Pregnancy-Associated Plasma Protein A (PAPP-A) as a Predictor of Third Trimester Obesity: Insights from the CRIOBES
Inmaculada Gabaldón-Rodríguez1, Carmen de Francisco-Montero1, Inmaculada Menéndez-Moreno1
1Andalusian Health Service, Primary Care Seville District, 41004 Seville, Spain.
Insights
This study developed a predictive model for third-trimester obesity using pregnancy biomarkers. Pregnancy-associated plasma protein-A (PAPP-A) and systolic blood pressure (SBP) show predictive value for obesity risk.
Area of Science:
- Obstetrics and Gynecology
- Maternal-Fetal Medicine
- Public Health
Background:
- Obesity in pregnancy poses risks to both mother and child.
- Predictive models for gestational obesity can aid early intervention.
- Biomarkers managed within routine antenatal care offer potential for predictive modeling.
Purpose of the Study:
- To develop a predictive model for third-trimester obesity.
- To utilize plasma and clinical biomarkers from the Chromosomopathies Programme.
- To apply these biomarkers within the Andalusian Public Healthcare System.
Main Methods:
- Observational, unmatched case-control study design.
- Data collected from 2011-2021 in Seville Primary Healthcare District.
- Binary logistic regression models used to identify predictors of third-trimester obesity.
Main Results:
- 104 cases and 423 controls identified for third-trimester obesity.
- The final model included PAPP-A, beta-hCG, and systolic blood pressure (SBP).
- The model achieved an ROC curve of 0.75, indicating moderate predictive accuracy.
Conclusions:
- PAPP-A is a significant predictor of third-trimester obesity risk in uncomplicated pregnancies.
- Beta-hCG and 12-week SBP enhance the predictive capacity of the model.
- The developed model is applicable to primary care settings for uncomplicated pregnancies.
Abstract:
Introduction: Our objective in this article was to develop a predictive model for obesity in the third trimester of pregnancy using the plasma and clinical biomarkers that are managed within the Chromosomopathies Programme in the Andalusian Public Healthcare System. Methods: The epidemiological design was observational, of the unmatched case-control type. The geographical environment was the Seville Primary Healthcare District (DSAP Sevilla). The information was collected between 2011 and 2021. The reference cohort consisted of women who had carried a pregnancy to term. The variables and biomarkers studied correspond to those managed within the primary-care Pregnancy Integrated Care Pathway (ICP). Unconditional binary logistic regression (BLR) models were created, with the outcome variable being whether or not the women were obese in their third trimester of pregnancy. Results: A total of 423 controls and 104 cases of obesity were obtained for women in their third trimester who had not been obese in their first trimester. The average age for the sample group (P50) was 34 years old. The final, most parsimonious model included the variables PAPP-A (p = 0.074), beta-hCG (p = 0.1631), and systolic blood pressure (SBP) (p = 0.085). ROC curve = 0.75 (C.I. at 95%: 0.63-0.86). Discussion: The results of this research can only be extrapolated to primary care and to pregnancies with no complications. PAPP-A has been shown in our research to be a significant predictor of obesity risk in the third trimester of pregnancies with no complications (OR = 0.53; C.I. at 95%: 0.39-0.66; p = 0.04 in the single-variant study; OR = 0.58; C.I. at 95%: 0.29-0.93; p = 0.074 in the multi-variant analysis). This predictive capacity is further enhanced from an operational perspective by beta-hCG and 12-week SBP.
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