Relative Validity of a Method Based on a Smartphone App (Electronic 12-Hour Dietary Recall) to Estimate Habitual Dietary Intake in Adults

Luis María Béjar, María Dolores García-Perea, Óscar Adrián Reyes, Esther Vázquez-Limón, Luis María Béjar, María Dolores García-Perea, Óscar Adrián Reyes, Esther Vázquez-Limón

Abstract

Background: Accurate dietary assessment is key to understanding nutrition-related outcomes and for estimating the dietary change in nutrition-based interventions. When researching the habitual consumption of selected food groups, it is essential to be aware of factors that could possibly affect reporting accuracy.

Objective: This study aimed to evaluate the relative validity of the current-day dietary recall, a method based on a smartphone app called electronic 12-hour dietary recall (e-12HR), to categorize individuals according to habitual intake, in the whole sample of adults and in different strata thereof.

Methods: University students and employees over 18 years recorded the consumption of 10 selected groups of food using e-12HR during 28 consecutive days. During this period, they also completed 4 dietary records. Once the period was finished, the subjects then completed a food frequency questionnaire (FFQ) and a usability-rating questionnaire for e-12HR. The food group intakes estimated by the e-12HR app, the dietary records, and the FFQ were categorized into sextiles: less than once a week, once or twice a week, 3-4 times a week, 5-6 times a week, once or twice a day, and 3 or more times a day. The 10 selected groups with e-12HR were compared with 4 dietary records and an FFQ reference method, in the whole sample and in different strata thereof: age (years): <25 and ≥25; gender: females and males; occupation: students and employees; smoking: no and yes; physical activity (minutes/week): ≥150 and <150; and body mass index (kg/m2): <25 and ≥25. The association between the different methods was assessed using Spearman correlation coefficient (SCC). Cross-classification and kappa statistic were used as a measure of agreement between the different methods.

Results: In total, 203 participants completed the study (56.7% [115/203] women, and 43.3% [88/203] men). For all food groups and all participants, the mean SCC for e-12HR versus FFQ was 0.67 (≥0.62 for all strata). On average, 50.7% of participants were classified into the same category (≥47.0% for all strata) and 90.2% within the nearest category (≥88.6% for all strata). Mean weighted kappa was 0.49 (≥0.44 for all strata). For e-12HR versus RDs, mean SCC was 0.65 (≥0.57 for all strata). On average, 50.0% of participants were classified into the same category (≥47.0% for all strata) and 88.2% within the nearest category (≥86.1% for all strata). Mean weighted kappa was 0.50 (≥0.44 for all strata).

Conclusions: The results indicate that e-12HR generated categories of dietary intake highly comparable with the 2 reference methods in the whole sample and in different strata thereof. The inclusion of photographs to facilitate estimation of the servings consumed generated correlation/agreement data between e-12HR and the FFQ that were similar to a previous study using an older version of the app, which did not include photographs.

Keywords: diet records; epidemiologic methods; mobile apps; nutrition assessment.

Conflict of interest statement

Conflicts of Interest: None declared.

©Luis María Béjar, María Dolores García-Perea, Óscar Adrián Reyes, Esther Vázquez-Limón. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 11.04.2019.

Figures

Figure 1
Figure 1
Assessment process using the electronic 12-hour dietary recall (e-12HR) app, 4 dietary records (DRs), food frequency questionnaire (FFQ), and usability rating questionnaire for the e-12HR app.

References

    1. Carroll RJ, Midthune D, Subar AF, Shumakovich M, Freedman LS, Thompson FE, Kipnis V. Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology. Am J Epidemiol. 2012 Feb 15;175(4):340–7. doi: 10.1093/aje/kwr317.
    1. Willett W. Nutritional Epidemiology, Third Edition. New York, MD: Oxford University Press; 2013.
    1. Stumbo PJ. New technology in dietary assessment: a review of digital methods in improving food record accuracy. Proc Nutr Soc. 2013 Feb;72(1):70–6. doi: 10.1017/S0029665112002911.
    1. Masson LF, McNeill G, Tomany JO, Simpson JA, Peace HS, Wei L, Grubb DA, Bolton-Smith C. Statistical approaches for assessing the relative validity of a food-frequency questionnaire: use of correlation coefficients and the kappa statistic. Public Health Nutr. 2003 May;6(3):313–21. doi: 10.1079/PHN2002429.
    1. Giabbanelli PJ, Adams J. Identifying small groups of foods that can predict achievement of key dietary recommendations: data mining of the UK National Diet and Nutrition Survey, 2008-12. Public Health Nutr. 2016 Dec;19(9):1543–51. doi: 10.1017/S1368980016000185.
    1. Rosso N, Giabbanelli P. Accurately inferring compliance to five major food guidelines through simplified surveys: applying data mining to the UK National Diet and Nutrition Survey. JMIR Public Health Surveill. 2018 May 30;4(2):e56. doi: 10.2196/publichealth.9536.
    1. Rutishauser IH. Dietary intake measurements. Public Health Nutr. 2005 Oct;8(7A):1100–7. doi: 10.1079/PHN2005798.
    1. Kristal AR, Kolar AS, Fisher JL, Plascak JJ, Stumbo PJ, Weiss R, Paskett ED. Evaluation of web-based, self-administered, graphical food frequency questionnaire. J Acad Nutr Diet. 2014 Apr;114(4):613–21. doi: 10.1016/j.jand.2013.11.017.
    1. Cleghorn CL, Harrison RA, Ransley JK, Wilkinson S, Thomas J, Cade JE. Can a dietary quality score derived from a short-form FFQ assess dietary quality in UK adult population surveys? Public Health Nutr. 2016 Nov;19(16):2915–23. doi: 10.1017/S1368980016001099.
    1. Saeedi P, Skeaff SA, Wong JE, Skidmore PM. Reproducibility and relative validity of a short food frequency questionnaire in 9–10 year-old children. Nutrients. 2016 May 7;8(5) doi: 10.3390/nu8050271.
    1. Buch-Andersen T, Pérez-Cueto FJ, Toft U. Relative validity and reproducibility of a parent-administered semi-quantitative FFQ for assessing food intake in Danish children aged 3-9 years. Public Health Nutr. 2016 May;19(7):1184–94. doi: 10.1017/S136898001500275X.
    1. Knudsen VK, Hatch EE, Cueto H, Tucker KL, Wise L, Christensen T, Mikkelsen EM. Relative validity of a semi-quantitative, web-based FFQ used in the 'Snart Forældre' cohort - a Danish study of diet and fertility. Public Health Nutr. 2016 Apr;19(6):1027–34. doi: 10.1017/S1368980015002189.
    1. Medin AC, Carlsen MH, Andersen LF. Associations between reported intakes of carotenoid-rich foods and concentrations of carotenoids in plasma: a validation study of a web-based food recall for children and adolescents. Public Health Nutr. 2016 Dec;19(18):3265–75. doi: 10.1017/S1368980016001622.
    1. Forster H, Fallaize R, Gallagher C, O'Donovan CB, Woolhead C, Walsh MC, Macready AL, Lovegrove JA, Mathers JC, Gibney MJ, Brennan L, Gibney ER. Online dietary intake estimation: the Food4Me food frequency questionnaire. J Med Internet Res. 2014;16(6):e150. doi: 10.2196/jmir.3105.
    1. Fallaize R, Forster H, Macready AL, Walsh MC, Mathers JC, Brennan L, Gibney ER, Gibney MJ, Lovegrove JA. Online dietary intake estimation: reproducibility and validity of the Food4Me food frequency questionnaire against a 4-day weighed food record. J Med Internet Res. 2014;16(8):e190. doi: 10.2196/jmir.3355.
    1. Riobó SP, Sierra PR, Soldo RJ, Gómez-Candela C, García LP, Serra-Majem L. Special considerations for nutritional studies in elderly. Nutr Hosp. 2015 Feb 26;31(Suppl 3):84–90. doi: 10.3305/nh.2015.31.sup3.8756.
    1. Tucker KL, Smith CE, Lai C, Ordovas JM. Quantifying diet for nutrigenomic studies. Annu Rev Nutr. 2013;33:349–71. doi: 10.1146/annurev-nutr-072610-145203.
    1. Gibson R. Principles of Nutritional Assessment, Second Edition. New York, Md: Oxford University Press; 2005.
    1. Martín-Moreno JM, Gorgojo L. [Assessment of dietary intake at the population level through individual questionnaires: methodological shadows and lights] Rev Esp Salud Publica. 2007;81(5):507–18.
    1. Dhurandhar NV, Schoeller D, Brown AW, Heymsfield SB, Thomas D, Sørensen TI, Speakman JR, Jeansonne M, Allison DB, Energy Balance Measurement Working Group Energy balance measurement: when something is not better than nothing. Int J Obes (Lond) 2014 Nov 13; doi: 10.1038/ijo.2014.199.
    1. Kim DW, Oh S, Kwon S, Kim J. Comparison of validity of food group intake by food frequency questionnaire between pre- and post- adjustment estimates derived from 2-day 24-hour recalls in combination with the probability of consumption. Asian Pac J Cancer Prev. 2012;13(6):2655–61.
    1. Gerdessen JC, Souverein OW, van 't Veer P, de Vries JH. Optimising the selection of food items for FFQs using Mixed Integer Linear Programming. Public Health Nutr. 2015 Jan;18(1):68–74. doi: 10.1017/S1368980013003479.
    1. Rangan AM, O'Connor S, Giannelli V, Yap ML, Tang LM, Roy R, Louie JC, Hebden L, Kay J, Allman-Farinelli M. Electronic Dietary Intake Assessment (e-DIA): comparison of a mobile phone digital entry app for dietary data collection with 24-hour dietary recalls. JMIR Mhealth Uhealth. 2015 Oct 27;3(4):e98. doi: 10.2196/mhealth.4613.
    1. Falomir Z, Arregui M, Madueño F, Corella D, Coltell O. Automation of food questionnaires in medical studies: a state-of-the-art review and future prospects. Comput Biol Med. 2012 Oct;42(10):964–74. doi: 10.1016/j.compbiomed.2012.07.008.
    1. Christensen SE, Möller E, Bonn SE, Ploner A, Wright A, Sjölander A, Bälter O, Lissner L, Bälter K. Two new meal- and web-based interactive food frequency questionnaires: validation of energy and macronutrient intake. J Med Internet Res. 2013 Jun;15(6):e109. doi: 10.2196/jmir.2458.
    1. Swierk M, Williams PG, Wilcox J, Russell KG, Meyer BJ. Validation of an Australian electronic food frequency questionnaire to measure polyunsaturated fatty acid intake. Nutrition. 2011 Jun;27(6):641–6. doi: 10.1016/j.nut.2010.06.011.
    1. Labonté M, Cyr A, Baril-Gravel L, Royer M, Lamarche B. Validity and reproducibility of a web-based, self-administered food frequency questionnaire. Eur J Clin Nutr. 2012 Feb;66(2):166–73. doi: 10.1038/ejcn.2011.163.
    1. Svensson A, Larsson C. A mobile phone app for dietary intake assessment in adolescents: an evaluation study. JMIR Mhealth Uhealth. 2015;3(4):e93. doi: 10.2196/mhealth.4804.
    1. Saloheimo T, González SA, Erkkola M, Milauskas DM, Meisel JD, Champagne CM, Tudor-Locke C, Sarmiento O, Katzmarzyk PT, Fogelholm M. The reliability and validity of a short food frequency questionnaire among 9-11-year olds: a multinational study on three middle-income and high-income countries. Int J Obes Suppl. 2015 Dec;5(Suppl 2):S22–8. doi: 10.1038/ijosup.2015.15.
    1. Tabacchi G, Filippi AR, Breda J, Censi L, Amodio E, Napoli G, Bianco A, Jemni M, Firenze A, Mammina C. Comparative validity of the ASSO-Food Frequency Questionnaire for the web-based assessment of food and nutrients intake in adolescents. Food Nutr Res. 2015;59:26216. doi: 10.3402/fnr.v59.26216.
    1. Alcantara I, Haardörfer R, Gazmararian JA, Hartman TJ, Greene B, Kegler MC. Relative validation of fruit and vegetable intake and fat intake among overweight and obese African-American women. Public Health Nutr. 2015 Aug;18(11):1932–40. doi: 10.1017/S1368980014002547.
    1. Béjar LM, Reyes ÓA, García-Perea MD. Electronic 12-Hour Dietary Recall (e-12HR): comparison of a mobile phone app for dietary intake assessment with a food frequency questionnaire and four dietary records. JMIR Mhealth Uhealth. 2018 Jun 15;6(6):e10409. doi: 10.2196/10409.
    1. Souverein OW, Dekkers AL, Geelen A, Haubrock J, de Vries JH, Ocké MC, Harttig U, Boeing H, van 't Veer P. Comparing four methods to estimate usual intake distributions. Eur J Clin Nutr. 2011 Jul;65(Suppl 1):S92–101. doi: 10.1038/ejcn.2011.93.
    1. Head of State [State Agency Official State Gazette] 1999. [2019-03-08]. Law 15/1999, of Protection of Personal Data .
    1. Marshall SJ, Livingstone KM, Celis-Morales C, Forster H, Fallaize R, O'Donovan CB, Woolhead C, Marsaux CF, Macready AL, Navas-Carretero S, San-Cristobal R, Kolossa S, Tsirigoti L, Lambrinou CP, Moschonis G, Godlewska M, Surwiłło A, Drevon CA, Manios Y, Traczyk I, Martínez JA, Saris WH, Daniel H, Gibney ER, Brennan L, Walsh MC, Lovegrove JA, Gibney M, Mathers JC, Food4Me Study Reproducibility of the online Food4Me food-frequency questionnaire for estimating dietary intakes across Europe. J Nutr. 2016 Dec;146(5):1068–75. doi: 10.3945/jn.115.225078.
    1. Medin AC, Astrup H, Kåsin BM, Andersen LF. Evaluation of a web-based food record for children using direct unobtrusive lunch observations: a validation study. J Med Internet Res. 2015 Dec 7;17(12):e273. doi: 10.2196/jmir.5031.
    1. Hongu N, Pope BT, Bilgiç P, Orr BJ, Suzuki A, Kim AS, Merchant NC, Roe DJ. Usability of a smartphone food picture app for assisting 24-hour dietary recall: a pilot study. Nutr Res Pract. 2015 Apr;9(2):207–12. doi: 10.4162/nrp.2015.9.2.207.
    1. Henriksson H, Bonn SE, Bergström A, Bälter K, Bälter O, Delisle C, Forsum E, Löf M. A new mobile phone-based tool for assessing energy and certain food intakes in young children: a validation study. JMIR Mhealth Uhealth. 2015 Apr 24;3(2):e38. doi: 10.2196/mhealth.3670.
    1. Daugherty BL, Schap TE, Ettienne-Gittens R, Zhu FM, Bosch M, Delp EJ, Ebert DS, Kerr DA, Boushey CJ. Novel technologies for assessing dietary intake: evaluating the usability of a mobile telephone food record among adults and adolescents. J Med Internet Res. 2012;14(2):e58. doi: 10.2196/jmir.1967.
    1. Casperson SL, Sieling J, Moon J, Johnson L, Roemmich JN, Whigham L. A mobile phone food record app to digitally capture dietary intake for adolescents in a free-living environment: usability study. JMIR Mhealth Uhealth. 2015;3(1):e30. doi: 10.2196/mhealth.3324.
    1. Rodríguez IT, Ballart JF, Pastor GC, Jordà EB, Val VA. [Validation of a short questionnaire on frequency of dietary intake: reproducibility and validity] Nutr Hosp. 2008;23(3):242–52.
    1. Vereecken CA, Maes L. A Belgian study on the reliability and relative validity of the Health Behaviour in School-Aged Children food-frequency questionnaire. Public Health Nutr. 2003 Sep;6(6):581–8. doi: 10.1079/PHN2003466.
    1. Knudsen VK, Gille M, Nielsen TH, Christensen T, Fagt S, Biltoft-Jensen A. Relative validity of the pre-coded food diary used in the Danish National Survey of Diet and Physical Activity. Public Health Nutr. 2011 Dec;14(12):2110–6. doi: 10.1017/S1368980011001650.
    1. Bejar LM, Sharp BN, García-Perea MD. The e-EPIDEMIOLOGY mobile phone app for dietary intake assessment: comparison with a food frequency questionnaire. JMIR Res Protoc. 2016 Nov 2;5(4):e208. doi: 10.2196/resprot.5782.
    1. Béjar LM. First evaluation steps of a new method for dietary intake estimation regarding a list of key food groups in adults and in different sociodemographic and health-related behaviour strata. Public Health Nutr. 2017 Oct;20(15):2660–9. doi: 10.1017/S1368980017001641.
    1. Watanabe M, Yamaoka K, Yokotsuka M, Adachi M, Tango T. Validity and reproducibility of the FFQ (FFQW82) for dietary assessment in female adolescents. Public Health Nutr. 2011 Feb;14(2):297–305. doi: 10.1017/S1368980010001618.
    1. StataCorp L. [2018-07-07]. Stata Statistical Software: Release 13
    1. Cohen J. Statistical Power Analysis for the Behavioral Sciences, Second Edition. New York: Lawrence Erlbaum Associates; 1988.
    1. Viera AJ, Garrett JM. Understanding interobserver agreement: the kappa statistic. Fam Med. 2005 May;37(5):360–3.
    1. World Health Organization. 2001. [2018-07-07]. Global Recommendations on Physical Activity for Health .
    1. World Health Organization. 1998. [2018-07-07]. Programme of nutrition, family and reproductive health. Obesity. Preventing and managing the global epidemic .
    1. England CY, Thompson JL, Jago R, Cooper AR, Andrews RC. Development of a brief, reliable and valid diet assessment tool for impaired glucose tolerance and diabetes: the UK Diabetes and Diet Questionnaire. Public Health Nutr. 2017 Feb;20(2):191–9. doi: 10.1017/S1368980016002275.
    1. Tabacchi G, Filippi AR, Amodio E, Jemni M, Bianco A, Firenze A, Mammina C. A meta-analysis of the validity of FFQ targeted to adolescents. Public Health Nutr. 2016 May;19(7):1168–83. doi: 10.1017/S1368980015002505.
    1. Deschamps V, de Lauzon-Guillain B, Lafay L, Borys J, Charles MA, Romon M. Reproducibility and relative validity of a food-frequency questionnaire among French adults and adolescents. Eur J Clin Nutr. 2009 Feb;63(2):282–91. doi: 10.1038/sj.ejcn.1602914.
    1. Vereecken CA, Rossi S, Giacchi MV, Maes L. Comparison of a short food-frequency questionnaire and derived indices with a seven-day diet record in Belgian and Italian children. Int J Public Health. 2008;53(6):297–305. doi: 10.1007/s00038-008-7101-6.
    1. Matthys C, Pynaert I, De Keyzer W, De Henauw S. Validity and reproducibility of an adolescent web-based food frequency questionnaire. J Am Diet Assoc. 2007 Apr;107(4):605–10. doi: 10.1016/j.jada.2007.01.005.
    1. [2019-03-08]. nQuery Advisor Version 7 .
    1. Bassett JK, English DR, Fahey MT, Forbes AB, Gurrin LC, Simpson JA, Brinkman MT, Giles GG, Hodge AM. Validity and calibration of the FFQ used in the Melbourne Collaborative Cohort Study. Public Health Nutr. 2016 Sep;19(13):2357–68. doi: 10.1017/S1368980016000690.
    1. Hedrick VE, Dietrich AM, Estabrooks PA, Savla J, Serrano E, Davy BM. Dietary biomarkers: advances, limitations and future directions. Nutr J. 2012 Dec 14;11:109. doi: 10.1186/1475-2891-11-109.

Source: PubMed

Sponzoři a spolupracovníci

Zdravotní podmínky

Drogové intervence

3
Předplatit