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. 2023 Mar 30;14:1114250. doi: 10.3389/fendo.2023.1114250

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Copyright © 2023 Lin, Chen, Qian, Wang, Xiu, Ou, Fang and Li

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Paternal BMI and the risk of SGA/Macrosomia was analyzed by logistic regression, stratified by maternal BMI. BMI, body mass index; SGA, small for gestational age; OR, odds ratio;95% CI, 95% confidence interval of the estimated trend. (a) Univariate logistic regression compared with the referent (norma paternal BMI). (b) Estimated using multivariate logistic regression. Model for SGA/Macrosomia adjusted for child sex, child age, paternal age, paternal education, maternal age, maternal education, parity, gravidity, annual family income, HDCP, cesarean delivery, GWG. And macrosomia is also adjusted for gestational age. (c) P values for interaction showed the interaction effect of paternal obesity and maternal obesity on the risk of SGA/Macrosomia. *P < 0.05 was considered statistically significant.