Background
Excessive gestational weight gain is a global public health problem with serious and long-term effects on maternal and offspring health. Early identification of at-risk groups and interventions is crucial for controlling weight gain and reducing the incidence of excessive gestational weight gain. Currently, tools for predicting the risk of excessive gestational weight gain are lacking in China. This study aimed to develop a risk-prediction model and screening tool for the early identification of at-risk groups.
Methods
Convenience sampling was used to select 306 pregnant women who underwent regular obstetric checkups at a tertiary-level hospital in China between January and March 2023. Logistic regression analysis was used to construct the risk-prediction model. The goodness of fit of the model was assessed using the Hosmer-Lemeshow test, and the predictive performance was evaluated using the area under the receiver operating characteristic (ROC) curve. R4.3.1 software was used to create a nomogram.
Results
The prevalence of excessive gestational weight gain was 49.53%. Logistic regression analysis revealed that prepregnancy overweight (odds ratio [OR] = 2.662), obesity (OR = 3.851), and primiparity (OR = 5. 134); eating in front of a screen (OR = 5.588); consumption of sugar-sweetened beverages, desserts, and western fast food (> 5 times per week) (OR = 6.733); and pregnancy body image (OR = 1.031) were risk factors for excessive gestational weight gain. Protective motivation to manage pregnancy body mass (OR = 0.979) and duration of moderate-intensity physical activity (OR = 0.234) were protective factors against excessive gestational weight gain. The area under the ROC curve of the model was 0.885, with a maximum Youden index of 0.617, optimal threshold of 0.404, sensitivity of 83.96%, and specificity of 77.78%. The model validation results showed a sensitivity, specificity, and accuracy of 83.33%, 77.27%, and 80.43%, respectively.
Conclusion
The risk-prediction model developed in this study proved to be effective, providing a valuable basis for early identification and precise intervention in individuals at risk of excessive gestational weight gain.