Risk of metabolic syndrome among law enforcement officers due to physical activity and posture behaviors.

BACKGROUND: There are limited data on objectively measured activity and postural behaviors of law enforcement officers (LEOs) in relation to risk of metabolic syndrome (MetS). OBJECTIVES: To examine the associations between objectively measured activity and postural behaviors and MetS risk among LEOs. METHODS: Thirty-one LEOs, mean (SD) age 33 (10) years, participated in the study. LEOs had their metabolic risk factors measured using blood samples after fasting for at least 10 hours prior to testing. Participants wore activity-monitoring devices for 7 consecutive days during on-duty and off-duty shifts. Eighteen participants adhered to wearing the devices. Descriptive statistics were used to determine means for all MetS risk factors; time in intensity-specific physical activity behaviors; and time in various postural shifts. Correlation analyses were employed to examine relationships between activity behaviors, postures, and MetS risk factors. RESULTS: Over half (51.6%; n = 16) of the participants had 2 or more positive MetS risk factors. Mean (SD) on-duty sedentary behavior was 273 (59) minutes compared with off-duty sedentary behavior of 401 (146) minutes. Mean on-duty moderate-intensity activity was 236 (40) minutes compared with off-duty moderate-intensity activity of 305 (80) minutes. Average on-duty sitting time was 435 (69) minutes compared with off-duty sitting time of 528 (142) minutes. Average on-duty standing time was 116 (43) minutes compared with off-duty standing time of 171 (51) minutes. There were negative correlations between on-duty sedentary activity and Systolic Blood Pressure (r = -0.48) and Diastolic Blood Pressure (r = -0.48), respectively. CONCLUSIONS: Law enforcement officers have unfavorable activity and postural behaviors during a typical day regardless of working status and may be at risk for developing MetS.

Association between sleep quality and physical functioning in adults with Down syndrome: A brief report.

BACKGROUND: Sleep quality is associated with physical functioning in adults, but this has not been examined in those with Down syndrome (DS). High body mass index (BMI) and accelerated aging, both common in adults with DS, may alter the relationship between sleep quality and physical functioning in this population. OBJECTIVE: To examine sleep quality indicators and its association with physical functioning in adults with DS, and whether associations are altered by BMI and age. METHODS: Participants were 15 adults with DS (8 women; age 29 ± 14 years). We evaluated sleep quality over seven days with wrist-worn accelerometers and physical functioning with the timed-up-and-go (TUG) and 6-min walk (6 MW) tests. We examined the associations between sleep quality and physical functioning variables using Spearman's rho. RESULTS: Sleep quality indicators were: total sleep time 407 ± 54 min; latency 26.8 ± 21 min; efficiency 73.9 ± 12 %; wake after sleep onset 122.8 ± 65.2 min; number of awakenings 21.0 ± 6.2; and average length of awakenings 6.1 ± 3 min. Total sleep time and average length of awakenings were significantly associated with 6 MW distances (rho = 0.58 and -0.69; p < 0.05, respectively). After controlling for age and BMI, 6 MW distance was significantly associated with total sleep time, latency, efficiency, and average length of awakenings (rho = 0.56, -0.73, 0.60, and -0.87; p < 0.05, respectively). TUG was significantly associated with total time in bed (rho = 0.71); p < 0.05). CONCLUSIONS: Sleep quality indicators are associated with walking performance in adults with DS. Age and BMI strengthen the relationship between sleep quality and physical functioning.

Validity of the Samsung Phone S Health application for assessing steps and energy expenditure during walking and running: Does phone placement matter?

BACKGROUND: The emergence of mHealth and the utilization of smartphones in physical activity interventions warrant a closer examination of validity evidence for such technology. This study examined the validity of the Samsung S Health application in measuring steps and energy expenditure. METHODS: Twenty-nine participants (mean age 21.69 ± 1.63) participated in the study. Participants carried a Samsung smartphone in their non-dominant hand and right pocket while walking around a 200-meter track and running on a treadmill at 2.24 m∙s-1. Steps and energy expenditure from the S Health app were compared with StepWatch 3 Step Activity Monitor steps and indirect calorimetry. RESULTS: No significant differences between S Health estimated steps and energy expenditure during walking and their respective criterion measures, regardless of placement. There was also no significant difference between S Health estimated steps and the criterion measure during treadmill running, regardless of placement. There was significant differences between S Health estimated energy expenditure and the criterion during treadmill running for both placements (both p < 0.001). CONCLUSIONS: The S Health application measures steps and energy expenditure accurately during self-selected pace walking regardless of placement. Placement of the phone impacts the S Health application accuracy in measuring physical activity variables during treadmill running.

Activity Monitors Step Count Accuracy in Community-Dwelling Older Adults.

Objective: To examine the step count accuracy of activity monitors in community-dwelling older adults. Method: Twenty-nine participants aged 67.70 ± 6.07 participated. Three pedometers and the Actical accelerometer step count functions were compared with actual steps taken during a 200-m walk around an indoor track and during treadmill walking at three different speeds. Results: There was no statistical difference between activity monitors step counts and actual steps during self-selected pace walking. During treadmill walking at 0.67 m∙s-1, all activity monitors step counts were significantly different from actual steps. During treadmill walking at 0.894m∙s-1, the Omron HJ-112 pedometer step counts were not significantly different from actual steps. During treadmill walking at 1.12 m∙s-1, the Yamax SW-200 pedometer steps were significantly different from actual steps. Discussion: Activity monitor selection should be deliberate when examining the walking behaviors of community-dwelling older adults, especially for those who walk at a slower pace.

Validity of the Actical activity monitor for assessing steps and energy expenditure during walking.

This study examined the validity of the Actical accelerometer step count and energy expenditure (EE) functions in healthy young adults. Forty-three participants participated in study 1. Actical step counts were compared to actual steps taken during a 200 m walk around an indoor track at self-selected pace and during treadmill walking at different speeds (0.894, 1.56 and 2.01 m · s(-1)) for 5 min. The Actical was also compared to three pedometers. For study 2, 15 participants from study 1 walked on a treadmill at their predetermined self-selected pace for 15 min. Actical EE was compared to EE measured by indirect calorimetry. One-way analysis of variance and t-tests were used to examine differences. There were no statistical difference between Actical steps and actual steps in self-selected pace walking and during treadmill walking at moderate and fast speeds. During treadmill walking at slow speed, the Actical step counts significantly under predicted actual steps taken. For study 2, there was no statistical difference between measured EE and Actical-recorded EE. The Actical provides valid estimates of step counts at self-selected pace and walking at constant speeds of 1.56 and 2.01 m · s(-1). The Actical underestimates EE of walking at constants speeds ≥ 1.38 m · s(-1).

Validity evidence for self-report with assistance to measure physical activity behavior in adults with intellectual disabilities.

Self-reported physical activity (PA) behavior with assistance from a secondary source has previously been used with adults with an intellectual disability (ID). Limited evidence of reliability and validity have been provided for this approach. This study examined evidence of convergent (CV) and discriminant (DV) validity for self-report with assistance from a secondary source as a measure of PA in adults with ID. PA of 37 participants with ID were assessed using (a) self-report, (b) accelerometers, and (c) pedometers. The multitrait-multimethod (MTMM) analysis was used to evaluate validity. MTMM analysis revealed high reliability among variables, low to strong CV, and moderate DV. The study outcomes provide initial convergent and discriminant validity evidence for this measure of PA in adults with ID.

ADA Compliance and Accessibility of Fitness Facilities in Western Wisconsin.

PURPOSE: The study expands the research on fitness facility accessibility by determining how compliant fitness facilities in rural western Wisconsin were with Title III of the Americans with Disabilities Act (ADA). Comparisons were made with 4 other studies that were conducted in different geographical regions. The study also examined fitness professionals' disability knowledge and awareness. METHOD: An ADA fitness facility compliance instrument and a fitness professional disability awareness survey were used. Direct observation and physical measurements were taken during on-site visits to 16 of 36 eligible fitness facilities in rural western Wisconsin. Ten fitness professionals from participating facilities completed an online survey. Frequencies were used to analyze the results. RESULTS: None of the participating facilities were in 100% compliance with ADA. Customer service desk (84%) and path of travel throughout the facility (72%) were the highest compliance areas. Telephone (6%) and locker rooms (32%) were the lowest compliance areas. No fitness professional was trained in wheelchair transfers and very few had received training in providing services to individuals with disabilities. CONCLUSION: Fitness facility accessibility remains a concern nationally. Continued efforts need to be made to raise the awareness of ADA compliance among fitness professionals across the United States, especially in rural areas where fitness facility availability is limited.