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Background The number of days of pedometer or accelerometer data needed to reliably assess physical activity (PA) is important for research that examines the relationship with health. While this important research has been completed in young to middle-aged adults, data is lacking in older adults. Further, data determining the number of days of self-reports PA data is also void. The purpose of this study was to examine the number of days needed to predict habitual PA and sedentary behaviour across pedometer, accelerometer, and physical activity log (PA log) data in older adults. Methods Participants (52 older men and women; age = 69.3 ± 7.4 years, range= 55-86 years) wore a Yamax Digiwalker SW-200 pedometer and an ActiGraph 7164 accelerometer while completing a PA log for 21 consecutive days. Mean differences each instrument and intensity between days of the week were examined using separate repeated measures analysis of variance for with pairwise comparisons. Spearman-Brown Prophecy Formulae based on Intraclass Correlations of .80, .85, .90 and .95 were used to predict the number of days of accelerometer or pedometer wear or PA log daily records needed to represent total PA, light PA, moderate-to-vigorous PA, and sedentary behaviour. Results Results of this study showed that three days of accelerometer data, four days of pedometer data, or four days of completing PA logs are needed to accurately predict PA levels in older adults. When examining time spent in specific intensities of PA, fewer days of data are needed for accurate prediction of time spent in that activity for ActiGraph but more for the PA log. To accurately predict average daily time spent in sedentary behaviour, five days of ActiGraph data are needed. Conclusions The number days of objective (pedometer and ActiGraph) and subjective (PA log) data needed to accurately estimate daily PA in older adults was relatively consistent. Despite no statistical differences between days for total PA by the pedometer and ActiGraph, the magnitude of differences between days suggests that day of the week cannot be completely ignored in the design and analysis of PA studies that involve < 7-day monitoring protocols for these instruments. More days of accelerometer data were needed to determine typical sedentary behaviour than PA level in this population of older adults.

Background Metabolic syndrome (MetS) increases the risk of cardiovascular disease morbidity and mortality. Physical activity (PA) reduces the likelihood of MetS, but it is a complex behavior and is accumulated in multiple domains. Purpose To cross-sectionally investigate the total and domain-specific relationships between PA and MetS in U.S. adults. Methods Data from 3,408 adults participating in the National Health and Nutrition Examination Survey (2013–2018) were analyzed. Blood pressure (BP), waist circumference (WC), fasting blood glucose (GLU), triglycerides (TRIG), and high-density lipoprotein (HDL) were measured. MetS and its risk factors were the primary and secondary outcomes, respectively. Weekly minutes of total PA and domain-specific PA (i.e., leisure-time (LTPA), transportation (TPA), occupational & household (OHPA)), were self-reported. For each exposure, participants were grouped into weekly PA: (1) 0 min, (2) 1–149 min, (3) 150–299 min, (4) 300–599 min, and (5) 600 + minutes. Logistic regression estimated the odds of having MetS, and its risk factors from PA. Results Total PA was associated with lower odds of most MetS risk factors. Compared to no LTPA, and independent of TPA and OHPA, engaging in 150–299 and 300–599 min/week of LTPA was associated with 30% (OR = 0.70 [95%CI: 0.50, 0.98]) and 43% (OR = 0.57 [95%CI: 0.35, 0.92]) lower odds of MetS, respectively. LTPA was also associated with lower odds of having high WC, GLU, TRIG, and low HDL (ORs = 0.52–0.68). Compared to no TPA, and independent of LTPA and OHPA, engaging in 300–599 min/week of TPA was associated with 54% lower odds of MetS (OR = 0.46 [95%CI: 0.25, 0.84]) and 40% lower odds of having a high WC (OR = 0.40 [95%CI: 0.21, 0.76]). Engaging in OHPA was not associated with MetS but was associated with greater odds of having a high WC (OR = 1.44 [95%CI: 1.03, 2.01]), and GLU (ORs = 1.52–1.83), independent of LTPA and TPA. Conclusion Total PA, seemingly driven by LTPA, was inversely associated with cardiometabolic health. TPA also showcases some protective associations, while OHPA appears to not confer cardiometabolic health benefits. Longitudinal data should confirm these associations using more robust PA measurement tools.

Direct observation is a ground-truth measure for physical behavior, but the high cost limits widespread use. The purpose of this study was to develop and test machine learning methods to recognize aspects of physical behavior and location from videos of human movement: Adults (N = 26, aged 18–59 y) were recorded in their natural environment for two, 2- to 3-h sessions. Trained research assistants annotated videos using commercially available software including the following taxonomies: (1) sedentary versus non-sedentary (two classes); (2) activity type (four classes: sedentary, walking, running, and mixed movement); and (3) activity intensity (four classes: sedentary, light, moderate, and vigorous). Four machine learning approaches were trained and evaluated for each taxonomy. Models were trained on 80% of the videos, validated on 10%, and final accuracy is reported on the remaining 10% of the videos not used in training. Overall accuracy was as follows: 87.4% for Taxonomy 1, 63.1% for Taxonomy 2, and 68.6% for Taxonomy 3. This study shows it is possible to use computer vision to annotate aspects of physical behavior, speeding up the time and reducing labor required for direct observation. Future research should test these machine learning models on larger, independent datasets and take advantage of analysis of video fragments, rather than individual still images.

Field tests to estimate maximal oxygen consumption (VO2max) are an alternative to traditional exercise testing methods. Published field tests and their accompanying estimation equations account for up to 80% of the variance in VO2max with an error rate of ~4.5 ml.kg-1.min-1. These tests are limited to very specific age-range populations. The purpose of this study was to create and validate a series of easily administered walking and stepping field equations to predict VO2max across a range of healthy 18-79-year-old adults. One-hundred-fifty-seven adults completed a graded maximal exercise test to assess VO2max. Five separate walking and three separate stepping tests of varying durations, number of stages, and intensities were completed. VO2max estimation equations were created using hierarchal multiple regression. Covariates including age, sex, body mass, resting heart rate, distance walked, gait speed, stepping cadence, and recovery heart rate were entered into each model using a stepwise approach. Each full model created had the same base model consisting of age, sex, and body mass. Validity of each model was assessed using a Jackknife cross-validation analysis, and percent bias and root mean square error (RMSE) were calculated. Base models accounted for ~72% of the total variance of VO2max. Full model variance ranged from ~79-83% and bias was minimal (<±1.0%) across models. RMSE for all models were approximately 4.5 ml.kg-1.min-1. Stepping tests performed better than walking tests by explaining ~2.5% more of the variance and displayed smaller RMSE. All eight models accounted for a large percentage of VO2max variance (~81%) with a RMSE of ~4.5 ml.kg-1.min-1. The variance and level of error of models examined highlight good group mean prediction with greater error expected at the individual level. All the models perform similarly across a broad age range, highlighting flexibility in application of these tests to a more general population.

Background Prior studies evaluating the impact of the COVID-19 pandemic on pregnancy physical activity (PA) have largely been limited to internet-based surveys not validated for use in pregnancy. Methods This study used data from the Pregnancy PA Questionnaire Validation study conducted from 2019–2021. A prospective cohort of 50 pregnant women completed the Pregnancy PA Questionnaire (PPAQ), validated for use in pregnancy, in early, mid, and late pregnancy and wore an ActiGraph GT3X-BT for seven days. COVID-19 impact was defined using a fixed date of onset (March 13, 2020) and a self-reported date. Multivariable linear mixed effects regression models adjusted for age, early pregnancy BMI, gestational age, and parity. Results Higher sedentary behavior (14.2 MET-hrs/wk, 95% CI: 2.3, 26.0) and household/caregiving PA (34.4 MET-hrs/wk, 95% CI: 8.5, 60.3 and 25.9 MET-hrs/wk, 95% CI: 0.9, 50.9) and lower locomotion (-8.0 h/wk, 95% CI: -15.7, -0.3) and occupational PA (-34.5 MET-hrs/wk, 95% CI: -61.9, -7.0 and -30.6 MET-hrs/wk, 95% CI: -51.4, -9.8) was observed in middle and late pregnancy, respectively, after COVID-19 vs. before. There was no impact on steps/day or meeting American College of Obstetricians and Gynecologists guidelines. Conclusions Proactive approaches for the promotion of pregnancy PA during pandemic-related restrictions are critically needed.

Background Advances in technology, social influences and environmental attributes have resulted in substan-tial portions of the day spent in sedentary pursuits. Sedentary behavior may be a cause of many chronic diseases including obesity, insulin resistance, type 2 diabetes and the metabolic syndrome. Research demonstrated that breaking up sedentary time was beneficially associated with markers of body composition, cardiovascular health and type 2 diabetes. Therefore, the purpose of this study was to quantify the total energy expenditure of three different durations of physical activity within a 30-minute sedentary period and to examine the potential benefits of interrupting sedentary behavior with physical activity for weight control. Methods Participants completed four consecutive 30-minute bouts of sedentary behavior (reading, working on the computer, or doing other desk activities) with and without interruptions of walking at a self-selected pace. Bout one contained no walking interruptions. Bout two contained a 1-minute walking period. Bout three contained a 2-minute walking period. Bout four contained a 5-minute walking period. Body composition and resting metabolic rate were assessed. Result Twenty males and females (18-39 years) completed this study. Results of the repeated measures analysis of variance with post-hoc testing showed that significantly more energy was expended during each 30 minute sedentary bout with a walking break than in the 30 minute sedentary bout ( p < 0.05 for all comparisons). On average, participants expended an additional 3.0, 7.4, and 16.5 additional net or activity kilocalories during bouts 2, 3, and 4, respectively compared with bout 1. When extrapolated for a full eight-hour working day, this data shows that an individual would theoretically expend an additional 24, 59 or 132 kilocalories per day, if they stood up and walked at a normal, self selected pace for one, two or five minutes every hour, respectively, compared with sitting for the 8-hour period. Conclusions This study demonstrated that making small changes, such as taking a five minute walking break every hour could yield beneficial weight control or weight loss results. Therefore, taking breaks from sedentary time is a potential outlet to prevent obesity and the rise of obesity in developed countries.

Background Few studies have investigated both the self-perceived and measured environment with objectively determined physical activity in older adults. Accordingly, the aim of this study was to examine measured and perceived environmental associations with physical activity of older adults residing across different neighborhood types. Methods One-hundred and forty-eight older individuals, mean age 64.3 ± 8.4, were randomly recruited from one of four neighborhoods that were pre-determined as either having high- or low walkable characteristics. Individual residences were geocoded and 200 m network buffers established. Both objective environment audit, and self-perceived environmental measures were collected, in conjunction with accelerometer derived physical activity behavior. Using both perceived and objective environment data, analysis consisted of a macro-level comparison of physical activity levels across neighborhood, and a micro-level analysis of individual environmental predictors of physical activity levels. Results Individuals residing in high-walkable neighborhoods on average engaged in 11 min of moderate to vigorous physical activity per day more than individuals residing in low-walkable neighborhoods. Both measured access to non-residential destinations (b = .11, p < .001) and self-perceived access to non-residential uses (b = 2.89, p = .031) were significant predictors of time spent in moderate to vigorous physical activity. Other environmental variables significantly predicting components of physical activity behavior included presence of measured neighborhood crime signage (b = .4785, p = .031), measured street safety (b = 26.8, p = .006), and perceived neighborhood satisfaction (b = .5.8, p = .003). Conclusions Older adult residents who live in high-walkable neighborhoods, who have easy and close access to nonresidential destinations, have lower social dysfunction pertinent to crime, and generally perceive the neighborhood to a higher overall satisfaction are likely to engage in higher levels of physical activity behavior. Efforts aimed at promoting more walkable neighborhoods could influence activity levels in older adults.

Background Despite the known benefits of non-sedentary behavior, physical activity, and protein and caloric intake to health and muscle mass, strength, and function, many older adults do not meet physical activity and dietary recommendations. A better understanding of the factors associated with sedentary behavior, physical activity and dietary self-management behaviors, and muscle outcomes (muscle mass, strength, and function) is needed, particularly among continuing care retirement community residents. The objective of this study was to examine the factors associated with sedentary behavior, physical activity and dietary self-management behaviors, and muscle outcomes among continuing care retirement community residents. It also aimed to determine whether sedentary behavior and physical activity and dietary self-management behaviors mediate the relationships between self-efficacy, goal congruence, aging expectations, social support, and muscle outcomes. Methods A sample of 105 continuing care retirement community residents (age  >  70 years) participated in this correlational, cross-sectional study. Questionnaires on pain, self-efficacy, goal congruence, aging expectation, social support, and daily protein and caloric intake were administered. Physical activity and sedentary behavior (ActiGraph wGT3X-BT), muscle mass (ImpediMed SFB7), muscle strength (Jamar Smart Digital Hand Dynamometer), and muscle function (Short Physical Performance Battery) were measured. Multiple regression, logistic regression, and mediation analyses were performed. Results Low goal congruence predicted engagement in sedentary behavior and light physical activity. Higher levels of self-efficacy and social support were associated with increased likelihoods of achieving greater moderate physical activity and meeting daily recommendations for caloric intake, respectively. Self-efficacy and goal congruence predicted muscle function and strength. Moreover, sedentary behavior and achieving greater moderate physical activity were found to partially but significantly mediate the relationship between self-efficacy and muscle function. Conclusion Future research should evaluate whether attempts to reduce sedentary behavior and promote physical activity and dietary self-management behaviors and muscle outcomes are more successful when modifications to the self-management process factors are also targeted.

Background Accelerometers were incorporated in the 2003–2004 National Health and Nutritional Examination Survey (NHANES) study cycle for objective assessment of physical activity. This is the first time that objective physical activity data are available on a nationally representative sample of U.S. residents. The use of accelerometers allows researchers to measure total physical activity, including light intensity and unstructured activities, which may be a better predictor of health outcomes than structured activity alone. The aim of this study was to examine objectively determined physical activity levels by sex, age and racial/ethnic groups in a national sample of U.S. adults. Methods Data were obtained from the 2003–2004 NHANES, a cross-sectional study of a complex, multistage probability sample of the U.S. population. Physical activity was assessed with the Actigraph AM-7164 accelerometer for seven days following an examination. 2,688 U.S. adults with valid accelerometer data (i.e. at least four days with at least 10 hours of wear-time) were included in the analysis. Mean daily total physical activity counts, as well as counts accumulated in minutes of light, and moderate-vigorous intensity physical activity are presented by sex across age and racial/ethnic groups. Generalized linear modeling using the log link function was performed to compare physical activity in sex and racial/ethnic groups adjusting for age. Results Physical activity decreases with age for both men and women across all racial/ethnic groups with men being more active than women, with the exception of Hispanic women. Hispanic women are more active at middle age (40–59 years) compared to younger or older age and not significantly less active than men in middle or older age groups (i.e. age 40–59 or age 60 and older). Hispanic men accumulate more total and light intensity physical activity counts than their white and black counterparts for all age groups. Conclusion Physical activity levels measured objectively by accelerometer demonstrated that Hispanic men are, in general, more active than their white and black counterparts. This appears to be in contrast to self-reported physical activity previously reported in the literature and identifies the need to use objective measures in situations where the contribution of light intensity and/or unstructured physical activity cannot be assumed homogenous across the populations of interest.

With a growing aging population, the routine assessment of physical function may become a critical component of clinical practice. The purpose of this cross-sectional study is to compare two common assessments of muscular function: (1) isometric knee extension strength (KES) and (2) sit-to-stand (STS) muscle power tests, in predicting objective physical function (i.e., gait speed) in aging adults. 84 adults (56% female, mean (SD) age = 66.6 (9.4) years) had their relative KES, STS power, usual gait speed (UGS), and fast gait speed (FGS) assessed. Multiple linear regression examined the associations between KES, STS power, and gait outcomes. When entered in separate models, KES and STS power were both independently associated with UGS and FGS (Std. β = 0.35–0.44 and 0.42–0.55 for KES and STS power, respectively). When entered in the same model, STS power was associated with UGS and FGS (Std. β = 0.37 [95%CI: 0.15, 0.58] and 0.51 [95%CI: 0.31, 0.70], respectively), while KES was only associated with FGS (Std. β = 0.25 [95%CI: 0.02, 0.48]). STS power seems to be a valid indicator of function in aging adults. Its feasibility as a screening tool for “low” function in the primary care setting should be explored.