Online food delivery (OFD) platforms have changed how consumers purchase food prepared outside of home by capitalising on convenience and smartphone technology. Independent food outlets encompass a substantial proportion of partnering outlets, but their offerings’ nutritional quality is understudied. Little is also known as to how OFD platforms influence consumer choice. This study evaluated the nutritional quality and marketing attributes of offerings from independent takeaway outlets available on Sydney’s market-leading OFD platform (UberEats^®). Complete menus and marketing attributes from 202 popular outlets were collected using web scraping. All 13841 menu items were classified into 38 food and beverage categories based on the Australian Dietary Guidelines. Of complete menus, 80.5% (11,139/13,841) were discretionary and 42.3% (5849/13,841) were discretionary cereal-based mixed meals, the largest of the 38 categories. Discretionary menu items were more likely to be categorised as most popular (OR: 2.5, 95% CI 1.9–3.2), accompanied by an image (OR: 1.3, 95% CI 1.2–1.5) and offered as a value bundle (OR: 6.5, 95% CI 4.8–8.9). Two of the three discretionary food categories were more expensive than their healthier Five Food Group counterparts (p < 0.02). The ubiquity of discretionary choices offered by independent takeaways and the marketing attributes employed by OFD platforms has implications for public health policy. Further research on the contribution of discretionary choices and marketing attributes to nutritional intakes is warranted.

For artificial intelligence (AI) to support nutrition care, high quality and accuracy of its features within smartphone applications (apps) are essential. This study evaluated popular apps’ features, quality, behaviour change potential, and comparative validity of dietary assessment via manual logging and AI. The top 200 free and paid nutrition-related apps from Australia’s Apple App and Google Play stores were screened (n = 800). Apps were assessed using MARS (quality) and ABACUS (behaviour change potential). Nutritional outputs from manual food logging and AI-enabled food-image recognition apps were compared with food records for Western, Asian, and Recommended diets. Among 18 apps, Noom scored highest on MARS (mean = 4.44) and ABACUS (21/21). From 16 manual food-logging apps, energy was overestimated for Western (mean: 1040 kJ) but underestimated for Asian (mean: −1520 kJ) diets. MyFitnessPal and Fastic had the highest accuracy (97% and 92%, respectively) out of seven AI-enabled food image recognition apps. Apps with more AI integration demonstrated better functionality, but automatic energy estimations from AI-enabled food image recognition were inaccurate. To enhance the integration of apps into nutrition care, collaborating with dietitians is essential for improving their credibility and comparative validity by expanding food databases. Moreover, training AI models are needed to improve AI-enabled food recognition, especially for mixed dishes and culturally diverse foods.

Online food delivery (OFD) platforms have become increasingly popular due to advanced technology, which is changing the way consumers purchase food prepared outside of the home. There is limited research investigating the healthiness of the digital food environment and its influence on consumer choice and dietary behaviours. This study is the first to examine the nutritional quality and marketing attributes of menu items from popular independent and franchise restaurants and takeaway outlets on New Zealand’s market leading OFD platform (UberEATS^®). A total of 374 popular independent and franchise restaurants and takeaway outlets were identified to form a database of complete menus and marketing attributes. All 25,877 menu items were classified into 38 food and beverage categories based on the Australian Dietary Guidelines. Of complete menus, 73.3% (18,955/25,877) were discretionary. Thirty-six percent (9419/25,877) were discretionary cereal-based mixed meals, the largest of the 38 categories. Discretionary menu items were more likely to be categorized as most popular (OR: 2.0, 95% CI 1.7–2.2), accompanied by a photo (OR: 1.7, 95% CI 1.6–1.8), and offered as a value bundle (OR: 4.6, 95% CI 3.2–6.8). Two of the three discretionary mixed meal categories were significantly less expensive than their healthier counterparts (p < 0.001). The overwhelming availability and promotion of discretionary choices offered by restaurants and takeaway outlets on OFD platforms have implications for public health policy. Further research to explore direct associations between nutritional quality and consumers’ dietary choices is required.

Growing social media use in young adults may have applications in health promotion. This study aimed to determine the acceptability and feasibility of using Instagram to disseminate nutritional information to young Australians and assess the most preferred post style. A cross-sectional web-based pilot survey was conducted in 18–30-year-olds residing in New South Wales. Eight sets of mock Instagram posts were generated comprising three formats: (i) text/icon, (ii) realistic image, or (iii) video. Respondents (n = 108) were asked to review and rank posts from highest to lowest according to likelihood of engagement, visual preference, motivation to change eating behaviors, and relevancy of information. The Friedman test (Wilcoxon signed-rank test post hoc analysis with Bonferroni correction) was conducted to determine differences between the three post styles. Video style posts were more likely to be engaged with (p < 0.001), visually preferred (p < 0.001), more motivating to change eating behaviors (p < 0.001), and presented the most relevant food and nutrition knowledge (p < 0.001) compared with the other post styles. Most participants reported that Instagram was a suitable platform to share food and nutrition information (96%). The findings of this pilot study can be used to inform a large study that investigates the use of Instagram among a more diverse population and with a greater number of video posts tailored for audience segmentation.

Technology-enhanced methods of dietary assessment may still face common limitations of self-report. This study aimed to assess foods and beverages omitted when both a 24 h recall and a smartphone app were used to assess dietary intake compared with camera images. For three consecutive days, young adults (18–30 years) wore an Autographer camera that took point-of-view images every 30 seconds. Over the same period, participants reported their diet in the app and completed daily 24 h recalls. Camera images were reviewed for food and beverages, then matched to the items reported in the 24 h recall and app. ANOVA (with post hoc analysis using Tukey Honest Significant Difference) and paired t-test were conducted. Discretionary snacks were frequently omitted by both methods (p < 0.001). Water was omitted more frequently in the app than in the camera images (p < 0.001) and 24 h recall (p < 0.001). Dairy and alternatives (p = 0.001), sugar-based products (p = 0.007), savoury sauces and condiments (p < 0.001), fats and oils (p < 0.001) and alcohol (p = 0.002) were more frequently omitted in the app than in the 24 h recall. The use of traditional self-report methods of assessing diet remains problematic even with the addition of technology and finding new objective methods that are not intrusive and are of low burden to participants remains a challenge.