Journal List > J Nutr Health > v.52(5) > 1136455

Choi and Kim: Mobile application-based dietary sugar intake reduction intervention study according to the stages of behavior change in female college students

Abstract

Purpose

This study examined the effects of a mobile app-based program to reduce the dietary sugar intake according to the stages of the behavioral change in dietary sugar reduction in female college students.

Methods

The program used in this study can monitor the dietary sugar intake after recording the dietary intake and provide education message for the reduction of dietary sugar intake. In an eight-week pre-post intervention study, 68 female college students were instructed to record all the food they consumed daily and received weekly education information. At pre-post intervention, the subjects were asked to answer the questionnaire about sugar-related nutrition knowledge, sugar-intake behavior, and sugar-intake frequency. For statistical analysis, ANOVA and a paired t-test were used for comparative analysis according Precontemplation (PC), Contemplation ·Preparation (C ·P), and A ·M (Action ·Maintenance) stage.

Results

Significant differences were observed in the frequency of snacking, experience of nutrition education, and preference for sweetness according to the stages of behavior change in dietary sugar reduction. After finishing an intervention, the sugar-related nutrition knowledge score was increased significantly in the stages of Precontemplation (PC) and Contemplation ·Preparation (C ·P). The score of the sugar intake behavior increased significantly in all stages. The intake frequency of chocolate, muffins or cakes, and drinking yogurt decreased significantly in the PC stage and the intake frequency of biscuits, carbonated beverages, and fruit juice decreased significantly in the C ·P stage. Subjects in the PC and C ·P stages had an undesirable propensity in nutrition knowledge, sugar-intake behavior, and sugar-intake frequency compared to the A ·M stage, but this intervention improved significantly their nutrition knowledge, sugar-intake behavior, and sugar-intake frequency.

Conclusion

This program can be an effective educational tool in the stages of PC and C ·P, and is expected to further increase the usability and sustainability of mobile application if supplemented appropriately to a health platform program.

Figures and Tables

Fig. 1

Application screen (A) Select the kind of meal (B) Record diet after the meal (C) Real-time feedback on the intake of total energy and total sugar.

jnh-52-488-g001
Fig. 2

Examples of card news: ‘Description of nutritive components and how to read it’.

jnh-52-488-g002
Table 1

General characteristics of subjects according to the stages of dietary sugar reduction behavior

jnh-52-488-i001

n (%)

1) PC, Precontemplation; C · P, Contemplation · Preparation; A · M, Action · Maintenance

2) Significantly different by t-test (*p < 0.05, **p < 0.01, ***p < 0.001) between pre and post intervention

Table 2

Sugar-related nutrition knowledge scores of subjects according to stage of dietary sugar reduction behavior between pre and post intervention

jnh-52-488-i002

Each value is mean ± standard deviation.

1) Pre, pre intervention of reducing dietary sugar intake; Post, post intervention of reducing dietary sugar intake

2) PC, Precontemplation; C · P, Contemplation · Preparation; A · M, Action · Maintenance

3) Means with different superscript in row are significantly different among pre-intervention by ANOVA with Scheffe's multiple range test (p < 0.05).

4) Significantly different by t-test (*p < 0.05, **p < 0.01, ***p < 0.001) between pre and post intervention by stage of change for reducing dietary sugar intake.

Table 3

Sugar intake behavior scores of subjects according to stage of dietary sugar reduction behavior between pre and post intervention

jnh-52-488-i003

Each value is mean ± standard deviation.

By using likert 5-point scale: from "totally agree" (1 point) to "totally disagree" (5 point).

The higher score means an sugar intake behavior that eats less sugar.

1) Pre, pre intervention of reducing dietary sugar intake; Post, post intervention of reducing dietary sugar intake

2) PC, Precontemplation; C · P, Contemplation · Preparation; A · M, Action · Maintenance

3) Means with different superscript in row are significantly different among pre-intervention by ANOVA with Scheffe's multiple range test.

Table 4

Sugar intake frequency of subjects according to stage of dietary sugar reduction behavior between pre and post intervention

jnh-52-488-i004

Each value is mean ± standard deviation.

1) Pre, pre intervention of reducing dietary sugar intake; Post, post intervention of reducing dietary sugar intake

2) PC, Precontemplation; C · P, Contemplation · Preparation; A · M, Action · Maintenance

3) Means with different superscript in row are significantly different among pre-intervention by ANOVA with Scheffe's multiple range test (p<0.05).

4) Significantly different by t-test (*p < 0.05, **p < 0.01, ***p < 0.001) between pre and post intervention by stage of change for reducing dietary sugar intake

Notes

This work was partly supported by grants from Co. Wehuddling Korea.

References

1. Murphy SP, Johnson RK. The scientific basis of recent US guidance on sugars intake. Am J Clin Nutr. 2003; 78(4):827S–833S.
crossref
2. World Health Organization. WHO technical report series 916. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. [Internet]. Geneva: World Health Organization;2002. cited 2019 Jul 29. Available from: https://www.who.int/dietphysicalactivity/publications/trs916/en/.
3. World Health Organization. WHO opens public consultation on draft sugars guideline [Internet]. Geneva: World Health Organization;2014. cited 2019 Jul 29. Available from: https://www.who.int/mediacentre/news/notes/2014/consultationsugar-guideline/en/.
4. Lim YO, Kim YN. The effects of stress and social support on obesity in junior high school students living in small cities. Korean J Community Nutr. 2002; 7(5):705–714.
5. Yoon EK. Current status of Korean sugar intake and reduction policy. Food Ind Nutr. 2018; 23(2):10–13.
6. Charlton KE, Kolbe-Alexander TL, Nel JH. Micronutrient dilution associated with added sugar intake in elderly black South African women. Eur J Clin Nutr. 2005; 59(9):1030–1042.
crossref
7. Oh KS, Lee HJ, Hu SJ, Shin YW, Oh JM, Hwang KM, et al. A Study on the Dietary Pattern and intake of Potentially Hazardous Nutrients among Korean Adults. Cheongju: National Institute of Food and Drug Safety Evaluation;2017.
8. Lee HS, Kwon SO, Yon MY, Kim DH, Lee JY, Nam JW, et al. Dietary total sugar intake of Koreans: based on the Korea National Health and Nutrition Examination Survey (KNHANES), 2008-2011. J Nutr Health. 2014; 47(4):268–276.
crossref
9. Sigman-Grant M. Stages of change: a framework for nutrition interventions. Nutr Today. 1996; 31(4):162–170.
10. Mirmiran P, Azadbakht L, Azizi F. Dietary behaviour of Tehranian adolescents does not accord with their nutritional knowledge. Public Health Nutr. 2007; 10(9):897–901.
crossref
11. Contento I, Balch GI, Bronner YL, Lytle LA, Maloney SK, Olson CM, et al. The effectiveness of nutrition education and implications for nutrition education policy, programs, and research: a review of research. J Nutr Educ. 1995; 27(6):277–418.
12. Yoon JW. A study on office workers intake of the sweetened foods [dissertation]. Seoul: Yonsei University;2017.
13. Shin EK, Doo YT. The sugars Intake through processed foods and its related factors in college students. J Agric Med Community Health. 2016; 41(2):85–97.
crossref
14. Jee YM. A study on sugar intake of female university students [dissertation]. Seoul: Yonsei University;2017.
15. Kim MH, Bae YJ, Yeon JY. Dietary behaviors and total sugar intake from snacks of female college students according to sweet taste perception. Korean J Food Nutr. 2016; 29(2):267–274.
crossref
16. Lee YM, Bae YJ, Kim EY, Yeon JY, Kim MH, Kim MH, et al. Relationship between total sugar intake and obesity indices in female collegians. Korean J Nutr. 2012; 45(1):57–63.
crossref
17. Cho SK. Smartphones used for foreign language learning. Multimed Assist Lang Learn. 2009; 12(3):211–228.
18. Wang DH, Kogashiwa M, Ohta S, Kira S. Validity and reliability of a dietary assessment method: the application of a digital camera with a mobile phone card attachment. J Nutr Sci Vitaminol (Tokyo). 2002; 48(6):498–504.
crossref
19. Pem D, Jeewon R. Fruit and Vegetable Intake: Benefits and Progress of Nutrition Education Interventions- Narrative Review Article. Iran J Public Health. 2015; 44(10):1309–1321.
20. Dunneram Y, Jeewon R. Healthy diet and nutrition education program among women of reproductive age: a necessity of multilevel strategies or community responsibility. Health Promot Perspect. 2015; 5(2):116–127.
crossref
21. Lee JW, Lee HS, Chang N, Kim JM. The relationship between nutrition knowledge scores and dietary behavior, dietary intakes and anthropometric parameters among primary school children participating in a nutrition education program. Korean J Nutr. 2009; 42(4):338–349.
crossref
22. Sharma SV, Gernand AD, Day RS. Nutrition knowledge predicts eating behavior of all food groups except fruits and vegetables among adults in the Paso del Norte region: Qué Sabrosa Vida. J Nutr Educ Behav. 2008; 40(6):361–368.
crossref
23. Lee YJ, Kim GM, Chang KJ. The analysis of effect an nutrition education of elementary school children, Inchon. J Korean Diet Assoc. 2000; 6(2):86–96.
24. National Institute of Food and Drug Safety Evaluation. Food nutrition data sheet [Internet]. Cheongju: National Institute of Food and Drug Safety Evaluation;2017. cited 2019 Jul 29. Available from: https://www.foodsafetykorea.go.kr/portal/healthyfoodlife/foodnutrient/simpleSearch.do?menu_grp=MENU_NEW03&menu_no=2805.
25. Rural Development Administration, National Institute of Agricultural Sciences. Consumer friendly food composition table. 2nd rev. ed. Seoul: Kyomunsa;2013.
26. Ministry of Health and Welfare, The Korean Nutrition Society. Dietary reference intakes for Koreans 2015. Seoul: The Korean Nutrition Society;2015.
27. Ahn SH, Kwon JS, Kim K, Yoon JS, Kang BW, Kim JW, et al. Study on the eating habits and practicability of guidelines for reducing sodium intake according to the stage of change in housewives. Korean J Community Nutr. 2012; 17(6):724–736.
crossref
28. Joo N, Kim SK, Yoon JY. High school students' sugar intake behaviors and consumption of sugary processed food based on the level of sugar-related nutrition knowledge in Seoul area. Korean J Community Nutr. 2017; 22(1):1–12.
crossref
29. Kim YS, Lee MJ. Effects of nutrition education through social cognitive theory in elementary school students-focusing on the nutrition education of sugar intake. Korean J Food Nutr. 2011; 24(2):246–257.
30. Choi EY. Evaluation of reliability and validity of total sugar food frequency questionnaires for Korean adolescents [dissertation]. Seoul: Sungshin Women's University;2014.
31. Ha K, Chung S, Joung H, Song Y. Dietary sugar intake and dietary behaviors in Korea: a pooled study of 2,599 children and adolescents aged 9-14 years. Nutr Res Pract. 2016; 10(5):537–545.
crossref
32. Seo YM. A study on the effects of the sugar intake reduction nutrition education program applying the health belief model for the elementary 3rd graders [dissertation]. Seoul: Yonsei University;2017.
33. Lee KA. Pre-service elementary school teachers' sugar intake and perceptions towards reducing sugar intake. J Korean Pract Arts Educ. 2016; 29(4):111–127.
crossref
TOOLS
ORCID iDs

Yunjung Choi
https://orcid.org/0000-0002-8784-4884

Hyun-Sook Kim
https://orcid.org/0000-0002-1095-3660

Similar articles