5.1: Why Predict Physical Activityand Sedentary Behavior?

Researchers want to predict physical activity and sedentary behavior to better explain what makes people behave in ways that would improve their quality of life. This health promotion goal is a dominant pursuit in physical activity research and for good reason. There is well established scientific evidence that physical activity is associated with a wide range of health benefits (U.S. Department of Health and Human Services, 2018). Almost everyone can benefit their health from engaging in regular physical activity. Importantly, physical activity can be used as a preventative strategy to reduce the risk of chronic disease or therapeutic strategy to help individuals mitigate or reverse the detrimental effects of disease and disorders(Singh, 2002).

When viewing physical activity as a preventative strategy, getting enough physical activity can help prevent 6% to 10% of major non-communicable diseases and save millions of lives per year(Lee et al., 2012; U.S. Department of Health and Human Services, 2018). Physical activity is useful as both a primary and secondary preventative strategy for reducing the risk of cardiovascular disease, diabetes, specific cancers, obesity, hypertension, bone diseases, and depression (Warburton et al.,2006).As a therapeutic strategy, regular physical activity is also beneficial to help improve sleep and mood as well as reduce anxiety, depression, and stress (Sharma et al., 2006).

Physical activity is also beneficial for improving brain health and performance (Hillman et al., 2008). This has important implications for the academic performance of young people, the cognitive functioning of older adults, and helping special populations who experience challenges with cognitive functioning (Pontifex et al., 2014).

The health promotion, disease prevention, therapeutic benefits, and positive psychological effects of physical activity provide substantive justifications for the reason why predicting physical activity is important. Predicting sedentary behavior follows the same health promotion goal. Research shows that television viewing and screen time are associated with all-cause mortality, childhood obesity, increased blood pressure and total cholesterol, decrease self-esteem, social behavior problems, poorer physical fitness, and lower academic achievement (Rezende et al., 2014). Therefore, once researchers explain the predictors of physical activity and sedentary behavior, the next step is to design interventions targeting these factors in populations that would benefit from increasing physical activity and reducing sedentary behavior. Successful interventions can lead to higher-quality public health recommendations and policy changes to help improve quality of life.Ultimately, the goal is to increase population-level physical activity participation and reduce sedentary behavior.

5.1.1. Approaches to Predicting

Predicting physical activity and sedentary behavior relies on two approaches: explaining what factors cause people to behave and what factors are associated with behavior. The first approach often identifies these factors as determinants of physical activity and sedentary behavior. A useful place to start identifying what factors cause people to be physically active or sedentary is to start with a relevant theory and previous empirical evidence. A theory helps specify what factors lead to changes in behavior, how those factors are organized, and shows causal hypotheses between predictors and outcomes. A theory is useful when researchers are interested in designing interventions or making public health recommendations to increase physical activity or reduce sedentary time. The overarching goal with the explanation approach is to effectively explain how and why people behave.

The second approach tries to accurately as possible predict behavior and is not necessarily interested in cause and effect or theory to specify what factors lead to behavior. This approach often identifies these factors as correlates of physical activity and sedentary behavior. For example, a researcher may be interested in predicting sedentary behavior among high-school teenagers. This researcher may collect data on numerous factors that may be associated with sedentary behavior to try to accurately predict it. This approach may help identify what factors such as television viewing and individual characteristics are associated with sedentary behavior. From this perspective, television viewing is related to sedentary behavior,but one does not cause the other.This second approach is also useful for identifying more distally related or background factors beyond what is specified in a theory. The same researcher may also be interested in learning more about how watching television differs among different ethnicities and socioeconomic classes. For example, research shows that British Black 11–12-year-old students were more sedentary than their White peers (Brodersen et al.,2007).

5.1.2. What Counts as Physical Activity and Sedentary Behavior?

The concepts of physical activity and sedentary behavior are distinct. That is, sedentary behavior is different than not getting enough physical activity or being physically inactive. Physical activity is any bodily movement produced by the skeletal muscles that results in energy expenditure (Caspersen et al., 1985).Sedentary behavior is any waking behavior characterized by an energy expenditure ≤1.5 metabolic equivalents (METs), while in a sitting, reclining or lying posture (Tremblay et al., 2017). Over the past 30 years, researchers have mentioned physical activity more times than sedentary behavior (see Figure 5.1). One result of these publication trends is that researchers and health professionals know more about the health enhancing effects of physical activity than the detriments of sedentary behavior. This has led to more fine-tuned and specific public health recommendations for what counts as being physically active than for reducing sedentary behavior. Although the research on the predictors of sedentary behavior is rapidly increasing, predictors of physical activity dominate the extant literature base.

Figure 5.1: Number of Publications Containing “Physical Activity” vs. “Sedentary”

Note: The number of publications containing “physical activity” has outpaced the number of publications containing “sedentary” by an average of 21:1 over the past 30 years. Data from https://app.dimensions.ai.