Background: Despite the existence of physical activity policies across many countries, insufficient physical activity remains a major global public health problem. Physical inactivity is an emergent feature of complex systems; it results from a wide range of factors at multiple levels that interact to influence behavior. Traditional approaches to public policy often fail within complex systems, largely due to unpredictability in how the system will respond. Adaptive policies, which are designed to allow for uncertainty about future system behavior and to change over time, may offer a promising solution. In this paper, we introduce the concept of adaptive policies and illustrate how this innovative approach to policy making may be beneficial for reducing physical inactivity. Design: Drawing on existing literature and guiding principles for policy making, we provide 3 examples to illustrate how the concept of adaptive policies can be applied to address physical inactivity. Discussion: The examples illustrate how changes to the way policies and interventions are developed, implemented, and evaluated could help to overcome some of the limitations in existing practices. A key challenge will be engaging policymakers to take a broader perspective of the physical activity system, develop policies that are designed to be adaptable across a range of different future scenarios, and embrace uncertainty and long-term adaptability. Conclusion: Adaptive policies may support decision makers globally to achieve the widespread and sustained changes necessary to increase population levels of physical activity.
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A Conceptual Primer on the Potential of Adaptive Policies to Reduce Physical Inactivity
Karen Milton, Harry Rutter, Harriet Koorts, and Leandro Garcia
The Association Between the Type, Context, and Levels of Physical Activity Amongst Adolescents
Harriet Koorts, Calum Mattocks, Andy R. Ness, Kevin Deere, Steven N. Blair, Russell R. Pate, and Chris Riddoch
Background:
Little is known about how the type and context of physical activity behaviors varies among adolescents with differing activity levels. The aim of this study was to assess differences in the type and context of physical activity behaviors in adolescents by level of objectively measured physical activity.
Methods:
Cross-sectional analysis of 2728 adolescents (1299 males, 1429 females) participating in the Avon Longitudinal Study of Parents and Children (ALSPAC). The mean (SD) age was 13.8 (+0.1) years. Physical activity was measured using an Actigraph over 7 days. Adolescents were categorized into tertiles of activity (less, moderately, highly active) using counts/min and min/d of moderate-to-vigorous activity (MVPA). Activity type was reported using the Previous Day Physical Activity Recall (PDPAR). Differences in the type and context of activity by activity level were analyzed using Chi squared.
Results:
Highly active boys reported more job, outside, and sports activities on school days (P < .05), and more sports activities on nonschool days (P < .05). Highly active girls reported more outside activities on school days (P < .05).
Conclusions:
Identifying the type and context of physical activity behaviors associated with more active adolescents, can help inform policy and physical activity interventions aimed at increasing activity levels in adolescents.
