臺灣博碩士論文加值系統

Dietary intake plays a unique role to promote health throughout the lifespan. This study was designed to examine the impact of food literacy toward dietary patterns among adolescents.
Design A cross-sectional study was conducted using a validated questionnaire to measure the level of food literacy. Six food patterns were identified as ‘vegetable’, ‘traditional snack’, ‘fruit’, ‘fish’, ‘processed meat’ and ‘poultry’ using a principal component analysis.
Participants/setting Four hundred and sixty four high school students (15-18 years) were selected using a multistage random sampling method from July to September 2015 in Malang City, Indonesia.
Results The results showed that high level of food literacy was positively correlated with high consumption (Q4, quartile 4) of vegetables (r=0.412, p≤0.01) and fruits (r=0.297, p≤0.05) among adolescents. There were no significant differences in consumption of traditional snacks, fish, processed meat, and poultry.
Conclusion A positive correlation was observed between high level of food literacy and high consumption of vegetables and fruits. Implementing intervention based on food literacy can be beneficial for improving the consumption of vegetables and fruits.

Dietary intake plays a unique role to promote health throughout the lifespan. This study was designed to examine the impact of food literacy toward dietary patterns among adolescents.
Design A cross-sectional study was conducted using a validated questionnaire to measure the level of food literacy. Six food patterns were identified as ‘vegetable’, ‘traditional snack’, ‘fruit’, ‘fish’, ‘processed meat’ and ‘poultry’ using a principal component analysis.
Participants/setting Four hundred and sixty four high school students (15-18 years) were selected using a multistage random sampling method from July to September 2015 in Malang City, Indonesia.
Results The results showed that high level of food literacy was positively correlated with high consumption (Q4, quartile 4) of vegetables (r=0.412, p≤0.01) and fruits (r=0.297, p≤0.05) among adolescents. There were no significant differences in consumption of traditional snacks, fish, processed meat, and poultry.
Conclusion A positive correlation was observed between high level of food literacy and high consumption of vegetables and fruits. Implementing intervention based on food literacy can be beneficial for improving the consumption of vegetables and fruits.

TABLE OF CONTENTS
GRADUATE STUDENT THESIS PUBLICATION AGREEMENT ii
GRADUATE THESIS CERTIFICATION iii
GRADUATE THESIS DEFENSE CONFIDENTIALITY AGREEMENT iv
ACKNOWLEDGEMENT vii
LIST OF FIGURES viii
LIST OF TABLES viii
ABSTRACT x
1. INTRODUCTION 1
2. LITERATURE REVIEW 3
2.1 Definition of food literacy 3
2.1.1 Planning and management component in food literacy 4
2.1.2 Selection 4
2.1.3 Preparation 5
2.1.4 Eating 5
2.2 Food literacy in Canada 6
2.2.1 Meal purchasing and preparation skills 7
2.2.2 Food safety 9
2.2.3 Planning and budgeting for food 10
2.2.4 The state of food literacy in Canada 10
2.3 Dietary intake of adolescents in Indonesia 11
2.4 The association between food literacy and dietary intake 13
3. MATERIALS AND METHODS 14
3.1 Study design and subject 14
3.2 Demographic and anthropometry characteristics 14
3.3 Food literacy level 15
3.4 Dietary intake 16
3.5 Statistical methods 16
4. RESULTS 18
5. DISCUSSION 33
6. CONCLUSION 37
REFERENCES 38
APPENDICES 44

LIST OF FIGURES
Figure 1. The eleven components of food literacy 3
Figure 2. Canadians food purchasing priorities 7
Figure 3. Nutrition information sought on labels 8
Figure 4. Food safety concerns 9


LIST OF TABLES
Table 1 Demographic and anthropometry characteristics in adolescents aged 15-18 years (n=464) 22
Table 2 Correlation coefficient (r) between components of food literacy and food literacy in adolescents aged 15-18 years (n=464) 23
Table 3 Comparison between score of food literacy between males and females in adolescents aged 15-18 years (n=464) 23
Table 4 The correlation ((β) between demographic data and anthropometric measurements according the food literacy level in adolescents aged 15-18 years (n=464) 24
Table 5 Factor loading matrix for the six dietary patterns in adolescents aged 15-18 years (n=464) 25
Table 6 Correlation coefficient (r) between demographic of study participants and dietary patterns according to the quartile of dietary pattern scores in adolescents aged 15-18 years (n=464) 26
Table 7 The correlation (β) between food literacy level and dietary patterns in adolescents aged 15-18 years (n=464) 28
Table 8 The correlation (β) between food literacy level and dietary patterns in males adolescent aged 15-18 years (n=186) 28
Table 9 The correlation (β) between food literacy level and dietary patterns in females adolescent aged 15-18 years (n=278) 29
Table 10 The correlation (β) between body mass index (underweight and normal) and dietary patterns in adolescents aged 15-18 years (n=464) 29
Table 11 The correlation (β) between body mass index (underweight and normal) and dietary patterns in males adolescents aged 15-18 years (n=186) 30
Table 12 The correlation (β) between body mass index (underweight and normal) and dietary patterns in females adolescents aged 15-18 years (n=278) 30
Table 13 The correlation (β) between body mass index (overweight/obese and normal) and dietary patterns in adolescents aged 15-18 years (n=464) 31
Table 14 The correlation (β) between body mass index (overweight/obese and normal) and dietary patterns in males adolescent aged 15-18 years (n=186) 31
Table 15 The correlation (β) between body mass index (overweight/obese and normal) and dietary patterns in females adolescent aged 15-18 years (n=278) 32

1.Hiza HA, Casavale KO, Guenther PM, Davis CA. Diet quality of Americans differs by age, sex, race/ethnicity, income, and education level. J Acad Nutr Diet.2013;113:297-306.
2.Peltzer K, Pengpid S. Fruits and vegetables consumption and associated factors among in-school adolescents in five Southeast Asian countries. Int J Environ Res Public Health.2012;9:3575-3587.
3.Thomson CA, Ravia J. A systematic review of behavioral interventions to promote intake of fruit and vegetables. J Am Diet Assoc.2011;111:1523-1535.
4.Chen ST, Maruthur NM, Appel LJ. The effect of dietary patterns on estimated coronary heart disease risk: results from the Dietary Approaches to Stop Hypertension (DASH) trial. Circ Cardiovasc Qual Outcomes.2010;3:484-489.
5.Elwood PC, Pickering JE, Givens DI, Gallacher JE. The consumption of milk and dairy foods and the incidence of vascular disease and diabetes: an overview of the evidence. Lipids.2010;45:925-939.
6.Mellen PB, Walsh TF, Herrington DM. Whole grain intake and cardiovascular disease: a meta-analysis. Nutr Metab Cardiovasc Dis.2008;18:283-290.
7.Kant AK. Dietary patterns: biomarkers and chronic disease risk. Appl Physiol Nutr Metab.2010;35:199-206.
8.Rae A. Food consumption patterns and nutrition in urban Java households: the discriminatory porwer of some socioeconomic variables. Aust J Agr Resour Ec.1999;43:359-383.
9.McNaughton SA, Ball K, Mishra GD, Crawford DA. Dietary patterns of adolescents and risk of obesity and hypertension. J Nutr.2008;138:364-370.
10.Laska MN, Larson NI, Neumark-Sztainer D, Story M. Does involvement in food preparation track from adolescence to young adulthood and is it associated with better dietary quality? Findings from a 10-year longitudinal study. Public Health Nutr.2012;15:1150-1158.
11.Nelson MC, Lytle LA, Pasch KE. Improving literacy about energy-related issues: the need for a better understanding of the concepts behind energy intake and expenditure among adolescents and their parents. J Am Diet Assoc.2009;109:281-287.
12.Vaitkeviciute R, Ball LE, Harris N. The relationship between food literacy and dietary intake in adolescents: a systematic review. Public Health Nutrition.2015;18:649-658.
13.Vidgen HA, Gallegos D. Defining food literacy and its components. Appetite.2014;76:50-59.
14.Larson NI, Perry CL, Story M, Neumark-Sztainer D. Food preparation by young adults is associated with better diet quality. J. Acad. Nutr. Diet.2006;106:2001-2007.
15.Caraher M, Seeley A, Wu M, Lloyd S. When chefs adopt a school? An evaluation of a cooking intervention in English primary schools. Appetite.2013;62:50-59.
16.Canada TCBo. Improving Food Literacy in Canada. 2013. https://appetite4change.files.wordpress.com/2013/12/cbofc-food-literacy.pdf. Accessed February 20, 2015.
17.Nutrition CCoFa. Tracking Nutrition Trends VII. 2008. https://http://www.cfdr.ca/Downloads/CCFN-docs/C1180---TNT-VII-FINAL-REPORT---full-report--Sept-1.aspx. Accessed January 29, 2015.
18.Chenhall C. Improving Cooking and Food Preparation Skills : A Synthesis of the Evidence to Inform Program and Policy Development. 2010. http://www.hc-sc.gc.ca/fn-an/alt_formats/pdf/nutrition/child-enfant/cfps-acc-synthes-eng.pdf. Accessed April, 25, 2015.
19.Waterloo Ro. Food Skills of Waterloo Region Adults (2008-2014). 2015. http://chd.region.waterloo.on.ca/en/researchResourcesPublications/resources/FoodSkills_WR.pdf. Accessed January 31, 2015.
20.Wahyuni, Krisnamurni. Report Compilation of Studies Related to Food Consumption, Physical Exercise, Healthy Lifestyle, and Nutritional Status Conducted in Indonesia between 2000-2010: Age Group Adolescence Age 13-18 Years. 2010. http://www.danonenutrindo.org/pdf/Wahyuni.pdf. Accessed March, 30, 2015.
21.Usfar AA, Fahmida U. Do Indonesians follow its dietary guidelines?: evidence related to food consumption, healthy lifestyle, and nutritional status within the period 2000-2010. Asia Pac J Clin Nutr.2011;20:484-494.
22.Collins AE, Pakiz B, Rock CL. Factors associated with obesity in Indonesian adolescents. Int J Pediatr Obes.2008;3:58-64.
23.Brooks N, Begley A. Adolescent food literacy programmes: A review of the literature. Nutr & Diet.2014;71:158-171.
24.Smith AD, Emmett PM, Newby PK, Northstone K. Dietary patterns obtained through principal components analysis: the effect of input variable quantification. Br J Nutr.2013;109:1881-1891.
25.Paquette MC. Perceptions of healthy eating. Can J Public Health.2005;96:S16-S21.
26.Mirmiran P, Azadbakht L, Azizi F. Dietary behaviour of Tehranian adolescents does not accord with their nutritional knowledge. Public Health Nutr.2007;10:897-901.
27.Kant AK. Dietary patterns and health outcomes. J Am Diet Assoc.2004;104:615-635.
28.Taylor JP, Evers S, McKenna M. Determinants of Healthy Eating in Children and Youth. Can J Public Health.2005:S20-S26.
29.Riediger ND, Shooshtari S, Moghadasian MH. The influence of sociodemographic factors on patterns of fruit and vegetable consumption in Canadian adolescents. J Am Diet Assoc.2007;107:1511-1518.
30.Pearson T, Russell J, Campbell MJ, Barker ME. Do ''food deserts'' influence fruit and vegetable consumption?--A cross-sectional study. Appetite.2005;45:195-197.
31.Gose M, Plachta-Danielzik S, Willie B, Johannsen M, Landsberg B, Muller MJ. Longitudinal influences of neighbourhood built and social environment on children''s weight status. Int J Environ Res Public Health.2013;10:5083-5096.
32.Leung CW, Ding EL, Catalano PJ, Villamor E, Rimm EB, Willett WC. Dietary intake and dietary quality of low-income adults in the Supplemental Nutrition Assistance Program. Am J Clin Nutr.2012;96:977-988.
33.WHO. Diet, nutrition and prevention of chronic disease. Joint WHO-FAO consultation. World Health Organisation Technical Serios.2003;No. 916. Geneva: WHO.
34.Knai C, Pomerleau J, Lock K, McKee M. Getting children to eat more fruit and vegetables: a systematic review. Prev Med.2006;42:85-95.
35.Dennison BA, Rockwell HL, Baker SL. Excess fruit juice consumption by preschool-aged children is associated with short stature and obesity (vol 99, pg 15, 1997). Pediatrics.1997;100:733-733.
36.Field AE, Gillman MW, Rosner B, Rockett HR, Colditz GA. Association between fruit and vegetable intake and change in body mass index among a large sample of children and adolescents in the United States. Int J Obes Relat Metab Disord.2003;27:821-826.
37.Bes-Rastrollo M, Martinez-Gonzalez MA, Sanchez-Villegas A, de la Fuente Arrillaga C, Martinez JA. Association of fiber intake and fruit/vegetable consumption with weight gain in a Mediterranean population. Nutrition.2006;22:504-511.
38.Newby PK, Tucker KL. Empirically Derived Eating Patterns Using Factor or Cluster Analysis: A Review. Nutrition Reviews.2004;62:177-203.
39.Schulze MB, Hoffmann K. Methodological approaches to study dietary patterns in relation to risk of coronary heart disease and stroke. Br J Nutr.2006;95:860-869.
40.Merten MJ, Williams AL, Shriver LH. Breakfast consumption in adolescence and young adulthood: parental presence, community context, and obesity. J Am Diet Assoc.2009;109:1384-1391.