Accuracy of Nonexercise Prediction Equations for Assessing Longitudinal Changes to Cardiorespiratory Fitness in Apparently Healthy Adults: BALL ST Cohort

Measuring Cardiorespiratory Fitness without Exercise Testing: The Development and Validation of a New Tool for Spanish Adults

Background: Cardiorespiratory fitness (CRF) is an important component of overall physical fitness and is associated with numerous health benefits, including a reduced risk of heart disease, diabetes, and obesity. However, direct measurement of CRF is time-consuming and therefore not feasible for screening purposes. Methods: A maximal treadmill exercise test with the Bruce protocol was performed to estimate VO2max in 1047 Spanish men and women aged 17 to 62 years. Weight, height, and heart rate were measured. Leisure-time physical activity (LTPA) was recorded using the Minnesota Leisure Time Physical Activity Questionnaire. A multiple linear regression model was developed to predict exercise-based VO2max. The validity of the model was examined by correlation, concordance, Bland-Altman analysis, cross-validation, and construct validity analysis. Results: There was no significant difference between VO2max obtained by the Bruce protocol (43.56 mL/kg/min) or predicted by the equation (43.59 mL/kg/min), with R2 of 0.57, and a standard error of the estimate of 7.59 mL/kg/min. Pearson's product-moment correlation and Lin's concordance correlation between measured and predicted CRF values were 0.75 and 0.72, respectively. Bland-Altman analysis revealed a significant proportional bias of non-exercise eCRF, overestimating unfit and underestimating highly fit individuals. However, 64.3% of participants were correctly classified into CRF tertile categories, with an important 69.9% in the unfit category. Conclusions: The eCRF equation was associated with several cardiovascular risk factors in the anticipated directions, indicating good construct validity. In conclusion, the non-exercise eCRF showed a reasonable validity to estimate true VO2max, and it may be a useful tool for screening CRF.

Update to the 2016 American Heart Association cardiorespiratory fitness statement

In 2016 the American Heart Association published a scientific statement that summarized a large body of evidence concluding that cardiorespiratory fitness (CRF) was a powerful marker of cardiovascular disease (CVD) and CVD-mortality risk; its association with morbidity and mortality was independent of commonly obtained risk factors, and consequently, that it should be a routine measure in all health care settings. Since 2016 the interest in CRF as a prognostic for human health and performance has increased exponentially. This review will summarize a growing body of evidence that reinforces the notion that the assessment of CRF improves patient/client management. Feasible means of CRF assessment in health care settings is considered, and the expected response of CRF to exercise consistent with consensus recommendations is reviewed. The association between CRF and health care costs is also explored. The evidence reviewed will reinforce the conclusions drawn in 2016; that overwhelming evidence demands that CRF should be a routine assessment in all health care settings - a vital sign.

Assessing cardiorespiratory fitness in clinical and community settings: Lessons and advancements in the 100th year anniversary of VO2max

Cardiorespiratory fitness (CRF) is a well-established biomarker that has applications to all adults across the health and disease spectrum. Despite overwhelming evidence supporting the prognostic utility of CRF, it remains vastly underutilized. CRF is optimally measured via cardiopulmonary exercise testing which may not be feasible to implement on a large scale. Therefore, it is prudent to develop ways to accurately estimate CRF that can be applied in clinical and community settings. As such, several prediction equations incorporating non-exercise information that is readily available from routine clinical encounters have been developed that provide an adequate reflection of CRF that could be implemented to raise awareness of the importance of CRF. Further, technological advances in smartphone apps and consumer-grade wearables have demonstrated promise to provide reasonable estimates of CRF that are widely available, which could enhance the utilization of CRF in both clinical and community settings.

2023 update: The importance of cardiorespiratory fitness in the United States

The American Heart Association issued a Policy Statement in 2013 that characterized the importance of cardiorespiratory fitness (CRF) as an essential marker of health outcomes and specifically the need for increased assessment of CRF. This statement summarized the evidence demonstrating that CRF is "one of the most important correlates of overall health status and a potent predictor of an individual's future risk of cardiovascular disease." Subsequently, this Policy Statement led to the development of a National Registry for CRF (Fitness Registry and the Importance of Exercise: A National Data Base [FRIEND]) which established normative reference values for CRF for adults in the United States (US). This review provides an overview of the progress made in the past decade to further our understanding of the importance of CRF, specifically related to prevention and for clinical populations. Additionally, this review overviews the evolvement and additional uses of FRIEND and summarizes a hierarchy of assessment methods for CRF. In summary, continued efforts are needed to expand the representation of data from across the US, and to include data from pediatric populations, to further develop the CRF Reference Standards for the US as well as further develop Global CRF Reference Standards.

Developing First Native Regression Equations to Predict of Cardiorespiratory Fitness in Healthy Boys

Background

Cardio-respiratory fitness (CRF) is a strong predictor of overall health and is considered a key physiological measure in health care settings. Maximal oxygen uptake (VO2max) is considered the gold standard for measuring CRF. Non-exercise VO2max regression equations provide a safe, simple and relatively accurate means of measuring CRF in the general population. This study aimed to develop first native regression equations to predict of CRF without exercise test in Iranian healthy boys.

Methods

Laboratory gold standard CRF and anthropometric variables were measured in 597 healthy boys (8-17 yr) in Hmadan City, Iran in 2019. Multiple regression analysis was used to generate CRF regression equations. Cross validation of the CRF regression equations was assessed using PRESS statistics, Pearson correlation, Bland-Althman plot and paired t-test.

Results

CRF regression equations based on age, body mass index, body fat and resting heart rate were developed (R2=0.602 - 0.639, SEE = 3.42 - 3.73 ml/kg/min). PRESS statistics show that, shrinkage of the R2 (0.04 - 0.06) and the increment of SEE (0.18 - 0.25 ml/kg/min) is minor. There was strong correlation (R =0.847-0.883, P<0.001) and no significant difference (min diff= 0.09-0.18 ml/kg/min, P>0.05) between measured and predicted CRF. The Bland-Altman plot illustrates the strong agreement between the two values.

Conclusion

We introduced simple and satisfactorily accurate CRF regression equations based in healthy boys. Prediction of CRF of the boys by regression equations would provide a simple tool for assessing cardiorespiratory fitness in large studies including Iranian boys.

Estimation methods to detect changes in cardiorespiratory fitness due to exercise training and subsequent detraining

PURPOSE

To determine whether estimated maximal oxygen consumption ([Formula: see text]) can detect cardiorespiratory fitness (CRF) changes by behavioral modifications. This study compared changes in measured [Formula: see text]O_2max (m[Formula: see text]O_2max) through exercise intervention with e[Formula: see text]O_2max using a multiple regression model (MRM) and linear extrapolation method (LEM).

METHODS

A cross-sectional analysis involving 173 adults was conducted to establish an MRM by including age, sex, body mass index, questionnaire score, heart rate (HR) from step test, and m[Formula: see text]O_2max. Subsequently, 15 men participated in an intervention experiment comprising an 8-week, high-intensity interval training, followed by 8-week detraining, and completed anthropometric measurements, questionnaires, step tests, and m[Formula: see text]O_2max tests. m[Formula: see text]O_2max changes throughout the intervention were compared to e[Formula: see text]O_2max changes calculated using the MRM and LEM. The LEM used the HR during the step test with constant values (predetermined [Formula: see text]O₂), such as the Chester step test.

RESULTS

Inclusion of the step test HR in a questionnaire-based MRM improved the estimation power, although the MRM underestimated higher m[Formula: see text]O_2max values. In the intervention, m[Formula: see text]O_2max increased by 20.0 ± 14.1% (P < 0.01) and subsequently decreased by 9.5 ± 6.6% (P < 0.01) after exercise training and detraining, respectively. Significant method × time interactions were observed between m[Formula: see text]O_2max and e[Formula: see text]O_2max in the MRM but not in the LEM, i.e., an apparent systematic error (underestimation of high values) of the MRM was absent in the LEM, although the correlation between m[Formula: see text]O_2max and e[Formula: see text]O_2max using the LEM was moderate.

CONCLUSION

e[Formula: see text]O_2max, particularly using the MRM with HR as an explanatory factor, is not an appropriate method for detecting CRF changes along with behavioral modifications.

CLINICAL TRIAL REGISTRATION

Registered number, UMIN000041031; Registered date, 2020/07/08; URL, https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000046855.

A Nonexercise Prediction of Peak Oxygen Uptake for Patients With Cardiovascular Disease: DATA FROM THE FITNESS REGISTRY AND THE IMPORTANCE OF EXERCISE INTERNATIONAL DATABASE (FRIEND)

PURPOSE

Nonexercise predictions of peak oxygen uptake (V˙ o2peak ) are used clinically, yet current equations were developed from cohorts of apparently healthy individuals and may not be applicable to individuals with cardiovascular disease (CVD). Our purpose was to develop a CVD-specific nonexercise prediction equation for V˙ o2peak .

METHODS

Participants were from the Fitness Registry and Importance of Exercise International Database (FRIEND) with a diagnosis of coronary artery bypass surgery (CABG), myocardial infarction (MI), percutaneous coronary intervention (PCI), or heart failure (HF) who met maximal effort criteria during a cardiopulmonary exercise test (n = 15 997; 83% male; age 63.1 ± 10.4 yr). The cohort was split into development (n = 12 798) and validation groups (n = 3199). The prediction equation was developed using regression analysis and compared with a previous equation developed on a healthy cohort.

RESULTS

Age, sex, height, weight, exercise mode, and CVD diagnosis were all significant predictors of V˙ o2peak . The regression equation was:V˙ o2peak (mL · kg -1 · min -1 ) = 16.18 - (0.22 × age [yr]) + (3.63 × sex [male = 1; female = 0]) + (0.14 × height [cm]) - (0.12 × weight [kg]) + (3.62 × mode [treadmill = 1; cycle = 0]) - (2.70 × CABG [yes = 1, no = 0]) - (0.31 × MI [yes = 1, no = 0]) + (0.37 × PCI [yes = 1, no = 0]) - (4.47 × HF [yes = 1, no = 0]). Adjusted R 2 = 0.43; SEE = 4.75 mL · kg -1 · min -1 .Compared with measured V˙ o2peak in the validation group, percent predicted V˙ o2peak was 141% for the healthy cohort equation and 100% for the CVD-specific equation.

CONCLUSIONS

The new equation for individuals with CVD had lower error between measured and predicted V˙ o2peak than the healthy cohort equation, suggesting population-specific equations are needed for predicting V˙ o2peak ; however, errors associated with nonexercise prediction equations suggest V˙ o2peak should be directly measured whenever feasible.

A new set of estimated cardiorespiratory fitness equations are associated with cognitive performance in older adults

This study aimed to develop new equations to estimate cardiorespiratory fitness specifically for older adults and, secondly, to analyze the associations of cardiorespiratory fitness, both objectively measured and estimated using new equations, with cognitive performance. Ninety-two older adults (41 females, 65-75 years) from baseline data of a randomized controlled trial were analyzed ("ClinicalTrials.gov" Identifier: NCT03923712). Participants completed 4 measurement sessions including (i) physiological and health indicators in a laboratory setting, (ii) field-based fitness tests, (iii) sociodemographic and physical activity questionnaires, and (iv) a battery of neuropsychological tests to evaluate cognitive performance. The main findings were as follows: (i) a set of new equations with good predictive value for estimated cardiorespiratory fitness were developed (74-87%), using different scenarios of complexity and/or equipment requirements, and (ii) higher estimated cardiorespiratory fitness, even using its simplest equation (eCRF =  - 1261.99 + 1.97 × 6 min walking test (m) + 1.12 × bioimpedance basal metabolic rate (kcal/day) + 5.25 × basal heart rate (bpm)), was associated with better cognitive performance evaluated by several neuropsychological tests (i.e., language, cognitive flexibility, fluency, attention, and working memory), similar to using objectively measured cardiorespiratory fitness. In summary, a new set of estimated cardiorespiratory fitness equations have been developed with predictive values ranging from 74 to 87% that could be used based on necessity, availability of equipment, resources, or measurement context. Moreover, similar to objectively measured cardiorespiratory fitness, this measure of estimated cardiorespiratory fitness was positively associated with performance on language, fluency, cognitive flexibility, attention, and working memory, independently of sex, age, and education level.

Percentage of Age-Predicted Cardiorespiratory Fitness May Be a Stronger Risk Indicator for Incident Type 2 Diabetes Than Absolute Levels of Cardiorespiratory Fitness

PURPOSE

There are inverse and independent associations between cardiorespiratory fitness (CRF) and several adverse cardiometabolic outcomes. The percentage of age-predicted CRF (%age-predicted CRF) is comparable to absolute CRF as a risk indicator for some of these outcomes, but the association between %age-predicted CRF and risk of type 2 diabetes (T2D) has not been previously investigated. We aimed to assess the association between %age-predicted CRF and T2D in a prospective cohort study.

METHODS

Cardiorespiratory fitness, as measured directly by peak oxygen uptake, was assessed in 1901 men aged 42-60 yr who underwent cardiopulmonary exercise testing. The age-predicted CRF estimated from a regression equation for age was converted to %age-predicted CRF using (achieved CRF/age-predicted CRF) × 100. Hazard ratios (95% CI) were estimated for T2D.

RESULTS

During a median follow-up of 26.8 yr, 227 T2D cases were recorded. The risk of T2D decreased continuously with increasing %age-predicted CRF ( P value for nonlinearity = .30). A 1-SD increase in %age-predicted CRF was associated with a decreased risk of T2D in analysis adjusted for established risk factors (HR = 0.68: 95% CI, 0.59-0.79). The corresponding adjusted risk was (HR = 0.51: 95% CI, 0.35-0.75) comparing extreme tertiles of %age-predicted CRF. The respective estimates for the association between absolute CRF and T2D were-HR (95% CI)-0.71 (0.60-0.83) and 0.64 (0.44-0.95).

CONCLUSIONS

Percentage of age-predicted CRF is linearly, inversely, and independently associated with the risk of incident T2D and may be a stronger risk indicator for T2D compared to absolute CRF in a general population of middle-aged and older men.

Cardiorespiratory fitness as a vital sign of CVD risk in the COVID-19 era

The severe health consequences of the corona virus disease 2019 (COVID-19) pandemic have been exacerbated by the prevalence of cardiovascular disease (CVD) risk factors, such as physical inactivity, obesity, hypertension, and diabetes. Further, policy decisions during the pandemic augmented unhealthy lifestyle behaviors and health inequalities, likely increasing the global disease burden. Cardiorespiratory fitness (CRF) is a well-established biomarker associated with CVD risk. Emerging data demonstrate that high CRF offers some protection against severe outcomes from COVID-19 infection, highlighting the importance of CRF for population health and the potential for limiting the severity of future pandemics. CRF is best assessed by cardiopulmonary exercise testing (CPET), which will be an important tool for understanding the prolonged pathophysiology of COVID-19, the emergence of long-COVID, and the lasting effects of COVID-19 on CVD risk. Utilization of CRF and CPET within clinical settings should become commonplace because of lessons learned from the COVID-19 pandemic.

Improved VO2max Estimation by Combining a Multiple Regression Model and Linear Extrapolation Method

Maximal oxygen consumption (VO_2max) is an important health indicator that is often estimated using a multiple regression model (MRM) or linear extrapolation method (LEM) with the heart rate (HR) during a step test. Nonetheless, both methods have inherent problems. This study investigated a VO_2max estimation method that mitigates the weaknesses of these two methods. A total of 128 adults completed anthropometric measurements, a physical activity questionnaire, a step test with HR measurements, and a VO_2max treadmill test. The MRM included step-test HR, age, sex, body mass index, and questionnaire scores, whereas the LEM included step-test HR, predetermined constant VO₂ values, and age-predicted maximal HR. Systematic differences between estimated and measured VO_2max values were detected using Bland-Altman plots. The standard errors of the estimates of the MRM and LEM were 4.15 and 5.08 mL·kg^-1·min^-1, respectively. The range of 95% limits of agreement for the LEM was wider than that for the MRM. Fixed biases were not significant for both methods, and a significant proportional bias was observed only in the MRM. MRM bias was eliminated using the LEM application when the MRM-estimated VO_2max was ≥45 mL·kg^-1·min^-1. In conclusion, substantial proportional bias in the MRM may be mitigated using the LEM within a limited range.

Cardiorespiratory Fitness Moderates the Age-Related Association Between Executive Functioning and Mobility: Evidence From Remote Assessments

Background and Objectives

In older adults, executive functions are important for daily-life function and mobility. Evidence suggests that the relationship between cognition and mobility is dynamic and could vary according to individual factors, but whether cardiorespiratory fitness reduces the age-related increase of interdependence between mobility and cognition remains unexplored.

Research Design and Methods

One hundred eighty-nine participants (aged 50-87) were divided into 3 groups according to their age: middle-aged (MA; <65), young older adults (YOA; 65-74), and old older adults (OOA; ≥75). Participants performed Timed Up and Go and executive functioning assessments (Oral Trail Making Test and Phonologic verbal fluency) remotely by videoconference. Participants completed the Matthews questionnaire to estimate their cardiorespiratory fitness (VO2 max in ml/min/kg). A 3-way moderation was used to address whether cardiorespiratory fitness interacts with age to moderate the relationship between cognition and mobility.

Results

Results showed that the cardiorespiratory fitness × age interaction moderated the association between executive functioning and mobility (β = -0.05; p = .048; R2 = 17.6; p < .001). At lower levels of physical fitness (<19.16 ml/min/kg), executive functioning significantly influenced YOA's mobility (β = -0.48, p = .004) and to a greater extent OOA's mobility (β = -0.96, p = .002).

Discussion and Implications

Our results support the idea of a dynamic relationship between mobility and executive functioning during aging and suggest that physical fitness could play a significant role in reducing their interdependency.

Cardiorespiratory fitness estimations and their ability to predict all-cause mortality in patients with cardiovascular disease

Background

In cardiac rehabilitation programs, cardiorespiratory fitness is commonly estimated (eCRF) from the maximum workload achieved on a graded exercise test. This study compared four well-established eCRF equations in their ability to predict mortality in patients with cardiovascular disease (CVD).

Methods

A total of 7269 individuals with CVD were studied (81% male; age 59.4 ± 10.3yr). eCRF was calculated using equations from the American College of Sports Medicine, Bruce et al., the Fitness Registry and the Importance of Exercise International Database, and McConnell and Clark. The eCRF from each equation was compared with a RMANOVA. Cox proportional hazard models assessed the relationship between the eCRF equations and mortality risk. The predictive ability of the models was compared using the concordance index.

Results

There were 284 deaths (85% male) over a follow-up period of 5.8 ± 2.8yr. Although differences in eCRF were observed between each equation (P < 0.05), the eCRF from each of the four equations was predictive of mortality (P < 0.05). The concordance index values for each of the models were the same (0.77) indicating similar predictive performance.

Conclusions

The four well-established eCRF equations did not differ in their ability to predict mortality in patients with CVD, indicating any could be used for this purpose. However, the differences in eCRF from each of the equations suggest potential differences in their ability to guide clinical care and should be the focus of future research.

Estimated Oxygen Consumption with the Abbreviated Method and Its Association with Vaccination and PCR Tests for COVID-19 from Socio-Demographic, Anthropometric, Lifestyle, and Morbidity Outcomes in Chilean Adults

COVID-19 causes cardiovascular and lung problems that can be aggravated by confinement, but the practice of physical activity (PA) could lessen these effects. The objective of this study was to evaluate the association of maximum oxygen consumption (V˙O2max) with vaccination and PCR tests in apparently healthy Chilean adults. An observational and cross-sectional study was performed, in which 557 people from south-central Chile participated, who answered an online questionnaire on the control of COVID-19, demographic data, lifestyles, and diagnosis of non-communicable diseases. V˙O2max was estimated with an abbreviated method. With respect to the unvaccinated, those who received the first (OR:0.52 [CI:0.29;0.95], p = 0.019) and second vaccine (OR:0.33 [CI:0.18;0.59], p = 0.0001) were less likely to have an increased V˙O2max. The first vaccine was inversely associated with V˙O2max (mL/kg/min) (β:−1.68 [CI:−3.06; −0.3], p = 0.017), adjusted for BMI (β:−1.37 [CI:−2.71; −0.03], p = 0.044) and by demographic variables (β:−1.82 [CI:−3.18; −0.46], p = 0.009); similarly occur for the second vaccine (β: between −2.54 and −3.44, p < 0.001) on models with and without adjustment. Having taken a PCR test was not significantly associated with V˙O2max (mL/kg/min). It is concluded that vaccination significantly decreased V˙O2max, although it did not indicate cause and effect. There is little evidence of this interaction, although the results suggest an association, since V˙ O2max could prevent and attenuate the contagion symptoms and effects.

Current state of unhealthy living characteristics in White, African American and Latinx populations

The United States (US) is similar to most industrialized countries in that it falls short on many of the basic metrics related to cardiovascular and overall health. These metrics include nutritional patterns, levels of physical activity (PA), cardiorespiratory fitness (CRF), and prevalence of overweight and obesity. These issues are even more apparent in underserved communities, among whom unhealthy living characteristics cluster and contribute to a disproportionate chronic disease burden. The reasons for these inequities are complex and include social and economic factors as well as reduced access to health care. CRF has been demonstrated to be a critically important risk factor that tends to be lower in disadvantaged groups. In this article we discuss the current state of health & lifestyle characteristics in the US, the impact of social inequality on health, and the particular role that CRF and PA patterns play in the current state of unhealthy living characteristics as they relate to underserved populations.

A Nonexercise Estimate of Cardiorespiratory Fitness Using a Symptom Questionnaire and Clinical Variables

PURPOSE

Cardiorespiratory fitness (CRF) has recently been recognized as a risk factor for mortality, but it is not routinely measured in clinical settings. The purpose of this study was to assess a nonexercise method to estimate CRF (eCRF) and its association with mortality in a clinically referred population.

METHODS

A symptom tool, termed the Veterans Specific Activity Questionnaire (VSAQ), and nonexercise clinical variables were obtained from 1545 clinically referred subjects (60 ± 13 yr), and followed for a mean of 5.6 ± 4.2 yr. The VSAQ along with nonexercise clinical and historical variables was used to develop a multivariate model to predict achieved CRF from maximal exercise testing. Proportional hazards analysis was used to assess the association between measured and eCRF and all-cause mortality.

RESULTS

The eCRF model was significantly associated with achieved CRF (multiple R= 0.67, P< .001). Mean achieved CRF from maximal treadmill testing and eCRF were similar (8.6 ± 5.0 metabolic equivalents [METs] vs 8.7 ± 4.7 METs respectively, P= .27). Achieved CRF and eCRF performed similarly for predicting mortality. After full adjustment, each 1 MET higher increment in achieved CRF and eCRF was associated with 19% and 26% reductions in mortality risk, respectively. Compared with the lowest fit group (<5 METs), the highest CRF groups (>11 METs) had 88% and 87% lower risks for mortality for achieved CRF and eCRF, respectively.

CONCLUSIONS

A multivariable nonexercise model featuring a symptom questionnaire combined with clinical variables that are readily available during a typical clinical encounter had a reasonably strong association with achieved CRF and exhibited prognostic characteristics that were similar to achieved CRF.

Investigation of the Effects of Home-Based Exercise and Cognitive Training on Cognitive and Physical Functions in Cardiac Patients: The COVEPICARDIO Study Protocol of a Randomized Clinical Trial

Introduction: During the COVID-19 pandemic, confinement measures are likely to produce collateral damage to health (stress, confusion, anxiety), especially in frail individuals and those living with cardiovascular disease (CVD). In cardiac patients in particular, these measures dramatically increase the level of physical inactivity and sedentary lifestyle, which can decrease cardiorespiratory capacity and increase the risk of acute events, rehospitalization, and depressive syndromes. Maintaining a minimum level of physical activity and cognitive stimulation during the COVID-19 crisis is essential for cardiac patients. This study is designed to document the effects of 6 months of home-based physical exercise alone or combined with cognitive training on cognitive and physical functions in patients with CVD over 50 years old.

Methods and Analysis: 122 patients (>50 years old) with stable CVD and no contraindication to perform physical exercise training will be recruited and randomly assigned to one of the 2 following arms: (1) Home-based physical exercise alone, (2) Home-based physical exercise combined with cognitive training. The intervention lasts 6 months, with remote assessments performed prior to, mid and post-training. A follow-up 6 months after the end of the intervention (12 month) is also proposed. The primary outcome is cognition, including general functioning (Montreal Cognitive Assessment (MoCA) score), as well as performances on measures of executive functions, processing speed, and episodic memory. The secondary outcome is physical performance, including balance, gait and mobility, leg muscle strength and estimated cardiorespiratory fitness. Tertiary outcomes include mood, anxiety, and health-related quality of life as assessed by self-reported online questionnaires.

Discussion: With the COVID-19 crisis, there is a critical need for remote exercise and cognitive training, and to further investigate this topic, in particular for cardiac patients. The present context can be viewed as an opportunity to perform a major shift from center-based programs to home-based physical exercise. This is especially important to reach out to older adults living in remote areas, where access to such interventions is limited.

ClinicalTrials.gov: [https://clinicaltrials.gov/ct2/show/NCT04661189], NCT04661189.

The importance of healthy lifestyle behaviors in the prevention of cardiovascular disease

Cardiovascular disease (CVD) is the leading cause of death globally. Advancements in the treatment of CVD have reduced mortality rates, yet the global burden of CVD remains high. Considering that CVD is still largely a preventable disease, prioritizing preventative measures through healthy lifestyle (HL) behaviors is necessary to lessen the burden of CVD. HL behaviors, such as regular exercise, healthy eating habits, adequate sleep, and smoking cessation, can influence a number of traditional CVD risk factors as well as a less commonly measured risk factor, cardiorespiratory fitness (CRF). It is important to note that cardiac rehabilitation programs, which traditionally have focused on secondary prevention, also emphasize the importance of making comprehensive HL behavior changes. This review discusses preventative measures to reduce the burden of CVD through an increased uptake and assessment of HL behaviors. An overview of the importance of CRF as a risk factor is discussed along with how to improve CRF and other risk factors through HL behavior interventions. The role of the clinician for promoting HL behaviors to prevent CVD is also reviewed.

Association of Estimated Cardiorespiratory Fitness in Midlife With Cardiometabolic Outcomes and Mortality

IMPORTANCE

The associations of estimated cardiorespiratory fitness (eCRF) during midlife with subclinical atherosclerosis, arterial stiffness, incident cardiometabolic disease, and mortality are not well understood.

OBJECTIVE

To examine associations of midlife eCRF with subclinical atherosclerosis, arterial stiffness, incident cardiometabolic disease, and mortality.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included 2962 participants in the Framingham Study Second Generation (conducted between 1979 and 2001). Data were analyzed from January 2020 to June 2020.

EXPOSURES

eCRF was calculated using sex-specific algorithms (including age, body mass index, waist circumference, physical activity, resting heart rate, and smoking) and was categorized as: (1) tertiles of standardized eCRF at examination cycle 7 (1998 to 2001); (2) tertiles of standardized average eCRF between examination cycles 2 and 7 (1979 to 2001); and (3) eCRF trajectories between examination cycles 2 and 7, with the lowest tertile or trajectory (ie, low eCRF) as referent group.

MAIN OUTCOMES AND MEASURES

Subclinical atherosclerosis (carotid intima-media thickness [CIMT], coronary artery calcium [CAC] score); arterial stiffness (carotid-femoral pulse wave velocity [-1000/CFPWV]); incident hypertension, diabetes, chronic kidney disease (CKD), cardiovascular disease (CVD), and mortality after examination cycle 7.

RESULTS

A total of 2962 participants were included in this cohort study (mean [SD] age, 61.5 [9.2] years; 1562 [52.7%] women). The number of events or participants at risk after examination cycle 7 (at a mean follow-up of 15 years) was 728 of 1506 for hypertension, 214 of 2268 for diabetes, 439 of 2343 for CKD, 500 of 2608 for CVD, and 770 of 2962 for mortality. Compared with the low eCRF reference value, high single examination eCRF was associated with lower CFPWV (β [SE], -11.13 [1.33] ms/m) and CIMT (β [SE], -0.12 [0.05] mm), and lower risk of hypertension (hazard ratio [HR], 0.63; 95% CI, 0.46-0.85), diabetes (HR, 0.38; 95% CI, 0.23-0.62), and CVD (HR, 0.71; 95% CI, 0.53-0.95), although it was not associated with CKD or mortality. Similarly, compared with the low eCRF reference, high eCRF trajectories and mean eCRF were associated with lower CFPWV (β [SE], -11.85 [1.89] ms/m and -10.36 [1.54] ms/m), CIMT (β [SE], -0.19 [0.06] mm and -0.15 [0.05] mm), CAC scores (β [SE], -0.67 [0.25] AU and -0.63 [0.20] AU), and lower risk of hypertension (HR, 0.54; 95% CI, 0.34-0.87 and HR, 0.48; 95% CI, 0.34-0.68), diabetes (HR, 0.27; 95% CI, 0.15-0.48 and HR, 0.31; 95% CI, 0.18-0.54), CKD (HR, 0.63; 95% CI, 0.40-0.97 and HR, 0.64; 95% CI, 0.44-0.94), and CVD (HR, 0.46; 95% CI, 0.31-0.68 and HR, 0.43; 95% CI, 0.30-0.60). Compared with the reference value, a high eCRF trajectory was associated with lower risk of mortality (HR, 0.69; 95% CI, 0.50-0.95).

CONCLUSIONS AND RELEVANCE

In this cohort study, higher midlife eCRF was associated with lower burdens of subclinical atherosclerosis and vascular stiffness, and with a lower risk of hypertension, diabetes, chronic kidney disease, cardiovascular disease, and mortality. These findings suggest that midlife eCRF may serve as a prognostic marker for subclinical atherosclerosis, arterial stiffness, cardiometabolic health, and mortality in later life.

Prediction of Cardiorespiratory Fitness in Czech Adults: Normative Values and Association with Cardiometabolic Health

Cardiorespiratory fitness (CRF) is a strong independent predictor of morbidity and mortality. However, there is no recent information about the impact of CRF on cardiometabolic risk specifically in Central and Eastern Europe, which are characterized by different biological and social determinants of health. In this cross-sectional study normative CRF values were proposed and the association between CRF and cardiometabolic outcomes was evaluated in an adult Czechian population. In 2054 participants (54.6% females), median age 48 (IQR 19 years), the CRF was predicted from a non-exercise equation. Multivariable-adjusted logistic regressions were carried out to determine the associations. Higher CRF quartiles were associated with lower prevalence of hypertension, type 2 diabetes (T2D) and dyslipidemia. Comparing subjects within the lowest CRF, we see that those within the highest CRF had decreased chances of hypertension (odds ratio (OR) = 0.36; 95% CI: 0.22-0.60); T2D (OR = 0.16; 0.05-0.47), low HDL-c (OR = 0.32; 0.17-0.60), high low-density lipoprotein (OR = 0.33; 0.21-0.53), high triglycerides (OR = 0.13; 0.07-0.81), and high cholesterol (OR = 0.44; 0.29-0.69). There was an inverse association between CRF and cardiometabolic outcomes, supporting the adoption of a non-exercise method to estimate CRF of the Czech population. Therefore, more accurate cardiometabolic studies can be performed incorporating the valuable CRF metric.

COVEPIC (Cognitive and spOrt Virtual EPIC training) investigating the effects of home-based physical exercise and cognitive training on cognitive and physical functions in community-dwelling older adults: study protocol of a randomized single-blinded clinical trial

BACKGROUND

In the context of the COVID-19 pandemic, lockdown and social distancing measures are applied to prevent the spread of the virus. It is well known that confinement and social isolation can have a negative impact on physical and mental health, including cognition. Physical activity and cognitive training can help enhance older adults' cognitive and physical health and prevent the negative collateral impacts of social isolation and physical inactivity. The COVEPIC study aims to document the effects of 6 months of home-based physical exercise alone versus home-based physical exercise combined with cognitive training on cognitive and physical functions in adults 50 years and older.

METHODS

One hundred twenty-two healthy older adults (> 50 years old) will be recruited from the community and randomized to one of the two arms for 6 months: (1) home-based physical exercises monitoring alone and (2) combined physical exercises monitoring with home-based cognitive training. The primary outcome is cognition, including general functioning (Montreal Cognitive Assessment (MoCA) score), as well as executive functions, processing speed, and episodic memory (composite Z-scores based on validated neuropsychological tests and computerized tasks). The secondary outcome is physical functions, including balance (one-leg stance test), gait and mobility performance (Timed Up and Go, 4-meter walk test), leg muscle strength (5-time sit-to-stand), and estimated cardiorespiratory fitness (Matthews' questionnaire). Exploratory outcomes include mood, anxiety, and health-related quality of life as assessed by self-reported questionnaires (i.e., Geriatric depression scale-30 items, Perceived stress scale, State-trait anxiety inventory-36 items, Perseverative thinking questionnaire, Connor-Davidson Resilience Scale 10, and 12-item Short Form Survey).

DISCUSSION

This trial will document the remote monitoring of home-based physical exercise alone and home-based physical combined with cognitive training to enhance cognitive and physical health of older adults during the COVID-19 pandemic period. Remote interventions represent a promising strategy to help maintain or enhance health and cognition in seniors, and potentially an opportunity to reach older adults in remote areas, where access to such interventions is limited.

TRIAL REGISTRATION

Clinical trial Identifier NCT04635462 . COVEPIC was retrospectively registered on November 19, 2020.

Is estimated cardiorespiratory fitness an effective predictor for cardiovascular and all-cause mortality? A meta-analysis

BACKGROUND AND AIMS

Estimated cardiorespiratory fitness (eCRF) derived from algorithm correlates well with exercise testing-measured CRF, yet its clinical use for mortality risk stratification has not been systematically evaluated. This meta-analysis with dose-response analysis was conducted to quantify its association with risk of cardiovascular and all-cause mortality.

METHODS

Electronic databases were searched for prospective cohort studies that investigated the association of eCRF with risk of cardiovascular and all-cause mortality. Study-specific multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) per 1-metabolic equivalent (MET) higher of eCRF were pooled using a random-effects model.

RESULTS

Twenty-five datasets from 8 cohort studies that enrolled more than 170,000 participants were included. The summary HR per 1-MET higher of eCRF was 0.83 (95% CI 0.80 to 0.86) for cardiovascular mortality (11 datasets) and 0.83 (95% CI 0.78 to 0.88) for all-cause mortality (14 datasets) in the general population. These associations showed no sex-difference and were all linearly shaped (all p_nonlinearity ≥ 0.27). The performance of eCRF (assessed by the area under the curve) in discriminating future risk of cardiovascular and all-cause mortality was higher than all its components (such as physical activity, resting heart rate, and body mass index, all p < 0.05), but slightly lower than exercise testing-measured CRF.

CONCLUSIONS

Higher eCRF was independently associated with lower risk of cardiovascular and all-cause mortality in the general population, indicating that eCRF might hold the potential as an effective and practical risk prediction tool in epidemiological or population research.

Accuracy of Nonexercise Prediction Equations for Assessing Longitudinal Changes to Cardiorespiratory Fitness in Apparently Healthy Adults: BALL ST Cohort

Background

Repeated assessment of cardiorespiratory fitness (CRF) improves mortality risk predictions in apparently healthy adults. Accordingly, the American Heart Association suggests routine clinical assessment of CRF using, at a minimum, nonexercise prediction equations. However, the accuracy of nonexercise prediction equations over time is unknown. Therefore, we compared the ability of nonexercise prediction equations to detect changes in directly measured CRF.

Methods and Results

The sample included 987 apparently healthy adults from the BALL ST (Ball State Adult Fitness Longitudinal Lifestyle Study) cohort (33% women; average age, 43.1±10.4 years) who completed 2 cardiopulmonary exercise tests ≥3 months apart (3.2±5.4 years of follow‐up). The change in estimated CRF (eCRF) from 27 distinct nonexercise prediction equations was compared with the change in directly measured CRF. Analysis included Pearson product moment correlations, SEE values, intraclass correlation coefficient values, Cohen's κ coefficients, γ coefficients, and the Benjamini‐Hochberg procedure to compare eCRF with directly measured CRF. The change in eCRF from 26 of 27 equations was significantly associated to the change in directly measured CRF (P<0.001), with intraclass correlation coefficient values ranging from 0.06 to 0.63. For 16 of the 27 equations, the change in eCRF was significantly different from the change in directly measured CRF. The median percentage of participants correctly classified as having increased, decreased, or no change in CRF was 56% (range, 39%–61%).

Conclusions

Variability was observed in the accuracy between nonexercise prediction equations and the ability of equations to detect changes in CRF. Considering the appreciable error that prediction equations had with detecting even directional changes in CRF, these results suggest eCRF may have limited clinical utility.