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An approach to determine the net predictive multivariate association pattern between cardiorespiratory fitness and a high-resolution physical activity spectrum in the presence of multicollinear covariates.
J Sports Sci
January 2025
Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Sogndal, Norway.
Multivariate pattern analysis was recently extended with covariate projections to solve the challenging task of modelling and interpreting associations in the presence of linear dependent multivariate covariates. Within a joint model, this approach allows quantification of the net association pattern between the outcome and the explanatory variables and between the individual covariates and these variables. The aim of this paper is to apply this methodology to establish the net multivariate association pattern between cardiorespiratory fitness (CRF) and a high-resolution linear dependent physical activity (PA) intensity descriptor derived from accelerometry in children and to validate the crucial sub-regions in the PA spectrum predicting CRF.
View Article and Find Full Text PDFUnderstanding the local-level variations in seasonality of human respiratory syncytial virus infection: a systematic analysis.
BMC Med
January 2025
Department of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China.
Background: While previous reports characterised global and regional variations in RSV seasonality, less is known about local variations in RSV seasonal characteristics. This study aimed to understand the local-level variations in RSV seasonality and to explore the role of geographical, meteorological, and socio-demographic factors in explaining these variations.
Methods: We conducted a systematic literature review to identify published studies reporting data on local-level RSV season onset, offset, or duration for at least two local sites.
Impact of positive psychological capital and shared leadership on nurses' organizational well-being: a descriptive survey study.
BMC Nurs
January 2025
College of Nursing, Pusan National University, Yangsan-si, Gyeongsangnam-do, Korea.
Background: Organizational well-being is a critical issue that should be addressed within nursing organizations as it boosts the morale and work motivation of its members by enhancing their satisfaction and happiness.
Aim: This study aimed to evaluate the levels of positive psychological capital, shared leadership, and organizational well-being among nurses, and examine the impact of positive psychological capital and shared leadership on organizational well-being.
Methods: A descriptive survey research design was used, involving 177 nurses with at least one year of work experience at highly specialized hospitals in Korea treating patients with severe conditions.
Association between early dietary patterns and cardiometabolic health at age 8: a confirmatory analysis of the European Childhood Obesity Project.
Nutr J
January 2025
Paediatrics, Nutrition and Development Research Unit, Universitat Rovira i Virgili. Reus, Tarragona, Spain.
Background & Aim: Metabolic and cardiovascular health outcomes are strongly influenced by diet. Dietary habits established in early childhood may persist into adulthood. This study aimed to examine the association between dietary patterns at both 2 and 8 years of age, explaining the maximum variability of high- and low-quality fats, sugars, and fibre, and cardiometabolic markers at age 8 years.
View Article and Find Full Text PDFAI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
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