The relationship between physical fitness capacity and risk factors of metabolic syndrome

Physiotherapy ◽  
2015 ◽  
Vol 101 ◽  
pp. e598-e599 ◽  
Author(s):  
C.-Y. Huang ◽  
H.-Y. Chen ◽  
S.-S. Liu
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Physical Fitness ◽  
The Relationship

scholarly journals Metabolic syndrome in psychiatry: advances in understanding and management

2014 ◽  
Vol 20 (2) ◽  
pp. 101-112 ◽  
Author(s):  
Cyrus S. H. Ho ◽  
Melvyn W. B. Zhang ◽  
Anselm Mak ◽  
Roger C. M. Ho
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Psychiatric Disorders ◽  
Psychiatric Patients ◽  
Learning Objectives ◽  
List Type ◽  
Type Number ◽  
Unhealthy Lifestyle ◽  
Definition Of ◽  
The Relationship

SummaryMetabolic syndrome comprises a number of cardiovascular risk factors that increase morbidity and mortality. The increase in incidence of the syndrome among psychiatric patients has been unanimously demonstrated in recent studies and it has become one of the greatest challenges in psychiatric practice. Besides the use of psychotropic drugs, factors such as genetic polymorphisms, inflammation, endocrinopathies and unhealthy lifestyle contribute to the association between metabolic syndrome and a number of psychiatric disorders. In this article, we review the current diagnostic criteria for metabolic syndrome and propose clinically useful guidelines for psychiatrists to identify and monitor patients who may have the syndrome. We also outline the relationship between metabolic syndrome and individual psychiatric disorders, and discuss advances in pharmacological treatment for the syndrome, such as metformin.LEARNING OBJECTIVES•Be familiar with the definition of metabolic syndrome and its parameters of measurement.•Appreciate how individual psychiatric disorders contribute to metabolic syndrome and vice versa.•Develop a framework for the prevention, screening and management of metabolic syndrome in psychiatric patients.

scholarly journals Osteoprotegerin in Cardiometabolic Disorders

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
C. Pérez de Ciriza ◽  
A. Lawrie ◽  
N. Varo
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Metabolic Syndrome ◽  
Positive Relationship ◽  
Bone Remodelling ◽  
Potential Biomarker ◽  
Cardiometabolic Disorders ◽  
Obesity Hypertension ◽  
The Relationship

Osteoprotegerin (OPG), a glycoprotein traditionally implicated in bone remodelling, has been recently related to cardiovascular disease (CVD). Human studies show a positive relationship between circulating OPG, vascular damage, and CVD, and as such OPG has emerged as a potential biomarker for CVD. This review focuses on the relationship between circulating OPG and different endocrine cardiometabolic alterations such as type 1 and 2 diabetes. The association of OPG with diabetic complications (neuropathy, nephropathy, or retinopathy) as well as with atherosclerosis, coronary artery calcification, morbidity, and mortality is pointed out. Moreover, OPG modulation by different treatments is also established. Besides, other associated diseases such as obesity, hypertension, and metabolic syndrome, which are known cardiovascular risk factors, are also considered.

scholarly journals Ultraviolet A Radiation and COVID-19 Deaths in the USA with replication studies in England and Italy

2020 ◽  
Author(s):  
Mark Cherrie ◽  
Tom Clemens ◽  
Claudio Colandrea ◽  
Zhiqiang Feng ◽  
David J Webb ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Risk Factors ◽  
Metabolic Syndrome ◽  
Vitamin D ◽  
Meteorological Conditions ◽  
Ultraviolet A ◽  
Replication Studies ◽  
The Usa ◽  
The Relationship ◽  
Uva Radiation

AbstractSeasonal variation in environmental meteorological conditions affect the incidence of infectious diseases. Ultraviolet A (UVA) radiation induces release of cutaneous photolabile nitric oxide (NO) impacting the cardiovascular system and metabolic syndrome, COVID-19 risk factors. NO also inhibits the replication of SARS-CoV. We therefore model the relationship between UVA radiation, derived from remote sensed data, and COVID-19 deaths for counties across the USA during their ‘UV vitamin D winter’ (Jan-April) adjusting for confounding including by temperature and humidity. The Mortality Risk Ratio (MRR) falls by 29% (40% -15% (95% CI)) per 100 (KJ/m2) increase in mean daily UVA. We replicate this in independent studies in Italy and England and estimate a pooled decline in MRR of 32% (48%-12%) per 100 KJ/m2 across the three studies.

scholarly journals Metabolic Syndrome and Physical Performance: The Moderating Role of Cognition among Middle-to-Older-Aged Adults

2020 ◽  
pp. 1-9
Author(s):  
Elisa F. Ogawa ◽  
Elizabeth Leritz ◽  
Regina McGlinchey ◽  
William Milberg ◽  
Jonathan F. Bean
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Executive Function ◽  
Physical Performance ◽  
Explicit Memory ◽  
Gait Speed ◽  
Metabolic Risk Factors ◽  
Metabolic Risk ◽  
Mobility Performance ◽  
The Relationship

Abstract Objective: Mobility limitation and cognitive decline are related. Metabolic syndrome (MetS), the clustering of three or more cardiovascular risk factors, is associated with decline in both mobility and cognition. However, the interrelationship among MetS, mobility, and cognition is unknown. This study investigated a proposed pathway where cognition moderates the relationship between MetS and Mobility. Method: Adults ages 45–90 years were recruited. MetS risk factors and mobility performance (Short Physical Performance Battery (SPPB) and gait speed) were evaluated. Cognition was assessed using a comprehensive neuropsychological battery. A factor analysis of neuropsychological test scores yielded three factors: executive function, explicit memory, and semantic/contextual memory. Multivariable linear regression models were used to examine the relationship among MetS, mobility, and cognition. Results: Of the 74 participants (average age 61 ± 9 years; 41% female; 69% White), 27 (36%) participants manifested MetS. Mean SPPB score was 10.9 ± 1.2 out of 12 and gait speed was 1.0 ± 0.2 m/s. There were no statistically significant differences in mobility by MetS status. However, increase in any one of the MetS risk factors was associated with decreased mobility performance after adjusting for age and gender (SPPB score: β (SE) -.17 (0.08), p < .05; gait speed: -.03 (.01), p < .01). Further adjusting for cognitive factors (SPPB score: explicit memory .31 (.14), p = .03; executive function 0.45 (0.13), p < .01; gait speed: explicit memory 0.04 (0.02), p = .03; executive function 0.06 (0.02), p < .01) moderated the relationships between number of metabolic risk factors and mobility. Conclusion: The relationship between metabolic risk factors and mobility may be moderated by cognitive performance, specifically through executive function and explicit memory.

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