Hierarchical framework to improve individualised exercise prescription in adults: a critical review

Defining and reporting exercise intensity in interventions for older adults: a modified Delphi process

BACKGROUND

Many exercise studies, including older adults, do not report all relevant exercise characteristics. Especially the description of exercise intensity is missing and mostly not controlled. This leads to difficulties in interpreting study results and summarizing the evidence in systematic reviews or meta-analyses. Therefore, the aim of the present Delphi study was to gain recommendations about the categorization of exercise intensity and for the conducting and reporting of characteristics in future intervention studies with older adults by experts in exercise science and physiology.

METHODS

Two hundred ninety-seven international interdisciplinary participants from an EU COST action were invited to participate in three rounds of online questionnaires in April/May 2023. Up to N = 93 experts participated in each round. Round 1 included open-ended questions to solicit possible recommendations and categorizations for light, moderate, vigorous, and high intensity. In round 2, the experts rated their agreement using Likert scales (1-10) on the revealed categories and recommendations. Clusters with a higher average rating of M = 8.0 were summarized into round 3. In the final round, the results were presented for a final rating of agreement (based on a simple majority > 50%).

RESULTS

In round 1 a total of 416 qualitative statements were provided from thirteen questions. From round 1 to round 3, a total of 38 items were excluded, with 205 items retained for the final consensus. In round three 37 participants completed the whole questionnaire. The experts showed overall agreement on the final categorizations with 6.7 to 8.8 out of 10 points on the Likert scale. They also showed broad consensus on the relevance of reporting exercise intensity and the recommendations for future conducting and reporting of study results. However, exercise types such as yoga, balance, and coordination training led to conflicting results for categorization into light or moderate.

DISCUSSION AND IMPLICATIONS

The results of the current survey can be used to classify the intensity of exercise and suggest a practical approach that can be adopted by the scientific community and applied when conducting systematic reviews and meta-analysis articles when vital and objective information regarding exercise intensity is lacking from the original article.

Prescribing statin therapy in physically (in)active individuals vs prescribing physical activity in statin-treated patients: A four-scenario practical approach

Statins are among the most commonly prescribed medications worldwide. Statin-associated muscle symptoms (SAMS) represent a frequent statin-related adverse effect associated with statin discontinuation and increased cardiovascular disease (CVD) events. Emerging evidence indicate that the majority of SAMS might not be actually caused by statins, and the nocebo/drucebo effect (i.e. adverse effects caused by negative expectations) might also explain SAMS. Physical activity (PA) is a cornerstone in the management of CVD risk. However, evidence of increased creatine-kinase levels in statin-treated athletes exposed to a marathon has been generalized, at least to some extent, to the general population and other types of PA. This generalization is likely inappropriate and might induce fear around PA in statin users. In addition, the guidelines for lipid management focus on aerobic PA while the potential of reducing sedentary behavior and undertaking resistance training have been overlooked. The aim of this report is to provide a novel proposal for the concurrent prescription of statin therapy and PA addressing the most common and clinically relevant scenarios by simultaneously considering the different stages of statin therapy and the history of PA. These scenarios include i) statin therapy initiation in physically inactive patients, ii) PA/exercise initiation in statin-treated patients, iii) statin therapy initiation in physically active patients, and iv) statin therapy in athletes and very active individuals performing SAMS-risky activities.

Variability in exercise tolerance and physiological responses to exercise prescribed relative to physiological thresholds and to maximum oxygen uptake

NEW FINDINGS

What is the central question of this study? Does prescribing exercise intensity using physiological thresholds create a more homogeneous exercise stimulus than using traditional intensity anchors? What is the main finding and its importance? Prescribing exercise using physiological thresholds, notably critical power, reduced the variability in exercise tolerance and acute metabolic responses. At higher intensities, approaching or exceeding the transition from heavy to severe intensity exercise, the imprecision of using fixed %V ̇ O 2 max ${\dot V_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$  as an intensity anchor becomes amplified.

ABSTRACT

The objective of this study was to determine whether the variability in exercise tolerance and physiological responses is lower when exercise is prescribed relative to physiological thresholds (THR) compared to traditional intensity anchors (TRAD). Ten individuals completed a series of maximal exercise tests and a series of moderate (MOD), heavy (HVY) and severe intensity (HIIT) exercise bouts prescribed using THR intensity anchors (critical power and gas exchange threshold) and TRAD intensity anchors (maximum oxygen uptake;V ̇ O 2 max ${\dot V_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ ). There were no differences in exercise tolerance or acute response variability between MODTHR and MODTRAD . All individuals completed HVYTHR but only 30% completed HVYTRAD . Compared to HVYTHR , where work rates were all below critical power, work rates in HVYTRAD exceeded critical power in 70% of individuals. There was, however, no difference in acute response variability between HVYTHR and HVYTRAD . All individuals completed HIITTHR but only 20% completed HIITTRAD . The variability in peak (F = 0.274) and average (F = 0.318) blood lactate responses was lower in HIITTHR compared to HIITTRAD . The variability in W' depletion (the finite work capacity above critical power) after the final interval bout was lower in HIITTHR compared to HIITTRAD (F = 0.305). Using physiological thresholds to prescribe exercise intensity reduced the heterogeneity in exercise tolerance and physiological responses to exercise spanning the boundary between the heavy and severe intensity domains. To increase the precision of exercise intensity prescription, it is recommended that, where possible, physiological thresholds are used in place ofV ̇ O 2 max ${\dot V_{{{\rm{O}}_{\rm{2}}}{\rm{max}}}}$ .

Maximum Heart Rate- and Lactate Threshold-Based Low-Volume High-Intensity Interval Training Prescriptions Provide Similar Health Benefits in Metabolic Syndrome Patients

Exercise is an integral part of metabolic syndrome (MetS) treatment. Recently, low-volume high-intensity interval training (LOW-HIIT) has emerged as a time-efficient approach to improving cardiometabolic health. Intensity prescriptions for LOW-HIIT are typically based on maximum heart rate (HR_max) percentages. However, HR_max determination requires maximal effort during exercise testing, which may not always be feasible/safe for MetS patients. This trial compared the effects of a 12-week LOW-HIIT program based on: (a) HR_max (HIIT-HR), or (b) submaximal lactate threshold (HIIT-LT), on cardiometabolic health and quality of life (QoL) in MetS patients. Seventy-five patients were randomized to HIIT-HR (5 × 1 min at 80-95% HR_max), HIIT-LT (5 × 1 min at 95-105% LT) groups, both performed twice weekly on cycle ergometers, or a control group (CON). All patients received nutritional weight loss consultation. All groups reduced their body weight (HIIT-HR: -3.9 kg, p < 0.001; HTT-LT: -5.6 kg, p < 0.001; CON: -2.6 kg, p = 0.003). The HIIT-HR and HIIT-LT groups similarly, improved their maximal oxygen uptake (+3.6 and +3.7 mL/kg/min, p < 0.001), glycohemoglobin (-0.2%, p = 0.005, and -0.3%, p < 0.001), homeostasis model assessment index (-1.3 units, p = 0.005, and -1.0 units, p = 0.014), MetS z-score (-1.9 and -2.5 units, p < 0.001) and QoL (+10 points, p = 0.029, and +11 points, p = 0.002), while the CON did not experience changes in these variables. We conclude that HIIT-LT is a viable alternative to HIIT-HR for patients who are not able/willing to undergo maximal exercise testing.

Agreement and relationship between measures of absolute and relative intensity during walking: A systematic review with meta-regression

INTRODUCTION

A metabolic equivalent (MET) is one of the most common methods used to objectively quantify physical activity intensity. Although the MET provides an 'objective' measure, it does not account for inter-individual differences in cardiorespiratory fitness. In contrast, 'relative' measures of physical activity intensity, such as heart rate reserve (HRR), do account for cardiorespiratory fitness. The purpose of this systematic review with meta-regression was to compare measures of absolute and relative physical activity intensity collected during walking.

METHODS

A systematic search of four databases (SPORTDiscus, Medline, Academic Search Premier and CINAHL) was completed. Keyword searches were: (i) step* OR walk* OR strid* OR "physical activity"; (ii) absolute OR "absolute intensity" OR mets OR metabolic equivalent OR actigraph* OR acceleromet*; (iii) relative OR "relative intensity" OR "heart rate" OR "heart rate reserve" OR "VO2 reserve" OR VO2* OR "VO2 uptake" OR HRmax* OR metmax. Categories (i) to (iii) were combined using 'AND;' with studies related to running excluded. A Bayesian regression was conducted to quantify the relationship between METs and %HRR, with Bayesian logistic regression conducted to examine the classification agreement between methods. A modified Downs and Black scale incorporating 13 questions relative to cross-sectional study design was used to assess quality and risk of bias in all included studies.

RESULTS

A total of 15 papers were included in the systematic review. A comparison of means between absolute (METs) and relative (%HRR, %HRmax, %VO2R, %VO2max, HRindex) values in 8 studies identified agreement in how intensity was classified (light, moderate or vigorous) in 60% of the trials. We received raw data from three authors, incorporating 3 studies and 290 participants. A Bayesian random intercept logistic regression was conducted to examine the agreement between relative and absolute intensity, showing agreement in 43% of all trials. Two studies had identical relative variables (%HRR) totalling 240 participants included in the Bayesian random intercept regression. The best performing model was a log-log regression, which showed that for every 1% increase in METs, %HRR increased by 1.12% (95% CI: 1.10-1.14). Specifically, the model predicts at the lower bound of absolute moderate intensity (3 METs), %HRR was estimated to be 33% (95%CI: 18-57) and at vigorous intensity (6 METs) %HRR was estimated to be 71% (38-100).

CONCLUSION

This study highlights the discrepancies between absolute and relative measures of physical activity intensity during walking with large disagreement observed between methods and large variation in %HRR at a given MET. Consequently, health professionals should be aware of this lack of agreement between absolute and relative measures. Moreover, if we are to move towards a more individualised approach to exercise prescription and monitoring as advocated, relative intensity could be more highly prioritised.