Purpose: Research suggests a relationship between birth weight and season of birth, but findings vary across countries and underlying factors are not well understood. We examine the seasonality of birth weight and explore alternative hypotheses for its etiology-exposure to environmental factors and varying socioeconomic composition of mothers-in Chile.
Methods: Birth weight of approximately 5 million Chilean singleton live births 37 of 41 weeks of gestation between 1987 and 2007 were analyzed for seasonality by using regression models with month dummies and parametric sinusoidal specifications. Multivariate models with socioeconomic covariates and interactions across geographic regions examine potential factors accounting for seasonal variation.
Results: Marked 12-month and 6-month periodic cycles were found. The amplitude and phase of the seasonal variation change across geographic regions. In the low-latitude northern region, there is a spring peak and a fall nadir, while in middle-latitude colder regions, a bimodal periodicity emerges with peaks in spring and fall, a pronounced winter nadir, and smaller nadir in the summer. Socioeconomic composition of mothers is found to vary with annual periodicity, but it does not account for the seasonality in birth weight.
Conclusions: Environmental factors rather than the socioeconomic composition of mothers likely account for seasonal variation in birth weight. The change in periodicity of birth weight across latitudes is consistent with a beneficial exposure to sunlight both early and late in the pregnancy, and a detrimental late exposure to cold temperatures only in areas with low winter temperatures.
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http://dx.doi.org/10.1016/j.annepidem.2010.08.005 | DOI Listing |
Detecting low birth weight is crucial for early identification of at-risk pregnancies which are associated with significant neonatal and maternal morbidity and mortality risks. This study presents an efficient and interpretable framework for unsupervised detection of low, very low, and extreme birth weights. While traditional approaches to managing class imbalance require labeled data, our study explores the use of unsupervised learning to detect anomalies indicative of low birth weight scenarios.
View Article and Find Full Text PDFSouth Med J
February 2025
the Department of Public Health Sciences.
Objectives: Sickle cell disease (SCD), which disproportionately affects minorities, increases complications during pregnancy. Severe maternal mortality is increased in women with SCD, including morbidity related to the disease and other nondisease-related complications. It also can have devastating complications for fetuses, with increases in premature birth and low birth weight.
View Article and Find Full Text PDFInt Urogynecol J
January 2025
School of Nursing, Binzhou Medical University, Bincheng District, No. 522, Huanghe Third Road, Binzhou, Shandong, China.
Introduction And Hypothesis: This study aims to develop a postpartum stress urinary incontinence (PPSUI) risk prediction model based on an updated definition of PPSUI, using machine learning algorithms. The goal is to identify the best model for early clinical screening to improve screening accuracy and optimize clinical management strategies.
Methods: This prospective study collected data from 1208 postpartum women, with the dataset randomly divided into training and testing sets (8:2).
Purpose: To assess the association between periodontal health and pregnancy or delivery complications in type 1 diabetic (TIDM) and non-diabetic pregnant women.
Materials And Methods: 15 TIDM and 15 non-diabetic primiparous women were enrolled in the prospective case-control study. We compared periodontal status, levels of glycosylated hemoglobin (HbA1c), gestational week of birth, birth weight of a newborn and pregnancy or delivery complications between the groups.
J Neurosurg Anesthesiol
January 2025
Departments of Anesthesiology.
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