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Validation of a digitally displayed photographic food portion size estimation aid among women in urban and rural Malawi
Flax, V., Thakwalakwa, C., Schnefke, C., Stobaugh, H., Phuka, J., Coates, J., Rogers, B., Bell, W., Colaiezzi, B., & Muth, M. (2019). Validation of a digitally displayed photographic food portion size estimation aid among women in urban and rural Malawi. Current Developments in Nutrition, 3(Suppl 1), Article P13-012-19. https://doi.org/10.1093/cdn/nzz036.P13-012-19
Objectives: Easy-to-use tools to facilitate portion size estimation in low-income countries are needed. The objective of this study was to validate digitally displayed photographic portion size estimation aids (PSEAs) against a weighed meal record and compare findings with an atlas of printed photographic PSEAs and actual prepared food PSEAs in a low-income country.
Methods: In Blantyre and Chikwawa Districts, Malawi, we enrolled 300 women 18-45 years of age equally divided by urban/rural residence and years of education (≤4 years and >4 years). Participants served themselves water and five prepared foods, which were weighed separately before the meal and again after the meal to measure any leftovers. Participants returned the following day and completed a meal recall. They estimated the quantities of foods consumed three times using the different PSEAs in a randomized order.
Results: Responses for digital and printed PSEAs were highly correlated (>91% agreement for all foods, Cohen's κ = 0.78-0.93). Overall, digital and actual-food PSEAs had a similar level of agreement with the weighed meal record at the group level. The proportion of participants who estimated within 20% of the weighed grams of food consumed ranged by type of food from 30-45% for digital PSEAs and 40-56% for actual food PSEAs. Digital PSEAs consistently underestimated grams and nutrients across foods, whereas actual-food PSEAs provided a mix of under- and overestimates that balanced each other to produce accurate mean energy and nutrient intake estimates. Results did not differ by urban and rural location or participant education level.
Conclusions: Digital PSEAs require further testing in low-income settings to improve accuracy of estimations because they offer several logistical advantages over other PSEAs.
