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Influence of perinatal factors on full-term low-birth-weight infants and construction of a predictive model
Liang Xu1, Xue-Juan Sheng2, Lian-Ping Gu3
1Department of Neonatology, Suzhou Ninth People's Hospital, Suzhou 215200, Jiangsu Province, China.
Insights
Low birth weight (LBW) in full-term infants is linked to maternal education, prenatal care, and pregnancy health. A predictive model accurately identifies LBW risk, aiding clinical management for healthier newborns.
Area of Science:
- Perinatal Medicine
- Neonatal Health
- Public Health
Background:
- Low birth weight (LBW) is a significant risk factor for infant diseases.
- Identifying perinatal factors associated with LBW is crucial for early intervention.
Purpose of the Study:
- To investigate perinatal factors influencing term low-birth-weight (LBW) infants.
- To develop a predictive model for term LBW to guide clinical care and support newborn health.
Main Methods:
- Retrospective analysis of 1794 full-term pregnancies.
- Logistic regression to identify LBW risk factors.
- Development and validation of a risk prediction model using ROC curve and Hosmer-Lemeshow test.
Main Results:
- The incidence of term LBW was 3.46% (62/1794).
- Key risk factors identified: low maternal education, fewer prenatal exams, insufficient weight gain, irregular calcium supplementation, and pregnancy hypertension syndrome.
- The predictive model demonstrated high accuracy (AUC=0.853, overall accuracy=81.67%).
Conclusions:
- Term LBW is associated with maternal education, prenatal examination frequency, maternal weight gain, calcium supplementation, and pregnancy hypertension.
- The developed predictive model is effective in assessing the risk of term LBW.
Background:
Being too light at birth can increase the risk of various diseases during infancy.
Aim:
To explore the effect of perinatal factors on term low-birth-weight (LBW) infants and build a predictive model. This model aims to guide the clinical management of pregnant women's healthcare during pregnancy and support the healthy growth of newborns.
Methods:
A retrospective analysis was conducted on data from 1794 single full-term pregnant women who gave birth. Newborns were grouped based on birth weight: Those with birth weight < 2.5 kg were classified as the low-weight group, and those with birth weight between 2.5 kg and 4 kg were included in the normal group. Multiple logistic regression analysis was used to identify the factors influencing the occurrence of full-term LBW. A risk prediction model was established based on the analysis results. The effectiveness of the model was analyzed using the Hosmer-Leme show test and receiver operating characteristic (ROC) curve to verify the accuracy of the predictions.
Results:
Among the 1794 pregnant women, there were 62 cases of neonatal weight < 2.5 kg, resulting in an LBW incidence rate of 3.46%. The factors influencing full-term LBW included low maternal education level [odds ratio (OR) = 1.416], fewer prenatal examinations (OR = 2.907), insufficient weight gain during pregnancy (OR = 3.695), irregular calcium supplementation during pregnancy (OR = 1.756), and pregnancy hypertension syndrome (OR = 2.192). The prediction model equation was obtained as follows: Logit (P) = 0.348 × maternal education level + 1.067 × number of prenatal examinations + 1.307 × insufficient weight gain during pregnancy + 0.563 × irregular calcium supplementation during pregnancy + 0.785 × pregnancy hypertension syndrome - 29.164. The area under the ROC curve for this model was 0.853, with a sensitivity of 0.852 and a specificity of 0.821. The Hosmer-Leme show test yielded χ 2 = 2.185, P = 0.449, indicating a good fit. The overall accuracy of the clinical validation model was 81.67%.
Conclusion:
The occurrence of full-term LBW is related to maternal education, the number of prenatal examinations, weight gain during pregnancy, calcium supplementation during pregnancy, and pregnancy-induced hypertension. The constructed predictive model can effectively predict the risk of full-term LBW.
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