Prospective Association of Daily Steps With Cardiovascular Disease: A Harmonized Meta-Analysis.

BACKGROUND: Taking fewer than the widely promoted "10 000 steps per day" has recently been associated with lower risk of all-cause mortality. The relationship of steps and cardiovascular disease (CVD) risk remains poorly described. A meta-analysis examining the dose-response relationship between steps per day and CVD can help inform clinical and public health guidelines. METHODS: Eight prospective studies (20 152 adults [ie, ≥18 years of age]) were included with device-measured steps and participants followed for CVD events. Studies quantified steps per day and CVD events were defined as fatal and nonfatal coronary heart disease, stroke, and heart failure. Cox proportional hazards regression analyses were completed using study-specific quartiles and hazard ratios (HR) and 95% CI were meta-analyzed with inverse-variance-weighted random effects models. RESULTS: The mean age of participants was 63.2±12.4 years and 52% were women. The mean follow-up was 6.2 years (123 209 person-years), with a total of 1523 CVD events (12.4 per 1000 participant-years) reported. There was a significant difference in the association of steps per day and CVD between older (ie, ≥60 years of age) and younger adults (ie, <60 years of age). For older adults, the HR for quartile 2 was 0.80 (95% CI, 0.69 to 0.93), 0.62 for quartile 3 (95% CI, 0.52 to 0.74), and 0.51 for quartile 4 (95% CI, 0.41 to 0.63) compared with the lowest quartile. For younger adults, the HR for quartile 2 was 0.79 (95% CI, 0.46 to 1.35), 0.90 for quartile 3 (95% CI, 0.64 to 1.25), and 0.95 for quartile 4 (95% CI, 0.61 to 1.48) compared with the lowest quartile. Restricted cubic splines demonstrated a nonlinear association whereby more steps were associated with decreased risk of CVD among older adults. CONCLUSIONS: For older adults, taking more daily steps was associated with a progressively decreased risk of CVD. Monitoring and promoting steps per day is a simple metric for clinician-patient communication and population health to reduce the risk of CVD.

Using a consumer-based wearable activity tracker for physical activity goal setting and measuring steps in pregnant women with gestational diabetes mellitus: exploring acceptance and validity.

BACKGROUND: Activity monitoring devices may be used to facilitate goal-setting, self-monitoring, and feedback towards a step-based physical activity (PA) goal. This study examined the performance of the wrist-worn Fitbit Charge 3™ (FC3) and sought opinions on walking and stepping-in-place from women with gestational diabetes (GDM). METHODS: Participants completed six 2-min metronome-assisted over ground bouts that varied by cadence (67, 84, or 100 steps per minute) and mode (walking or stepping-in-place; N = 15), with the sequence randomized. Steps were estimated by FC3 and measured, in duplicate, by direct observation (hand-tally device, criterion). Equivalence testing by the two one-sided tests (TOST) method assessed agreement within ± 15%. Mean absolute percent error (MAPE) of steps were compared to 10%, the accuracy standard of the Consumer Technology Association (CTA)™. A subset (n = 10) completed a timed, 200-m self-paced walk to assess natural walking pace and cadence. All participants completed semi-structured interviews, which were transcribed and analyzed using descriptive and interpretive coding. RESULTS: Mean age was 27.0 years (SD 4.2), prepregnancy BMI 29.4 kg/m2 (8.3), and gestational age 32.8 weeks (SD 2.6). The FC3 was equivalent to hand-tally for bouts of metronome-assisted walking and stepping-in-place at 84 and 100 steps per minute (i.e., P < .05), although walking at 100 steps per minute (P = .01) was no longer equivalent upon adjustment for multiple comparisons (i.e., at P < .007). The FC3 was equivalent to hand-tally during the 200-m walk (i.e., P < .001), in which mean pace was 68.2 m per minute (SD 10.7), or 2.5 miles per hour, and mean cadence 108.5 steps per minute (SD 6.5). For walking at 84 and 100 steps per minute, stepping-in-place at 100 steps per minute, and the 200-m walk, MAPE was within 10%, the accuracy standard of the CTA™. Interviews revealed motivation for PA, that stepping-in-place was an acceptable alternative to walking, and competing responsibilities made it difficult to find time for PA. CONCLUSIONS: The FC3 appears to be a valid step counter during the third trimester, particularly when walking or stepping-in-place at or close to women's preferred cadence.

Systematic review of the prospective association of daily step counts with risk of mortality, cardiovascular disease, and dysglycemia.

BACKGROUND: Daily step counts is an intuitive metric that has demonstrated success in motivating physical activity in adults and may hold potential for future public health physical activity recommendations. This review seeks to clarify the pattern of the associations between daily steps and subsequent all-cause mortality, cardiovascular disease (CVD) morbidity and mortality, and dysglycemia, as well as the number of daily steps needed for health outcomes. METHODS: A systematic review was conducted to identify prospective studies assessing daily step count measured by pedometer or accelerometer and their associations with all-cause mortality, CVD morbidity or mortality, and dysglycemia (dysglycemia or diabetes incidence, insulin sensitivity, fasting glucose, HbA1c). The search was performed across the Medline, Embase, CINAHL, and the Cochrane Library databases from inception to August 1, 2019. Eligibility criteria included longitudinal design with health outcomes assessed at baseline and subsequent timepoints; defining steps per day as the exposure; reporting all-cause mortality, CVD morbidity or mortality, and/or dysglycemia outcomes; adults ≥18 years old; and non-patient populations. RESULTS: Seventeen prospective studies involving over 30,000 adults were identified. Five studies reported on all-cause mortality (follow-up time 4-10 years), four on cardiovascular risk or events (6 months to 6 years), and eight on dysglycemia outcomes (3 months to 5 years). For each 1000 daily step count increase at baseline, risk reductions in all-cause mortality (6-36%) and CVD (5-21%) at follow-up were estimated across a subsample of included studies. There was no evidence of significant interaction by age, sex, health conditions or behaviors (e.g., alcohol use, smoking status, diet) among studies that tested for interactions. Studies examining dysglycemia outcomes report inconsistent findings, partially due to heterogeneity across studies of glycemia-related biomarker outcomes, analytic approaches, and sample characteristics. CONCLUSIONS: Evidence from longitudinal data consistently demonstrated that walking an additional 1000 steps per day can help lower the risk of all-cause mortality, and CVD morbidity and mortality in adults, and that health benefits are present below 10,000 steps per day. However, the shape of the dose-response relation is not yet clear. Data are currently lacking to identify a specific minimum threshold of daily step counts needed to obtain overall health benefit.

Association of Daily Step Count and Step Intensity With Mortality Among US Adults.

Importance: It is unclear whether the number of steps per day and the intensity of stepping are associated with lower mortality. Objective: Describe the dose-response relationship between step count and intensity and mortality. Design, Setting, and Participants: Representative sample of US adults aged at least 40 years in the National Health and Nutrition Examination Survey who wore an accelerometer for up to 7 days ( from 2003-2006). Mortality was ascertained through December 2015. Exposures: Accelerometer-measured number of steps per day and 3 step intensity measures (extended bout cadence, peak 30-minute cadence, and peak 1-minute cadence [steps/min]). Accelerometer data were based on measurements obtained during a 7-day period at baseline. Main Outcomes and Measures: The primary outcome was all-cause mortality. Secondary outcomes were cardiovascular disease (CVD) and cancer mortality. Hazard ratios (HRs), mortality rates, and 95% CIs were estimated using cubic splines and quartile classifications adjusting for age; sex; race/ethnicity; education; diet; smoking status; body mass index; self-reported health; mobility limitations; and diagnoses of diabetes, stroke, heart disease, heart failure, cancer, chronic bronchitis, and emphysema. Results: A total of 4840 participants (mean age, 56.8 years; 2435 [54%] women; 1732 [36%] individuals with obesity) wore accelerometers for a mean of 5.7 days for a mean of 14.4 hours per day. The mean number of steps per day was 9124. There were 1165 deaths over a mean 10.1 years of follow-up, including 406 CVD and 283 cancer deaths. The unadjusted incidence density for all-cause mortality was 76.7 per 1000 person-years (419 deaths) for the 655 individuals who took less than 4000 steps per day; 21.4 per 1000 person-years (488 deaths) for the 1727 individuals who took 4000 to 7999 steps per day; 6.9 per 1000 person-years (176 deaths) for the 1539 individuals who took 8000 to 11 999 steps per day; and 4.8 per 1000 person-years (82 deaths) for the 919 individuals who took at least 12 000 steps per day. Compared with taking 4000 steps per day, taking 8000 steps per day was associated with significantly lower all-cause mortality (HR, 0.49 [95% CI, 0.44-0.55]), as was taking 12 000 steps per day (HR, 0.35 [95% CI, 0.28-0.45]). Unadjusted incidence density for all-cause mortality by peak 30 cadence was 32.9 per 1000 person-years (406 deaths) for the 1080 individuals who took 18.5 to 56.0 steps per minute; 12.6 per 1000 person-years (207 deaths) for the 1153 individuals who took 56.1 to 69.2 steps per minute; 6.8 per 1000 person-years (124 deaths) for the 1074 individuals who took 69.3 to 82.8 steps per minute; and 5.3 per 1000 person-years (108 deaths) for the 1037 individuals who took 82.9 to 149.5 steps per minute. Greater step intensity was not significantly associated with lower mortality after adjustment for total steps per day (eg, highest vs lowest quartile of peak 30 cadence: HR, 0.90 [95% CI, 0.65-1.27]; P value for trend = .34). Conclusions and Relevance: Based on a representative sample of US adults, a greater number of daily steps was significantly associated with lower all-cause mortality. There was no significant association between step intensity and mortality after adjusting for total steps per day.

Energy Cost Expression for a Youth Compendium of Physical Activities: Rationale for Using Age Groups.

PURPOSE: This study compared the accuracy of physical activity energy expenditure (PAEE) prediction using 2 methods of accounting for age dependency versus 1 standard (single) value across all ages. METHODS: PAEE estimates were derived by pooling data from 5 studies. Participants, 6-18 years (n = 929), engaged in 14 activities while in a room calorimeter or wearing a portable metabolic analyzer. Linear regression was used to estimate the measurement error in PAEE (expressed as youth metabolic equivalent) associated with using age groups (6-9, 10-12, 13-15, and 16-18 y) and age-in-years [each year of chronological age (eg, 12 = 12.0-12.99 y)] versus the standard (a single value across all ages). RESULTS: Age groups and age-in-years showed similar error, and both showed less error than the standard method for cycling, skilled, and moderate- to vigorous-intensity activities. For sedentary and light activities, the standard had similar error to the other 2 methods. Mean values for root mean square error ranged from 0.2 to 1.7 youth metabolic equivalent across all activities. Error reduction ranged from -0.2% to 21.7% for age groups and -0.23% to 18.2% for age-in-years compared with the standard. CONCLUSIONS: Accounting for age showed lower errors than a standard (single) value; using an age-dependent model in the Youth Compendium is recommended.

Estimating physical activity in youth using an ankle accelerometer.

This study developed and validated a vector magnitude (VM) two-regression model (2RM) for use with an ankle-worn ActiGraph accelerometer. For model development, 181 youth (mean ± SD; age, 12.0 ± 1.5 yr) completed 30 min of supine rest and 2-7 structured activities. For cross-validation, 42 youth (age, 12.6 ± 0.8 yr) completed approximately 2 hr of unstructured physical activity (PA). PA data were collected using an ActiGraph accelerometer, (non-dominant ankle) and the VM was expressed as counts/5-s. Measured energy expenditure (Cosmed K4b2) was converted to youth METs (METy; activity VO2 divided by resting VO2). A coefficient of variation (CV) was calculated for each activity to distinguish continuous walking/running from intermittent activity. The ankle VM sedentary behavior threshold was ≤10 counts/5-s, and a CV≤15 counts/5-s was used to identify walking/running. The ankle VM2RM was within 0.42 METy of measured METy during the unstructured PA (P > 0.05). The ankle VM2RM was within 5.7 min of measured time spent in sedentary, LPA, MPA, and VPA (P > 0.05). Compared to the K4b2, the ankle VM2RM provided similar estimates to measured values during unstructured play and provides a feasible wear location for future studies.

Effect of Adding Online Social Support Tools to an Adult Walking Program: A Pilot Randomized Controlled Trial.

This pilot study examined the efficacy of providing access to online social support tools on adults' step counts during a technology-mediated walking intervention. Sixty-three insufficiently active adults were randomized to a 12-week walking intervention with (SUPPORT) or without (NO SUPPORT) access to online social support tools. Both groups received a pedometer, step goals, and access to relevant websites. The SUPPORT group also received access to online social support tools. A mixed-factor analysis of variance was conducted to examine within- and between-group differences in measures of daily steps, psychosocial indicators, and health. Both groups significantly (p < .05) increased their daily steps over time from baseline by 1,401 (SUPPORT) and 2,461 (NO SUPPORT), with no significant differences between groups. Psychosocial and health improvements were no greater for SUPPORT versus NO SUPPORT. The SUPPORT group's use of the online social support tools was low. Results suggest that giving adults access to online social support tools during a technology-mediated walking program did not lead to an enhanced increase in daily steps versus an identical program without these tools; however, the low use of these tools may have weakened their effect. Future studies should examine SUPPORT versus NO SUPPORT among groups with preexisting social ties.

Accelerometer-Derived Total Activity Counts, Bouted Minutes of Moderate to Vigorous Activity, and Insulin Resistance: NHANES 2003-2006.

INTRODUCTION: The objective of this study was to compare the associations of accelerometer-derived total activity counts per day and minutes of bouted moderate to vigorous physical activity (MVPA) with insulin resistance. METHODS: The sample included 2,394 adults (aged ≥20 y) from the 2003-2006 National Health and Nutrition Examination Survey. Time spent in MVPA, measured by using 2 cutpoints (≥2,020 counts/min [MVPA2,020] and ≥760 counts/min [MVPA760]), was calculated for bouts of at least 8 to 10 minutes. Total activity counts per day reflects the total amount of activity across all intensities. Insulin resistance was measured via the homeostatic model assessment of insulin resistance (HOMA-IR) and the quantitative insulin sensitivity check index (QUICKI). Two nested regression models regressed HOMA-IR and QUICKI, respectively, on minutes of bouted MVPA and total activity counts per day. We used an adjusted Wald F statistic to illustrate strength of association. RESULTS: After adjustment for covariates, total activity counts per day was more strongly associated with both HOMA-IR (adjusted Wald F = 36.83 , P < .001) and QUICKI (adjusted Wald F = 29.44, P < .001) compared with MVPA2,020 (HOMA-IR, adjusted Wald F = 4.00, P = .06; QUICKI, adjusted Wald F = 1.08, P = .31).Total activity counts per day was more strongly associated with both HOMA-IR (adjusted Wald F = 13.64, P < .001) and QUICKI (adjusted Wald F = 12.10, P < .001) compared with MVPA760 (HOMA-IR, adjusted Wald F = 1.13, P = .30; QUICKI, adjusted Wald F = 0.97, P = .33). CONCLUSION: Our study indicated that total activity counts per day has stronger associations with insulin resistance compared with minutes of bouted MVPA. The most likely explanation is that total activity counts per day captures data on light physical activity and intermittent MVPA, both of which influence insulin resistance.

Psycho-Physiological Effects of Television Viewing During Exercise.

We propose that enjoyment is an important factor in the adoption and long-term maintenance of exercise. Television (TV) viewing is believed to be a highly enjoyed leisure-time activity, combining it with exercise may make for a more enjoyable exercise experience. The objective of this study was to examine the effects of television (TV) viewing on psychological and physiological variables during a moderate-intensity exercise bout. Twenty-eight insufficiently active (<150 minutes per week of moderate intensity PA and/or 75 minutes of vigorous PA) adults (Age: M = 47.4 ± 7.6 years) participated in this study. Each participant performed three separate 30-minute walking bouts on a motorized treadmill. During each bout, participants watched a program they selected (30-minute scripted show) (self-selected TV condition), a British Broadcasting Corporation (BBC) nature program (standardized TV condition), or no TV program (no TV condition). Participants were unable to select the nature program as their self-selected program, as it was not a 30-minute scripted program. A Polar Heart Rate (HR) monitor and validated surveys on affect and enjoyment were used. Participants reported greater enjoyment of exercise for both self-selected and standardized TV conditions (97.1 ± 15.2 and 92.7 ± 15.2), compared to the No TV condition (77.5 ± 13.4, p < 0.001). The two TV conditions resulted in similar levels of focus on TV viewing (self-selected TV: 81.2 ± 19.7; standardized TV: 79.1 ± 14.2, p > 0.05) and dissociation from walking (self-selected TV: 38.1 ± 6.7 and standardized TV: 33.2 ± 3.9); they also resulted in more dissociation than the no TV condition (TV: 72.6 ± 5.6, p = 0.002). The findings indicate that TV viewing, regardless of whether the programming is self-selected or standardized, associates with greater enjoyment of exercise.

Introducing novel approaches for examining the variability of individuals' physical activity.

Tudor-Locke and colleagues previously assessed steps/day for 1 year. The aim of this study was to use this data set to introduce a novel approach for the investigation of whether individual's physical activity exhibits periodicity fluctuating round a mean and, if so, the degree of fluctuation and whether the mean changes over time. Twenty-three participants wore a pedometer for 365 days, recorded steps/day and whether the day was a workday. Fourier transform of each participant's daily steps data showed the physical activity had a periodicity of 7 days in half of the participants, matching the periodicity of the workday pattern. Activity level remained stable in half of the participants, decreased in ten participants and increased in two. In conclusion, the 7-day periodicity of activity in half of the participants and correspondence with the workday pattern suggest a social or environmental influence. The novel analytical approach introduced herein allows the determination of the periodicity of activity, the degree of variability in activity that is tolerated during day-to-day life and whether the activity level is stable. Results from the use of these methodologies in larger data sets may enable a more focused approach to the design of interventions that aim to increase activity.

Predicting energy expenditure through hand rim propulsion power output in individuals who use wheelchairs.

AIM: To examine the relationship between hand rim propulsion power and energy expenditure (EE) during wheelchair wheeling and to investigate whether adding other variables to the model could improve on the prediction of EE. METHODS: Individuals who use manual wheelchairs (n=14) performed five different wheeling activities in a wheelchair with a PowerTap power meter hub built into the right rear wheel. Activities included wheeling on a smooth, level surface at three different speeds (4.5, 5.5 and 6.5 km/h), wheeling on a rubberised track at one speed (5.5 km/h) and wheeling on a sidewalk course that included uphill and downhill segments at a self-selected speed. EE was measured using a portable indirect calorimetry system. Stepwise linear regression was performed to predict EE from power output variables. A repeated-measures analysis of variance was used to compare the measured EE to the estimates from the power models. Bland-Altman plots were used to assess the agreement between the criterion values and the predicted values. RESULTS: EE and power were significantly correlated (r=0.694, p<0.001). Regression analysis yielded three significant prediction models utilising measured power; measured power and speed; and measured power, speed and heart rate. No significant differences were found between measured EE and any of the prediction models. CONCLUSION: EE can be accurately and precisely estimated based on hand rim propulsion power. These results indicate that power could be used as a method to assess EE in individuals who use wheelchairs.

Monitoring capabilities of the Omron HJ-720ITC pedometer.

PURPOSE: The purpose of our study was to examine the monitoring capabilities of the Omron HJ-720ITC pedometer and determine the feasibility of using it in physical activity interventions. METHODS: Using data from an 8-week lifestyle-intervention study, we tested the capabilities of the pedometer for recording physical activity data. Data from a total of 28 subjects were used in our analysis. The total number of patient steps per day was recorded over the duration of an intervention, as well as "aerobic steps per day" (ie, those taken at a cadence of > 60 steps per minute for ≥ 10 consecutive minutes). Daily wear time was computed in order to ascertain participant compliance in wearing the pedometer. In addition, aerobic steps per minute were computed, providing an assessment of activity intensity during continuous walking bouts. RESULTS: Total steps per day and aerobic steps per day increased from baseline assessment to Week 8. Participants exceeded 100 steps/minute for 89% of their aerobic minutes, suggesting that they were in the moderate-intensity range (3-6 metabolic equivalent tasks) when performing continuous bouts of walking (> 10 minutes). CONCLUSION: The new pedometer is a reasonably priced, wearable activity monitor that is feasible for use in clinical and research settings.

Comparative Analysis of ActiGraph Step Counting Methods in Adults: A Systematic Literature Review and Meta-Analysis.

PURPOSE: The primary aim of this study was to compare steps per day across ActiGraph models, wear locations, and filtering methods. A secondary aim was to compare ActiGraph steps per day to those estimated by the ankle-worn StepWatch. METHODS: We conducted a systematic literature review to identify studies of adults published before May 12, 2022, that compared free-living steps per day of ActiGraph step counting methods and studies that compared ActiGraph to StepWatch. Random-effects meta-analysis compared ActiGraph models, wear locations, filter mechanisms, and ActiGraph to StepWatch steps per day. A sensitivity analysis of wear location by younger and older age was included. RESULTS: Twelve studies, with 46 comparisons, were identified. When worn on the hip, the AM-7164 recorded 123% of the GT series steps (no low-frequency extension (no LFE) or default filter). However, the AM-7164 recorded 72% of the GT series steps when the LFE was enabled. Independent of the filter used (i.e., LFE, no LFE), ActiGraph GT series monitors captured more steps on the wrist than on the hip, especially among older adults. Enabling the LFE on the GT series monitors consistently recorded more steps, regardless of wear location. When using the default filter (no LFE), ActiGraph recorded fewer steps than StepWatch (ActiGraph on hip 73% and ActiGraph on wrist 97% of StepWatch steps). When LFE was enabled, ActiGraph recorded more steps than StepWatch (ActiGraph on the hip, 132%; ActiGraph on the wrist, 178% of StepWatch steps). CONCLUSIONS: The choice of ActiGraph model, wear location, and filter all impacted steps per day in adults. These can markedly alter the steps recorded compared with a criterion method (StepWatch). This review provides critical insights for comparing studies using different ActiGraph step counting methods.

Can sedentary behavior be made more active? A randomized pilot study of TV commercial stepping versus walking.

BACKGROUND: There is a growing problem of physical inactivity in America, and approximately a quarter of the population report being completely sedentary during their leisure time. In the U.S., TV viewing is the most common leisure-time activity. Stepping in place during TV commercials (TV Commercial Stepping) could increase physical activity. The purpose of this study was to examine the feasibility of incorporating physical activity (PA) into a traditionally sedentary activity, by comparing TV Commercial Stepping during 90 min/d of TV programming to traditional exercise (Walking). METHODS: A randomized controlled pilot study of the impact of 6 months of TV Commercial Stepping versus Walking 30 min/day in adults was conducted. 58 sedentary, overweight (body mass index 33.5 ± 4.8 kg/m2) adults (age 52.0 ± 8.6 y) were randomly assigned to one of two 6-mo behavioral PA programs: 1) TV Commercial Stepping; or 2) Walking 30 min/day. To help facilitate behavior changes participants received 6 monthly phone calls, attended monthly meetings for the first 3 months, and received monthly newsletters for the last 3 months. Using intent-to-treat analysis, changes in daily steps, TV viewing, diet, body weight, waist and hip circumference, and percent fat were compared at baseline, 3, and 6 mo. Data were collected in 2010-2011, and analyzed in 2011. RESULTS: Of the 58 subjects, 47 (81%) were retained for follow-up at the completion of the 6-mo program. From baseline to 6-mo, both groups significantly increased their daily steps [4611 ± 1553 steps/d vs. 7605 ± 2471 steps/d (TV Commercial Stepping); 4909 ± 1335 steps/d vs. 7865 ± 1939 steps/d (Walking); P < 0.05] with no significant difference between groups. TV viewing and dietary intake decreased significantly in both groups. Body weight did not change, but both groups had significant decreases in percent body fat (3-mo to 6-mo), and waist and hip circumference (baseline to 6-mo) over time. CONCLUSIONS: Participants in both the TV Commercial Stepping and Walking groups had favorable changes in daily steps, TV viewing, diet, and anthropometrics. PA can be performed while viewing TV commercials and this may be a feasible alternative to traditional approaches for increasing daily steps in overweight and obese adults. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov, NCT01342471.

The Effects of Multi-Domain Interventions on Cognition: A Systematic Review.

This review aimed to evaluate the effects of multi-domain interventions on cognition among individuals without dementia. Multi-domain interventions refer to those combining any single preventive measure such as physical activity, cognitive training, and/or nutrition to prevent dementia. Seventeen studies were included (n = 10,056 total participants; mean age = 73 years), eight of which were rated as strong in quality while the other nine showed moderate quality. The standardized mean difference (SMD; d) was used to calculate the effect size for each included study. Multi-domain interventions consisting of physical activity, cognitive training, cardioprotective nutrition, and/or cardiovascular health education exerted beneficial effects on global cognition, episodic memory, and/or executive function with very small to moderate effect sizes (0.16-0.77). Nurses may consider combining these components to potentially stave off dementia. Future research is warranted to identify the optimal multi-domain intervention components that can induce clinically significant beneficial effects on cognition.

Time Trends in Physical Activity Using Wearable Devices: A Systematic Review and Meta-analysis of Studies from 1995 to 2017.

INTRODUCTION: Conflicting evidence exists on whether physical activity (PA) levels of humans have changed over the last quarter-century. The main objective of this study was to determine if there is evidence of time trends in PA, from cross-sectional studies that assessed PA at different time points using wearable devices (e.g., pedometers and accelerometers). A secondary objective was to quantify the rate of change in PA. METHODS: A systematic literature review was conducted of English-language studies indexed in PubMed, SPORTDiscus, and Web of Science (1960-2020) using search terms (time OR temporal OR secular) AND trends AND (steps per day OR pedometer OR accelerometer OR MVPA). Subsequently, a meta-analytic approach was used to aggregate data from multiple studies and to examine specific factors (i.e., sex, age-group, sex and age-group, and PA metric). RESULTS: Based on 16 peer-reviewed scientific studies conducted between 1995 and 2017, levels of ambulatory PA are trending downward in developed countries. Significant declines were seen in both males and females (P < 0.001) as well as in children (P = 0.020), adolescents (P < 0.001), and adults (P = 0.004). The average study duration was 9.4 yr (accelerometer studies, 5.3 yr; pedometer studies, 10.8 yr). For studies that assessed steps, the average change in PA was -1118 steps per day over the course of the study (P < 0.001), and adolescents had the greatest change in PA at -2278 steps per day (P < 0.001). Adolescents also had the steepest rate of change over time, expressed in steps per day per decade. CONCLUSIONS: Evidence from studies conducted in eight developed nations over a 22-yr period indicates that PA levels have declined overall, especially in adolescents. This study emphasizes the need for continued research tracking time trends in PA using wearable devices.

Accelerometer-Measured Physical Activity and Cardiometabolic Risk Factors by Race-Ethnicity: 2003-2006 NHANES.

Previous studies suggest that the magnitude of morbidity/mortality reduction may differ between race-ethnic groups despite equated dose of physical activity (PA). The purpose of this study was to compare the potential racial-ethnic differences in cardiometabolic risk factors (CMRF) across quartiles of accelerometer-derived total activity counts/day (TAC/d) among US adults. The final sample (n=4144) included adults who participated in the 2003-2006 National Health and Nutrition Examination Survey (NHANES). CMRF included fasting glucose (FG), fasting insulin (FI), HOMA-IR, resting systolic (SBP) and diastolic blood pressure (DBP), waist circumference (WC), BMI, CRP, HDL-C, LDL-C, and triglycerides. Race-ethnic groups examined included non-Hispanic white (NHW), non-Hispanic black (NHB), and Mexican American (MA). In the highest quartile, NHW had significantly lower values of HOMA-IR, FI, SBP, BMI, WC, and HDL-C when compared to NHB. Compared to MA in the highest quartile, NHW had significantly lower values of HOMA-IR, FI, BMI, and triglycerides. Significant race-ethnic differences were found for several CMRF, especially among those who were in the top quartile of PA (e.g., the most active adults). It is probable that the protective effect of higher volumes of PA on CMRF is moderated by other non-PA factors distinct to NHB and MA.

Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts.

BACKGROUND: Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality. METHODS: In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose-response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models. FINDINGS: We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per 1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3-9·9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI 0·51-0·71) for quartile 2, 0·55 (0·49-0·62) for quartile 3, and 0·47 (0·39-0·57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000-8000 steps per day and among adults younger than 60 years until 8000-10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56-0·83]) and a peak of 60 min (0·67 [0·50-0·90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1·12 [0·96-1·32]) and 100 steps per min or faster (0·86 [0·58-1·28]). INTERPRETATION: Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity. FUNDING: US Centers for Disease Control and Prevention.

Validity of estimating minute-by-minute energy expenditure of continuous walking bouts by accelerometry.

BACKGROUND: Objective measurement of physical activity remains an important challenge. For wearable monitors such as accelerometer-based physical activity monitors, more accurate methods are needed to convert activity counts into energy expenditure (EE). PURPOSE: The purpose of this study was to examine the accuracy of the refined Crouter 2-Regression Model (C2RM) for estimating EE during the transition from rest to walking and walking to rest. A secondary purpose was to determine the extent of overestimation in minute-by-minute EE between the refined C2RM and the 2006 C2RM. METHODS: Thirty volunteers (age, 28 ± 7.7 yrs) performed 15 minutes of seated rest, 8 minutes of over-ground walking, and 8 minutes of seated rest. An ActiGraph GT1M accelerometer and Cosmed K4b2 portable metabolic system were worn during all activities. Participants were randomly assigned to start the walking bout at 0, 20, or 40 s into the minute (according to the ActiGraph clock). Acceleration data were analyzed by two methods: 2006 Crouter model and a new refined model. RESULTS: The 2006 Crouter 2-Regression model over-predicted measured kcal kg-1 hr-1 during the first and last transitional minutes of the 20-s and 40-s walking conditions (P < 0.001). It also over-predicted the average EE for a walking bout (4.0 ± 0.5 kcal kg-1 hr-1), compared to both the measured kcal kg-1 hr-1 (3.6 ± 0.7 kcal kg-1 hr-1) and the refined Crouter model (3.5 ± 0.5 kcal kg-1 hr-1) (P < 0.05). CONCLUSION: The 2006 Crouter 2-regression model over-predicts EE at the beginning and end of walking bouts, due to high variability in accelerometer counts during the transitional minutes. The new refined model eliminates this problem and results in a more accurate prediction of EE during walking.