Background And Objective: There is a paucity of prospective evidence examining the links between sedentary time (ST) and cardiometabolic outcomes in youth. We examined the associations between objectively assessed ST and moderate to vigorous physical activity (MVPA) in childhood with cardiometabolic risk in adolescence.
Methods: The study included 4639 children (47% male) aged 11 to 12 years at baseline whose mothers were enrolled in ALSPAC (Avon Longitudinal Study of Parents and Children) during their pregnancy in the early 1990s. A total of 2963 children had valid blood samples at age 15 to 16 years. Associations with baseline ST and MVPA were examined for BMI, waist circumference, body fat mass, lean body mass, systolic and diastolic blood pressure, fasting triglycerides, total cholesterol, low-density lipoprotein and high-density lipoprotein (HDL) cholesterol, glucose, insulin, C-reactive protein, and a clustered standardized cardiometabolic risk score (CMscore).
Results: Baseline ST was not associated deleteriously with any cardiometabolic markers. MVPA was beneficially associated with the 3 adiposity indicators, lean body mass, systolic blood pressure, triglycerides, C-reactive protein, insulin, HDL cholesterol, and CMscore; once the models were adjusted for baseline levels of these markers, these associations remained for body fat mass (mean difference per 10 minutes of MVPA: -0.320 [95% confidence interval (CI): -0.438 to -0.203]; P < .001), HDL cholesterol (0.006 logged mmol/L [95% CI: 0.001 to 0.011]; P = .028), insulin (-0.024 logged IU/L [95% CI: -0.036 to -0.013]; P < .001), and CMscore (-0.014 [95% CI: -0.025 to -0.004]; P = .009).
Conclusions: We found no evidence linking ST in late childhood with adverse cardiometabolic outcomes in adolescence. Baseline MVPA was beneficially linked to broad cardiometabolic health in adolescence.
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http://dx.doi.org/10.1542/peds.2014-3750 | DOI Listing |
J Prev Alzheimers Dis
January 2025
School of Psychology, University of New South Wales, Sydney, NSW 2057, Australia; Neuroscience Research Australia, Margarete Ainsworth Building, 139 Barker St, Randwick NSW 2031, Australia. Electronic address:
Background: A brain healthy lifestyle, consisting of good cardiometabolic health and being cognitively and socially active in midlife, is associated with a lower risk of cognitive decline years later. However, it is unclear whether lifestyle changes over time also affect the risk for mild cognitive impairment (MCI)/dementia, and rate of cognitive decline.
Objectives: To investigate if lifestyle changes over time are associated with incident MCI/dementia risk and rate of cognitive decline.
J Prev Alzheimers Dis
January 2025
Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China. Electronic address:
Background: While optimal cardiovascular health (CVH) has been linked to a lower risk of dementia, few studies considered individuals' genetic background. We aimed to examine the interaction between CVH and genetic predisposition on dementia risk among individuals with atherosclerotic cardiovascular disease (ASCVD).
Methods: We included 30,818 ASCVD patients from the UK Biobank.
Clin Nutr ESPEN
January 2025
Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK; Institute for Food, Nutrition, and Health (IFNH), University of Reading, Reading, RG6 6AP, UK. Electronic address:
Background & Aims: Cardiometabolic traits are complex interrelated traits that result from a combination of genetic and lifestyle factors. This study aimed to assess the interaction between genetic variants and dietary macronutrient intake on cardiometabolic traits [body mass index, waist circumference, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triacylglycerol, systolic blood pressure, diastolic blood pressure, fasting serum glucose, fasting serum insulin, and glycated haemoglobin].
Methods: This cross-sectional study consisted of 468 urban young adults aged 20 ± 1 years, and it was conducted as part of the Study of Obesity, Nutrition, Genes and Social factors (SONGS) project, a sub-study of the Young Lives study.
Comput Biol Med
January 2025
Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences and Institute for Cardiovascular and Metabolic Research (ICMR), University of Reading, Reading, RG6 6DZ, UK; Institute for Food, Nutrition and Health (IFNH), University of Reading, Reading, RG6 6AH, UK. Electronic address:
Background: Machine learning (ML) integration of clinical, metabolite, and genetic data reveals variable results in predicting cardiometabolic health (CMH) outcomes. Therefore, we aim to (1) evaluate whether a multi-modal approach incorporating all three data types using ML algorithms can improve CMH outcome prediction compared to single-modal or paired-modal models, and (2) compare the methodologies used in existing prediction models.
Methods: We systematically searched five databases from 1998 to 2024 for ML predictive modelling studies using the multi-modal approach for CMH outcomes.
Nutr Metab Cardiovasc Dis
December 2024
Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain.
Backgrounds And Aim: To prospectively evaluate the associations between changes in (poly)phenol intake, body weight(BW), and physical activity(PA) with changes in an inflammatory score after 1-year.
Methods And Results: This is a prospective observational analysis involving 484 participants from the PREDIMED-Plus with available inflammatory measurements. (Poly)phenol intake was estimated using a validated semi-quantitative food frequency questionnaire and the Phenol-Explorer database.
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