Mounting evidence has firmly established that low levels of cardiorespiratory fitness (CRF) are associated with a high risk of cardiovascular disease, all-cause mortality, and mortality rates attributable to various cancers. A growing body of epidemiological and clinical evidence demonstrates not only that CRF is a potentially stronger predictor of mortality than established risk factors such as smoking, hypertension, high cholesterol, and type 2 diabetes mellitus, but that the addition of CRF to traditional risk factors significantly improves the reclassification of risk for adverse outcomes. The purpose of this statement is to review current knowledge related to the association between CRF and health outcomes, increase awareness of the added value of CRF to improve risk prediction, and suggest future directions in research. Although the statement is not intended to be a comprehensive review, critical references that address important advances in the field are highlighted. The underlying premise of this statement is that the addition of CRF for risk classification presents health professionals with unique opportunities to improve patient management and to encourage lifestyle-based strategies designed to reduce cardiovascular risk. These opportunities must be realized to optimize the prevention and treatment of cardiovascular disease and hence meet the American Heart Association's 2020 goals.

pdf/importance-of-assessing-cardiorespiratory-fitness-in-v407bkh4h5.pdf

Importance of Assessing Cardiorespiratory Fitness in Clinical Practice: A Case for Fitness as a Clinical Vital Sign: A Scientific Statement From the American Heart Association.

Journal of sports science & medicine

Longitudinal changes in body composition in older men and women: role of body weight change and physical activity

This review focuses on how blood flow to contracting skeletal muscles is regulated during exercise in humans The idea is that blood flow to the contracting muscles links oxygen in the atmosphere with the contracting muscles where it is consumed In this context, we take a top down approach and review the basics of oxygen consumption at rest and during exercise in humans, how these values change with training, and the systemic hemodynamic adaptations that support them We highlight the very high muscle blood flow responses to exercise discovered in the 1980s We also discuss the vasodilating factors in the contracting muscles responsible for these very high flows Finally, the competition between demand for blood flow by contracting muscles and maximum systemic cardiac output is discussed as a potential challenge to blood pressure regulation during heavy large muscle mass or whole body exercise in humans At this time, no one dominant dilator mechanism accounts for exercise hyperemia Additionally, complex interactions between the sympathetic nervous system and the microcirculation facilitate high levels of systemic oxygen extraction and permit just enough sympathetic control of blood flow to contracting muscles to regulate blood pressure during large muscle mass exercise in humans

Regulation of Increased Blood Flow (Hyperemia) to Muscles During Exercise: A Hierarchy of Competing Physiological Needs

Purpose: Maximal heart rate (HRmax)-prediction equations based on a person's age are frequently used in prescribing exercise intensity and other clinical applications. Results from various cross-sectional studies have shown a linear decrease in HRmax during exercise with increasing age. However, it is less well established that longitudinal tracking of the same individuals' HRmax as they age exhibits an identical linear relationship. This study examined the longitudinal relationship between age and HRmax during exercise.

Methods: A retrospective analysis of maximal graded exercise test (GXT) results for members participating in a university-based health-assessment/fitness center between 1978 and 2003 was undertaken in 2006. Records were examined from individuals (N = 132) of both sexes who represented a broad range of age and fitness levels and who had multiple GXT (total N = 908) conducted over 25 years. HRmax-prediction equations based on participants' age and HRmax elicited during the tests were developed using a linear mixed-models statistical analysis approach.

Results: Clinical measurements obtained during the administration of the GXT included in this longitudinal study resulted in the generation of a univariate prediction model: HRmax = 207 - 0.7 × age. Model parameters were highly statistically significant (P < 0.001).

Conclusions: The relationship between age and HRmax during exercise developed in this longitudinal study has resulted in a prediction equation appreciably different from the conventional HRmax formula (220 - age) often used in exercise prescription, and it confirms findings from recent cross-sectional investigations of HRmax.

Longitudinal modeling of the relationship between age and maximal heart rate.

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak) of women. The cross-sectional sample consisted of 409 healthy women, ages 20-64 yr. The 43 women of the longitudinal sample were from the same population and examined twice, the mean time between tests was 3.7 (+/-2.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill test. The zero-order correlation of -0.742 between VO2peak and %fat was significantly (P < 0.05) higher then the SR-PA (r = 0.626) and age correlations (r = -0.633). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.537 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.851) showed that adding %fat and SR-PA and their interaction to the regression model reduced the age regression weight of -0.537, to -0.265 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results. These findings are consistent with men's data from the same lab showing that about 50% of the cross-sectional age-related decline in VO2peak was due to %fat and SR-PA.

Changes in aerobic power of women, ages 20-64 yr

UNLABELLED Previously published nonexercise models using either percent fat or body mass index (BMI) as body composition measures provided valid estimates of VO2max. PURPOSE This study was conducted to investigate the use of waist girth (WG) as a body composition surrogate in the nonexercise models and to compare the accuracy of nonexercise models that include WG, %fat, or BMI. METHODS A total of 2417 men and 384 women were measured for VO2max by indirect calorimetry (RER > 1.1); age (yr); gender by M = 1, W = 0; self-report activity habit by the 11-point (0-10) NASA physical activity status scale (PASS); WG at the apex of the umbilicus; %fat by skinfolds; and BMI by weight (kg) divided by height squared (m). RESULTS Three models were developed by multiple regression to estimate VO2max from age, gender, PASS, and either WG (R = 0.81, standard error of estimate (SEE) = 4.80 mL.kg.min), %fat (R = 0.82, SEE = 4.72 mL x kg(-1) x min(-1)), or BMI (R = 0.80, SEE = 4.90 mL x kg(-1) x min(-1)). Cross-validation by the PRESS technique confirmed these statistics. Accuracy of the models for predicting VO2max of subsamples was supported by constant errors (CE) 1 mL x kg(-1) x min(-1) for VO2max 50 mL x kg(-1) x min(-1). CONCLUSIONS Waist girth is an acceptable surrogate for body composition in the nonexercise models. All models were similar in accuracy and valid for estimating VO2max of most adults, but with reduced accuracy at the extremes of fitness (VO2max 50 mL x kg(-1) x min(-1)).

Nonexercise models for estimating VO2max with waist girth, percent fat, or BMI.

196 DETERMINATES OP MALE AND FEMALE LONGITUDINAL CHANGES IN V02max

Longitudinal assessment of 10-year weight change in a large federal workforce252

Aim: Type 2 Diabetes (T2D) is a major cause of morbidity and mortality. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT-2i) are highly effective but underutilized. We assessed racial/ethnic and other sociodemographic disparities in GLP-1/SGLT-2 use among US adults with T2D. Materials and Methods: We conducted a retrospective analysis using nationally representative data from National Health and Nutrition Examination Survey 2005-March 2020. Participants were adults with T2D taking [≥]1 diabetes medication, excluding pregnant women and adults with probable T1D. We performed univariate analyses to examine characteristics of patients using GLP-1/SGLT-2 and multivariable logistic regression to assess disparities in GLP-1/SGLT-2 use after adjusting for other patient factors. Results: Among 4,585 T2D patients (representing >18 million US adults) taking [≥]1 medication, GLP-1/SGLT-2 usage increased from 1.4% in 2005-2006 to 13.3% in 2017-2020. In univariate analyses, patients using GLP-1/SGLT-2 vs. other T2D drugs were more likely to be white than nonwhite (72% vs. 60%, p = .001), but in multivariable analysis there was no significant difference in GLP-1/SGLT-2 use for nonwhite vs. white patients (aOR = 0.84, 95% CI [0.61, 1.16]). GLP-1/SGLT-2 use was higher for patients who completed some college (aOR = 1.83, 95% CI [1.06, 3.15]) or above (aOR = 2.06, 95% CI [1.28, 3.32]) vs. high school or less, and for those with an income-poverty ratio [≥]4 vs. <2 (aOR = 2.11, 95% CI [1.30, 3.42]). Conclusions: Use of GLP-1/SGLT-2 drugs increased over time but remained low in March 2020. Higher education and income, but not race/ethnicity, were associated with GLP-1/SGLT-2 use.

/pdf/sociodemographic-disparities-in-the-use-of-glp-1-receptor-1r8d9jfp.pdf

Sociodemographic disparities in the use of GLP-1 receptor agonists and SGLT-2 inhibitors among US adults with type 2 diabetes: NHANES 2005-March 2020

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