Skip to main content Accessibility help

Optimizing portion-size estimation aids: a formative evaluation in Malawi

  • Courtney H Schnefke (a1), Chrissie Thakwalakwa (a2), Mary K Muth (a1), John Phuka (a3), Jennifer Coates (a4), Beatrice Rogers (a4), Brooke Colaiezzi (a4), Winnie Bell (a4) and Valerie L Flax (a1)...



To investigate preferences for and ease-of-use perceptions of different aspects of printed and digitally displayed photographic portion-size estimation aids (PSEA) in a low-resource setting and to document accuracy of portion-size selections using PSEA with different visual characteristics.


A convergent mixed-methods design and stepwise approach were used to assess characteristics of interest in isolation. Participants served themselves food and water, which were weighed before and after consumption to measure leftovers and quantity consumed. Thirty minutes later, data collectors administered a meal recall using a PSEA and then a semi-structured interview.


Blantyre and Chikwawa Districts in the southern region of Malawi.


Ninety-six women, aged 18–45 years.


Preferences and ease-of-use perceptions favoured photographs rather than drawings of shapes, three and five portion-size options rather than three with four virtual portion-size options, a 45° rather than a 90° photograph angle, and simultaneous rather than sequential presentation of portion-size options. Approximately half to three-quarters of participants found the portion-size options represented appropriate amounts of foods or water consumed. Photographs with three portion sizes resulted in more accurate portion-size selections (closest to measured consumption) than other format and number of portion-size option combinations. A 45° angle and simultaneous presentation were more accurate than a 90° angle and sequential presentation of images.


Results from testing PSEA visual characteristics separately can be used to generate optimal PSEA, which can improve participants’ experiences during meal recalls.


Corresponding author

*Corresponding author: Email


Hide All
1. Gibson, RS, Charrondiere, UR & Bell, W (2017) Measurement errors in dietary assessment using self-reported 24-hour recalls in low-income countries and strategies for their prevention. Adv Nutr 8, 980991.
2. Cypel, YS, Guenther, PM & Petot, GJ (1997) Validity of portion-size measurement aids: a review. J Am Diet Assoc 97, 289292.
3. Lazarte, CE, Encinas, ME, Alegre, C et al. (2012) Validation of digital photographs, as a tool in 24-h recall, for the improvement of dietary assessment among rural populations in developing countries. Nutr J 11, 61.
4. Nelson, M & Haraldsdottir, J (1998) Food photographs: practical guidelines I. Design and analysis of studies to validate portion size estimates. Public Health Nutr 1, 219230.
5. Nelson, M & Haraldsdottir, J (1998) Food photographs: practical guidelines II. Development and use of photographic atlases for assessing food portion size. Public Health Nutr 1, 231237.
6. Ovaskainen, ML, Paturi, M, Reinivuo, H et al. (2008) Accuracy in the estimation of food servings against the portions in food photographs. Eur J Clin Nutr 62, 674681.
7. Naska, A, Valanou, E, Peppa, E et al. (2016) Evaluation of a digital food photography atlas used as portion size measurement aid in dietary surveys in Greece. Public Health Nutr 19, 23692376.
8. Amougou, N, Cohen, E, Mbala, ML et al. (2016) Development and validation of two food portion photograph books to assess dietary intake among adults and children in Central Africa. Br J Nutr 115, 895902.
9. Bouchoucha, M, Akrout, M, Bellali, H et al. (2016) Development and validation of a food photography manual, as a tool for estimation of food portion size in epidemiological dietary surveys in Tunisia. Libyan J Med 11, 32676.
10. Harris-Fry, H, Paudel, P, Karn, M et al. (2016) Development and validation of a photographic food atlas for portion size assessment in the southern plains of Nepal. Public Health Nutr 19, 24952507.
11. Huybregts, L, Roberfroid, D, Lachat, C et al. (2008) Validity of photographs for food portion estimation in a rural West African setting. Public Health Nutr 11, 581587.
12. Kirkpatrick, SI, Potischman, N, Dodd, KW et al. (2016) The use of digital images in 24-hour recalls may lead to less misestimation of portion size compared with traditional interviewer-administered recalls. J Nutr 146, 25672573.
13. Tueni, M, Mounayar, A & Birlouez-Aragon, I (2012) Development and evaluation of a photographic atlas as a tool for dietary assessment studies in Middle East cultures. Public Health Nutr 15, 10231028.
14. Venter, CS, MacIntyre, UE & Vorster, HH (2000) The development and testing of a food portion photograph book for use in an African population. J Hum Nutr Diet 13, 205218.
15. Subar, AF, Crafts, J, Zimmerman, TP et al. (2010) Assessment of the accuracy of portion size reports using computer-based food photographs aids in the development of an automated self-administered 24-hour recall. J Am Diet Assoc 110, 5564.
16. Baranowski, T, Baranowski, JC, Watson, KB et al. (2011) Children’s accuracy of portion size estimation using digital food images: effects of interface design and size of image on computer screen. Public Health Nutr 14, 418425.
17. Vereecken, C, Dohogne, S, Covents, M et al. (2010) How accurate are adolescents in portion-size estimation using the computer tool Young Adolescents’ Nutrition Assessment on Computer (YANA-C)? Br J Nutr 103, 18441850.
18. Choplin, JM & Motyka Joss, L (2012) Simultaneous and sequential comparisons of food quantity and consumption. Eat Behav 13, 310316.
19. Liu, Y, Chiu, S, Lin, Y et al. (2014) Pictogram-based method of visualizing dietary intake. Methods Inf Med 53, 493500.
20. National Statistical Office & ICF Macro (2011) Malawi Demographic and Health Survey, 2010. Zomba and Calverton, MD: NSO and ICF Macro.
21. Kuehneman, T, Stanek, K, Eskridge, K et al. (1994) Comparability of four methods for estimating portion sizes during a food frequency interview with caregivers of young children. J Am Diet Assoc 94, 548551.
22. Guest, G, Bunce, A & Johnson, L (2006) How many interviews are enough? An experiment with data saturation and variability. Field Methods 18, 5982.
23. Creswell, JW (2015) A Concise Introduction to Mixed Methods Research. Thousand Oaks, CA: SAGE Publications, Inc.
24. Hjertholm, KG, Iversen, PO, Holmboe-Ottesen, G et al. (2018) Maternal dietary intake during pregnancy and its association to birth size in rural Malawi: a cross-sectional study. Matern Child Nutr 14, e12433.
25. Godwin, SL, Chambers, ET & Cleveland, L (2004) Accuracy of reporting dietary intake using various portion-size aids in-person and via telephone. J Am Diet Assoc 104, 585594.
26. Gibbs, G (2007) Analyzing Qualitative Data. Thousand Oaks, CA: SAGE Publications, Inc.
27. Patton, MQ (1990) Qualitative Evaluation and Research Methods. Thousand Oaks, CA: SAGE Publications, Inc.
28. Miles, MB & Huberman, AM (1994) Qualitative Data Analysis: An Expanded Sourcebook, 2nd ed. Thousand Oaks, CA: SAGE Publications, Inc.
29. Turconi, G, Guarcello, M, Berzolari, FG et al. (2005) An evaluation of a colour food photography atlas as a tool for quantifying food portion size in epidemiological dietary surveys. Eur J Clin Nutr 59, 923931.
30. Godwin, S, Chambers, ET, Cleveland, L et al. (2006) A new portion size estimation aid for wedge-shaped foods. J Am Diet Assoc 106, 12461250.
31. Gibson, RS & Ferguson, EL (2008) An Interactive 24-hour Recall for Assessing the Adequacy of Iron and Zinc Intakes in Developing Countries. HarvestPlus Technical Monograph Series no. 8. Washington, DC: HarvestPlus.
32. Souverein, OW, de Boer, WJ, Geelen, A et al. (2011) Uncertainty in intake due to portion size estimation in 24-hour recalls varies between food groups. J Nutr 141, 13961401.
33. Faulkner, GP, Livingstone, MB, Pourshahidi, LK et al. (2016) An evaluation of portion size estimation aids: precision, ease of use and likelihood of future use. Public Health Nutr 19, 23772387.
34. Al Marzooqi, HM, Burke, SJ, Al Ghazali, MR et al. (2015) The development of a food atlas of portion sizes for the United Arab Emirates. J Food Compost Anal 43, 140148.
35. Bell, W, Colaiezzi, BA, Prata, CS et al. (2017) Scaling up dietary data for decision-making in low-income countries: new technological frontiers. Adv Nutr 8, 916932.
36. Flax, VL, Thakwalakwa, C, Schnefke, CH et al. (2019) Validation of a digitally displayed photographic food portion-size estimation aid among women in urban and rural Malawi. Public Health Nutr (In the Press).


Type Description Title
Supplementary materials

Schnefke et al. supplementary material
Schnefke et al. supplementary material 1

 Word (53 KB)
53 KB
Supplementary materials

Schnefke et al. supplementary material
Schnefke et al. supplementary material 2

 Word (15 KB)
15 KB
Supplementary materials

Schnefke et al. supplementary material
Schnefke et al. supplementary material 3

 Word (287 KB)
287 KB
Supplementary materials

Schnefke et al. supplementary material
Schnefke et al. supplementary material 4

 Word (16 KB)
16 KB


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed