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.

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.

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 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 Assessment of Household Work as Compensation for Physical Activity Deficit Amongst Older Adults in a Nigerian Urban Setting

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Eucharia O. Ejechi ◽  
◽  
May O. Esiri
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Health Benefits ◽  
Urban Setting ◽  
Moderate Intensity ◽  
Intensity Level ◽  
Household Work ◽  
Health Campaigns ◽  
Household Chores ◽  
Public Health Campaigns

Urban older adults tend to be physically inactive and often remain indoors. Household work of a sample of 300 urban-dwelling adults (50-65 years) from a Nigerian state capital was therefore investigated for physical activity (PA) levels. Questionnaire on participation in household tasks, time and days/week for the tasks, awareness of health benefits of PA and household work as exercise was used. Greater participation occurred in household chores than outdoor/yard work (70.0 vs 44.0%) while participation varied with specific chores (55.0-70.0%) and yard work (28.7-34.0%). Gender, education, age and living with spouse or children/helper were associated with performance of household chores (P<0.05) as well as with yard work except living with spouse. Prevalence of low-intensity household PA was high with only 0.9-13.8% attaining moderate-intensity level and no vigorous-intensity. Low prevalence of awareness of PA health benefits (32.3%) and household work as exercise (14.4%) was observed, but were related to good performance of household work (OR, 1.50-1.55; CL, 0.55-3.54). The finding that 13% of the respondents attained moderate-intensity PA indicated the potential of household work to compensate for the absence of other physical activities. Thus public health campaigns based on household work as exercise in a gender sensitive African society becomes necessary.

Physical Activity Measurement in Community-Dwelling Older Adults

2018 ◽  
Vol 99 (10) ◽  
pp. e71
Author(s):  
Julia M. Wright ◽  
Logan Taulbee ◽  
Allison O' Halloran ◽  
Trishia Yada ◽  
Lauren E. Graham ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Community Dwelling ◽  
Activity Measurement ◽  
Physical Activity Measurement ◽  
Community Dwelling Older Adults

Overweight adult cats have significantly lower voluntary physical activity than adult lean cats

2017 ◽  
Vol 19 (12) ◽  
pp. 1267-1273 ◽  
Author(s):  
Maria RC de Godoy ◽  
Anna K Shoveller
Keyword(s):  
Physical Activity ◽  
Social Interaction ◽  
Body Condition Score ◽  
Potential Interaction ◽  
Living Environment ◽  
Activity Level ◽  
Activity Measurement ◽  
Voluntary Physical Activity ◽  
Overweight Adult ◽  
Condition Score

Objectives The objectives of the current pilot study were to evaluate whether body condition score (BCS) and body weight are significantly related to physical activity counts, and to evaluate potential interaction between BCS and voluntary physical activity measured over a 14 day period. Methods Ten (five lean, five overweight), neutered, adult American Shorthair cats were selected for this study (median age 4 ± 0.5 years). Cats with a BCS of ⩽3.0 were considered lean, whereas cats with a BCS >3.0 were considered overweight, using a 5-point scale. Cats were housed in a free-living environment with indoor/outdoor access and were individually fed once daily a commercially available dry extruded diet and allowed 1 h to eat. Voluntary physical activity was measured consecutively for 14 days using the Actical Activity Monitors that were worn parallel to the ribs and attached via a harness. Results Lean cats had a greater mean total daily voluntary physical activity ( P = 0.0059), and a greater voluntary physical activity during light ( P = 0.0023) and dark ( P = 0.0446) periods, with overweight cats having 60% of the physical activity of lean cats. Lean cats were more active before feeding and during animal care procedures. These data suggest that lean cats have a greater anticipatory physical activity prior to feeding and are more eager to have social interaction with humans than overweight cats. A significant interaction was observed between day of physical activity measurement and BCS for total daily voluntary physical activity ( P = 0.0133) and activity during the light period ( P = 0.0016) where lean cats were consistently more active than overweight cats. In general, cats were more active during weekdays vs weekends. Conclusions and relevance The results of this study suggest that overweight cats are less active than lean cats and that voluntary physical activity level appears to be influenced by social interaction with humans.

scholarly journals Physical Activity Measurement in Older Adults: Relationships with Mental Health

2008 ◽  
Vol 16 (4) ◽  
pp. 369-380 ◽  
Author(s):  
Sarah J. Parker ◽  
Scott J. Strath ◽  
Ann M. Swartz
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Older Adults ◽  
Negative Affect ◽  
Satisfaction With Life ◽  
The Elderly ◽  
Satisfaction With Life Scale ◽  
Activity Measurement ◽  
Positive And Negative Affect ◽  
The Relationship

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.

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.

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