Institute of Genetic Epidemiology, Medical University of Innsbruck, Schoepfstrasse 41, 6020, Innsbruck, Austria. Electronic address: Stefan.Coassin@i-med.ac.at.
1 BK21 Plus KNU Creative BioResearch Group, School of Life Sciences, Institute of Life Science and Biotechnology, Kyungpook National University, Daegu, Korea.
1 BK21 Plus KNU Creative BioResearch Group, School of Life Sciences, Institute of Life Science and Biotechnology, Kyungpook National University, Daegu, Korea.
1 BK21 Plus KNU Creative BioResearch Group, School of Life Sciences, Institute of Life Science and Biotechnology, Kyungpook National University, Daegu, Korea.
9 Brain Science and Engineering Institute, Kyungpook National University, Daegu, Korea.
The Armenise-Harvard Laboratory of Structural Biology, Department of Biology and Biotechnology, University of Pavia, Via Ferrata 9A, 27100 Pavia, Italy.
Department of Molecular Medicine, Unit of Immunology and General Pathology, University of Pavia, Pavia, Italy. Electronic address: claudia.scotti@unipv.it.
Cardiometabolic diseases are rapidly becoming primary causes of death in developing countries, including Ghana. However, risk factors for these diseases, including obesity phenotype, and availability ...
The overall goal of this study is to determine the prevalence of undiagnosed diabetes, prediabetes, and associated cardiovascular risks using a multi-sampled oral glucose tolerance test. The study wil...
The study employs a community-based quasi-experimental design, making use of pre- and post-intervention data, as well as a questionnaire survey of 1200 individuals residing in the Cape Coast metropoli...
Ethics approval was granted by the Institutional Review Board of the University of Cape Coast, Ghana (UCCIRB/EXT/2022/27). The findings will be disseminated in community workshops, online learning pla...
Family meals represent a novel strategy for improving cardiovascular health in youth. The purpose of this paper is to describe the association between family meals, dietary patterns, and weight status...
According to the American Heart Association's Life's Essential 8, poor diet quality and overweight/obesity status are key contributors to suboptimal cardiovascular health. Current literature highlight...
Chronic stress leads to circadian disruption, with variability in sleep time and duration. This scenario increases the prevalence and incidence of cardiometabolic abnormalities. Social jetlag (SJL), a...
Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder. Cardiometabolic and genetic risk factors play an important role in the trajectory of AD. Cardiometabolic risk factors including...
High intake of ultraprocessed foods (UPFs) has been associated with higher cardiometabolic risk in adults; however, the evidence in children is limited....
To investigate the association between UPF consumption and cardiometabolic risk factors in the Childhood Obesity Risk Assessment Longitudinal Study (CORALS)....
This baseline cross-sectional analysis was conducted using the data of CORALS participants recruited between March 22, 2019, and June 30, 2022. Preschool children (aged 3-6 years) were recruited from ...
Energy-adjusted UPF consumption (in grams per day) from food frequency questionnaires and based on the NOVA food classification system....
Age- and sex-specific z scores of adiposity parameters (body mass index [BMI], fat mass index, waist-to-height ratio, and waist circumference) and cardiometabolic parameters (diastolic and systolic bl...
Of 1509 enrolled CORALS participants, 1426 (mean [SD] age, 5.8 [1.1] years; 698 boys [49.0%]) were included in this study. Mothers of children with high UPF consumption were younger, had a higher BMI,...
These findings suggest that high UPF consumption in young children is associated with adiposity and other cardiometabolic risk factors, highlighting the need for public health initiatives to promote t...
To examine clustering of cardiometabolic markers in Mexican children at age 11 years and compare a metabolic syndrome (MetS) score to an exploratory cardiometabolic health (CMH) score....
We used data from children enrolled in the POSGRAD birth cohort with cardiometabolic data available (n = 413). We used principal component analysis (PCA) to derive a Metabolic Syndrome (MetS) score an...
At least one cardiometabolic risk factor was present in 42 % of study participants; the most common risk factors were low High-Density Lipoprotein (HDL) cholesterol (31.9 %) and elevated triglycerides...
MetS and CMH scores capture a similar amount of variation. Additional follow-up studies comparing predictive abilities of MetS and CMH scores may enable improved identification of children at risk for...
This study analyzes the correlation between oxidative balance score (OBS), cardiometabolic risk factors (CMRFs), and mortality in individuals with CMRFs....
Data were chosen from the National Health and Nutrition Examination Survey. The survey-weighted multivariable logistic regression models were implemented to explore the relationship between OBS and th...
Following multivariate adjustment, the subjects in the highest quartile exhibited a 46% reduction in the risk of CMRFs, a 33% reduction in the risk of diabetes, a 31% reduction in the risk of hyperten...
An increased OBS might reflect a lower risk of CMRFs and a favorable prognosis for individuals with CMRFs. Moreover, WBC and GGT may play a potential mediating role between OBS and CMRFs....
Youth with Down syndrome (DS) have a high prevalence of obesity and dyslipidemia. Diet quality may influence cardiometabolic risk (CMR) in youth....
The aim of this secondary analysis was to investigate the relationship between diet quality (Healthy Eating Index [HEI-2015]) with CMR factors in youth with DS compared with age, sex, race, ethnicity,...
Adolescents (aged 10 to 20 years) with DS and controls of comparable age, sex, race, ethnicity, and body mass index percentile were recruited from 2012 to 2017 for a cross-sectional study from two lar...
CMRs in 143 adolescents with DS were compared with 100 controls. Exclusion criteria consisted of major organ-system illnesses....
The average of three 24-hour dietary recalls was used to calculate the HEI-2015. Anthropometrics, blood pressure, and fasting labs were collected....
Group differences were tested using Wilcoxon rank-sum tests. Relationships of CMR factors with HEI-2015 score within DS and controls were tested using linear regression models adjusted for sex, age, r...
Compared with controls (n = 100, median age = 14.8 years [interquartile range = 12.2 to 17.3 years]; 41% male; 24% African American; 65% with body mass index ≥85th percentile), adolescents with DS (n ...
Adolescents in both the control and DS groups reported low-quality diets, although the DS group had HEI-2015 scores more closely aligned with recommendations. In the DS group, diet quality was not sig...
We analysed data on 2842 subjects aged ≥40 years enrolled in the National Diet and Nutrition Survey (NDNS 2008-2019). Based on serum 25(OH)D concentrations, study subjects were grouped in three catego...
With a prevalence of 15%, polycystic ovary syndrome (PCOS) is the most common endocrinopathy in fertile-aged women. Insulin resistance and obesity play a pivotal role in the pathophysiology of PCOS, m...
