Collecting wrappers, labels, and packages to enhance accuracy of food records among children 2-8 years in the Pacific region: Children's Healthy Living Program (CHL)

Kim M Yonemori, Tui Ennis, Rachel Novotny, Marie K Fialkowski, Reynolette Ettienne, Lynne R Wilkens, Rachael T Leon Guerrero, Andrea Bersamin, Patricia Coleman, Fenfang Li, Carol J Boushey, Kim M Yonemori, Tui Ennis, Rachel Novotny, Marie K Fialkowski, Reynolette Ettienne, Lynne R Wilkens, Rachael T Leon Guerrero, Andrea Bersamin, Patricia Coleman, Fenfang Li, Carol J Boushey

Abstract

The aim was to describe differences in dietary outcomes based on the provision of food wrappers, labels or packages (WLP) to complement data from dietary records (DR) among children from the US Affiliated Pacific. The WLP were intended to aid food coding. Since WLP can be associated with ultra-processed foods, one might expect differences in sodium, sugar, and other added ingredients to emerge. Dietary intakes of children (2-8 y) in Alaska, Hawai'i, Commonwealth of the Northern Mariana Islands, and Guam were collected using parent/caregiver completed 2-day DR. Parents were encouraged to collect WLP associated with the child's intake. Trained staff entered data from the DRs including the WLP when available using PacTrac3, a web application. Of the 1,868 DRs collected and entered at the time of this report, 498 (27%) included WLP. After adjusting for confounders (sex, age, location, education, food assistance), the DRs with WLP had significantly higher amounts of energy (kcal), total fat, saturated fat, added sugar, and sodium. These results suggest the inclusion of WLP enhanced the dietary intake data. The intake of energy, fat, added sugar and sodium derived from processed foods and foods consumed outside the home was better captured in children who had WLP.

Keywords: Dietary assessment; Dietary intake; Dietary records; Food analysis; Food composition; Food labels/packaging; Minority populations; US Affiliated Pacific.

Figures

Fig. 1
Fig. 1
Example of a participant’s array of a school menu and wrappers, labels, and packages (WLP) provided by parents completing dietary records for two days. Also shown are a Food and Activity Log and Ziploc® bag.
Fig. 2
Fig. 2
Example of images to capture the front (image #3) and back (image #4) of wrappers, labels, and packages (WLP) provided by parents completing dietary records for two days. These images represent WLP items #2 through #6 by child ID number.
Fig. 3
Fig. 3
Total energy (kcal) differences1 by tertiles of food wrappers, labels, and packages (WLP) provided by parent/caregiver completed dietary records of children (2–8 y) from the Children’s Healthy Living Program (n=480) 1Adjusted for sex, age, body mass index, location, education and financial assistance for food.
Fig. 4
Fig. 4
Total added sugar (tsp) differences1 by tertiles of food wrappers, labels, and packages (WLP) provided by parent/caregiver completed dietary records of children (2–8 y) from the Children’s Healthy Living Program (n=480) 1Adjusted for sex, age, body mass index, location, education and financial assistance for food.

References

    1. Aflague TF, Boushey CJ, Guerrero RT, Ahmad Z, Kerr DA, Delp EJ. Feasibility and use of the mobile food record for capturing eating occasions among children ages 3–10 years in Guam. Nutrients. 2015;7:4403–15.
    1. Aquino RC, Philippi ST. Association of children's consumption of processed foods and family income in the city of São Paulo, Brazil. Revista de Saude Publica. 2002;36:655–660.
    1. Baxter SD, Smith AF, Nichols MD, Guinn CH, Hardin JW. Children’s dietary reporting accuracy over multiple 24-hour recalls varies by body mass index category. Nutrition Research. 2006;26:241–248.
    1. Bolland JE, Ward JY, Bolland TW. Improved accuracy of estimating food quantities up to 4 weeks after training. Journal of the American Dietetic Association. 1990;90:1402–1407.
    1. Braakhuis AJ, Meredith K, Cox GR, Hopkins WG, Burke LM. Variability in estimation of self-reported dietary intake data from elite athletes resulting from coding by different sports dietitians. International Journal of Sport Nutrition and Exercise Metabolism. 2003;13:152–165.
    1. Collins CE, Burrows TL, Truby H, Morgan PJ, Wright IMR, Davies PSW, Callister R. Comparison of Energy Intake in Toddlers Assessed by Food Frequency Questionnaire and Total Energy Expenditure Measured by the Doubly Labeled Water Method. Journal of the Academy of Nutrition and Dietetics. 2013;113:459–463.
    1. Center for Science in the Public Interest (CSPI) Salt assault: Brand-name comparisons of processed foods. 2. Washington, DC, USA: Center for Science in the Public Interest; 2008.
    1. Dachner N, Ricciuto L, Kirkpatrick SI, Tarasuk V. Food purchasing and food insecurity among low-income families in Toronto. Canadian Journal of Dietetic Practice and Research. 2010;71:e50–e56.
    1. Dowler E. Budgeting for food on a low income in the UK: the case of lone-parent families. Food Policy. 1997;22:405–417.
    1. Fernandez-Alvira JM, Mouratidou T, Bammann K, Hebestreit A, Barba G, Sieri S, Reisch L, Eiben G, Hadjigeorgiou C, Kovacs E, Huybrechts I, Moreno LA. Parental education and frequency of food consumption in European children: the IDEFICS study. Public Health Nutrition. 2013;16:487–498.
    1. Fialkowski MK, McCrory MA, Roberts SM, Tracy JK, Grattan LM, Boushey CJ. Evaluation of dietary assessment tools used to assess the diet of adults participating in the Communities Advancing the Studies of Tribal Nations Across the Lifespan (CoASTAL) cohort. Journal of the American Dietetic Association. 2010;110:65–73.
    1. Flynn A, Walton J, Gibney M, Nugent A, McNulty B. National Adult Nutrition Survey: Summary Report. 2011 Retrieved April 28, 2016 from: .
    1. Greenfield H, Southgate DAT. Food Composition Data: Production, Management and Use. (2) 2003:194. Retrieved April 28, 2016 from: .
    1. Gutierrez OM, Katz R, Peralta CA, de Boer IH, Siscovick D, Wolf M, Diez Roux A, Kestenbaum B, Nettleton JA, Ix JH. Associations of socioeconomic status and processed food intake with serum phosphorus in community-living adults: the Multi-Ethnic Study of Atherosclerosis (MESA) Journal of Renal Nutrition. 2012;22:480–489.
    1. Hawley NL, McGarvey ST. Obesity and diabetes in Pacific Islanders: the current burden and the need for urgent action. Current Diabetes Reports. 2015;15:29.
    1. Li F, Wilkens LR, Novotny R, Fialkowski MK, Paulino YC, Nelson R, Bersamin A, Martin U, Deenik J, Boushey CJ. Anthropometric measurement standardization in the US-affiliated pacific: Report from the Children’s Healthy Living Program. American Journal of Human Biology. 2016;28:364–371.
    1. Livingstone MBE, Robson PJ, Wallace JMW. Issues in dietary intake assessment of children and adolescents. British Journal of Nutrition. 2004;92(Suppl 2):S213–S222.
    1. Lv J, Chen Y, Wamg S, Liu Q, Ren Y, Karrar S. A Survey of Nutrition Labels and Fats, Sugars, and Sodium Ingredients in Commercial Packaged Foods in Hangzhou, China. Public Health Reports. 2011;126:116–122.
    1. Maclntyre UE. Measuring Food Intake. In: Gibney MJ, Lanham-New SA, Cassidy A, Vorster HH, editors. Introduction to Human Nutrition. 2. United Kingdom: Oxford Wiley-Blackwell; 2009. pp. 238–275.
    1. Martin CL, Murphy SP, Leon Guerrero RT, Davison N, Jung YO, Novotny R. The Pacific Tracker (PacTrac): Development of a dietary assessment instrument for the Pacific. Journal of Food Composition and Analysis. 2008;21(Suppl 2):S103–S108.
    1. Martinez Steele E, Baraldi LG, Louzada ML, Moubarac JC, Mozaffarian D, Monteiro CA. Ultra-processed foods and added sugars in the US diet: evidence from a nationally representative cross-sectional study. British Medical Journal Open. 2016;6:e009892.
    1. Murphy S. Collection and Analysis of Intake Data from the Integrated Survey. Journal of Nutrition. 2003;133:585S–589S.
    1. Murphy S, Blitz C, Novotny R. Pacific Tracker (PacTrac): an interactive dietary assessment program at the CRCH website. Hawaii Medical Journal. 2006;65:175–178.
    1. National Center for Health Statistics, Centers for Disease Control and Prevention. Growth charts. Retrieved April 28, 2016 from:
    1. Novotny R, Nigg C, McGlone K, Renda G, Jung N, Matsunaga M, Karanja N. Pacific Tracker 2 - expert system (PacTrac2-ES) behavioural assessment and intervention tool for the Pacific Kids DASH for Health (PacDASH) study. Food Chemistry. 2013;140:471–477.
    1. Paulino YC, Coleman P, Davison NH, Lee SK, Camacho TB, Tenorio LF, Murphy SP, Novotny R. Nutritional characteristics and body mass index of children in the Commonwealth of the Northern Mariana Islands. Journal of the American Dietetic Association. 2008;108:2100–2104.
    1. Popkin BM, Hawkes C. Sweetening of the global diet, particularly beverages: patterns, trends, and policy responses. The Lancet Diabetes and Endocrinology. 2016;4:174–86.
    1. Reedy J, Krebs-Smith SM. Dietary sources of energy, solid fats, and added sugars among children and adolescents in the United States. Journal of the American Dietetic Association. 2010;110:1477–1484.
    1. Roberts C, Stickely E, Ziauddeen N, Nicholson S, Steer T. National Diet and Nutrition Survey: Appendix A. Dietary data collection and editing. Retrieved April 28, 2016 from: .
    1. Rosario R, Araujo A, Oliveira B, Padrao P, Lopes O, Teixeira V, Moreira A, Barros R, Pereira B, Moreira P. The impact of an intervention taught by trained teachers on childhood fruit and vegetable intake: a randomized trial. Journal of Obesity. 2012;2012:342138.
    1. Rothman RL, Housam R, Weiss H, Davis D, Gregory R, Gebretsadik T, Shintani A, Elasy TA. Patient understanding of food labels: the role of literacy and numeracy. American Journal of Preventive Medicine. 2006;31:391–398.
    1. Saldiva SR, Venancio SI, de Santana AC, da Santana Castro AL, Escuder MM, Giugliani ER. The consumption of unhealthy foods by Brazilian children is influenced by their mother's educational level. Nutrition Journal. 2014;13:33.
    1. Sevenhuysen GP. Food composition databases: Current problems and solutions. FAO Corporate Document Repository; Retrieved April 28, 2016 from: .
    1. Sinclair S, Hammond D, Goodman S. Sociodemographic differences in the comprehension of nutritional labels on food products. Journal of Nutrition Education and Behavior. 2013;45:767–772.
    1. Speirs KE, Messina LA, Munger AL, Grutzmacher SK. Health literacy and nutrition behaviours among low-income adults. Journal of Health Care for the Poor and Underserved. 2012;23:1082–1091.
    1. Stephen AM, Mak TN, Fitt E, Nicholson S, Roberts C, Sommerville J. Innovations in national nutrition surveys. Proceedings of the Nutrition Society. 2013;72:77–88.
    1. Webster JL, Dunford EK, Neal BC. A systematic survey of the sodium contents of processed foods. American Journal of Clinical Nutrition. 2010;91:413–420.
    1. Wiig K, Smith C. The art of grocery shopping on a food stamp budget: factors influencing the food choices of low-income women as they try to make ends meet. Public Health Nutrition. 2009;12:1726–1734.
    1. Wilken LR, Novotny R, Fialkowski MK, Boushey CJ, Nigg C, Paulino Y, Leon Guerrero R, Bersamin A, Vargo D, Kim J, Deenik J. Children's Healthy Living (CHL) Program for remote underserved minority populations in the Pacific region: rationale and design of a community randomized trial to prevent early childhood obesity. BioMed Central Public Health. 2013;13:944.
    1. Yin HS, Johnson M, Mendelsohn AL, Abrams MA, Sanders LM, Dreyer BP. The health Literacy of parents in the United States: a nationally representative study. Pediatrics. 2009;124(Suppl 3):S289–98.
    1. Zachary DA, Palmer AM, Beckham SW, Surkan PJ. A framework for understanding grocery purchasing in a low-income urban environment. Qualitative Health Research. 2013;23:665–678.

Source: PubMed

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