION: Maternal age, SES, preeclampsia, multiple pregnancy, ART, higher maternal BMI, parity, and male infant sex were determined to be predictive variables for birth weight and gestational age after taking into consideration their association by using a joint multilevel multiple logistic regression model.

Copyright© by Royan Institute. All rights reserved.

Keywords: Birth Weight; Gestational Age; Multilevel; Statistical Model

Conflict of interest statement

The authors declare no conflicts of interest.

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