Literature DB >> 25706120

Development and implementation of the National Cancer Institute's Food Attitudes and Behaviors Survey to assess correlates of fruit and vegetable intake in adults.

Temitope O Erinosho1, Courtney A Pinard2, Linda C Nebeling3, Richard P Moser3, Abdul R Shaikh3, Ken Resnicow4, April Y Oh5, Amy L Yaroch2.   

Abstract

BACKGROUND: Low fruit and vegetable (FV) intake is a leading risk factor for chronic disease globally as well as in the United States. Much of the population does not consume the recommended servings of FV daily. This paper describes the development of psychosocial measures of FV intake for inclusion in the U.S. National Cancer Institute's 2007 Food Attitudes and Behaviors Survey.
METHODS: This was a cross-sectional study among 3,397 adults from the United States. Scales included conventional constructs shown to be correlated with fruit and vegetable intake (FVI) in prior studies (e.g., self-efficacy, social support), and novel constructs that have been measured in few- to- no studies (e.g., views on vegetarianism, neophobia). FVI was assessed with an eight-item screener. Exploratory factor analysis, Cronbach's alpha, and regression analyses were conducted.
RESULTS: Psychosocial scales with Cronbach's alpha ≥0.68 were self-efficacy, social support, perceived barriers and benefits of eating FVs, views on vegetarianism, autonomous and controlled motivation, and preference for FVs. Conventional scales that were associated (p<0.05) with FVI were self-efficacy, social support, and perceived barriers to eating FVs. Novel scales that were associated (p<0.05) with FVI were autonomous motivation, and preference for vegetables. Other single items that were associated (p<0.05) with FVI included knowledge of FV recommendations, FVI "while growing up", and daily water consumption.
CONCLUSION: These findings may inform future behavioral interventions as well as further exploration of other potential factors to promote and support FVI.

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Year:  2015        PMID: 25706120      PMCID: PMC4338082          DOI: 10.1371/journal.pone.0115017

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Diets high in fruits and vegetables (FVs) are associated with reduced risk for obesity and several chronic diseases [1-5]. National guidelines recommend that adults in the United States (U.S.) consume 7–13 servings (3½-6½ cups) of FVs daily, depending on sex and activity level [5,6]. However, surveillance studies report that most U.S. adults consume less than recommended amounts [7-9]. Understanding correlates of fruit and vegetable intake (FVI) are critical for developing and testing effective FVI interventions. Studies report that psychosocial factors are associated with adults’ FVI [10-16]. For instance, greater perceived access and availability of FVs are associated with higher FVI [11,17,18]. Having positive attitudes toward FVs, believing in their health importance, liking their taste, having greater self-efficacy to eat them, and being knowledgeable of the FV recommendations are also associated with higher FVI in adults [10,12-14,16]. Measures for assessing psychosocial constructs related to FVI vary, and many assess a limited number of psychosocial constructs [19-23]. Therefore, the items developed for the current survey drew from multiple traditional behavioral theories such as the Social Cognitive Theory, Self-Determination Theory, Theory of Reasoned Action, and Health Belief Model, as well as novel items that are not specified in established behavioral theories [24-28]. Furthermore, although some measures have been developed for use with specific population subgroups such as low-income adults [13,29], but few measures for assessing psychosocial constructs have been specifically developed and tested in a national sample of U.S. adults [22]. This paper describes the development of psychosocial measures for inclusion in the U.S. National Cancer Institute’s (NCI) Food Attitudes and Behaviors (FAB) Survey. The survey included assessment of both conventional constructs that have been shown to be correlated with FVI in prior studies (e.g., barriers, self-efficacy, social support), and novel constructs that have been measured in few- to- no studies that specifically assess attitudes and behaviors in relation to food (e.g., views on vegetarianism, neophobia). First, the paper describes the process of identifying, selecting, and testing the psychometric properties of the survey items. Second, an evaluation of the psychosocial constructs’, including scales and single items, and the association with FVI will be reported.

Methods

Design

Development and Pilot-testing of the FAB Survey. Survey items were selected based on an extensive literature review [15] in which we identified conventional psychosocial constructs from cross-sectional and longitudinal studies that were significantly associated FVI. Most constructs and associated survey items (both existing and new items) included on the survey were based on common health behavior theories as stated above. Some novel scales and items that were not related to existing theories and/or had not been examined specifically with regard to FV attitudes and behaviors were included in the survey. A content validity review was conducted by nutrition, public health, and health behavior experts. Extensive cognitive interviewing was conducted with 68 adults to assess comprehension of survey items, and adjustments were made iteratively to ensure the items were understandable. Psychometric testing of the survey was conducted in a pilot study (N = 579 adults). Based on pilot findings, some survey items were retained for use in scales and as single items, others were dropped, and some items were modified for use in the larger main implementation study (described below). Findings regarding reliability estimates from the pilot were consistent with the larger main implementation study, thus we do not report details from the pilot here.

The Main FAB Implementation Study and Sample

The final FAB Survey [30] was comprised of 65 items that assessed food attitudes, beliefs and preferences, social support, knowledge, perceived access to FVs, food shopping behaviors, physical activity, perceived health, demographic characteristics, and FVI [31-34]. The study was approved by the National Cancer Institute’s institutional review board and passed through clearance at the Office of Management and Budget (OMB). The survey was administered to adults ages ≥18 years across the U.S. September-December, 2007. Respondents were selected from the Synovate Consumer Opinion Panel (http://www.ipsos.com/) using stratified random sampling, with an oversampling of African Americans. The FAB Survey was mailed to 5,803 adults; 3,418 surveys were returned, yielding a response rate of 57%; 21 incomplete surveys were excluded, for a final sample of 3,397. Respondents received a thank you letter and $5 for completing the survey.

Measures

The following describe the constructs and associated survey items. A full copy of the FAB Survey and associated materials can be found at http://cancercontrol.cancer.gov/brp/fab/. Psychosocial Constructs and Single Items on the FAB Survey. Conventional psychosocial constructs included self-efficacy, social support, perceived barriers and benefits of eating FVs, and FV purchasing behaviors (Table 1). These constructs have been shown in prior studies to be strong correlates of FVI [15]. Self-efficacy (7 items) measured confidence to consume FVs. Social support (5 items) asked about family/friends support and encouragement in eating FVs. Perceived benefits (7 items) asked about perceptions of health benefits of FVs. Perceived barriers (14 items) included: access, high cost, and short shelf-life of FVs.
Table 1

Internal consistency for conventional constructs related to fruit and vegetable intake.

FV ConstructsItems for measuring constructItems KeptItems Excluded# of items includedCronbach’s Alpha
Self-efficacy Confidence to:
Eat a healthy snack, like a fruit/ vegetable, when hungryX70.92
Eat healthy foods, like fruit/vegetables, when tiredX
Eat healthy foods, like fruit/vegetables, when junk foods are in your houseX
Eat fruit instead of cake, cookies, candy, ice cream, or other sweets for dessertX
Eat fruits/vegetables when family and friends are eating junk foodsX
Buy or bring FVs to eat at workX
Snack on FVs rather than on junk foods while watching TVX
Social Support My family/friends:30.68
Encourage me to eat FVs
Remind me not to eat junk foodX
Would say something if they saw I was not eating FVsX
Often eat FVs when we are togetherX
Would be willing to eat a vegetarian/vegetable-based mealX
Perceived benefits If you eat plenty of FVs every day, how likely are you to:
Have more energyX70.91
Live a long lifeX
Control your weightX
Look better (appearance)X
Be regular (cleanse the body)X
Feel good about yourselfX
I eat enough FVs to keep me healthyX
Perceived barriers I don’t eat FVs as much as I would like because:
They cost too muchX140.85
They often spoil before I get a chance to eat themX
They take too much time to prepareX
They are not filling enoughX
I have trouble digesting themX
My family doesn’t like themX
I don’t know how to choose fresh FVsX
Perceived barriers I don’t think of FVs when I’m looking for something to eatX
They are too messyX
I often forget to eat FVs because they are stored out of sightX
Restaurants I go to don’t serve fruitX
Restaurants I go to don’t serve vegetablesX
It is not easy for me to purchase FVs in my neighborhoodX
It is hard for me to eat more FVs because I don’t know how to prepare themX
When I eat out, it is easy for me to get FVsX

Abbreviations: FVs denotes fruits and vegetables.

Abbreviations: FVs denotes fruits and vegetables. Novel psychosocial constructs included views on vegetarianism (6 items), autonomous (11 items) and controlled motivation (7 items), preference for FVs (36 items), and food neophobia (3 items) (Table 2). The development of items was exploratory and based on emerging evidence or in the case of motivation, had previously been explored with other behaviors (e.g., smoking). Autonomous motivation was defined as motivations for performing behaviors for which the rewards were internal to the individual, while controlled motivation were those that were based on the receipt of external rewards or punishment [25,26,35]. Food neophobia asked about reluctance to try new foods.
Table 2

Internal consistency for novel constructs related to fruit and vegetable intake.

FV ConstructItems for measuring constructItems KeptItems Excluded# of Items includedCronbach’s Alpha
Views on Vegetarianism Dinner doesn’t seem right without meat as a main courseX50.76
After I eat a meal without meat, I still feel hungryX
Vegetarians are a bit “different”X
I think meals should include some meatX
I just don’t understand how someone could be a vegetarianX
My family/friends would be willing to eat a vegetarian/ vegetable-based mealX
Autonomous motivation What motivates you to eat FVs:
To feel in control of my healthX110.95
I have a strong value for eating healthyX
I personally believe it is a good thing for my healthX
I have carefully thought about it and believe it is very important for meX
I would feel better about myself if I did eat a healthy dietX
I would like to improve my physical healthX
An important choice I really want to makeX
Consistent with my life goalsX
Important for being as healthy as possibleX
To take responsibility for my own healthX
Important to treat my body with respectX
Controlled Motivation What motivates you to eat FVs:
Others would be upset with me if I did notX70.89
I feel pressure from others to eat FVsX
I want others to approve of meX
It’s easier to do what I am told than to think about itX
I want others to see I can do itX
I want to set a good example for my communityX
I don’t want to let others downX
I want to set a good example for my familyX
Preference for FVs Preference (like/dislike) for:
a) apples, applesauce; b) bananas; c) pears; d) watermelon; e) other melon;X360.92
f) peaches, nectarine, apricots; g) plums; h) grapes; i) oranges, tangerines;X
j) strawberries; k) other berries; l) grapefruit; m) kiwi; n) cherries; o) mango, papaya; p) pineapple; q) dried fruitX
Preference (like/dislike) for:
a) tomatoes, tomato sauce; b) broccoli; c) spinach (cooked);X
d) collards, turnip greens, or mustard greens (cooked); e) string beans, green beansX
f) asparagus; g) green, red, or yellow pepper; h) celery; i) cucumber; j) peasX
k) lima, red, pinto, kidney, lentils, and other beans; l) squash, zucchiniX
m) Brussels sprouts; n) cauliflower; o) okra; p) corn; q) carrots; r) green saladX
s) yams, sweet potatoesX
t) baked potatoes, mashed potatoes, or potato saladX
Neophobia I enjoy trying new foodsX30.57
When it comes to food, I’m a creature of habit. I eat the same things all the timeX
I am usually the first of my friends to try new food/nutrition productsX

Abbreviations: FVs denotes fruits and vegetables.

Abbreviations: FVs denotes fruits and vegetables. Single items on the survey were either other behaviors or items that did not fit within a scale (i.e., low alphas) and included: physical activity (participation/non-participation for ≥30 minutes daily); smoking (never/former/current smoker); awareness and knowledge of FV recommendation; and two out of three items from the original food neophobia scale (see Table 2). Additional single items asked about “worry” (how much has worrying about your health led you to change the way you ate in the past year), and seasonality (do you tend to eat the same types of FVs all year round or tend to eat different types of FVs depending on the season?). Finally, respondents were asked about the amount (cups) of water they consumed daily, and how often they ate FVs while growing up. Fruit and Vegetable Intake. The main outcome variable on the survey was FVI during the past month. This was assessed with an eight-item FV screener that was modified from the NCI FV screener [36], and validated using multiple 24-hour dietary recalls (adjusted correlation coefficients ranged from 0.39–0.57 for fruit, vegetable, and FV combined) [37]. Responses included ten frequency categories ranging from never to ≥5 times/day, and four portion size categories ranging from about ¼ cup to more than 2 cups. Responses were converted into servings, as defined by the MyPyramid 1992 dietary guidelines [36]. Total FVI was calculated as the sum of all items on the screener, excluding fried potatoes. Demographic Characteristics. Demographic characteristics that were assessed included sex, age, race/ethnicity, highest level of education completed, income, and geographic region of residence.

Analysis

Exploratory factor analysis was conducted using Mplus statistical software (v.5). Factor loadings helped inform the factor structures and determined items to retain within each scale. Items with factor loading lower than 0.3 were considered unsatisfactory items and were excluded from the scales, while items with factor loadings of ≥0.3 were typically kept in the scales [38]. Following exploratory factor analysis, internal consistency was assessed with the items that were retained after the factor analysis. Within each scale, an overall Cronbach’s alpha (α) was computed, and for each item, an index “α if item deleted” was computed. Scales with Cronbach’s α ≥0.68 were entered into regression models for further analysis. Hierarchical linear regression was conducted using SAS (v.9.1, SAS Institute, Cary, NC) to evaluate associations between the psychosocial scales and single items with FVI. Five regression models were tested in a stepwise manner with statistical significance set at p<0.05 (two-sided): (1) sociodemographic variables, (2) lifestyle variables (physical activity, smoking status), (3) conventional scales (self-efficacy, social support, perceived barriers, perceived benefits), (4) novel scales (views on vegetarianism, autonomous and controlled motivation, preference/liking for FVs), (5) unscaled single items. All regression models incorporated sample weights to obtain population-level estimates. These weights were based on post-stratified U.S. Census values for sex, race/ethnicity, age, education, and income. Tests for collinearity were conducted for final regression models and no collinearity issues were found. Missing data, generally around 1% for all items, were imputed using the cyclic n-partition hot decks and predictive means matching method [39,40].

Results

Sociodemographic characteristics of respondents are described in Table 3. Fifty-three percent were female, 27% non-Hispanic black, and 36% were 35–54 years old. Sixty percent had completed high school, 38% resided in the West, and 66% were overweight/obese.
Table 3

Sociodemographic characteristics of main implementation (unweighted frequencies and weighted percentages).

n (%)
Sex
 Male1300(47)
 Female2009(53)
Age (years)
 18–34949(31)
 35–541312(36)
 ≥ 551053(33)
Race/ethnicity
 Non-Hispanic white/Other2368(73)
 Non-Hispanic black896(27)
Highest level of education completed
 < high school408(14)
 High school degree2001(60)
 College degree or higher901(26)
Region
 Northeast603(19)
 Midwest677(23)
West1248(38)
 South493(20)
Body mass index
 ≤ 24.9 kg/m2 (under/normal weight)1031(32)
 25.0–29.9 kg/m2 (overweight)1094(34)
 ≥ 30.0 kg/m2 (obese)1102(33)
Scales with Cronbach’s α≥0.68 were self-efficacy, social support, perceived barriers and benefits of eating FVs, views on vegetarianism, autonomous and controlled motivation, and preference for FVs (Tables 1 and 2). Food neophobia had a Cronbach’s α<0.68, thus the scale was excluded from the regression models while the strongest single items were included. Table 4 describes associations between the psychosocial scale and single items and FVI. The final model that included only psychosocial scales and single items that were significant in Model Five explained 31% of the variance in FVI. Lower FVI (p<0.01) was reported by respondents who reported not participating in physical activity (β = 0.16), or perceived barriers that prevented them from eating FVs (β = -0.14). Lower FVI (p<0.05) was also reported by respondents who said they did not eat fruits (β = -0.07) or vegetables (β = -0.08) while growing up, were a “creature of habit” (i.e., eating the same foods all the time) (β = -0.03), and did not know daily FV recommendations (β = -0.12).
Table 4

Associations of conventional and novel psychosocial constructs and single items with fruit and vegetable intake (excluding fried potatoes) .

Model 1 Model 2 Model 3 Model 4 Model 5 Final Model
β (p-value) β (p-value) β (p-value) β (p-value) β (p-value) β (p-value)
Sociodemographic variables
Sex (female vs. male)0.13(<0.001)0.13(<0.001)0.04(0.29)-0.03(0.46)-0.14(0.21)
Age0.09(<0.001)0.11<0.001)0.06(0.02)-0.02(0.55)-0.05(0.57)
Race/ethnicity
 Hispanic0.29(0.03)0.28(0.02)0.14(0.21)0.11(0.29)0.10(0.32)
 NH Black0.20(<0.001)0.21(<0.001)0.01(0.90)-0.01(0.86)0.03(0.59)
 NH Other0.34(<0.001)0.32(<0.001)0.20(0.03)0.15(0.10)0.12(0.17)
 NH WhiteReferenceReferenceReferenceReferenceReference
Education0.10(<0.001)0.07(0.00)0.05(0.02)0.04(0.09)0.01 (0.55)
Income0.00(0.94)-0.00(0.50)-0.01(0.20)-0.00(0.27)-0.00 (0.20)
Region
 Midwest-0.00(0.96)-0.01(0.85)0.01(0.83)0.03(0.65)0.07(0.24)
 Northeast0.04(0.50)0.05(0.47)0.06(0.36)0.08(0.15)0.12(0.03)
 South-0.07(0.30)-0.05(0.42)-0.06(0.27)-0.06(0.28)-0.02(0.77)
 WestReferenceReferenceReferenceReferenceReference
Lifestyle variables
Physical activity (participation vs. non-participation) -0.48(<0.00)-0.30(<0.001)-0.26(<0.001)-0.16(<0.001)-0.16(<0.001)
Smoking status (current vs. former and never smoker) -0.02(0.41)-0.01(0.74)0.01(0.80)0.00(0.93)----
Conventional Psychosocial Constructs
Self-efficacy0.30(<0.001)0.20(<0.001)0.14(<0.001)0.15(<0.001)
Social Support0.13(<0.001)0.11(<0.001)0.08(<0.001)0.08(<0.001)
Barriers-0.31(<0.001)-0.23(<0.001)-0.13(<0.001)-0.14(<0.001)
Benefits0.04(0.08)-0.07(0.02)-0.03(0.21)----
Novel Psychosocial Constructs
Vegetarianism views0.03(0.19)-0.02(0.44)----
Autonomous motivation0.17(<0.001)0.08(<0.001)0.06(0.01)
Controlled motivation-0.02(0.35)-0.03(0.23)----
Preference for fruit0.44(<0.001)0.20(0.06)----
Preference for vegetable0.55(<0.001)0.31(0.01)0.37(<0.001)
Singe Items
Creature of habit (eating same things all the time)-0.04(0.03)-0.03 (0.04)
Unwillingness to try new foods-0.04(0.06)----
Not attentive to government FV recommendations-0.01(0.46)----
Worry about one’s health0.01(0.55)----
Drink several cups of water daily0.14(<0.001)0.13(<0.001)
Seasonality (varying FV intake by season vs. eating same types year round) 0.18(<0.001)0.19(<0.001)
Did not eat fruit when growing up (negative responses) -0.07(<0.001)-0.08(<0.001)
Did not eat vegetable when growing up (negative responses) -0.08(<0.001)-0.08(<0.001)
No knowledge of FV recommendations (wrong responses vs. correct) -0.12(<0.001)-0.12(<0.001)
Eat more FV than other people I know0.16(<0.001)0.16(<0.001)
Often encourage my family/friends to eat FV0.02(0.33)----
R2 0.020.060.210.250.320.31
R2 change---0.040.15

Abbreviations: FVs denotes “fruits and vegetables”; NH denotes “Non-Hispanic”.

aScales that demonstrated good internal consistency (Tables 1 and 2) with Cronbach’s alpha ≥.68 were included in the regression analyses Single items that did not fit within a scale were also entered into the regression models.

Abbreviations: FVs denotes “fruits and vegetables”; NH denotes “Non-Hispanic”. aScales that demonstrated good internal consistency (Tables 1 and 2) with Cronbach’s alpha ≥.68 were included in the regression analyses Single items that did not fit within a scale were also entered into the regression models. Higher FVI (p<0.05) was reported by respondents reporting greater self-efficacy (β = 0.15), social support (β = 0.08), and autonomous motivation for consuming FVs (β = 0.06), as well as a preference for vegetables (β = 0.37). Higher FVI (p<0.01) was also reported by respondents that consumed different FVs seasonally (β = 0.19), perceived that they ate more FVs than other people they knew (β = 0.16), and drank several cups of water daily (β = 0.13).

Discussion

The FAB Survey measured conventional psychosocial constructs related to FVI (i.e., self-efficacy, social support, perceived barriers and benefits of eating FVs) that have been shown to be strong correlates of FVI [13,15,19,20,41,42]. Additionally, the survey included the development and assessment of novel psychosocial constructs related to FVI (i.e., vegetarianism, autonomous and controlled motivation, food neophobia, and preference for FVs). All scales, except food neophobia, demonstrated good internal consistency with Cronbach’s α ≥0.68. With regard to outcomes, adults consumed more FVs if they reported having greater self-efficacy and social support but consumed fewer FVs if they perceived more barriers. Other studies have reported similar findings [13,41-43]. Consistent with other studies [14,44], this study demonstrated that adults having preferences for a greater selection of vegetables ate more FVs. In addition, adults with higher autonomous motivation for consuming FVs also ate more FVs. According to the Self-Determination Theory, enhancing autonomous motivation is likely to result in sustainable behaviors (in this case, greater FVI), because it is self-driven, and not influenced by external pressures such as rewards/punishment [25,26,43]. Nevertheless, the effects of autonomous motivation on FVI have varied across studies [35,45]. Assessing and intervening on autonomous motivation in relation to FVI is relatively new, hence we termed it as novel; prior studies have focused mostly on autonomous motivation for other behaviors (i.e., smoking cessation) [46-48]. With regard to single items, the current study showed that FVI was greater among adults that reported eating more FVs than other people they knew, seasonality effects, and greater water consumption. However, lower FVI was reported by adults who did not eat FVs frequently while growing up, and those not knowledgeable of the daily recommendation. The current study highlights the need to introduce individuals to FVs early in life, given that these behaviors tend to track into adulthood, where they play a significant role in health and well-being [49-51]. In addition, this study helps provide foundational information in elucidating the role psychosocial constructs may play and their potential associations with FVI and how they can be harnessed and applied in behavioral interventions. Specifically, results from this study underscore the need to continue examining and intervening on “usual suspect” FV constructs (e.g., self-efficacy and social support) but that we should also continue to test novel constructs; namely ones explored in this analysis (e.g., seasonality, water intake, fruit and vegetable behaviors when growing up), as well as others, either derived from existing theories or as they are discovered through conducting research. Next steps include application of this information in intervention research. This study has some limitations. The cross-sectional design does not allow for assessment of causality between the psychosocial scales, single items, and FVI. Data were collected via self-report from participants and subject to recall bias. Due to budget constraints and the declining response rates to random-digit-dial telephone surveys [52], the samples for both the pilot and implementation studies were drawn from a consumer opinion panel. This approach has been used successfully with other health survey, such as the Styles [53]. Nevertheless, the FAB sample was weighted based on post-stratified 2000 U.S. Census values for sex, race/ethnicity, age, education, and income. Specifically for this sample, eligible participants were selected to be representative of the U.S. population and previous research that has compared panel and random digit dial results have shown comparability, indicating that panel studies are a viable alternative for data collection, especially as telephone random digit dial response rates are dropping [54]. Lastly, some consider the theory behind hot deck imputation underdeveloped [55], however, we used cyclical n-partition hot deck imputation, a method that retains the semiparametric features of the data and have no strong assumption required about distribution shapes [56,57]. Strengths of the study are the large sample size and oversampling of African Americans. The FV screener was tested for reliability and validated using 24-hour dietary recalls [37].

Conclusions

Most U.S. adults continue to not meet FV recommendations. Measures for assessing psychosocial constructs related to FVI vary and many assess a limited number of constructs. Few existing measurement tools have been tested among a national sample of U.S. adults. This paper describes the development and testing of FV-related measures among a sample of U.S. adults. It describes both conventional and novel correlates of FVI, which augments the literature in this area. Items and scales from the FAB Survey can be utilized and/or adapted by researchers interested in measuring FVI. It can also help inform behavioral interventions.
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Authors:  Sasha A Fleary; Patrece Joseph; Hong Chang
Journal:  Appetite       Date:  2019-12-03       Impact factor: 3.868

4.  Rationale and design for the community activation for prevention study (CAPs): A randomized controlled trial of community gardening.

Authors:  J S Litt; K Alaimo; M Buchenau; A Villalobos; D H Glueck; T Crume; L Fahnestock; R F Hamman; J R Hebert; T G Hurley; J Leiferman; K Li
Journal:  Contemp Clin Trials       Date:  2018-03-18       Impact factor: 2.226

5.  Psychometric Evidence of the Attitudes Toward Food Scale for Native Hawaiians.

Authors:  Olivia K Uchima; George M Harrison; Phoebe W Hwang; Ilima Ho-Lastimosa; Jane J Chung-Do
Journal:  Hawaii J Health Soc Welf       Date:  2021-10

6.  Positive attitudes toward legumes are associated with legume intake among adults in Puerto Rico.

Authors:  Elena C Hemler; Martha Tamez; José F Rodríguez Orengo; Josiemer Mattei
Journal:  Nutr Res       Date:  2022-03-25       Impact factor: 3.876

7.  The association between motivation and fruit and vegetable intake: The moderating role of social support.

Authors:  Kate E McSpadden; Heather Patrick; April Y Oh; Amy L Yaroch; Laura A Dwyer; Linda C Nebeling
Journal:  Appetite       Date:  2015-08-29       Impact factor: 3.868

8.  Dietary behaviors of adults born prematurely may explain future risk for cardiovascular disease.

Authors:  Mastaneh Sharafi; Valerie B Duffy; Robin J Miller; Suzy B Winchester; Tania B Huedo-Medina; Mary C Sullivan
Journal:  Appetite       Date:  2016-01-12       Impact factor: 3.868

9.  Fruit and Vegetable Intake and Barriers to Their Consumption among University Students in Kuwait: A Cross-Sectional Survey.

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Journal:  J Environ Public Health       Date:  2021-07-09

10.  Process Evaluation of a Farm-to-WIC Intervention.

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Journal:  J Acad Nutr Diet       Date:  2021-06-16       Impact factor: 5.234

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