Accelerometers’ accuracy for sedentary time (ST) and moderate-to-vigorous physical activity (MVPA) classification depends on accelerometer placement, data processing, activities, and sample characteristics. As intensities differ by age, this study sought to determine intensity cut-points at various wear locations people more than 70 years old. Data from 59 older adults were used for calibration and from 21 independent participants for cross-validation purposes. Participants wore accelerometers on their hip and wrists while performing activities and having their energy expenditure measured with portable calorimetry. ST and MVPA were defined as ≤1.5 metabolic equivalents (METs) and ≥3 METs (1 MET = 2.8 mL/kg/min), respectively. Receiver operator characteristic (ROC) analyses showed fair-to-good accuracy (area under the curve [AUC] = 0.62–0.89). ST cut-points were 7 mg (cross-validation: sensitivity = 0.88, specificity = 0.80) and 1 count/5 s (cross-validation: sensitivity = 0.91, specificity = 0.96) for the hip; 18 mg (cross-validation: sensitivity = 0.86, specificity = 0.86) and 102 counts/5 s (cross-validation: sensitivity = 0.91, specificity = 0.92) for the non-dominant wrist; and 22 mg and 175 counts/5 s (not cross-validated) for the dominant wrist. MVPA cut-points were 14 mg (cross-validation: sensitivity = 0.70, specificity = 0.99) and 54 count/5 s (cross-validation: sensitivity = 1.00, specificity = 0.96) for the hip; 60 mg (cross-validation: sensitivity = 0.83, specificity = 0.99) and 182 counts/5 s (cross-validation: sensitivity = 1.00, specificity = 0.89) for the non-dominant wrist; and 64 mg and 268 counts/5 s (not cross-validated) for the dominant wrist. These cut-points can classify ST and MVPA in older adults from hip- and wrist-worn accelerometers.

Background: Physical activity and sedentary behaviour have been suggested to independently affect a number of health outcomes. To what extent different combinations of physical activity and sedentary behaviour may influence physical function and frailty outcomes in older adults is unknown. The aim of this study was to examine the combination of mutually exclusive categories of accelerometer-measured physical activity and sedentary time on physical function and frailty in older adults. Methods: 771 older adults (54% women; 76.8 ± 4.9 years) from the Toledo Study for Healthy Aging participated in this cross-sectional study. Physical activity and sedentary time were measured by accelerometry. Physically active was defined as meeting current aerobic guidelines for older adults proposed by the World Health Organization. Low sedentary was defined as residing in the lowest quartile of the light physical activity-to-sedentary time ratio. Participants were then classified into one of four mutually exclusive movement patterns: (1) ‘physically active & low sedentary’, (2) ‘physically active & high sedentary’, (3) ‘physically inactive & low sedentary’, and (4) ‘physically inactive & high sedentary’. The Short Physical Performance Battery was used to measure physical function and frailty was assessed using the Frailty Trait Scale. Results: ‘Physically active & low sedentary’ and ‘physically active & high sedentary’ individuals had significantly higher levels of physical function (β = 1.73 and β = 1.30 respectively; all p < 0.001) and lower frailty (β = − 13.96 and β = − 8.71 respectively; all p < 0.001) compared to ‘physically inactive & high sedentary’ participants. Likewise, ‘physically inactive & low sedentary’ group had significantly lower frailty (β = − 2.50; p = 0.05), but significance was not reached for physical function. Conclusions: We found a dose-response association of the different movement patterns analysed in this study with physical function and frailty. Meeting the physical activity guidelines was associated with the most beneficial physical function and frailty profiles in our sample. Among inactive people, more light intensity relative to sedentary time was associated with better frailty status. These results point out to the possibility of stepwise interventions (i.e. targeting less strenuous activities) to promote successful aging, particularly in inactive older adults.

Background: Although the metabolic equivalents (METs) system is a common procedure to quantify the intensity of physical activity in older adults, it remains unclear whether the conventional METs intensity thresholds (CTs) used for this purpose are appropriate in this population. Therefore, this study aimed (i) to derive overall and fitness-specific METs intensity thresholds in older adults ≥ 60 years old (OATs) expressed both in standard METs (VO₂/3.5 mL O₂·kg⁻¹·min⁻¹) and older adults METs₆₀₊ (VO₂/2.7 mL O₂·kg⁻¹·min⁻¹), and (ii) to compare them with the CTs. Methods: A total of 93 subjects were assessed for cardiorespiratory fitness. Graded exercise test protocols using indirect calorimetry were performed to calculate individual VO_2max and categorize subjects as "very poor/fair" or "good/superior" fitness. Overall and fitness-specific OATs expressed in standard METs (OATs_standard) and METs₆₀₊ (OATs₆₀₊) were derived based on the %VO_2max and the ventilatory thresholds (VTs) physical intensity categories. Results: Significantly higher VO_2max, VO₂ at VT₁ and VO₂ at VT₂ (p < 0.001) were obtained in the "good/superior" subgroup compared to the "very poor/fair" fitness subgroup. Accordingly, OATs were approximately 69% higher in individuals with a "good/superior" fitness compared to those with a "very poor/fair" fitness. Furthermore, this study showed that OATs_standard were approximately 21–24% lower than OATs₆₀₊, and 10–22% higher OATs were observed when following the VTs intensity categories (heavy-intensity physical activity [HPA] and severe-intensity physical activity [SPA]) compared to the %VO_2max categories (moderate-intensity physical activity [MPA] and vigorous-intensity physical activity [VPA]). When compared with the CTs, similar or higher OATs_standard and OATs₆₀₊ for MPA, and HPA were obtained compared to the conventional MPA threshold (3.0 METs). Conversely, for VPA and SPA, lower, similar, or higher OATs were obtained depending on the METs derivation approach (OATs_standard or OATs₆₀₊) or the intensity categories (VO_2max or VTs), compared to the conventional VPA threshold (6.0 METs). Conclusions: None of the derived OATs were concurrently similar to the CTs, suggesting that fitness-specific METs intensity thresholds adapted to the METs derivation approach should be used in older adults. Trial registration: FenotipAGING (Non-health-care intervention study), PRO-Training (NCT05619250).

This study aimed to compare the Cosmed K5 portable indirect calorimeter, using the mixing chamber mode and face mask, with a stationary metabolic cart when measuring the resting metabolic rate (RMR) and to derive fitting equations if discrepancies are observed. Forty--three adults (18--84 years) were assessed for their RMR for two 30--min consecutive and counterbalanced periods using a Cosmed K5 and an Oxycon Pro. Differences among devices were tested using paired sample Student's t--tests, and correlation and agreement were assessed using Pearson's correlation coefficients, intraclass correlation coefficient and Bland--Altman plots. Forward stepwise multiple linear regression models were performed to develop fitting equations for estimating differences among devices when assessing oxygen uptake (VO(2)diff, mL center dot min-1) and carbon dioxide production (VCO2diff, mL center dot min-1). Furthermore, the Oxycon Pro was tested before being confirmed as a reference device. Significant differences between devices were found in most metabolic and ventilatory parameters, including the primary outcomes of VO2 and VCO2. These differences showed an overestimation of the Cosmed K-5 in all metabolic outcomes, except for Fat, when compared to the Oxycon Pro. When derived fitting equations were applied (VO2diff - 139.210 + 0.786 [weight, kg] + 1.761 [height, cm] --0.941 [Cosmed K-5 VO2, mL center dot min(-1)]; VCO(2)diff - 86.569 + 0.548 [weight, kg] + 0.915 [height, cm] --0.728 [Cosmed K-5 VCO2, mL center dot min(-1)]), differences were minimized, and agreement was maximized. This study provides fitting equations which allow the use of the Cosmed K5 for reasonably optimal RMR determinations.

Life expectancy has increased worldwide alongside a rise in disability prevalence during old age. The impact and interrelationship among the precursors of disability in midlife remain to be better understood. Furthermore, investigating whether lifestyle factors may potentially influence health outcomes and the prognosis of vascular disease could be especially relevant among the middle-aged population, which is a priority subpopulation when prevention is the goal. This is an observational, cross-sectional, and population-based study. Participants, between 50 and 55 years old, are randomly selected from the municipality of Toledo (Spain). There are 6 nonconsecutive days for the assessments, providing enough rest between evaluations. Participants perform the interview of the Toledo Study for Healthy Aging. Blood pressure monitoring and a resting electrocardiogram are also recorded. Then, resting peripheral and cerebral vascular measurements along with muscle size and architecture are assessed. Blood and urine samples and body composition data are collected after an overnight fasting. On a different visit, physical performance and muscle function tests are performed. Additionally, brain magnetic resonance imaging is conducted. And finally, an accelerometer is given to the participants for a week. Frailty is evaluated by the Frailty Trait Scale and Fried Frailty Phenotype. This project will shed light on the associations between frailty, early cognitive impairment, and vascular aging during midlife, and on the role that lifestyles play in their development. Lastly, this project will provide meaningful implications for public health strategies aimed at promoting healthy aging in later life.