Impact of joint effect of parental anthropometrics on fetal growth trajectories: A national multicenter cohort study

To the Editor: Maternal anthropometrics are well-established determinants of fetal size. However, the joint effect of maternal and paternal anthropometrics on fetal growth trajectories remains unexplored. To address this, our study enrolled 9075 low-risk singleton pregnant women from 24 hospitals across 18 provinces in China and identified four distinct fetal growth trajectory profiles with K-means clustering, enabling an analysis of the parental anthropometrics composite effect. The study was approved by the Peking University Third Hospital Medical Science Research Ethics Committee (approval number: 2021 No. 336-02), and informed consent was obtained from all participants. This nationwide, multicenter cohort study recruited singleton pregnant women without major obstetric complications who delivered between September 1 and October 31, 2019, across 24 hospitals spanning 18 provinces in China. The detailed information on the exclusion criteria is provided in the Supplementary Methods, https://links.lww.com/CM9/C919. To ensure rigorous participant selection, each site employed a three-physician review panel: two independent reviewers assessed eligibility based on the inclusion and exclusion criteria, with discrepancies resolved by a third adjudicating physician. All reviewers underwent standardized training to maintain inter-rater reliability. The primary exposures comprised maternal anthropometrics (height and prepregnancy weight) and paternal height. The ultrasonic measurement of fetal anthropometric parameters was performed in accordance with the Chinese Prenatal Ultrasound Guide (2012). All participants underwent at least three ultrasound examinations between 12 gestational weeks and delivery to measure biometric parameters, including head circumference (HC), abdominal circumference (AC), biparietal diameter (BPD), femur length (FL), and estimated fetal weight (EFW). Each parameter was measured twice, and the average value was used for analysis. All measurements were obtained from ultrasonic images with the highest magnification. The original values of all measurements and images were achieved for random quality control checks, allowing for the tracing of outliers. To analyze the joint effect of the paternal height, the maternal height and prepregnancy weight, we first performed a K-means cluster analysis using these variables via the “stats” package in R software (version 4.3.2, R Foundation, Vienna, Austria). Then we used the two-level linear regression models with cubic spline to analyze the impact of the clusters on fetal growth trajectories, with the medium-build group as the reference, incorporating a random intercept model to account for the inherent variability among individuals. All statistical tests were two-sided, with a significance level of α = 0.05. All analyzes were implemented using SAS software (version 9.4, SAS Institute Inc., Cary, NC, USA) and R software. A total of 9075 couples were included in the final study cohort. The baseline characteristics of the study cohort are detailed in Supplemental Table 1, https://links.lww.com/CM9/C919. The mean maternal age was 29.47 years (standard deviation [SD] = 4.01). Among the fetuses, 607 (6.69%) and 1112 cases (12.25%) were diagnosed with small for gestational age (SGA) and large for gestational age (LGA), respectively. Maternal anthropometric measurements revealed an average height of 161.16 cm (SD = 4.89) and prepregnancy weight of 55.45 kg (SD = 8.44). The mean paternal height was 173.99 cm (SD = 5.17). Cluster analysis was used to explore the joint effects of parental anthropometries on fetal growth trajectory. Four clusters were identified in the study, and the distribution of the cluster feature variables is presented in Supplementary Table 2 and Supplementary Figure 1, https://links.lww.com/CM9/C919. Specifically, Cluster 1 comprised couples with medium builds, Cluster 2 encompassed short and lean pregnant women, Cluster 3 featured tall husbands, and Cluster 4 encompassed overweight pregnant women. The joint effects by clusters are detailed in Table 1 and Supplementary Figure 2, https://links.lww.com/CM9/C919. Compared with fetuses in Cluster 1, fetuses in Cluster 2 exhibited significantly smaller biometric parameters, including EFW (β = −34.44, 95% CI: −43.44, −25.44), AC (β = −1.83, 95% CI: −2.36, −1.31), HC (β = −0.98, 95% CI: −1.41, −0.54), BPD (β = −0.21, 95% CI: −0.36, −0.07), and FL (β = −0.26, 95% CI: −0.36, −0.15). Conversely, fetuses in Cluster 4 showed significantly larger measurements, particularly for EFW (β = 32.79, 95% CI: 21.89, 43.69), AC (β = 1.34, 95% CI: 0.70, 1.98), HC (β = 0.94, 95% CI: 0.42, 1.47), BPD (β = 0.35, 95% CI: 0.18, 0.53), and FL (β = 0.33, 95% CI: 0.21, 0.46). Moreover, fetuses in Cluster 3 were more prone to having larger HC (β = 0.67, 95% CI: 0.22, 1.12), BPD (β = 0.41, 95% CI: 0.26, 0.56), and FL (β = 0.35, 95% CI: 0.24, 0.46). Table 1 - Joint effects of parental anthropometrics on fetal growth trajectories. Anthropometric clusters EFW AC HC BPD FL β (95% CI) P-value β (95% CI) P-value β (95% CI) P-value β (95% CI) P-value β (95%CI) P-value Unadjusted model Cluster 1 Ref. Ref. Ref. Ref. Ref. Cluster 2 −39.57 (−48.52 to −30.63) <0.001 −2.18 (−2.70 to −1.65) <0.001 −1.09 (−1.52 to −0.66) <0.001 −0.22 (−0.36 to −0.07) 0.003 −0.26 (−0.36 to −0.16) <0.001 Cluster 3 2.03 (−7.13 to 11.19) 0.664 −0.70 (−1.24 to –0.17) 0.010 0.65 (0.21 to 1.09) 0.004 0.52 (0.37 to 0.67) <0.001 0.30 (0.20 to 0.41) <0.001 Cluster 4 31.11 (20.27 to 41.96) <0.001 1.25 (0.61 to 1.89) <0.001 0.92 (0.40 to 1.44) <0.001 0.42 (0.25 to 0.60) <0.001 0.29 (0.17 to 0.42) <0.001 Adjusted model Cluster 1 Ref. Ref. Ref. Ref. Ref. Cluster 2 −34.44 (−43.44 to −25.44) <0.001 −1.83 (−2.36 to −1.31) <0.001 −0.98 (−1.41 to −0.54) <0.001 −0.21 (−0.36 to −0.07) 0.004 −0.26 (−0.36 to −0.15) <0.001 Cluster 3 6.07 (–3.20 to 15.34) 0.199 −0.44 (−0.99 to 0.10) 0.111 0.67 (0.22 to 1.12) 0.004 0.41 (0.26 to 0.56) <0.001 0.35 (0.24 to 0.46) <0.001 Cluster 4 32.79 (21.89 to 43.69) <0.001 1.34 (0.70 to 1.98) <0.001 0.94 (0.42 to 1.47) <0.001 0.35 (0.18 to 0.53) <0.001 0.33 (0.21 to 0.46) <0.001 Cluster 1 represented medium-build couples; Cluster 2 represented short, slim pregnant women; Cluster 3 represented tall husbands; Cluster 4 represented overweight pregnant women. Model 2 was adjusted for maternal age, ethnic groups, education level, and parity. AC: Abdominal circumference; BPD: Biparietal diameter; CI: Confidence interval; EFW: Estimated fetal weight; FL: Femur length; HC: Head circumference; Ref.: Reference. This multicenter cohort study leveraged a large, nationally representative dataset in China to investigate variations in fetal growth trajectories across clusters defined by maternal height, prepregnancy weight, and paternal height. Cluster analysis identified distinct fetal growth patterns, with Cluster 2 demonstrating significantly attenuated growth across all biometric parameters compared to the reference Cluster 1. Conversely, Cluster 4 exhibited accelerated fetal development. Additionally, fetuses belonging to Cluster 3 exhibited larger HC, BPD, and FL. These findings underscore the complex interplay of parental anthropometric characteristics in shaping fetal growth. Fetal growth is highly linked to various maternal conditions, including height, weight, and body mass index.[1] In the study, we observed that two-thirds of Chinese pregnant women exceeded 160 cm in height, with nearly half exceeding 55 kg in prepregnancy weight; both anthropometric profiles correlated with increased fetal biometric measurements. Recent research by Zhang et al[2] used the Mendelian randomization analysis to elucidate that the significant association between maternal height and fetal growth is largely driven by fetal genetics. Prepregnancy weight, functioning as a proxy for maternal nutritional reserves, also emerged as a critical determinant of fetal development. Paternal stature additionally contributes to fetal growth dynamics through epigenetic mechanisms. Supporting this, Wills et al[3] demonstrated the impact of genomic imprinting on fetal development, showing differential expression patterns between parental alleles: paternally derived growth-related genes exhibit sustained expression throughout gestation, while maternal alleles become activated in later pregnancy stages. In addition, the study by Stulp et al[4] demonstrated that parental height differences also significantly influenced the necessity for emergency cesarean section in primiparous women. The compatibility between spouses affects fetal development during pregnancy to a certain extent. Distinguishing from previous related studies that failed to conduct the joint effect analysis of parental anthropometrics, the study innovatively categorized parents into four distinct types based on their height and maternal prepregnancy weight. Compared with medium-build couples, those with short and lean pregnant women faced a higher risk of having a fetus with a smaller size. Conversely, couples with overweight pregnant women were likely to have higher levels of fetal growth trajectories. It is worth pointing out that current mate preferences tend toward selecting male partners who are above the average level and female partners who are below the average level.[5] This sociodemographic trend aligns with our findings that short and lean pregnant women partnered with taller males were more likely to suffer from giving birth to large fetuses, potentially increasing obstetric complications during delivery. Inevitably, this study has some limitations. First, there were inherent variations in the timing and frequency of ultrasound examinations conducted on different fetuses, reflecting real-world clinical practice. However, our inclusion criteria mandated a minimum of three biometric evaluations to ensure adequate characterization of individual fetal growth patterns. Second, while maternal prepregnancy weight was meticulously analyzed, gestational weight gain dynamics were not incorporated into the current model. Acknowledging this parameter’s established influence on fetal development, subsequent investigations should integrate longitudinal weight gain metrics to refine predictive accuracy. In conclusion, our findings revealed four distinct parental anthropometric clusters associated with differential fetal growth trajectories. Specifically, couples with short and lean pregnant women, overweight pregnant women or tall husbands were more likely to experience either lower or higher levels of fetal growth trajectories, in comparison with medium-build couples. These observations underscore the necessity for targeted surveillance protocols in such subpopulations to optimize gestational management. Furthermore, the development of personalized fetal growth standards stratified by parental phenotype demonstrates enhanced clinical utility, offering more precise growth benchmarks for diverse anthropometric pairings. Acknowledgments We would like to express our gratitude to all participating hospitals for providing data for this study, the clinicians who assisted in data collection and upload, and the staff responsible for data verification. We also acknowledge the valuable assistance of Wei Zhou (Chongqing Maternal and Child Health Hospital), Xiaohui Liu (Maternal and Child Health Hospital of Urumqi), Jin Dong (Northwest Women and Children’s Hospital), Xiaoming Zeng (Maternal and Child Health Hospital of Jiangxi Province), and Yun Zhao (Hubei Province Maternal and Child Health Hospital). Funding This work was supported by the National Key Research and Development Program of China (No. 2023YFC2705900), the National Natural Science Foundation of China (No. 8217060975), Capital’s Funds for Health Improvement and Research (No. 2022-2G-4099), and the Beijing Municipal Natural Science Foundation (No. 7244459).