Dataset Information

Influence of the Duration and Timing of Data Collection on Accelerometer-Measured Physical Activity, Sedentary Time and Associated Insulin Resistance.

ABSTRACT: Accelerometry is a commonly used method to determine physical activity in clinical studies, but the duration and timing of measurement have seldom been addressed. We aimed to evaluate possible changes in the measured outcomes and associations with insulin resistance during four weeks of accelerometry data collection. This study included 143 participants (median age of 59 (IQR9) years; mean BMI of 30.7 (SD4) kg/m2; 41 men). Sedentary and standing time, breaks in sedentary time, and different intensities of physical activity were measured with hip-worn accelerometers. Differences in the accelerometer-based results between weeks 1, 2, 3 and 4 were analyzed by mixed models, differences during winter and summer by two-way ANOVA, and the associations between insulin resistance and cumulative means of accelerometer results during weeks 1 to 4 by linear models. Mean accelerometry duration was 24 (SD3) days. Sedentary time decreased after three weeks of measurement. More physical activity was measured during summer compared to winter. The associations between insulin resistance and sedentary behavior and light physical activity were non-significant after the first week of measurement, but the associations turned significant in two to three weeks. If the purpose of data collection is to reveal associations between accelerometer-measured outcomes and tenuous health outcomes, such as insulin sensitivity, data collection for at least three weeks may be needed.

SUBMITTER: Sjoros T

PROVIDER: S-EPMC8125504 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Influence of the Duration and Timing of Data Collection on Accelerometer-Measured Physical Activity, Sedentary Time and Associated Insulin Resistance.

Sjöros Tanja T Vähä-Ypyä Henri H Laine Saara S Garthwaite Taru T Löyttyniemi Eliisa E Sievänen Harri H Kalliokoski Kari K KK Knuuti Juhani J Vasankari Tommi T Heinonen Ilkka H A IHA

International journal of environmental research and public health 20210506 9

Accelerometry is a commonly used method to determine physical activity in clinical studies, but the duration and timing of measurement have seldom been addressed. We aimed to evaluate possible changes in the measured outcomes and associations with insulin resistance during four weeks of accelerometry data collection. This study included 143 participants (median age of 59 (IQR9) years; mean BMI of 30.7 (SD4) kg/m<sup>2</sup>; 41 men). Sedentary and standing time, breaks in sedentary time, and dif ...[more]

PMID: 34066552

Similar Datasets

Project description:ImportanceThe amount and intensity of physical activity required to prevent stroke are yet to be fully determined because of previous reliance on self-reporting measures. Furthermore, the association between objectively measured time spent being sedentary as an independent risk factor for stroke is unknown.ObjectiveTo investigate the associations of accelerometer-measured sedentary time and physical activity of varying intensity and duration with the risk of incident stroke.Design, setting, and participantsThis cohort study involved participants who were enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study from February 5, 2003, to October 30, 2007. Accelerometer data were collected from 7607 Black and White adults 45 years or older in the contiguous US between May 12, 2009, and January 5, 2013. Data on other races and ethnicities were not collected for scientific and clinical reasons. By design, Black adults and residents of the southeastern US stroke belt and stroke buckle were oversampled. Data were analyzed from May 5, 2020, to November 11, 2021.ExposuresSedentary time, light-intensity physical activity (LIPA), and moderate- to vigorous-intensity physical activity (MVPA) were measured using a hip-mounted accelerometer worn for 7 consecutive days and stratified by tertile for the analyses.Main outcomes and measuresIncident stroke.ResultsAmong 7607 participants, the mean (SD) age was 63.4 (8.5) years; 4145 participants (54.5%) were female, 2407 (31.6%) were Black, and 5200 (68.4%) were White. A total of 2523 participants (33.2%) resided in the stroke belt, and 1638 (21.5%) resided in the stroke buckle. Over a mean (SD) of 7.4 (2.5) years of follow-up, 286 incident stroke cases (244 ischemic [85.3%]) occurred. The fully adjusted hazard ratios (HRs) for incident stroke in the highest tertile compared with the lowest tertile were 0.74 (95% CI, 0.53-1.04; P = .08) for LIPA and 0.57 (95% CI, 0.38-0.84; P = .004) for MVPA. Higher sedentary time was associated with a 44% greater risk of incident stroke (HR, 1.44; 95% CI, 0.99-2.07; P = .04). When comparing the highest with the lowest tertile, mean sedentary bout duration was associated with a significantly greater risk of incident stroke (HR, 1.53; 95% CI, 1.10-2.12; P = .008). After adjustment for sedentary time, the highest tertile of unbouted MVPA (shorter bouts [1-9 minutes]) was associated with a significantly lower risk of incident stroke compared with the lowest tertile (HR, 0.62; 95% CI, 0.41-0.94; P = .02); however, bouted MVPA (longer bouts [at least 10 minutes]) was not (HR, 0.78; 95% CI, 0.53-1.15; P = .17). When expressed as continuous variables, sedentary time was positively associated with incident stroke risk (HR per 1-hour/day increase in sedentary time: 1.14; 95% CI, 1.02-1.28; P = .02), and LIPA was negatively associated with incident stroke risk (HR per 1-hour/day increase in LIPA: 0.86; 95% CI, 0.77-0.97; P = .02).Conclusions and relevanceIn this cohort study, objectively measured LIPA, MVPA, and sedentary time were significantly and independently associated with incident stroke risk. Longer sedentary bout duration was also independently associated with an increased risk of incident stroke. These findings suggest that replacing sedentary time with LIPA, or even very short bouts of MVPA, may lower stroke risk, supporting the concept of moving more and sitting less as a beneficial stroke risk reduction strategy among adults.

Project description:ImportanceHeart failure (HF) prevention is paramount to public health in the 21st century.ObjectiveTo examine incident HF and its subtypes with preserved ejection fraction (HFpEF) and reduced EF (HFrEF) according to accelerometer-measured physical activity (PA) and sedentary time.Design, setting, and participantsThis was a prospective cohort study, the Objective Physical Activity and Cardiovascular Health (OPACH) in Older Women study, conducted from March 2012 to April 2014. Included in the analysis were women aged 63 to 99 years without known HF, who completed hip-worn triaxial accelerometry for 7 consecutive days. Follow-up for incident HF occurred through February 2022. Data were analyzed from March to December 2023.ExposureDaily PA (total, light, moderate to vigorous PA [MVPA], steps) and sedentary (total, mean bout duration) behavior.Main outcomes and measuresAdjudicated incident HF, HFpEF, and HFrEF.ResultsA total of 5951 women (mean [SD] age, 78.6 [6.8] years) without known HF were included in this analysis. Women self-identified with the following race and ethnicity categories: 2004 non-Hispanic Black (33.7%), 1022 Hispanic (17.2%), and 2925 non-Hispanic White (49.2%). There were 407 HF cases (257 HFpEF; 110 HFrEF) identified through a mean (SD) of 7.5 (2.6) years (range, 0.01-9.9 years) of follow-up. Fully adjusted hazard ratios (HRs) for overall HF, HFpEF, and HFrEF associated with a 1-SD increment were 0.85 (95% CI, 0.75-0.95), 0.78 (95% CI, 0.67-0.91), and 1.02 (95% CI, 0.81-1.28) for minutes per day total PA; 0.74 (95% CI, 0.63-0.88), 0.71 (95% CI, 0.57-0.88), and 0.83 (95% CI, 0.62-1.12) for steps per day; and 1.17 (95% CI, 1.04-1.33), 1.29 (95% CI, 1.10-1.51), and 0.94 (95% CI, 0.75-1.18) for minutes per day total sedentary. Cubic spline curves for overall HF and HFpEF were significant inverse for total PA and steps per day and positive for total sedentary. Light PA and MVPA were inversely associated with overall HF (HR per 1 SD: 0.88; 95% CI, 0.78-0.98 and 0.84; 95% CI, 0.73-0.97) and HFpEF (0.80; 95% CI, 0.70-0.93 and 0.85; 95% CI, 0.72-1.01) but not HFrEF. Associations did not meaningfully differ when stratified by age, race and ethnicity, body mass index, physical function, or comorbidity score. Results for sedentary bout duration were inconsistent.Conclusions and relevanceHigher accelerometer-measured PA (MVPA, light PA, steps per day) was associated with lower risk (and greater total sedentary time with higher risk) of overall HF and HFpEF in a racially and ethnically diverse cohort of older women. Increasing PA and reducing sedentary time for primary HFpEF prevention may have relevant implications for cardiovascular resilience and healthy aging in later life.

Project description:BackgroundRetrospective self-report questionnaires are the most common method for assessing physical activity (PA) and sedentary behavior (SB) in children when the use of objective assessment methods (eg, accelerometry) is cost prohibitive. However, self-report measures have limitations (eg, recall bias). The use of real-time, mobile ecological momentary assessment (EMA) has been proposed to address these shortcomings. The study findings will provide useful information for researchers interested in using EMA surveys for measuring PA and SB in children, particularly when reported by a parent or caregiver.ObjectiveThis study aimed to examine the associations between the parent's EMA report of their child's PA and SB and accelerometer-measured sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous-intensity PA (MVPA) and to examine if these associations differed by day of week, sex, and season.MethodsA total of 140 parent-child dyads (mean child age 6.4 years, SD 0.8; n=66 girls; n=21 African American; n=24 American Indian; n=25 Hispanic/Latino; n=24 Hmong; n=22 Somali; and n=24 white) participated in this study. During an 8-day period, parents reported child PA and SB via multiple daily signal contingent EMA surveys, and children wore a hip-mounted accelerometer to objectively measure ST, LPA, and MVPA. Accelerometer data was matched to the time period occurring before parent EMA-report of child PA and SB. Generalized estimating equations with interaction-term analyses were performed to determine whether the relationship between parent-EMA report of child PA and SB and accelerometer-measured ST and LPA and MVPA outcomes differed by day of the week, sex and season.ResultsThe parent's EMA report of their child's PA and SB was strongly associated with accelerometer-measured ST, LPA, and MVPA. The parent's EMA report of their child's PA was stronger during the weekend than on weekdays for accelerometer-measured ST (P≤.001) and LPA (P<.001). For the parent's EMA report of their child's SB, strong associations were observed with accelerometer-measured ST (P<.001), LPA (P=.005), and MVPA (P=.008). The findings related to sex-interaction terms indicated that the association between the parent-reported child's PA via EMA and the accelerometer-measured MVPA was stronger for boys than girls (P=.02). The association between the parent's EMA report of their child's PA and SB and accelerometer-measured ST and PA was similar across seasons in this sample (all P values >.31).ConclusionsWhen the use of accelerometry-based methods is not feasible and in contexts where the parent is able to spend more proximate time observing the child's PA and SB, the parent's EMA report might be a superior method for measuring PA and SB in young children relative to self-report, given the EMA's strong associations with accelerometer-measured PA and ST.

Dataset Information

Influence of the Duration and Timing of Data Collection on Accelerometer-Measured Physical Activity, Sedentary Time and Associated Insulin Resistance.

Publications

Influence of the Duration and Timing of Data Collection on Accelerometer-Measured Physical Activity, Sedentary Time and Associated Insulin Resistance.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets