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. 2018 Oct 23;10(11):1569.
doi: 10.3390/nu10111569.

Multilevel Structural Equation Modeling of Students' Dietary Intentions/Behaviors, BMI, and the Healthfulness of Convenience Stores

Affiliations

Multilevel Structural Equation Modeling of Students' Dietary Intentions/Behaviors, BMI, and the Healthfulness of Convenience Stores

Tanya Horacek et al. Nutrients. .

Abstract

Background: When dietary behaviors are habitual, intentions are low, and environmental cues, such as the consumer food environment, might guide behavior. How might intentions to eat healthily and ultimately actual dietary behaviors, be influenced by the consumer food environment (including the availability and affordability of healthy foods) in convenience stores? This study will determine pathways between the healthfulness of convenience stores and college students' dietary intentions/behaviors, and body mass index (BMI).

Methods: Through multilevel structural equation modeling, a comparison was made of students' healthful meal intentions (HMI); intake (fruits/vegetables, %kcal/fat, sugar-sweetened beverages (SSBs) and whole-grains); and measured BMI; as well as the healthfulness of convenience stores (fruits/vegetables availability/quality, healthy food availability/affordability). Data was collected on 1401 students and 41 convenience stores across 13 US college campuses.

Results: Controlling for gender, HMI was negatively associated with SSBs (β = -0.859) and %kcal/fat (β = -1.057) and positively with whole-grains (β = 0.186) and fruits/vegetables intake (β = 0.267); %Kcal/fat was positively (β = 0.098) and fruits/vegetables intake (β = -0.055) negatively associated with BMI. Campus level, fruits/vegetables availability were positively associated to HMI (β = 0.214, β = 0.129) and directly/negatively to BMI (β = -2.657, β = -1.124).

Conclusions: HMI modifies dietary behaviors, with energy from fat and fruit/vegetable intake the most predictive of weight. Availability of fruit/vegetables in convenience stores make it easier for young adults to eat well.

Keywords: college environment; consumer nutrition food environment; fruit/vegetable intake; percentage k-calories from fat; weight; young adults.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Multilevel structural equation modeling: Level 1—individual intentions/behaviors. * p < 0.05; ** p < 0.001 Definitions: Healthy meal intentions: self-instruction to plan for healthful mealtime behavior (i.e., planning, choosing, and assembling healthful meals); Energy from Fat: % Kcal/Fat/day; SSB Kcal: Sugar-sweetened beverages intake/day; Whole Grain: Whole grain intake/day, Fruit and vegetable intake—intake per day as determined by NCI food frequency; BMI: body mass index, calculated from assessed weight and height.
Figure 2
Figure 2
Multilevel structural equation modeling: Level 2—Campuses healthfulness of store environment and BMI. * p < 0.05; Definitions: Availability of Healthy Food: The total of 13 food categories from NEMS-S, Quality of Fruits and Vegetables: for fresh produce; Affordability: healthy food affordability; Fruits: Availability of fruits (fresh, frozen and canned); Vegetables: Availability of vegetables (fresh, frozen and canned); Healthy meal intentions: self-instruction to plan for healthful mealtime behavior (i.e., planning, choosing, and assembling healthful meals); Energy from fat: % Kcal/Fat/day; SSB Kcal: Sugar-sweetened beverages intake/day; Whole Grains: Whole grain intake/day, Fruit and vegetable intake: intake per day as determined by NCI food frequency; BMI: Body Mass Index—calculated from assessed weight and height.

References

    1. Cerin E., Frank L.D., Sallis J.F., Saelens B.E., Conway T.L., Chapman J.E., Glanz K. From neighborhood design and food options to residents’ weight status. Appetite. 2011;56:693–703. doi: 10.1016/j.appet.2011.02.006. - DOI - PubMed
    1. Franco M., Diez-Roux A.V., Nettleton J.A., Lazo M., Brancati F., Caballero B., Glass T., Moore L.V. Availability of healthy foods and dietary patterns: The Multi-Ethnic Study of Atherosclerosis. Am. J. Clin. Nutr. 2009;89:897–904. doi: 10.3945/ajcn.2008.26434. - DOI - PMC - PubMed
    1. Gustafson A., Hankins S., Jilcott S. Measures of the consumer food store environment: a systematic review of the evidence 2000–2011. J. Community Health. 2011;37:897–911. doi: 10.1007/s10900-011-9524-x. - DOI - PMC - PubMed
    1. Izumi B.T., Zenk S.N., Schulz A.J., Mentz G.B., Wilson C. Associations between neighborhood availability and individual consumption of dark-green and orange vegetables among ethnically diverse adults in detroit. J. Am. Diet. Assoc. 2011;111:274–279. doi: 10.1016/j.jada.2010.10.044. - DOI - PMC - PubMed
    1. Hermstad A.K., Swan D.W., Kegler M.C., Barnette J.K., Glanz K. Individual and environmental correlates of dietary fat intake in rural communities: a structural equation model analysis. Soc. Sci. Medicine. 2010;71:93–101. doi: 10.1016/j.socscimed.2010.03.028. - DOI - PubMed

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