Bibliography Assignment. 1. Identify the independable and dependable variables. 2. Get 3 scholarly Journal Article and write one or two paragraph from each article 3. Do not use abstracts and background, and if used it considered plagiarism. 4. This is

The Effect of a Pilot Nutrition Education Intervention on Perceived Cancer Risk in a Rural Texas Community

Liliana Correa, MS', Debra B. Reed, PhD, RDN, LD:, Barent N. McCool, PhD3, Mary Murimi, PhD, RDN, LD2, Conrad Lyford, PhD4 'Former M.S. Nutritional Sciences Graduate Student, Texas Tech University, Lubbock, TX departm ent of Nutritional Sciences, Texas Tech University, Lubbock, TX departm ent of Hospitality and Retail Management, Texas Tech University, Lubbock, TX departm ent of Agricultural & Applied Economics, Texas Tech University, Lubbock, TX Correspondence to: Debra B. Reed, PhD, RDN, LD [email protected]

ABSTRACT Background: A high consumption o f fruits, vegetables, and whole grain foods and adequate levels o f physical activity are associated with a lower risk o f obesity and lower risk o f lifestyle cancers. Re­ search suggests that rural communities have a high risk o f unhealthy behaviors that may contribute to excessive weight gain and risk o f lifestyle related cancers. The purpose o f this pilot study was to deter­ mine the effect o f an educational intervention in a rural Texas com­ munity on the intermediate outcomes o f eating behavior (increasing the intake o f fruits, vegetables, and whole grain foods) and physical activity behavior, and the distal outcome o f body mass index (BM1). Methods: The intervention, guided by the Social Cognitive Theory, was implemented over a 10-month period and included a variety o f community-based education activities related to nutrition, physical activity, and cancer in a variety o f settings. The effect o f the inter­ vention was assessed by analyzing pre- and post-data (N=67) using independent and paired samples t-tests and bivariate correlations. Results: Participants were mainly Hispanic (53.7%) and White (44.8%). At pre-intervention, 6% o f participants reported consuming >5 servings o f fruits and vegetables daily, 19.4% consumed >3 serv­ ings o f whole grain foods daily, and 85.1% were either overweight or obese. Only 31% o f participants were aware that cancer risk was related to overweight at pre-intervention. At post-intervention, His- panics showed a significant increase in the consumption o f fruits and vegetables (p<0.05). Participation in sports or physical activity pro­ grams showed a significant increase (p<0.05). However, no signifi­ cant decrease in BM1 was shown. Conclusion: This intervention had a limited effect in increasing tar­ geted behaviors and no effect on reducing BMI. More assessment is needed in this rural community to identify barriers to healthy behav­ iors and to improve interventions to increase consumption o f fruits, vegetables, and whole grain foods, levels o f physical activity, and awareness o f the cancer and obesity relationship.

INTRODUCTION During the last 20 years, there has been an increase in the rates o f excessive weight in the U.S. population with more than 69% o f the adult population classified as overweight or obese.1 The increased rate o f obesity and other chronic diseases, including cancer, is influ­ enced by behavioral changes in rural and urban populations.2-4 These changes include an increased intake o f energy-dense foods that are high in saturated fat, trans fat, sugars, and salt, lower consumption o f fruits, vegetables, and whole grain foods, and a lack o f physical activity.2

Rural populations are at a higher risk o f obesity and chronic diseases because they are more affected by unhealthy lifestyles and the lack o f access to health care than urban populations.5 The prevalence o f unhealthy lifestyles in rural populations is in part due to a lack o f health-friendly environments. In health-friendly environments, per­ sons have access to healthy, affordable food and nutrition informa­

tion, as well as to facilities, such as walking trails, which encourage participation in health activities.6'7 In addition, factors such as low educational and socioeconomic levels, low physical activity, high prevalence o f obesity, and high smoking rates are associated with a negative health status among rural populations.8

Hispanics (42.5%) have the highest age-adjusted rates o f obesity compared to non-Hispanic Whites (32.6%) and non-Hispanic Asians (10.8%) but are lower than Non-Hispanic Blacks (47.8%).' Thus, except for non-Hispanic Blacks, Hispanics may be at greater risk for the development o f obesity-related cancers o f the colon, breast, kidneys, esophagus, pancreas, prostate, gallbladder, and liver.9 It has been estimated that up to one-third o f the 589,430 cancer deaths ex­ pected to occur in 2015 in the U.S. will be related to overweight or obesity, physical inactivity and poor nutrition.10 The cancer incidence rates for Hispanics in Texas during 2007-2011 were 412/100,000 for males and 325/100,000 for females; for Whites they were 532/100,000 males and 415/100,000 females; and for Blacks they were 583/100,000 males and 499/100.000 females." Although the cancer incidence rates for Hispanics are actually lower compared to other races, Hispanics are an important population to include in an educational intervention as they represent 38.6% o f the total popula­ tion and 31.8% o f the rural population in Texas.12-13 In the 2010 U.S. Census, 19.3% o f the total U.S. population was classified as rural, and in Texas, 15.3% o f the population was considered rural.14 Ap­ proximately 18% o f the rural U.S. population lives in poverty with Hispanic, Native American, and African-American populations hav­ ing the highest percentage o f poverty in both rural and urban com­ munities.15

Approximately 40% o f the Texas population reported consuming fruits less than one time daily, and 21.8% reported consuming vege­ tables less than one time daily.16 Lutfiyya et al reported that rural pop­ ulations were less likely than non-rural populations to consume five or more daily servings o f fruits and vegetables.6 Specifically, almost 79% o f the U.S. rural population does not eat the recommended serv­ ings o f fruits and vegetables. Consumers are eating 6% more total grains than recommended but are eating only 34% o f recommended amounts o f whole grains.17 Fruits, vegetables, and whole grain foods are often not easily accessible and affordable by racial and ethnic minority groups in large urban centers or populations in rural areas.18 While research shows that increasing fruits, vegetables, and whole grains may help with weight management and cancer prevention,2 no rural intervention studies were found that addressed all o f these targeted food groups in a single study. Further, while previous studies have used smaller rural food stores for the intervention setting,19'20 no studies were found that used a full-sized supermarket in combination with other settings for intervention within the rural community. Thus, a rural community in Texas was chosen for a multi-component pilot intervention that was delivered across several settings. It was hy­ pothesized that participants in the intervention would increase their

14 TPIIA Journal Volume 68, Issue 1

intake o f fruits, vegetables, and whole grains and increase physical activity levels and that overweight/obesity levels (body mass index, BMI) would be reduced,

METHODS This study was part o f a Cancer Prevention Research Institute o f Texas grant-funded project and was approved by the Texas Tech University Health Sciences Center’s Institutional Review Board for the Protection o f Human Subjects. The pre-intervention data were collected during summer 2011, and post-intervention data were col­ lected during spring 2012. The subjects were recruited from Mule- shoe, a rural community in West Texas. The population o f Muleshoe is estimated to be 5,123 with more than 60% Hispanics.21

Study sample Participants were recruited using a variety o f methods, including dis­ tributing flyers at the local supermarket, library, senior center, and churches. In addition, presentations about the study were made to the Chamber o f Commerce, School Board, and Rotary and Lions service organizations. Outdoor electronic message boards at the schools dis­ played information about the study. Any adult 18 years and older liv­ ing in Muleshoe and willing to participate in this study was included, after they signed a consent form. Individuals who did not meet these requirements were excluded; no other screening criteria were used. Also, participants who did not participate in both data collections (pre- and post-intervention) were excluded from analyses in this study. Pre-intervention data were collected from 225 participants, with pre- and post-intervention data available for 67 participants. No data are available related to reasons for participant drop out.

Intervention Participants received a 10-month intervention focused on encourag­ ing participants to increase their consumption o f fruits, vegetables, and whole grain foods and to increase their levels o f physical ac­ tivity. The 10-month intervention period was determined by the grant schedule and arrangements with the other community groups/ settings.\ a b l e 1 shows the specific implementation settings and de­ tails about the intervention’s content and timeline. This intervention differed from others in two aspects: 1) the focus was on a rural su­ permarket as the primary site for the interventions; and 2) multiple “channels” throughout the community were used, with all interven­ tions coordinated around the monthly themes reflected on the posters placed in the supermarket.

The Social Cognitive Theory’s constructs o f behavioral capability and self-efficacy were used as the theoretical foundation for this in­ tervention to change food and physical activity behaviors. Behav­ ioral capability (knowledge and skill to perform a given behavior) was addressed by promoting fruit, vegetable, and whole grain intake in nutrition classes; handouts, flyers, and videos; demonstration o f new healthy recipes and traditional recipes that had been modified with the targeted healthier ingredients; and food tastings.

Self-efficacy (confidence in one’s ability to take action and overcome barriers) was addressed in the classes and food preparation demon­ strations and tastings by emphasizing that healthy, low-cost food can be easy to prepare, tasty, and cost less than fast food. Participants were presented with healthy options to be able to “make over” tra­ ditional recipes and encouraged to discuss their ideas in class to ad­ dress cultural barriers to change. To increase self-efficacy in making healthier food choices at the supermarket, classes and store posters showed participants how to read food labels and how to use the su­ permarket’s NuVal™ system for evaluating the nutritional value o f foods. As part o f the broader weight management messaging, foods low in fat, sugar, and sodium were encouraged in addition to portion

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control.

Class topics and educational materials related to physical activity included recommendations for amounts o f daily physical activity to reduce weight (60 minutes) or maintain a healthy weight (30 min­ utes). Low or moderate impact physical activities, such as walking, biking, gardening, and stretching were encouraged. The advantages to making the desired behavior changes (increase fruit, vegetable, and whole grain intake and increase physical activity) and the health effects o f not making these changes were discussed in classes.

Most o f the educational materials were obtained from the Ameri­ can Institute for Cancer Research (AICR) and were available in both English and Spanish. Flyers and posters created specifically for this project were developed by the Registered Dietitians associated with this project and translated into Spanish by bilingual (English/Span- ish) graduate students who were familiar with the food and culture. However, as the intervention unfolded, less emphasis was placed on Spanish written materials as it was determined that while many o f the Hispanic participants spoke Spanish and English, they were unable to read Spanish and relied on family members who were bilingual to interpret for them. The intervention activities were implemented by faculty and graduate students with a background in nutritional sciences. All classes were taught in English, with the exception o f the classes conducted with Head Start parents, which were taught in Spanish.

Measures This study was a pre-and post-intervention design with outcome measures o f dietary intake, physical activity, and BMI. The Nutri­ tion and Health Practices Survey included demographic questions from the Behavioral Risk Factor Surveillance System (BRFSS) 2010 Survey22 and questions on participants’ eating practices, attitudes re­ garding cancer risk, and health practices. The survey was translated into Spanish by native Spanish speakers who were part o f the project staff. It was pretested with 30 participants at a supermarket with a primarily Hispanic clientele in a suburban city about 70 miles from Muleshoe. In addition, the AIM-HI Fitness Inventory23 created by the American Academy o f Family Physicians (AAFP) was used to collect data on participants’ dietary intake and physical activity. It was selected based on its use in various clinical settings and demo­ graphic groups,23-24 ease o f administration, face validity, and Spanish availability. Height and weight were measured by trained research staff and used to determine BMI. Participants received a $25 gift card from the local supermarket at both pre- and post- data collection.

Statistical A nalysis Descriptive statistical analyses were performed to evaluate partici­ pants’ demographic and physical characteristics at baseline. The de­ pendent variables included were BMI, physical activity level, and intake o f fruits, vegetables, and whole grain foods, while age, gender, race, language, marital status, income, education, and beliefs regard­ ing cancer risk were independent variables. Independent and paired sample t-tests were used to compare the pre- and post-intervention change score o f the variables tested. Bivariate analyses were used to determine the relationship between BMI, age, education, income, and physical activity with the participants’ reported consumption o f fruits, vegetables, and whole grain foods. A p-value <0.05 was con­ sidered statistically significant. To perform the statistical analysis, IBM SPSS Statistics, version 21 was used.

RESULTS The majority o f the participants were older than 50 years (59.7%), fe­ male (70.1 %), married (59.7%), and spoke English as a first language (85.1%) (demographic data not shown). Participants were predomi-

15

Table 1. Implementation of intervention activities

L o c a t i o n I m p l e m e n t a t io n F r e q u e n c y

Supermarket Based

Food Product Tastings

Samples of a variety o f foods (e.g. soups, salads, casseroles, desserts) prepared with healthy ingredients were offered to supermarket customers. Nutrition information and recipes were provided.

2 times per month for 10 months - products related to monthly themes

Posters Large posters reflecting healthy eating and healthy physical activity themes were placed strategically in the supermarket.

New posters placed each month for 10 months

NuVallm a and Healthy Food Markers

Healthy food markers were placed throughout the supermarket to supplement the supermarket’s NuValtm nutrition scoring system.

Markers moved monthly in support of poster themes

Communitv Based Classes

Community Center

Series of classes held in the evenings included food demonstrations and tastings and distribution of educational materials. Examples of class topics included weight management, recipe modification, portion distortion, reading food labels, and physical activity strategies.

Offered monthly for 10 months; 40 minutes long

Library Classes held as part of the library’s community education program - incorporated presentation and discussion; flyers and materials from American Institute for Cancer Research were placed in racks for patrons to take.

2 classes during the 10 month period

Head Start Center Classes presented to parents of children enrolled as part of their parent education program.

2 classes during the 10 month period

Health Fairs

High School Healthy eating and physical activity information provided at parents’ organization pre-football game dinner. Flyers promoting classes and events at the supermarket and community center were distributed.

1 time about mid­ way through 10 month period

Senior Center Healthy eating and physical activity information provided; blood pressure, height, and weight measurements taken.

2 times during the 10 month period

Two Local Churches Healthy eating and physical activity information provided; blood pressure, height, and weight measurements taken.

1 time each during the 10 month period

Media

Television Interviews Project personnel interviewed about the project and the importance of healthy eating and physical activity by local TV station.

2 interviews during the 10 month period

Videos Videos of project activities prepared by local TV station. Videos were posted on TV station’s website, and videos could be viewed at any time during the project.

6 videos posted during the 10 month period

aNuVallm System summarizes comprehensive nutritional information in one number between 1 and 100 for each food in the supermarket (http://www.nuval.com/How ). The higher the NuValtm Score, the better the nutritional value. Approximately 30 supermarket chains nationwide use NuVal (http://www.nuval.com/location).

Table 2. Participants’ beliefs regarding cancer risk at pre- and post-intervention (N=67)

Pre A n sw e re d c o rrectly

%

P ost A n sw e re d c o rrectly

%

C h a n g e

%

Pre vs. Post p -v a lu ea

D rin k in g tap w a terb 62.7 55.2 -7.5 0.058 U sed o f tan n in g beds 65.7 91.0 25.3 0.103 G e ttin g sun b u rn ed 89.6 98.5 8.9 0.568 B ein g o verw eigh t 31.3 52.2 20.9 0.083 D rin k in g excessive q u a n tities o f alcohol

61.2 61.2 0.0 0.421

C h e w in g tob acco/u sin g s n u ff

97.0 98.5 1.5 1.000

S m o k in g tob acco p rod ucts 98.5 100.0 1.5 0.321 D rin k in g large q uan tities o f caffein eb

28.4 32.8 4.4 0.083

a Paired samples t-test. b Not considered to cause cancer by the American Cancer Society and National Cancer Institut

nantiy Hispanics (53.7%) and Whites (44.8%), had a high school education or less (71.6%) [elementary school 32.8% and high school 38.8%], and had an annual income o f less than $20,000 (66.1%). After analyzing by race, it was found that 70.7% o f the Hispanics had

16

an annual income o f less than $20,000.

In Table 2, participants’ beliefs regarding cancer risk related to over­ weight and selected behaviors are presented. At pre-intervention, there was much more awareness about the cancer risk related to the use o f tobacco (97.0-98.5%) and getting sunburned (89.6%) when compared to the risk o f being overweight (31.3%). While the aware­ ness o f cancer risk related to being overweight increased by 21 % at post-intervention, this increase was not statistically significant and was still well below the awareness levels o f other risk factors.

At pre-intervention, participants had a mean BMI o f 30.4±6.97, and 85.1% were either overweight or obese (37.3% overweight; 47.8% obese) (data not shown). Only 6% consumed five or more servings o f fruits and vegetables daily, and 19.4% consumed three or more servings o f whole grain foods daily. There were no statistically sig­ nificant differences found in fruit, vegetable, and whole grain food consumption from pre- to post-intervention. However, after ana-

TPHA Journal Volume 68, Issue 1

lyzing data by race, Hispanics showed a significant increase in the consumption o f fruits and vegetables at post-intervention (mean change 0.30+0.67; p<0.05) (Table 3). Participation in sports or phys­ ical activity programs showed a significant increase (mean change 0.21+0.75; p <0.05) from pre- to post-intervention (Table 4). No change was found in BMI from pre- to post-intervention.

Bivariate correlations between BMI and servings o f fruits, veg­ etables, and whole grain foods did not show significant associa­ tions (data not shown). However, significant positive associations (p<0.05) were found among intake o f fruits and vegetables and edu­ cation level (r =0.26) and fruits and vegetables and income (r=0.31) at pre-intervention, but not post-intervention.

In our study, attendance was taken at the classes at the Community Center, but unfortunately only 10 o f the 67 participants, for whom pre/post test data were available, attended these classes. The mean (standard deviation) number o f classes attended by these 10 partici­ pants was 5.10 (+1.97). Participants who attended the most classes did not have better outcomes than those who attended fewer classes (data not shown).

education intervention in our study would have lower BMI at post­ intervention; however, this was not found. Similarly, Tussing-Hum- phreys et al conducted a multi-component, six-month church-based intervention (kickoff celebration followed by monthly, 60-minute educational sessions emphasizing increased intake o f fruits, vege­ tables, whole grains, and low fat dairy foods; a didactic physical ac­ tivity session, and a self-directed physical activity component) with rural, lower Mississippi Delta African-American adults, and did not find a significant reduction in BMI.29 However, successful weight loss was reported for rural African-American women participating in a community-based intervention program conducted in churches in South Carolina.30 Since Muleshoe churches were receptive to one in­ tervention session, they may be a good avenue for a continued higher dose o f intervention.

From pre- to post-intervention, the percentage o f participants who were aware that overweight is related to cancer risk increased from 31% to 52%; however, this increase was not statistically significant and shows the need for additional education efforts related to over­ weight as a factor that may increase cancer risk. A 2007 national cross-sectional study (n = 7452) found that 82-89% o f respondents

Table 3. Fruits and vegetables intake by race at pre- and post-intervention (N=66)

Race W hite (n=30) C hange W hite H ispanic (n=36) C hange H ispanic W vs.

(W) (H) H Pre Post P re vs. Pre Post P re vs. C hange

Post Post P- p-valuea p-valuea valueb

* mean ± standard deviation * < mean ± standard deviation- *' F ru its and 1.80+0.61 1.70+0.70 - 0.522 1.33+0.53 1.63+0.68 0.30+0.67 0.010* 0.033* Vegetables9 0.10+0.84

n (%) 5 o r more 3 (10.0) 4(1 3 .3 ) 1 (3.3) 1 (2.8) 4(11.1) 3 (8.3) 3 to 4 18(60.0) 13 (43.3) -5 (-16.7) 10(27.8) 15 (41.7) 5(13.9) 2 o r less 9 (30.0) 13 (43.3) 4 (13.3) 25 (69.4) 17(47.2) -8 (-22.2)

‘ W h ite (pre vs. p o st) an d H isp an ic (pre vs. p o st) p valu es w ere calcu lated using p aired sam ples t-test, *p <0.05. b W h ite vs. H isp an ic in d ep en d en t sam ples t-test. c Serv in g s eaten a day; 1= 2 o r less; 2 = 3 to 4; 3 = 5 o r m ore

DISCUSSION This study examined the effect o f a nutrition intervention on improv­ ing eating behaviors, specifically those related to the intake o f fruits, vegetables, and whole grains, and increasing physical activity in a ru­ ral community o f West Texas. These health behaviors are important in the prevention o f obesity, cancer, and other chronic diseases.2,25

The 2010 Census found that Hispanics (31.8%) and Whites (58.4%) were the most predominant races in rural Texas.13 In Muleshoe, per­ centages were higher for Hispanics (53.7%) and lower for Whites (44.8%). Rural populations are more likely to live in poverty than urban populations, and Hispanics have the highest prevalence o f poverty.14 Our findings indicated that a majority o f Muleshoe’s par­ ticipants, especially Hispanic participants, were living below the poverty level. Limited income has been shown to affect a house­ hold’s ability to purchase healthy foods.26

The prevalence o f obesity is higher in rural populations who are more vulnerable to unhealthy lifestyles.27 Data from the 2005-2008 Na­ tional Health and Nutrition Examination Survey (NHANES) showed that the prevalence o f obesity was 39.6% among rural adults com­ pared to 33.4% among urban adults.28 Rural populations’ increased likelihood to be obese was reflected in this study as 47.8% o f Mule­ shoe participants were obese, compared to 34.9% in the total U.S. population.1 It was hypothesized that participants who received the

across all races said they had never looked for information related to cancer prevention.31

In our study, it was hypothesized that participants who received the nutrition education intervention would have a significantly higher mean intake o f fruits, vegetables, and whole grains after the inter­ vention. Most o f the participants in. Muleshoe reported a low con­ sumption o f fruits, vegetables, and whole grains at pre- and post­ intervention. Although the consumption o f fruits and vegetables was still low at post-intervention in the total sample, we found that Hispanics, not Whites, significantly increased their consumption o f fruits and vegetables. This racial difference was found also in a

Table 4. Physical activity at pre- and post-intervention (N=67)

C h aracteristics

Times a week o f physical activity3

Pre P ost C han ge Pre vs. Post p -valu eb

mean ± standard deviation- * Yard or housew ork 2.36±0.7 2.34±0.6 0.01±0.8

0.8853 6 4 W alk >10 m inutes 2.01±0.8 2.07±0.7 0.06±0.9 0.609

6 8 5 S ports or p hysical activity 1.40±0.6 1.61±0.8 0.21±0.7

0.026*program 5 3 5 al= less than 1; 2= 1 -3; 3= 4 or more. b Paired samples t-test. *p<0.05.

TPHA Journal Volume 68, Issue 1 17

study that analyzed fruits and vegetables dietary behavior to assess the effects o f a low-intensity, physician-endorsed intervention in a rural population, where the majority o f participants were Whites or African-Americans. The authors found that for Whites there was not a significant effect, but African-Americans increased their intentions compared to controls, at one and six months.32 In a systematic review o f interventions designed to increase fruit and vegetable intake, the authors found that the largest effects o f these interventions were ob­ served among sub-groups o f participants who were at a higher risk o f disease, implying that these participants had increased motivation to improve their eating behaviors.33 In our study, Hispanics comprised 54% o f the total participants, and 61% were considered obese at pre­ intervention. Therefore, it is possible that participants perceived the need to lose weight, and thus they were motivated to increase their intake o f fruits and vegetables. However, the motivation or strategies used by those who increased fruits and vegetables was not deter­ mined.

In comparing our results related to changes in fruit, vegetable, and whole grain intake to other studies, similar findings were reported for different intervention methods. A six-week community-based partic­ ipatory research intervention to make the home environment more supportive o f healthy eating and physical activity for rural adults o f Southwest Georgia consisted o f a tailored home environment pro­ file, goal-setting, and behavioral contracting delivered through two home visits and two telephone calls.34 While intervention households reported significant improvements in purchasing o f fruit and vegeta­ bles and family support for healthy eating and increased purchasing o f exercise equipment and family support for physical activity rela­ tive to comparison households, no significant changes were observed for fruit and vegetable intake, physical activity, or weight between intervention and comparison households.

Tussing-Humphreys et al reported in their study with lower Missis­ sippi Delta African-American adults that fruit, vegetable, and whole grain intake for both the intervention and control groups increased, but there were no significant differences.29 However, they did find that the high participation intervention group had significant increas­ es in these dietary outcome variables compared to the control group. They also found a positive effect o f vehicle ownership on study com­ pletion and attendance at intervention activities. Given the limited attendance at classes in our study, transportation and other barriers to classes should be explored in future work with the Muleshoe com­ munity.

Additionally, it was hypothesized that the intervention would in­ crease physical activity levels. A significant increase in engagement in a sport or physical activity program on a regular basis was found and may indicate a socially acceptable way o f increasing physical activity in this community. However, participants did not report significant increases in yard or housework or walking from pre- to post-intervention. Previous research using a community-based ap­ proach to promote walking in rural Missouri Caucasian and Black participants also did not find a statistically significant intervention ef­ fect, although a positive net change in rates o f seven-day total walk­ ing in two subgroups (persons with a high school degree or less and persons living in households with annual incomes o f <$20,000) was reported.35 Even so, walking has been determined as the most com­ mon physical activity, especially in overweight, low income, and low education populations.36,37 Thus, it would be helpful to determine barriers to walking in this rural community.

Study Limitations One limitation was the lack o f a comparable control group, and therefore the positive changes seen may not be totally attributable

to the intervention. Also, while there were 225 participants at pre­ intervention, only 67 provided survey data and anthropometries at post-intervention, which limits the generalizability to all Muleshoe residents. Further, the small number o f participants decreased the ability to detect changes in outcomes. Another limitation is that self- reported data were used to assess food intake and physical activity levels. In self-reported measures, participants have the tendency to under-report normal daily food intake and under- or over-estimate physical activity levels. This could be due to inaccurate memory, social desirability, or their inability to capture accurately their physi­ cal activity and food intake.38,39 Additionally, although the Aim-Hi Fitness Inventory has been used in a number o f settings nationally, it was not validated or tested for reliability in this study population. Another limitation was that only individual factors were assessed and not environmental factors such as access to walking trails, qual­ ity o f food (food portions and nutritional value) sold in the com­ munity venues other than the intervention supermarket, and food af­ fordability, which could contribute to unhealthy behaviors. Although low-cost, healthy foods were promoted by the intervention, food insecurity was not assessed or addressed directly through activities or referrals.

Study Strengths This study has several strengths. First, limited data are available on rural interventions that include multiple components (diet and physi­ cal activity) in a bi-racial rural population. Second, assessment tools and most educational materials were available both in English and Spanish, and recipes used in classes and materials reflected the com­ munity’s cultural groups. Third, height and weight were measured by trained staff, rather than using self-reported data, to increase validity. In addition, the data collected in this study helped to assess the BMI, eating habits, and physical activity status in this rural community that had not been studied before. .

CONCLUSIONS It is encouraging that Hispanics improved their intake o f fruits and vegetables and that participation in physical activity programs in­ creased in the total sample in this rural community. The interven­ tion did not have a significant effect in helping participants to reduce their BMI or increase intake o f whole grain foods. The 21 % increase in participants who were aware o f the relationship between over­ weight and cancer at post-intervention was a positive finding, but much improvement is still needed in knowledge and behavior. This study showed that the rural community o f Muleshoe is at high risk of continued obesity and chronic diseases due to unhealthy behaviors and knowledge gaps. There is a need for additional assessment in this rural community to identify other possible barriers to healthy behaviors and to improve interventions to make them more success­ ful. Focus group discussions or other forms o f community partici­ patory research could help further assess needs and promote more community ownership. Also, the sport and group activities results are promising and should be explored further.7

REFERENCES 1. Centers for Disease Control and Prevention. Overweight and Obesity 2015. Available at: http://www.cdc.gov/obesitv/data/adult.html Accessed on Octo­ ber 15, 2015. 2. World Health Organization. Cancer. Fact sheet N° 297. Available at: http:// www.who.int/mediacentre/factsheets/fs297/en/index.htmlAccessed on Octo­ ber 15, 2015. 3. Bamidge E, Radvanyi C, Duggan K, Motton F, Wiggs I, Baker E, Brown- son, R. Understanding and addressing barriers to implementation o f envi­ ronmental and policy interventions to support physical activity and healthy eating in rural communities. J Rural Health 2013;29( 1 ):97-105. 4. Osuji T, Lovegreen S, Elliott M, Brownson R. Barriers to physical activity among women in the rural midwest. Women Health 2006;44(l):41-55.

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5. Jepson RG, Harris FM, Platt S, Tannahill C. The effectiveness o f inter­ ventions to change six health behaviours: a review of reviews. BMC Public Health 2010; 10:538. 6. Lutfiyya M, Chang L, Lipsky M. A cross-sectional study o f US rural adults’ consumption o f fruits and vegetables: do they consume at least five servings daily? BM C Public Health 2012; 12:280. 7. Whaley D, Haley P. Creating community, assessing need: preparing for a community physical activity intervention. Res Q Exerc Sport 2008;79(2):245- 255. 8. Jones C, Parker T, Aheam M, Mishra A, Variyam J. Health Status and Health Care Access o f Farm and Rural Population. U.S. Department o f Agri­ cultural Economics 2009;(ElB-57)72 pp. 9. Anand P, Kunnumakkara A, Sundaram C, Harikumar B, Tharakan S, Lai O, Aggarwal B. Cancer is a preventable disease that requires major lifestyle changes. Pharm Res 2008;25(9):2097-2116. 10. American Cancer Society. Cancer Facts & Figures 2015. Atlanta: Ameri­ can Cancer Society. Available at: http://www.cancer.org/acs/groups/con- tent/foieditorial/documents/document/acspc-044552.ndf Accessed on 10-28- 2015. 11. Texas Department o f State Health Services. Texas Selected Can­ cer Facts 2014. Available at: https://www.dshs.state.tx.us/tcr/ statisticalData/2014FactSheets/Texas-Fact-Sheets-2014.asnx Accessed on October 15, 2015. 12. U.S. Census Bureau. State and County Quick Facts 2014. Available at: http://quickfacts.census.gov/qfd/states/48000.html Accessed on October 15, 2015. 13. Housing Assistance Council. Race and Ethnicity in Rural America 2012. Available at: httD://www.ruralhome.org/storage/research notes/rm-race- and-ethnicitv-web.pdf Accessed on October 15, 2015. 14. U.S. Census Bureau. 2010 Census Urban and Rural Classification and Urban Area Criteria. Available at: http://www.censns.gov/geo/reference/ua/ urban-rural-2010.html Accessed on October 15, 2015. 15. Housing Assistance Council. Rural poverty increases, while the U.S. poverty rate remains unchanged. Available at: httD://www.ruralhome.org/ storage/documents/rrbriefs/rm poverty supplement 2013.pdf Accessed on October 15, 2015. 16. Centers for Disease Control and Prevention. 2013 State Indicator Re­ port on Fruits and Vegetables. Available at: http://www.cdc.gov/nutrition/ downloadsState-Indicator-Renort-Fruits-Vegetables-2013.pdf Accessed on October 15, 2015. 17. U.S. Department o f Agriculture. The U.S. Grain Consumption Landscape. Available at: http://www.ers.usda.gov/publications/err50/err50.pd f Accessed on October 15, 2015. 18. Dunn RA, Sharkey JR, Lotade-Manje J, Bouhlal Y, Nayga RM. Socio­ economic status, racial composition and the affordability o f fresh fruits and vegetables in neighborhoods o f a large rural region in Texas. N u trJ 2011; 10:6. 19. Bustillos B, Sharkey JR, Anding J, McIntosh A. Availability o f more healthful food alternatives in traditional, convenience, and nontradi- tional types o f food stores in two rural Texas counties. J Am Diet Assoc 2009;109(5):883-889. 20. Gittelsohn J, Rowan M, Gadhoke P. Interventions in small food stores to change the food environment, improve diet, and reduce risk o f chronic disease. Prev Chronic Dis 2012;9:110015. 21. Texas Tech University Health Science Center. Atlas o f Rural and Com­ munity Health. Demographic and Economics Maps 2010. Available at: http:// www.gis.ttu.edu/center/Arch/Demogranhv.html Accessed on October 15, 2015. 22. Centers for Disease Control and Prevention. 2010 Behavioral Risk Fac­ tor Surveillance System Survey Questionnaire. Available at: http://www.cdc. gov/brfss/auestionnaires/index.htm Accessed on October 15, 2015. 23. McAndrews J, McMullen S, Wilson S. Four strategies for promoting healthy lifestyles in your practice. Fam Pract M anag 2011; 18(2): 16-20. 24. Pace DW, Lanigan MA, Staton WE, Graham GD, Manning KB, Dick­ inson ML, Emsermann BC, Stewart EE. Effectiveness o f 2 methods of promoting physical activity, healthy eating, and emotional well-being with the Americans in Motion - Healthy Interventions Approach. Ann Fam Med 2008; 11 (4):371-380. 25. Wang X, Ouyang Y, Liu J, Zhu M, Zhao G, Bao W, Hu FB. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis o f prospec­ tive cohort studies. RM /2014;349:g4490. 26. Larson NI, Story MT, Nelson MC. Neighborhood environments: dispari­ ties in access to healthy foods in the U.S. Am J Prev M et/2009;36(1):74-81.

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27. Wilson S, Gallivan A, Kratzke C, Amatya A. Nutritional status and socio- ecological factors associated with overweight/obesity at a rural-serving US- Mexico border university. Rural Remote Health 2012;12(4):2228. 28. Befort C, Nazir N, Perri M. Prevalence o f obesity among adults from rural and urban areas o f the United States: findings from NHANES (2005-2008). J Rural Health 2012;28(4):392-397. 29. Tussing-Humphreys HL, Thomson JL, Mayo T, Edmond E. A church- based diet and physical activity intervention for rural, lower Mississippi Delta African American adults: Delta Body and Soul effectiveness study, 2010- 2011. Prev Chronic Dis 2013; 10:120286. 30. Parker GV, Coles C, Logan NB, Davis L. A community-based weight loss intervention program for rural African American women. Fam Community Health 2010;33(2): 133-143. 31. Davis J, Buchanan K, Green B. Racial/ethnic differences in cancer pre­ vention beliefs: applying the health belief model framework. Am J Health Promot 2013;27(6):384-389. 32. Carcaise-Edinboro P, McClish D, Kracen A, Bowen D, Fries E. Fruit and vegetable dietary behavior in response to a low-intensity dietary intervention: the rural physician cancer prevention project. J Rural Health 2008;24(3):299- 305. 33. Pomerlau J, Lock K, Knai C, McKee M. Interventions designed to in­ crease adult fruit and vegetable intake can be effective: a systematic review o f the literature. J A rnt/-2005;135(10):2486-2495. 34. Kegler CM, Alcantara I, Veluswamy JK, Haardorfer R, Hotz AJ, Glanz K. Results from an intervention to improve rural home food and physical activity environments. Prog Community Health Partnersh 2012;6(3):265-277. 35. Brownson R, Baker E, Boyd R, Caito N, Duggan K, Housemann R, Wal­ ton D. A community-based approach to promoting walking in rural areas. Am J Prev M ed 2004;27(l):28-34. 36. Brownson RC, Jones DA, Pratt M, Blanton C, Heath GW. Measuring physical activity with the behavioral risk factor surveillance system. M ed Sci Sports Exerc 2000;32(11):19I3-1918. 37. Eyler AA, Brownson RC, Bacak SJ, Housemann RA. The epidemiology o f walking for physical activity in the United States. M ed Sci Sports Exerc 2003;35(9): 1529-1536. 38. Prince SA, Adamo KB, Hamel ME, Hardt J, Gorber SC, Tremblay M. A comparison o f direct versus self-report measures for assessing physical activ­ ity in adults: a systematic review. Int J Behav Nutr Phys A ct 2008;5:56. 39. Seale JL. Predicting total energy expenditure from self-reported dietary records and physical characteristics in adult and elderly men and women. Am J Clin Nutr 2002;76(3):529-534. JL

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