Scaling up Dietary Data for Decision‐Making in Africa and Asia: New Technological Frontiers

Interventions and policies that seek to improve human health through diet or influence the effects of food systems on dietary outcomes require high quality data on the food and nutrient intake of individuals. Dietary surveys in low‐income countries generally rely on interviewer‐administered recalls using paper questionnaires and re‐develop food composition databases and other key components with each new survey. This approach is cumbersome, prone to error, and cost‐ and time‐prohibitive, resulting in a dearth of dietary information in many low‐income countries. As part of a multi‐year effort to scale up research architecture for dietary assessment in low‐income countries, this study investigates the suitability of emerging innovative dietary assessment technologies for developing countries in Africa and Asia. Seven types of technologies were reviewed: 1) personal digital assistants, 2) smartphone applications (“apps”), 3) active image‐based methods, 4) passive image‐based methods, 5) wearable devices, 6) scale‐based devices, and 7) handheld devices. A set of predefined search terms identified technologies from peer‐reviewed and recent gray literature, using PubMed and Google. Android apps were searched through the Google Play store. For each technology, available information was extracted about the a) primary purpose, b) terminal type, c) type of method, d) data input type, e) data processing, f) data output type and content, g) mode of administration, h) evidence of validity, i) financial and other required resources, j) appropriateness for low‐income countries (literacy, electricity, internet connectivity, technical capacity), k) additional strengths and weaknesses. None of the emergent technologies reviewed met all of the predefined criteria for suitability for use in large‐scale surveys in low‐income country contexts. Many of them are still under development in commercial laboratories and will require further assessment of their scientific validity and feasibility for population studies. Several emergent technologies showed potential, but not readiness, to alleviate the critical bottleneck of insufficient food composition data in low‐income countries. Interviewer‐administered, tablet‐based 24‐hour dietary recall platforms are in widespread use in industrialized countries but have not yet penetrated low‐income contexts. A standardized, yet adaptable assessment and processing platform tailored to low‐income contexts would be a feasible and scientifically defensible investment with potentially huge benefits for increasing dietary data availability. Along with the necessary research architecture, certain features of the more emergent technologies could be integrated into such a platform, including computer‐assisted personal interviewing (CAPI) features for enhanced respondent interaction ‐‐ possibly allowing for concurrent dietary counseling ‐‐and image recognition software to improve the accuracy of portion size estimation and food identification. Many of the user‐friendly features of smartphone apps could be integrated into this platform, to enhance the experience of the interviewers, interviewees, and those using the data. Support or Funding Information This research was conducted as part of the International Dietary Data Expansion (INDDEX) Project, which is made possible with funding from Tufts University's Gerald J. and Dorothy R. Friedman School of Nutrition Science and Policy, who received a grant from the Bill & Melinda Gates Foundation.