Stubborn exercise responders–where to next?
- Bell, Leo, Gabbett, Tim, Davis, Gregory, Wallen, Matthew, O’Brien, Brendan
- Authors: Bell, Leo , Gabbett, Tim , Davis, Gregory , Wallen, Matthew , O’Brien, Brendan
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Sports Vol. 10, no. 6 (2022), p.
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- Description: There is a wide variance in the magnitude of physiological adaptations after resistance or endurance training. The incidence of “non” or “poor” responders to training has been reported to represent as high as 40% of the project’s sample. However, the incidence of poor responders to training can be ameliorated with manipulation of either the training frequency, intensity, type and duration. Additionally, global non‐response to cardio‐respiratory fitness training is eliminated when evaluating several health measures beyond just the target variables as at least one or more measure improves. More research is required to determine if altering resistance training variables results in a more favourable response in individuals with an initial poor response to resistance training. Moreover, we recommend abandoning the term “poor” responders, as ultimately the magnitude of change in cardiorespiratory fitness in response to endurance training is similar in “poor” and “high” responders if the training frequency is subsequently increased. Therefore, we propose “stubborn” responders as a more appropriate term. Future research should focus on developing viable physiological and lifestyle screening tests that identify likely stubborn responders to conventional exercise training guidelines before the individual engages with training. Exerkines, DNA damage, metabolomic responses in blood, saliva and breath, gene sequence, gene expression and epigenetics are candidate biomarkers that warrant investigation into their relationship with traina-bility. Crucially, viable biomarker screening tests should show good construct validity to distinguish between different exercise loads, and possess excellent sensitivity and reliability. Furthermore “red flag” tests of likely poor responders to training should be practical to assess in clinical settings and be affordable and non‐invasive. Early identification of stubborn responders would enable op-timization of training programs from the onset of training to maintain exercise motivation and optimize the impact on training adaptations and health. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Bell, Leo , Gabbett, Tim , Davis, Gregory , Wallen, Matthew , O’Brien, Brendan
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Sports Vol. 10, no. 6 (2022), p.
- Full Text:
- Reviewed:
- Description: There is a wide variance in the magnitude of physiological adaptations after resistance or endurance training. The incidence of “non” or “poor” responders to training has been reported to represent as high as 40% of the project’s sample. However, the incidence of poor responders to training can be ameliorated with manipulation of either the training frequency, intensity, type and duration. Additionally, global non‐response to cardio‐respiratory fitness training is eliminated when evaluating several health measures beyond just the target variables as at least one or more measure improves. More research is required to determine if altering resistance training variables results in a more favourable response in individuals with an initial poor response to resistance training. Moreover, we recommend abandoning the term “poor” responders, as ultimately the magnitude of change in cardiorespiratory fitness in response to endurance training is similar in “poor” and “high” responders if the training frequency is subsequently increased. Therefore, we propose “stubborn” responders as a more appropriate term. Future research should focus on developing viable physiological and lifestyle screening tests that identify likely stubborn responders to conventional exercise training guidelines before the individual engages with training. Exerkines, DNA damage, metabolomic responses in blood, saliva and breath, gene sequence, gene expression and epigenetics are candidate biomarkers that warrant investigation into their relationship with traina-bility. Crucially, viable biomarker screening tests should show good construct validity to distinguish between different exercise loads, and possess excellent sensitivity and reliability. Furthermore “red flag” tests of likely poor responders to training should be practical to assess in clinical settings and be affordable and non‐invasive. Early identification of stubborn responders would enable op-timization of training programs from the onset of training to maintain exercise motivation and optimize the impact on training adaptations and health. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Keating, Shelley, Parker, Helen, Hickman, Ingrid, Gomersall, Sjaan, Wallen, Matthew, Coombes, Jeff, Macdonald, Graeme, George, Jacob, Johnson, Nathan
- Authors: Keating, Shelley , Parker, Helen , Hickman, Ingrid , Gomersall, Sjaan , Wallen, Matthew , Coombes, Jeff , Macdonald, Graeme , George, Jacob , Johnson, Nathan
- Date: 2017
- Type: Text , Journal article
- Relation: Liver International Vol. 37, no. 12 (2017), p.1907-1915
- Full Text: false
- Reviewed:
- Description: Background & Aims: Research in NAFLD management is commonly based on quantitative assessment of liver fat by proton-magnetic resonance spectroscopy (1H-MRS), and translation of this into clinical practice is currently limited by availability and expense. Novel steatosis biomarkers have been proposed for the prediction of liver fatness; however, whether these are suitable for detecting changes in liver fat is unknown. We aimed to determine the accuracy of these indices, and waist circumference (WC), in quantifying longitudinal change in 1H-MRS-quantified liver fat. Methods: We performed a secondary analysis using data from 97 overweight/obese adults (age: 39.7±11.5 years, body mass index: 30.7±4.4 kg/m2, liver fat: 6.0±4.8%, 65% male) who completed either an 8-week exercise or 12-week nutraceutical intervention, with varying degrees of change in liver fat. Baseline and post-intervention measures were liver fat (1H-MRS), NAFLD Liver Fat Score, Liver Fat Equation (LFE), Fatty Liver Index (FLI), Hepatic Steatosis Index (HSI), the Visceral Adiposity Index (VAI) and WC. Results: Only the change in HSI, FLI and WC was associated with change in liver fat; however, correlations were weak to moderate. There was no agreement between the LFE and 1H-MRS for detecting liver fat change. Only change in WC significantly affected change in liver fat (P<.001), and WC AUROC for the presence of steatosis was 0.65 and 0.78 for men and women respectively.Conclusions: Novel indices are limited in their ability to detect longitudinal change in liver fat. Waist circumference may offer modest utility as a surrogate to infer liver fat change with lifestyle interventions.
- Description: Background & Aims: Research in NAFLD management is commonly based on quantitative assessment of liver fat by proton-magnetic resonance spectroscopy (1H-MRS), and translation of this into clinical practice is currently limited by availability and expense. Novel steatosis biomarkers have been proposed for the prediction of liver fatness; however, whether these are suitable for detecting changes in liver fat is unknown. We aimed to determine the accuracy of these indices, and waist circumference (WC), in quantifying longitudinal change in 1H-MRS-quantified liver fat. Methods: We performed a secondary analysis using data from 97 overweight/obese adults (age: 39.7±11.5 years, body mass index: 30.7±4.4 kg/m2, liver fat: 6.0±4.8%, 65% male) who completed either an 8-week exercise or 12-week nutraceutical intervention, with varying degrees of change in liver fat. Baseline and post-intervention measures were liver fat (1H-MRS), NAFLD Liver Fat Score, Liver Fat Equation (LFE), Fatty Liver Index (FLI), Hepatic Steatosis Index (HSI), the Visceral Adiposity Index (VAI) and WC. Results: Only the change in HSI, FLI and WC was associated with change in liver fat; however, correlations were weak to moderate. There was no agreement between the LFE and 1H-MRS for detecting liver fat change. Only change in WC significantly affected change in liver fat (
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