Gestational Hypertension in Adolescent Mothers: A 2016-2022 Trend Analysis
Oloyede, O.; Xu, L.; Adepoju, L.
Show abstract
Hypertensive disorders in pregnancy (HDPs) significantly contribute to maternal and fetal complications, particularly in adolescent pregnancies. This study examines the prevalence and predictors of gestational hypertension (gHTN) among U.S. adolescents between 2016 and 2022, using data from the CDCs Birth Data Files. The analysis included various maternal factors, such as age, race, education, BMI, prenatal care, and participation in the Women, Infants, and Children (WIC) Nutritional Program. Logistic Regression and Random Forest models were employed to evaluate these predictors, with Random Forest showing superior predictive performance. The study found that gHTN prevalence increased from 6.72% in 2016 to 9.51% in 2022, with BMI, month prenatal visits began, WIC participation, and race emerging as key predictors. The findings highlight the importance of early prenatal care and targeted support for adolescents to manage gHTN, emphasizing the need for interventions that address modifiable risk factors such as BMI and access to nutritional programs. This research underscores the critical need for continued efforts to mitigate the rising trend of gHTN in adolescent pregnancies and improve maternal and fetal outcomes in this vulnerable population. Future studies should focus on identifying additional predictors and tailoring interventions to meet the unique needs of adolescent mothers.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Identification and Mitigation of High-Risk Pregnancy with the Community Maternal Danger Score Mobile Application in Gboko, Nigeria 95%
- Magnitude, pattern and correlates of multimorbidity among patients attending chronic outpatient medical care in Bahir Dar, northwest Ethiopia: the application of latent class analysis model 95%
- Demographic and socioeconomic determinants of access to care: A subgroup disparity analysis using new equity-focused measurements 94%
Similar papers in this journal
- Influence of parental anthropometry and gestational weight gain on intrauterine growth and neonatal outcomes: Findings from the MAI cohort study in rural India 95%
- Changes in the prevalence of the common risk factors for non-communicable diseases in Uganda between 2014 and 2023: Informed by nationally representative cross-sectional surveys 94%
- Overweight and Obesity among Women at Reproductive Age 15-49 Years Old in Cambodia: Data Analysis of Cambodia Demographic and Health Survey 2014 94%
Similar papers in this journal
- Predicting mortality in SARS-COV-2 (COVID-19) positive patients in the inpatient setting using a Novel Deep Neural Network 93%
- Predicting nutrition and environmental factors associated with female reproductive disorders using a knowledge graph and random forests 92%
- Machine Learning Directed Interventions Associate with Decreased Hospitalization Rates in Hemodialysis Patients 92%
Similar papers in this journal
- Rapid Clinical Screening and Staging for COVID-19 Severe Outcome A Hospitalization Study in New York City 94%
- Classification models for Invasive Ductal Carcinoma Progression, based on gene expression data-trained supervised machine learning 93%
- Mapping domains of early-life determinants of future multimorbidity across three UK longitudinal cohort studies 93%
Similar papers in this journal
- Beyond vaccination: A Cross-Sectional Study of the importance of Behavioral and Native Factors on COVID-19 Infection and Severity. 92%
- Machine Learning Prediction Models for Chronic Kidney Disease using National Health Insurance Claim Data in Taiwan 91%
- Analysis of daily reproduction rates of COVID-19 using Current Health Expenditure as Gross Domestic Product percentage (CHE/GDP) across countries 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.