Search Results

This study examined the relationship between physical activity (PA) and mental health among older adults as measured by objective and subjective PA-assessment instruments. Pedometers (PED), accelerometers (ACC), and the Physical Activity Scale for the Elderly (PASE) were administered to measure 1 week of PA among 84 adults age 55–87 (mean = 71) years. General mental health was measured using the Positive and Negative Affect Scale (PANAS) and the Satisfaction With Life Scale (SWL). Linear regressions revealed that PA estimated by PED significantly predicted 18.1%, 8.3%, and 12.3% of variance in SWL and positive and negative affect, respectively, whereas PA estimated by the PASE did not predict any mental health variables. Results from ACC data were mixed. Hotelling–William tests between correlation coefficients revealed that the relationship between PED and SWL was significantly stronger than the relationship between PASE and SWL. Relationships between PA and mental health might depend on the PA measure used.

This study examined objectively determined walking profiles of older adults across a wide range of sociocultural backgrounds. All individuals (N = 415; 131 men age 70.5 ± 9.2 yr and 284 women age 71.5 ± 9.0 yr) underwent physiological measurements, completed pen-and-paper surveys, and wore a pedometer for 7 consecutive days. The total sample accumulated a mean of 3,987 ± 2,680 steps/day. Age (r = –.485, p < .001) and body-mass index (BMI; r = –.353, p < .001) were negatively associated with steps per day. Multivariate analysis revealed that race/ethnic category (F = 3.15, df = 3), gender (F = 2.46, df = 1), BMI (F = 6.23, df = 2), income (F = 9.86, df = 1), education (F = 43.3, df = 1), and retirement status (F = 52.3, df = 1) were significantly associated with steps per day. Collectively these categories accounted for 56% of the variance in walking activity in this independently living, community-dwelling older adult sample. Sedentary characteristics highlighted within, and step-per-day values specific to, older adults have implications for planning targeted physical activity interventions related to walking activity in this population.

The purpose of this study was to investigate the combined impact of obesity and physical activity (PA) on the health of older adults. Pedometer-determined steps/d, body-mass index (BMI), resting blood pressure, and fasting glucose (FG) were assessed in 137 older adults (69.0 ± 8.9 yr). The active group (>4,227 steps/d) had lower systolic blood pressure (SBP; p = .001), diastolic blood pressure (DBP; p = .028), and FG (p < .001) than the inactive group (≤4,227 steps/d). The normal-BMI group (18.5-24.9 kg/m²) had lower SBP (p < .001) and DBP (p = .01) than the obese group (≤30 kg/m²). There were no differences in SBP (p = .963) or DBP (p = 1.0) between active obese and inactive normal-BMI groups. The active obese group, however, had a more favorable FG than the inactive normal-BMI group (χ² = 18.9, df = 3, p = .001). Efforts to increase PA of older adults should receive the same priority as reducing obesity to improve BP and FG levels.

Older adult physical activity (PA) levels obtained from the International Physical Activity Questionnaire–Short Form (IPAQ) and accelerometry (ACC) were compared. Mean difference scores between accumulated or bout ACC PA and the IPAQ were computed. Spearman rank-order correlations were used to assess relations between time spent in PA measured from ACC and self-reported form of the IPAQ, and percentage agreement across measures was used to classify meeting or not meeting PA recommendations. The IPAQ significantly underestimated sitting and overestimated time spent in almost all PA intensities. Group associations across measures revealed significant relations in walking, total PA, and sitting for the whole group (r = .29–.36, p < .05). Significant relationships between bout ACC and IPAQ walking (r = .28–.39, p < .05) were found. There was 40–46% agreement between measures for meeting PA recommendations. The IPAQ appears not to be a good indicator of individual older adult PA behavior but is better suited for larger population-based samples.

This study examined the predictive validity of accelerometers (ACC) to estimate physical activity intensity (PAI) across age and differences in intensity predictions when expressed in relative and absolute PAI terms. Ninety adults categorized into 3 age groups (20–29, 40–49, and 60–69 yr) completed a treadmill calibration study with simultaneous ACC (7164 Actigraph) and oxygen-consumption assessment. Results revealed strong linear relations between ACC output and measured PAI (R ² = .62–.89) across age and similar ACC cut-point ranges across age delineating absolute PAI ranges compared with previous findings. Comparing measured metabolic equivalents (METs) with estimated METs derived from previously published regression equations revealed that age did not affect predictive validity of ACC estimates of absolute PAI. Comparing ACC output expressed in relative vs. absolute terms across age revealed substantial differences in PAI ACC count ranges. Further work is warranted to increase the applicability of ACC use relative to PAI differences associated with physiological changes with age.

The purpose of the study was to evaluate the accuracy of direct observation (DO) to estimate MET level and intensity category during laboratory-based and free-living activity in older adults. Older adults engaged in unstructured laboratory and free-living activity. Participants wore a portable metabolic system to measure energy expenditure and were directly observed. DO recorded MET-level point estimates. 32,401 in-laboratory and 87,715 free-living data points (9 participants, 67% male, 71.0 ± 6.9 years, 27.1 ± 4.3 kg·m^–2) were included in final analysis. Results revealed 45.4% of in-laboratory and 61.1% of free-living mean DO activities fell within 0.5 METs of the measured MET values. DO accurately classified intensity category 45.0% of the time in-laboratory and 50.9% of free-living observations. DO-estimated activity cost resulted in low point estimate accuracy however there was low variability between the mean measured and estimated METs. This suggests, dependent on the desired outcome, DO could provide a viable option for activity assessment, however, the low point estimate accuracy presents a need for further research to continue to refine the approach to increase accuracy.

Background: Older adults spend 30% of their day in light-intensity physical activity (LPA). This study was designed to determine if increasing the proportion of time spent in LPA would affect glucose control. Methods: Older adults (N = 9) completed four 3-hour treatment conditions consisting of a seated control and 3 randomized conditions: (1) 20% time spent in continuous LPA, 80% seated; (2) 40% time spent in continuous LPA, 60% seated; and (3) 60% time spent in continuous LPA, 40% seated. Energy expenditure was measured continuously, and glucose was measured prior to mixed-meal ingestion and hourly thereafter. Glucose area under the curve was compared between conditions using Friedman test. Results: There was a significant difference in glucose area under the curve by time spent in LPA (P < .001); specifically, between the seated and 60% LPA (mean difference = 35.0 [24.6] mg/dL, P = .01), seated and 40% LPA (mean difference = 25.2 [11.8] mg/dL, P = .03), seated and 20% LPA (mean difference = 17.8 [22.5] mg/dL, P = .03), 20% LPA and 60% LPA (mean difference = 17.2 [22.5] mg/dL, P = .01), and 40% LPA and 60% LPA (mean difference = 9.8 [7.3] mg/dL, P = .01). Conclusion: These results provide experimental evidence to the importance LPA has on metabolic health. If older adults who already spend, on average, about 3 hours per day in LPA, further increase their LPA, they could see benefit to glucose control.

Undergraduate enrollments in kinesiology have grown over the past 20 years as the popularity of this major increased among students interested in the health professions. A panel discussion at the 2018 American Kinesiology Association workshop provided an overview of challenges facing kinesiology departments. Department leaders at four public universities discussed enrollment trends, faculty resources for teaching undergraduates, and budget models used at their universities. Comparisons were made with kinesiology departments at Big Ten universities to reflect more broadly on what is happening at U.S. public research institutions. At several universities, undergraduate kinesiology enrollments grew between 2008 and 2017, but at others, they leveled off or declined. In many cases, faculty resources have not kept pace with enrollments, leading to unhealthy student-to-faculty ratios. The panel discussed methods of coping with scarce resources for teaching undergraduates and how department leaders can use comparison data to stress the importance of adequate resources.