scholarly journals Estimating physical activity energy expenditure, sedentary time, and physical activity intensity by self-report in adults

2009 ◽  
Vol 91 (1) ◽  
pp. 106-114 ◽  
Author(s):  
Hervé Besson ◽  
Søren Brage ◽  
Rupert W Jakes ◽  
Ulf Ekelund ◽  
Nicholas J Wareham
Author(s):  
Angelika Wientzek ◽  
Anna Floegel ◽  
Sven Knüppel ◽  
Matthaeus Vigl ◽  
Dagmar Drogan ◽  
...  

The aim of our study was to investigate the relationship between objectively measured physical activity (PA) and cardiorespiratory fitness (CRF) and serum metabolites measured by targeted metabolomics in a population- based study. A total of 100 subjects provided 2 fasting blood samples and engaged in a CRF and PA measurement at 2 visits 4 months apart. CRF was estimated from a step test, whereas physical activity energy expenditure (PAEE), time spent sedentary and time spend in vigorous activity were measured by a combined heart rate and movement sensor for a total of 8 days. Serum metabolite concentrations were determined by flow injection analysis tandem mass spectrometry (FIA-MS/MS). Linear mixed models were applied with multivariable adjustment and p-values were corrected for multiple testing. Furthermore, we explored the associations between CRF, PA and two metabolite factors that have previously been linked to risk of Type 2 diabetes. CRF was associated with two phosphatidylcholine clusters independently of all other exposures. Lysophosphatidylcholine C14:0 and methionine were significantly negatively associated with PAEE and sedentary time. CRF was positively associated with the Type 2 diabetes protective factor. Vigorous activity was positively associated with the Type 2 diabetes risk factor in the mutually adjusted model. Our results suggest that CRF and PA are associated with serum metabolites, especially CRF with phosphatidylcholines and with the Type 2 diabetes protective factor. PAEE and sedentary time were associated with methionine. The identified metabolites could be potential mediators of the protective effects of CRF and PA on chronic disease risk.


2020 ◽  
Vol 76 ◽  
pp. 104-109 ◽  
Author(s):  
Florêncio Diniz-Sousa ◽  
Lucas Veras ◽  
José Carlos Ribeiro ◽  
Giorjines Boppre ◽  
Vítor Devezas ◽  
...  

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Kaitlyn P. Roland ◽  
Kayla M. D. Cornett ◽  
Olga Theou ◽  
Jennifer M. Jakobi ◽  
Gareth R. Jones

Females with Parkinson’s disease (PD) are vulnerable to frailty. PD eventually leads to decreased physical activity, an indicator of frailty. We speculate PD results in frailty through reduced physical activity.Objective. Determine the contribution of physical activity on frailty in PD (n=15, 65 ± 9 years) and non-PD (n=15, 73 ± 14 years) females.Methods. Frailty phenotype (nonfrail/prefrail/frail) was categorized and 8 hours of physical activity was measured using accelerometer, global positioning system, and self-report. Two-way ANCOVA (age as covariate) was used to compare physical activity between disease and frailty phenotypes. Spearman correlation assessed relationships, and linear regression determined associations with frailty.Results. Nonfrail recorded more physical activity (intensity, counts, self-report) compared with frail. Self-reported physical activity was greater in PD than non-PD. In non-PD, step counts, light physical activity time, sedentary time, and self-reported physical activity were related to frailty (R=0.91). In PD, only carbidopa-levodopa dose was related to frailty (r=0.61).Conclusion. Physical activity influences frailty in females without PD. In PD females, disease management may be a better indicator of frailty than physical activity. Further investigation into how PD associated factors contribute to frailty is warranted.


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