Introduction: Nutritional exposure is considered the main environmental influence that contributes to gallstone disease (GD).
Aim: The aim of this study was to determine food intakes patters and estimate risk of GD.
Methods: A nested case-control study was carried out within the framework of a previous screening study conducted on a representative sample in Rosario, Argentina. Participants underwent a personal interview. Average amount of each food intake and quantity nutrients were estimated applying a food-frequency questionnaire. Food consumption patterns were identified by principal component analysis, and logistic regression analysis was used to estimate risks.
Results: The sample was conformed by 51 cases and 69 controls. Two dietary patterns were identified. Cases were characterised by the unhealthy intake pattern (high intakes of animal fats, sugar, cereals, grains, cold cuts, processed meats, chicken with skin, fat beef and low intake of red vegetables and yellows, cabbages, fruits and fish).
Conclusion: Controls were characterised by the healthy intake pattern (high intake of skinless chicken, nuts, lean beef, vitamin A and C rich fruits, and low consumption of chicken with skin, green leaves vegetables and sprouts). The unhealthy pattern showed an increased risk of developing GD while healthy patter behaved as a protective factor.
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http://dx.doi.org/10.31053/1853.0605.v81.n2.36961 | DOI Listing |
Sci Rep
December 2024
Department of Civil Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Deep learning models are widely used for traffic forecasting on freeways due to their ability to learn complex temporal and spatial relationships. In particular, graph neural networks, which integrate graph theory into deep learning, have become popular for modeling traffic sensor networks. However, traditional graph convolutional networks (GCNs) face limitations in capturing long-range spatial correlations, which can hinder accurate long-term predictions.
View Article and Find Full Text PDFSci Rep
December 2024
School of Computer and Information Engineering, Hubei Normal University, Huangshi, 435002, China.
For finely representation of complex reservoir units, higher computing overburden and lower spatial resolution are limited to traditional stochastic simulation. Therefore, based on Generative Adversarial Networks (GANs), spatial distribution patterns of regional variables can be reproduced through high-order statistical fitting. However, parameters of GANs cannot be optimized under insufficient training samples.
View Article and Find Full Text PDFNat Commun
December 2024
Anthropology Department, University of California Santa Cruz, Santa Cruz, CA, USA.
Strontium isotope (Sr/Sr) analysis with reference to strontium isotope landscapes (Sr isoscapes) allows reconstructing mobility and migration in archaeology, ecology, and forensics. However, despite the vast potential of research involving Sr/Sr analysis particularly in Africa, Sr isoscapes remain unavailable for the largest parts of the continent. Here, we measure the Sr/Sr ratios in 778 environmental samples from 24 African countries and combine this data with published data to model a bioavailable Sr isoscape for sub-Saharan Africa using random forest regression.
View Article and Find Full Text PDFAm J Hum Biol
January 2025
LIFE Research Group, University Jaume I, Castellon, Spain.
Background: Previous research in adults has suggested that healthy dietary patterns could be an effective strategy for blood pressure (BP) control. However, during adolescence, the scientific literature examining this relationship is scarce and controversial since inverse and null associations have been reported. Thus, the aim of our study was to analyze the relationship between the level of adherence to the Mediterranean diet (MD) and consumption of fresh fruits and vegetables at baseline with changes in BP over a two-year period during adolescence.
View Article and Find Full Text PDFIndian J Med Res
November 2024
Department of Community Medicine, Burdwan Medical College & Hospital, Kolkata, West Bengal, India.
Background & objectives Non communicable diseases (NCD) have emerged as one of the leading causes of mortality and morbidity in India in the past few decades. This study was undertaken to determine the prevalence of NCD risk factors among adults residing in urban slums of West Bengal, India. Methods A community based cross-sectional study was conducted among adult population aged 15-69 yr in urban slums of Purba Burdwan district, West Bengal over a period of two months.
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