SOCIAL MOVEMENTS AND HEALTH: THE BENEFITS OF BEING INVOLVED

Elizabeth A. Emley

A Thesis

Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of

MASTER OF ARTS

May 2017

Committee:

Dara Musher-Eizenman, Advisor

Abby Braden

Catherine Stein

SOCIAL MOVEMENTS AND HEALTH ii

ABSTRACT

Dara Musher-Eizenman, Advisor

Unhealthy lifestyle behaviors significantly contribute to poor health and obesity risk,

which in turn impact chronic illness outcomes. Thus, improving individual health behaviors

remains a vital target to improving overall well-being. A possible mechanism for improving health outcomes is to capitalize on the link between social movement involvement and overlapping health behaviors. Targeting social movement involvement may be a viable stealth

intervention for health outcomes, utilizing intrinsic motivators to improve health without an

explicit focus on changing health behavior. For the current study, two samples from the college

population and the general population were recruited to participate in an online survey, which

included measures of social movement involvement, social movement behaviors, and

questionnaires on health outcomes. Results revealed that social movement-related behaviors

mediated the relationship between social movement involvement and numerous health outcomes

among both samples, particularly fruit and vegetable consumption, fiber intake, whole grain

intake, and average daily MET minutes of physical activity in both samples. Additionally, no

movement was significantly related to greater health indicators compared to the others in either

sample. These findings suggest that behaviors associated with social movement involvement are

an important mechanism in promoting health among social movement members. This research

adds to existing literature on stealth interventions as a viable means of improving human health

and social movements as a potential form of stealth intervention. SOCIAL MOVEMENTS AND HEALTH iii

ACKNOWLEDGEMENTS I would like to thank my advisor, Dara Musher-Eizenman, for her invaluable support and her dedication to the development of this project. I would also like to thank my committee members Abby Braden and Cathy Stein for their continued support and guidance.

SOCIAL MOVEMENTS AND HEALTH iv

TABLE OF CONTENTS

Page

CHAPTER I. INTRODUCTION ...... 1

Current Interventions ...... 1

BMI ...... 3

Barriers ...... 4

Rationality ...... 5

Stealth Interventions ...... 5

Social Movements ...... 8

Individual Behaviors ...... 11

Research Questions ...... 11

CHAPTER II. METHOD ...... 14

Participants ...... 14

Procedures ...... 15

Measures ...... 15

Demographics ...... 15

Social Movement Assessment Scale ...... 15

Social Movement Inventory of Involvement Scale ...... 16

Individual behaviors Inventory ...... 17

Dietary Screener Questionnaire ...... 18

International Physical Activity Questionnaire ...... 19

RAND 36-Item Health Survey ...... 20

Diabetes Symptom Checklist ...... 21 SOCIAL MOVEMENTS AND HEALTH v

Method of Analysis ...... 22

CHAPTER III. RESULTS ...... 24

Preliminary Analyses ...... 24

Main Effect Analyses ...... 25

General Adults ...... 25

College Students ...... 26

Mediation Analyses ...... 27

General Adults ...... 27

College Students ...... 29

Exploratory Analyses ...... 29

CHAPTER IV. DISCUSSION...... 32

Primary Findings ...... 32

Unexpected Findings ...... 33

Comparing Social Movements ...... 35

Comparing Samples ...... 36

Demographic Findings ...... 38

Indicators of Health ...... 38

Unexplored Potential Mechanisms ...... 39

Limitations and Future Directions ...... 40

Conclusions ...... 43

REFERENCES ...... 45

APPENDIX A. MEASURES...... 57

APPENDIX B. HSRB FORM FOR ORIGINAL APPLICATION ...... 76 SOCIAL MOVEMENTS AND HEALTH vi

APPENDIX C. HSRB FORM FOR MODIFICATION REQUEST ...... 77

APPENDIX D. CONSENT FORM (ADULT SAMPLE ...... 78

APPENDIX E. CONSENT FORM (COLLEGE SAMPLE) ...... 79

APPENDIX F. TABLES ...... 80

APPENDIX G. FIGURES ...... 99

SOCIAL MOVEMENTS AND HEALTH 1

CHAPTER I. INTRODUCTION

Unhealthy lifestyle is one of the largest contributors to illness and disease.

Cardiovascular disease, the leading cause of death in the US, is strongly linked to poor diet,

inadequate physical activity, and obesity (CDC, 2015). Diabetes mellitus affects almost one in

every ten Americans (ADA, 2015), and Type 2 diabetes, accounting for approximately 90% of

diabetes cases, results in part from diet and physical activity deficiencies (WHO, n.d.-a).

According to the World Health Organization, in 2014, 39% of adults were considered

overweight (Body Mass Index ≥ 25) and 13% were obese (BMI ≥ 30) worldwide, a prevalence

that has more than doubled since 1980 (WHO, 2016). Elevated BMI as well as metabolic

markers that tend to accompany obesity (e.g., high abdominal adiposity and high blood pressure)

are leading risk factors for some of the deadliest preventable causes of death today:

cardiovascular disease, diabetes, stroke, and even some cancers (NHLBI, 2016; WHO, 2016).

Clearly, there is a vital need for the reduction of overweight and obesity as well as other

indicators of poor health.

Current Interventions

Although there are many types of obesity and overweight interventions and treatments,

existing programs have failed to produce the significant health improvements we need to tackle

this pandemic. Current behavioral interventions encourage at-risk individuals to change their

lifestyle (Cutler, 2004). For adults, such techniques include self-monitoring (e.g., food diaries), nutrition education, increasing physical activity, and other behavior modification efforts (Foster,

Makris, and Bailer, 2005).

A review of recent meta-analyses on lifestyle interventions and health outcomes yielded mixed results. While many interventions are successful in producing positive short-term SOCIAL MOVEMENTS AND HEALTH 2 outcomes, few have been able to sustain adequate long-term weight loss and changes in health behaviors unless they are highly interactive or individually tailored (Hartmann-Boyce, Jebb,

Fletcher, & Aveyard, 2015; Krebs, Prochaska, Rossi, 2010; Curioni & Lourenço, 2005).

Two large, longitudinal studies have examined the impact of lifestyle intervention on health outcomes among individuals with diabetes: the Look AHEAD study and the Finnish

Diabetes Prevention Study. Both included aspects of dietary and physical activity intervention

(Look AHEAD, 2006; Lindstrom et al., 2003). These studies have yielded interesting and relevant findings in the context of the current study.

In the Look AHEAD study, compared to the usual diabetes care group (Diabetes Support and Education; DSE), those in the intensive lifestyle intervention (ILI) group had better weight loss outcomes from years 1 through 4 among multiple measures of weight loss (Wadden, 2011).

However, after a large initial weight loss at year 1 among ILI subjects, a majority gained some of the weight back, resulting in only a 4.7% reduction in initial weight at year 4, an ecologically insignificant reduction considering the lengthy intervention. A similar pattern of results was found for other health indicators including level of fitness, systolic blood pressure (SBP), triglycerides, and low-density lipoproteins (LDL): each indicator significantly improved after year 1 in the ILI group, but all regressed towards original levels and some ended at a similar level as the DSE group at year 4 (Look AHEAD, 2010).

The Finnish Diabetes Prevention Study had similar results, as initial improvements in weight, waist circumference, calories consumed, and fiber in the lifestyle intervention group did not continue onward past year 1, although many did remain somewhat better than the comparison group at year 3 (Lindstrom et al., 2003). Taken together, these two studies provide evidence that lifestyle interventions are able to establish significant improvements with SOCIAL MOVEMENTS AND HEALTH 3

consistent intervention and support, but without continuation of that support, health outcomes are

not likely to be sustained in the long term, a more crucial outcome in health promotion.

BMI. Most obesity-related interventions use changes in BMI as the primary outcome

variable of interest. However, this focus has many pitfalls. Most notably, assessing an

intervention’s impact on weight requires longitudinal studies, which are both time and resource

consuming. Relatedly, studies that find reductions in weight are often short-term, skewing the

conclusions by ignoring the more relevant outcome of long-term weight loss (Janicke et al.,

2014; Zenzen & Kridli, 2009). Many studies do not include follow-up data and, therefore, cannot definitively claim success.

Another key flaw in utilizing weight to measure health is that other measures and biological markers exist that more appropriately reflect one’s health. A meta-analysis conducted by the Mayo clinic revealed that BMI cutoff values as an indicator of obesity were highly specific (i.e., resulted in true negatives), but across studies, BMI failed to identify half of the people with excess body fat percentage (Okorodudu et al., 2010). BMI does not take into account muscle mass versus adipose tissue, nor does it differentiate between types of fat, some of which have more harmful metabolic effects than others (i.e., abdominal fat; Lee, Huxley, Wildman, and

Woodwarn, 2008). Better health indicators include: dietary quality and physical activity, as low levels of these have major implications in chronic diseases (WHO, n.d.-b; WHO, n.d.-c; WHO, n.d.-d); waist-to-height ratio (WHtR) to identify abdominal obesity (Lee et al., 2008; Ashwell &

Hsieh, 2005); other metabolic syndrome risk factors such as high blood pressure, high

triglyceride levels, and insulin resistance (Kaur, 2013); quality of life (Döring, de Munter, &

Rasmussen, 2015; Jia & Lubetkin, 2005); and other factors that encourage a “heath-centered rather than weight-centered [approach, which] focuses on the whole person,” (Misner, 2003). SOCIAL MOVEMENTS AND HEALTH 4

All of these indicators as well as other indicators of health are not necessarily dependent on a person’s weight but still have major impacts on health. Moving away from a focus on weight and BMI and shifting to a health at every size (HAES) model will address the broader forces that support health, such as greater access to health care, and will encourage a more holistic approach to health (i.e., quality of life is just as crucial as the absence of physical and mental illness; Tylka et al., 2014).

A final issue with using BMI as the sole outcome criterion is weight stigma. Measuring weight and BMI in research may stigmatize study participants, and focusing on weight as an indicator of health may further perpetuate the idea that weight stigmatization is an effective public health tool in reducing obesity (Puhl & Heuer, 2010).

Barriers. A second concern with many of the current interventions that push for individual change in weight is that they fail to consider barriers to health behavior change. There are many situational constraints that interfere with a person’s ability to do what is recommended in health interventions. For example, deterrents to obtaining adequate physical activity include time constraints, poor state of health, and already overweight status (Korkiakangas et al., 2011).

In addition, healthy eating behavior is made difficult by established taste preferences, money constraints, and lack of convenience and availability (Lucan, Barg, & Long, 2010; Alaimo,

Packnett, Miles, & Kruger, 2006) as well as political barriers that impede people’s ability to make healthy decisions (e.g., urban street designs that inhibit one’s ability to walk, government subsidizing of fat and sugar production while fruit and vegetable prices remain high; Swinburn,

2008). With all of these barriers, it is likely that the short-term skills and knowledge learned in interventions are difficult to sustain over time. SOCIAL MOVEMENTS AND HEALTH 5

Rationality. A final concern with current behavior interventions is that attempts to improve health are often motivated by arguments for human rationality, with a majority of existing interventions assuming that humans will act rationally in their own best interest, conduct cost-benefit analyses for each behavioral choice they make, and will have the insight to focus on future benefits while ignoring the short-term rewards (Robinson, 2010). In reality, human decision-making and behavior are far from rational and are consistently influenced by our environment and cognitive biases. We are more narrowly focused on short-term, immediate gains and losses rather than making the more rational decision to hold out for long-term benefits and assets (Kahneman, 2003; Kanheman & Lovallo, 1993). In the case of dietary and physical health, our desire to eat something delicious but bad for us or put off a workout until another day overpowers our ability to think about how a decision will impact our future health.

Chandon and Wansink (2007) found that having knowledge of nutrition information did not lead people to choose healthier decisions and in fact allowed those individuals to indulge in more food with the impression that anything they touched was “healthy.” Similarly, a systematic review by Haack and Byker (2014) found no association between nutrition guideline knowledge and adherence. These studies reveal that educating people on healthy choices may not positively influence their actual behavior. Simply providing education and encouraging rational decision- making is not enough to help people make healthy lifestyle choices.

Stealth Interventions

Due to the limited success of existing obesity-focused interventions, some researchers have turned their attention to the potential of stealth interventions as a way to overcome several of the problems with traditional interventions. Stealth interventions are a viable option to solving some of the more prominent issues with current behavioral interventions. First, stealth SOCIAL MOVEMENTS AND HEALTH 6 interventions target multiple facets of health other than obesity and BMI. The goal of stealth interventions is to increase health without an explicit focus on changing health behavior. Thus, the field is wide open to assessing many indicators of health. Additionally, these types of interventions have the potential to avoid many common barriers to health behavior. Stealth interventions target values and behaviors associated with those values in order to improve health, so motivation to partake in health behaviors is more likely to be maintained despite barriers.

Finally, stealth interventions avoid issues with irrational thinking by shifting the focus from explicitly changing health behavior to finding other ways to vicariously improve health in a more positive, emotionally-charged way. Consistent with the notion of human irrationality, findings suggest that the number of lifestyle recommendations made within an intervention can negatively influence how likely a person is to adopt health behaviors (Wilson et al., 2015). In essence, the fewer recommendations made, the more likely participants are to adhere to them, indicating that less interventional push may in fact be more useful.

Stealth interventions are a hypothesized method for increasing health behaviors by targeting people’s existing intrinsic motivators while improving their health as a side effect.

Intrinsic motivation is any motivation that comes from internal drives or goals versus external rewards. When it comes to physical health, examples of intrinsic motivators could include a goal to achieve a higher quality of life or to feel better about oneself as opposed to a goal of looking good to others or weight loss in and of itself. For example, a study exploring middle-aged women’s goals for exercise showed that women participated less often in exercise activities when their goals were weight-loss related than when their goals were intrinsic in nature, such as improved well-being and stress-reduction (Segar, Eccles, & Richardson, 2008). If people are unable to always act rationally in their own interests and face a multitude of barriers that impair SOCIAL MOVEMENTS AND HEALTH 7

their ability to make healthier choices, perhaps using methods that focus on initiatives not

directly related to health could remedy some of those impairments. To be clear, stealth

interventions do not aim to hide or conceal the connection between a given motivator and health;

instead, they aim to target a new way of motivating people to engage in health behaviors without

an explicit goal or focus of changing behavior.

Although research in this field is sparse, a few studies have been conducted to date that investigated various stealth interventions as a means of improving health. Robinson has conducted multiple studies that have shown health behavior can be increased by reducing children’s television viewing (Robinson, 1999); raising students’ awareness of the negative aspects of media usage (Robinson & Borzekowski, 2006); increasing participation in an after- school dance program to reduce television viewing (Robinson et al., 2003; Robinson et al.,

2008); an after-school soccer team to reduce BMI (Weintraub et al., 2008); and conducting a food-related college course focusing on the environmental and social impacts of food versus health issues to produce more healthful diets (Hekler, Gardner, & Robinson, 2010).

Other stealth-related intervention studies have also shown promising results. A study on mindfulness found that individuals with a higher level of mindfulness also had higher levels of moderate and vigorous physical activity, exercise self-efficacy, fruit and vegetable intake, dietary self-efficacy, and lower levels of fat intake (Gilbert & Waltz, 2010). This suggests that

increasing mindfulness may be a stealth intervention for increasing health. A study on

caregivers’ use of positive behavior support (PBS) strategies in toddlerhood found that children

who received greater PBS with the Family Check-Up intervention had higher nutritional quality

of meals among other familial benefits (Smith, Montaño, Dishion, Shaw, & Wilson, 2014). It has also been hypothesized that policies to improve mental health (i.e., depression and anxiety SOCIAL MOVEMENTS AND HEALTH 8 disorders) are stealth interventions, as dietary health has recently been shown to be a risk factor for such mental disorders, and mental health as a target may be more salient and proximal to individuals than future health outcomes such as heart disease or diabetes (Jacka, Sacks, Berk, &

Allender, 2014). There is clear support for stealth interventions as a viable option to improve health outcomes and reduce obesity, potentially at a greater rate than current interventions.

Social Movements

Getting people more involved in their already valued social movements may prove to be an important intrinsic motivator for health behavior, and it is a plausible next step within the stealth intervention approach. In his foundational book on social movements, Heberle (1951) defined social movements as any collective attempt to “bring about fundamental changes in the social order,” typically organized in the form of committees, clubs, or formal organizations.

According to Heberle, a decision to join a social movement is more often motivated by emotional rather than rational reasons, exemplifying the potential in shifting away from the current theories of behavioral interventions towards a more affective, value-laden approach.

One’s life experiences and values are important catalysts for social movement involvement. As such, motivation to engage in social movement-related behaviors may be key at sustaining associated health behaviors. Joseph Gusfield’s (1981) chapter on social movements and social change explains that the ultimate goal of social movements is to initiate social change on a large scale. Gusfield goes on to discuss that a defining feature of social movements includes their system of generalized beliefs, which demand societal change. According to Gusfield, this can be contrasted with special interest groups and expressive protests alone, which do not develop explicit demands for a changed society. SOCIAL MOVEMENTS AND HEALTH 9

Robinson (2010) lists 13 key social movements that have overlapping values and behaviors with those of the health movement (see Table 1). One example is the environmental movement, which arguably has the highest overlap with health promotion and obesity prevention

(Skouteris et al., 2013). Some individual-level behaviors that overlap include eating more fresh fruits and vegetables; eating less meat, processed and packaged foods, and foods that require long-distance transportation; and less automobile use and more walking, biking, and public transportation use. One study looked at the association between attitudes toward organic, local, and sustainable foods and higher dietary quality (Pelletier, Laska, Neumark-Sztainer, & Story,

2012). Those who rated these food choices as highly important consumed more fruits and vegetables, more dietary fiber, less sugar and percent calories from fat, ate breakfast more often, and consumed less fast food and sugar-sweetened beverages than those who rated these food choices of moderate and low importance. Thus, environmentalism appears to overlap highly with health behaviors.

While most successful social movements begin among those who are more highly educated and in a higher socioeconomic class, a noteworthy conclusion based on Robinson’s

(2010) described social movements is that many low-income, less-educated populations are already involved in these movements or are even leading them. This is especially useful, as obesity has a greater prevalence in such populations and is also impacted by the complex relation of gender, SES, ethnicity, and obesity (Wang & Beydoun, 2007). In both high school and college students, activism for social change is becoming more and more centered around human rights, including racial, environmental, and educational justice to name a few (Conner & Rosen, 2016).

This suggests that youth activism in particular may be especially well-suited to improve health outcomes among these non-Caucasian and otherwise disenfranchised social movement members. SOCIAL MOVEMENTS AND HEALTH 10

While social movements have the potential to positively influence health outcomes, the

inverse may also be true. Activist burnout is a formidable barrier to sustaining social justice

movements. Individuals who are highly involved in these movements participate because it

provides a sense of meaningfulness and purpose in life, and knowing what’s at stake in the event

of failure to inspire social change makes these activists particularly susceptible to anxiety, stress,

and burnout (Pines, 1994; Kovan & Dirkx, 2003). According to Gorski (2015), this is due largely

to these movements’ culture that disregards self-care. Thus, emphasizing health and self-care as components that are highly related to the goals of the movement may increase dedication and motivation to participate more fully and may also improve psychological health for these

individuals.

Another benefit to targeting social movements as a possible mechanism to improving

health is that many people are already involved in them, so leveraging them as stealth

interventions for health may be extremely efficient, requiring fewer resources because the

cultural support and systematic structures are already in place. While there is a significant lack of

literature on social involvement base rates, it is likely that many people consider themselves to

be involved in some social movement on some level. Therefore, emphasizing the overlap

between health and a person’s respective values will require less individual time and effort and

could be a better intrinsic motivator than doing something “for their own good,” thus better

sustaining any relevant behaviors in the long-term (Robinson, 2010).

While social movements have the potential to influence health behavior and outcomes,

they also offer a multitude of benefits that should not be overlooked. As such, even if the link

between social movement involvement and health is small or does not range across movements,

there are still many reasons to participate. On an individual level, social movements offer many SOCIAL MOVEMENTS AND HEALTH 11 rewards, most commonly including social cohesion and a sense of community, feelings of meaningfulness and accomplishment, and the enjoyment of success in achieving goals (Gomes,

1992). Among college students, higher rates of social change behavior are associated with greater social perspective taking, or being ability to take someone else’s point of view (Johnson,

2015). Related activities are also highly linked with individual values, so participation would presumable strengthen one’s values and, thus, mental well-being and life satisfaction. On a broader level, social movements can also contribute to a better society through outcomes such as positive political change and general societal improvement.

Individual Behaviors

Individual behaviors may act as mediators in the relationship between social movement involvement and health outcomes. When an individual joins a social movement, he or she takes action and participates in behaviors that support its goals and initiatives. Those behaviors, if they relate to health in any way, will theoretically lead a person to be healthier. Robinson (2010) discussed many individual behaviors that overlap with social movements and health (see Table

1). It is hypothesized that it is not involvement in social movements alone that leads to health, as there are many related factors that in and of themselves are not explicitly related to health (e.g., social cohesion, feelings of accomplishment); instead, it is the behaviors associated with the movement that improve health. An individual will presumably be more motivated to engage in such behaviors when they are components of a highly-valued social movement. Therefore, these behaviors have the potential to be sustained in the long-term.

Research Questions The aim of this study was to identify if participation in social movements as mediated by individual behaviors is associated with increased health behaviors (see Figure 1). This relationship will be explored through two samples: adults and college students. Confirmation of SOCIAL MOVEMENTS AND HEALTH 12

this theorized relationship would help to substantiate social movement involvement as a viable

stealth intervention. This research is an important first step on the road to 1) supporting the

promotion of higher levels of social movement involvement, 2) identifying which social

movements correlate more strongly with health behaviors, and 3) identifying specific techniques that can be used within various movements to promote health behavior on a more motivational

level.

Based on Robinson’s (2010) theorized health-related social movements and individual

behaviors, the following main effect and mediation hypotheses will be analyzed:

Hypothesis 1: In both samples, level of social movement involvement (LSMI) will be

positively associated with frequency of individual behaviors (FIB).

Hypothesis 2A: In both samples, FIB will be positively associated with FV, fiber,

calcium, whole grain, and dairy intake; average daily MET minutes; and physical functioning,

energy level, role capabilities due to physical health, role capabilities due to emotional health,

emotional well-being, social functioning, freedom from pain, and general health perception.

Hypothesis 2B: In both samples, FIB will be negatively associated with sugar intake and number of diabetes symptoms endorsed.

Hypothesis 3A: In both samples, FIB will mediate the positive relationship between

LSMI and FV, fiber, calcium, whole grain, and dairy intake; average daily MET minutes; and physical functioning, energy level, role capabilities due to physical health, role capabilities due to emotional health, emotional well-being, social functioning, freedom from pain, and general health perception.

Hypothesis 3B: In both samples, FIB will mediate the negative relationship between

LSMI and sugar intake and number of diabetes symptoms endorsed. SOCIAL MOVEMENTS AND HEALTH 13

In addition, this research seeks to answer the following questions with exploratory analyses:

1. Are these relationships similar in both the college sample and in a sample taken from

the general population?

2. Are college students more involved in social movements, do they partake in more

related individual behaviors, and are they generally healthier than the general

population?

3. Which social movements have the greatest relationship to overall health?

4. Which social movements are more highly endorsed by individuals who are unhealthy

or overweight/obese?

5. Is level of involvement different depending on one’s achieved education or income

status in the general population?

6. Do Caucasians and non-Caucasians differ in level of involvement among the general

adult population and/or among college students?

7. Do the health outcomes assessed in the current study correlate with BMI, or do they

differ enough to suggest the importance of other health indicators?

SOCIAL MOVEMENTS AND HEALTH 14

CHAPTER II. METHOD

Participants

To increase the generalizability of results, samples were drawn from two populations.

Little research has been done on base rates of social movement involvement, so a general adult sample obtained through Amazon’s Mechanical Turk (MTurk) was selected to provide a socio- economically, ethnically, and geographically diverse sample as well as high quality data (Casler,

Bickel, & Hackett, 2013). A total of 229 adults were recruited to complete the questionnaire

through MTurk. Twenty-three participants did not meet quality control criteria, meaning that 1)

survey length was less than 15 minutes and/or 2) both quality control items (e.g., “Please select

some of the time”) were not accurately endorsed. Those who met the inclusion criteria were

credited $0.50 for completion of the 20-30-minute study. A subsequent 11 responses were

removed from the data set due to the uninformative nature of the “none of the above” option

asking participants to choose their prioritized social movement (described below). Thus, analyses

were conducted on a final sample of 195 adults in the general population.

Due to a long history of civic engagement occurring in higher education as well as

increasing prioritization of students’ moral and civic development in universities, a college

student sample was also included (Colby, Beaumont, Ehrlich, & Corngold, 2003; Jacoby, 2009).

Assessing both adult and college student samples would allow for greater exploration and comparison of social movement involvement among these diverse populations. Both samples completed the same questionnaire through Qualtrics with the exception of one item (see

Measures). The college student sample was recruited through SONA, an online system for students to participate in research for class credit. Two-hundred and thirty-six students were recruited to complete the 20-30-minute questionnaire. Based on exclusionary criteria of 1) SOCIAL MOVEMENTS AND HEALTH 15 survey length and/or 2) missed quality control items, 28 students were not granted credit and were excluded from the data set. Those who met exclusion criteria were awarded 0.5 credit hours. Again, due to a measurement error concerning prioritized social movement (described below), 9 responses were not usable. Finally, three participants over the age of 27 were excluded to maintain a typical college student age range and to remove students in graduate school. This resulted in a final sample of 196 college students.

Procedures

The Bowling Green State University Human Subjects Review Board approved all procedures prior to participant recruitment (see Appendix B and C). Participants consented via an electronic form at the beginning of the survey (see Appendices D and E), at which point they were provided with the Principal Investigator’s and HSRB Chair’s contact information in the event they had any questions. Inclusion criteria for this study included: 1) Adulthood (18 years or older), 2) U.S. residency, and 3) English fluency. Upon completion of the survey, participants were thanked for their participation and were either paid or granted class credit.

Measures

All measures are located in Appendix A and were ordered as described below.

Demographics. Participants reported on demographic variables, including age, gender, race/ethnicity, education level, household income, height and weight, political conservatism

(single item on a scale from 1 to 7), employment status, and relationship status. In the college sample, household income was instead measured by asking in which socioeconomic class they considered their family to be (single item on a scale from lower class to upper class).

Social Movement Assessment Scale. For the independent variable, I created a scale based on Robinson’s (2010) list of potential social movements to inquire about the participants’ SOCIAL MOVEMENTS AND HEALTH 16

views of each movement’s importance (e.g., “I think animal protection (reducing inhumane

treatment of animals) is important”) as well as their perceived level of personal involvement

(e.g., “I am actively involved in the animal protection movement”) in the movement. All items were measured on a Likert-type scale from 0 (not important/involved) to 4 (extremely important/involved). This scale included the 13 social movements from Robinson’s (2010) paper

(e.g., “Anticonsumerism”) in order to stay consistent with his theory. Finally, participants chose

one of the previously mentioned social movements that they viewed to be their highest priority in

terms of both importance and involvement to refer to for subsequent questions. The list included

a 14th option for participants to select “none of the above.” Unfortunately, this final option was

ambiguous as it did not differentiate between those involved in a different social movement and

those not involved in any social movement. In the future, having two options – both “other” and

“I am not involved in any social movements” – would be beneficial in determining base rates of

social movement involvement. Due to the uninformative nature of the “none of the above”

option, individuals who selected this option were removed from the data set, as the meaning of

their responses to subsequent questions was indeterminable.

Social Movement Inventory of Involvement Scale. To capture each participant’s self-

reported involvement level in his or her prioritized movement, I adapted the Indicators of

Environmentalism measure (Stern, Dietz, Abel, Guagnano, & Kalof, 1999) and the

Environmental Involvement Inventory (Matsuba, 2012) to include other social movements of

interest and to better assess individuals of all generations. For example, “Watched a television

special on the environment” was changed to “Watched a video, movie, or television show on

your social cause,” as the ubiquity of social media and streaming services has increased access to

a multitude of video sources. This scale assessed how highly involved participants are in their SOCIAL MOVEMENTS AND HEALTH 17

respective movements by assessing the frequency of both public and personal involvement. This

measure consisted of 12 items, which are measured either on a Likert scale from 0 (never) to 4 (a

lot; e.g., “Had a serious discussion about your social cause with your family, friends, coworkers,

etc.”) or with a yes/no (1/0; e.g., “Are you a member of any group whose main aim is to promote

your social movement?”) response. Likert scale responses were recoded into a scale from 0 to 1 to match yes/no responses, and the items were averaged to determine mean level of social movement involvement (LSMI). All social movements were included together in these analyses.

Although this reduced the ability to discriminate among various social movements, it allowed each sample to be analyzed in a single model and it examined social movement involvement more broadly. In the general adult and college student samples, internal consistency was high, α

= .83 and α = .73, respectively.

Individual Behavior Inventory. Also based on Robinson’s (2010) paper, I created a measure of individual behaviors presumed to be associated with various social movements. This measure allowed for the exploration of a person’s social movement-related behaviors as a mediator in the relationship between social movement involvement and health. This list of behaviors included 19 individual behaviors hypothesized by Robinson (2010; e.g., “Eat organic, locally-grown fruits and vegetables”) as well as six other items not related to social movements or health. All items assessed how often participants engage in an activity in a typical month.

Responses were averaged and used as the measure of frequency of individual behaviors (FIB) in the meditation analyses. In the general adult and college student samples, internal consistency was high, α = .88 and α = .85, respectively.

Four control items in the IBI were included to examine divergent validity of the scale.

These items were found to be highly correlated with the actual items of the scale in both the SOCIAL MOVEMENTS AND HEALTH 18

general adult sample, r = .67, p < .001, and college student sample, r = 0.44, p < .001. For the

general adult sample, both the actual items and the control items were correlated with average

involvement in one’s social movement, r = 0.50, p < .001, and r = .48, p < .001, respectively.

These associations were smaller but significant in the college student sample: actual items were correlated with involvement at r = 0.25, p = .001, and control items at r = 0.41, p < .001. These findings suggest the potential of socially desirable responding on the part of the participants as the four control items were positive or social in nature (e.g., “Read books for leisure”).

Dietary Screener Questionnaire. The dependent variable, health outcomes, was measured four ways. The first was the Dietary Screener Questionnaire (DSQ; NCI, 2016), which measures participants’ nutrition intake. It provided detailed information about food, nutrient, and supplement intake and other dietary behaviors. This measure included 28 items that are rated based on the number of times various foods (never to 2 or more times a day) and beverages

(never to 6 or more times a day) are consumed (e.g., “During the past month, how often did you eat fruit? Include fresh, frozen or canned fruit. Do not include juices”). Data reduction analyses

(conducted using SAS statistical software) yielded daily consumption estimates of daily fruit and vegetable (both with and without the inclusion of fried potatoes; cup equivalents), whole grains

(ounce equivalents), added sugar (tsp equivalents), sugar sweetened beverages (tsp equivalents), fiber (g), and calcium (mg) consumption. Six dietary outcomes were drawn from this measure for the purposes of the current study: Fruit, vegetable, and legume (no fried potatoes; FV), added sugar, whole grain, fiber, calcium, and dairy intake. Fruit, vegetable, and legume including fried potatoes was not analyzed due to its lower nutritional value, and sugar-sweetened beverage consumption is already included in the added sugar variable, which is more comprehensive in nature. Reporting internal consistency is not appropriate for dietary measures, as not all dietary SOCIAL MOVEMENTS AND HEALTH 19

components are similarly nutritious or non-nutritious, and within this measure, one item may be

utilized in the computation of more than one dietary variable.

All of the dietary outcomes were highly positively skewed in both samples, with skew to

standard error of the skew ratios greater than two to one. Therefore, all variables were

transformed with square root, reciprocal, and log computations, the latter of which resolved some skews and improved others in both samples. These log transformed data were interpreted and

utilized for subsequent analyses.

International Physical Activity Questionnaire. To measure physical exercise, participants completed the International Physical Activity Questionnaire (IPAQ), which measured physical activity patterns in and around the home, activity at work, and recreational exercise. This measure included 27 items which comprise five subscales: Job-related physical

activity; transportation physical activity; housework, house maintenance, and caring for family;

recreation, sport, and leisure-time physical activity; and time spent sitting. Items are measured as

to how many days per week the individual participates in an activity (e.g., “Not counting any

walking you have already mentioned, during the last 7 days, on how many days did you walk

for at least 10 minutes at a time in your leisure time?”) with follow-up items based on how

many hours and minutes were spent on the activity (e.g., “How much time did you usually spend

on one of those days walking in your leisure time?”). Reporting internal consistency is not applicable to this measure, as different types of physical activity are not assumed to behave similarly.

Many individuals had difficulty accurately estimating their activity level per week, resulting in high outliers. To resolve this issue, several steps were taken. First, any high number of hours per day per activity that were clearly meant to be minutes (e.g., intervals of 15) were SOCIAL MOVEMENTS AND HEALTH 20

transferred into the minute category. Any high hours that were undeterminable as either hours or

minutes were marked as “missing.” Next, activities were summed into three categories – walking, moderate activity, and vigorous activity per week – by multiplying each activity’s hours by 60 and adding their respective minutes, multiplying this final number by reported days per week partaking in the activity, and summing total minutes of activities within each category. Any

summed hours per week that exceeded three hours per category per day (1,260 minutes per

week) were truncated at 1,260 based on the IPAQ’s scoring protocol. At this point, total weekly

minutes per category were multiplied by their respective METs, summed into total MET minutes

per week, and finally divided by seven to create a variable of daily physical activity.

This variable had a positive skew more than twice the standard error of the skew in both samples. Thus, square root transformation were conducted, resulting in a more normal distribution in both samples. Subsequent analyses were run and interpreted on these transformed variables.

RAND 36-Item Health Survey. The RAND 36-Item Health Survey provided a general measure of health and quality of life. The survey assessed eight subscales, including an individual’s physical functioning, freedom from pain, role capabilities due to physical health, role capabilities due to emotional health, emotional well-being, social functioning, energy/fatigue level, and general health perceptions (RAND, 2009). In addition, it included one item that provided an indication of the individual’s perceived change in health. This measure contained 35 items that assess how an individual’s health limits various activities (e.g., Lifting or carrying groceries) and other daily functioning within the past month (e.g., During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious)?). All SOCIAL MOVEMENTS AND HEALTH 21 responses are recoded to scales of 1 to 100 and then averaged into the previously mentioned subscales, greater values indicating greater health on all subscales. Due to conceptual differences among the eight subscales, each was retained as a separate health indicator as opposed to combining them into one composite of quality of life. Previous examination of the scale’s internal consistency resulted in alphas ranging from .72 to .92 among the eight subscales

(VanderZee, Sanderman, Heyink & de Haes, 1996). In the general adult sample, alphas ranged from .84 to .94, indicating high internal consistency. Cronbach’s alpha values ranged from .71 to

.94 in the college student sample.

With the exception of the energy subscale in both samples, all subscales had a negative skew that was greater than twice the standard error of the skew. In attempt to remedy this, all subscales were reflected and then transformed with square root, reciprocal, and log transformations. However, skew ratios remained high for most variables and some worsened.

Therefore, to maintain clarity of interpretations, subsequent analyses were conducted on raw data in both samples.

Diabetes Symptom Checklist. The Diabetes Symptom Checklist – Revised (DSC-R) was used to identify diabetes-related symptoms endorsed by participants. This 34-item measure assessed whether an individual experiences a particular symptom (yes/no). For the purposes of this study, items were averaged to create a mean number of symptoms endorsed, with higher values indicating poorer health. Sample items include “Tingling sensations in the limbs at night” and “Pain in the chest or heart region.” Among clinical samples, internal consistency has ranged from .69 to .87 (Arbuckle et al., 2009). In the general adult and college student samples, internal consistency was high, α = .86 and α = .89, respectively. SOCIAL MOVEMENTS AND HEALTH 22

This scale was also negatively skewed. Once again, square root, reciprocal, and log transformations were conducted and analyzed in comparison to raw data. The skew ratio remained high in the general adult sample, so raw data were utilized in subsequent analyses for the sake of clarity. However, the square root transformation resolved the high skew in the college student sample, so this transformed variable was utilized in subsequent analyses in this sample.

Method of Analysis

While it has been argued that there is no need to establish main effects before testing mediation analyses (Zhao, Lynch, & Chen, 2010), due to the large number of outcome variables in the current study, main effects on the variables of interest were examined to provide stronger support for mediations. To demonstrate mediation in the context of the current study, the predictor (LSMI) must be associated with the mediator (FIB), which must in turn be associated with the outcome variable (Baron and Kenney, 1986). Therefore, Pearson correlations were conducted to ascertain the existence of these relationships, and follow-up hierarchical regressions were conducted to control for known covariates and examine the unique contribution of the variables of interest to outcomes. Known covariates were entered into Step 1, and the variable of interest was entered into Step 2 of these analyses.

The Process macro created by Hayes (2014) for SPSS was used to test the mediation hypotheses of the current study. A separate mediation analysis was conducted for each outcome variable that was supported by regression analyses within each sample.

Regarding interpretation, Baron and Kenny’s (1986) foundational framework for mediation analyses has been somewhat disputed in statistical literature. Zhao, Lynch, and Chen

(2010) provided a simplified version of criticisms, and their manuscript as well as Field’s (2014) book on statistics argue against the “full mediation” gold standard for two dimensions – the SOCIAL MOVEMENTS AND HEALTH 23 indirect and direct effects – to be reported. As supported by Zhao et al., the indirect effect was interpreted as the main indicator of whether or not mediation occurred, and significant direct effects do not impact this interpretation but instead provide evidence for the potential of other important mediators not measured. Terminology provided by Zhao et al. was used to interpret the current study’s findings: Indirect-only mediation is synonymous with full mediation, meaning the indirect effect is significant while the direct effect is not. Complementary mediation means that both the indirect and direct effects are significant and point in the same direction; this is similar to Baron and Kenny’s (1986) definition of partial mediation. Finally, competitive mediation (both significant but in opposite directions), direct-only nonmediation (direct significant, indirect nonsignificant), and no-effect nonmediation (neither direct nor indirect significant) are all synonymous with no mediation present.

To interpret mediation indirect effect sizes, the index of mediation (ab’) proposed by

Preacher and Kelley (2008) was utilized. This measure is more easily comparable across studies as it does not depend on the metrics of the variables involved as other measures of effect size often do (Field, 2013). SOCIAL MOVEMENTS AND HEALTH 24

CHAPTER III. RESULTS

Preliminary Analyses

Tables 2 and 3 provide the demographic make-up of the general adult and college student samples, respectively. Among the general adult sample, race and education variables were somewhat proportionate to recent U.S. census data, revealing a relatively accurate representation of the current population. For example, the current sample was slightly more White than census date from 2010, with 84.0 percent of this sample identifying as Caucasian versus 72.4 percent

(Humes, Jones, & Ramirez, 2011). Also in this census brief, 12.6 percent of the population identified as Black or African American compared to this sample’s 4.9 percent. Other race percentages were within one or two percentage points compared to census data. Additionally, this sample was slightly more educated, with 98.5 percent holding at least a high school diploma and 48.1 percent holding a bachelor’s degree or higher, compared to census rates of 88 percent and 33 percent, respectively, based on data from the 2015 Current Population Survey (CPS;

Ryan & Bauman, 2016).

The demographic make-up of the college sample was similar to that of the university’s demographic composition and was closer racially to the U.S. census rates listed previously. For example, 79.1 percent of BGSU undergraduate students identify as Caucasian, almost the same as this sample’s 80.4 percent; also, 9.8 percent identify as African American, similar to 9.0 percent in this sample (COLLEGEdata, 2016). Both the general adult and college student sample over-represented women, with 63.6 percent of the general adults and 76.9 percent of the college sample identifying as female compared to 51 percent of the U.S. population and 57 percent of the undergraduate student body (COLLEGEdata, 2016; Howden & Meyer, 2011). SOCIAL MOVEMENTS AND HEALTH 25

To identify any demographic variables that might impact the mediation analyses, bivariate correlations were conducted on age, education achieved, and income with all outcome variables. In the college sample, education level was not analyzed as all students were undergraduates, and income was assessed by family SES as previously mentioned. Due to their dichotomous nature, t-tests were conducted on race and gender with all outcome variables.

Correlation coefficients and t-test results for each sample are located in Tables 4 through 7.

Additionally, because frequency of individual behaviors (FIB) is considered an outcome as the mediator, analyses were also run on this variable. FIB was significantly positively correlated with education level in the general adult sample, r = 0.17, p = 0.02.

Table 8 provides the number of general adults and college students who endorsed each social movement. Human rights/social justice was the most frequently endorsed in both samples, followed by environmental sustainability in the general adult sample and followed by animal protection in the college student sample.

Main Effect Analyses

Bivariate correlations, simple regressions, and hierarchical regressions among LSMI,

FIB, and all health outcomes were conducted to identify which health variables would be analyzed in mediation analyses.

General adults. LSMI was highly correlated with FIB, r = .44, p < .001. A follow-up hierarchical regression was conducted to control for education level. After controlling for this

2 variable, LSMI uniquely contributed to the variance in FIB, and this link was positive (R ∆unadj =

0.20, F(1, 192) = 49.23, p < 0.001). At Step 2, education level was no longer significant.

FIB was correlated with several outcome variables: fruit, vegetable, and legume (no fried potatoes) consumption (FV; r = 0.36, p < .001), fiber intake (r = .29, p < 0.001), whole grain SOCIAL MOVEMENTS AND HEALTH 26

intake (r = 0.24, p = 0.001), average daily MET minutes (r = 0.48, p < 0.001), energy level (r =0

.21, p = 0.003), and general health perception (r = 0.19, p = 0.01), all of which were in the

hypothesized direction. Thus, regression analyses were conducted controlling for associated

demographics only on these significant health variables to streamline analyses.

Hierarchical multiple regression results are located in Table 9. After controlling for

gender, FIB accounted for a unique portion of the variance in FV, fiber, and whole grain intake,

positively predicting these dietary variables. Gender remained significant at Step 2 in all three

analyses, with males reporting more FV, fiber, and whole grain consumption than females. FIB

accounted for a unique portion of the variance in MET minutes after controlling for income,

positively predicting amount of daily physical activity. Income was no longer significant in Step

2. After controlling for gender and income, FIB accounted for a unique portion of the variance in

energy level, positively predicting energy level. Both gender and income remained significant at

Step 2, with females and individuals with higher incomes reporting higher energy levels. Finally,

after controlling for income, FIB accounted for a unique portion of the variance in general health

perception, and this was again a positive link. Income remained significant at Step 2, with

individuals reporting higher income also reporting greater perceived health.

College students. Among the college student sample, LSMI and FIB were significantly

correlated, r = .25, p < .001. In a simple regression, LSMI uniquely contributed to the variance in

2 FIB, and this link was positive (R unadj = 0.061, F(1, 194) = 12.57, p < 0.001). FIB was in turn correlated with several outcome variables: fruit vegetable, and legume (no fried potatoes) consumption (FV; r = 0.40, p < .001), fiber intake (r = 0.35, p < .001), whole grain intake (r =

0.33, p < .001), average daily MET minutes (r = 0.26, p < .001), and role capabilities due to

emotional health (r = -0.19, p = .01), all of which were in the hypothesized direction except for SOCIAL MOVEMENTS AND HEALTH 27 the latter. Thus, regression analyses were conducted controlling for associated demographics only on these significant health variables again to streamline analyses.

Simple and hierarchical multiple regressions are located in Table 10. After controlling for gender, FIB accounted for a unique portion of the variance in FV intake, positively predicting

FV intake. Gender remained significant at Step 2, indicating that males reported consuming more

FV than females. In simple regressions with no demographic covariates, FIB accounted for a unique portion of the variance in fiber and whole grain intake, positively predicting these dietary variables. A simple regression revealed that FIB accounted for a significant portion of the variance in average daily MET minutes, positively predicting physical activity. Finally, after controlling for gender, FIB accounted for a unique portion of the variance in role capabilities due to emotional health, negatively predicting capabilities, and gender was no longer significantly associated with these capabilities.

Examining these regression analyses among both samples, hypothesis 1 was fully supported and hypothesis 2A was partially supported. Therefore, follow-up mediation analyses were conducted on FV, fiber, and whole grain consumption, average daily MET minutes in both samples; energy level and general health perception among the adult sample; and role capabilities due to emotional health among the college sample.

Mediation Analyses

General adults. Because gender was significantly associated with FV, fiber, and whole grain consumption, this variable was added as a covariate in these analyses. Income was added as a covariate into the mediation model predicting average daily MET minutes and general health perception, and income status and gender were added as covariates into the analysis for energy level. Refer to Figures 2 through 7 for visual depictions of these results. SOCIAL MOVEMENTS AND HEALTH 28

After covarying out the effects of gender on FV intake, there was a significant indirect- only mediation effect of social movement involvement on FV consumption, b = 0.13, 95% CI

[0.07, 0.20], ab’ = 0.15, 95% BCa CI [0.08, 0.23]. After covarying out the effects of gender on fiber intake, there was a significant indirect-only mediation effect of social movement involvement on fiber intake, b = 0.10, 95% CI [0.04, 0.17], ab’ = 0.16, 95% BCa CI [0.07, 0.25].

After controlling for gender on whole grain consumption, there was a significant indirect-only mediation effect of social movement involvement on whole grain intake, b = 0.25, 95% CI [0.10,

0.43], ab’ = 0.13, 95% BCa CI [0.05, 0.22].

After covarying out the effects of income on daily MET minutes, there was a significant indirect-only mediation effect of social movement involvement on average daily MET minutes of physical activity, b = 10.21, 95% CI [6.42, 15.16], ab’ = 0.19, 95% BCa CI [0.12, 0.28].

Regarding energy level, after covarying out the effects of income and gender, there was a significant indirect-only mediation effect of social movement involvement and reported energy level, b = 9.62, 95% CI [2.28, 19.85], ab’ = 0.10, 95% BCa CI [0.03, 0.21]. Finally, after covarying out the effects of income, there was a significant indirect effect of social movement involvement and general health perception, b = 11.12, 95% CI [4.97, 18.84], ab’ = 0.12, 95%

BCa CI [0.06, 0.21]. However, the direct effect was also present and in an opposite direction of the indirect effect, b = -17.66, p = 0.025, indicating a competitive mediation and, thus, as explained above, no significant mediation. Therefore, these mediations partially support hypothesis 3A, including the models predicting FV, fiber, whole grain, daily MET minutes, and energy level. SOCIAL MOVEMENTS AND HEALTH 29

College students. Because gender was significantly associated with FV consumption and

role capabilities due to emotional health, this variable was added as a covariate in these analyses.

Refer to Figures 8 through 12 for visual depictions of these results.

After covarying out the effects of gender on FV intake, there was a significant indirect- only mediation effect of social movement involvement on FV consumption, b = .10, 95% CI

[.04, .19], ab’ = .10, 95% BCa CI [.05, .19]. There was a significant indirect-only mediation effect of social movement involvement on fiber consumption, b = 0.06, 95% CI [0.03, 0.12], ab’

= 0.08, 95% BCa CI [0.03, 0.15]. There was a significant indirect-only mediation effect of social movement involvement on whole grain consumption, b = .17, 95% CI [.07, .32], ab’ = .07, 95%

BCa CI [.03, .15]. There was a significant indirect-only mediation effect of social movement involvement on average daily MET minutes, b = 4.13, 95% CI [1.79, 8.36], ab’ = .07, 95% BCa

CI [.03, .13]. Finally, after covarying out the effects of gender, there was a significant indirect effect of social movement involvement role capabilities due to emotional health, b = -6.74, 95%

CI [-18.93, -.08], ab’ = -.03, 95% BCa CI [-.10, -.001]. The direct effect was also significant, b =

-31.90, p = .04, indicating a complementary mediation in the opposite direction hypothesized.

Exploratory Analyses

Exploratory analyses were also conducted to better understand the relationships between some these variables. To improve the sample sizes of prioritized social movements and to better interpret related findings, certain movements of smaller size were combined to create a total of six social movements. Table 11 describes these new categories in more detail and provides updated n and percent values for both samples. Human rights, environmentalism, and animal protection were endorsed by enough participants that they remained unchanged. “Nationalism”

was created by combining nationalism/patriotism, energy independence, anti-globalization, and SOCIAL MOVEMENTS AND HEALTH 30

national security. Crime prevention was combined with community improvement to create the

fifth social movement, and all others were combined into an “other” category due to low

endorsement. The creation of these new categories was based on overlapping individual

behaviors as theorized by Robinson (2010); however, the “other” category was created solely

due to relatively low endorsement, so many subsequent analyses excluded individuals in this new

group.

Excluding the “other” category, ANOVAs were conducted on these new categories of

social movements and all outcome variables to identify which, if any, predict healthier outcomes.

In neither sample were these analyses significant, and the pattern for each outcome did not

remain stable. An ANOVA was also conducted on social movements as a predictor of BMI to

examine which movements are more highly endorsed by individuals with a higher BMI. Again,

these analyses were nonsignificant in both sample.

To explore how education and income status impact one’s level of involvement among

general adults, bivariate correlations were conducted on these variables among the general

sample. Neither relationship was significant (p’s > .05), indicating that individuals are similarly

involved regardless of their socioeconomic class or level of education.

A t-test was conducted on involvement level among Caucasians and non-Caucasians in

both sample to determine if Caucasians are differentially involved compared to minority

individuals. In the general adult sample, this result was nonsignificant (p > .05). In the college sample, however, non-Caucasians were significantly more involved than Caucasians (t = -3.05, p

= 0.01).

T-tests were conducted to compare the college sample to the general sample on demographic variables, level of involvement, social movement behaviors, and health outcomes. SOCIAL MOVEMENTS AND HEALTH 31

Contrary to hypotheses, the general sample reported to be more involved in their prioritized social movement, t(376.56) = 2.51, p = .012, and partake in more associated behaviors, t(378.2)

= 3.63, p < .001, than the college sample. Regarding health outcomes, several findings were significant, several expected and several not. The general adults were healthier in regards to greater fruit and vegetable consumption, t(381.98) = 3.10, p = .002 and lower sugar intake, t(327.73) = -2.42, p = .016. However, college students reported greater levels of physical activity, t(381.38) = -3.09, p = .002, greater physical functioning, t(369.05) = -2.96, p = .003, more freedom from pain, t(358.92) = -2.76, p = .006, and lower BMI, t(341.33) = 4.53, p < .001.

The outcome variables utilized in this study were correlated with BMI to identify how well they map on to the field’s common measurement of health. With the exception of role capabilities due to emotional health (r = -.12, p = .084), all general health subscales were significantly associated with BMI in the general adult sample: physical functioning (r = -.30, p <

.001), role capabilities due to physical health (r = -.22, p = .002), energy level (r = -.35, p <

.001), emotional well-being (r = -.15, p = .035), social functioning (r = -.14, p = .048), freedom from pain (r = -.33, p < .001), and general health perception (r = -.44, p < .001). The number of diabetes-related symptoms was also significantly related to BMI, r = .21, p = .003. All other outcome variables – dietary outcomes and daily MET minutes – were associated with BMI in the hypothesized direction but were not significant. Among the college sample, none of these analyses were significant (p’s > 0.05). Because many of these correlations are either non- significant or small in magnitude, these results provide support for using other indictors of health beyond BMI, particularly among diverse samples. SOCIAL MOVEMENTS AND HEALTH 32

CHAPTER IV. DISCUSSION

This research adds to the small current literature on stealth interventions as a means of

improving health and highlights the potential of using social movements as a form of stealth

intervention. This is the first empirical study to examine social movements as they relate to

health outcomes, and the results reported here suggest a promising future avenue for improving

the health outcomes of those who are involved in such activities. As an intervention, encouraging

greater involved in valued movements and activities that vicariously improve health may have a

large impact on behavior change maintenance in the long-term and may circumvent common

barriers compared to current behavioral interventions. Furthermore, as social movements offer

many social and mental benefits beyond physical health, this avenue takes a more holistic

approach to health promotion by emphasizing one’s quality of life and happiness, factors that

also contribute to one’s overall health.

Primary findings

Based on the findings of this project, being more involved in one’s valued social

movement is associated with numerous positive health outcomes. When considering the

hypothesized model, the frequency of practicing social movement-related behaviors was a

significant mediator in the relationship between level of social movement involvement and FV,

fiber, and whole grain intake, and daily MET minutes of physical activity in both samples as well

as energy level in the general adult sample. This suggests that those who are more involved in

social movement activities are likely to eat more nutritious foods and get adequate physical

activity in part due to certain activities considered valuable to their social movement.

Additionally, it is possible that this relationship exists in the opposite direction, meaning that SOCIAL MOVEMENTS AND HEALTH 33 healthier people may be more likely to get involved in social movements and partake in these activities.

FV, fiber, and whole grains were the only significant dietary variables supported by the mediation analyses. Because fiber is highest in produce, legumes, and whole grains, it makes sense that there was a similar pattern for these variables. FV and fiber are crucial dietary components in health outcomes. Higher intake of fruits has been associated with decreased weight and waist circumference, and greater FV consumption has been linked to reduced risk of adiposity (Schwingshackl et al., 2015). Individuals with higher consumption of FV also have lower risk of cardiovascular disease (Hung et al., 2004). Legume consumption is associated with reduced risk of incident ischemic heart disease (IDH; Afshin, Micha, Khatibzadeh, &

Mozaffarian, 2014). Fiber is well-known to promote gut health, an up-and-coming field of research that has already linked the health of our microbiota to obesity, immunology, gut-related diseases (e.g., Crohn’s disease), and many chronic conditions such as type 2 diabetes and heart disease (Sonnenburg & Sonnenburg, 2015). Thus, these findings support the potential and importance of interventions that can increase these crucial dietary targets.

Unexpected findings

The competitive mediation finding for the general health perception subscale among these general adults suggests that individuals who are more involved and partake in more social movement behaviors perceive themselves to be generally healthy, but other mediators exist that may explain the significant opposing direct effect. People who are more involved in positive social movements and their respective health-related behaviors would presumably have a more positive view of the impacts of such activities on health. However, it is possible that being more involved in a social movement may also produce more negative outcomes that impact health, SOCIAL MOVEMENTS AND HEALTH 34 such as activist burnout and stress. As supported by Gorski (2015), some social movements may disregard self-care (e.g., healthy lifestyle behaviors), so examining this phenomenon and its consequences (e.g., burnout) as other potential mediators may better explain the relationship between involvement and outcomes such as health perception and mental health. Gorski’s findings also support the unexpected findings of role capabilities due to emotional health among these college students. This relationship was in the opposite direction hypothesized, indicating that greater involvement negatively predicts capabilities due to emotional health. Greater involvement may lead to more emotional difficulties due to stress and burnout from the burdens of being active in these movements that sometimes have limited success. Perhaps for college students, the challenges of activism are particularly harmful to one’s emotional status. The complementary nature of this mediation points to other likely mechanisms. Other potential mediators and moderators for all findings will be discussed below.

It is unclear why some outcomes in hypotheses 2A (main effects of Frequency of

Individual Behavior on positive health outcomes) and 3A (mediation analyses with positive health outcomes) as well as any outcomes in hypotheses 2B (main effects of FIB on negative health outcomes) and 3B (mediation analyses with negative health outcomes) were not supported in the current study. As no other studies have examined the impact of social movement involvement on these health outcomes, any explanation is purely speculative. The social movements assessed in this study theoretically include behaviors that would increase consumption of healthy food options and/or increase physical activity. However, it is possible that individuals involved in social movements, no matter their level of involvement, may not partake in some or any of the behaviors proposed by Robinson (2010). Or, it is possible that the theorized behaviors only influence specific outcomes and do not have broader impacts. For SOCIAL MOVEMENTS AND HEALTH 35 example, while certain movements involve the behavior of purchasing more FV from local farmers or foods that are organic, this may not also extend to reduce their added sugar consumption or increase their emotional well-being for example.

Comparing social movements

No social movement emerged as more clearly associated with any health outcome or

BMI compared to other social movements measured. These findings indicate that the particular social movement one is involved in may be less pertinent to health outcomes than simply being more involved and partaking in more associated behaviors. This is good news for future interventions because encouraging involvement in a movement of value would be simpler and reach more individuals than attempting to get people involved in specific movements they may not value. However, the absence of significant findings in this study does not mean social movements have no differential impact on health in reality. Future research may aim to highlight the importance of specific movements, and stronger health patterns may emerge with larger samples, more equal cell sizes, and the inclusion of other social movements not included in

Robinson’s (2010) theory.

In both samples, the human rights movement was most highly endorsed, likely because it encompasses a wide variety of initiatives (e.g., equal pay for women, fair treatment of racial and gender minorities). Among the general-population adults, environmentalism was second most commonly endorsed, and animal protection was second most popular among college students.

With the current scientific standings and societal emphasis on climate change, it was surprising that this movement was not as highly prioritized by students as well. Perhaps college students, encountering novel forms of autonomy (e.g., exposure to vegetarian diet, ability to own pets), find animal protection to be particularly salient. It is worth noting that the college sample SOCIAL MOVEMENTS AND HEALTH 36

consisted of young adults living in a rural area. This population’s social movement

characteristics may differ by geographical location, public versus private status, or university’s level of prestige.

Comparing samples

The findings that the general adult participants were more involved in their prioritized social movements was unexpected. Previous studies have found emerging adults in college to be greatly involved in social movements and a greater university-wide prioritization of increasing students’ engagement in recent years (Colby, Beaumont, Ehrlich, & Corngold, 2003; Jacoby,

2009). However, no studies to date have compared students to the general population, so it is possible that findings from the current study are typical. Perhaps adults are more involved in social movements because they have more resources to donate to such activism. Indeed, the questionnaire adapted for the current study, while edited in an attempt to assess all ages and populations, may not accurately capture involvement activities among all groups equally. For example, several items assessed money-related activities of involvement (e.g., “Contributed time or money to a group that promotes your social cause” and “Have you ever donated money to a group pertaining to your social cause?”). Other items asked about voting in an election and reading a website or other publication in support of one’s social cause; these items may not accurately depict activities of college students. In addition, college students may exhibit other activities of involvement not measured. The validity of this questionnaire as an equal measure of involvement in each sample warrants further exploration to help explain these findings.

Nonetheless, these findings suggest even wider applicability of these types of interventions, as adults who are generally more overweight than their young adult counterparts (Sutin, Ferrucci, SOCIAL MOVEMENTS AND HEALTH 37

Zonderman, & Terracciano, 2011) may benefit substantially from intervention if they are more involved.

Regarding health outcomes, dietary intake was somewhat better in the general adult sample regarding FV and sugar intake. This is supported by previous research that young adults tend to experience a decrease in dietary quality (e.g., less fruit, more sugar-sweetened beverages) from childhood dietary quality (Demory-Luce, Morales, Nicklas, Baranowski, Zakeri, &

Berenson, 2004), and that college students, in a new stage of food independence, tend to eat less

FV, fiber, and calcium (Deforche, Van Dyck, Deliens, & De Bourdeaudhuji, 2015). It is possible that young adults, particularly college students, have not yet recognized the relevance of healthy eating as it overlaps with social movements. College students also reported greater amounts of physical activity, which is supported by previous findings that physical activity levels are correlated but decrease slightly overtime (Friedman, Martin, Tucker, Criqui, Kern, & Reynolds,

2008). While physical activity decreases and sedentary activity increases from high school to college, (Deforche, Van Dyck, Deliens, & De Bourdeaudhuji, 2015), these changes seem to continue into adulthood, while dietary intake may instead increase with continued food independence and other activities in adulthood (e.g., access to own kitchen, having children).

Physical functioning was also significantly greater among college students compared to general adults, which has been shown as the RAND health survey subscale with the largest discrepancy among younger and older age groups (VanderZee, Sanderman, Heyink, & de Haes, 1996).

Freedom from pain was higher in college students than in this sample of general adults, a logical finding considering the general deterioration of health as people age. Finally, college students had lower BMI than the general adults. This is consistent with previous literature on the SOCIAL MOVEMENTS AND HEALTH 38 progression of obesity over the life span from Baltimore Longitudinal Study of Aging (BLSA;

Sutin, Ferrucci, Zonderman, & Terracciano, 2011).

Demographic findings

Level of involvement was not significantly related to education or income, which suggests that people who have less education or are in a lower socioeconomic class are similarly involved in social movements compared to better educated, more wealthy counterparts.

Similarly, involvement did not differ significantly based on race in the general adult sample

(Caucasian versus non-Caucasian), although it did in the college sample. These findings are positive as they indicate that encouraging greater involvement may benefit individuals of all classes and races, including minority groups and individuals of a lower social class who tend to have higher rates of obesity (Wang & Beydoun, 2007), greater increases in BMI and waist circumference (Beydoun & Wang, 2009), and poorer dietary quality (Beydoun & Wang, 2007), which consequently increase the risk of chronic health conditions. Significant findings for some demographic variables with dietary outcomes are worth exploring further. Gender was significantly related to each of the three dietary variables explored in mediation analyses among the general adult sample. Thus, further research should explore these relationships with a more heterogeneous sample to determine the extent to which these variables impact health.

Indicators of health

Some health measures were correlated with BMI in the general adult sample while others were not correlated at all. In the college sample, none were significantly related to BMI. These results highlight the importance of examining other constructs in the realm of health than overweight and obesity, particularly when assessing different populations. Waist circumference

(WC) has been supported as a greater indicator of cardiovascular risk than BMI by the data from SOCIAL MOVEMENTS AND HEALTH 39 the Canadian Heart Health study (Dobbelsteyn, Foffres, MacLean, & Flowerdew, 2001); a

Danish cohort study found no association between total energy intake and WC but significant inverse relationships between animal protein and complex carbohydrates (i.e., FV) and WC, and a positive association between refined grains, potatoes, and other simply sugars and WC

(Halkjær, Tjønneland, Thomsen, Overvad, & Sørensen, 2006). These findings highlight the importance of breaking down health indicators into more specific subgroups to identify a true impact on health. BMI, as previously discusses, overlooks numerous factors that contribute to health outcomes, so emphasizing other measures may be more indicative of long-term health.

Measurement of various health outcomes could have impacted findings. The DSQ provides rough estimates, whereas multiple collections of a 24-hour dietary recall may have improved the accuracy of these findings. With both the general health subscales and the DSC-R, distributions were highly skewed, indicating that most participants reported no or little general health problems. Therefore, it is possible that many outcomes did not appear due to the lack of variability in reporting. A similar study conducted on a sample with known health conditions such as type 2 diabetes or overweight status may have yielded more variability in these measures and could have improved exploration of these variables in regards to involvement.

Unexplored potential mechanisms

There are several other potential explanations for mediation findings that should be explored. First, being more involved in one’s prioritized social movement suggests a high motivation to contribute to its purpose. Thus, values undoubtedly play a role in one’s dedication to and participation in a social movement. For example, Schultz and Zelezney (1999) showed that values of universalism, power, and tradition were correlated with environmental attitudes and concerns, revealing that a person’s general values are related to their identification with the SOCIAL MOVEMENTS AND HEALTH 40

environmental movement. Essentially, values may play a role in both one’s level of involvement

in social movements as well as his or her health behaviors, confounding these results. For

example, individuals who values activities that benefit broader society may also highly value

self-care and making healthy decisions.

It could also be that one’s personality and worldview play a large role in influencing both

their level of involvement and their healthier lifestyle. Individuals who are more involved and

have a “go-getter” mentality may also be more likely to live in a more healthful way. Individuals with lower neuroticism, lower agreeableness, and higher openness have a higher propensity to

participate in political protests (Brandstatter & Opp, 2014). In regard to health outcomes, higher

levels of positive Big Five personality traits have been shown to be associated with greater levels of physical activity (Wilson & Dishman, 2015), and higher neuroticism has also been linked to

higher LDL and total cholesterol levels (Hengartner, Kawohl, Haker, Rossler, & Ajdacic-Gross,

2016). Additionally, a meta-analysis on personality disorders and deleterious health outcomes

supports the link between these disorders and chronic conditions including obesity (Dixon-

Gordon, Whalen, Layden, & Chapman, 2015). These studies suggest that individuals with more

positive personality traits may simply be healthier, and these constructs may act as either

potential mediators or confounds, influencing greater involvement, more related activities, and

healthier lifestyle.

Finally, perceived benefits of participating in social movements may also play a key

mediating role in the impact of involvement on health outcomes. As previously identified by

Gomes (1992), some of the most commonly perceived benefits of involvement – social cohesion

and a sense of community, feelings of accomplishment, and the actualization of goal SOCIAL MOVEMENTS AND HEALTH 41

achievement and success – contribute to one’s level of health as well, particularly outcomes such

as emotional and mental health.

Limitations and Future Directions

Several limitations in the current study are worth noting. First, all measures used to assess

social movement involvement and behaviors were created by the author for the specific purposes

of the study. While they were developed based on supporting literature and internal consistency

alpha coefficients were high, these measures could be further refined to better measure these constructs.

Within the Social Movement Assessment Scale, the “none of the above” option was especially problematic. As previously discussed, responses to this item were indeterminable as to whether the participant answered items about another movement not mentioned or whether they do not perceive themselves to be involved in any social movement. More accurate identification of these two possibilities would have allowed the author to examine the portion of participants who do not consider themselves to be involved in any social movements, thus establishing base rates. Fortunately, something can be learned from the information that is available. The varying sample sizes reporting for each social movement sheds light on the social movements that are more commonly endorsed by U.S. citizens and those that may be especially crucial to focus on in future research. For example, within the general adult sample, only 11 people selected this “none

of the above” category, indicating that a small percentage of the original sample did not identify

with any of the movements listed. In the college student sample, only 9 students chose this

option. This is promising for Robinson’s proposed social movements of relative interest in

promoting health, as it seems most individuals report to being at least somewhat involved in one

or more of the theorized health-promoting movements. This scale could also be potentially SOCIAL MOVEMENTS AND HEALTH 42

improved by including other social movements not discussed in Robinson’s paper that may be

important. To improve the measure’s divergent validity, other movements that would not be

hypothesized to be related to health could also be added.

The Social Movement Involvement Inventory Survey, which measured involvement

level, may require further development. While items derived from original measures were altered

to fit the activities of more current generations and encompass more social movements, it would

benefit from further validation in other samples. Additionally, more items could be added to

explore the construct of involvement, potentially adding items specific to different social movements or other general activities. Qualitative research might also be helpful in development

of this measure.

One indicator of potentially flawed measurement of social movement-related behaviors in

the IBI was the high correlation between theorized individual behaviors and the six items meant

to act as control items. These items were positive in nature and suggest socially desirable

responding among participants. Better control items should be developed to support divergent

validity. Additionally, the items on this measure may not accurately assess for confounds. While

items were meant to measure how often behaviors are done for social movement purposes only,

they may not offer enough distinction from behaviors done for the sake of health or behaviors

associated with one’s values. Future researchers may choose to make the items more explicitly

related to social movement purposes and may choose to extend beyond only the behaviors

proposed by Robinson (2010) to strengthen this measure. A latent class analyses might help; if

the behaviors group into the social movements as proposed by Robinson (2010), this measure

would be further validated. In general, adding other potential behaviors that may influence health

would allow for greater validity (e.g., walking your dog daily, avoiding plastic bottled SOCIAL MOVEMENTS AND HEALTH 43 beverages). Ecological Momentary Assessment (EMA) might also be a useful tool to assess for these behaviors objectively. This would allow individuals to report on these theorized behaviors in the moment as opposed to utilizing retrospective self-report.

As previously mentioned, it is also possible that the relationships examined in the current study occurred in the opposite temporal or causal direction, meaning that people who are healthier tend to be more involved in social movements and activities. Therefore, future longitudinal studies and prospective and experimental designs would be beneficial to explore the directionality and causality of these relationships.

To expand this model, future studies should look at social movement involvement’s associations with other holistic health outcomes and should explore other potential mediators, including but not limited to values, positive personality traits, and perceived benefits of involvement such as social cohesion and feelings of meaningfulness. These possibilities may prove to be crucial in social movements’ impact on health outcomes and may add to the long list of benefits of being more involved, thus substantiating this construct as a useful prevention and intervention tool.

Conclusions

Social movements are a particularly relevant intervention strategy for health promotion, as many of the causes of poor health and overweight status involve the current social system that many activists want to change. Social and environmental issues in agriculture, transportation, exercise, work demands, and food systems have a major influence in how Americans live. As argued by Gusfield (1981), industrialized societies are prone to mobilizing people to change the system due to large-scale organizational alienation. The very flaws in our society that induce alienation, low morale, and poor health, are the very same flaws that motivate individuals to SOCIAL MOVEMENTS AND HEALTH 44 make change. Thus, improvement of these cultural impediments to living healthfully could be a potential remedy to poor health, and social movement agendas are in a perfect position to play a role in that improvement.

This study provides novel, substantial support for social movements as a viable stealth intervention. Encouraging involvement in these movements and activities not only has a positive influence on health, as evidenced by the current findings, but also promotes the betterment of mankind. People’s values of making the world or their community a better place underlie these movements in some way or another, and tapping into and further encouraging those values can have tremendous benefits. The results of this study warrants continued research on other potential mechanisms and beneficial outcomes of social movement involvement, as there is undoubtedly much more to learn.

SOCIAL MOVEMENTS AND HEALTH 45

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APPENDIX A. MEASURES

A. Demographic Questionnaire

1. What is your gender? a. Male b. Female 2. What is your age? ___ 3. What is your race/ethnicity? a. African American b. Asian c. Caucasian d. Hispanic e. Middle Eastern f. Other 4. What is the highest level of education that you have obtained? a. Less than high school b. High school c. Some college or university d. Bachelors degree e. Graduate level training 5. (MTurk sample only): What is your annual household income? a. $12,000 or less b. $12,000 to $18,000 c. $18,000 to $25,000 d. $25,000 to $50,000 e. $50,000 to $75,000 f. $75,000 to $100,000 g. $100,000 or more 6. (SONA sample only): Which economic class would you consider your family to be in? a. Lower b. Lower-middle c. Middle d. Upper-middle e. Upper 7. What is your height in feet? ___ 8. What is your weight in pounds? ___ 9. On a scale of 1 being extremely liberal and 7 being extremely conservative, where do you consider your political identification to be? (scale of 1 through 7) 10. What is your relationship status? a. Single b. Married c. Divorced d. Widowed 11. What is your current employment status? a. Part-time SOCIAL MOVEMENTS AND HEALTH 58

b. Full-time c. Unemployed d. Student e. Other

B. Social Movement Assessment Scale

For each of the following social causes and movements, please select how important you think it is and how actively involved you perceive yourself to be on a scale from 0 (not important/involved) to 4 (extremely important/involved).

0 1 2 3 4 Not important or Somewhat Neutral Mostly important Extremely involved important or importance or or involved important or involved average involved involvement

1. I think equality (gender, race, sexual orientation, etc.), improving workers’ rights, and improving the well-being of people living in poverty (human rights/social justice) is important. 2. I am actively involved in the human rights/social justice cause. 3. I think supporting one’s own national economy and culture (patriotism, nationalism) is important. 4. I am actively involved in the patriotism/nationalism cause. 5. I think buying and using fewer material possessions and reducing the influence of advertising (anti-consumerism) is important. 6. I am actively involved in the anti-consumerism cause. 7. I think improving the safety and beauty of my neighborhood to increase quality of life and property values (community improvement) is important. 8. I am actively involved in the community improvement cause. 9. I think organic farming, eating locally, recycling, improving air quality, conserving resources, and preventing global warming (environmental sustainability) is important. 10. I am actively involved in environmental sustainability. 11. I think reducing youth and adult involvement in crime (crime prevention) is important. 12. I am actively involved in the crime prevention cause. 13. I think reducing inhumane treatment of animals (animal protection) is important. 14. I am actively involved in the animal protection cause. 15. I think raising awareness and funding for charitable causes such as cancer and community organizations (cause-related fundraising) is important. 16. I am actively involved in cause-related fundraising. 17. I think freeing our nation from dependence on foreign oil (energy independence) is important. 18. I am actively involved in the energy independence cause. SOCIAL MOVEMENTS AND HEALTH 59

19. I think reducing risk of diseases from food and harmful additives or other contaminants (food safety) is important. 20. I am actively involved in the food safety cause. 21. I think participation in political campaigns or other political causes (political action) is important. 22. I am actively involved in political action. 23. I think protecting the nation from foreign countries and supporting a strong military (national security) is important. 24. I am actively involved in the national security cause. 25. I think resisting multi-national corporations (e.g., companies who import goods from factors and business in multiple countries) (anti-globalization) is important. 26. I am actively involved in the anti-globalization movement. You may think multiple social causes are important, and you may be highly involved in more than one. Please choose one of the following causes that you consider to be your highest priority in terms of personal involvement:

Human rights/social justice Patriotism, nationalism Anti-consumerism Community improvement Environmental sustainability Crime prevention Animal protection Cause-related fundraising Energy independence Food safety Political action National security Anti-globalization None of the above

C. Social Movement Inventory of Involvement Scale The following is a list of community and political activities that people can get involved in. For each of these activities, please use the following scale to indicate whether, in the last year you did this for your prioritized social cause: 0 1 2 3 4 never once or twice a few times a fair bit a lot

1. Contributed time or money to a group that promotes your social cause 2. Read a website, magazine, or other publication related to your social cause 3. Watched a video, movie, or television show on your social cause 4. Attended a club, meeting, or other group-based event for your social cause 5. Bought something because you thought it supported your social cause 6. Had a serious discussion about your social cause with your family, friends, coworkers, etc.

Please answer yes or no to the following questions.

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1. I would be willing to pay higher prices (on products, through taxes, etc.) to support my social cause 2. Are you a member of any group whose main aim is to promote your social cause? 3. Have you ever signed a petition in support of your social cause? 4. Have you ever donated money to a group pertaining to your social cause? 5. Have you ever boycotted or avoided buying something because you felt that it was against your social cause? 6. Have you ever voted for a candidate in an election at least in part because he or she was in favor of your social cause?

D. Individual Behavior Inventory

Please indicate how often you do the following in a typical week. We are interested in how often you make a conscious effort to do any of the following behaviors.

1 2 3 4 5 6 7 Never Rarely (less Once a 2-3 times Once a 2-3 times Almost than once a month per month week per week every day month)

1. Make a meal choice that involves eating less meat. 2. Avoid processed and packaged foods. 3. Choose locally grown foods or avoid foods that have been transported over long distances. 4. Walk for leisure, exercise, or transportation. 5. Bike for leisure, exercise, or transportation. 6. Use public transportation 7. Eat organic foods. 8. Eat foods from farmers’ markets, local farmers, CSA, or other sellers who follow fair trade practices 9. Deliberately spend less time using media such as TV, the internet, etc. 10. Avoid food from multinational corporations (e.g., fast food, large distributors) 11. Avoid imported food 12. Make a meal choice that involves eating fewer animal products 13. Purchase fewer highly advertised foods (i.e., fast food, snack foods, and convenience foods) 14. Participate in walk-a-thons, 5Ks, or other activity-related fundraisers 15. Participate in a school-related or community program aimed at helping at-risk youth 16. Participate in a neighborhood watch program 17. Participate in garden, clean-up, and other home and neighborhood improvement activities 18. Spend time outdoors in recreation and neighborhood social activities (e.g., community gardening) 19. Do door-to-door campaigning and other political demonstrations (e.g., protests) 20. Engage in craft-related hobbies 21. Go out with friends or family to the movies 22. Go to a coffee shop SOCIAL MOVEMENTS AND HEALTH 61

23. Read books for leisure 24. Go to the public library

E. Dietary Screener Questionnaire

1) During the past month, how often did you eat hot or cold cereals? Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

2) During the past month, what kind of cereal did you usually eat? Print cereal. ______

3) If there was another kind of cereal that you usually ate during the past month, what kind was it? Print cereal, if none leave black. ______

4) During the past month, how often did you have any milk (either to drink or on cereal)? Include regular milks, chocolate or other flavored milks, lactose-free milk, buttermilk. Please no not include soy milk or small amounts of milk in coffee or tea. Never 5-6 times per week 1 time the last month 1 time per day 2-3 times last month 2-3 times per day 1 time per week 4-5 times per day 2 times per week 6 or more times per day 3-4 times per week

5) During the past month, what kind of milk did you usually drink? Whole or regular milk 2% fat or reduced-fat milk 1%, ½%, or low-fat milk Fat-free, skim or nonfat milk Soy milk Other kind of milk (please specify)

6) During the past month, how often did you drink regular soda or pop that contains sugar? Do not include diet soda. Never 5-6 times per week 1 time the last month 1 time per day 2-3 times last month 2-3 times per day 1 time per week 4-5 times per day 2 times per week 6 or more times per day 3-4 times per week

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7) During the past month, how often did you drink 100% pure fruit juice such as orange, mango, apple, grape, and pineapple juices? Do not include fruit-flavored drinks with added sugar or fruit juices you made at home and added sugar to. Never 5-6 times per week 1 time the last month 1 time per day 2-3 times last month 2-3 times per day 1 time per week 4-5 times per day 2 times per week 6 or more times per day 3-4 times per week

8) During the past month, how often did you drink coffee or tea that had sugar or honey added to it? Include coffee and tea you sweetened yourself and presweetened tea and coffee drinks such as Arizona Iced Tea and Frappuccino. Do not include artificially sweetened coffee or diet tea. Never 5-6 times per week 1 time the last month 1 time per day 2-3 times last month 2-3 times per day 1 time per week 4-5 times per day 2 times per week 6 or more times per day 3-4 times per week

9) During the past month, how often did you drink sweetened fruit drinks, sports or energy drinks, such as Kool-Aid, lemonade, Hi-C, cranberry drink, Gatorade, Red Bull or Vitamin Water? Include fruit juices you made at home and added sugar to. Do not include diet drinks or artificially sweetened drinks. Never 5-6 times per week 1 time the last month 1 time per day 2-3 times last month 2-3 times per day 1 time per week 4-5 times per day 2 times per week 6 or more times per day 3-4 times per week

10) During the past month, how often did you eat fruit? Include fresh, frozen or canned fruit. Do not include juices. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

11) During the past month, how often did you eat a green leafy or lettuce salad, with or without other vegetables? Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day SOCIAL MOVEMENTS AND HEALTH 63

2 times per week

12) During the past month, how often did you eat any kind of fried potatoes, including French fries, home fries, or hash brown potatoes? Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

13) During the past month, how often did you eat any other kind of potatoes, such as baked, boiled, mashed potatoes, sweet potatoes, or potato salad? Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

14) During the past month, how often did you eat refried beans, baked beans, beans in soup, pork and beans or any other type of cooked dried beans? Do not include green beans. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

15) During the past month, how often did you eat brown rice or other cooked whole grains, such as bulgur, cracked wheat, or millet? Do not include white rice. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

16) During the past month, not including what you just told me about (green salads, potatoes, cooked dried beans), how often did you eat other vegetables? Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

17) During the past month, how often did you have Mexican-type salsa made with tomato? Never 3-4 times per week 1 time the last month 5-6 times per week SOCIAL MOVEMENTS AND HEALTH 64

2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

18) During the past month, how often did you eat pizza? Include frozen pizza, fast food pizza, and homemade pizza. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

19) During the past month, how often did you have tomato sauces such as with spaghetti or noodles or mixed into foods such as lasagna? Do not include tomato sauce on pizza. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

20) During the past month, how often did you eat any kind of cheese? Include cheese as a snack, cheese on burgers, sandwiches, and cheese in foods such as lasagna, quesadillas, or casseroles. Do not include cheese on pizza. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

21) During the past month, how often did you eat red meat, such as beef, pork, ham, or sausage? Do not include chicken, turkey or seafood. Include red meat you had in sandwiches, lasagna, stew, and other mixtures. Red meats may also include veal, lamb, and any lunch meats made with these meats. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

22) During the past month, how often did you eat any processed meat, such as bacon, lunch meats, or hot dogs? Include processed meats you had in sandwiches, soups, pizza, casseroles, and other mixtures. Processed meats are those preserved by smoking, curing, or salting, or by the addition of preservatives. Examples are: ham, bacon, pastrami, salami, sausages, bratwursts, frankfurters, hot dogs, and spam. Never 3-4 times per week SOCIAL MOVEMENTS AND HEALTH 65

1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

23) During the past month, how often did you eat whole grain bread including toast, rolls and in sandwiches? Whole grain breads include whole wheat, rye, oatmeal and pumpernickel. Do not include white bread. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

24) During the past month, how often did you eat chocolate or any other types of candy? Do not include sugar-free candy. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

25) During the past month, how often did you eat doughnuts, sweet rolls, Danish, muffins, pan dulce, or pop-tarts? Do not include sugar-free items. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

26) During the past month, how often did you eat cookies, cake, pie or brownies? Do not include sugar-free kinds. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

27) During the past month, how often did you eat ice cream or other frozen desserts? Do not include sugar-free kinds. Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week SOCIAL MOVEMENTS AND HEALTH 66

28) During the past month, how often did you eat popcorn? Never 3-4 times per week 1 time the last month 5-6 times per week 2-3 times last month 1 time per day 1 time per week 2 or more times per day 2 times per week

F. International Physical Activity Questionnaire We are interested in finding out about the kinds of physical activities that people do as part of their everyday lives. The questions will ask you about the time you spent being physically active in the last 7 days. Please answer each question even if you do not consider yourself to be an active person. Please think about the activities you do at work, as part of your house and yard work, to get from place to place, and in your spare time for recreation, exercise or sport.

Think about all the vigorous and moderate activities that you did in the last 7 days. Vigorous physical activities refer to activities that take hard physical effort and make you breathe much harder than normal. Moderate activities refer to activities that take moderate physical effort and make you breathe somewhat harder than normal.

PART 1: JOB-RELATED PHYSICAL ACTIVITY The first section is about your work. This includes paid jobs, farming, volunteer work, course work, and any other unpaid work that you did outside your home. Do not include unpaid work you might do around your home, like housework, yard work, general maintenance, and caring for your family. These are asked in Part 3.

1. Do you currently have a job or do any unpaid work outside your home? ___Yes ___No Skip to PART 2: TRANSPORTATION

The next questions are about all the physical activity you did in the last 7 days as part of your paid or unpaid work. This does not include traveling to and from work.

2. During the last 7 days, on how many days did you do vigorous physical activities like heavy lifting, digging, heavy construction, or climbing up stairs as part of your work? Think about only those physical activities that you did for at least 10 minutes at a time. _____ days per week _____No vigorous job-related physical activity Skip to question 4

3. How much time did you usually spend on one of those days doing vigorous physical activities as part of your work? _____ hours per day _____ minutes per day

SOCIAL MOVEMENTS AND HEALTH 67

4. Again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate physical activities like carrying light loads as part of your work? Please do not include walking. _____ days per week _____No moderate job-related physical activity Skip to question 6

5. How much time did you usually spend on one of those days doing moderate physical activities as part of your work? _____ hours per day _____ minutes per day

6. During the last 7 days, on how many days did you walk for at least 10 minutes at a time as part of your work? Please do not count any walking you did to travel to or from work. _____ days per week _____No job-related walking Skip to PART 2: TRANSPORTATION

7. How much time did you usually spend on one of those days walking as part of your work? _____ hours per day _____ minutes per day

PART 2: TRANSPORTATION PHYSICAL ACTIVITY These questions are about how you traveled from place to place, including to places like work, stores, movies, and so on.

8. During the last 7 days, on how many days did you travel in a motor vehicle like a train, bus, car, or tram? _____ days per week _____No traveling in a motor vehicle Skip to question 10

9. How much time did you usually spend on one of those days traveling in a train, bus, car, tram, or other kind of motor vehicle? _____ hours per day _____ minutes per day Now think only about the bicycling and walking you might have done to travel to and from work, to do errands, or to go from place to place.

10.During the last 7 days, on how many days did you bicycle for at least 10 minutes at a time to go from place to place? _____ days per week _____No bicycling from place to place Skip to question 12

11.How much time did you usually spend on one of those days to bicycle from place to place? _____ hours per day _____ minutes per day

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12.During the last 7 days, on how many days did you walk for at least 10 minutes at a time to go from place to place? _____ days per week _____No walking from place to place Skip to PART 3: HOUSEWORK, HOUSE MAINTENANCE, AND CARING FOR FAMILY

13.How much time did you usually spend on one of those days walking from place to place? _____ hours per day _____ minutes per day

PART 3: HOUSEWORK, HOUSE MAINTENANCE, AND CARING FOR FAMILY This section is about some of the physical activities you might have done in the last 7 days in and around your home, like housework, gardening, yard work, general maintenance work, and caring for your family.

14.Think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do vigorous physical activities like heavy lifting, chopping wood, shoveling snow, or digging in the garden or yard? _____ days per week _____No vigorous activity in garden or yard Skip to question 16

15.How much time did you usually spend on one of those days doing vigorous physical activities in the garden or yard? _____ hours per day _____ minutes per day

16.Again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate activities like carrying light loads, sweeping, washing windows, and raking in the garden or yard? _____ days per week _____No moderate activity in garden or yard Skip to question 18

17.How much time did you usually spend on one of those days doing moderate physical activities in the garden or yard? _____ hours per day _____ minutes per day

18.Once again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate activities like carrying light loads, washing windows, scrubbing floors and sweeping inside your home? _____ days per week _____No moderate activity inside home Skip to PART 4: RECREATION, SPORT AND LEISURE-TIME PHYSICAL ACTIVITY

19.How much time did you usually spend on one of those days doing moderate physical activities inside your home? SOCIAL MOVEMENTS AND HEALTH 69

_____ hours per day _____ minutes per day

PART 4: RECREATION, SPORT, AND LEISURE-TIME PHYSICAL ACTIVITY This section is about all the physical activities that you did in the last 7 days solely for recreation, sport, exercise or leisure. Please do not include any activities you have already mentioned.

20.Not counting any walking you have already mentioned, during the last 7 days, on how many days did you walk for at least 10 minutes at a time in your leisure time? _____ days per week _____No walking in leisure time Skip to question 22

21. How much time did you usually spend on one of those days walking in your leisure time? _____ hours per day _____ minutes per day

22. Think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do vigorous physical activities like aerobics, running, fast bicycling, or fast swimming in your leisure time? _____ days per week _____No vigorous activity in leisure time Skip to question 24

23. How much time did you usually spend on one of those days doing vigorous physical activities in your leisure time? _____ hours per day _____ minutes per day

24. Again, think about only those physical activities that you did for at least 10 minutes at a time. During the last 7 days, on how many days did you do moderate physical activities like bicycling at a regular pace, swimming at a regular pace, and doubles tennis in your leisure time? _____ days per week _____No moderate activity in leisure time Skip to PART 5: TIME SPENT SITTING

25. How much time did you usually spend on one of those days doing moderate physical activities in your leisure time? _____ hours per day _____ minutes per day

PART 5: TIME SPENT SITTING The last questions are about the time you spend sitting while at work, at home, while doing course work and during leisure time. This may include time spent sitting at a desk, visiting friends, reading or sitting or lying down to watch television. Do not include any time spent sitting in a motor vehicle that you have already told me about. SOCIAL MOVEMENTS AND HEALTH 70

26. During the last 7 days, how much time did you usually spend sitting on a weekday? _____ hours per day _____ minutes per day

27. During the last 7 days, how much time did you usually spend sitting on a weekend day? _____ hours per day _____ minutes per day

G. RAND 36-Iten Health Survey

1. In general, would you say your health is: a. Excellent b. Very good c. Good d. Fair e. Poor

2. Compared to one year ago, how would you rate your health in general now? a. Much better now than one year ago b. Somewhat better now than one year ago c. About the same d. Somewhat worse than one year ago e. Much worse now than one year ago

The following items are about activities you might do during a typical day. Does your health now limit you in these activities? If so, how much?

1 2 3 Yes, Limited a Lot Yes, Limited a Little No, Not Limited at All

3. Vigorous activities, such as running, lifting heavy objects, participating in strenuous sports

4. Moderate activities, such as moving a table, pushing a vacuum cleaner, bowling, or playing golf

5. Lifting or carrying groceries

6. Climbing several flights of stairs SOCIAL MOVEMENTS AND HEALTH 71

7. Climbing one flight of stairs

8. Bending, kneeling, or stooping

9. Walking more than a mile

10. Walking several blocks

11. Walking one block

12. Bathing or dressing yourself

During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of your physical health?

Yes No

13. Cut down the amount of time you spent on work or other activities 1 2

14. Accomplished less than you would like 1 2

15. Were limited in the kind of work or other activities 1 2

16. Had difficulty performing the work or other activities (for example, it took 1 2 extra effort)

During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious)?

Yes No

17. Cut down the amount of time you spent on work or other activities 1 2

18. Accomplished less than you would like 1 2

19. Didn't do work or other activities as carefully as usual 1 2

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20. During the past 4 weeks, to what extent has your physical health or emotional problems interfered with your normal social activities with family, friends, neighbors, or groups? a. Not at all b. Slightly c. Moderately d. Quite a bit e. Extremely

21. How much bodily pain have you had during the past 4 weeks? a. None b. Very mild c. Mild d. Moderate e. Severe f. Very severe

22. During the past 4 weeks, how much did pain interfere with your normal work (including both work outside the home and housework)? a. Not at all b. A little bit c. Moderately d. Quite a bit e. Extremely

These questions are about how you feel and how things have been with you during the past 4 weeks. For each question, please give the one answer that comes closest to the way you have been feeling. How much of the time during the past 4 weeks . . .

A Good All of Most Bit of Some A Little None the of the the of the of the of the Time Time Time Time Time Time

23. Did you feel full of 1 2 3 4 5 6 pep?

24. Have you been a 1 2 3 4 5 6 very nervous person?

25. Have you felt so 1 2 3 4 5 6 down in the dumps that nothing could cheer you up? SOCIAL MOVEMENTS AND HEALTH 73

26. Have you felt calm 1 2 3 4 5 6 and peaceful?

27. Did you have a lot 1 2 3 4 5 6 of energy?

28. Have you felt 1 2 3 4 5 6 downhearted and blue?

29. Did you feel worn 1 2 3 4 5 6 out?

30. Have you been a 1 2 3 4 5 6 happy person?

31. Did you feel tired? 1 2 3 4 5 6

32. During the past 4 weeks, how much of the time has your physical health or emotional problems interfered with your social activities (like visiting with friends, relatives, etc.)? a. All of the time b. Most of the time c. Some of the time d. A little of the time e. None of the time

How TRUE or FALSE is each of the following statements for you.

Definitely Mostly Don't Mostly Definitely True True Know False False

33. I seem to get sick a 1 2 3 4 5 little easier than other people

34. I am as healthy as 1 2 3 4 5 anybody I know

35. I expect my health 1 2 3 4 5 to get worse SOCIAL MOVEMENTS AND HEALTH 74

36. My health is 1 2 3 4 5 excellent

H. Diabetes Symptom Checklist – Revised (DSC-R) People with diabetes can experience various discomforting physical and mental symptoms related to their disease. In order to know how much you are troubled by particular symptoms, we would like you to fill in this questionnaire. Please circle whether you have experienced the symptom or not in the past month, today included. If you circle “yes” then indicate to what extent the symptom listed has caused you discomfort by circling the number that most closely reflects your experience. If a symptom did NOT occur, please circle “No” in the column “DID SYMPTOM OCCUR” How much trouble have these symptoms given you over the last month? [Scale for each item: Did symptom occur? (No, Yes ) The symptom did occur and was troublesome to me. (1 not at all, 2 a little, 3 moderately, 4 very, 5 extremely)] 1. Lack of energy? 2. Aching calves when walking? 3. Numbness (loss of sensation) in feet? 4. An overall sense of fatigue? 5. Shortness of breath at night? 6. Sleepiness or drowsiness? 7. Difficulty concentrating? 8. Moodiness? 9. Numbness (loss of sensation) in the hands? 10. Persistently blurry vision (even with glasses on)? 11. Tingling sensations in the limbs at night? 12. Very thirsty? 13. Palpitations or pounding in the heart region? 14. Deteriorating vision? 15. Burning pain in the calves at night? 16. Dry mouth? 17. Increasing fatigue during the course of the day? 18. Flashes or black spots in the field of vision? 19. Irritability just before a meal? 20. Fatigue in the morning when getting up? 21. Shooting pain in the legs? 22. Alternating clear and blurred vision? 23. Frequent need to empty your bladder? 24. Pains in the chest or heart region? 25. Burning pain in the legs during the day? 26. Tingling or prickling sensations in the hands or fingers? SOCIAL MOVEMENTS AND HEALTH 75

27. Easily irritated or annoyed? 28. Sudden deterioration of vision? 29. Odd feeling in the (lower) legs or feet when touched? 30. Shortness of breath during physical exertion? 31. Fuzzy feelings in your head (difficulty thinking clearly)? 32. Drinking a lot (all sorts of beverages)? 33. Difficulty paying attention? 34. Tingling or prickling sensations in the lower legs?

SOCIAL MOVEMENTS AND HEALTH 76

APPENDIX B. HSRB FORM FOR ORIGINAL APPLICATION

SOCIAL MOVEMENTS AND HEALTH 77

APPENDIX C. HSRB FORM FOR MODIFICATION REQUEST

SOCIAL MOVEMENTS AND HEALTH 78

APPENDIX D. INFORMED CONSENT (ADULT SAMPLE)

SOCIAL MOVEMENTS AND HEALTH 79

APPENDIX E. INFORMED CONSENT (COLLEGE SAMPLE)

SOCIAL MOVEMENTS AND HEALTH 80

APPENDIX F. TABLES

Table 1.

Social and ideological movements and/or causes with behavioral goals that overlap with obesity prevention.

Movements/causes Individual-level behaviors Environmental sustainability/climate change Eat more fresh fruits and vegetables. Eat less Preventing global warming and climate meat, particularly beef. Eat less processed change, sustainable agriculture, organic and packaged foods. Eat fewer foods farming, slow food, eating locally (locavores), transported over long distances. agrarianism, recycling/waste reduction, Less automobile use, more walking, bicycling, improving air quality, conserving water and mass transit use. Food safety Eat less meat, particularly beef, and less fast Reducing risk of infectious diseases from food food restaurant food. Eat more organically (e.g., Escherichia coli O157:H7, Bovine and locally grown fruits and vegetables. Spongiform Encephalopathy/mad cow disease) and potentially harmful additives and/or contaminants (e.g., toxic additives in imported food) Human rights/social justice Eat less fast food restaurant food. Eat less Improving workers’ rights, poor working meat. Eat more fruits and vegetables from conditions in fast food industry and suppliers farmers’ markets, local farmers, CSA, (e.g., slaughterhouses, farm workers); food following fair trade practice. justice, increasing access to more healthful Watch less media to reduce exposure to foods such as fresh fruits and vegetables in negative racial/ethnic gender stereotypes. low-income areas; women’s rights, families rights; fair trade; reducing racial/ethnic and gender discrimination from stereotypes in media Antiglobalization Eat more locally grown/domestically grown Farmers, labor unions, human rights groups, food. Eat less fast food and processed foods nationalists, etc. resisting corporate and and beverages from multinational cultural globalization and WTO and World corporations. Eat less imported foods. Bank free trade policies Animal protection Less beef, pork, poultry, dairy, and fish Reducing inhumane treatment of animals consumption, more vegetarianism during farming and slaughter Anticonsumerism Less purchase and consumption of heavily Reducing consumer culture and/or the advertised and marketed fast food and snack influence of consumer culture foods/convenience foods. Less television watching and other screen media use. Cause-related fundraising Walk-a-thons, door-to-door fundraising, Raising awareness and funding for charitable training and participation in distance and/or SOCIAL MOVEMENTS AND HEALTH 81 causes such as cancer or AIDS research and endurance races, long distance walks and services (e.g., Team-in-Training) bike rides, etc. Energy independence/reduce dependence on Less automobile use, more walking, bicycling, foreign oil and mass transit. Eat more locally grown Freeing nations from dependence on foreign oil produce and less meat and processed and packaged foods transported over long distances. Youth violence and crime prevention Participating in after school sports programs Reducing youth involvement in gangs and for at-risk youth (e.g., midnight basketball crime leagues), or as mentors or coaches; participating in community policy/neighborhood watch programs. Less television watching and other screen media use. Community safety, beautification, and traffic Participating in gardening, clean-up, reduction playground building, home and Improving safety and beauty to increase neighborhood improvement and repair, and neighborhood quality of life and property other community beautification projects. values Spend more time outdoors in recreation and neighborhood social activities. Political action Door-to-door campaigning or petition drives, As part of political campaigns or in support of picketing, public demonstrations, marches the movements listed and other specific causes Patriotism, nationalism Eat more locally grown/domestically grown Supporting one’s own national economy and food. Eat less fast food and processed foods culture and beverages from multinational corporations. Eat less imported foods. National security Regular participation in physical activity to Protecting the nation’s security from foreign maintain physical fitness countries and terrorists with a strong military, Eat more locally grown produce and less meat. protected food supply, and food and energy Eat less mass produced fast food and independence/self-sufficiency processed foods and beverages from multinational corporations. Eat less imported foods. Eat less processed and packaged foods transported over long distances. Less automobile use, more walking, bicycling, and mass transit. Note: Adapted from “Save the World, Prevent Obesity: Piggybacking on Existing Social and Ideological Movements,” by Robinson, 2010. SOCIAL MOVEMENTS AND HEALTH 82

Table 2.

Demographic make-up of the general adult sample.

Factors Mean (SD) Age 36.21 (11.74) BMI 27.83 (7.58) Percent (Frequency) Gender Male 35.4 (73) Female 63.6 (131) Other 1.0 (2) Race African American 4.9 (10) Asian 3.4 (7) Caucasian 84.0 (173) Hispanic 7.3 (15) Middle Eastern 0 (0) Other 0.5 (1) Education Less than high school 1.5 (3) High school 10.2 (21) Some college 26.7 (55) 2 year degree 13.6 (28) 4 year degree 34.0 (70) Graduate level training 14.1 (29) Household income $12,000 or less 11.7 (24) $12,000 to $18,000 6.8 (14) $18,000 to $25,000 11.2 (23) $25,000 to $50,000 26.2 (54) $50,000 to $75,000 18.9 (39) $75,000 to $100,000 16.5 (34) $100,000 or more 8.7 (18) Note: N = 195 SOCIAL MOVEMENTS AND HEALTH 83

Table 3. Demographic make-up of the college student sample.

Factors Mean (SD) Age 19.34 (1.54) BMI 24.82 (5.14) Percent (Frequency) Gender Male 23.5 (46) Female 76.5 (150) Other 0 (0) Race African American 9.2 (18) Asian 2.6 (5) Caucasian 81.1 (159) Hispanic 3.6 (7) Middle Eastern 1.0 (2) Other 2.6 (5) Socioeconomic status Lower class 4.1 (8) Lower-middle class 13.3 (26) Middle class 57.1 (112) Middle-upper class 24.0 (47) Upper class 1.5 (3) Note: N = 196, BMI N = 193 SOCIAL MOVEMENTS AND HEALTH 84

Table 4. Pearson correlations with demographic variables and outcome variables in the general adult sample.

Outcome variable Age Education Income

Fiber -0.10 -0.03 -0.00

Whole grain -0.07 0.10 0.06

FV and legume (no fried potatoes) 0.07 -0.04 0.04

Added sugar 0.05 -0.11 -0.07

Calcium -0.21** -0.04 0.06

Dairy -0.20** 0.00 0.13

Daily MET minutes -0.03 0.05 0.15*

Physical functioning -0.15* 0.14* 0.30**

Role capabilities due to physical health -0.24** 0.06 0.26**

Role capabilities due to emotional health 0.08 0.15* 0.11

Energy level -0.05 0.13 0.19**

Emotional well-being 0.11 0.08 0.16*

Social functioning 0.01 0.17* 0.21**

Freedom from pain -0.21** 0.10 0.17* SOCIAL MOVEMENTS AND HEALTH 85

General health perception -0.13 0.12 0.26**

Diabetes symptoms 0.09 -0.24** -0.17*

Note: N = 192 for dietary variables (two adults identified as “other” gender, and one did not report age; binary gender and age are requisites for dietary estimate computation); N = 190 for MET minutes (five adults’ IPAQ data was undeterminable and was marked as “missing”); N = 195 for general health subscales and diabetes symptoms. All dietary variables are based on log transformed data; daily MET minutes is based on square root transformed data. *p < .05. **p < .01. SOCIAL MOVEMENTS AND HEALTH 86

Table 5. T-tests on demographic variables and outcome variables in the general adult sample.

Outcome variable Overall Gender Race sample M (SD) Male Female Caucasian Non-Cauc. M (SD) M (SD) M (SD) M (SD) Fibera 1.16 (.17) 1.25 (.18) 1.12 (.14) 1.15 (.15) 1.21 (.24)

Whole graina -.34 (.46) -.21 (.50) -.41 (.43) -.36 (.45) -.28 (.55)

FV and legume (no fried .37 (.21) .44 (.21) .34 (.20) .36 (.20) .44 (.23) potatoes)a Added sugara 1.02 (.36) 1.15 (.34) .95 (.35) 1.00 (.37) 1.10 (.33)

Calciuma 2.91 (.22) 3.04 (.23) 2.84 (.18) 2.90 (.22) 2.95 (.24)

Dairya .11 (.29) .24 (.30) .04 (.27) .11 (.29) .13 (.30)

Daily MET minutes 26.83 29.11 25.77 26.56 28.27 (12.65) (14.42) (11.60) (12.51) (13.49) Physical functioning 84.74 85.76 84.49 84.48 86.13 (23.91) (26.49) (22.54) (23.72) (25.26) Role capabilities due to 81.79 84.09 80.32 80.95 86.13 physical health (32.64) (30.58) (33.87) (33.22) (25.26) Role capabilities due to 74.02 79.29 71.65 74.59 70.97 emotional health (38.55) (35.45) (39.63) (38.70) (38.24) Energy levela 53.82 59.02 50.04 52.41 55.00 (23.37) (22.07) (23.24) (23.03) (23.40) Emotional well-being 67.77 69.88 66.93 67.63 68.52 (22.79) (19.85) (24.02) (22.77) (23.23) Social functioning 80.13 84.85 77.95 80.49 78.23 (24.07) (22.63) (24.17) (24.35) (22.81) Freedom from paina 78.41 83.98 75.51 77.38 83.87 (23.19) (22.48) (23.15) (23.35) (21.92) SOCIAL MOVEMENTS AND HEALTH 87

General health perception 67.38 67.35 67.91 66.77 70.65 (22.26) (22.10) (22.00) (22.60) (20.40) Diabetes symptoms .22 (.15) .19 (.17) .23 (.14) .21 (.15) .23 (.17)

Note: N = 192 for dietary variables (two adults identified as “other” gender, and one did not report age; binary gender and age are requisites for dietary estimate computation); N = 190 for MET minutes (five adults’ IPAQ data was undeterminable and was marked as “missing”); N = 193 for general health subscales and diabetes symptoms (two adults’ gender identified as “other” were marked as “missing”); N = 195 for diabetes symptoms. Gender 1 = male, 2 = female; race 1 = Caucasian, 2 = non-Caucasian. All dietary variables are based on log transformed data; daily MET minutes is based on square root transformed data. Unequal variances assumed. a t-test significant for gender at p < .05 level. SOCIAL MOVEMENTS AND HEALTH 88

Table 6. Pearson correlations with demographic variables and outcome variables in the college student sample.

Outcome variable Age Family SES

Fiber -0.00 0.00

Whole grain -0.06 -0.02

FV and legume (no fried potatoes) 0.06 -0.06

Added sugar 0.07 0.00

Calcium -0.09 0.03

Dairy -0.14 0.09

Daily MET minutes -0.02 -0.01

Physical functioning -0.09 -0.03

Role capabilities due to emotional health -0.16* -0.01

Role capabilities due to emotional health -0.06 0.18*

Energy level -0.06 0.11

Emotional well-being -0.02 -0.01

Social functioning 0.03 0.07

Freedom from pain -0.03 -0.14* SOCIAL MOVEMENTS AND HEALTH 89

General health perception -0.13 0.02

Diabetes symptoms 0.13 -0.10

Note: N = 192 for dietary variables, and general health subscales (four students did not complete the DSQ, and four others did not complete the RAND survey, both due to an error with the online survey); N = 194 for MET minutes (two students did not complete the IPAQ due to an error with the online survey); N = 190 for diabetes symptoms (six students did not complete the DSC-R due to an error with the online survey). All dietary variables are based on log transformed data; daily MET minutes is based on square root transformed data; diabetes symptoms variable is based on square root transformed data. *p < .05. SOCIAL MOVEMENTS AND HEALTH 90

Table 7. T-tests on demographic variables and outcome variables in the college student sample.

Outcome variable Overall Gender Race sample M (SD) Male Female Caucasian Non-Cauc. M (SD) M (SD) M (SD) M (SD) Fiber 1.12 (.16) 1.21 (.15) 1.09 (.15) 1.13 (.16) 1.09 (.17)

Whole grain -.35 (.46) -.37 (.43) -.34 (.47) 2.93 (.87) 2.92 (1.10)

FV and legume (no fried .31 (.21) .40 (.16) .28 (.21) .32 (.19) .27 (.26) potatoes)a Added sugarb 1.09 (.23) 1.17 (.22) 1.07 (.24) 1.11 (.23) 1.02 (.24)

Calciuma 2.91 (.22) 3.06 (.26) 2.86 (.18) 2.91 (.22) 2.88 (.22)

Dairy .12 (.28) .31 (.28) .07 (.25) .13 (.28) .08 (.29)

Daily MET minutes 30.78 31.01 30.71 30.95 30.05 (12.41) (13.00) (12.27) (12.11) (13.76) Physical functioning 91.25 91.22 91.26 91.86 88.61 (19.05) (21.40) (18.36) (18.83) (20.06) Role capabilities due to 86.20 93.33 84.01 87.66 79.86 physical healtha (27.76) (20.23) (29.40) (26.10) (33.71) Role capabilities due to 70.14 78.52 67.57 70.73 67.59 emotional healtha (40.93) (35.64) (42.19) (40.31) (44.00) Energy level 49.82 56.00 47.93 49.90 49.44 (19.28) (17.31) (19.51) (19.66) (17.80) Emotional well-being 64.50 70.31 62.72 64.10 66.22 (20.73) (19.55) (20.82) (20.92) (20.09) Social functioning 79.30 85.56 77.38 79.89 76.74 (24.29) (23.68) (24.36) (24.20) (25.38) Freedom from paina 84.14 90.28 82.26 83.53 86.81 (17.31) (14.12) (17.80) (17.74) (15.27) SOCIAL MOVEMENTS AND HEALTH 91

General health perception 67.59 73.02 65.93 67.07 69.87 (19.31) (17.90) (19.48) (19.55) (18.32) Diabetes symptoms .41 (.21) .36 (.18) .43 (.21) .42 (.21) .41 (.20)

Note: N = 192 for dietary variables, and general health subscales (four students did not complete the DSQ, and four others did not complete the RAND survey, both due to an error with the online survey); N = 194 for MET minutes (two students did not complete the IPAQ due to an error with the online survey); N = 190 for diabetes symptoms (six students did not complete the DSC-R due to an error with the online survey). Gender 1 = male, 2 = female; race 1 = Caucasian, 2 = non-Caucasian. All dietary variables are based on log transformed data; daily MET minutes is based on square root transformed data; diabetes symptoms variable is based on square root transformed data. Unequal variances assumed. a t-test significant for gender at p < .05 level. b t-test significant for race at p < .05 level. SOCIAL MOVEMENTS AND HEALTH 92

Table 8. Social movements endorsed by both sample participants.

General adult sample College student sample Social movement n Percent n Percent Human rights/social justice 56 28.7 55 27.6 Anti-consumerism 6 3.1 0 0 Environmental sustainability 34 17.4 14 7.0 Animal protection 31 15.9 35 17.6 Energy independence 1 0.5 2 1.0 Political action 5 2.6 5 2.5 Anti-globalization 3 1.5 1 0.5 Patriotism/nationalism 6 3.1 5 2.5 Community improvement 10 5.1 20 10.1 Crime prevention 13 6.7 22 11.1 Cause-related fundraising 4 2.1 16 8.0 Food safety 7 3.6 7 3.5 National security 19 9.7 17 8.5

SOCIAL MOVEMENTS AND HEALTH 93

Table 9

Hierarchical multiple regression analyses of frequency of individual behaviors predicting health outcomes within the general adult sample.

Step/predictor R2 ∆R2 ∆F B SE B β t

Criterion: FV Step 1 .06 .06 11.09** Gender -0.10 .03 -.24 -3.33** Step 2 .19 .14 32.54** Gender -.11 .03 -.25 -3.82** FIB .07 .01 .37 5.70**

Criterion: Fiber Step 1 .16 .16 35.62** Gender -.14 .02 -.40 -5.97** Step 2 .25 .09 22.67** Gender -.14 .02 -.41 -6.48** FIB .05 .01 .30 4.76**

Criterion: Whole grains Step 1 .04 .04 8.16** Gender -.20 .07 -.20 -2.86** Step 2 .11 .06 13.43** Gender -.21 .07 -.21 -3.09** FIB .11 .03 .25 -3.67**

Criterion: MET minutes Step 1 .02 .02 4.18* Income 1.08 .53 .15 2.05* Step 2 .25 .22 55.17** Income .85 .47 .12 1.82 FIB 5.56 .75 .47 7.43**

Criterion: Energy level Step 1 .07 .07 6.86** Gender 2.47 .95 .18 2.61** Income -8.73 3.42 -.18 -2.56* Step 2 .11 .04 8.75** Gender 2.31 .93 .17 2.49* Income -9.15 3.35 -.19 -2.73** FIB 4.38 1.48 .20 2.96**

Criterion: General health Step 1 .07 .07 14.40** Income 3.43 .90 .26 3.79** Step 2 .10 .03 6.29* Income 3.30 .89 .25 3.69** FIB 3.55 1.42 .17 2.51*

Note. N = 192 for FV, fiber, whole grain intake (two adults identified as “other” gender, and one did not report age; binary gender and age are requisites for dietary estimate computation); N = SOCIAL MOVEMENTS AND HEALTH 94

190 for MET minutes (five adults’ IPAQ data was undeterminable and was marked as “missing”; N = 193 for energy level (gender was a covariate in this analysis, and two adults’ gender identified as “other” were marked as “missing”); N = 195 for general health. R2 = percentage of variance accounted for by the set of predictors at each step, ∆R2 = how much incremental variance in R2 that is accounted for by the predictors at each step, ∆F = change in the F test from the last step, B = unstandardized beta, SE B = standard error of the corresponding unstandardized beta, β = standardized beta, t = t value. *p < .05. **p < .01. SOCIAL MOVEMENTS AND HEALTH 95

Table 10

Hierarchical multiple regression analyses of frequency of individual behaviors predicting health outcomes within the college student sample.

Step/predictor R2 ∆R2 ∆F B SE B β t

Criterion: FV Step 1 .07 .07 14.19** Gender -0.13 .03 -.26 -3.64** Step 2 .26 .19 47.87** Gender -.15 .03 -.31 -4.93** FIB .10 .01 .44 0.44**

Criterion: Fiber Step 1 .12 .12 26.31** FIB .06 .01 .35 5.13**

Criterion: Whole grains Step 1 .11 .11 23.56** FIB .17 .03 .33 4.85**

Criterion: MET minutes Step 1 .07 .07 13.45* Income 3.47 .36 .26 3.67**

Criterion: Role capabilities due to emotional health Step 1 .01 .01 2.48 Gender -10.95 6.95 -.11 -1.58 Step 2 .04 .03 6.24* Gender -9.11 6.89 -.10 -1.32 FIB -7.97 3.19 -.18 -2.50*

Note. N = 192 for FV, fiber, whole grain, and capabilities due to emotional problems (four students did not complete the DSQ, and four others did not complete the RAND survey, both due to an error with the online survey); N = 194 for MET minutes (two students did not complete the IPAQ due to an error with the online survey). R2 = percentage of variance accounted for by the set of predictors at each step, ∆R2 = how much incremental variance in R2 that is accounted for by the predictors at each step, ∆F = change in the F test from the last step, B = unstandardized beta, SE B = standard error of the corresponding unstandardized beta, β = standardized beta, t = t value. *p < .05. **p < .01.

SOCIAL MOVEMENTS AND HEALTH 96

Table 11

New categories of social movements based on Robinson’s (2010) original theory.

General College Movements/causes Individual-level behaviors n % n % Human rights/social justice Eat less fast food restaurant 56 28.7 54 27.6 Improving workers’ rights, poor food. Eat less meat. Eat more working conditions in fast food fruits and vegetables from industry and suppliers (e.g., farmers’ markets, local slaughterhouses, farm workers); farmers, CSA, following fair food justice, increasing access to trade practice. more healthful foods such as fresh Watch less media to reduce fruits and vegetables in low-income exposure to negative areas; women’s rights, families racial/ethnic gender rights; fair trade; reducing stereotypes. racial/ethnic and gender discrimination from stereotypes in media Environmental sustainability Eat more fresh fruits and 34 17.4 14 7.1 Preventing global warming and vegetables. Eat less meat, climate change, sustainable particularly beef. Eat less agriculture, organic farming, slow processed and packaged food, eating locally (locavores), foods. Eat fewer foods agrarianism, recycling/waste transported over long reduction, improving air quality, distances. conserving water Less automobile use, more walking, bicycling, and mass transit use. Animal protection Less beef, pork, poultry, dairy, 31 15.9 35 17.9 Reducing inhumane treatment of and fish consumption, more animals during farming and vegetarianism slaughter Nationalism 29 14.9 24 12.2 Patriotism, nationalism – Supporting Eat more locally one’s own national economy and grown/domestically grown culture food. Eat less fast food and processed foods and beverages from multinational corporations. Eat less Energy independence – Freeing imported foods. nations from dependence on foreign Less automobile use, more oil walking, bicycling, and mass transit. Eat more locally grown produce and less meat and processed and packaged SOCIAL MOVEMENTS AND HEALTH 97

Antiglobalization – Farmers, labor foods transported over long unions, human rights groups, distances. nationalists, etc. resisting corporate Eat more locally and cultural globalization and WTO grown/domestically grown and World Bank free trade policies food. Eat less fast food and processed foods and National security – Protecting the beverages from multinational nation’s security from foreign corporations. Eat less countries and terrorists with a strong imported foods. military, protected food supply, and Regular participation in physical food and energy independence/self- activity to maintain physical sufficiency fitness Eat more locally grown produce and less meat. Eat less mass produced fast food and processed foods and beverages from

Community improvement 23 11.8 41 20.9 Community safety, beautification, Participating in gardening, and traffic reduction – Improving clean-up, playground safety and beauty to increase building, home and neighborhood quality of life and neighborhood improvement property values and repair, and other community beautification projects. Spend more time outdoors in recreation and Youth violence and crime prevention neighborhood social – Reducing youth involvement in activities. gangs and crime Participating in after school sports programs for at-risk youth (e.g., midnight basketball leagues), or as mentors or coaches; participating in community policy/neighborhood watch programs. Less television watching and other screen media use. Other 22 11.3 28 14.3 Food safety – Reducing risk of Eat less meat, particularly beef, infectious diseases from food (e.g., and less fast food restaurant Escherichia coli O157:H7, Bovine food. Eat more organically Spongiform Encephalopathy/mad and locally grown fruits and cow disease) and potentially harmful vegetables. additives and/or contaminants (e.g., SOCIAL MOVEMENTS AND HEALTH 98 toxic additives in imported food) Anticonsumerism – Reducing consumer culture and/or the Less purchase and consumption influence of consumer culture of heavily advertised and marketed fast food and snack foods/convenience foods. Less television watching and Political action other screen media use. As part of political campaigns or in Door-to-door campaigning or support of the movements listed and petition drives, picketing, other specific causes public demonstrations, Cause-related fundraising – Raising marches awareness and funding for charitable causes such as cancer or AIDS Walk-a-thons, door-to-door research and services (e.g., Team-in- fundraising, training and Training) participation in distance and/or endurance races, long distance walks and bike rides, etc. Note: Adapted from “Save the World, Prevent Obesity: Piggybacking on Existing Social and Ideological Movements,” by Robinson, 2010. SOCIAL MOVEMENTS AND HEALTH 99

APPENDIX G. FIGURES

Frequency of Individual Behaviors

Level of Social Health Outcomes Movement Involvement

Figure 1. Proposed mediation model of social movement involvement and health outcomes. SOCIAL MOVEMENTS AND HEALTH 100

FIB b = 2.15, p < 0.001 b = 0.06, p < 0.001

LSMI FV Intake

Direct effect, b = 0.11, p = 0.08 Indirect effect, b = 0.13, 95% CI [0.07, 0.20]

Figure 2. Model of social movement involvement as a predictor of servings of FV among general adults, mediated by individual behaviors, covarying out gender. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 101

FIB b = 2.15, p < .001 b = 0.05, p < 0.001

LSMI Fiber Intake

Direct effect, b = -0.001, p = 0.98 Indirect effect, b = 0.10, 95% CI [0.04, 0.17]

Figure 3. Model of social movement involvement as a predictor of fiber intake among general adults, mediated by individual behaviors, covarying out gender. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 102

FIB

b = 0.12, p = 0.002 b = 2.15, p < .001

LSMI Whole Grain Intake

Direct effect, b = -0.08, p = 0.65

Indirect effect, b = 0.25, 95% CI [0.10, 0.43] Figure 4. Model of social movement involvement as a predictor of whole grain intake among general adults, mediated by individual behaviors, covarying out gender. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 103

FIB b = 4.84, p < 0.001 b = 2.11, p < 0.001

LSMI Average daily MET minutes

Direct effect, b = 6.89, p = 0.10 Indirect effect, b = 10.21, 95% CI [6.42, 15.16]

Figure 5. Model of social movement involvement as a predictor of average MET minutes per day among general adults, mediated by individual behaviors, covarying out income. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples. MET minutes = square root transformed data

SOCIAL MOVEMENTS AND HEALTH 104

FIB

b = 2.15, p < 0.001 b = 4.48, p = 0.02

LSMI Energy Level

Direct effect, b = -0.87, p = 0.92

Indirect effect, b = 9.62, 95% CI [2.28, 19.85]

Figure 6. Model of social movement involvement as a predictor of energy level among general adults, mediated by individual behaviors. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 105

FIB

b = 2.08, p < 0.001 b = 5.35, p = 0.001

LSMI General Health Perception

Direct effect, b = -17.66, p = 0.03

Indirect effect, b = 11.12, 95% CI [4.97, 18.84]

Figure 7. Model of social movement involvement as a predictor of general health perception among general adults, mediated by individual behaviors. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 106

FIB

b = 1.07, p < .001 b = .09, p < .001

LSMI FV intake

Direct effect, b = .06, p = 0.37 Indirect effect, b = .10, 95% CI [.04, .19] Figure 8. Model of social movement involvement as a predictor of servings of FV intake among college students, mediated by individual behaviors, covarying out gender. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 107

FIB b = 1.12, p < .001 b = .06, p < .001

LSMI Fiber intake

Direct effect, b = .07, p = 0.24

Indirect effect, b = .06, 95% CI [.03, .12]

Figure 9. Model of social movement involvement as a predictor of fiber intake among college students, mediated by individual behaviors. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

SOCIAL MOVEMENTS AND HEALTH 108

FIB b = 1.12, p < .001 b = .15, p < .001

LSMI Whole grain intake

Direct effect, b = .33, p = 0.07

Indirect effect, b = .17, 95% CI [.07, .32]

Figure 10. Model of social movement involvement as a predictor of whole grain intake among college students, mediated by individual behaviors. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

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FIB b = 1.20, p < .001 b = 3.46, p < .001

LSMI MET minutes

Direct effect, b = .21, p = 0.97

Indirect effect, b = 4.13, 95% CI [1.79, 8.36]

Figure 11. Model of social movement involvement as a predictor of average daily MET minutes among college students, mediated by individual behaviors. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.

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FIB b = 1.07, p = .001 b = -6.32, p = .10

LSMI Role capabilities due to emotional health

Direct effect, b = -31.90, p = .04

Indirect effect, b = -6.74, 95% CI [-18.93, -.08]

Figure 12. Model of social movement involvement as a predictor of role capabilities due to emotional health among college students, mediated by individual behaviors, covarying out gender. The confidence interval for the indirect relationship is a BCa bootstrapped CI based on 1000 samples.