Students Cluster into 4 Groups According to the Factors Influencing their Dietary Intake
1998; Elsevier BV; Volume: 98; Issue: 12 Linguagem: Inglês
10.1016/s0002-8223(98)00333-2
ISSN1878-3570
AutoresTanya Horacek, Nancy M. Betts,
Tópico(s)Health and Lifestyle Studies
ResumoStudents typically have poor dietary habits ((1)Hertzler A.A. Frary R.B. Food behavior of college students.Adolescence. 1989; 24: 349-356Google Scholar, (2)Hoffman C.J. Dietary intake of calcium, iron, folacin, alcohol, and fat for college students in central Michigan.J Am Diet Assoc. 1989; 89: 836-838Google Scholar, (3)Horwarth C.C. Dietary intakes and nutritional status among university undergraduates.Nutr Res. 1991; 11: 395-404Google Scholar, (4)Huang Y. Song W.O. Schemmel R.A. Hoerr S.M. What do college students eat? Food selection and meal pattern.Nutr Res. 1994; 14: 1143-1153Google Scholar, (5)Marrale JC, Shipman JH, Rhodes ML. What some college students eat. Nutr Today. Jan-Feb 1986:16–21.Google Scholar, (6)Skinner J.D. Changes in students' dietary behavior during a college nutrition course.J Nutr Educ. 1991; 23: 72-75Google Scholar, (7)Schuette L.K. Song W.O. Hoerr S.L. Quantitative use of the Food Guide Pyramid to evaluate dietary intake of college students.J Am Diet Assoc. 1996; 96: 453-457Google Scholar, (8)Horacek T.M. The effect of nutrition education and the differences in dietary intake and factors influencing intake according to personality preferences for a sample of college students. University of Nebraska, Lincoln1996Google Scholar). Although many researchers have determined the factors that influence intakes, not all students choose foods for the same reasons, and the set of factors that influence 1 group may be different from that which influences another ((8)Horacek T.M. The effect of nutrition education and the differences in dietary intake and factors influencing intake according to personality preferences for a sample of college students. University of Nebraska, Lincoln1996Google Scholar, (9)Betts N.M. Amos R.J. Georgiou C. Hoerr S.L. Ivanturi R. Keim K.S. Tinsley A. Voichick J. What young adults say about factors affecting their food intake.Ecol Food Nutr. 1995; 34: 59-64Google Scholar, (10)Betts N.M. Amos R.J. Keim K. Peters P. Stewart B. Ways young adults view food.J Nutr Educ. 1997; 29: 73-79Google Scholar, (11)Koszewski W.M. Kuo M. Factors that influence the food consumption behavior and nutritional adequacy of college women.J Am Diet Assoc. 1996; 96: 1286-1288Google Scholar). The objectives of our study were to determine how a sample of college students clustered according to the factors influencing their dietary intake, and to identify the differences in dietary intake that existed between the clustered groups.MethodsTo ensure diversity in the study sample, approximately 400 students from 3 large, introductory nutrition classes and approximately 600 students from 26 various small classes were invited to participate. A 20-minute recruitment presentation was made to each class. Students volunteered to complete packets and return them via campus mail. The research was approved by the Institutional Review Board for the Protection of Human Subjects at the University of Nebraska, Lincoln.The survey of factors influencing diet was based on the findings of Betts and colleagues ((9)Betts N.M. Amos R.J. Georgiou C. Hoerr S.L. Ivanturi R. Keim K.S. Tinsley A. Voichick J. What young adults say about factors affecting their food intake.Ecol Food Nutr. 1995; 34: 59-64Google Scholar). Two versions of the survey were developed and pretested with 50 students. The selected version was revised and included questions on influencing factors, basic demographics, and meal frequencies. Each influencing factor (see Table 1 for the questions) was rated on a 4-point scale, ranging from very likely (high score) to very unlikely (low score) to influence what the student ate.Table 1Dietary influences: factor analysis, sample factor averages, and cluster group factor averagesFactoraEach factor is listed with its Cronbach α, a measure of factor reliability.Contributing questionsFactor loadingbFactor loading is the contributing questions' correlation with the factor.Mean±SDcMean±standard deviation is given for each factor for the whole sample. Factor scores range from 1 to 4, with a higher score indicating a stronger influence on what students chose to eat.Cluster groups1, Cues (n=155; 47.7%)2. Budget (n=30; 9.2%)3, Health (n=86; 26.5%)4, No cues (n=54; 16.6%)Weight/healthFat (amount of fat in food)0.862.72±0.78t(P<.05) significant difference between values down the column whose letters differ.2.94x(P<.05) significant difference between values in a row whose letters differ.1.58z(P<.05) significant difference between values in a row whose letters differ.3.13x(P<.05) significant difference between values in a row whose letters differ.2.06y(P<.05) significant difference between values in a row whose letters differ.(α=.87)Calories (number of calories in food)0.83Weight (gain, lose, or maintain)0.83Health (concern for present and future status)0.72Appearance (how you look)0.65Nutrients (amount of nutrients in foods)0.60BudgetPrice (expense of a food)0.832.83±0.64u(P<.05) significant difference between values down the column whose letters differ3.19x(P<.05) significant difference between values in a row whose letters differ.3.03x(P<.05) significant difference between values in a row whose letters differ.2.38y(P<.05) significant difference between values in a row whose letters differ.2.40y(P<.05) significant difference between values in a row whose letters differ.(α=.72)Money (sufficiency for food)0.81Fast-food cost (cost effect on purchase decision)0.54Coupons (foods bought to save money)0.53ConvenienceConvenience (minimal or no preparation)0.723.15±0.50v(P<.05) significant difference between values down the column whose letters differ.3.38x(P<.05) significant difference between values in a row whose letters differ.3.08y(P<.05) significant difference between values in a row whose letters differ.2.84z(P<.05) significant difference between values in a row whose letters differ.2.99y(P<.05) significant difference between values in a row whose letters differ.(α=.58)Availability (foods on hand—cabinet/refrigerator)0.65Microwavable (preference for cooking method)0.57Cooking (food preparation ability in the kitchen)0.54BeliefsCulture (heritage or family food traditions)0.701.90±0.74r(P<.05) significant difference between values down the column whose letters differ.2.11x(P<.05) significant difference between values in a row whose letters differ.1.30y(P<.05) significant difference between values in a row whose letters differ.2.03x(P<.05) significant difference between values in a row whose letters differ.1.45y(P<.05) significant difference between values in a row whose letters differ.(α=.42)Chemicals (pesticides or additives in food)0.64Time sufficiencySchedule (busyness of lifestyle)0.783.21±0.68v(P<.05) significant difference between values down the column whose letters differ.3.48x(P<.05) significant difference between values in a row whose letters differ.2.17z(P<.05) significant difference between values in a row whose letters differ.3.10y(P<.05) significant difference between values in a row whose letters differ.3.19y(P<.05) significant difference between values in a row whose letters differ.(α=.57)Time (amount of time sufficient to eat)0.74Preference/Taste (preferences for foods in general)0.653.50±0.45w(P<.05) significant difference between values down the column whose letters differ.3.64x(P<.05) significant difference between values in a row whose letters differ.3.57x(P<.05) significant difference between values in a row whose letters differ.y(P<.05) significant difference between values in a row whose letters differ.3.34y(P<.05) significant difference between values in a row whose letters differ.3.30z(P<.05) significant difference between values in a row whose letters differ.internal cuesCraving (appetite for a specific food)0.59(α=.42)Hunger (physical feeling vs appetite)0.56External cuesAdvertisements (TV, billboards, magazines)0.552.31±0.68s(P<.05) significant difference between values down the column whose letters differ.2.71x(P<.05) significant difference between values in a row whose letters differ.1.87y(P<.05) significant difference between values in a row whose letters differ.1.87y(P<.05) significant difference between values in a row whose letters differ.2.09y(P<.05) significant difference between values in a row whose letters differ.(α=.38)Social (foods others are eating)0.54ValueQuantity (amount per serving size)0.732.89±0.67u(P<.05) significant difference between values down the column whose letters differ3.16x(P<.05) significant difference between values in a row whose letters differ.3.02x(P<.05) significant difference between values in a row whose letters differ.y(P<.05) significant difference between values in a row whose letters differ.2.88y(P<.05) significant difference between values in a row whose letters differ.2.05z(P<.05) significant difference between values in a row whose letters differ.(α=.56)Quality (perceived value of a food)0.67a Each factor is listed with its Cronbach α, a measure of factor reliability.b Factor loading is the contributing questions' correlation with the factor.c Mean±standard deviation is given for each factor for the whole sample. Factor scores range from 1 to 4, with a higher score indicating a stronger influence on what students chose to eat.r (P<.05) significant difference between values down the column whose letters differ.s (P<.05) significant difference between values down the column whose letters differ.t (P<.05) significant difference between values down the column whose letters differ.u (P<.05) significant difference between values down the column whose letters differv (P<.05) significant difference between values down the column whose letters differ.w (P<.05) significant difference between values down the column whose letters differ.x (P<.05) significant difference between values in a row whose letters differ.y (P<.05) significant difference between values in a row whose letters differ.z (P<.05) significant difference between values in a row whose letters differ. Open table in a new tab Dietary intake data were collected using a version of the 100-item National Cancer Institute (NCI) food frequency questionnaire ((12)Block G. Coyle L.M. Hartman A.M. Scoppa S.M. HHHQ-DIETSYS Food Frequency Questionnaire. National Cancer Institute, Bethesda, Md1996Google Scholar) that could be scored by electronic scanner. The questionnaire was pilot tested with nutrition science students and staff members, and changes were made to improve its wording. The food frequency data were examined for total energy, percent of energy from fat, vitamin A, vitamin C, fiber, calcium, iron, and folate using the NCI Data Analysis System (versions 3.7, 1995, NCI, Bethesda, Md).The SPSSx statistical software package (version 3, 1988, SPSS Inc, Chicago, Ill) was used to execute a principle-components factor analysis with a varimax rotation on the 30 dietary influence questions. Questions with factor-loading scores greater than .50 were retained (Table 1). Reliability was assessed by determining the Cronbach α for each factor. Cluster analysis was applied to sort the sample into 3 to 8 groups by the similarity of their factors. The analysis sequentially subdivided the data into smaller, more homogeneous subclusters. Analysis of variance, the Tukey test of significance, and χ2 analysis were applied as appropriate.Results and DiscussionApproximately 600 packets were distributed to student subjects; of the 374 surveys returned (62% response rate), 325 were usable. Students enrolled in the basic nutrition classes made up 39.4% of the final sample. Because no significant (P≤.05) differences were found between the nutrition students' and other students' dietary intakes, they were combined for this analysis.More women (67.4%) than men participated in this study, and the mean±standard deviation age of the subjects was 20.48±4.42 years. Student participants lived in the dormitories (39.1%), apartments (24.6%), and with their parents (16.0%). More than 48% of the participants were in their first year of college. Equal numbers of sophomores (16.9%) and juniors (16.3%) participated, with a smaller representation of seniors (14.2%). Prevalent academic majors were undecided (20%), agriculture (16.0%), premedicine/nursing (15.7%), and business (8.0%).Eight factors emerged from the principle components analysis, accounting for 57% of the variance (Table 1). On average, students were most influenced by their hunger or taste preferences (preferences/internal cues), second by the factors time sufficiency and convenience, and third by the factors value and budget (Table 1). A comparable factor analysis for an adult English population ((13)Steptoe A. Pollard T.M. Wardle J. Development of a measure of the motives underlying the selection of food the Food Choice Questionnaire.Appetite. 1995; 25: 267-284Google Scholar) had many similarities with, yet differed slightly from, these results.Students were divided into 4 groups on the basis of cluster analysis (Table 2). Group 1, Cues, was strongly influenced by a variety of factors, including: internal cues (hunger and taste), external cues (friends and media), convenience, time, and budget. Group 2, Budget, was highly influenced by the factors internal cues and budget and least influenced by the factors health and weight. Group 3, Health, was most influenced by the factors health and weight and least by the factors budget or convenience. Group 4, No Cues, was influenced weakly by all factors with a notable lack of concern for budget and health.Table 2Dietary intake differences between cluster groups by sexaUnless otherwise indicated, values are given as mean±standard deviation.MenWomenGroup 1, cues (n=34; 31.8%)Group 2, Budget (n-24; 22.4%)Group 3, Health (n=25; 23.4%)Group 4, No cues (n=24; 22.4%)Group 1, cues (n=121; 55.5%)Group 2, Budget (n=6; 2.7%)Group 3, Health (n=61; 28.0%)Group 4, No cues (n=30; 13.8%)Energy (kcal)2,587±1,1352,497±1,0002,098±7782,477±1,0061,729±653xP<.05 between values in a row whose letters differ.1,569±909yP<.05 between values in a row whose letters differ.1,445±481zP<.05 between values in a row whose letters differ.1,416±474zP<.05 between values in a row whose letters differ.Subjects who consume ≤RDA for energy (%)bRecommended Dietary Allowance (RDA) of energy is ≤2,900kcal/day for men; for women, the RDA is ≤2,200kcal/day (19).64.775.088.062.579.383.390.270% kcal from fat34.0±5.3xP<.05 between values in a row whose letters differ.34.4±5.9xP<.05 between values in a row whose letters differ.31.5±6.2yP<.05 between values in a row whose letters differ.36.2±5.0xP<.05 between values in a row whose letters differ.33.6±7.3yP<.05 between values in a row whose letters differ.35.2±5.8xP<.05 between values in a row whose letters differ.27.2±10.5zP<.05 between values in a row whose letters differ.34.8±7.6yP<.05 between values in a row whose letters differ.Subjects who consume ≤30% energy from fat (%)23.520.836.012.533.116.759.026.7Vitamin A (RE)cRE=retinol equivalents.1,033±480878±4071,052±5361,008±484893±437xP<.05 between values in a row whose letters differ.478±231yP<.05 between values in a row whose letters differ.870±427xP<.05 between values in a row whose letters differ.633±284xP<.05 between values in a row whose letters differ.Subjects who consume ≤67% RDA for vitamin A (%)32.433.332.016.723.166.719.740.0Vitamin C (mg)228±188190±185201±140266±232127±81xP<.05 between values in a row whose letters differ.yP<.05 between values in a row whose letters differ.74±27y155±102xP<.05 between values in a row whose letters differ.87±83yP<.05 between values in a row whose letters differ.Subjects who consume ≤67% RDA for vitamin C (%)00009.103.320.0Fiber (g)12.5±4.512.2±5.612.9±6.614.3±5.510.8±4.9xP<.05 between values in a row whose letters differ.9.2±2.5xP<.05 between values in a row whose letters differ.yP<.05 between values in a row whose letters differ.11.1±5.5xP<.05 between values in a row whose letters differ.7.0±2.6yP<.05 between values in a row whose letters differ.Subjects who consume ≤67% DRV for fiber (%)dDRV=Dietary Reference Value (19).82.470.180.066.790.110090.2100Iron (mg)15.7±6.914.5±5.315.6±9.515.9±5.411.7±4.7xP<.05 between values in a row whose letters differ.10.2±3.9xP<.05 between values in a row whose letters differ.11.2±6.4xP<.05 between values in a row whose letters differ.yP<.05 between values in a row whose letters differ.8.5±3.2yP<.05 between values in a row whose letters differ.Subjects who consume ≤67% RDA for iron (%)2.904.0043.083.347.580.0Calcium (mg)1,158±7201,061±6101,114±6071,204±670958±628xP<.05 between values in a row whose letters differ.453±203yP<.05 between values in a row whose letters differ.958±553xP<.05 between values in a row whose letters differ.686±436yP<.05 between values in a row whose letters differ.Subjects who consume ≤67% RDA for calcium (%)41.241.740.033.350.410047.573.3Folate (μg)393±181374±192424±357412±180292±149xP<.05 between values in a row whose letters differ.211±77xP<.05 between values in a row whose letters differ.yP<.05 between values in a row whose letters differ.331±234xP<.05 between values in a row whose letters differ.191±76yP<.05 between values in a row whose letters differ.Subjects who consume ≤67% RDA for folate (%)eThe RDA for folate for women is 400μg (19). The nonparenthetical value is based on the 1989 RDAs (20).2.908.004.1 (49.6)0 (83.3)8.2 (84.1)16.7 (83.8)No. of breakfast meals eaten/wk4.0±2.13.3±2.34.1±2.43.5±2.24.4±2.23.0±2.85.0±2.24.2±2.5No. meals eaten out/wk3.6±2.33.5±1.43.1±2.13.5±2.84.0±3.0xP<.05 between values in a row whose letters differ.3.0±2.12.7±2.03.3±2.0a Unless otherwise indicated, values are given as mean±standard deviation.b Recommended Dietary Allowance (RDA) of energy is ≤2,900kcal/day for men; for women, the RDA is ≤2,200kcal/day (19)Food and Drug Administration. Food labeling: Reference Daily Intakes and Daily Reference Values. 55 Federal Register 29476-29486 (1991).Google Scholar.c RE=retinol equivalents.d DRV=Dietary Reference Value (19)Food and Drug Administration. Food labeling: Reference Daily Intakes and Daily Reference Values. 55 Federal Register 29476-29486 (1991).Google Scholar.e The RDA for folate for women is 400μg (19)Food and Drug Administration. Food labeling: Reference Daily Intakes and Daily Reference Values. 55 Federal Register 29476-29486 (1991).Google Scholar. The nonparenthetical value is based on the 1989 RDAs (20)Food and Nutrition Board.Recommended Dietary Allowances. 10th ed. National Academy Press, Washington, DC1989Google Scholar.x P<.05 between values in a row whose letters differ.y P<.05 between values in a row whose letters differ.z P<.05 between values in a row whose letters differ. Open table in a new tab Men were equally distributed among the 4 cluster groups, whereas significantly more women (P<.05) clustered into group 1, Cues, and fewer into group 2, Budget. Comparing the dietary intake variables, the men differed from each other significantly (P<.05) only in the percentage of energy from fat in their diet, with the most health-conscious group, group 3, Health, consuming the lowest percentage. Numerous differences appeared in the womens' dietary intake according to their cluster group. Group 1, Cues, had a significantly (P<.05) higher intake of energy coupled with a significantly (P<.05) higher mean intake of the indicator nutrients (vitamin A, vitamin C, fiber, iron, calcium, and folate). Group 4, No Cues, had a lower mean energy and indicator nutrient intake, with a higher percentage of energy from fat. The most health-conscious group, group 3, Health, had lower intakes of energy and percentage of fat concurrent with a significantly (P<.05) higher intake of indicator nutrients. Those least concerned about their health, group 2, Budget, had a moderate energy intake, a high percentage of energy from fat, and a significantly (P<.05) lower mean indicator nutrient intake.ApplicationsStudents' dietary intakes differ depending on the factors influencing their diet. Only 26% of subjects were motivated by health and weight and exhibited dietary intakes consistent with their beliefs. Conversely, the 26% of subjects least motivated by health (groups 2 and 4), had high fat intakes coupled with low nutrient intakes, putting them at greater risk for chronic disease. Because nutrition and health are not a concern for this group, it is likely that typical action-oriented messages used in nutrition education would not motivate them and could be detrimental. These subjects may be in a state of precontemplation regarding their dietary habits, indicating a resistance to change. Similar clients might best be served through a consciousness-raising technique suggested for those in the precontemplation stage of change ((14)Prochaska J.O. DiClemente C.C. Norcross J.C. In search of how people change.Am Psychologist. 1992; 47: 1102-1114Google Scholar, (15)Glanz K. Patterson R.E. Kristal A.R. DiClemente C.C. Heimendinger J. Linnan L. McLerran D.F. Stages of change in adopting healthy diets fat and fiber, and correlates of nutrient intake.Health Educ Q. 1994; 21: 499-519Google Scholar, (16)Greene G.W. Rossi S.R. Reed G.R. Willey C. Prochaska J.O. Stages of change for reducing dietary fat to 30% of energy or less.J Am Diet Assoc. 1994; 94: 1105-1110Google Scholar, (17)Smith K.J. Subich L.M. Kalodner C. The transtheoretical model's stages and processes of change and their relation to premature termination.J Counseling Psychol. 1995; 42: 34-39Google Scholar).The remaining 48% of subjects require a more creative nutrition intervention approach. On average these students were most influenced by what tastes good, is convenient, and fits within their social life. They had sufficient nutrient intakes, but consumed more energy and fat than the more health conscious group. Effective messages for these students should focus on some combination of budget, taste, convenience, and social appeal—but not on nutrition!Rather than taking a direct approach to dietary changes with educational messages that reference specific foods, nutrients, or nutrition/health principles comfortable for dietitians, a social marketing approach ((18)Lefebvre R.C. Lurie D. Goodman L.S. Weinberg L. Loughrey K. Social marketing and nutrition education inappropriate or misunderstood.J Nutr Educ. 1995; 27: 146-150Google Scholar) is necessary. Such indirect and personally appealing messages and environmental strategies may work for this majority of students who are not interested in health or weight. A few examples of applied social marketing include:■ Change the basic food supply.■ Through foodservice avenues, provide foods and entrees that are traditional and appealing to this age group, but that are more nutrient dense, without advertising them as nutritious or healthful.■ Introduce students to new foods by having a chef cook on site and provide samples with recipes of different, cheap, and easy-to-prepare foods.■ Have contests between groups of students (eg, sorority and fraternity houses and residence hall floors) using certain foods to prepare a meal or dish.■ Provide pamphlets with examples of a wide variety of cheap and portable snacks.With all of these examples, the less frequently nutrition or health is mentioned, the more likely it is that the students' attention will be captured. Health-conscious students naturally choose to eat more healthful, nutrient-dense foods; they do not need nutrition education. To be effective, new approaches to improving nutrition must first be fun and put the nutrition message second to capture the attention of these very typical, but harder to reach, students and clients. Students typically have poor dietary habits ((1)Hertzler A.A. Frary R.B. Food behavior of college students.Adolescence. 1989; 24: 349-356Google Scholar, (2)Hoffman C.J. Dietary intake of calcium, iron, folacin, alcohol, and fat for college students in central Michigan.J Am Diet Assoc. 1989; 89: 836-838Google Scholar, (3)Horwarth C.C. Dietary intakes and nutritional status among university undergraduates.Nutr Res. 1991; 11: 395-404Google Scholar, (4)Huang Y. Song W.O. Schemmel R.A. Hoerr S.M. What do college students eat? Food selection and meal pattern.Nutr Res. 1994; 14: 1143-1153Google Scholar, (5)Marrale JC, Shipman JH, Rhodes ML. What some college students eat. Nutr Today. Jan-Feb 1986:16–21.Google Scholar, (6)Skinner J.D. Changes in students' dietary behavior during a college nutrition course.J Nutr Educ. 1991; 23: 72-75Google Scholar, (7)Schuette L.K. Song W.O. Hoerr S.L. Quantitative use of the Food Guide Pyramid to evaluate dietary intake of college students.J Am Diet Assoc. 1996; 96: 453-457Google Scholar, (8)Horacek T.M. The effect of nutrition education and the differences in dietary intake and factors influencing intake according to personality preferences for a sample of college students. University of Nebraska, Lincoln1996Google Scholar). Although many researchers have determined the factors that influence intakes, not all students choose foods for the same reasons, and the set of factors that influence 1 group may be different from that which influences another ((8)Horacek T.M. The effect of nutrition education and the differences in dietary intake and factors influencing intake according to personality preferences for a sample of college students. University of Nebraska, Lincoln1996Google Scholar, (9)Betts N.M. Amos R.J. Georgiou C. Hoerr S.L. Ivanturi R. Keim K.S. Tinsley A. Voichick J. What young adults say about factors affecting their food intake.Ecol Food Nutr. 1995; 34: 59-64Google Scholar, (10)Betts N.M. Amos R.J. Keim K. Peters P. Stewart B. Ways young adults view food.J Nutr Educ. 1997; 29: 73-79Google Scholar, (11)Koszewski W.M. Kuo M. Factors that influence the food consumption behavior and nutritional adequacy of college women.J Am Diet Assoc. 1996; 96: 1286-1288Google Scholar). The objectives of our study were to determine how a sample of college students clustered according to the factors influencing their dietary intake, and to identify the differences in dietary intake that existed between the clustered groups. MethodsTo ensure diversity in the study sample, approximately 400 students from 3 large, introductory nutrition classes and approximately 600 students from 26 various small classes were invited to participate. A 20-minute recruitment presentation was made to each class. Students volunteered to complete packets and return them via campus mail. The research was approved by the Institutional Review Board for the Protection of Human Subjects at the University of Nebraska, Lincoln.The survey of factors influencing diet was based on the findings of Betts and colleagues ((9)Betts N.M. Amos R.J. Georgiou C. Hoerr S.L. Ivanturi R. Keim K.S. Tinsley A. Voichick J. What young adults say about factors affecting their food intake.Ecol Food Nutr. 1995; 34: 59-64Google Scholar). Two versions of the survey were developed and pretested with 50 students. The selected version was revised and included questions on influencing factors, basic demographics, and meal frequencies. Each influencing factor (see Table 1 for the questions) was rated on a 4-point scale, ranging from very likely (high score) to very unlikely (low score) to influence what the student ate.Table 1Dietary influences: factor analysis, sample factor averages, and cluster group factor averagesFactoraEach factor is listed with its Cronbach α, a measure of factor reliability.Contributing questionsFactor loadingbFactor loading is the contributing questions' correlation with the factor.Mean±SDcMean±standard deviation is given for each factor for the whole sample. Factor scores range from 1 to 4, with a higher score indicating a stronger influence on what students chose to eat.Cluster groups1, Cues (n=155; 47.7%)2. Budget (n=30; 9.2%)3, Health (n=86; 26.5%)4, No cues (n=54; 16.6%)Weight/healthFat (amount of fat in food)0.862.72±0.78t(P<.05) significant difference between values down the column whose letters differ.2.94x(P<.05) significant difference between values in a row whose letters differ.1.58z(P<.05) significant difference between values in a row whose letters differ.3.13x(P<.05) significant difference between values in a row whose letters differ.2.06y(P<.05) significant difference between values in a row whose letters differ.(α=.87)Calories (number of calories in food)0.83Weight (gain, lose, or maintain)0.83Health (concern for present and future status)0.72Appearance (how you look)0.65Nutrients (amount of nutrients in foods)0.60BudgetPrice (expense of a food)0.832.83±0.64u(P<.05) significant difference between values down the column whose letters differ3.19x(P<.05) significant difference between values in a row whose letters differ.3.03x(P<.05) significant difference between values in a row whose letters differ.2.38y(P<.05) significant difference between values in a row whose letters differ.2.40y(P<.05) significant difference between values in a row whose letters differ.(α=.72)Money (sufficiency for food)0.81Fast-food cost (cost effect on purchase decision)0.54Coupons (foods bought to save money)0.53ConvenienceConvenience (minimal or no preparation)0.723.15±0.50v(P<.05) significant difference between values down the column whose letters differ.3.38x(P<.05) significant difference between values in a row whose letters differ.3.08y(P<.05) significant difference between values in a row whose letters differ.2.84z(P<.05) significant difference between values in a row whose letters differ.2.99y(P<.05) significant difference between values in a row whose letters differ.(α=.58)Availability (foods on hand—cabinet/refrigerator)0.65Microwavable (preference for cooking method)0.57Cooking (food preparation ability in the kitchen)0.54BeliefsCulture (heritage or family food tradi
Referência(s)