Missing value imputation for physical activity data measured by accelerometer

2016 ◽  
Vol 27 (2) ◽  
pp. 490-506 ◽  
Author(s):  
Jung Ae Lee ◽  
Jeff Gill
Keyword(s):  
Physical Activity ◽  
Count Data ◽  
R Package ◽  
Predictive Distribution ◽  
Epidemiological Studies ◽  
Accelerometer Data ◽  
Activity Data ◽  
Health And Nutrition ◽  
Log Normal ◽  
Over Dispersion

An accelerometer, a wearable motion sensor on the hip or wrist, is becoming a popular tool in clinical and epidemiological studies for measuring the physical activity. Such data provide a series of activity counts at every minute or even more often and displays a person’s activity pattern throughout a day. Unfortunately, the collected data can include irregular missing intervals because of noncompliance of participants and therefore make the statistical analysis more challenging. The purpose of this study is to develop a novel imputation method to handle the multivariate count data, motivated by the accelerometer data structure. We specify the predictive distribution of the missing data with a mixture of zero-inflated Poisson and Log-normal distribution, which is shown to be effective to deal with the minute-by-minute autocorrelation as well as under- and over-dispersion of count data. The imputation is performed at the minute level and follows the principles of multiple imputation using a fully conditional specification with the chained algorithm. To facilitate the practical use of this method, we provide an R package accelmissing. Our method is demonstrated using 2003−2004 National Health and Nutrition Examination Survey data.

scholarly journals Development and Evaluation of an Accelerometer-Based Protocol for Measuring Physical Activity Levels in Cancer Survivors: Development and Usability Study

10.2196/18491 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e18491
Author(s):  
Tracy E Crane ◽  
Meghan B Skiba ◽  
Austin Miller ◽  
David O Garcia ◽  
Cynthia A Thomson
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Data Collection ◽  
Cancer Survivors ◽  
Accelerometer Data ◽  
Activity Tracking ◽  
Activity Data ◽  
Convenience Sample ◽  
Time Points ◽  
Activity Measurements

Background The collection of self-reported physical activity using validated questionnaires has known bias and measurement error. Objective Accelerometry, an objective measure of daily activity, increases the rigor and accuracy of physical activity measurements. Here, we describe the methodology and related protocols for accelerometry data collection and quality assurance using the Actigraph GT9X accelerometer data collection in a convenience sample of ovarian cancer survivors enrolled in GOG/NRG 0225, a 24-month randomized controlled trial of diet and physical activity intervention versus attention control. Methods From July 2015 to December 2019, accelerometers were mailed on 1337 separate occasions to 580 study participants to wear at 4 time points (baseline, 6, 12, and 24 months) for 7 consecutive days. Study staff contacted participants via telephone to confirm their availability to wear the accelerometers and reviewed instructions and procedures regarding the return of the accelerometers and assisted with any technology concerns. Results We evaluated factors associated with wear compliance, including activity tracking, use of a mobile app, and demographic characteristics with chi-square tests and logistic regression. Compliant data, defined as ≥4 consecutive days with ≥10 hours daily wear time, exceeded 90% at all study time points. Activity tracking, but no other characteristics, was significantly associated with compliant data at all time points (P<.001). This implementation of data collection through accelerometry provided highly compliant and usable activity data in women who recently completed treatment for ovarian cancer. Conclusions The high compliance and data quality associated with this protocol suggest that it could be disseminated to support researchers who seek to collect robust objective activity data in cancer survivors residing in a wide geographic area.

Development and Evaluation of the Physical Activity Questionnaire for Elderly Japanese: The Nakanojo Study

2007 ◽  
Vol 15 (4) ◽  
pp. 398-411 ◽  
Author(s):  
Akitomo Yasunaga ◽  
Hyuntae Park ◽  
Eiji Watanabe ◽  
Fumiharu Togo ◽  
Sungjin Park ◽  
...  
Keyword(s):  
Physical Activity ◽  
Activities Of Daily Living ◽  
Barthel Index ◽  
Daily Living ◽  
Epidemiological Studies ◽  
Accelerometer Data ◽  
Physical Activity Questionnaire ◽  
Repeat Administration ◽  
Elderly Japanese ◽  
Activity Questionnaire

The Physical Activity Questionnaire for Elderly Japanese (PAQ-EJ) is a self-administered physical activity questionnaire for elderly Japanese; the authors report here on its repeatability and direct and indirect validity. Reliability was assessed by repeat administration after 1 month. Direct validation was based on accelerometer data collected every 4 s for 1 month in 147 individuals age 65–85 years. Indirect validation against a 10-item Barthel index (activities of daily living [ADL]) was completed in 3,084 individuals age 65–99 years. The test–retest coefficient was high (r= .64–.71). Total and subtotal scores for lower (transportation, housework, and labor) and higher intensity activities (exercise/sports) were significantly correlated with step counts and durations of physical activity <3 and ≥3 METs (r= .41, .28, .53), respectively. Controlling for age and ADL, scores for transportation, exercise/sports, and labor were greater in men, but women performed more housework. Sex- and ADL- or age-adjusted PAQ-EJ scores were significantly lower in older and dependent people. PAQ-EJ repeatability and validity seem comparable to those of instruments used in Western epidemiological studies.

scholarly journals The Relation of Accelerometer-Measured Physical Activity and Serum Uric Acid Using the National Health and Nutrition Survey (NHANES) 2003–2004

2022 ◽  
Vol 3 ◽  
Author(s):  
Isaac D. Smith ◽  
Leanna M. Ross ◽  
Josi R. Gabaldon ◽  
Nicholas Holdgate ◽  
Carl F. Pieper ◽  
...  
Keyword(s):  
Physical Activity ◽  
Uric Acid ◽  
Serum Uric Acid ◽  
National Health ◽  
Moderate Intensity ◽  
Accelerometer Data ◽  
Health And Nutrition ◽  
Non Linear ◽  
Objectively Measured ◽  
Objectively Measured Physical Activity

Objective: Gout is a crystal-induced inflammatory arthritis caused by elevated uric acid. Physical activity has the potential to reduce serum uric acid (SUA), thus improving the disease burden of gout. In this study, we examined the association of objectively-measured physical activity and SUA.Methods: A cross-sectional study was conducted using survey, laboratory, and accelerometer data from the 2003–2004 National Health and Nutrition Examination Survey (NHANES). SUA concentrations (mg/dL) were obtained during an initial exam, and then physical activity (kCal/day) was measured with 7 days of ActiGraph accelerometry in participants (n = 3,475) representative of the ambulatory, non-institutionalized US civilian population. Regression, including restricted cubic splines, was used to assess the relation of physical activity and SUA in bivariate and adjusted models. Covariates included age, gender, race/ethnicity, alcohol use, body mass index, renal function, and urate-lowering therapy.Results: In the bivariate model, physical activity was correlated with SUA concentrations and included a non-linear component (p &lt; 0.01). In the adjusted model, linear splines were employed with a node at the SUA nadir of 5.37mg/dL; this occurred at 703 kCal/day of physical activity. The association of physical activity and SUA was negative from 0 to 703 kCal/day (p = 0.07) and positive &gt;703 kCal/day (p &lt; 0.01 for the change in slope).Conclusion: Physical activity and SUA are associated in a non-linear fashion, with a minimum estimated SUA at 703 kCal/day of objectively-measured physical activity. These findings raise intriguing questions about the use of physical activity as a potential adjunctive therapy in patients with gout, and further interventional studies are needed to elucidate the effects of moderate intensity exercise on SUA concentrations.

Waist-Worn Actigraphy: Population-Referenced Percentiles for Total Activity Counts in U.S. Adults

2015 ◽  
Vol 12 (4) ◽  
pp. 447-453 ◽  
Author(s):  
Dana L. Wolff-Hughes ◽  
Eugene C. Fitzhugh ◽  
David R. Bassett ◽  
James R. Churilla
Keyword(s):  
Physical Activity ◽  
Vigorous Physical Activity ◽  
Current Method ◽  
Total Activity ◽  
Accelerometer Data ◽  
Activity Count ◽  
Health And Nutrition ◽  
And Gender ◽  
Gender Specific ◽  
Daily Total

Background:Accelerometer-derived total activity count is a measure of total physical activity (PA) volume. The purpose of this study was to develop age- and gender-specific percentiles for daily total activity counts (TAC), minutes of moderate-to-vigorous physical activity (MVPA), and minutes of light physical activity (LPA) in U.S. adults.Methods:Waist-worn accelerometer data from the 2003-2006 National Health and Nutrition Examination Survey were used for this analysis. The sample included adults >20 years with >10 hours accelerometer wear time on >4 days (N = 6093). MVPA and LPA were defined as the number of 1-minute epochs with counts >2020 and 100 to 2019, respectively. TAC represented the activity counts acquired daily. TAC, MVPA, and LPA were averaged across valid days to produce a daily mean.Results:Males in the 50th percentile accumulated 288 140 TAC/day, with 357 and 22 minutes/day spent in LPA and MVPA, respectively. The median for females was 235 741 TAC/day, with 349 and 12 minutes/day spent in LPA and MVPA, respectively.Conclusions:Population-referenced TAC percentiles reflect the total volume of PA, expressed relative to other adults. This is a different approach to accelerometer data reduction that complements the current method of looking at time spent in intensity subcategories.

scholarly journals GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies

2021 ◽  
pp. bjsports-2020-103604
Author(s):  
Jairo H Migueles ◽  
Eivind Aadland ◽  
Lars Bo Andersen ◽  
Jan Christian Brønd ◽  
Sebastien F Chastin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Compositional Data ◽  
Epidemiological Studies ◽  
Future Research ◽  
Compositional Data Analysis ◽  
Accelerometer Data ◽  
Physical Behaviour ◽  
Analytical Approaches

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

scholarly journals Response Conversion for Improving Comparability of International Physical Activity Data

2012 ◽  
Vol 9 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Marijke Hopman-Rock ◽  
Elise Dusseldorp ◽  
Astrid Chorus ◽  
Gert Jacobusse ◽  
Alfred Ruetten ◽  
...  
Keyword(s):  
Physical Activity ◽  
Measurement Instrument ◽  
Principal Component ◽  
Cultural Bias ◽  
Face Validity ◽  
Key Comparisons ◽  
Accelerometer Data ◽  
Activity Data ◽  
Country Culture ◽  
Common Items

Background:Many questionnaires for measuring physical activity (PA) exist. This complicates the comparison of outcomes.Methods:In 8 European countries, PA was measured in random samples of 600 persons, using the IPAQ as a ‘bridge’ to historical sets of country-specific questions. We assume that a unidimensional scale of PA ability exists on which items and respondents can be placed, irrespective of country, culture, background factors, or measurement instrument. Response Conversion (RC) based on Item Response Theory (IRT) was used to estimate such a common PA scale, to compare PA levels between countries, and to create a conversion key. Comparisons were made with Eurobarometer (IPAQ) data.Results:Appropriateness of IRT was supported by the existence of a strong first dimension established by principal component analysis. The IRT analysis resulted in 1 common PA scale with a reasonable fit and face validity. However, evidence for cultural bias (Differential Item Functioning, DIF) was found in all IPAQ items. This result made actual comparison between countries difficult.Conclusions:Response Conversion can improve comparability in the field of PA. RC needs common items that are culturally unbiased. Wide-scale use of RC awaits measures that are more culturally invariant (such as international accelerometer data).

scholarly journals Measurement of Physical Activity and Sedentary Behavior by Accelerometry Among a Nationwide Sample from the KiGGS and MoMo Study: Study Protocol (Preprint)

2019 ◽  
Author(s):  
Alexander Burchartz ◽  
Kristin Manz ◽  
Bastian Anedda ◽  
Claudia Niessner ◽  
Doris Oriwol ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Collection ◽  
Children And Adolescents ◽  
Study Protocol ◽  
Large Scale ◽  
Epidemiological Studies ◽  
Activity Data ◽  
National Cohort ◽  
Technical Details ◽  
The Right

BACKGROUND Currently, no nationwide objective physical activity data exists for children and adolescents living in Germany. The German Health Interview and Examination Survey for Children and Adolescents (KiGGS) and the Motorik-Modul study (MoMo) is a national cohort study that has incorporated accelerometers in its most recent data collection wave (wave 2, since 2014). This wave 2 marks the first nationwide collection of objective data on the physical activity of children and adolescents living in Germany. OBJECTIVE The purpose of this protocol is to describe the methods used in the KiGGS and MoMo study to capture the intensity, frequency, and duration of physical activity with accelerometers. METHODS Participants (N=11,003, aged 6 to 31 years) were instructed to wear an ActiGraph GT3X+ or wGT3X-BT accelerometer laterally on the right hip. Accelerometers were worn on consecutive days during waking hours, including at least 4 valid weekdays and 1 weekend day (wear time &gt;8 hours) in the evaluation. A nonwear time protocol was also implemented. RESULTS Data collection was completed by October 2017. Data harmonization took place in 2018. The first accelerometer results from this wave were published in 2019, and detailed analyses are ready to be submitted in 2020. CONCLUSIONS This study protocol provides an overview of technical details and basic choices when using accelerometers in large-scale epidemiological studies. At the same time, the restrictions imposed by the specified filters and the evaluation routines must be taken into account. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/14370

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