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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.

Happiness is a complex subjective experience that is essential to societal progress. This study investigated the association between Sudarshan Kriya Yoga (SKY) and subjective happiness in Singapore. Subjective happiness data were collected from a convenience sample (N = 733) comprised of 2 groups: SKY (n = 385) and non-SKY (n = 348) practitioners. SKY was categorized into non-, monthly, weekly, and daily practitioners and happiness was categorized into lower, middle and higher tertile groups. Confounding variables included age, gender, ethnicity, marital status, education level, body mass index (BMI), smoking status, alcohol consumption and self-reported health. Daily SKY participation was positively associated with a 2-fold higher likelihood of being happier in a multivariate regression analysis. The trend analysis showed that as SKY frequency increases, the odds of being happier increases. These findings help generate the hypothesis that yogic breathing may promote happiness. Further experimental and prospective investigations are warranted.

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.