Costs and barriers associated with a behavior have been recognized as important influences on that behavior since theories about how people make decisions began to proliferate in the 1950s (Janis and Mann 1977). Some barriers to physical activity differ among children and youths, middle-aged people, and older adults and between women and men (Godin et al. 1994). For example, pregnancy and early child rearing can present unique barriers to physical activity for mothers. Also, health conditions that limit mobility increase with age. Nonetheless, not enough is known about the roles of costs and barriers in determining physical activity. Most barriers that are known can be categorized as personal factors, environmental factors, social factors, or features of physical activity (Dishman and Sallis 1994).
The descriptive epidemiology of physical activity in the United States presented in chapter 3 illustrates that racial and ethnic minorities, people who have less formal education or low-income jobs, and people who live in rural areas are least physically active during their leisure time. The highest prevalence of physical inactivity is found in the southeastern region of the United States, which is heavily rural. Generally, participation in moderate-intensity activity is similar for males and females, but the rate of participation in vigorous physical activity is lower among females (U.S. Department of Health and Human Services 2000b; Centers for Disease Control and Prevention [CDC] 2010a).
Several personal factors are targets of interventions to increase physical activity because they are potential mediators of people’s behavioral choices regarding physical activity. Key personal factors are listed in table 17.2. These include people’s beliefs about the outcomes of being physically active or inactive (Steinhardt and Dishman 1989), the values they place on those outcomes (Godin and Shephard 1990) compared with other behaviors, satisfaction with their current status and physical activity goals (Dzewaltowski 1994), self-efficacy (i.e., confidence) about being physically active (McAuley and Blissmer 2000) or their ability to change their current level of physical activity (Sallis et al. 1988), behavioral intentions about being active (Godin 1994), and enjoyment of physical activity (Kendzierski and DeCarlo 1991; Motl et al. 2001), among many other factors.
Other personal attributes may be related to levels of physical activity but are not changeable (e.g., age and sex). Nonetheless, such attributes are important to identify and consider when designing physical activity programs or behavioral interventions because they may moderate the effects of interventions to increase physical activity. They can serve as sentinel markers of people who have high risk for being sedentary or who may need special interventions. The personal characteristics that have been considered in determinants research have been organized into demographic factors and social cognitive factors.
Occupation, ethnicity, smoking, education, income, age, and obesity are examples of personal attributes that can present barriers to physical activity or are signals of underlying habits or circumstances that reinforce sedentary living. However, their associations with physical activity can be complex and are still poorly understood.
Hourly workers in low-exertion blue-collar occupations are among the least-active Americans in their leisure time and have high risk of dropping out of a rehabilitative exercise program (Oldridge et al. 1983). In one study, eight years after graduation from high school, people who held blue-collar jobs or were unemployed had lower cardiorespiratory fitness than classmates who became civil servants, white-collar workers, or students, even though the two groups had similar fitness levels at the end of high school (Andersen 1996). Many blue-collar or hourly workers may have the attitude that their job requires enough physical activity for health and fitness, but with the use of technology in today’s industry, most workers do not expend much energy compared with workers 50 years ago. Nonetheless, physical activity on the job still contributes to overall physical activity. For example, nearly half of 1400 girls in 12th grade from 22 high schools in South Carolina said they had a job and worked nearly 5 h per day outside of school (Dowda et al. 2007b). Nearly one-third of the employed girls’ total physical activity occurred while they were at work. Otherwise, the girls with jobs were 20% less active during their leisure time than girls without jobs.
A recent review of 62 studies from 16 nations concluded that people in blue-collar occupations reported higher overall physical activity but lower leisure-time physical activity than white-collar professionals. People in occupations requiring long work hours (more than 45-50 h) and low physical activity on the job appeared to be at high risk for overall inactivity (Kirk and Rhodes 2011). However, more than 80% of the studies used a cross-sectional design (which fails to account for changing work demands), often failed to consider that many blue-collar occupations no longer require physical activity on the job, or didn’t adjust for aspects of socioeconomic status (SES) other than job status that can be more influential on leisure-time physical activity (e.g., social networks or dependence on public transport). Thus, the direct and indirect influences of occupation and occupational physical activity remain unclear (Hillsdon 2011).
A longitudinal analysis of the population-based Health and Retirement Study (1996-2002) in the United States found that participation in either work-related or leisure-time physical activity decreased with retirement from a physically demanding job but increased with retirement from a sedentary job (Chung et al. 2009). Lack of wealth made the negative impact of retirement on physical activity worse, whereas wealthy people were more likely to increase their physical activity after retirement.
Physical activity tends to decline with advancing age (Caspersen, Pereira, and Curran 2000), especially when people have age-related disabilities, but age does not necessarily predispose an individual to lower activity. As we just saw, factors associated with a person’s job (e.g., conflicts with leisure time or a false perception of adequate physical activity at work) or disposable income (e.g., leisure physical activity may be a low-priority expense) that created barriers to exercise during middle age may diminish during retirement.
Studies have also examined personal determinants of physical activity in younger age groups. A review of 108 studies published between 1970 and 1999 examined determinants of physical activity in children (ages 3-12) and adolescents (ages 13-18; Sallis, Prochaska, and Taylor 2000). Among children, negative associations with physical activity were found for female sex, previous physical inactivity, lack of access to programs or facilities, and time spent indoors. Some of the variables negatively associated with physical activity in adolescents were female sex, ethnicities other than white European, nonparticipation in community sports, being sedentary after school and on weekends, sibling’s nonparticipation in physical activity, previous physical inactivity, lack of parents’ support or support from significant others, and lack of opportunities to exercise or access to facilities or programs.
Excessive body mass can make activities that require weight bearing physically harder than for people of normal weight (Wilfley and Brownell 1994) and contributes to disabilities that can limit physical activity. Also, a history of bad experiences with physical activity, including embarrassment, can contribute to bad attitudes toward physical activity, especially exercise classes with participants of normal weight. An obese person may be less confident about exercising successfully. Indeed, the high failure rate of maintaining weight loss after a diet among people who are obese may lead to lower confidence about staying with an exercise program too. The typical obese person regains one-third of an average 22-lb (10 kg) weight loss within the year after a diet, with all the weight regained within three to five years (Foreyt and Goodrick 1993, 1994).
Personality is weakly associated with physical activity (Rhodes and Smith 2006), but it plausibly could influence spontaneous physical activity or moderate and help explain gene–environment influences on exercise behavior. Psychological factors other than personality can help explain why physical activity varies even among people whose age, education, income, social circumstance, and other demographic factors are very similar. In other words, psychological attributes are important for explaining why some people are active despite circumstances that predict they would be sedentary and why others are sedentary even though they have many opportunities and resources available to them that support physical activity. To put this another way, there are senior citizens who are active despite their age, high school dropouts who are active despite their lack of education, and smokers who exercise. Social and physical environments operating at the levels of families, schools, places of employment, and neighborhoods, all located within communities, can modify how psychological influences on physical activity are formed.
Social Cognitive Determinants of Physical Activity
Social cognitive factors are psychological variables that are transmitted to people from society by learning and reinforcement history. Attitudes toward exercising and to a lesser extent social norms about exercise influence intention to exercise, but intentions are often fleeting, influenced by changing priorities and personality factors such as willpower or self-motivation. The intention to exercise can also be influenced by actual (e.g., available leisure time or access to facilities) and perceived personal control over the ability to exercise, especially self-efficacy.