Association between Functional Fitness and Health-Related Quality of Life in the Balearic Islands' Old Adults with Metabolic Syndrome.
Javier Conde-PipòCristina BouzasMiguel Mariscal-ArcasJosep Antonio TurPublished in: Nutrients (2022)
Research assessing the relationship between functional fitness (FF) and health-related quality of life (HRQoL) is still scarce. The objective of this research is to assess the association between FF and HRQoL in older adults with metabolic syndrome (MetS) from Balearic Islands (Spain). The design is a cross-sectional, descriptive, and comparative study involving 209 participants (42.2% women). The sociodemographic data and medical history of the participants were collected. Physical activity was evaluated using the Spanish version of the Rapid Assessment of Physical Activity Questionnaire. Anthropometrics and blood pressure were measured. Glucose, total cholesterol, high-density lipoprotein cholesterol, and triglyceride plasma levels were measured. A battery of functional fitness tests was applied. HRQoL was measured with the Spanish version of the SF-36 questionnaire. Adherence to the Mediterranean dietary pattern was assessed. In older subjects with MetS, a higher FF score and, within it, endurance, lower body strength, one-leg balance, and agility are positively associated with lower physical function ( p < 0.001; d = 0.56), better general health ( p = 0.019; d = 0.35), and better summary physical component of HRQoL ( p < 0.001; d = 0.57). The FF score and HRQoL physical component are both positively associated with high levels of physical activity (ORadj = 10.3, IC 4.19-28.2, p < 0.001; ORadj = 3.25, IC 1.44-7.72, p < 0.005). Older adults with MetS should consider practicing physical activity above the general recommendations to improve their functional fitness and health status and quality of life.
Keyphrases
- physical activity
- metabolic syndrome
- psychometric properties
- blood pressure
- body mass index
- healthcare
- cross sectional
- sleep quality
- public health
- uric acid
- risk assessment
- depressive symptoms
- type diabetes
- machine learning
- big data
- body composition
- heart rate
- adipose tissue
- cardiovascular risk factors
- blood glucose
- health information
- deep learning
- artificial intelligence
- patient reported
- human health