Journal of South Asian Federation of Obstetrics and Gynaecology

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VOLUME 13 , ISSUE 3 ( May-June, 2021 ) > List of Articles

Original Article

Modeling Gestational Age and Lack of Fit

Mohammad Lutfor Rahman, Ema Akter, Zakir Hossain, Aysha Sultana, Kalyan Das

Keywords : Biparietal diameter, Box-Cox transformation, Gestational age, Lack of fit

Citation Information : Rahman ML, Akter E, Hossain Z, Sultana A, Das K. Modeling Gestational Age and Lack of Fit. J South Asian Feder Obs Gynae 2021; 13 (3):81-85.

DOI: 10.5005/jp-journals-10006-1902

License: CC BY-NC 4.0

Published Online: 09-09-2021

Copyright Statement:  Copyright © 2021; Jaypee Brothers Medical Publishers (P) Ltd.


Introduction: Gestational age (GA) refers to age of an unborn baby. Accurate determination of GA is crucial as precise calculation of GA helps reducing post-date labor induction and is particularly useful to assess viability in premature labor and in post-date deliveries. Aim: The aim of the article was to determine GA by a minimal number of fetal parameters along with greater accuracy. Materials and methods: This was a prospective cross-sectional study, comprising a total of 229 singleton pregnant mothers enrolled from December 2015 to November 2016 in Ibn Sina Diagnostic and Imaging Center and Ad-Din Hospital in Dhaka, Bangladesh. Multiple linear regression models were fitted with four fetal parameters, namely biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL), and lack of fit was tested in each of the cases. In case of having a significant lack of fit, different types of transformation including Box-Cox transformation have been adopted on the variables to improve the adequacy of the model. Results: Among all the fitted models for gestational age by last menstrual period (GALMP), a model with a single explanatory variable, BPD, was found to be comparatively better than others. The Box-Cox transformation was taken on the dependent variable GALMP with λ that equals 0.2, and lack of fit test was not significant at 1% level (p-value = 0.027). Though the results from comparative models do not vary substantially, emphasis on BPD in GA calculation might suffice while cost of experimentation or screening is a grave concern. Conclusion: By considering the Box-Cox transformation and proper dealing of outliers, a model for GALMP was obtained without lack of fit where only the BPD appeared to be sufficient as an explanatory variable.

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