An analysis of food and beverage advertising on bus shelters in a deprived area of Northern England

Objective: To quantify the extent of food and beverage advertising on bus shelters in a deprived area of the UK, to identify the healthfulness of advertised products, and any differences by level of deprivation. The study also sought to assess the creative strategies used and extent of appeal to young people. Design: Images of bus shelter advertisements were collected via in person photography (in 2019) and Google Street View (photos recorded in 2018). Food and beverage advertisements were grouped into one of seventeen food categories and classified as healthy/less healthy using the UK Nutrient Profile Model. The deprivation level of the advertisement location was identified using the UK Index of Multiple Deprivation. Setting: Middlesbrough and Redcar and Cleveland in South Teesside. Participants: N/A Results: 832 advertisements were identified, almost half (48.9%) of which were for foods or beverages. Of food and non-alcoholic beverage adverts, 35.1% were less healthy. Most food advertisements (98.9%) used at least one of the persuasive creative strategies. Food advertisements were found to be of appeal to children under 18 years (71.9%). No differences in healthiness of advertised foods were found by level of deprivation. Conclusions: Food advertising is extensive on bus shelters in parts of the UK, and a substantial proportion of this advertising is classified as less healthy and would not be permitted to be advertised around television programming for children. Bus shelter advertising should be considered part of the UK policy deliberations around restricting less healthy food marketing exposure.

Advertising patterns of a fast-food chain on social media in Brazil

Objective: To investigate the advertising patterns on the posts of a fast-food chain in Brazil on three social media platforms in 2019. Design: An exploratory cross-sectional study. Setting: Advertising strategies on the posts of a major fast-food chain on their official Facebook, Instagram, and YouTube accounts. The strategies were investigated according to the INFORMAS protocol for food promotion monitoring. Principal component analysis (PCA) was employed to identify advertising patterns in each platform. Participants: 305 advertisements Results: Four advertising patterns were identified in the PCA of Facebook and Instagram. In both platforms, the components for kids and product exaltation were similar. On Facebook, a pattern corresponding to economic appeal was identified as price and discount, while on Instagram, this pattern also included a practical approach. On Facebook, the fourth component was named celebrity, while on Instagram it was celebrity/innovation since on this second social media the component also included the ‘new brand development’ variable. On YouTube, three advertising patterns were identified in PCA. Similar to the other platforms, the first and the second patterns were called for kids and price and discount, and the third component referred to both celebrity and commemorative dates. Conclusions: The advertising patterns of the fast-food chain on three social media platforms were commonly directed to children and addressed price, discounts, and the celebrities’ universe. The findings of this study corroborate other data in the literature regarding unhealthy food advertising on social media. This study discusses the urgency of regulating food advertising content on this medium.

Impact of a voluntary industry code for advertising food to children and young people: an analysis of New Zealand television data

Objective: To evaluate the impact of the 2017 update to the voluntary Advertising Standards Authority (ASA) Code for Advertising Food on children and young people’s exposure to unhealthy food advertisements on New Zealand television. Design: Audience ratings data were analysed for New Zealand children and young people’s television viewing for eight random days prior to (June to August 2015) and following (October to December 2018) the code update, from 6.00am-midnight (864 hours). Food advertisements were coded using three nutrient profiling models. The number of children and young people watching television each year were compared. Setting: Three free-to-air New Zealand television channels. Participants: New Zealand children aged 5-18 years. Results: Television viewer numbers decreased over the three years (P<0.0001). The mean rate of unhealthy food advertising on weekdays was 10.4 advertisements/hour (2015) and 9.5 advertisements/hour (2018). Corresponding rates for weekend days were 8.1 and 7.3 advertisements/hour, respectively. The percentage of food advertisements which were for unhealthy foods remained high (63.7% on weekdays and 65.9% on weekends) in 2018. The ASA definition of children’s ‘peak viewing time’ (when 25% of the audience are children) did not correspond to any broadcast times across weekdays and weekend days. Conclusions: Between 2015 and 2018, children and young people’s television exposure to unhealthy food advertising decreased. However, almost two-thirds of all food advertisements were still unhealthy, and the updated ASA code excluded the times when the greatest number of children were watching television. Consequently, government regulation and regular monitoring should reflect the evolving food marketing environment.

A CNN-Based Advertisement Recommendation through Real-Time User Face Recognition

The advertising market’s use of smartphones and kiosks for non-face-to-face ordering is growing. An advertising video recommender system is needed that continuously shows advertising videos that match a user’s taste and displays other advertising videos quickly for unwanted advertisements. However, it is difficult to make a recommender system to identify users’ dynamic preferences in real time. In this study, we propose an advertising video recommendation procedure based on computer vision and deep learning, which uses changes in users’ facial expressions captured at every moment. Facial expressions represent a user’s emotions toward advertisements. We can utilize facial expressions to find a user’s dynamic preferences. For such a purpose, a CNN-based prediction model was developed to predict ratings, and a SIFT algorithm-based similarity model was developed to search for users with similar preferences in real time. To evaluate the proposed recommendation procedure, we experimented with food advertising videos. The experimental results show that the proposed procedure is superior to benchmark systems such as a random recommendation, an average rating approach, and a typical collaborative filtering approach in recommending advertising videos to both existing users and new users. From these results, we conclude that facial expressions are a critical factor for advertising video recommendations and are helpful in properly addressing the new user problem in existing recommender systems.

Prevalence and Correlates of US Adult Public Opinion on Restricting Junk Food Advertising to Children on Social Media: 2020 Health Information National Trends Survey

Objective: To describe US adults’ levels of support, neutrality, and opposition to restricting junk food advertising to children on social media and explore associations with sociodemographic and health-related characteristics. Design: In 2020-2021, we used cross-sectional data from the National Cancer Institute’s 2020 Health Information National Trends Survey to estimate the prevalence of opinions toward advertising restrictions, and correlates of neutrality and opposition using weighted multivariable logistic regression. Setting: United States. Participants: Adults aged 18+ years. Results: Among the analytic sample (n=2852), 54% of adults were neutral or opposed to junk food advertising restrictions on social media. The odds of being neutral or opposed were higher among Non-Hispanic Black adults (vs non-Hispanic White; OR: 2.03 (95% CI: 1.26, 3.26)); those completing some college (OR: 1.68 (95% CI: 1.20, 2.34)) or high school or less (OR: 2.62 (95% CI: 1.74, 3.96)) (vs those with a college degree); those who were overweight (vs normal weight; OR: 1.42 (95% CI: 1.05, 1.93)); and those reporting a moderate (OR: 1.45 (95% CI: 1.13, 1.88)) or conservative (OR: 1.71 (95% CI: 1.24, 2.35)) political viewpoint (vs liberal). Having strong (vs weaker) weight and diet-related cancer beliefs was associated with 53% lower odds of being neutral or opposed to advertising restrictions (OR: 0.47 (95% CI: 0.36, 0.61)). Conclusions: This study identified subgroups of US adults for whom targeted communication strategies may increase support for policies to improve children’s food environment.