Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S.
Abstract
:1. Introduction
Study Objectives
2. Materials and Methods
2.1. Participants
2.2. Measures
2.2.1. Food Choice Priorities (FCP)
2.2.2. Dietary Intake
2.2.3. Anthropometrics
2.2.4. Sociodemographic Variables
2.3. Analysis
3. Results
3.1. Primary Aim: FCP and Dietary Intake at the End of the Freshmen Year
3.2. Sociodemographic Variables and Dietary Intake
3.3. Secondary Aim 1: Changes in FCPS Scores and Dietary Intake
3.4. Secondary Aim 2: FCP and Participant Characteristics at Baseline and at Follow-up
3.4.1. Sex
3.4.2. Race
3.4.3. BMI
4. Discussion
4.1. FCPS as Predictor of Healthy Dietary Intake
4.2. FCPS as Predictor of Less Healthy Dietary Intake
4.3. Limitations
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Grotto, D.; Zied, A.E. The standard American diet and its relationship to the health status of Americans. Nutr. Clin. Pract. 2010, 25, 603–612. [Google Scholar] [CrossRef] [PubMed]
- Banfield, E.C.; Liu, Y.; Davis, J.S.; Chang, S.; Frazier-Wood, A.C. Poor adherence to US dietary guidelines for children and adolescents in the national health and nutrition examination survey population. J. Acad. Nutr. Diet. 2016, 116, 21–27. [Google Scholar] [CrossRef] [PubMed]
- Strong, K.A.; Parks, S.L.; Anderson, E.; Winett, R.; Davy, B.M. Weight gain prevention: Identifying theory-based targets for health behavior change in young adults. J. Am. Diet. Assoc. 2008, 108, 1708–1715. [Google Scholar] [CrossRef] [PubMed]
- Rossi, R.E.; Pericleous, M.; Mandair, D.; Whyand, T.; Caplin, M.E. The role of dietary factors in prevention and progression of breast cancer. Anticancer Res. 2014, 34, 6861–6875. [Google Scholar] [PubMed]
- Mozaffarian, D. Dietary and policy priorities for cardiovascular disease, diabetes, and obesity: A comprehensive review. Circulation 2016, 133, 187–225. [Google Scholar] [CrossRef] [PubMed]
- Wiseman, M. The second world cancer research fund/American institute for cancer research expert report. Food, Nutrition, Physical Activity, and the Prevention of Cancer: A global perspective. Proc. Nutr. Soc. 2008, 67, 253–256. [Google Scholar] [CrossRef] [PubMed]
- Micha, R. Association between dietary factors and mortality from heart disease, stroke, and Type 2 diabetes in the United States. JAMA 2017, 317, 912–924. [Google Scholar] [CrossRef] [PubMed]
- U.S. Department of Health and Human Services and U.S. Department of Agriculture. Dietary Guidelines for Americans 2015–2020, 8th Ed. 2015. Available online: https://health.gov/dietaryguidelines/2015/guidelines/ (accessed on 12 September 2018).
- Bleich, S.N.; Vercammen, K.A.; Koma, J.W.; Li, Z. Trends in beverage consumption among children and Adults, 2003–2014. Obesity 2017. [Google Scholar] [CrossRef]
- Small, M.; Bailey-Davis, L.; Morgan, N.; Maggs, J. Changes in eating and physical activity behaviors across seven semesters of college: Living on or off campus matters. Health Educ. Behav. 2013, 40, 435–441. [Google Scholar] [CrossRef] [PubMed]
- American College Health Association-National College Health Assessment Spring 2008 Reference Group Data Report (Abridged): The American College Health Association. J. Am. Coll. Health 2009, 57, 477–488. [CrossRef] [PubMed]
- Furst, T.; Connors, M.; Bisogni, C.A.; Sobal, J.; Winter Falk, L. Food Choice: A Conceptual Model of the Process. Appetite 1996, 26, 247–266. [Google Scholar] [CrossRef] [PubMed]
- Glanz, K.; Basil, M.; Maibach, E.; Goldberg, J.; Snyder, D. Why Americans eat what they do: Taste, nutrition, cost, convenience, and weight control concerns as influences on food consumption. J. Am. Diet. Assoc. 1998. [Google Scholar] [CrossRef]
- Connors, M.; Bisogni, C.A.; Sobal, J.; Devine, C.M. Managing values in personal food systems. Appetite 2001, 36, 189–200. [Google Scholar] [CrossRef] [PubMed]
- Vilaro, M.J.; Barnett, T.E.; Mathews, A.; Pomeranz, J.; Curbow, B. Income differences in social control of eating behaviors and food choice priorities among southern rural women in the US: A qualitative study. Appetite 2016, 107, 604–612. [Google Scholar] [CrossRef] [PubMed]
- Vilaro, M.J. Development and preliminary testing of the Food Choice Priorities Survey (FCPS): Assessing the importance of multiple factors on college students’ food choices. Eval. Health Prof. 2017, 40. [Google Scholar] [CrossRef] [PubMed]
- Lloyd-Richardson, E.E.; Bailey, S.; Fava, J.L.; Wing, R. A prospective study of weight gain during the college freshman and sophomore years. Prev. Med. 2009, 48, 256–261. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Economos, C. College freshman stress and weight change: Differences by gender. Am. J. Health Behav. 2008, 32, 16–25. [Google Scholar] [CrossRef] [PubMed]
- Eaton, D.K.; Kann, L.; Kinchen, S.; Shanklin, S.; Flint, K.H.; Hawkins, J.; Harris, W.A.; Lowry, R.; McManus, T.; Chyen, D.; et al. Youth risk behavior surveillance—United States, 2011. MMWR Surveill. Summ. 2012, 61, 1–162. [Google Scholar] [PubMed]
- Thompson, F.E. Fruit and vegetable assessment: Performance of 2 new short instruments and a food frequency questionnaire. J. Am. Diet. Assoc. 2002, 102, 1764–1772. [Google Scholar] [CrossRef]
- Boyce, W.; Torsheim, T.; Currie, C.; Zambon, A. The family affluence scale as a measure of national wealth: Validation of an adolescent self-report measure. Soc. Indic. Res. 2006. [Google Scholar] [CrossRef]
- Thompson, F.E.; Midthune, D.; Kahle, L.; Dodd, K.W. Development and evaluation of the national cancer institute’s dietary screener questionnaire scoring algorithms. J. Nutr. 2017, 147, 1226–1233. [Google Scholar] [CrossRef] [PubMed]
- Lee-Kwan, S.H.; Moore, L.V.; Blanck, H.M.; Harris, D.M.; Galuska, D. Disparities in state-specific adult fruit and vegetable consumption—United States, 2015. MMWR Morb. Mortal. Wkly. Rep. 2017, 66, 1241–1247. [Google Scholar] [CrossRef] [PubMed]
- Racette, S.B.; Deusinger, S.S.; Strube, M.J.; Highstein, G.R.; Deusinger, R.H. Weight changes, exercise, and dietary patterns during freshman and sophomore years of college. J. Am. Coll. Health 2005, 53, 245–251. [Google Scholar] [CrossRef] [PubMed]
- Yu, Z.M. Fruit and vegetable intake and body adiposity among populations in eastern Canada: The atlantic partnership for tomorrow’s health study. BMJ Open 2018, 8, e018060. [Google Scholar] [CrossRef] [PubMed]
- Jagadeeswari, T.; Harini, N.; Satya Kumar, C.; Tech, M. Identification of outliers by cook’s distance in agriculture datasets. Int. J. Eng. Comput. Sci. 2013, 2, 2319–7242. [Google Scholar]
- Mötteli, S.; Siegrist, M.; Keller, C. Women’s social eating environment and its associations with dietary behavior and weight management. Appetite 2017, 110, 86–93. [Google Scholar] [CrossRef] [PubMed]
- Spence, M. A qualitative study of psychological, social and behavioral barriers to appropriate food portion size control. Int. J. Behav. Nutr. Phys. Act. 2013, 10, 92. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Biswas, D.; Lund, K.D.; Lund, K.; Szocs, C. Ambient Music and Food Choices: Can Music Volume Level Nudge Healthier Choices? In NA—Advances in Consumer Research; Moreau, P., Puntoni, S., Eds.; Association for Consumer Research: Duluth, MN, USA, 2016; Volume 44, pp. 53–58. [Google Scholar]
- Watts, A.W. Multicontextual correlates of adolescent sugar-sweetened beverage intake. Eat. Behav. 2018, 30, 42–48. [Google Scholar] [CrossRef] [PubMed]
- Ellis, J.M.; Galloway, A.T.; Webb, R.M.; Martz, D.M. Measuring adult picky eating: The development of a multidimensional self-report instrument. Psychol. Assess. 2017, 29, 955–966. [Google Scholar] [CrossRef] [PubMed]
- Ellis, J.M.; Galloway, A.T.; Zickgraf, H.F.; Whited, M.C. Picky eating and fruit and vegetable consumption in college students. Eat. Behav. 2018, 30, 5–8. [Google Scholar] [CrossRef] [PubMed]
- Horacek, T.M.; Betts, N.M. Students cluster into 4 groups according to the factors influencing their dietary intake. J. Am. Diet. Assoc. 1998, 98, 1464–1467. [Google Scholar] [CrossRef]
- French, S.A. Pricing effects on food choices. J. Nutr. 2003, 133, 841S–843S. [Google Scholar] [CrossRef] [PubMed]
- Steenhuis, I.H.; Waterlander, W.E.; de Mul, A. Consumer food choices: The role of price and pricing strategies. Public Health Nutr. 2011, 14, 2220–2226. [Google Scholar] [CrossRef] [PubMed]
- Eisend, M. The third-person effect in advertising: A. meta-analysis. J. Advert. 2017, 46, 377–394. [Google Scholar] [CrossRef]
- Boulos, R.; Vikre, E.K.; Oppenheimer, S.; Chang, H.; Kanarek, R.B. ObesiTV: How television is influencing the obesity epidemic. Physiol. Behav. 2012, 107, 146–153. [Google Scholar] [CrossRef] [PubMed]
- Harris, J.L.; Bargh, J.A.; Brownell, K.D. Priming effects of television food advertising on eating behavior. Health Psychol. 2009, 28, 404–413. [Google Scholar] [CrossRef] [PubMed]
- Halford, J.C.G.; Boyland, E.J.; Hughes, G.; Oliveira, L.P.; Dovey, T.M. Beyond-brand effect of television (TV) food advertisements/commercials on caloric intake and food choice of 5–7-year-old children. Appetite 2007, 49, 263–267. [Google Scholar] [CrossRef] [PubMed]
- Park, S.; Blanck, H.M.; Sherry, B.; Brener, N.; O’Toole, T. Factors associated with sugar-sweetened beverage intake among United States high school students. J. Nutr. 2012, 142, 306–312. [Google Scholar] [CrossRef] [PubMed]
- Story, M.; Kaphingst, K.M.; Robinson-O’Brien, R.; Glanz, K. Creating healthy food and eating environments: Policy and environmental approaches. Annu. Rev. Public Health 2008, 29, 253–272. [Google Scholar] [CrossRef] [PubMed]
- Klesges, R.C.; Eck, L.H.; Ray, J.W. Who underreports dietary intake in a dietary recall? Evidence from the second national health and nutrition examination survey. J. Consult. Clin. Psychol. 1995, 63, 438–444. [Google Scholar] [CrossRef] [PubMed]
- Hill, R.J.; Davies, P.S.W. The validity of self-reported energy intake as determined using the doubly labelled water technique. Br. J. Nutr. 2001, 85, 415. [Google Scholar] [CrossRef] [PubMed]
- Macdiarmid, J.; Blundell, J. Assessing dietary intake: Who, what and why of under-reporting. Nutr. Res. Rev. 1998, 11, 231. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Marks, G.C.; Hughes, M.C.; van der Pols, J.C. Relative validity of food intake estimates using a food frequency questionnaire is associated with sex, age, and other personal characteristics. J. Nutr. 2006, 136, 459–465. [Google Scholar] [CrossRef] [PubMed]
(M, SD) | Fall 2015 | Spring 2016 |
---|---|---|
N = 1149 | n = 857 | |
BMI (kg/m2) | 24.4 (4.9) | 24.6 (4.7) |
(n, %) | ||
Female | 745 (64.8) | 585 (68.5) |
Male | 377 (32.8) | 265 (31.0) |
18 years old | 974 (84.6) | 293 (34.7) |
19 years old | 128 (11.1) | 520 (61.5) |
20 years old | 11 (1.0) | 18 (2.1) |
21+ years old | 14 (1.3) | 14 (1.7) |
Non-Hispanic White | 604 (52.5) | 433 (51.3) |
Non-Hispanic Black | 117 (10.2) | 86 (10.2) |
Hispanic/Latino only | 204 (17.8) | 170 (20.1) |
Other or multiracial | 190 (16.5) | 155 (18.4) |
Live on campus | 957 (83.3) | 704 (82.5) |
Live off campus | 133 (11.5) | 117 (13.7) |
Live with parents | 21 (1.8) | 16 (1.9) |
Live in sorority/fraternity | 11 (1.0) | 12 (1.4) |
Other living arrangement | 4 (.3) | 1 (.1) |
Alabama | 81 (7.0) | 57 (6.7) |
Florida | 299 (26.0) | 244 (28.5) |
Maine | 167 (14.5) | 130 (15.2) |
Kansas | 111 (9.7) | 94 (11.0) |
New York | 156 (13.6) | 130 (15.2) |
Tennessee | 171 (14.9) | 88 (10.3) |
South Dakota | 69 (6.0) | 44 (5.1) |
West Virginia | 95 (8.3) | 70 (8.2) |
Currently single | 752 (65.4) | 538 (63.1) |
Currently in a relationship | 348 (30.3) | 301 (35.3) |
Model 1 | Adjusted Model 2 (Age, Race, Sex, BMI) | |||||
---|---|---|---|---|---|---|
B | SE | p | B | SE | p | |
Fruits, vegetables, legumes (CE/day) * | −0.01 | 0.02 | 0.51 | |||
Advertising Environment Scale | −0.02 | 0.16 | 0.20 | 0.10 | 0.16 | 0.00 |
Healthy Aesthetic Scale | 0.09 | 0.16 | 0.00 | −0.05 | 0.02 | 0.04 |
Busy Daily Life and Preferences Scale | −0.05 | 0.02 | 0.02 | −0.04 | 0.01 | 0.00 |
Price | −0.04 | 0.01 | 0.00 | 0.01 | 0.01 | 0.43 |
Stress | −0.01 | 0.01 | 0.52 | −0.02 | 0.01 | 0.11 |
Family | −0.02 | 0.01 | 0.10 | 0.01 | 0.01 | 0.52 |
Peer | 0.02 | 0.01 | 0.23 | 0.00 | 0.01 | 0.87 |
Significant other | 0.00 | 0.01 | 0.83 | 0.16 | 0.03 | 0.00 |
Sex (ref = Female) | NA | 0.00 | 0.02 | 0.92 | ||
Age | NA | |||||
Race (ref = White) | −0.03 | 0.05 | 0.49 | |||
Black | NA | −0.03 | 0.03 | 0.35 | ||
Hispanic | NA | −0.03 | 0.04 | 0.34 | ||
Multiracial | NA | −0.01 | 0.00 | 0.04 | ||
BMI | NA | 0.10 | ||||
Adj. R2 | 0.06 | |||||
Added sugar from sugar sweetened beverages (tsp/day) | 0.18 | 0.05 | 0.00 | |||
Advertising Environment Scale | 0.13 | 0.05 | 0.01 | −0.33 | 0.05 | 0.00 |
Healthy Aesthetic Scale | −0.37 | 0.05 | 0.00 | 0.23 | 0.07 | 0.00 |
Busy Daily Life and Preferences Scale | 0.23 | 0.07 | 0.00 | 0.08 | 0.04 | 0.04 |
Price | 0.06 | 0.04 | 0.10 | −0.01 | 0.04 | 0.72 |
Stress | −0.04 | 0.04 | 0.25 | 0 | 0.04 | 0.90 |
Family | 0.02 | 0.04 | 0.63 | −0.09 | 0.04 | 0.03 |
Peer | −0.09 | 0.04 | 0.02 | 0.11 | 0.04 | 0.00 |
Significant other | 0.13 | 0.04 | 0.00 | |||
Added sugar from sugar sweetened beverages (tsp/day) | 0.57 | |||||
Sex (ref = Female) | NA | 0.05 | 0.09 | 0.00 | ||
Age | NA | 0.05 | 0.33 | |||
Race (ref = White) | 0.09 | |||||
Black | NA | −0.11 | 0.14 | 0.51 | ||
Hispanic | NA | −0.18 | 0.10 | 0.28 | ||
Multiracial | NA | 0.01 | 0.12 | 0.10 | ||
BMI | NA | 0.01 | 0.43 | |||
Adj. R2 | 0.09 | 0.14 | ||||
Added sugar (tsp/day) | 0.04 | |||||
Advertising Environment Scale | 0.02 | 0.02 | 0.22 | −0.14 | 0.02 | 0.03 |
Healthy Aesthetic Scale | −0.16 | 0.02 | 0.00 | 0.08 | 0.02 | 0.00 |
Busy Daily Life and Preferences Scale | 0.07 | 0.03 | 0.00 | 0.04 | 0.03 | 0.00 |
Price | 0.03 | 0.01 | 0.045 | 0.01 | 0.01 | 0.38 |
Stress | 0.00 | 0.01 | 0.87 | 0.01 | 0.01 | 0.30 |
Family | 0.02 | 0.01 | 0.2 | 0.01 | 0.01 | 0.19 |
Peer | −0.02 | 0.02 | 0.28 | −0.02 | 0.02 | 0.01 |
Significant other | 0.04 | 0.01 | 0.00 | 0.04 | 0.01 | 0.00 |
Sex (ref = Female) | NA | 0.26 | 0.03 | 0.37 | ||
Age | NA | 0.02 | 0.02 | |||
Race (ref = White) | 0.21 | |||||
Black | NA | −0.07 | 0.05 | 0.27 | ||
Hispanic | NA | −0.04 | 0.04 | 0.00 | ||
Multiracial | NA | −0.13 | 0.04 | 0.76 | ||
BMI | NA | 0.00 | 0.00 | 0.17 | ||
Adj. R2 | 0.10 | |||||
Fiber (g/day) | ||||||
Advertising Environment Scale | −0.02 | 0.01 | 0.2 | −0.01 | 0.01 | 0.62 |
Healthy Aesthetic Scale | 0.03 | 0.01 | 0.01 | 0.05 | 0.01 | 0.00 |
Busy Daily Life and Preferences Scale | −0.03 | 0.02 | 0.08 | −0.02 | 0.02 | 0.23 |
Price | −0.01 | 0.01 | 0.1 | −0.01 | 0.01 | 0.24 |
Stress | −0.01 | 0.01 | 0.27 | 0.01 | 0.01 | 0.30 |
Family | −0.01 | 0.01 | 0.08 | −0.02 | 0.01 | 0.04 |
Peer | 0.02 | 0.01 | 0.05 | 0.02 | 0.01 | 0.05 |
Significant other | 0.00 | 0.01 | 0.65 | 0.00 | 0.01 | 0.70 |
Sex (ref = Female) | NA | 0.22 | 0.02 | 0.00 | ||
Age | NA | 0 | 0.01 | 0.75 | ||
Race (ref = White) | ||||||
Black | NA | −0.06 | 0.03 | 0.07 | ||
Hispanic | NA | −0.03 | 0.02 | 0.14 | ||
Multiracial | NA | −0.04 | 0.02 | 0.00 | ||
BMI | NA | 0 | 0.00 | 0.08 | ||
Adj. R2 | 0.02 | 0.16 |
Mean (SD) | 2015 | 2016 | t Statistic (df) |
---|---|---|---|
Dietary Intake | |||
Fruit/vegetable/legumes minus French fries (CE/day) | 2.49 (1.12) | 2.26 (0.98) | 5.91 (832) *** |
Added sugar from sugar sweetened beverages (tsp/day) | 7.32 (8.85) | 6.07 (8.04) | 4.32 (833) *** |
Added sugar (tsp/day) | 15.11 (8.39) | 13.72 (7.78) | 5.30 (780) *** |
Fiber (g/day) | 14.73 (5.84) | 13.65 (4.54) | 6.19 (779) *** |
Food Choice Priorities Survey Scales/Items | |||
Price | 3.63 (1.11) | 3.92 (1.09) | −7.70 (846) *** |
Busy Daily Life and Preferences (Scale) | 3.64 (0.64) | 3.71 (0.67) | −2.90 (849) ** |
Healthy Aesthetic (Scale) | 3.33 (0.83) | 3.33 (0.86) | .31 (849) |
Stress | 2.62 (1.23) | 2.80 (1.28) | −4.00 (842) *** |
Peer and social situations | 2.53 (1.20) | 2.55 (1.22) | −0.58 (846) |
Family | 2.62 (1.26) | 2.43 (1.28) | 3.91 (846) *** |
Boyfriend/girlfriend/significant other | 1.80 (1.13) | 1.85 (1.18) | −0.98 (835) |
Advertising Environment (Scale) | 1.65 (0.86) | 1.70 (0.91) | −1.80 (845) |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Vilaro, M.J.; Colby, S.E.; Riggsbee, K.; Zhou, W.; Byrd-Bredbenner, C.; Olfert, M.D.; Barnett, T.E.; Horacek, T.; Sowers, M.; Mathews, A.E. Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S. Nutrients 2018, 10, 1296. https://doi.org/10.3390/nu10091296
Vilaro MJ, Colby SE, Riggsbee K, Zhou W, Byrd-Bredbenner C, Olfert MD, Barnett TE, Horacek T, Sowers M, Mathews AE. Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S. Nutrients. 2018; 10(9):1296. https://doi.org/10.3390/nu10091296
Chicago/Turabian StyleVilaro, Melissa J., Sarah E. Colby, Kristin Riggsbee, Wenjun Zhou, Carol Byrd-Bredbenner, Melissa D. Olfert, Tracey E. Barnett, Tanya Horacek, Morgan Sowers, and Anne E. Mathews. 2018. "Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S." Nutrients 10, no. 9: 1296. https://doi.org/10.3390/nu10091296
APA StyleVilaro, M. J., Colby, S. E., Riggsbee, K., Zhou, W., Byrd-Bredbenner, C., Olfert, M. D., Barnett, T. E., Horacek, T., Sowers, M., & Mathews, A. E. (2018). Food Choice Priorities Change Over Time and Predict Dietary Intake at the End of the First Year of College Among Students in the U.S. Nutrients, 10(9), 1296. https://doi.org/10.3390/nu10091296