Fruit and Vegetable Attitudes,Norms,and Intake in Low-Income Youth

Abstract

Fruit and vegetable (FV) attitudes and norms have been shown to influence intake in youth; yet research with low-income youth and studies supplementing self-report with objective measures of intake are lacking. Cross-sectional survey data on self-rated FV intake, FV attitudes, and FV norms were collected in a sample of 116 youth attending a residential summer camp serving low-income families. FV intake also was estimated by direct observation. Differences between self-rated and observed FV intake, perceived and observed peer intake, and perceived and peer-reported attitudes toward eating FVs were assessed with paired samples t tests. The role of FV attitudes, descriptive norms (perceived peer FV intake), injunctive norms (perceived peer attitudes toward eating FVs), and actual norms (observed peer FV intake and peer-reported FV attitudes) in predicting FV intake also was examined with multiple regression analysis. Youth misperceived their own and their peers’ FV intake (i.e., overestimated intake of fruit and underestimated intake of vegetables) and believed that peers held less favorable attitudes toward eating FVs than was the case. The models predicting self-rated intake were significant, accounting for 34% of the variance in fruit intake and 28% of the variance in vegetable intake. Attitudes and descriptive norms were positively associated with FV intake, and observed peer fruit intake was negatively associated with fruit intake. Findings suggest that in low-income youth, FV attitudes, descriptive norms, and normative peer behavior predict perceived but not actual intake. Youth may benefit from intervention to promote favorable FV attitudes and norms. A focus on descriptive norms holds promise for improving self-rated intake in this population.

Keywords

adolescents attitudes children fruit income social norms vegetables

Fruit and vegetable (FV) intake is an important component of a healthy diet, adding key nutrients that are underconsumed, reducing chronic disease risk, and facilitating weight management (Kim et al., 2014). Despite the health benefits of a diet rich in FVs, most U.S. children and adolescents have intakes that are below recommended levels (Holman & White, 2011; Kim et al., 2014; Liu, 2013). Low income is associated with low or less frequent intake (Rasmussen et al., 2006), underscoring the need for dietary intervention programs and policies to promote FV intake in this at-risk group. To reduce income disparities in intake, targeting low-income populations with tailored interventions is recommended (Robinson, 2008). Developing tailored interventions requires understanding of population-specific determinants of intake. Research on determinants of FV intake in low-income youth is limited, and studies of the same determinants are few, precluding understanding of which determinants are best supported by evidence and as such, should be the focus of intervention (Di Noia & Byrd-Bredbenner, 2014).

Theoretical understanding of personal health-related behaviors highlights the importance of such influences on behavior as attitudes toward the behavior, descriptive norms (perceptions of the behavior among peers), and injunctive norms (perceptions of peers’ attitudes toward the behavior). According to the theory of planned behavior, attitudes and injunctive norms predict behavioral intention, and ultimately, behavior (Larimer, Turner, Mallett, & Geisner, 2004). Support for the idea that descriptive norms influence behavior can be found in social learning, social comparison, and problem behavior theories emphasizing the role of observation and perception of the behavior of others in one’s social group in shaping behavior (Larimer et al., 2004). Dietary research has shown that positive attitudes toward eating FVs influence intake (Brug, Tak, te Velde, Bere, & de Bourdeaudhuij, 2008; Martens, van Assema, & Brug, 2005). Yet findings from studies examining the influence of FV descriptive and injunctive norms on intake are equivocal. For example, in one study, injunctive norms (perceptions of peers’ attitudes toward eating FVs) were negatively associated with FV intake, whereas descriptive norms (perceptions of peers’ intake) were unrelated to intake (Cullen et al., 2001), but positively associated with lunch FV consumption of fifth-grade students in another (Thompson, Bachman, Baranowski, & Cullen, 2007). In other work, injunctive norms were positively associated with FV intake (Granner et al., 2004). Elsewhere, injunctive norms were unrelated to FV intake, whereas descriptive norms were positively associated with intake (Lally, Bartle, & Wardle, 2011).

No or very small associations are found between child and adolescent FV intake and FV intake among peers, suggesting that peer behavior does not influence intake in youth (Ali, Amialchuk, & Heiland, 2011; Bruening et al., 2012; Cullen et al., 2001). Studies of the influence of descriptive norms on dietary behaviors including FV intake find that perceived but not actual norms are positively associated with the behaviors (Lally et al., 2011; Perkins, Perkins, & Craig, 2010). Together, this work suggests that in young people, dietary practices are influenced not by what peers do but by what youth think peers do. Whether this is true for injunctive FV norms is unknown, as studies of the influence on intake of actual norms (i.e., peer-reported attitudes toward eating FVs) are lacking.

According to the social norms approach commonly used in interventions to prevent alcohol and tobacco use in youth, problem behaviors are the result of social pressure to conform to erroneously perceived peer norms, that is, overestimates of problem behavior and peers’ acceptance of the behavior (Haines, Perkins, Rice, & Barker, 2005). The application of this approach to FV consumption would suggest that low FV intake is the result of conformity to misperceived descriptive and injunctive norms, that is, beliefs that friends eat less FVs and hold less favorable attitudes toward eating FVs than is the case. Notwithstanding investigations of the influence of social norms on FV intake, far less is known about whether youth accurately perceive peers’ FV intake and attitudes toward eating FVs. In one of the few studies of FV norms in youth to date, Lally et al. (2011) found that participants underestimated their peers’ FV intake and how positive their peers’ attitudes were toward eating FVs. The Lally et al. study was conducted in older adolescents (youth aged 16-19 years) using measures of norms for FV intake combined. The extent to which younger youth misperceive social norms for FV intake separately is unknown.

Although the aforementioned studies suggest that attitudes toward eating FVs and FV norms are important determinants of FV intake in youth, there is a dearth of studies of these potential determinants in low-income youth. Moreover, most findings to date are based on measures of FV intake obtained by self-report. Self-reported FV intake is susceptible to social desirability and social approval biases (Miller, Abdel-Maksoud, Crane, Marcus, & Byers, 2008). Differences also are found in the variance explained by attitudes and norms when behavior measures are self-reports than when measures are objective or observed (Armitage & Conner, 2001). Thus, greater use of objective assessments would overcome the limitations of self-report and aid understanding of the extent to which FV attitudes and norms explain objectively measured FV intake.

This study examined FV attitudes, norms, and intake (assessed separately for FVs) in a sample of low-income youth aged 7 to 13 years. FVs were treated as distinct owing to differences found by food type in intake levels and psychosocial correlates of intake (Glasson, Chapman, & James, 2010). The aims were to (1) determine whether youth misperceived their FV intake, their peers’ FV intake, and their peers’ attitudes toward eating FVs relative to observed FV intake, observed peer FV intake, and peer-reported attitudes toward eating FVs and (2) examine the role of attitudes toward eating FVs, descriptive norms, injunctive norms, and actual norms (observed peer intake and peer-reported attitudes toward eating FVs) in predicting self-rated and observed FV intake. Based on previous work, it was hypothesized that (1) youth would overestimate their FV intake, underestimate their peers’ FV intake, and underestimate how positive their peers’ attitudes were toward eating FVs; (2) FV attitudes and norms would be significantly associated with self-rated and observed FV intake; (3) the associations between descriptive and injunctive norms and FV intake would be stronger than the associations between actual norms and FV intake; and (4) the models predicting self-rated FV intake would explain more of the variance in intake than the models predicting observed FV intake. Study constructs, operational definitions, and hypothesized relationships with intake are shown in Figure 1.

Figure 1.

Study constructs, operational definitions, and hypothesized associations with fruit and vegetable (FV) intake.

Method

Design and Participants

This cross-sectional study was a secondary analysis of baseline data provided by youth in a dietary intervention study (Di Noia, Orr, & Byrd-Bredbenner, 2014). The study setting was a residential summer camp serving low-income youth (i.e., those eligible for free or reduced-price lunch during the school year). Youth attending the first of three 9-day camping sessions were offered the opportunity to participate when registering for camp. The inclusionary criterion was participation in regular programming (those attending programs that did not run each session were excluded). Eligible youth (N = 137) provided informed written assent, and informed written consent was obtained from a parent or guardian. Data provided by 21 youth who went home before the end of the session and were therefore not present across days of data collection were excluded. The analysis sample size of 116 provided 80% power to detect an R² value = .14 in multiple regression analyses with up to 10 predictor variables. Study procedures were reviewed and approved by William Paterson University’s Institutional Review Board.

FV intake was assessed by direct observation on 3 nonconsecutive days (as described below), and on the next to last day of camp, youth were administered a questionnaire assessing demographics, self-rated FV intake, and FV attitudes and norms. Designed for youth at the youngest age involved in the study (7 years), the questionnaire was reviewed by a developmental psychologist experienced in working with this age group and was revised to simplify the wording and to add pictorial representations of response choices. The questionnaire was then pilot tested in a comparable group of 7 year olds (N = 6). Pilot test participants had some difficulty distinguishing fruits from vegetables. Instructions for completing the measure were therefore revised to include examples (and corresponding pictures) of these foods. Data were collected between June 30 and July 6, 2012.

Measures

Observed FV Intake

Procedures for observing participants’ FV intake are described in detail elsewhere (Di Noia et al., 2014). Briefly, counselors seated with youth at meals observed the amounts they consumed of FV servings using the plate-waste-by-visual-estimate method (Buzby & Guthrie, 2002) and recorded this information on a form (response options were zero, one fourth, one half, three fourths, and all). This quarter waste method has high interrater and intermethod reliability (Hanks, Wansink, & Just, 2014). Observations were conducted on 3 nonconsecutive days (2 weekdays and 1 weekend day). The amounts were averaged across days to derive a measure of servings per day. Counselors were trained to accurately record youths’ FV intake at a workshop held before the start of camp. The kappa statistic for pairs of observations by food type was .64 for fruits and .63 for vegetables, indicating a substantial level of agreement between observers (Viera & Garrett, 2005).

Self-Rated FV Intake

The youth questionnaire included items for assessing quantities of FVs typically consumed at camp. The items were aligned with FV offerings at meals. Youth were provided one serving of fruit or juice at breakfast and one serving each of FVs at lunch and dinner daily. Every third day, they were provided one serving of fruit as a midevening snack. One item each assessed their intake of the items (6 items; α = .75; sample item: “On most days at camp, how much do you eat of the fruit served at lunch?”). Response options on a 5-point scale were none, some, about half, most, and all. Circles depicting corresponding amounts were presented beneath each response choice, for example, for “some,” a circle with ¼ missing and ¾ left was shown; for “most” a circle with ¾ missing and ¼ left was shown. Responses were summed across items.

FV Norms

Youth were assigned to cabins based on sex and age. They shared sleeping quarters, ate meals, and participated in activities with other youth in their cabin as a group. FV norms were assessed with reference to this group. Youth completed measures of perceived peer intake (6 items; α = .83; sample item: “On most days at camp, how much do other boys or girls in your cabin eat of the fruit served at lunch?”), attitudes toward eating FVs (6 items; α = .79; sample item: “I think that eating fruit at lunch is a good thing to do”), and perceived peer attitudes toward eating FVs (6 items; α = .88; sample item: “Other boys or girls in my cabin think that eating fruit at lunch is a good thing to do”). The items were drawn from existing social norm measures (Cullen et al., 2001; Lally et al., 2011). Response options on 5-point scales were tailored to the nature of the questions (for perceived peer intake, the responses were the same as those in the measure of self-rated intake, and for attitudes and perceived peer attitudes, the responses were no, not really, in the middle, sort of, and yes). Responses were averaged across items.

Observed Peer Intake

The amounts of FVs consumed by peers were estimated using observational data. Youth with whom participants shared a cabin were the referent group (there were, on average, 13 participants per cabin [range = 9-17 participants]). A score was calculated for each participant as the mean observed intake among the referent group, that is, the mean observed intake for the cabin (excluding the participant’s observed intake).

Peer-Reported Attitudes Toward Eating FVs

Peer-reported attitudes toward eating FVs were estimated in a similar fashion using self-reported attitudinal data. A score was calculated for each participant as the mean self-reported attitude score among the referent group, that is, the mean attitude score for the cabin (excluding the participant’s self-reported attitude score).

Covariates

Closed-ended, multiple-choice items were used to assess participant demographic characteristics, that is, sex, age, race, and Hispanic ethnicity. An on-site nurse measured participants’ height and weight with a stadiometer and mechanical scale, respectively. Body mass index (BMI) was calculated, and youth were classified into one of four weight status categories based on BMI-for-age percentiles (Centers for Disease Control and Prevention, 2014).

Analysis

Descriptive statistics were computed to characterize the sample. Differences between mean self-rated and observed FV intake, perceived and observed peer FV intake, and perceived and peer-reported attitudes toward eating FVs were examined with paired samples t tests. A positive difference, if found, indicated the overestimation of self-rated intake, perceived peer intake, and perceived peer attitudes toward eating FVs. Multiple regression analysis was used to identify predictors of self-rated and observed FV intake. Analyses (conducted in SPSS version 22) were controlled for participant demographic and anthropometric characteristics. Categorical predictors were dichotomously coded as follows: sex (0 = male, 1 = female), race (0 = non-Hispanic White or other, 1 = non-Hispanic Black), and ethnicity (0 = non-Hispanic, 1 = Hispanic). Across analyses, the level of significance was set at p < .05.

Results

Participant demographic and anthropometric characteristics are shown in Table 1. Youth had a mean (SD) age of 10.12 (1.75) years (range = 7-13 years) and were 56% female, 43% Hispanic, and 37% non-Hispanic Black. A small percentage of youth (1%) were underweight, 58% were a healthy weight, 19% were overweight, and 22% were obese.

Table 1.

Participant Demographic and Anthropometric Characteristics (N = 116).

Characteristic	Mean (SD) or n (%)
Sex
Male	51 (44)
Female	65 (56)
Age	10.12 (1.75)
Race/ethnicity
Hispanic	50 (43)
Non-Hispanic Black	43 (37)
Non-Hispanic White or other	22 (19)
Not reported	1 (01)
Body mass index	20.40 (4.43)
CDC weight status category
Underweight	01 (01)
Healthy weight	67 (58)
Overweight	22 (19)
Obese	26 (22)

Note. CDC = Centers for Disease Control and Prevention.

Misperceived FV Intake and FV Norms

Differences between self-rated and observed FV intake, perceived and observed peer FV intake, and perceived and peer-reported attitudes toward eating FVs are shown in Table 2. Youth overestimated their fruit intake and underestimated their vegetable intake (mean [SD] self-rated and observed intake were 3.09 [0.92] and 2.71 [0.74], respectively, for fruit [t(113) = 4.00, p = .000] and 0.99 [0.63] and 1.48 [0.69], respectively, for vegetables [t(113) = −6.19, p = .000]). Similarly, youth overestimated the amount of fruit and underestimated the amount of vegetables consumed by peers (mean [SD] perceived and observed peer intake were 2.94 [0.93] and 2.71 [0.22], respectively, for fruit [t(115) = 2.58, p = .011] and 0.98 [0.58] and 1.47 [0.33], respectively, for vegetables [t(115) = −7.42, p = .000]). Youth underestimated how positive their peers’ attitudes were toward eating fruit and how positive their peers’ attitudes were toward eating vegetables (mean [SD] perceived and peer-reported attitudes were 4.32 [0.88] and 4.54 [0.18], respectively, for fruit [t(113) = −2.71, p = .008] and 4.00 [1.16] and 4.35 [0.20], respectively, for vegetables [t(113) = −3.17, p = .002]).

Table 2.

Differences Between Mean (SD) Subjective and Objective Measures of Respondents’ Fruit and Vegetable Intake, Their Peers’ Fruit and Vegetable Intake, and Their Peers’ Attitudes Toward Eating Fruit and Vegetables (N = 116).

Variable	Subjective	Objective	Difference
Fruit intake	3.09 ± 0.92^a	2.71 ± 0.74^b	0.38 ± 1.01***
Vegetable intake	0.99 ± 0.63^a	1.48 ± 0.69^b	−0.49 ± 0.84***
Peer fruit intake	2.94 ± 0.93^c	2.71 ± 0.22^d	0.22 ± 0.95*
Peer vegetable intake	0.98 ± 0.58^c	1.47 ± 0.33^d	−0.48 ± 0.70***
Peer attitudes toward eating fruit	4.32 ± 0.88^e	4.54 ± 0.18^f	−0.22 ± 0.89**
Peer attitudes toward eating vegetables	4.00 ± 1.16^e	4.35 ± 0.20^f	−0.35 ± 1.21**

Note. Differences examined with paired samples t tests.

Self-rated intake. ^bObserved intake. ^cPerceived peer intake. ^dObserved peer intake. ^ePerceived peer attitudes. ^fPeer-reported attitudes.

p < .05. **p < .01. ***p < .001.

Predictors of Self-rated and Observed Intake

Only the models predicting self-rated FV intake were significant, accounting for 40% and 34% of the variance in FV intake, respectively, F(10, 101) = 6.92, p = .000, adjusted R² = .34, for fruit and F(10, 101) = 5.30, p = .000, adjusted R² = .28, for vegetables. Beta weights (standardized regression coefficients) for variables included in the models are shown in Table 3. The beta weights for female sex (.21), perceived peer fruit intake (.44), attitudes toward eating fruit (.37), and observed peer fruit intake (−.24) were significant in the model predicting self-rated fruit intake. In the model predicting self-rated vegetable intake, the beta weights for perceived peer vegetable intake (.39) and attitudes toward eating vegetables (.33) were significant. Whereas attitudes and descriptive norms were positively associated with self-rated FV intake, respectively, observed peer fruit intake was negatively associated with self-rated fruit intake.

Table 3.

Multiple Regression Analysis of Variables Predicting Self-Rated and Observed Fruit and Vegetable Intake (N = 116).

	Self-rated intake		Observed intake
Predictor variable	Fruit, β ± SE	Vegetable, β ± SE	Fruit, β ± SE	Vegetable, β ± SE
Age	0.05 ± 0.05	0.05 ± 0.04	0.25 ± 0.04	0.07 ± 0.05
Female sex	0.21 ± 0.16*	−0.12 ± 0.10	0.23 ± 0.16	0.00 ± 0.13
Hispanic ethnicity	−0.05 ± 0.20	−0.08 ± 0.14	0.16 ± 0.19	−0.09 ± 0.19
Non-Hispanic Black race	−0.15 ± 0.20	−0.11 ± 0.14	0.10 ± 0.19	0.00 ± 0.18
Body mass index	−0.01 ± 0.01	−0.01 ± 0.01	−0.14 ± 0.01	−0.05 ± 0.01
Perceived peer intake	0.44 ± 0.08***	0.39 ± 0.09***	−0.17 ± 0.08	0.03 ± 0.12
Attitude^a	0.37 ± 0.14***	0.33 ± 0.06**	0.13 ± 0.13	0.10 ± 0.08
Perceived peer attitude^b	−0.16 ± 0.10	−0.10 ± 0.06	0.05 ± 0.10	−0.03 ± 0.07
Observed peer intake	−0.24 ± 0.45*	−0.15 ± 0.21	−0.25 ± 0.43	0.31 ± 0.27
Peer-reported attitude^c	0.07 ± 0.47	−0.03 ± 0.28	0.20 ± 0.45	0.02 ± 0.35
Adjusted R²	0.34	0.28	0.03	0.05
F	6.92***	5.30***	1.41	1.66

Defined as the perceived extent to which eating fruit and vegetables, respectively, is considered “a good thing to do.” ^bDefined as the perceived extent to which peers consider eating fruit and vegetables, respectively, “a good thing to do.” ^cCalculated as the mean attitude score among the respondents’ sex and age group, excluding the respondent’s score.

p < .05. **p < .01. ***p < .001.

Discussion

Drawing from theory and research on attitudes and norms affecting dietary behavior, this study examined, in a sample of low-income youth, whether participants misperceived their own FV intake, their peers’ FV intake, and their peers’ attitudes toward eating FVs. The relationships between FV attitudes, FV norms, and self-rated and observed FV intake also were examined. Participants believed that they and their peers ate more fruit and fewer vegetables and that their peers held less favorable attitudes toward eating FVs than was the case based on observational and peer-reported data. Whereas attitudes, descriptive norms, and injunctive norms were unrelated to observed FV intake, attitudes, descriptive norms, and observed peer intake were significant predictors of self-rated fruit intake, and attitudes and descriptive norms were significant predictors of self-rated vegetable intake. The somewhat larger beta weights found for attitudes and descriptive norms as compared with observed peer intake in the model predicting self-rated fruit intake suggest that their effects on intake were stronger than actual peer behavior. The more favorable attitudes toward eating fruit the respondent had, the more fruit the respondent believed peers ate, and the less fruit the respondent’s peers were observed eating, the more fruit he or she ate. The more favorable attitudes toward eating vegetables the respondent had and the more vegetables the respondent believed peers ate, the more vegetables he or she ate.

As reported elsewhere, youth misestimated their own FV intake relative to the amounts of FVs they were observed eating (Di Noia & Contento, 2009). It has been suggested that because of peer influence and a desire to conform to group norms, youth try to match their peers’ attitudes and behavior and thus adjust their eating habits to misperceived standards (Stok, de Ridder, de Vet, & de Wit, 2013; Story, Neumark-Sztainer, & French, 2002). As shown in this study, youth believed that their peers ate more fruit and fewer vegetables than was the case. They also overestimated their own fruit intake and underestimated their own vegetable intake. The over- and underestimations found may be an artifact of conformity to perceived peer norms. Alternatively, the misestimations may be explained by the greater number of questionnaire items assessing intake of fruit (4 items) as compared with vegetables (2 items). Reported FV intake has been shown to increase in direct proportion to the number of items assessing intake (Krebs-Smith, Heimendinger, Subar, Patterson, & Pivonka, 1995; Kristiansen, Lillegaard, & Anderson, 2013). The over- and underestimations may also be an artifact of the greater frequency with which fruit was served. On the other hand, because fruit was served often, youth may have believed that eating fruit was the expected norm. Because self-reported FV intake is susceptible to social desirability and social approval biases, the overestimation of fruit intake may be explained by the tendency to respond to FV questionnaire items in a manner consistent with expected norms (Miller et al., 2008).

These findings extend research demonstrating that youth misperceive their peers’ attitudes toward eating FVs and their peers’ FV intake (Lally et al., 2011). Whereas Lally et al. found that youth underestimated how positive their peers’ attitudes were toward eating FVs combined, this study found that youth underestimated how positive their peers’ attitudes were toward eating FVs considered separately. Lally et al. also found that youth underestimated their peers’ FV intake. In this study, participants’ perceptions of their peers’ FV intake differed by food type (i.e., peers were perceived as eating more fruit but fewer vegetables than was the case). Youth recognize fruit more easily than vegetables and rate fruit as more acceptable than vegetables (Cullen et al., 2001; Edwards & Hartwell, 2002). If eating fruit is considered to be more socially acceptable and less susceptible to peer ridicule than eating vegetables, this may explain why youth overestimated their peers’ fruit intake and underestimated their peers’ vegetable intake (Stok et al., 2013). On the other hand, the misestimations found may be explained by stronger taste preferences for fruit as compared with vegetables in youth (Cooke & Wardle, 2005). Youth may believe that their peers consume greater amounts of foods that are preferred and less of those that are disliked.

The aforementioned findings suggest that youth may benefit from intervention to correct misperceived FV norms. Presenting information on actual group norms is recommended for this purpose (Haines et al., 2005). A recent study found a positive impact of messages with positive descriptive social norms toward eating vegetables on observed vegetable intake (Robinson, Fleming, & Higgs, 2013). In other work, a positive impact of messages with positive descriptive social norms toward eating fruit was found on fruit intake (Stok et al., 2013). Addressing vegetable descriptive norms and FV injunctive norms seems warranted as raising awareness that peers eat more vegetables and hold more positive attitudes toward eating FVs than was believed may encourage higher vegetable intake. Unclear, however, is whether intervention is warranted to correct misperceived fruit descriptive norms. Possibly, increasing recognition that that peers eat less fruit than was believed would have the effect opposite that intended, that is, encourage lower fruit intake.

The finding that FV attitudes and descriptive norms were positively associated with self-rated FV intake supports the work of others (Brug et al., 2008; Lally et al., 2011; Martens et al., 2005; Thompson et al., 2007). The negative association found between observed peer and self-rated fruit intake is novel. As expected, the association was stronger for perceived as compared with actual peer intake. The associations found highlight the potent effects of descriptive norms on self-rated fruit intake. The more fruit the respondent believed peers consumed, the more fruit the respondent believed he or she consumed despite having peers who modeled low fruit intake.

FV attitudes, descriptive norms, and injunctive norms were unrelated to observed FV intake, raising questions regarding whether these constructs predict actual behavior. Previous work has shown that home FV availability moderates the associations between psychosocial variables and FV intake (Di Noia & Byrd-Bredbenner, 2013; Kratt, Reynolds, & Shewchuk, 2000; Young, Fors, & Hayes, 2004). Several factors limit access to FVs in low-income households, that is, food insecurity, low availability of FVs in low-income neighborhoods, and the high cost of FVs in areas lacking supermarkets (Larsen & Gilliland, 2009). Possibly, FV attitudes and norms have little influence on FV intake in a food environment where FVs are scarce. In a review of determinants of FV intake in low-income youth, FV attitudes and norms were not among the determinants studied. Understanding of their potential influence on intake is therefore limited (Di Noia & Byrd-Bredbenner, 2014). The present findings suggest that research using self-report measures of FV intake may overestimate the associations among FV attitudes, norms, and intake.

Several limitations must be noted. The study was conducted in a single setting; thus, findings may not be generalizable to low-income youth in other residential summer camp programs or in other settings such as schools. The cross-sectional design limited the ability to infer causality. Although the sample size provided adequate power to detect 14% or more of the variance in FV intake, it was not sufficiently large to detect smaller proportions of the variance. Possibly, FV attitudes and norms explain less of the variance in observed FV intake. A larger sample size would make it possible to determine whether this is the case. Because observations of youths’ intake were conducted by counselors seated with youth at meals, youth may have been aware that they were being observed and this awareness may have influenced their eating behavior. FV attitudes and norms were assessed via self-report and may therefore be susceptible to social desirability bias (Armitage & Conner, 2001). The focus on low-income youth and inclusion of objective measures of FV intake are study strengths.

Implications for Health Education Practice and Research

The present findings suggest that youth may benefit from intervention to promote favorable attitudes toward eating FVs and FV descriptive norms. The overestimation of peer fruit intake may encourage higher fruit intake in youth; thus, intervening on fruit descriptive norms may be unnecessary. Raising awareness that peer vegetable intake is higher than was believed is recommended. Health practitioners working with low-income youth are encouraged to assess FV attitudes and norms to confirm the over- and underestimations found in this study, and to use the resulting information to educate youth about actual group norms. Practitioners might consider using as delivery channels posters, flyers, and informational booklets found effective in conveying descriptive norm messages (Robinson et al., 2013; Stok et al., 2013). Further research is needed to determine whether FV attitudes and norms are associated with objectively measured FV intake. Research examining factors contributing to misperceived norms also is warranted. Studies that differentiate FV attitudes, norms, and intake may be more informative than those that operationalize these constructs for FVs combined.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported, in part, by funds from a summer stipend from the Research Center for the Humanities and Social Sciences at William Paterson University.

References

Ali

M. M.

Amialchuk

Heiland

F. W.

(2011). Weight-related behavior among adolescents: The role of peer effects. PLoS One, 6, e21179. doi:10.1371/journal.pone.0021179

Armitage

C. J.

Conner

(2001). Efficacy of the theory of planned behavior: Meta analytic review. British Journal of Social Psychology, 40, 471-499. doi:10.1348/014466601164939

Bruening

Eisenberg

MacLehose

Nanney

M. S.

Story

Neumark-Sztainer

(2012). The relationship between adolescents’ and their friends’ eating behaviors: Breakfast fruit, vegetable, whole grain, and dairy intake. Journal of the Academy of Nutrition and Dietetics, 112, 1608-1613. doi:10.1016/j.jand.2012.07.008

Brug

Tak

N. I.

te Velde

S. J.

Bere

de Bourdeaudhuij

(2008). Taste preferences, liking and other factors related to fruit and vegetable intakes among schoolchildren: Results from observational studies. British Journal of Nutrition, 99, S7-S14. doi:10.1017/S0007114508892458

Buzby

J. C.

Guthrie

J. F.

(2002). Plate waste in school nutrition programs: Final report to Congress (U.S. Department of Agriculture, Economic Research Service; Publication No. E-FAN-02-009). Retrieved from http://162.79.45.209/media/887982/efan02009.pdf

Centers for Disease Control and Prevention. (2014). About BMI for children and teens. Retrieved from http://www.cdc.gov/healthyweight/assessing/bmi/childrens_bmi/about_childrens_bmi.html

Cooke

L. J.

Wardle

(2005). Age and gender differences in children’s food preferences. British Journal of Nutrition, 93, 741-746. doi:10.1079/BJN20051389

Cullen

K. W.

Baranowski

Rittenberry

Cosart

Hebert

de Moor

(2001). Child-reported family and peer influences on fruit, juice and vegetable consumption: Reliability and validity of measures. Health Education Research, 16, 187-200. doi:10.1093/her/16.2.187

Di Noia

Byrd-Bredbenner

. (2013). Adolescent fruit and vegetable intake: Influence of family support and moderation by home availability of relationships with Afrocentric values and taste preferences. Journal of the Academy of Nutrition and Dietetics, 113, 803-808. doi:10.1016/j.jand.2013.02.001

10.

Di Noia

Byrd-Bredbenner

. (2014). Determinants of fruit and vegetable intake in low-income children and adolescents. Nutrition Reviews. Advance online publication. doi:10.1111/nure.12126

11.

Di Noia

Contento

I. R

. (2009). Use of a brief food frequency questionnaire for estimating daily number of servings of fruits and vegetables in a minority adolescent population. Journal of the American Dietetic Association, 109, 1785-1789. doi:10.1016/j.jada.2009.07.002

12.

Di Noia

Orr

Byrd-Bredbenner

. (2014). Residential summer camp intervention improves camp food environment. American Journal of Health Behavior, 38, 631-640. doi:10.5993/AJHB.38.4.17

13.

Edwards

J. S. A.

Hartwell

H. H.

(2002). Fruits and vegetables: Attitudes and knowledge of primary school children. Journal of Human Nutrition and Dietetics, 15, 365-374. doi:10.1046/j.1365-277X.2002.00386.x

14.

Glasson

Chapman

James

(2010). Fruit and vegetables should be targeted separately in health promotion programmes: Differences in consumption levels, barriers, knowledge and stages of readiness for change. Public Health Nutrition, 14, 694-701. doi:10.1017/S13689880010001643

15.

Granner

M. L.

Sargent

R. G.

Calderon

K. S.

Hussey

J. R.

Evans

A. E.

Watkins

K. W.

(2004). Factors of fruit and vegetable intake by race, gender, and age among young adolescents. Journal of Nutrition Education and Behavior, 36, 173-180. doi:10.1016/S1499-4046(06)60231-5

16.

Haines

M. P.

Perkins

H. W.

Rice

R. M.

Barker

(2005). A guide to marketing social norms for health promotion in schools and communities. Retrieved from http://www.alcoholeducationproject.org/guidebook.html

17.

Hanks

A. S.

Wansink

Just

D. R.

(2014). Reliability and accuracy of real-time visualization techniques for measuring school cafeteria tray waste: Validating the quarter-waste method. Journal of the Academy of Nutrition and Dietetics, 114, 470-474. doi:https://dx-doi-org.web.bisu.edu.cn/10.1016/j.jand.2013.08.013

18.

Holman

D. M.

White

M. C.

(2011). Dietary behaviors related to cancer prevention among preadolescents and adolescents: The gap between recommendations and reality. Nutrition Journal, 10, 60. doi:10.1186/1475-2891-10-60

19.

Kim

S. A.

Moore

L. V.

Galuska

Wright

A. P.

Harris

Grummer-Strawn

L. M.

. . .Rhodes

D. G.

(2014). Vital signs: Fruit and vegetable intake among children—United States, 2003-2010. Morbidity and Mortality Weekly Report, 63(31), 671-676.

20.

Kratt

Reynolds

Shewchuk

(2000). The role of availability as a moderator of family fruit and vegetable consumption. Health Education & Behavior, 27, 471-482. doi:10.1177/109019810002700409

21.

Krebs-Smith

S. M.

Heimendinger

Subar

A. F.

Patterson

B. H.

Pivonka

(1995). Using food frequency questionnaires to estimate fruit and vegetable intake: Association between the number of questions and total intake. Journal of Nutrition Education, 27, 80-85. doi:10.1016/S0022-3182(12)80346-3

22.

Kristiansen

A. L.

Lillegaard

I. T. L.

Anderson

L. F.

(2013). Effect of changes in a food frequency questionnaire: Comparing data from two national dietary survey instruments among 12-month-old infants. BMC Public Health, 13, 680. doi:10.1186/1471-2458-13-680

23.

Lally

Bartle

Wardle

(2011). Social norms and diet in adolescents. Appetite, 57, 623-627. doi:10.1016/j.appet.2011.07.015

24.

Larimer

M. E.

Turner

A. P.

Mallett

K. A.

Geisner

I. M.

(2004). Predicting drinking behavior and alcohol-related problems among fraternity and sorority members: Examining the role of descriptive and injunctive norms. Psychology of Addictive Behaviors, 18, 203-212. doi:10.1037/0893-164X.18.3.203

25.

Larsen

Gilliland

(2009). A farmers’ market in a food desert: Evaluating impacts on the price and availability of healthy food. Health & Place, 15, 1158-1162. doi:10.1016/j.healthplace.2009.06.007

26.

Liu

R. H.

(2013). Health-promoting components of fruits and vegetables in the diet. Advances in Nutrition, 4, 384S-392S. doi:10.3945/an.112.003517

27.

Martens

M. K.

van Assema

Brug

(2005). Why do adolescents eat what they eat? Personal and social environmental predictors of fruit, snack and breakfast consumption among 12-14-year-old Dutch students. Public Health Nutrition, 8, 1258-1265. doi:10.1079/PHN2005828

28.

Miller

T. M.

Abdel-Maksoud

M. F.

Crane

L. A.

Marcus

A. C.

Byers

T. E.

(2008). Effects of social approval bias on self-reported fruit and vegetable consumption: A randomized controlled trial. Nutrition Journal, 7, 118. doi:10.1186/1475-2891-7-18

29.

Perkins

J. M.

Perkins

H. W.

Craig

D. W.

(2010). Misperceptions of peer norms as a risk factor for sugar-sweetened beverage consumption among secondary school students. Journal of the American Dietetic Association, 110, 1916-1921. doi:10.1016/j.jada.2010.09.008

30.

Rasmussen

Krolner

Klepp

K. I.

Lytle

Brug

Bere

Due

(2006). Determinants of fruit and vegetable consumption among children and adolescents: A review of the literature. Part I: Quantitative studies. International Journal of Behavioral Nutrition and Physical Activity, 3, 22. doi:10.1186/1479-5868-3-22

31.

Robinson

Fleming

Higgs

(2013). Prompting healthier eating: Testing the use of health and social norm based messages. Health Psychology, 33, 1057-1064. doi:10.1037/a0034213

32.

Robinson

(2008). Applying the socio-ecological model to improving fruit and vegetable intake among low-income African Americans. Journal of Community Health, 33, 395-406. doi:10.1007/s10900-008-9109-5

33.

Stok

F. M.

de Ridder

D. T. D.

de Vet

de Wit

J. B. F.

(2013). Don’t tell me what I should do, but what others do: The influence of descriptive and injunctive peer norms on fruit consumption in adolescents. British Journal of Health Psychology, 19, 52-64. doi:10.1111/bjhp.12030

34.

Story

Neumark-Sztainer

French

(2002). Individual and environmental influences on adolescent eating behaviors. Journal of the American Dietetic Association, 102, S40-S51. doi:10.1016/S0002-8223(02)90421-9

35.

Thompson

V. J.

Bachman

C. M.

Baranowski

Cullen

K. W.

(2007). Self-efficacy and norm measures for lunch fruit and vegetable consumption are reliable and valid among fifth grade students. Journal of Nutrition Education and Behavior, 39, 2-7. doi:10.1016/j.jneb.2006.06.006

36.

Viera

A. J.

Garrett

J. M.

(2005). Understanding interobserver agreement: The kappa statistic. Family Medicine, 37, 360-363.

37.

Young

E. M.

Fors

S. W.

Hayes

D. M.

(2004). Associations between perceived parent behaviors and middle school student fruit and vegetable consumption. Journal of Nutrition Education and Behavior, 36, 2-12. doi:10.1016/S1499-4046(06)60122-X