Dataset Information

Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The Women's Health Initiative OPACH Calibration Study.

ABSTRACT: OBJECTIVE:We conducted a laboratory-based calibration study to determine relevant cutpoints for a hip-worn accelerometer among women ?60 years, considering both type and filtering of counts. METHODS:Two hundred women wore an ActiGraph GT3X+ accelerometer on their hip while performing eight laboratory-based activities. Oxygen uptake was measured using an Oxycon portable calorimeter. Accelerometer data were analyzed in 15-second epochs for both normal and low frequency extension (LFE) filters. Receiver operating characteristic (ROC) curve analyses were used to calculate cutpoints for sedentary, light (low and high), and moderate to vigorous physical activity (MVPA) using the vertical axis and vector magnitude (VM) counts. RESULTS:Mean age was 75.5 years (standard deviation 7.7). The Spearman correlation between oxygen uptake and accelerometry ranged from 0.77 to 0.85 for the normal and LFE filters and for both the vertical axis and VM. The area under the ROC curve was generally higher for VM compared to the vertical axis, and higher for cutpoints distinguishing MVPA compared to sedentary and light low activities. The VM better discriminated sedentary from light low activities compared to the vertical axis. The area under the ROC curves were better for the LFE filter compared to the normal filter for the vertical axis counts, but no meaningful differences were found by filter type for VM counts. CONCLUSION:The cutpoints derived for this study among women ?60 years can be applied to ongoing epidemiologic studies to define a range of physical activity intensities.

SUBMITTER: Evenson KR

PROVIDER: S-EPMC4625400 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The Women's Health Initiative OPACH Calibration Study.

Evenson Kelly R KR Wen Fang F Herring Amy H AH Di Chongzhi C LaMonte Michael J MJ Tinker Lesley Fels LF Lee I-Min IM Rillamas-Sun Eileen E LaCroix Andrea Z AZ Buchner David M DM

Preventive medicine reports 20150101

<h4>Objective</h4>We conducted a laboratory-based calibration study to determine relevant cutpoints for a hip-worn accelerometer among women ≥60 years, considering both type and filtering of counts.<h4>Methods</h4>Two hundred women wore an ActiGraph GT3X+ accelerometer on their hip while performing eight laboratory-based activities. Oxygen uptake was measured using an Oxycon portable calorimeter. Accelerometer data were analyzed in 15-second epochs for both normal and low frequency extension (LF ...[more]

PMID: 26527313

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Project description:BACKGROUND:Physical activity (PA) level is associated with multiple health benefits during early childhood. However, inconsistency in the methods for quantification of PA levels among preschoolers remains a problem. OBJECTIVE:This study aimed to develop PA intensity cut points for wrist-worn accelerometers by using machine learning (ML) approaches to assess PA in preschoolers. METHODS:Wrist- and hip-derived acceleration data were collected simultaneously from 34 preschoolers on 3 consecutive preschool days. Two supervised ML models, receiver operating characteristic curve (ROC) and ordinal logistic regression (OLR), and one unsupervised ML model, k-means cluster analysis, were applied to establish wrist-worn accelerometer vector magnitude (VM) cut points to classify accelerometer counts into sedentary behavior, light PA (LPA), moderate PA (MPA), and vigorous PA (VPA). Physical activity intensity levels identified by hip-worn accelerometer VM cut points were used as reference to train the supervised ML models. Vector magnitude counts were classified by intensity based on three newly established wrist methods and the hip reference to examine classification accuracy. Daily estimates of PA were compared to the hip-reference criterion. RESULTS:In total, 3600 epochs with matched hip- and wrist-worn accelerometer VM counts were analyzed. All ML approaches performed differently on developing PA intensity cut points for wrist-worn accelerometers. Among the three ML models, k-means cluster analysis derived the following cut points: ?2556 counts per minute (cpm) for sedentary behavior, 2557-7064 cpm for LPA, 7065-14532 cpm for MPA, and ?14533 cpm for VPA; in addition, k-means cluster analysis had the highest classification accuracy, with more than 70% of the total epochs being classified into the correct PA categories, as examined by the hip reference. Additionally, k-means cut points exhibited the most accurate estimates on sedentary behavior, LPA, and VPA as the hip reference. None of the three wrist methods were able to accurately assess MPA. CONCLUSIONS:This study demonstrates the potential of ML approaches in establishing cut points for wrist-worn accelerometers to assess PA in preschoolers. However, the findings from this study warrant additional validation studies.

Project description:BackgroundHip fractures are a significant post-stroke complication. We examined predictors of hip fracture risk after stroke using data from the Women's Health Initiative (WHI). In particular, we examined the association between post-stroke disability levels and hip fracture risk.MethodsThe WHI is a prospective study of 161,808 postmenopausal women aged 50-79 years. Trained physicians adjudicated stroke events and hip fractures. Our study included stroke survivors from the observational and clinical trial arms who had a Glasgow Outcome Scale of good recovery, moderately disabled, or severely disabled and survived more than 7 days post-stroke. Hip fracture-free status was compared across disability levels. Secondary analysis examined hip fracture risk while accounting for competing risk of death.ResultsAverage age at time of stroke was 74.6±7.2 years; 84.3% were white. There were 124 hip fractures among 4,640 stroke survivors over a mean follow-up time of 3.1±1.8 years. Mortality rate was 23.3%. Severe disability at discharge (Hazard Ratio (HR): 2.1 (95% Confidence Interval (CI): 1.4-3.2), but not moderate disability (HR: 1.1 (95%CI: 0.7-1.7), was significantly associated with an increased risk of hip fracture compared to good recovery status. This association was attenuated after accounting for mortality. White race, increasing age and higher Fracture Risk Assessment Tool (FRAX)-predicted hip fracture risk (without bone density information) were associated with an increased hip fracture risk. After accounting for mortality, higher FRAX risk and white race remained significant.ConclusionSevere disability after stroke and a higher FRAX risk score were associated with risk of subsequent hip fracture. After accounting for mortality, only the FRAX risk score remained significant. The FRAX risk score appears to identify stroke survivors at high risk of fractures. Our results suggest that stroke units can consider the incorporation of osteoporosis screening into care pathways.

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Dataset Information

Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The Women's Health Initiative OPACH Calibration Study.

Publications

Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The Women's Health Initiative OPACH Calibration Study.

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