Context of Physical Activity in a Representative Sample of Adults

Abstract

Purpose The establishment of formal physical activity (PA) guidelines has led to considerable interest in quantifying participation in moderate-to-vigorous PA (MVPA). However, evidence on the context of MVPA at the population level is scarce. The purpose of this study was to provide types, location and purpose information of MVPA in a representative sample of adults. Methods Data from a representative sample of 1,234 Iowa adults were included in this study. Each participant performed a telephone-administered 24-hour PA recall method recalling the previous 24-hour’s physical activities. Self-reported data from the recall instrument included time and types of reported activities across 5 distinct location and purpose codes. Reported activities were matched with corresponding metabolic equivalent (MET) scores from a reduced list of PA Compendium. MVPA was defined as any activities with assigned METs ≥ 3.0. Results Of the top 30 most frequently reported MVPAs, 16 were lifestyle activities involving walking in the definition, and only 4 can be regarded as traditional “exercises”. Occupational activities (41% for purpose and 40% for location) and household activities (37% for purpose and 39% for location) accounted for nearly 80% of the total reported MVPA time. Time allocations across the purpose and location codes considerably differed by socio-demographic indicators. Conclusion Lifestyle activities were more frequently reported than sports and/or recreational activities. Individuals with varying levels of socio-demographic indicators exhibited different patterns of use-of-time within the given day. A multi-domain approach is needed to better understand and increase MVPA in diverse populations of US adults.

The use of the behaviour change wheel in the development of ParticipACTION’s physical activity app

“…Furthermore, adults’ physical activity levels can be influenced by multiple social and environmental contextual variables depending on personal interests ( Burton et al, 2012 , Welk and Kim, 2015 ). Some of these variables include location (i.e., home, outdoors, at work, center-based), companions (i.e., alone or with a family member, coworkers, or friend), time of day (i.e., morning, afternoon, evening), structure (i.e., flexible or scheduled), and other aspects such as fun, music, and convenience ( Burton et al, 2012 , Lau and Faulkner, 2019 , Welk and Kim, 2015 ). Therefore, there is no ‘one model fits all’ approach and effective strategies to increase physical activity participation must be diverse in order to reflect people’s preferences ( Sallis et al, 2000 ).…”

Cross-sectional associations of neighbourhood socioeconomic disadvantage and greenness with accelerometer-measured leisure-time physical activity in a cohort of ageing workers

“…This was done because individuals with varying sociodemographic indicators may have different patterns of use-of-time. 47 We observed no such interactions (p values for interactions 0.14-0.40), thus results are reported for the total study population only. As an additional analysis, we ran models adjusted for BMI and number of chronic disease, where those with missing data for chronic disease were excluded.…”

Characterizing the context of sedentary lifestyles in a representative sample of adults: a cross-sectional study from the physical activity measurement study project

“…Data in the overall PAMS project were collected over a 2-year time span to capture the inherent variability in behavioral patterns across seasons. Additional detail on the overall study design, the sampling procedure and the data collection protocol is available [ 19 , 22 – 24 ].…”

“…Socio-demographic variables in the dataset included gender (female and male), age group (20–29 years, 30–39 years, 40–49 years, and 50–71 year), weight status defined by BMI (normal weight, overweight and obese), ethnicity (White, Black, and Other), education background (less than high school, some college/post high school, and college/graduate), and income level (less than $25,000, from $25,000 up to $75,000, and more than $75,000). Data from Trial 2 were not used in the analyses because results were highly similar to those from Trial 1 [ 19 , 23 ]. Data from the armband monitor were not reported in this study because it does not provide context information of SB.…”

“…Keys in these models are to better understand the nature and context of the underlying behaviors so that effective interventions can be developed. While considerable research has been performed to understand the context of PA [ 17 – 19 ] relatively little is known about the context of SB. This lack of evidence on the contextual profiles of SB is due, in large part, to the inabilities of traditional measurement tools to assess context of SB (and PA) [ 20 ].…”