scholarly journals Low Frequency Extension Filter and ActiGraph-Calculated Sleep Intervals in Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 428-428
Author(s):  
Hilary Hicks ◽  
Alex Laffer ◽  
Genna Losinski ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sleep Onset ◽  
Low Frequency ◽  
Careful Consideration ◽  
Living Environment ◽  
Non Invasive ◽  
Paired Samples ◽  
Improve Accuracy ◽  
Movement Threshold

Abstract Actigraphy has become a popular, non-invasive means of continuously monitoring physical activity and sleep. One optional setting, the low frequency extension (LFE) filter, reduces the movement threshold to capture low acceleration activity that is common in older adults. This filter significantly alters physical activity outcomes (e.g., step counts), but it is unclear if this has implications for sleep interval calculations that rely upon accurate differentiation between physical activity and sleep. We investigated the effects of the LFE filter on wrist-worn sleep estimates in older adults. Participants were 9 older adults who wore the ActiGraph GT9X on their non-dominant wrist for 7 days in a free-living environment. Raw data was processed with and without the LFE filter enabled, and sleep intervals were calculated by a proprietary ActiGraph algorithm. Paired samples t-tests demonstrated that the LFE filter generated significantly later bedtimes, fewer minutes spent in bed, shorter sleep duration, and fewer awakenings during the night compared to when the filter was disabled (all p < .043). Use of the LFE filter did not lead to differences in arise time, sleep latency, efficiency, or wake after sleep onset (all p > .052). While the LFE filter was designed to improve accuracy of physical activity estimates in more sedentary populations, these findings suggest that the LFE filter also has the potential to impact sleep estimates of older adults. Researchers using ActiGraph-calculated sleep would benefit from careful consideration of this software-dependent impact.

scholarly journals ACTIGRAPH’S LOW-FREQUENCY EXTENSION FILTER FOR ESTIMATING WRIST-WORN PHYSICAL ACTIVITY IN OLDER ADULTS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S520-S521
Author(s):  
Hilary J Hicks ◽  
Alex Laffer ◽  
Genna Losinski ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Low Frequency ◽  
Living Environment ◽  
Activity Measurement ◽  
Intensity Level ◽  
Paired Samples ◽  
Software Algorithms ◽  
Research Grade ◽  
Activity Variable

Abstract Advancements in body-worn activity devices make them valuable for objective physical activity measurement. Research-grade monitors utilize software algorithms developed with younger populations using waist-worn devices. ActiGraph offers the low frequency extension (LFE) filter which reduces the movement threshold to capture low acceleration activity that is more common in older adults. It is unclear how this filter changes activity variable calculations in older adults. We investigated the effects of the LFE filter on wrist-worn activity estimates in this population. Participants were 21 older adults who wore the GT9X on their non-dominant wrist for 7 days in a free-living environment. Activity counts were estimated both with and without the LFE filter. Paired samples t-tests revealed that the LFE estimated significantly higher number of counts than non-LFE calculated counts per minute on all three axes (p < .001). Step count estimates were higher with (M = 20,780.09, SD = 5300.85) vs. without (M = 10,896.54, SD = 3489.45) the LFE filter, (t (20) = -22.21, p < .001). These differences have implications for calculations based on axis counts (e.g., Axis-1 calculated steps, intensity level classifications) that rely on waist-worn standards. For example, even without the filter, the GT9X calculated an average of 10,897 steps, which is likely an overestimate in this population. This suggests that axes-based variables should be interpreted with caution when generated with wrist-worn data, and future studies should aim to develop separate wrist and waist-worn standard estimates of these variables in older adult populations.

Estimates of Physical Activity in Older Adults Using the ActiGraph Low-Frequency Extension Filter

2021 ◽  
pp. 1-8
Author(s):  
Hilary Hicks ◽  
Alexandra Laffer ◽  
Kayla Meyer ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Low Frequency ◽  
Living Environment ◽  
Older Individuals ◽  
Many Body ◽  
Highly Active ◽  
Software Algorithms ◽  
Intensity Physical Activity ◽  
Vigorous Intensity

As a default setting, many body-worn research-grade activity monitors rely on software algorithms developed for young adults using waist-worn devices. ActiGraph offers the low-frequency extension (LFE) filter, which reduces the movement threshold to capture low acceleration activity, which is more common in older adults. It is unclear how this filter changes activity estimates and whether it is appropriate for all older adults. The authors compared activity estimates with and without the LFE filter on wrist-worn devices in a sample of 34 older adults who wore the ActiGraph GT9X on their nondominant wrist for 7 days in a free-living environment. The authors used participant characteristics to predict discrepancy in step count estimates generated with and without the LFE filter to determine which individuals are most accurately characterized. Estimates of steps per minute were higher (M = 21, SD = 1), and more activity was classified as moderate to vigorous intensity (M = 5.03%, SD = 3.92%) with the LFE filter (M = 11, SD = 1; M = 4.27%, SD = 3.52%) versus without the LFE filter (all ps < .001). The findings suggest that axes-based variables should be interpreted with caution when generated with wrist-worn data, and future studies should develop separate wrist and waist-worn standard estimates in older adults. Participation in a greater amount of moderate to vigorous intensity physical activity predicted a larger discrepancy in step counts generated with and without the filter (p < .009), suggesting that the LFE filter becomes increasingly inappropriate for use in highly active older individuals.

scholarly journals Associations Between Actigraphy-Assessed Health Behaviors and Cognitive Performance in Older Adults

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 41-41
Author(s):  
Alex Laffer ◽  
Hilary Hicks ◽  
Genna Losinski ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Executive Function ◽  
Sleep Quality ◽  
Health Behaviors ◽  
Cognitive Performance ◽  
Verbal Memory ◽  
Brain Aging ◽  
Sleep Onset ◽  
Living Environment

Abstract Lifestyle behaviors are important determinants of healthy brain aging. Research has not fully explored how sleep quality and physical activity may differentially influence specific domains of cognitive function. The present study aimed to estimate the relative influence of sleep quality and physical activity on cognitive performance in three domains in a sample of older adults. Older adults (ages 60-89, M = 74.74) without cognitive impairment (N= 160) wore an accelerometer for 7 days in a free-living environment. We used average vector magnitude counts per minute to measure total physical activity (TPA), and average wake after sleep onset (WASO) to measure sleep quality. We created cognitive composite scores (executive function, attention, and verbal memory) from neuropsychological data using confirmatory factor analysis. We regressed cognitive scores onto TPA and WASO with age and education entered as covariates. Higher amounts of physical activity and better sleep quality were associated with better executive function (R2 = 20.3%, F (4, 155) = 11.12, p &lt; .001). Neither physical activity nor sleep quality was associated with verbal memory or attention. Results suggest that more physical activity and improved ability to stay asleep may benefit executive function, but not other cognitive domains. Future studies should clarify the interaction and mechanisms of action between health behaviors and cognitive performance in older adults.

scholarly journals The Predictive Performance of Objective Measures of Physical Activity Derived From Accelerometry Data for 5-Year All-Cause Mortality in Older Adults: National Health and Nutritional Examination Survey 2003–2006

2019 ◽  
Vol 75 (9) ◽  
pp. 1779-1785 ◽  
Author(s):  
Ekaterina Smirnova ◽  
Andrew Leroux ◽  
Quy Cao ◽  
Lucia Tabacu ◽  
Vadim Zipunnikov ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Logistic Regression ◽  
National Health ◽  
Predictive Performance ◽  
Wearable Technology ◽  
Living Environment ◽  
Activity Count ◽  
All Cause Mortality ◽  
Nutritional Examination Survey

Abstract Background Declining physical activity (PA) is a hallmark of aging. Wearable technology provides reliable measures of the frequency, duration, intensity, and timing of PA. Accelerometry-derived measures of PA are compared with established predictors of 5-year all-cause mortality in older adults in terms of individual, relative, and combined predictive performance. Methods Participants aged between 50 and 85 years from the 2003–2006 National Health and Nutritional Examination Survey (NHANES, n = 2,978) wore a hip-worn accelerometer in the free-living environment for up to 7 days. A total of 33 predictors of 5-year all-cause mortality (number of events = 297), including 20 measures of objective PA, were compared using univariate and multivariate logistic regression. Results In univariate logistic regression, the total activity count was the best predictor of 5-year mortality (Area under the Curve (AUC) = 0.771) followed by age (AUC = 0.758). Overall, 9 of the top 10 predictors were objective PA measures (AUC from 0.771 to 0.692). In multivariate regression, the 10-fold cross-validated AUC was 0.798 for the model without objective PA variables (9 predictors) and 0.838 for the forward selection model with objective PA variables (13 predictors). The Net Reclassification Index was substantially improved by adding objective PA variables (p &lt; .001). Conclusions Objective accelerometry-derived PA measures outperform traditional predictors of 5-year mortality, including age. This highlights the importance of wearable technology for providing reproducible, unbiased, and prognostic biomarkers of health.

scholarly journals Are Reallocations between Sedentary Behaviour and Physical Activity Associated with Better Sleep in Adults Aged 55+ Years? An Isotemporal Substitution Analysis

2020 ◽  
Vol 17 (24) ◽  
pp. 9579
Author(s):  
Julie Vanderlinden ◽  
Gregory Biddle ◽  
Filip Boen ◽  
Jannique van Uffelen
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behaviour ◽  
Sleep Problems ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Activity Levels ◽  
Activity Data ◽  
Wake Time ◽  
Alternative Treatment Option

Physical activity has been proposed as an effective alternative treatment option for the increasing occurrence of sleep problems in older adults. Although higher physical activity levels are associated with better sleep, the association between specific physical activity intensities and sedentary behaviour (SB) with sleep remains unclear. This study examines the associations of statistically modelled time reallocations between sedentary time and different physical activity intensities with sleep outcomes using isotemporal substitution analysis. Device-measured physical activity data and both objective and subjective sleep data were collected from 439 adults aged 55+ years. Replacing 30 min of SB with moderate to vigorous intensity physical activity (MVPA) was significantly associated with an increased number of awakenings. Moreover, a reallocation of 30 min between light physical activity (LPA) and MVPA was significantly associated with increased sleep efficiency. Furthermore, reallocating 30 min of SB to LPA showed a significant association with decreased sleep efficiency. There were no significant associations of time reallocations for wake time after sleep onset, length of awakenings, and sleep quality. These results improve our understanding of the interrelationships between different intensities of movement behaviours and several aspects of sleep in older adults.

scholarly journals Actigraphy Measured Physical Activity on Cognitive Functioning in Older Adults

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 899-899
Author(s):  
Pilar Thangwaritorn ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Executive Function ◽  
Cognitive Functioning ◽  
Verbal Memory ◽  
Vigorous Physical Activity ◽  
Living Environment ◽  
Future Research ◽  
Memory And Attention ◽  
Composite Scores

Abstract Physical activity may preserve cognitive functioning in older adults. This study examined associations between objectively measured physical activity and cognitive functioning. We recruited participants (Mage = 75.38 years, SD = 5.99) with (N=26) and without (N=181) cognitive impairment from the University of Kansas Alzheimer’s Disease Center (KU-ADC). We collected cognitive data representing verbal memory, attention, and executive function. Accelerometers (Actigraph GT9X) were used to measure physical activity 24 hours a day for 7 days in a free-living environment. Physical activity was categorized as moderate to vigorous physical activity (MVPA) based on the Freedson (2011) Adult Vector Magnitude cut points. The association between cognitive functioning and total MVPA was evaluated by using multiple regression. We used factor analysis to create three composite scores (verbal memory, attention, executive function) from 11 individual cognitive tests. Compared to verbal memory and attention, results indicate that total MVPA was more strongly associated with executive function (β = 0.001, p = .024). These findings are consistent with the literature suggesting that executive function in older adults may benefit from physical activity. Future research should investigate the physiological mechanisms by which MVPA benefits executive function in contrast to types of activity that might benefit verbal memory and attention.

scholarly journals Considerations in Processing Accelerometry Data to Explore Physical Activity and Sedentary Time in Older Adults

2020 ◽  
Vol 28 (4) ◽  
pp. 623-633
Author(s):  
Claire L. Cleland ◽  
Sara Ferguson ◽  
Paul McCrorie ◽  
Jasper Schipperijn ◽  
Geraint Ellis ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Low Frequency ◽  
Correlation Coefficients ◽  
Population Surveillance ◽  
Rank Test ◽  
Cut Points ◽  
The Impact

Processing decisions for accelerometry data can have important implications for outcome measures, yet little evidence exists exploring these in older adults. The aim of the current study was to investigate the impact of three potentially important criteria on older adults, physical activity, and sedentary time. Participants (n = 222: mean age 71.75 years [SD = 6.58], 57% male) wore ActiGraph GT3X+ for 7 days. Eight data processing combinations from three criteria were explored: low-frequency extension (on/off), nonwear time (90/120 min), and intensity cut points (moderate-to-vigorous physical activity ≥1,041 and >2,000 counts/min). Analyses included Wilcoxon signed-rank test, paired t tests, and correlation coefficients (significance, p < .05). Results for low-frequency extension on 90-min nonwear time and >1,041 counts/min showed significantly higher light and moderate-to-vigorous physical activity and lower sedentary time. Cut points had the greatest impact on physical activity and sedentary time. Processing criteria can significantly impact physical activity and/or sedentary time, potentially leading to data inaccuracies, preventing cross-study comparisons and influencing the accuracy of population surveillance.

scholarly journals Mobility, Physical Activity, and Social Engagement of Community-Living Older Adults

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 27-27
Author(s):  
Wenjun Li ◽  
Lien Quach
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Social Engagement ◽  
Healthy Aging ◽  
Ethnic Disparities ◽  
Personal Characteristics ◽  
Living Environment ◽  
Community Living ◽  
Community Programs ◽  
The Impact

Abstract Mobility, physical activity and social engagement are important to healthy aging and independent living among older adults. This symposium includes four related studies on these issues. Dr. Lien Quach and her team examined racial and ethnic disparities in social engagement among community-living older adults using data from the national Health and Retirement Study. The analysis found that Asians and Hispanics had significantly lower social engagement score compared with non-Hispanic Whites, advocating for further investigations of the causes of racial disparities in social engagement. Dr. Su-I Hou’s study examined the impact of physical activity and social relationship on social engagement. The study found positive impacts of more physical activity, better social relationships and volunteers on social engagement. The results have important implications to promotion of social engagement among older adults participating in aging-in-community programs. Dr. Ladda Thiamwong’s study demonstrated the benefits of using assistive health technology (AHT) to assess the relationships between fall risks, body compositions and objectively measured physical activity in older adults. Dr. Thiamwong’ will discuss the research protocol and preliminary results. Dr. Li’s Health Aging and Neighborhood Study examined variations of older adults’ driving behaviors by sex, age, race, income, health status and housing density of the neighborhoods. The study found substantial differences in mobility and driving patterns by both personal characteristics and neighborhood living environment. The findings have important implications to community programs that support older adults aging in place.

scholarly journals EXAMINING SEX DIFFERENCES WITHIN THE RELATIONSHIP BETWEEN PHYSICAL ACTIVITY AND EXECUTIVE FUNCTION IN OLDER ADULTS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S519-S520
Author(s):  
Genna Losinski ◽  
Hilary J Hicks ◽  
Alex Laffer ◽  
Amber Watts
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Executive Function ◽  
Vigorous Physical Activity ◽  
Living Environment ◽  
Digit Symbol Substitution Test ◽  
Activity Intensity ◽  
Symbol Substitution ◽  
Stroop Color Word Test ◽  
Current Sample

Abstract Research has demonstrated sex-associated differences in physical activity and its benefits on cognition in older adults. The present study explored differential associations between moderate-to-vigorous physical activity (MVPA) and executive function, which is known to decline with aging. N = 53 older adults without cognitive impairment (M = 73.19 years, SD = 6.53) wore accelerometers (Actigraph GT3X+) during 7 consecutive days. Activity intensity was categorized as light, moderate, or vigorous based on Freedson Adult Vector Magnitude cutpoints. Participants completed a battery of executive function tests: Digit Symbol Substitution Test, Verbal Fluency, Trail Making Test, and Stroop Color-Word Test. A cognitive composite score was created using confirmatory factor analysis. Women had a higher mean MVPA (4.57%) than men (2.64%, t (19.04) = -2.49, p = .022). However, executive function performance did not differ by sex (t (26.20) = 1.67, p =.107). The interaction between sex and time in MVPA did not predict performance on executive function, adjusting for age and education. Older age was the only significant predictor of poorer executive function (β = -0.038, p = .003). The current sample had limited engagement in MVPA (range 0.18-10.87%). These findings suggest that the amount of engagement in MVPA in a free-living environment may not be sufficient to demonstrate sex-associated differences in executive function performance. Future studies should explore executive function performance with other intensity levels and examine other areas of cognition.

scholarly journals OBJECTIVELY MEASURED SLEEP CHARACTERISTICS OF OLDER ADULTS WITH AND WITHOUT ALZHEIMER’S DISEASE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S1-S2
Author(s):  
Alex Laffer ◽  
Hilary J Hicks ◽  
Genna Losinski ◽  
Amber Watts
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Living Environment ◽  
Sleep Onset Latency ◽  
Significant Group ◽  
Time In Bed ◽  
Increased Risk

Abstract Older adults commonly experience disturbed sleep such as difficulty initiating or maintaining sleep. Older adults who experience impaired sleep are at increased risk for cognitive decline or developing Alzheimer’s disease (AD). Research has shown that people with AD experience changes in sleep patterns, however, these changes are not well characterized. To better understand sleep in an older adult population with and without AD, the present study aimed to describe and compare objective sleep characteristics in both. Participants were older adults (126 with and 41 without AD) who wore an ActiGraph GT9X monitor on their non-dominant wrist for 7 days in a free-living environment. Results suggest that, compared to those without AD, participants with AD spent significantly more time in bed, t (165) = -4.37, p = .001), slept for longer durations, t (165) = -2.39, p = .044), and had less efficient sleep, t (165) = 2.71, p = .007. Participants with AD also had significantly greater sleep onset latency, more time awake after sleep onset, longer awakening lengths, and tended to arise later in the morning (all p ≤ .016). No differences were found between the groups in age, bedtime, or the number of awakenings during the night. These findings add to our understanding of the sleep disturbances experienced by older adults with and without AD. Significant group differences suggest that interventions may be necessary in treating sleep disturbances for older adults with and without AD. Future studies should examine sleep longitudinally to understand risk factors related to AD.

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