Prediction of cardiovascular health by non-exercise estimated cardiorespiratory fitness

Estimated Cardiorespiratory Fitness and Metabolic Risks

This review focuses on the emerging evidence for the association between non-exercise fitness testing, estimated cardiorespiratory fitness (eCRF), and metabolic risk factors. Given the challenges associated with directly measuring cardiorespiratory fitness (CRF) in large populations, eCRF presents a practical alternative for predicting metabolic health risks. A literature search identified seven relevant cohort studies from 2020 to 2024 that investigated the association of eCRF with hypertension, hyperglycemia, dyslipidemia, and obesity. This review consistently demonstrates an inverse relationship between higher eCRF and a lower incidence of metabolic risks, which is in line with CRF cohort studies. It highlights the importance of low eCRF as a primordial indicator for metabolic risks and underscores the potential for broader application. Future research directions should include exploring eCRF's predictive ability across diverse populations and health outcomes and testing its real-world applicability in healthcare and public health settings.

Cardiorespiratory fitness and metabolic risk in Chinese population: evidence from a prospective cohort study

BACKGROUND

Studies on the association between estimated cardiorespiratory fitness (CRF) and changes in metabolic risk in the Chinese population are limited. This study aims to examine the associations between CRF and changes in metabolic risk.

SUBJECTS AND METHODS

We included 4,862 and 2,700 participants recruited from 28 provinces in the China Health and Retirement Longitudinal Study (CHARLS) in the baseline (Wave 1) and follow-up (Wave 4) analyses, respectively. CRF was calculated using sex-specific longitudinal non-exercise equations. Metabolic indicators included systolic blood pressure (SBP), diastolic blood pressure (DBP), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose (FPG) levels. The metabolic score was calculated as the number of changes in the above metabolic indicators above the 75th percentile of the distribution of changes (equal to or below the 25th percentile for HDL-C).

RESULTS

In the baseline analysis, CRF was negatively associated with SBP, DBP, TG, and FPG, and positively correlated with HDL-C after adjusting for age, smoking status, and drinking status (all P < 0.0001) in both males and females. In the follow-up analysis, higher baseline CRF was significantly related to a decrease in SBP, DBP, TG, FPG, and metabolic score (all P < 0.0005), and increased HDL-C (P < 0.0001) after further adjustment for corresponding baseline metabolic indicators. The associations remained significant after stratification by sex, except for the changes in HDL-C levels in females. Furthermore, improved CRF was associated with favorable changes in DBP, TG, HDL-C, FPG, and metabolic scores in all populations and males. Significant associations between changes in CRF and DBP, TG, and FPG levels were found in females.

CONCLUSION

Higher baseline CRF and improved CRF were associated with favorable changes in metabolic indicators.

Estimated cardiorespiratory fitness and incident risk of cardiovascular disease in China

BACKGROUND

Limited evidence is available on the association between estimated cardiorespiratory fitness (e-CRF) and incidence of cardiovascular disease (CVD) in Chinese population.

METHODS

A total of 10,507 adults including 5084 men (48.4%) and 5423 (51.6%) women with a median age of 56.0 (25% quantile: 49, 75% quantile 63) years from the China Health and Retirement Longitudinal Study (CHARLS) was recruited in 2011 as baseline. The CVD incident events were followed-up until 2018. e-CRF was calculated from sex-specific longitudinal non-exercise equations and further grouped into quartiles. Cox proportional models were used to calculate hazard ratio (HR) and 95% confidence interval (CI) for incidence risks of CVD, heart disease and stroke.

RESULTS

During a median follow-up of 7 years, a total of 1862 CVD, 1409 heart disease and 612 stroke events occurred. In fully adjusted models, each one MET increment of e-CRF was associated with lower risk of CVD (HR = 0.91, 95%CI = 0.85-0.96 for males, HR = 0.87, 95%CI = 0.81-0.94 for females). Compared with the Quartile (Q)1 group, the HRs (95%CI) of the Q2, Q3 and Q4 groups were 0.84 (0.63-1.03), 0.72 (0.57-0.91) and 0.66 (0.51-0.87) for CVD in males. Females had HRs of 0.79 (0.66-0.96) in Q2, 0.71 (0.57-0.88) in Q3 and 0.58 (0.45-0.75) in Q4 for CVD. The associations between e-CRF and heart disease and stroke were slightly weaker than that for CVD in both males and females.

CONCLUSIONS

Higher e-CRF decreases the incident risk of CVD, heart disease and stroke.

Association between Estimated Cardiorespiratory Fitness and Abnormal Glucose Risk: A Cohort Study

BACKGROUND

Cardiorespiratory fitness (CRF) is a predictor of chronic disease that is impractical to routinely measure in primary care settings. We used a new estimated cardiorespiratory fitness (eCRF) algorithm that uses information routinely documented in electronic health care records to predict abnormal blood glucose incidence.

METHODS

Participants were adults (17.8% female) 20-81 years old at baseline from the Aerobics Center Longitudinal Study between 1979 and 2006. eCRF was based on sex, age, body mass index, resting heart rate, resting blood pressure, and smoking status. CRF was measured by maximal treadmill testing. Cox proportional hazards regression models were established using eCRF and CRF as independent variables predicting the abnormal blood glucose incidence while adjusting for covariates (age, sex, exam year, waist girth, heavy drinking, smoking, and family history of diabetes mellitus and lipids).

RESULTS

Of 8602 participants at risk at baseline, 3580 (41.6%) developed abnormal blood glucose during an average of 4.9 years follow-up. The average eCRF of 12.03 ± 1.75 METs was equivalent to the CRF of 12.15 ± 2.40 METs within the 10% equivalence limit. In fully adjusted models, the estimated risks were the same (HRs = 0.96), eCRF (95% CIs = 0.93-0.99), and CRF (95% CI of 0.94-0.98). Each 1-MET increase was associated with a 4% reduced risk.

CONCLUSIONS

Higher eCRF is associated with a lower risk of abnormal glucose. eCRF can be a vital sign used for research and prevention.

Updating Framingham CVD risk score using waist circumference and estimated cardiopulmonary function: a cohort study based on a southern Xinjiang population

Purpose

To explore the association between waist circumference (WC), estimated cardiopulmonary function (eCRF), and cardiovascular disease (CVD) risk in southern Xinjiang. Update the Framingham model to make it more suitable for the southern Xinjiang population.

Methods

Data were collected from 7705 subjects aged 30–74 years old in Tumushuke City, the 51st Regiment of Xinjiang Production and Construction Corps. CVD was defined as an individual's first diagnosis of non-fatal acute myocardial infarction, death from coronary heart disease, and fatal or non-fatal stroke. The Cox proportional hazards regression analysis was used to analyze the association between WC, eCRF and CVD risk. Restricted cubic spline plots were drawn to describe the association of the two indicators with CVD risk. We update the model by incorporating the new variables into the Framingham model and re-estimating the coefficients. The discrimination of the model is evaluated using AUC, NRI, and IDI metrics. Model calibration is evaluated using pseudo R² values.

Results

WC was an independent risk factor for CVD (multivariate HR: 1.603 (1.323, 1.942)), eCRF was an independent protective factor for CVD (multivariate HR: 0.499 (0.369, 0.674)). There was a nonlinear relationship between WC and CVD risk (nonlinear χ2 = 12.43, P = 0.002). There was a linear association between eCRF and CVD risk (non-linear χ2 = 0.27, P = 0.6027). In the male, the best risk prediction effect was obtained when WC and eCRF were added to the model (AUC = 0.763((0.734,0.792)); pseudo R² = 0.069). In the female, the best risk prediction effect was obtained by adding eCRF to the model (AUC = 0.757 (0.734,0.779); pseudo R² = 0.107).

Conclusion

In southern Xinjiang, WC is an independent risk factor for CVD. eCRF is an independent protective factor for CVD. We recommended adding WC and eCRF in the male model and only eCRF in the female model for better risk prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14110-y.

Exercise Effects On Cardiovascular Disease: From Basic Aspects To Clinical Evidence

Cardiovascular (CV) disease (CVD) remains the leading cause of major morbidity and CVD- and all-cause mortality in most of the world. It is now clear that regular physical activity (PA) and exercise training (ET) induces a wide range of direct and indirect physiologic adaptations and pleiotropic benefits for human general and CV health. Generally, higher levels of PA, ET, and cardiorespiratory fitness (CRF) are correlated with reduced risk of CVD, including myocardial infarction, CVD-related death, and all-cause mortality. Although exact details regarding the ideal doses of ET, including resistance and, especially, aerobic ET, as well as the potential adverse effects of extreme levels of ET, continue to be investigated, there is no question that most of the world's population have insufficient levels of PA/ET, and many also have lower than ideal levels of CRF. Therefore, assessment and promotion of PA, ET, and efforts to improve levels of CRF should be integrated into all health professionals' practices worldwide. In this state-of-the-art review, we discuss the exercise effects on many areas related to CVD, from basic aspects to clinical practice.

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.