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Exploring patterns of accelerometry-assessed physical activity in elderly people.

Ortlieb S, Dias A, Gorzelniak L, Nowak D, Karrasch S, Peters A, Kuhn KA, Horsch A, Schulz H, KORA Study Gro - Int J Behav Nutr Phys Act (2014)

Bottom Line: Elderly people obtain significant health benefits from physical activity (PA), but the role of activity patterns has scarcely been researched.Subjects were divided into three groups by activity and the groups were compared.In rarely active people (often with reduced FEC, worse lung function, and diagnosis of multimorbidity or disability), longer periods of time in light PA may be sufficient to increase the overall level of activity.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. schulz@helmholtz-muenchen.de.

ABSTRACT

Background: Elderly people obtain significant health benefits from physical activity (PA), but the role of activity patterns has scarcely been researched. The present study aims to describe the patterns of PA among different intensities of activity in elderly people. We assess how patterns differ between more and less active groups ('rare', 'average', and 'frequent'), and explore whether and how various PA parameters are associated with functional exercise capacity (FEC).

Methods: PA was measured in 168 subjects (78 males; 65-89 years of age), using a triaxial GT3X accelerometer for ten consecutive days. Subjects were divided into three groups by activity and the groups were compared. A multiple linear regression model was used to predict FEC.

Results: Participants greater than or equal to 80 years are most prone to being sedentary for long periods, while women and the obese are the groups most likely to spend insufficient time in moderate to vigorous PA (MVPA). Rarely active elderly people had a decreased proportion of long bouts of MVPA and light PA and of short bouts in sedentary behavior than frequently active subjects did (p<0.001). As predictors of FEC, younger age, lower BMI, male sex, better lung function, absence of multimorbidity, longer times and longer bouts of MVPA emerged as significant parameters (r(2)=0.54). Patterns of MVPA explained most of the variance.

Conclusions: PA patterns provide information beyond reports of activity alone. MVPA in elderly people may be increased by increasing the proportion of long bouts, in order to increase FEC as well as average PA. However, health conditions may limit PA. In rarely active people (often with reduced FEC, worse lung function, and diagnosis of multimorbidity or disability), longer periods of time in light PA may be sufficient to increase the overall level of activity.

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Related in: MedlinePlus

Structure of physical activity variables. PA = physical activity; G = GINI-Index; high G = mainly few long bouts are responsible for the activity pattern; low G = mainly short bouts of similar length contribute to the activity pattern.
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Figure 1: Structure of physical activity variables. PA = physical activity; G = GINI-Index; high G = mainly few long bouts are responsible for the activity pattern; low G = mainly short bouts of similar length contribute to the activity pattern.

Mentions: Several variables were obtained from accelerometer data (uniaxial, 60-second epochs) to represent the characteristics of PA. Figure 1 presents an overview of the most important PA variables concerning this analysis. Parameters used in this study were:


Exploring patterns of accelerometry-assessed physical activity in elderly people.

Ortlieb S, Dias A, Gorzelniak L, Nowak D, Karrasch S, Peters A, Kuhn KA, Horsch A, Schulz H, KORA Study Gro - Int J Behav Nutr Phys Act (2014)

Structure of physical activity variables. PA = physical activity; G = GINI-Index; high G = mainly few long bouts are responsible for the activity pattern; low G = mainly short bouts of similar length contribute to the activity pattern.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4016218&req=5

Figure 1: Structure of physical activity variables. PA = physical activity; G = GINI-Index; high G = mainly few long bouts are responsible for the activity pattern; low G = mainly short bouts of similar length contribute to the activity pattern.
Mentions: Several variables were obtained from accelerometer data (uniaxial, 60-second epochs) to represent the characteristics of PA. Figure 1 presents an overview of the most important PA variables concerning this analysis. Parameters used in this study were:

Bottom Line: Elderly people obtain significant health benefits from physical activity (PA), but the role of activity patterns has scarcely been researched.Subjects were divided into three groups by activity and the groups were compared.In rarely active people (often with reduced FEC, worse lung function, and diagnosis of multimorbidity or disability), longer periods of time in light PA may be sufficient to increase the overall level of activity.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. schulz@helmholtz-muenchen.de.

ABSTRACT

Background: Elderly people obtain significant health benefits from physical activity (PA), but the role of activity patterns has scarcely been researched. The present study aims to describe the patterns of PA among different intensities of activity in elderly people. We assess how patterns differ between more and less active groups ('rare', 'average', and 'frequent'), and explore whether and how various PA parameters are associated with functional exercise capacity (FEC).

Methods: PA was measured in 168 subjects (78 males; 65-89 years of age), using a triaxial GT3X accelerometer for ten consecutive days. Subjects were divided into three groups by activity and the groups were compared. A multiple linear regression model was used to predict FEC.

Results: Participants greater than or equal to 80 years are most prone to being sedentary for long periods, while women and the obese are the groups most likely to spend insufficient time in moderate to vigorous PA (MVPA). Rarely active elderly people had a decreased proportion of long bouts of MVPA and light PA and of short bouts in sedentary behavior than frequently active subjects did (p<0.001). As predictors of FEC, younger age, lower BMI, male sex, better lung function, absence of multimorbidity, longer times and longer bouts of MVPA emerged as significant parameters (r(2)=0.54). Patterns of MVPA explained most of the variance.

Conclusions: PA patterns provide information beyond reports of activity alone. MVPA in elderly people may be increased by increasing the proportion of long bouts, in order to increase FEC as well as average PA. However, health conditions may limit PA. In rarely active people (often with reduced FEC, worse lung function, and diagnosis of multimorbidity or disability), longer periods of time in light PA may be sufficient to increase the overall level of activity.

Show MeSH
Related in: MedlinePlus