Dataset Information

Physical activity and adiposity markers at older ages: accelerometer vs questionnaire data.

ABSTRACT:

Objective

Physical activity is critically important for successful aging, but its effect on adiposity markers at older ages is unclear as much of the evidence comes from self-reported data on physical activity. We assessed the associations of questionnaire-assessed and accelerometer-assessed physical activity with adiposity markers in older adults.

Design/setting/participants

This was a cross-sectional study on 3940 participants (age range 60-83 years) of the Whitehall II study who completed a 20-item physical activity questionnaire and wore a wrist-mounted accelerometer for 9 days in 2012 and 2013.

Measurements

Total physical activity was estimated using metabolic equivalent hours/week for the questionnaire and mean acceleration for the accelerometer. Time spent in moderate-and-vigorous physical activity (MVPA) was also assessed by questionnaire and accelerometer. Adiposity assessment included body mass index, waist circumference, and fat mass index. Fat mass index was calculated as fat mass/height² (kg/m²), with fat mass estimated using bioimpedance.

Results

Greater total physical activity was associated with lower adiposity for all adiposity markers in a dose-response manner. In men, the strength of this association was 2.4 to 2.8 times stronger with the accelerometer than with questionnaire data. In women, it was 1.9 to 2.3 times stronger. For MVPA, questionnaire data in men suggested no further benefit for adiposity markers past 1 hour/week of activity. This was not the case for accelerometer-assessed MVPA where, for example, compared with men undertaking <1 hour/week of accelerometer-assessed MVPA, waist circumference was 3.06 (95% confidence interval 2.06-4.06) cm lower in those performing MVPA 1-2.5 hours/week, 4.69 (3.47-5.91) cm lower in those undertaking 2.5-4 hours/week, and 7.11 (5.93-8.29) cm lower in those performing ≥4 hours/week.

Conclusions

The association of physical activity with adiposity markers in older adults was stronger when physical activity was assessed by accelerometer compared with questionnaire, suggesting that physical activity might be more important for adiposity than previously estimated.

SUBMITTER: Sabia S

PROVIDER: S-EPMC4417049 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundHospital-acquired disability (HAD) is common and often related to low physical activity while in the hospital.ObjectiveTo examine whether wearable hospital activity trackers can be used to predict HAD.DesignA prospective observational study between January 2016 and March 2017.SettingAn academic medical center.ParticipantsCommunity-dwelling older adults, aged 60?years or older, enrolled within 24?hours of admission to general medicine (n = 46).Main measuresPrimary outcome was HAD, defined as having one or more new activity of daily living deficits, decline of four or greater on the Late-Life Function and Disability Instrument (calculated between baseline and discharge), or discharge to a skilled nursing facility. Hospital activity (mean active time, mean sedentary time, and mean step counts per day) was measured using ankle-mounted accelerometers. The association of the literature-based threshold of 900 steps/day with HAD was also evaluated.ResultsMean age was 73.2?years (SD = 9.5?years), 48% were male, and 76% were white. Median length of stay was 4?days (interquartile range [IQR] =?2.0-6.0?days); 61% (n = 28) reported being able to walk without assistance of another person or walking aid at baseline. Median daily activity time and step counts were 1.1 h/d (IQR = 0.7-1.7 h/d) and 1455.7 steps/day (IQR = 908.5-2643 steps/day), respectively. Those with HAD (41%; n = 19) had lower activity time (0.8 vs 1.4 h/d; P = .04) and fewer step counts (1186 vs 1808 steps/day; P = .04), but no difference in sedentary time, compared to those without HAD. The 900 steps/day threshold had poor sensitivity (40%) and high specificity (85%) for detecting HAD.ConclusionsLow hospital physical activity, as measured by wearable accelerometers, is associated with HAD. Clinicians can utilize wearable technology data to refer patients to physical/occupational therapy services or other mobility interventions, like walking programs. J Am Geriatr Soc 68:261-265, 2020.

Project description:Purpose: Most built environment studies have quantified characteristics of the areas around participants' homes. However, the environmental exposures for physical activity (PA) are spatially dynamic rather than static. Thus, merged accelerometer and global positioning system (GPS) data were utilized to estimate associations between the built environment and PA among adults. Methods: Participants (N = 142) were recruited on trails in Massachusetts and wore an accelerometer and GPS unit for 1-4 days. Two binary outcomes were created: moderate-to-vigorous PA (MVPA vs. light PA-to-sedentary); and light-to-vigorous PA (LVPA vs. sedentary). Five built environment variables were created within 50-meter buffers around GPS points: population density, street density, land use mix (LUM), greenness, and walkability index. Generalized linear mixed models were fit to examine associations between environmental variables and both outcomes, adjusting for demographic covariates. Results: Overall, in the fully adjusted models, greenness was positively associated with MVPA and LVPA (odds ratios [ORs] = 1.15, 95% confidence interval [CI] = 1.03, 1.30 and 1.25, 95% CI = 1.12, 1.41, respectively). In contrast, street density and LUM were negatively associated with MVPA (ORs = 0.69, 95% CI = 0.67, 0.71 and 0.87, 95% CI = 0.78, 0.97, respectively) and LVPA (ORs = 0.79, 95% CI = 0.77, 0.81 and 0.81, 95% CI = 0.74, 0.90, respectively). Negative associations of population density and walkability with both outcomes reached statistical significance, yet the effect sizes were small. Conclusions: Concurrent monitoring of activity with accelerometers and GPS units allowed us to investigate relationships between objectively measured built environment around GPS points and minute-by-minute PA. Negative relationships between street density and LUM and PA contrast evidence from most built environment studies in adults. However, direct comparisons should be made with caution since most previous studies have focused on spatially fixed buffers around home locations, rather than the precise locations where PA occurs.

Project description:There are challenges for researchers and clinicians to select the most appropriate physical activity tool, and a balance between precision and feasibility is needed. Currently it is unclear which physical activity tool should be used to assess physical activity in Bronchiectasis. The aim of this research is to compare assessment methods (pedometer and IPAQ) to our criterion method (ActiGraph) for the measurement of physical activity dimensions in Bronchiectasis (BE), and to assess their feasibility and acceptability.Patients in this analysis were enrolled in a cross-sectional study. The ActiGraph and pedometer were worn for seven consecutive days and the IPAQ was completed for the same period. Statistical analyses were performed using SPSS 20 (IBM). Descriptive statistics were used; the percentage agreement between ActiGraph and the other measures were calculated using limits of agreement. Feedback about the feasibility of the activity monitors and the IPAQ was obtained.There were 55 (22 male) data sets available. For step count there was no significant difference between the ActiGraph and Pedometer, however, total physical activity time (mins) as recorded by the ActiGraph was significantly higher than the pedometer (mean?±?SD, 232 (75) vs. 63 (32)). Levels of agreement between the two devices was very good for step count (97% agreement); and variation in the levels of agreement were within accepted limits of ±2 standard deviations from the mean value. IPAQ reported more bouted- moderate - vigorous physical activity (MVPA) [mean, SD; 167(170) vs 6(9) mins/day], and significantly less sedentary time than ActiGraph [mean, SD; 362(115) vs 634(76) vmins/day]. There were low levels of agreement between the two tools (57% sedentary behaviour; 0% MVPA10+), with IPAQ under-reporting sedentary behaviour and over-reporting MVPA10+ compared to ActiGraph. The monitors were found to be feasible and acceptable by participants and researchers; while the IPAQ was accepta ble to use, most patients required assistance to complete it.Accurate measurement of physical activity is feasible in BE and will be valuable for future trials of therapeutic interventions. ActiGraph or pedometer could be used to measure simple daily step counts, but ActiGraph was superior as it measured intensity of physical activity and was a more precise measure of time spent walking. The IPAQ does not appear to represent an accurate measure of physical activity in this population.Clinical Trials Registration Number NCT01569009 : Physical Activity in Bronchiectasis.