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Factors associated with active commuting to work among women a

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Melissa Bopp Ph.D. , Stephanie Child MPH & Matthew Campbell B.S.

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Department of Kinesiology , The Pennsylvania State University , University Park , PA , 16802 b

Department of Health Promotion, Education and Behavior , University of South Carolina , Columbia , SC , 29209 Accepted author version posted online: 10 Feb 2014.Published online: 10 Feb 2014.

To cite this article: Women & Health (2014): Factors associated with active commuting to work among women, Women & Health To link to this article: http://dx.doi.org/10.1080/03630242.2014.883663

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ACCEPTED MANUSCRIPT RUNNING HEAD: Active commuting among women Factors associated with active commuting to work among women Melissa Bopp, Ph.D.,1 Stephanie Child, MPH2 & Matthew Campbell, B.S.1 1

Department of Kinesiology, The Pennsylvania State University, University Park, PA 16802

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Department of Health Promotion, Education and Behavior, University of South Carolina, Columbia, SC 29209 Melissa Bopp (Contact author) 266 Recreation Building Pennsylvania State University University Park, PA, 16802 [email protected] (814) 863-3467 Number of words: 3647 Number of tables: 2 Number of figures: 1 Abstract Active commuting (AC), walking and biking to work, has notable health benefits though rates of AC remain low among women. This study used a social-ecological framework to examine the factors associated with AC among women. Methods: A convenience sample of employed, working women (n=709) completed an online survey about their mode of travel to work. Individual, interpersonal, institutional, community and environmental influences were assessed. Basic descriptive statistics and frequencies described the sample. Simple logistic regression models examined associations with the independent variables with AC participation and multiple

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ACCEPTED MANUSCRIPT logistic regression analysis determined the relative influence of social ecological factors on AC participation. Results: The sample was primarily middle-aged (44.09±11.38 years) and NonHispanic White (92%). Univariate analyses revealed several individual, interpersonal, institutional, community and environmental factors significantly associated with AC. The multivariable logistic regression analysis results indicated that significant factors associated with


AC included number of children, income, perceived behavioral control, coworker AC, coworker AC normative beliefs , employer and community supports, for AC, and traffic. The results of this study contribute to the limited body of knowledge on AC participation for women and may help to inform gender-tailored interventions to enhance AC behavior and improve health. Keywords: physical activity, behavior, social support

Introduction Physical inactivity is the second leading modifiable risk factor for morbidity and mortality, following smoking, among Western countries (Physical Activity Guidelines Advisory Committee 2008; Lee et al. 2012). With less than half of the American population engaging in the recommended levels of physical activity (PA)(Bauman et al. 2009), knowledge about the correlates of physical activity remains a major public health priority for disease prevention (Bauman et al. 2012; Kohl et al. 2012). Data suggest that physical inactivity may be due in part to physical and social environmental influences that hinder, or at least are not conducive to, PA (Sallis et al. 2012; Addy et al. 2004; Saelens et al. 2003). This may include a lack of physical features, such as sidewalks, that support leisure time and commuting activities, as well as social


ACCEPTED MANUSCRIPT norms that impede individuals from incorporating exercise into their daily routines. These environmental factors, combined with demographics factors such as age, sex or race/ethnicity provide some indication for which population groups are at risk for inactivity. Active commuting (AC), the act of walking or biking to work, has begun to receive considerable


attention in recent years as researchers highlight its potential for increasing population level physical activity and preventing chronic disease morbidity and mortality (Shephard 2008; Vuori, Oja, and Paronen 1994; Gordon-Larsen et al. 2009; Hamer and Chida 2008; Lindstrom 2008; Andersen et al. 2000). Public health initiatives such as Complete Streets (Smart Growth America 2013) and Safe Routes to School (National Center for Safe Routes to School 2013) that have included the installment of sidewalks, bike lanes, and other active transportation infrastructure have resulted in increased capacity for active commuting. These upstream efforts represent a paradigm shift in public health research and practice, and highlight how health behaviors are now often viewed as the result of several influences operating at multiple levels to produce health outcomes. This socio-ecological perspective posits that physical activity behaviors, such as active commuting, are influenced by an array of structural and social elements that operate at intrapersonal, institutional, community, policy, and environmental levels and has been applied to previous studies with active commuting (Sallis et al. 2006; McLeroy et al. 1988; Sallis, Owen, and Fisher 2008; Bopp, Kaczynski, and Campbell 2013). As such, studies have increasingly examined multiple levels of an individual’s environment that are thought to be associated with commuting.


ACCEPTED MANUSCRIPT At the broadest levels, AC may be influenced by community and environmental attributes, such as the design, aesthetics and available features of a neighborhood (Craig et al. 2002). For example, data have suggested that the presence of traffic, enjoyable scenery, and sidewalks are all positively associated with AC rates, even when controlling for personal factors, such as age and self-efficacy (Troped et al. 2003). Thus, elements of the built environment can influence or


hinder active commuting independently of personal factors. Beyond the built environment, previous research has suggested that positive social environments, such as social support from family, friends, and co-workers, as well as supportive policies within communities and the workplace also contribute to physical activity participation. For instance, one study reported that individuals with low perceived social support for activity among family, friends, and in the workplace were twice as likely to be sedentary than individuals whose perceived social support from these sources was higher (Stahl et al. 2001). At an individual level, another study found that individuals with a positive attitude, high self-efficacy, intentions to be physically active, and high levels of social support were more likely to engage in AC (WendelVos et al. 2004). Thus, social influences may be just as beneficial, and perhaps necessary, to AC as a conducive physical environment. To date, much of the literature examining the factors associated with AC and documenting the benefits of AC has focused on the general adult population, with a large number of studies examining children’s active commuting to school. Understanding these influences is an important public health goal, due the potential of AC to improve population health (Shepard, 2008). A growing amount of data has linked AC with increases in physical activity and overall


ACCEPTED MANUSCRIPT health outcomes (Shephard 2008; Vuori, Oja, and Paronen 1994; Gordon-Larsen et al. 2009; Hamer and Chida 2008; Lindstrom 2008; Andersen et al. 2000). However, few studies have examined AC among women, who may actually be more likely to benefit from the increased rates of physical activity associated with AC. Indeed, a meta-analysis on the health benefits of AC, including increased cardiovascular health, showed a more robust protective effect among


women than men (Hamer and Chida 2008). Another study showed that 15 minutes or more per day spent actively commuting was associated with reduced risk for cardiovascular disease and all-cause mortality in women, but not in men (Barengo et al. 2004). While AC appears to provide increased health benefits for women, some research has suggested specific barriers and challenges to AC that are unique to adult women. It is estimated that the number of bicycle trips currently made by men is twice that of women (Edmond, Tang, and Handy 2009) and that women may be differentially affected by factors associated with AC. For example, a previous study found that workplace environment features (e.g., availability of bike racks, locker rooms) were significantly associated with AC among women but not men (Kaczynski, Bopp, and Wittman 2010). Given that females tend to be less active than males overall, and that increasing AC may be a viable mechanism for increasing population-level PA, exploring the facilitators and barriers that are unique to women may be particularly effective in improving their activity levels and health. Given the importance of identifying strategies for increasing walking and biking to work among females specifically, the purpose of this study was to use the social ecological model (McLeroy et al. 1988) to examine the individual, interpersonal, institutional, community and environmental factors associated with AC participation among women.


ACCEPTED MANUSCRIPT Methods This study used a cross-sectional research design with an online survey delivered using the Qualtrics software program (Provo, UT) from June-December 2011. This study was approved by the Institutional Review Board at Pennsylvania State University. Participants were presented Downloaded by [Pennsylvania State University] at 11:05 10 February 2014

with a consent statement upon entering the online survey and consented to participation by advancing to the survey after reading the statement.

Participants Adult women (aged 18 years or older) who were employed full- or part-time outside of the home and self-reported being physically able to walk or bike were eligible to take part in the survey. Individuals who did not meet the eligibility criteria were directed to the end of the survey. Details of the entire sample (including men), are outlined elsewhere (Bopp, Kaczynski, and Campbell 2013). Recruitment took place primarily in the mid-Atlantic region of the US (PA, OH, WV, MD, NJ, DE). These states were selected due to their proximity to the institution where the research was conducted to enhance likelihood of study participation. The primary recruitment strategy involved visiting the websites of large employers (e.g., K-12 school districts, local/county government, private businesses, universities/colleges) in medium to large cities in the region for employee email addresses, then contacting the employees directly via email. When individual employee email addresses were not available, employers were contacted (n=142) and asked to


ACCEPTED MANUSCRIPT distribute an electronic invitation to employees to participate in the survey via listserv, enewsletter, or mass email to their employees and to track the number of employees who received the invitation. Of those employers contacted, two employers refused to send out an email invitation, 84 did not respond, and 56 (39.4%) sent out a recruitment invitation via internal methods (i.e. listserv) (Figure 1). The initial email invitation invited people to take part in a


“Commuting survey” in an attempt to limit a volunteer bias of people who may have been more interested in active commuting methods.

Instruments A number of the measures (demographic, medical, self-efficacy, institutional, community and environmental) that were developed specifically for the current study, and their psychometric properties were not assessed. Some previously validated measures were used as noted below.

Individual level Commuting patterns: Participants reported the number of times per week that they walked, biked, drove, and took public transportation to and from work. The number of individual trips via walking and biking was summed for number of active commuting trips/week. Participants were then dichotomized as participating in AC (at least one AC trip per week) or no AC for the dependent variable. Demographics and medical: Participants reported their age, race/ethnic group, marital status, number of children, sex, and number of cars in the household. Participants indicated (yes/no)


ACCEPTED MANUSCRIPT from a list of chronic diseases they had had and reported their height and weight for body mass index (BMI) calculations. Respondents rated their perceived health status with a 5-point Likert scale from 1(poor) to 5(excellent). Self-efficacy: Women’s confidence with their cycling skills in urban areas was assessed with one


item using a 4-point Likert scale (1=not at all confident to 4=very confident). AC behavioral beliefs: Respondents indicated their agreement using a 7-point Likert scale (1=completely disagree to 7=completely agree) with 13 statements about AC. Eight were related to AC and their physical or mental health (e.g., AC helps me control my weight, can help me to relieve stress) and five were related to other AC benefits (e.g., AC is good for the environment, helps me to save money). A total score was computed for all 13 items (range 13-91). This measure, based on a previously-tested scale (Blue, Marrero, and Black 2008) demonstrated excellent reliability in the present study (Cronbach’s α=0.91). Perceived behavioral control for AC: Participants used a 7-point Likert scale (1=completely disagree to 7=completely agree) to indicate their agreement with six statements about why AC is difficult (e.g., AC is difficult because I am not committed to it; because I am too tired), which was adapted from a previous measure (Conn, et al., 2003). A total score was computed for the six items (range 7-42), and the scale showed good reliability (Cronbach’s α=0.84).


ACCEPTED MANUSCRIPT Interpersonal Coworker AC participation and AC normative beliefs: Participants responded with a Likert scale (1=strongly disagree to 5=strongly agree) to a question about their coworkers’ AC behavior: “Most of my coworkers walk or bike to/from work.” Coworker normative beliefs were assessed Downloaded by [Pennsylvania State University] at 11:05 10 February 2014

with a 5-point Likert scale to measure an individuals’ level of agreement with four statements about their coworkers influence on their mode of travel to work which were adapted from other scales (Blue, Marrero, and Black 2008). Items included: “My coworkers and I discuss issues related to walking and biking to work”, “I value what my coworkers think about the way I travel to/from work”, “I have an opinion on the way my coworkers travel to/from work” and “My coworkers influences my choice on how I travel to/from work.” The scores were summed (range 4-20) to creative a coworker normative belief score and had good reliability (Cronbach’s α=0.76). Spouse AC participation and normative beliefs (for married/partnered respondents only): Respondents reported the number of times/week their spouse walked or biked to/from work. Spouse normative beliefs were assessed using a scale with similar items as coworker normative beliefs. The scale had good reliability (Cronbach’s α=0.83).

Institutional Worksite related: Women reported their employer’s size and number of employer supports for AC (yes/no) which included: incentives for AC, flexible work hours, bike parking, bike storage


ACCEPTED MANUSCRIPT policies, locker rooms, flexible dress code. Participants indicated how much they perceived their employer supported AC using a 5-point Likert scale (1=strongly disagree to 5= strongly agree). Perceived parking problems at work were assessed with three items (lack of availability, high cost, and difficulty of parking), which were summed (greater score= more parking problems).


Community Community factors: Participants reported (yes/no) on the availability of three supports for bicyclists in their community (bike racks on buses, covered bike parking, “share the road” signs), which were summed (range 0-3). Women indicated their agreement with five statements about perceived support for walking and biking in their community with a 5-point Likert scale (1=strongly disagree to 5= strongly agree). Items were summed to create a perceived environmental supports score (range 5-25) and included: town/city support for pedestrian or bicyclists issues, seeing others in their community walking/biking, and maintenance of sidewalks or bike lanes. Women were asked to rate their community’s perceived pedestrian and bike friendliness from 1 (not pedestrian/bicycle friendly at all) to 5 (very pedestrian/bicycle friendly). Lastly, participants also indicated how long it would take them to walk or bike to work, dichotomized as ≤ 20 minutes and greater than 20 minutes.

Environmental Barriers: Perceived environmental barriers were examined, with women rating the extent to which environmental features presented a barrier to walking or biking to work (1=strongly


ACCEPTED MANUSCRIPT disagree to 5=strongly agree). The seven items included a lack of on-street bike lanes, lack of off-street walking/biking paths, lack of sidewalks, speed/volume of traffic along route, perceived crime along route, difficult terrain, and bad weather.


Data Analysis Basic descriptive statistics and frequencies were used to describe the sample. Simple logistic regression models were used to examine associations of the individual, interpersonal, institutional, community and environmental variables with participation in AC. The significantly (p