Is older adults’ physical activity during transport compensated during other activities? Comparing 4 study cohorts using GPS and accelerometer data

Brondeel, Ruben; Wasfi, Rania; Perchoux, Camille; Chaix, Basile; Gerber, Philippe; Gauvin, Lise; Richard, Lucie; Gaudreau, Pierrette; Thierry, Benoît; Chevrier, Martin; Høj, Stine Bordier; Kestens, Yan

doi:10.1016/j.jth.2019.02.006

Cited by 20 publications

(12 citation statements)

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“…Quantity of OH activities might be more relevant to assess in people with depressive symptoms since a low number OH activities could be associated with a lower number of social activities [13]. Time spent in active transport modes contributes to overall physical activity levels [93, 94] and thus physical health, which should be the focus for sedentary older adults. As mentioned earlier (“Analytical aspects” section), GPS-based variability measures have barely been considered in the health and aging literature.…”

Section: Discussionmentioning

confidence: 99%

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

et al. 2019

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Background GPS tracking is increasingly used in health and aging research to objectively and unobtrusively assess individuals’ daily-life mobility. However, mobility is a complex concept and its thorough description based on GPS-derived mobility indicators remains challenging. Methods With the aim of reflecting the breadth of aspects incorporated in daily mobility, we propose a conceptual framework to classify GPS-derived mobility indicators based on their characteristic and analytical properties for application in health and aging research. In order to demonstrate how the classification framework can be applied, existing mobility indicators as used in existing studies are classified according to the proposed framework. Then, we propose and compute a set of selected mobility indicators based on real-life GPS data of 95 older adults that reflects diverse aspects of individuals’ daily mobility. To explore latent dimensions that underlie the mobility indicators, we conduct a factor analysis. Results The proposed framework enables a conceptual classification of mobility indicators based on the characteristic and analytical aspects they reflect. Characteristic aspects inform about the content of the mobility indicator and comprise categories related to space, time, movement scope , and attribute . Analytical aspects inform how a mobility indicator is aggregated with respect to temporal scale and statistical property . The proposed categories complement existing studies that often underrepresent mobility indicators involving timing, temporal distributions, and stop-move segmentations of movements. The factor analysis uncovers the following six dimensions required to obtain a comprehensive view of an older adult’s daily mobility: extent of life space, quantity of out-of-home activities, time spent in active transport modes, stability of life space, elongation of life space, and timing of mobility. Conclusion This research advocates incorporating GPS-based mobility indicators that reflect the multi-dimensional nature of individuals’ daily mobility in future health- and aging-related research. This will foster a better understanding of what aspects of mobility are key to healthy aging. Electronic supplementary material The online version of this article (10.1186/s12942-019-0181-0) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

et al. 2019

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“…The inhabitants of smaller towns and villages are more likely to achieve PA recommendations [ 42 ]. Seniors living in residential areas with ≤100,000 inhabitants are more likely to achieve the walking recommendation in the context of overall walking as well as active transport [ 43 ]. In contrast, our findings suggest, that urban living has a positive impact on quality of life, the urban residents have better QoL, than rural residents.…”

Section: Discussionmentioning

confidence: 99%

Association with subjective measured physical activity (GPAQ) and quality of life (WHOQoL-BREF) of ageing adults in Hungary, a cross-sectional study

et al. 2020

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Background: It is well known that physical activity (PA) has health benefits. This study aimed to examine physical activity carried out by the senior (over 50) participants and its relation to their quality of life (QoL). Methods: Surveillance of PA and QoL was measured by using questionnaires (GPAQ, WHOQoL-BREF) in this study. Descriptive data were presented as means and standard deviations (SD) for continuous variables and as percentages for categorical variables. Multivariate linear regression analysis was conducted. The significance level was set at p ≤ 0.05. Results: Overall, 250 participants were recruited, the mean age of the study population (n = 243) was 70.2 (SD 7.1) years. The results clearly showed that the Hungarian participants aged over 50 years were more likely to do PA if they had university degree and lower age (p ≤ 0.001) and used more active transportation (p = 0.035) if they had low education. The results of WHOQoL-BREF showed that the Hungarian individuals have better QoL if they have university degree (p ≤ 0.001) and lower age (p ≤ 0.001). Using multivariate linear regression analysis to examine the effect of PA patterns on QoL adjusted for demographic variables (age, education, BMI, place of living), the result showed significant correlation between WHOQoL-BREF dimensions and GPAQ (p ≤ 0.001). Conclusion: Higher amount of PA among aging population can result in better QoL in all dimensions.

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“…The detailed description of the features of the device has been reported elsewhere. 13 In both studies, the devices were initialised to record GPS data at every 1 s and accelerometer data at an 80 Hz sampling rate. The raw GPS and accelerometer data were extracted from SenseDoc V.2.0 with SenseAnalytics (V.1.9 and V.1.10) before being aggregated into counts at 1-min epochs.…”

Section: Methodsmentioning

confidence: 99%

“…Previous studies have shown that the physical activity of older adults often takes place on roads, 11 in areas where the density of shops and restaurants is high, 12 and during travel. 13 Prior findings suggest that most of the adults' moderate-to-vigorous physical activity (MVPA) was accumulated at home and in the workplace, but the highest MVPA ratios in relation to total time spent at a location were obtained at sport facilities and during travel. 14 To the best of our knowledge, no previous study has focused on different levels of activity intensity, including sedentary time, of ageing workers' and recent retirees while also using information about the type of day and the context of the activity behaviour.…”

Section: Open Accessmentioning

confidence: 99%

Contexts of sedentary time and physical activity among ageing workers and recent retirees: cross-sectional GPS and accelerometer study

et al. 2021

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ObjectivesWe examined sedentary time and physical activity in different contexts among ageing workers, between their workdays and days off, and recent retirees, between their weekdays and weekend days.DesignCross-sectional study.SettingFinnish Retirement and Aging study and Enhancing physical activity and healthy ageing among recent retirees—Randomised controlled in-home physical activity trial.Participants137 workers (544 measurement days) and 53 retirees (323 days), who provided data for at least 1 workday/weekday and 1 day off/weekend day.Primary and secondary outcome measuresPhysical activity behaviour was measured with a combined Global Positioning System and accelerometer device (SenseDoc V.2.0), providing information on sedentary time, light physical activity and moderate-to-vigorous physical activity (MVPA) by locations (home or non-home) and trips (active travel, ie, speed <20 km/hour and passive travel, ie, speed ≥20 km/hour).ResultsWorkers accumulated more sedentary time and physical activity at non-home locations than at home on workdays, while the opposite was confirmed for days off (p<0.01). Workers accrued more MVPA on days off than on workdays (34 vs 28 min, p<0.05), of which 9 min on workdays and 14 min on days off was accrued during active travel. Retirees’ physical activity behaviour did not differ between weekdays and weekend days (p>0.05). Regardless of the day, retirees accumulated 33 min of daily MVPA, of which 14 min was accrued during active travel.ConclusionsWorkers accumulated more MVPA on days off than on workdays, and their activity behaviour varied between workdays and days off at different locations. Our results showed that a large proportion of the MVPA was accumulated during travel at slower speeds, which suggests that active travel could be a feasible way to increase MVPA among older adults.Trial registration numberNCT03320746.

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Is older adults’ physical activity during transport compensated during other activities? Comparing 4 study cohorts using GPS and accelerometer data

Cited by 20 publications

References 31 publications

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research

Association with subjective measured physical activity (GPAQ) and quality of life (WHOQoL-BREF) of ageing adults in Hungary, a cross-sectional study

Contexts of sedentary time and physical activity among ageing workers and recent retirees: cross-sectional GPS and accelerometer study

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