Estimation Of Cardiorespiratory Fitness Research Articles

Cardiorespiratory Fitness Assessment for Exercise Research in Mild Cognitive Impairment Due to Alzheimer's Disease.

To analyze cardiorespiratory fitness (CRF) levels using the gold-standard, laboratory-based cardiopulmonary exercise test (CPET) in community-dwelling older adults (N = 145) with amnestic mild cognitive impairment (aMCI), specifically CPET feasibility, CRF prediction, and CRF status in comparison to published sedentary, cognitively normal, age- and sex-adjusted normative data. Peak oxygen consumption (VO2Peak [mL/kg/min]) was assessed by CPET, which was categorized as submaximal, near-maximal, or maximal tests. VO2Max predicted was compared to VO2Max measured to assess its utility. Data were analyzed with t tests. Participants' mean age was 73.77 years (SD = 5.74 years), with 51.7% males, 91.7% Caucasian, 68.3% married, and 16.9 years (SD = 2.88 years) of education. Mean VO2Peak measured was 17.07 (SD = 4.92) for the total sample (18.29 [SD = 4.64] for males, 15.78 [SD = 4.91] for females). Sixteen (11.03%) CPETs were submaximal, 53 (36.55%) were near-maximal, and 76 (52.41%) were maximal. Mean VO2Max predicted was 28.59 (SD = 21.94) for the total sample (29.36 [SD = 22.3] for males, 27.76 [SD = 21.68] for females) and was significantly higher than VO2Max measured (p < 0.0001). Among participants with maximal CPETs, VO2Peak measured was significantly lower than sedentary normative data (p < 0.0001). CPET was feasible for older adults with aMCI. VO2Max predicted overly inflates CRF estimates. Low levels of CRF in older adults with aMCI suggest aerobic exercise as an important intervention. [Journal of Gerontological Nursing, 50(9), 31-36.].

Abstract MP15: Developing and Validating VO 2 Prediction From 6-Minute Walk Test (6MWT) and Association With Cardiovascular Health and Risk Scores: Coronary Artery Risk Development in Young Adults (CARDIA)

Introduction: Cardiorespiratory fitness (CRF) is a valuable diagnostic and prognostic measure. Yet, assessing VO 2 max (indicator of CRF) in population-based studies can be challenging due to requiring sophisticated equipment and trained personnel. Thus, we built and validated a model to estimate VO 2 max from a 6MWT, which is less burdensome for participants (submaximal effort). We tested the hypothesis that our model provides valid estimates of VO 2 max that are associated with cardiovascular health - AHA’s Life’s Simple 7 (LS7) and ASCVD scores. Methods: Data are from 576 CARDIA participants [60% female; 40% Black; mean ± SD age = 61.5 ± 3.6; BMI = 28.6 ± 5.7 kg/m 2 ] who attended the Year 35 follow-up exam (2020-22) and completed VO 2 max and 6MWT tests. The study sample was split randomly into a training (2/3) or test (1/3) set. The prediction equation was developed using stepwise multiple linear regression models in the training set. We evaluated accuracy of the model using student's t-test and Pearson correlation coefficients (r) by examining the difference between the observed and predicted VO 2 max in the test dataset. Linear regression models adjusted for age, and sex were used to examine associations of VO 2 max estimates with cardiovascular health and risk indices. Results: The prediction equation included 6MWT distance, sex, age, BMI, physical activity status, and smoking status (R 2 adj = 0.55, RMSE = 4.84). No significant difference was observed between predicted and measured VO 2 max (26.2 ± 5.4 vs 26.0 ± 7.5 mL/kg/min; p =0.76) and the measures were strongly correlated (r=0.80, p &lt;.001) with Bland-Altman plot is presented (Figure). Predicted VO 2 max explained more variance in LS7 score (R 2 adj = 0.55) compared to measured (R 2 adj = 0.37), while explaining similar variance in ASCVD risk (R 2 adj = 0.40 vs 0.38). Conclusions: This prediction equation provides a convenient and useful estimate of CRF estimate of CRF from 6MWT and may provide utility in clinical practice to screen and monitor CRF when direct measurement is not feasible.

Longitudinal cardio-respiratory fitness prediction through wearables in free-living environments

Cardiorespiratory fitness is an established predictor of metabolic disease and mortality. Fitness is directly measured as maximal oxygen consumption (VO2max), or indirectly assessed using heart rate responses to standard exercise tests. However, such testing is costly and burdensome because it requires specialized equipment such as treadmills and oxygen masks, limiting its utility. Modern wearables capture dynamic real-world data which could improve fitness prediction. In this work, we design algorithms and models that convert raw wearable sensor data into cardiorespiratory fitness estimates. We validate these estimates’ ability to capture fitness profiles in free-living conditions using the Fenland Study (N=11,059), along with its longitudinal cohort (N = 2675), and a third external cohort using the UK Biobank Validation Study (N = 181) who underwent maximal VO2max testing, the gold standard measurement of fitness. Our results show that the combination of wearables and other biomarkers as inputs to neural networks yields a strong correlation to ground truth in a holdout sample (r = 0.82, 95CI 0.80–0.83), outperforming other approaches and models and detects fitness change over time (e.g., after 7 years). We also show how the model’s latent space can be used for fitness-aware patient subtyping paving the way to scalable interventions and personalized trial recruitment. These results demonstrate the value of wearables for fitness estimation that today can be measured only with laboratory tests.

Cardiorespiratory Fitness Estimation Based on Heart Rate and Body Acceleration in Adults With Cardiovascular Risk Factors: Validation Study.

Cardiorespiratory fitness (CRF) is an independent risk factor for cardiovascular morbidity and mortality. Adding CRF to conventional risk factors (eg, smoking, hypertension, impaired glucose metabolism, and dyslipidemia) improves the prediction of an individual's risk for adverse health outcomes such as those related to cardiovascular disease. Consequently, it is recommended to determine CRF as part of individualized risk prediction. However, CRF is not determined routinely in everyday clinical practice. Wearable technologies provide a potential strategy to estimate CRF on a daily basis, and such technologies, which provide CRF estimates based on heart rate and body acceleration, have been developed. However, the validity of such technologies in estimating individual CRF in clinically relevant populations is poorly known. The objective of this study is to evaluate the validity of a wearable technology, which provides estimated CRF based on heart rate and body acceleration, in working-aged adults with cardiovascular risk factors. In total, 74 adults (age range 35-64 years; n=56, 76% were women; mean BMI 28.7, SD 4.6 kg/m2) with frequent cardiovascular risk factors (eg, n=64, 86% hypertension; n=18, 24% prediabetes; n=14, 19% type 2 diabetes; and n=51, 69% metabolic syndrome) performed a 30-minute self-paced walk on an indoor track and a cardiopulmonary exercise test on a treadmill. CRF, quantified as peak O2 uptake, was both estimated (self-paced walk: a wearable single-lead electrocardiogram device worn to record continuous beat-to-beat R-R intervals and triaxial body acceleration) and measured (cardiopulmonary exercise test: ventilatory gas analysis). The accuracy of the estimated CRF was evaluated against that of the measured CRF. Measured CRF averaged 30.6 (SD 6.3; range 20.1-49.6) mL/kg/min. In all participants (74/74, 100%), mean difference between estimated and measured CRF was -0.1 mL/kg/min (P=.90), mean absolute error was 3.1 mL/kg/min (95% CI 2.6-3.7), mean absolute percentage error was 10.4% (95% CI 8.5-12.5), and intraclass correlation coefficient was 0.88 (95% CI 0.80-0.92). Similar accuracy was observed in various subgroups (sexes, age, BMI categories, hypertension, prediabetes, and metabolic syndrome). However, mean absolute error was 4.2 mL/kg/min (95% CI 2.6-6.1) and mean absolute percentage error was 16.5% (95% CI 8.6-24.4) in the subgroup of patients with type 2 diabetes (14/74, 19%). The error of the CRF estimate, provided by the wearable technology, was likely below or at least very close to the clinically significant level of 3.5 mL/kg/min in working-aged adults with cardiovascular risk factors, but not in the relatively small subgroup of patients with type 2 diabetes. From a large-scale clinical perspective, the findings suggest that wearable technologies have the potential to estimate individual CRF with acceptable accuracy in clinically relevant populations.

Descriptive Epidemiology of Cardiorespiratory Fitness in UK Adults: The Fenland Study.

Cardiorespiratory fitness (CRF) is rarely measured in population studies. Most studies of CRF do not examine differences by population subgroups or seasonal trends. We examined how estimated CRF levels vary by anthropometric, sociodemographic, and behavioral characteristics in a population-based cohort of UK adults (the Fenland Study). We used a validated submaximal exercise test to obtain CRF estimates (CRF estimated ) in 5976 women and 5316 men, residing in the East of England. CRF estimated was defined as estimated maximal oxygen consumption per kilogram total body mass (V̇O 2 max tbm ) and fat-free mass (V̇O 2 max ffm ). Descriptive statistics were computed across anthropometric and sociodemographic characteristics, and across the year. Progressive multivariable analyses were performed to examine associations with physical activity energy expenditure (PAEE) and body mass index (BMI). Mean ± SD V̇O 2 max tbm was lower in women (35.2 ± 7.5 mL·min -1 ·kg -1 ) than men (41.7 ± 7.3 mL·min -1 ·kg -1 ) but V̇O 2 max ffm was similar (women: 59.2 ± 11.6 mL·min -1 ·kg -1 ; men: 62.0 ± 10.3 mL·min -1 ·kg -1 ). CRF estimated was inversely associated with age but not after adjustment for PAEE. People in more physically demanding jobs were fitter compared with those in sedentary jobs, but this association was attenuated in women and reversed in men after adjustment for total PAEE. Physical activity energy expenditure and BMI were positively associated with CRF estimated at all levels of adjustment when expressed relative to fat-free mass. CRF estimated was 4% higher in summer than in winter among women, but did not differ by season among men. CRF estimated was inversely associated with age but less steeply than anticipated, suggesting older generations are comparatively fitter than younger generations. Physical activity energy expenditure and BMI were stronger determinants of the variance in CRF estimated than other characteristic including age. This emphasizes the importance of modifiable physical activity behaviors in public health interventions.

Estimating Cardiorespiratory Fitness Without Exercise Testing or Physical Activity Status in Healthy Adults: Regression Model Development and Validation.

BackgroundLow cardiorespiratory fitness (CRF) is an independent predictor of morbidity and mortality. Most health care settings use some type of electronic health record (EHR) system. However, many EHRs do not have CRF or physical activity data collected, thereby limiting the types of investigations and analyses that can be done.ObjectiveThis study aims to develop a nonexercise equation to estimate and classify CRF (in metabolic equivalent tasks) using variables commonly available in EHRs.MethodsParticipants were 42,676 healthy adults (female participants: n=9146, 21.4%) from the Aerobics Center Longitudinal Study examined from 1974 to 2005. The nonexercise estimated CRF was based on sex, age, measured BMI, measured resting heart rate, measured resting blood pressure, and smoking status. A maximal treadmill test measured CRF.ResultsAfter conducting nonlinear feature augmentation, separate linear regression models were used for male and female participants to calculate correlation and regression coefficients. Cross-classification of actual and estimated CRF was performed using low CRF categories (lowest quintile, lowest quartile, and lowest tertile). The multiple correlation coefficient (R) was 0.70 (mean deviation 1.33) for male participants and 0.65 (mean deviation 1.23) for female participants. The models explained 48.4% (SE estimate 1.70) and 41.9% (SE estimate 1.56) of the variance in CRF for male and female participants, respectively. Correct category classification for low CRF (lowest tertile) was found in 77.2% (n=25,885) of male participants and 74.9% (n=6,850) of female participants.ConclusionsThe regression models developed in this study provided useful estimation and classification of CRF in a large population of male and female participants. The models may provide a practical method for estimating CRF derived from EHRs for population health research.

Association between Cardiorespiratory Fitness and Metabolic Syndrome in Korean Older Adults.

Background: Little is known about the relationship between non-exercise-based estimation of cardiorespiratory fitness (eCRF) and metabolic syndrome (MetS) in Korea. The current study examined the prognostic role of eCRF in the risk stratification of MetS in a representative sample of Korean older adults (1822 men and 3069 women). Methods: The data used in the current study were extracted from the Korea National Health and Nutrition Examination Surveys IV and V. eCRF was obtained using a previously validated algorithm. MetS was defined according to the National Cholesterol Education Program definition with the acceptance of a Korean-specific waist circumference cutoff point. Results: Lower eCRF was significantly correlated with abnormalities in several components of MetS, including abdominal obesity, elevated glucose, elevated triglycerides, and decreased high-density lipoprotein cholesterol. Furthermore, there was an inverse linear relationship between MetS prevalence and eCRF levels; higher eCRF was significantly and independently associated with lower prevalence of MetS. Conclusion: The current findings suggest that eCRF can be adopted as a prognostic measure in determining the risk for MetS for elderly persons.

Adding Estimated Cardiorespiratory Fitness to the Framingham Risk Score and Mortality Risk in a Korean Population-Based Cohort Study.

Background: The added value of non-exercise-based estimation of cardiorespiratory fitness (eCRF) to cardiovascular disease (CVD) risk factors for mortality risk has not been examined in Korean populations. Methods: This population-based prospective cohort study examined the relationship of the 10-year Framingham risk score (FRS) for CVD risk and eCRF with all-cause and CVD mortality in a representative sample of Korean adults aged 30 years and older. Data regarding a total of 38,350 participants (16,505 men/21,845 women) were obtained from the 2007–2015 Korea National Health and Nutrition Examination Survey (KNHANES). All-cause and CVD mortality were the main outcomes. The 10-year FRS point sum and eCRF level were the main exposures. Results: All-cause and CVD mortality was positively correlated with the 10-year FRS point summation and inversely correlated with eCRF level in this study population. The protective of high eCRF against all-cause and CVD mortality was more prominent in the middle and high FRS category than in the low FRS category. Notably, the FRS plus eCRF model has better predictor power for estimating mortality risk compared to the FRS only model. Conclusions: The current findings indicate that eCRF can be used as an alternative to objectively measured CRF for mortality risk prediction.

Assessment of the Relationship Between Executive Function and Cardiorespiratory Fitness in Healthy Older Adults.

Associations between cardiorespiratory fitness and brain health in healthy older adults have been reported using a variety of cardiorespiratory fitness estimates (CRFe). Using commonly used methods to determine CRF, we assessed the relationship between CRFe and executive function performance. Healthy older adults (n = 60, mean age 68 years, 77% women), underwent three CRF tests: a Maximal Graded Exercise Test performed on a cycle ergometer, the Rockport Fitness Walking Test, and a Non-Exercise Prediction Equation. Executive function was assessed by a computerized cognitive assessment using an N-Back task (updating cost) and a Stroop task (interference cost, global and local switch cost). Multiple hierarchical regression analyses were conducted to assess the relationship between different CRFe and executive function performance. Regardless of age and education, cardiorespiratory fitness estimated from the Maximal Graded Exercise Test and the Rockport Fitness Walking Test was significantly associated with the global switch cost. All CRFe were associated with the interference cost. No association was observed between CRFe and local switching costs or the updating costs. In the present study, not all subcomponents of executive function were related to CRFe. Interestingly, the executive functions that were associated with CRFe are those that are known to be the most affected by aging.

Cardiorespiratory fitness assessment using risk-stratified exercise testing and dose\u2013response relationships with disease outcomes

Cardiorespiratory fitness (CRF) is associated with mortality and cardiovascular disease, but assessing CRF in the population is challenging. Here we develop and validate a novel framework to estimate CRF (as maximal oxygen consumption, VO2max) from heart rate response to low-risk personalised exercise tests. We apply the method to examine associations between CRF and health outcomes in the UK Biobank study, one of the world’s largest and most inclusive studies of CRF, showing that risk of all-cause mortality is 8% lower (95%CI 5–11%, 2670 deaths among 79,981 participants) and cardiovascular mortality is 9% lower (95%CI 4–14%, 854 deaths) per 1-metabolic equivalent difference in CRF. Associations obtained with the novel validated CRF estimation method are stronger than those obtained using previous methodology, suggesting previous methods may have underestimated the importance of fitness for human health.

Estimation of Cardiorespiratory Fitness Without Exercise Testing: Cross-Validation in Midlife and Older Women.

Cardiorespiratory fitness (CRF) is associated with important health risk outcomes, including the development of Type 2 diabetes and cardiovascular disease. Measures of maximal or peak oxygen consumption (VO2) are the typical criterion methods for determining CRF; however, in clinical settings, these measures are impractical. We validated a clinically derived estimate of CRF against predicted maximal VO2 in a sample of healthy, midlife and older adult women (n = 188). Women completed a clinic evaluation (including treadmill testing), daily diaries about their physical activity, and additional clinical scales. Two models were tested. The first model calculated estimated cardiorespiratory fitness (eCRF) using assigned weights and regressed eCRF on predicted cardiorespiratory fitness (pCRF). The second model used sample-specific, empirical weights. Both models were tested twice, once with retrospective and once with daily diary physical activity reports. The model accounted for 34% of the variance in pCRF when using assigned weights and 41% of the variance in pCRF when using empirical weights. For age, body mass index, and resting heart rate, assigned and estimated weights were similar, but estimates for physical activity differed. There was little improvement in model fit between retrospective and daily diary measurements of physical activity when either assigned (R 2 = 0.32) or fitted weights (R 2 = 0.40) were used. Midlife and older women's CRF can be estimated from routinely collected clinical measures, demonstrating their utility.

Comparison of the Ekblom-Bak Submaximal Test to a Maximal Test in a Cohort of Healthy Younger and Older Adults in the United States.

Cardiorespiratory fitness (CRF) is routinely investigated in diverse populations, including in older adults of varying physical activity levels. Commonly performed maximal exercise testing protocols might be contraindicated and/or inadequate for older individuals who have physical or cognitive impairment. Moreover, early termination of an attempted maximal exercise test could result in underestimation of CRF in this population. The goal of the current study was to compare CRF estimates using the Ekblom-Bak (EB) submaximal exercise test – previously validated in a cohort of Scandinavian adults – versus a subsequent maximal exercise test in a diverse, Midwestern United States cohort. Fifteen generally healthy individuals were included in this study who were either “Young” (25–34 years old) or “Older” (55–75 years old) as well as either sedentary or highly active. Participants completed the EB submaximal exercise test, followed immediately by a maximal exercise test. We found that all 15 individuals were able to successfully perform the EB submaximal testing method. Across the wide range of volumes of maximal oxygen consumption (VO2max; 12–52 ml/kg/min), the EB submaximal estimates of VO2max correlated highly with the maximal test based values (Pearson’s r = 0.98), but with a small bias (6 ml/kg/min, 95% limits of agreement −1.06 and −11.29). Our results suggest that the EB submaximal testing method may be useful in identifying wide differences in CRF among a diverse cohort of older adults in the United States, but larger studies will be needed to determine the degree of its accuracy and precision in identifying smaller differences.

Cardiorespiratory Fitness of Firefighters: Initial Results of a Multi-Phased Study.

Objective:To address which body composition (BC) measures best correlate with cardiorespiratory fitness (CRF) in firefighters and develop a model for accurate CRF estimation compared with traditional methods.Methods:Career firefighters had body mass index (BMI) and waist circumference (WC) measured in addition to body fat percentage (FM%) by dual-energy x-ray absorptiometry (DXA). CRF as maximum oxygen uptake (VO2max) was estimated by rowing machine and measured by indirect calorimetry in a treadmill exercise test.Results:Fifty two firefighters participated (92.3% men). Univariate correlations with BMI were best with WC. Univariate correlations with VO2max were best with FM%. Obesity classifications by BC measures agreed weakly at best. Multivariate analysis of several variables yielded an improved VO2max estimate (R2 = 0.70).Conclusions:Fire departments may benefit from more sophisticated measures of BC and CRF to evaluate firefighter fitness.

Cardiorespiratory fitness assessment among firefighters: Is the non-exercise estimate accurate?

Minimum cardiorespiratory fitness (CRF) has been recommended for firefighters due to job requirements. Thus, it is important to identify accurate and readily available methods to assess CRF in this population. Non-exercise CRF estimates (NEx-CRF) have been proposed but this approach requires validation in this population. To evaluate the accuracy of a NEx-CRF, as compared to a field maximum exercise test, among career military firefighters of both genders using a comprehensive agreement analysis. We evaluated the accuracy of a NEx-CRF estimate compared to the Cooper 12 min running test among 702 males and 106 female firefighters. Cooper and NEx-CRF tests yielded similar CRF in both genders (differences <1.8±4.7 ml/kg-1.min-1; effect size <0.34). However, NEx-CRF underestimated Cooper-derived CRF among the fittest firefighters. NEx-CRF showed moderate to high sensitivity/specificity to detect fit or unfit firefighters (71.9% among men and 100% among women). Among men, the NEx-CRF method correctly identified most firefighters with less than 11 METs or greater than 13 METs, but showed lower precision to discriminate those with CRF between 11-13 METs. The NEx-CRF method to estimate firefighters' CRF may be considered as an alternative method when an exercise-based method is not available or may be used to identify those who require more traditional testing (CRF 11-13 METs).

Estimated Cardiorespiratory Fitness, Comorbidity, And Health-related Quality Of Life In Korean Older Adults With Diabetes

PURPOSE: Health-related quality of life (HRQoL) is a multidimensional subcomponent of quality of life that can be affected by health or health-related interventions. This study examined whether or not non-exercise-based estimation of cardiorespiratory fitness (eCRF) mediates the relationship of -comorbidity with HRQoL in Korean older adults with diabetes. METHODS: Data from a subgroup (n=1371) of Korean older adults with diabetes and age of ≥60 years (55% women) who participated in the 2008-2011 Korean National Health and Nutritional Examination Survey were used in this analysis. HRQoL was assessed with the EuroQoL-5 dimensions index and EuroQoL visual analogue scale. Comorbidity was defined as physician-diagnosed chronic conditions. eCRF was assessed with a non-exercise regression equation derived from sex, age, body mass index, and self-reported physical activity. The SPSS macro provided by Preacher and Hayes was used to test whether CRF mediated the relationship between comorbidity and HRQoL at p=0.05. RESULTS: The total effect of the presence of comorbidities on HRQoL was significant (path c; β=-2.670, 95% CI=-3.868 ~ -1.472, p<0.001). The presence of comorbidities was negatively related to eCRF in HRQoL model (path a: β=-0.529, 95% CI=-0.652 ~ -0.404, p<0.001). The effect of eCRF as a mediator on HRQoL was also significant (path b: β=1.434, 95% CI=0.928 ~ 1.940, p<0.001). The mediation analysis using the bootstrapping method (5,000 resamples) showed that eCRF mediated the relationship between the presence of comorbidities and HRQoL in Korean older adults (path ab: β=-0.757, 95% CI=-1.104 ~ -0.453, Sobel test Z=-2.753, p<0.001). In addition, a direct effect of the presence of comorbidities on HRQoL was also significant (path c’: β=-1.913, 95% CI=-3.128 ~ -0.698, p<0.05). CONCLUSIONS: The current findings suggest that cardiorespiratory fitness (CRF) can contribute to explain the relationship between comorbidity and HRQoL in Korean older adults with diabetes, implying the clinical relevance that promotion of CRF may have an impact beyond physical health in the patients. This study was supported by the National Research Foundation funded by the Korean Government (NRF-2019R1I1A1A01043771).

A Nonexercise Prediction Equation For Cardiorespiratory Fitness Without The Use Of Physical Activity

Low cardiorespiratory fitness (CRF) is an independent predictor of morbidity and mortality. The majority of healthcare settings use some type of electronic health record system (EHRs). However, many EHRs do not have CRF data collected, thereby limiting the types of investigations and analyses that can be done for research. PURPOSE: To develop a nonexercise equation to estimate and classify CRF (METs) using variables commonly found in EHRs. METHODS: Participants were 41,861 apparently healthy adults (21.4% women) from the Aerobics Center Longitudinal Study examined from 1974 to 2005. Estimated CRF was based on sex, age, measured body mass index, measured resting heart rate, and smoking status. Actual CRF was measured by a maximal treadmill test. RESULTS: After nonlinear feature augmentation was conducted, separate linear regression models were used for male and female patients to calculate Pearson’s correlation and regression coefficients.Cross-classification of actual and estimated CRF was conducted using the lowest 20th percentile as the low-fit category. Correlation coefficients were 0.68 (MD 1.33) and 0.63 (MD 1.23) for men and women respectively. The models explained 46% (SEE 1.69) and 40% (SEE 1.54) variance in CRF for men and women respectively. Correct category classification was found in 84% of men and 80% of women. CONCLUSION: The regression models developed in the present study provided useful estimation and classification of CRF in a large population of men and women. The models may provide a valid method for conducting investigations using CRF data derived from EHRs. Supported by JSPS KAKENHI Grant 19K19437

Estimated Cardiorespiratory Fitness Attenuates the Impacts of Sarcopenia and Obesity on Non-Alcoholic Fatty Liver in Korean Adults.

This population-based, cross-sectional study examined the preventive role of non-exercise-based estimation of cardiorespiratory fitness (eCRF) against the impacts of sarcopenia and obesity on the non-alcoholic fatty liver (NAFL) in Korean adults. Data were obtained from the 2008–2011 Korea National Health and Nutrition Examination Surveys IV and V (n = 14,015 Koreans aged ≥ 18 years, 64% women). eCRF was calculated with the age- and sex-specific algorithms, and classified as lower (lowest 25%), middle (middle 50%) and upper (highest 25%). Individuals were classified as optimal (i.e., the absence of both sarcopenia and obesity), sarcopenia (i.e., the presence of sarcopenia), obesity (i.e., the presence of obesity) or sarcopenic obesity (i.e., the coexistence of sarcopenia and obesity). Limited to the sarcopenia phenotype, the adjusted odds ratio (OR) of NAFL was 2.2 (95% confidence interval, CI, 1.5–3.1) for the lower eCRF, 1.6 (95% CI, 1.3–2.1) for the middle eCRF and 2.1 (95% CI, 1.4–3.1) for the upper eCRF, compared to the optimal phenotype. Limited to the obesity phenotype, the adjusted OR of NAFL was 2.9 (95% CI, 2.0–4.2) for the lower eCRF, 3.5 (95% CI, 2.7–4.6) for the middle eCRF and 1.8 (95% CI, 1.2–2.8) for the upper eCRF, compared to the optimal phenotype. Limited to the sarcopenic obesity phenotype, the adjusted OR of NAFL was 5.9 (95% CI, 4.3–8.2) for the lower eCRF, 4.2 (95% CI, 3.2–5.5) for the middle eCRF and 2.5 (95% CI, 1.5–4.1) for the upper eCRF, compared to the optimal phenotype. The current findings suggest that high eCRF attenuates the individual and synergistic impacts of sarcopenia and obesity on NAFL in Korean adults.

Non-exercise based estimation of cardiorespiratory fitness is inversely associated with metabolic syndrome in a representative sample of Korean adults

BackgroundThis study investigated the association between non-exercise based estimation of cardiorespiratory fitness (eCRF) and metabolic syndrome (Mets) in Korean adults aged 18 years and older (13,400 women and 9885 men).MethodsData from the 2008 and 2011 Korea National Health and Nutrition Examination Surveys IV and V in South Korea were analyzed. eCRF was assessed with a previously validated procedure. Participants were classified into 5 categories from the lowest quantile to the highest quantile based on individual eCRF distributions.ResultsThe findings showed an independent and inverse association between eCRF and Mets in women and men separately. Individuals in the highest eCRF category (quantile 5) had a significantly lower prevalence of Mets (14.5 and 14.8% for women and men, respectively) compared with their counterparts (40.4 and 46.4% for women and men, respectively) in the lowest eCRF category (quantile 1), and the association showed a graded response, with the quantiles 2, 3, and 4 also significantly associated with a lower prevalence of Mets compared with the quantile 1. Furthermore, the prevalence of Mets in the highest quantile compared with the lowest quantile remained statistically significant in both men (p < 0.05) and women (p < 0.05) even after adjustments for age, body mass index, skeletal muscle index, smoking, heavy drinking, vitamin D, caloric intake, and dietary intakes of carbohydrates, fats, and proteins.ConclusionThe findings support a preventive role for eCRF against Mets in Korean adults.

Non-Exercise Based Estimation of Cardiorespiratory Fitness Mediates Associations between Comorbidities and Health-Related Quality of Life in Older Korean Adults with Diabetes.

This study investigated whether non-exercise-based estimation of cardiorespiratory fitness (eCRF) mediates the association between health-related quality of life (HRQoL) and comorbidities in older Korean adults with diabetes. A total of 1371 Korean adults (56% women) aged 60 years and older with diabetes was drawn from those who participated in the 2008–2011 Korea National Health and Nutrition Examination Surveys IV and V. Data on comorbidities included hypertension, heart disease (acute myocardial infarction or angina), stroke, arthritis, and chronic renal disease. HRQoL was assessed using the EuroQoL group, which consists of a health-status descriptive system and a visual analogue scale. eCRF was determined with sex-specific algorithms. Age, sex, household income, education level, marital status, smoking, alcohol consumption, and regular exercise were additionally measured as covariates. HRQoL found to be inversely associated with number of comorbidities and positively associated with increasing eCRF category (from low to high) in older Korean patients with diabetes. The Sobel mediation test showed a significant indirect effect (Z = −4.632, p < 0.001), and the result of a bootstrap procedure corroborated the Sobel test result: a non-zero range in the 95% bias-corrected confidence interval (95% CI −1.104 to −0.453) indicated that eCRF mediates the impact of comorbidities on HRQoL. Overall, the current findings suggest that enhancing CRF can facilitate positive outcomes, including better HRQoL, for patients with diabetes.

Cardiorespiratory fitness estimation from heart rate and body movement in daily life.

Low cardiorespiratory fitness (CRF) increases risk of all-cause mortality and cardiovascular events. Periodic CRF assessment can have an important preventive function. The objective of this study was to develop a protocol-free method to estimate CRF in daily life based on heart rate (HR) and body acceleration measurements. Acceleration and HR data were collected from 37 subjects (men = 49%) while they performed a standardized laboratory activity protocol (sitting, walking, running, cycling) and during a 5-day free-living monitoring period. CRF was determined by oxygen uptake (V̇o2max) during maximal exercise testing. A doubly labeled water-validated equation was used to predict total energy expenditure (TEE) from acceleration data. A fitness index was defined as the ratio between TEE and HR (TEE-pulse). Activity recognition techniques were used to process acceleration features and classify sedentary, ambulatory, and other activity types. Regression equations based on TEE-pulse data from each activity type were developed to predict V̇o2max. TEE-pulse measured within each activity type of the laboratory protocol was highly correlated with V̇o2max (r from 0.74-0.91). Averaging the outcome of each activity-type specific equation based on TEE-pulse from the laboratory data led to accurate estimates of V̇o2max [root mean square error (RMSE): 300 mL O2/min, or 10%]. The difference between laboratory and free-living determined TEE-pulse was 3.7 ± 11% (r = 0.85). The prediction method preserved the prediction accuracy when applied to free-living data (RMSE: 367 mL O2/min, or 12%). Measurements of body acceleration and HR can be used to predict V̇o2max in daily life. Activity-specific prediction equations are needed to achieve highly accurate estimates of CRF.NEW & NOTEWORTHY This is among the very few studies validating, in free-living conditions, a method to estimate cardiorespiratory fitness using heart rate and body acceleration data. A novel parameter called TEE-pulse, which was defined as the ratio between accelerometer-determined energy expenditure and heart rate, was highly correlated with maximal oxygen uptake (V̇o2max). Activity classification and the use of activity-selective prediction equations outperformed previously published methods for estimating V̇o2max from heart rate and acceleration data.