Vietnam has successfully reduced population stunting, but ethnic minority groups are being systematically left behind, limiting progress on national reductions. This mixed methods study aims to understand how policy drivers of stunting reduction differ between ethnic majority and minority communities. We used decomposition analysis to explain key determinants of stunting change between 2000 and 2010; and framework analysis to qualitatively assess changes in policy, actors and narratives that have underpinned these over decades. Our analysis shows that stunting reductions are associated with increased household wealth (accounting for 61% of change), improved access to specific health services (16%), and changes in level of maternal education (12%). Despite multiple actors involved in change and a large set of policies designed to address inequities, many among Vietnam’s defined ethnic minority groups are not finding themselves able to effectively engage with central government plans for their communities, and central policies often do not consider their preferences or limitations. This in turn impacts the nutrition of minority groups through the determinants above. Vietnam has achieved the easier portion of stunting reduction through national economic growth and sustained commitment to socially-oriented policy. In order to tackle the remaining pockets of high malnutrition, more attention, thought and funding will need to focus on marginalised ethnic minority communities. The current national development discourse aims to incorporate minorities into mainstream majority systems. This paper argues that policy should rather take into account their particular needs and preferences to address and overcome the identified determinants of malnutrition.

Background Adolescents’ consumption of healthy foods is suboptimal in low- and middle-income countries. Adolescents’ fondness for games and social media and the increasing access to smartphones make apps suitable for collecting dietary data and influencing their food choices. Little is known about how adolescents use phones to track and shape their food choices. Objective This study aimed to examine the acceptability, usability, and likability of a mobile phone app prototype developed to collect dietary data using artificial intelligence–based image recognition of foods, provide feedback, and motivate users to make healthier food choices. The findings were used to improve the design of the app. Methods A total of 4 focus group discussions (n=32 girls, aged 15-17 years) were conducted in Vietnam. Qualitative data were collected and analyzed by grouping ideas into common themes based on content analysis and ground theory. Results Adolescents accepted most of the individual- and team-based dietary goals presented in the app prototype to help them make healthier food choices. They deemed the overall app wireframes, interface, and graphic design as acceptable, likable, and usable but suggested the following modifications: tailored feedback based on users’ medical history, anthropometric characteristics, and fitness goals; new language on dietary goals; provision of information about each of the food group dietary goals; wider camera frame to fit the whole family food tray, as meals are shared in Vietnam; possibility of digitally separating food consumption on shared meals; and more appealing graphic design, including unique badge designs for each food group. Participants also liked the app’s feedback on food choices in the form of badges, notifications, and statistics. A new version of the app was designed incorporating adolescent’s feedback to improve its acceptability, usability, and likability. Conclusions A phone app prototype designed to track food choice and help adolescent girls from low- and middle-income countries make healthier food choices was found to be acceptable, likable, and usable. Further research is needed to examine the feasibility of using this technology at scale.

Background There is a gap in data on dietary intake of adolescents in low- and middle-income countries. Traditional methods for dietary assessment are resource intensive and lack accuracy with regards to portion size estimation. Technology assisted dietary assessment tools have been proposed but few have been validated for feasibility of use in LMICs. Objectives We assess the relative validity of FRANI (Food Recognition Assistance and Nudging Insights), a mobile Artificial Intelligence (AI) application for dietary assessment in adolescent females (n = 36) aged 12–18y in Vietnam, against weighed records (WR) standard, and compared FRANI performance to a multi-pass 24-hour recall (24HR). Methods Dietary intake was assessed using 3 methods: FRANI, WRs and 24HRs undertaken on three non-consecutive days. Equivalence of nutrient intakes was tested using mixed effect models adjusting for repeated measures, using 10%, 15% and 20% bounds. The concordance correlation coefficient (CCC) was used to assess the agreement between methods. Sources of errors were identified for memory and portion size estimation bias. Results Equivalence between FRANI app and WR was determined at the 10% bound for energy, protein and fat and four nutrients (iron, riboflavin, vitamin B6 and zinc), and at 15% and 20% bounds for carbohydrate, calcium, vitamin C, thiamin, niacin, and folate. Similar results were observed for differences between 24HR and WR with 20% equivalent bound for all nutrients except for vitamin A. The CCCs between FRANI and WR (0.60,0.81) were slightly lower CCCs between 24HR and WR (0.70,0.89) for energy and most nutrients. Memory error (food omissions or intrusions) was ∼21% with no clear pattern apparent on portion size estimation bias for foods. Conclusions AI assisted dietary assessment and 24HR accurately estimate nutrient intake in adolescent females when compared to WR. Errors could be reduced with further improvements of AI-assisted food recognition and portion estimation.

Unhealthy eating habits are common among adolescents in Vietnam, where transitioning food environments increasingly offer energy‐dense micronutrient‐poor foods. Successful behavior change approaches must be feasible and acceptable, promoting local foods that are available, accessible, and preferred. Yet, few studies have investigated the potential of food‐based approaches for adolescents. We used linear programming to identify problem nutrients, local nutrient sources, and realistic food‐based recommendations (FBRs) to improve nutrient intake among girls 16–22 years in Thai Nguyen, Vietnam. We then identified a reduced set of FBRs to prioritize the most critical micronutrient gaps. Calcium and iron targets could not be met in any realistic diet modeling scenario. The best set of FBRs included seven recommendations which could meet intake targets for 9 of 11 modeled micronutrients. The best reduced set of three FBRs targeting iron and calcium only—although more feasible for behavior change—was less effective at improving intake of these nutrients since fewer foods were recommended. Given the difficulty of meeting calcium and iron targets using local foods within acceptable dietary patterns, additional interventions, such as supplementation, staple food fortification, or increasing the availability of affordable calcium‐ and iron‐rich foods, may be necessary to promote dietary adequacy for adolescent girls.

Unhealthy diets are a critical global concern while dietary measure methods are time consuming and expensive. There is limited evidence that phone-based interventions can improve nutrition data collection and dietary quality, especially for adolescents in developing countries. We developed an artificial-intelligence-based phone application called Food Recognition Assistance and Nudging Insights (FRANI) to address these problems. FRANI can recognize foods in images, track food consumption, display statistics and use gamified nudges to give positive feedback on healthy food choice. This study protocol describes the design of new pilot studies aimed at measuring the feasibility (acceptability, adherence, and usability) of FRANI and its effects on the quality of food choice of adolescents in Ghana and Vietnam. In each country, 36 adolescents (12–18 years) will be randomly allocated into two groups: The intervention group with the full version of FRANI and the control group with the functionality limited to image recognition and dietary assessment. Participants in both groups will have their food choices tracked for four weeks. The control groups will then switch to the full version of FRANI and both groups will be tracked for a further 2 weeks to assess acceptability, adherence, and usability. Analysis of outcomes will be by intent to treat and differences in outcomes between intervention and control group will use Poisson and odds ratio regression models, accounting for repeated measures at individual levels. If deemed feasible, acceptable and usable, FRANI will address gaps in the literature and advance the nutrition field by potentially improving the quality of food choices of adolescent girls in developing countries. This pilot study will also provide insights on the design of a large randomized controlled trial. The functioning and dissemination of FRANI can be an important step towards highly scalable nutrition data collection and healthier food choices for a population at risk of malnutrition.The study protocol and the methods and materials were approved by the Institutional Review Board (IRB) of the IFPRI on April 29th, 2020 (registration number #00007490), the Thai Nguyen National Hospital on April 14th, 2020 (protocol code 274/ĐĐĐ-BVTWTN) and the University of Ghana on August 10th, 2020 (Federalwide Assurance FWA 00001824; NMIMR-IRB CPN 078–19/20). The study protocol was registered in the International Standard Randomized Controlled Trial Number (ISRCTN 10681553; https://doi.org/10.1186/ISRCTN10681553) on November 12, 2021.