Beverage Availability and Price: Variations by Neighborhood Poverty Level in New York City.

Objective: To describe the variability in the availability and price of sugary drinks, low-calorie drinks, and water/seltzer across high- and low-poverty census tracts in the five boroughs of New York City (NYC). Design: Cross-sectional study. Our primary analysis compared the overall sample of beverages. Secondary analyses included tests for differences in the availability of beverage categories by neighborhood poverty level. Setting: We collected data from 106 stores (31 supermarkets, 29 convenience stores, 29 pharmacies, 9 Targets, and 8 Dollar Trees) in NYC. Fifty-four stores were located in high-poverty census tracts and 52 were located in low-poverty census tracts. Results: The mean Price per 0.03-liter of sugary drinks across the sample was $0.08, which was significantly higher than the price of low-calorie drinks ($0.07, p=0.01) but not different from water/seltzer ($0.08, p=0.65). Sugary drinks and water/seltzer were available in 91% of retailers, and low-calorie drinks were available in 87% of retailers. There was no statistical difference in availability of sugary drinks compared with low-calorie drinks or water/seltzer overall or within high- or low-poverty census tracts. Analyzed by store type, the mean price per ounce of sugary drinks differed significantly from water/seltzer at convenience stores, pharmacies, and Target stores (bodegas: $0.08 vs. $0.09, p=0.03; pharmacies: $0.11 vs. $0.08, p=0.02; Target stores: $0.07 vs. $0.09, p=0.01). Conclusions: Sugary drinks were available in most food retail settings in NYC, with little variation by census tract poverty level. Interventions that raise the price of sugary drinks to make healthier alternatives, such as water, the more affordable option should be considered.

Brands with personalities - good for businesses, but bad for public health? A content analysis of how food and beverage brands personify themselves on Twitter.

OBJECTIVE: To examine the extent to which food and beverage brands exhibit personalities on Twitter, quantify Twitter users' engagement with posts displaying personality features and determine advertising spending across these brands on Twitter. DESIGN: We identified 100 tweets from 10 food and beverage brands that displayed a 'personality', and 100 'control' tweets (i.e. a post by that brand on the same day). Our codebook quantified the following personification strategies: (1) humour; (2) trendy language and (3) absence of food product mentions. We used media articles to quantify other personification strategies: (4) referencing trending topics; (5) referencing current events; (6) referencing internet memes and (7) targeting niche audiences. We calculated brands' number of tweets, re-tweets, 'likes', and comments and report the relationship between advertising spending and retweets per follower. SETTING: Twitter posts. PARTICIPANTS: Ten food and beverage brands that were described in media articles (e.g. Forbes) as having distinct personalities. RESULTS: Personality tweets earned 123 013 retweets, 732 076 'likes' and 14 806 comments, whereas control tweets earned 61 044 retweets, 256 105 'likes' and 14 572 comments. The strategies used most included humour (n 81), trendy language (n 80) and trending topics (n 47). The three brands that spent the most on advertising had similar or fewer retweets per follower than the four that spent relatively little on advertising. CONCLUSIONS: Some food and beverage brands have distinct 'personalities' on Twitter that generate millions of 'likes' and retweets. Some retweets have an inverse relationship with advertising spending, suggesting 'personalities' may be a uniquely powerful advertising tool for targeting young adults.

A Qualitative Analysis of Black and White Adolescents' Perceptions of and Responses to Racially Targeted Food and Drink Commercials on Television.

Food and beverage marketing is a major driver of childhood obesity, and companies target their least nutritious products to Black youth. However, little is known about adolescents' perceptions of and responses to racially targeted food marketing. In this qualitative study, we investigated how Black and White adolescents perceived and responded to racially targeted television commercials for food and beverages. We recruited 39 adolescents aged 12-17 years in New York City to watch a series of commercials and then participate in an in-depth interview using a semi-structured interview guide. The research team recorded, transcribed, and analyzed interviews using ATLAS.ti. Overall, participants responded positively to commercials that featured celebrities. They were also able to recognize the commercials and reported they had been exposed to marketing from these companies on social media and in subways/buses. Many participants considered the advertised brands as healthy or able to enhance athletic performance because of their endorsement by or association with athletes. Participants also understood that marketers were using racial targeting in their ads but that targeting did not translate into improved perceptions or responses towards advertised products. These findings suggest the need to empirically evaluate and further explore Black and White adolescents' responses to racially targeted food marketing.

How Food Marketing on Instagram Shapes Adolescents' Food Preferences: Online Randomized Trial.

BACKGROUND: Worldwide obesity rates have prompted 16 countries to enact policies to reduce children's exposure to unhealthy food marketing, but few policies address online advertising practices or protect adolescents from being targeted. Given adolescents spend so much time online, it is critical to understand how persuasive Instagram food advertisements (ads) are compared with traditional food ads. To strengthen online food marketing policies, more evidence is needed on whether social media ads are more persuasive than other types of ads in shaping adolescents' preferences. OBJECTIVE: This study examined whether adolescents could identify food companies' Instagram posts as ads, and the extent to which Instagram versus traditional food ads shape adolescents' preferences. METHODS: In Part 1, participants aged 13-17 years (N=832) viewed 8 pairs of ads and were asked to identify which ads originated from Instagram. One ad in each pair was selected from traditional sources (eg, print; online banner ad), and the other ad was selected from Instagram, but we removed the Instagram frame-which includes the logo, comments, and "likes." In Part 2, participants were randomized to rate food ads that ostensibly originated from (1) Instagram (ie, we photoshopped the Instagram frame onto ads); or (2) traditional sources. Unbeknownst to participants, half of the ads in their condition originated from Instagram and half originated from traditional sources. RESULTS: In Part 1, adolescents performed worse than chance when asked to identify Instagram ads (P<.001). In Part 2, there were no differences on 4 of 5 outcomes in the "labeled ad condition." In the "unlabeled ad condition," however, they preferred Instagram ads to traditional ads on 3 of 5 outcomes (ie, trendiness, P=.001; artistic appeal, P=.001; likeability, P=.001). CONCLUSIONS: Adolescents incorrectly identified traditional ads as Instagram posts, suggesting the artistic appearance of social media ads may not be perceived as marketing. Further, the mere presence of Instagram features caused adolescents to rate food ads more positively than ads without Instagram features.

Understanding the Extent of Adolescents' Willingness to Engage With Food and Beverage Companies' Instagram Accounts: Experimental Survey Study.

BACKGROUND: Social media platforms have created a new advertising frontier, yet little is known about the extent to which this interactive form of advertising shapes adolescents' online relationships with unhealthy food brands. OBJECTIVE: We aimed to understand the extent to which adolescents' preferences for Instagram food ads are shaped by the presence of comments and varying numbers of "likes." We hypothesized that adolescents would show the highest preferences for ads with more "likes" and comments. We predicted that these differences would be greater among adolescents who were "heavy social media users" (ie, >3 hours daily) vs "light social media users" (ie, <3 hours daily). METHODS: We recruited Black and non-Latinx White adolescents (aged 13-17 years; N=832) from Dynata, a firm that maintains online participant panels. Participants completed an online survey in which they were randomized to view and rate Instagram food ads that either did or did not show comments. Within each condition, adolescents were randomized to view 4 images that had high (>10,000), medium (1000-10,000), or low (<100) numbers of "likes." Adolescents reported ad preferences and willingness to engage with the brand. RESULTS: Adolescents rated ads with medium or high numbers of "likes" higher than ads with few "likes" (P=.001 and P=.002, respectively). Heavy social media users (>3 hours/day) were 6.366 times more willing to comment on ads compared to light users (P<.001). CONCLUSIONS: Adolescents interact with brands in ways that mimic interactions with friends on social media, which is concerning when brands promote unhealthy products. Adolescents also preferred ads with many "likes," demonstrating the power of social norms in shaping behavior. As proposed in 2019, the Children's Online Privacy and Protection Act should expand online advertising restrictions to include adolescents aged 12 to 16 years.

Child Social Media Influencers and Unhealthy Food Product Placement.

OBJECTIVES: We aimed to determine the frequency with which kid influencers promote branded and unbranded food and drinks during their YouTube videos and assess the nutritional quality of food and drinks shown. METHODS: Researchers used Socialbakers data to identify the 5 most-watched kid influencers (ages 3 to 14 years) on YouTube in 2019. We searched for 50 of their most-watched videos and 50 of their videos that featured food and/or drinks on the thumbnail image of the video. We coded whether kid influencers consumed or played with food or toys, quantified the number of minutes food and/or drinks appeared, and recorded names of branded food and/or drinks. We assessed the nutritional quality of foods using the Nutrient Profile Model and identified the number of drinks with added sugar. RESULTS: A sample of 418 YouTube videos met the search criteria, and 179 of those videos featured food and/or drinks. Food and/or drinks were featured in those videos 291 times. Kid influencers' YouTube videos were collectively viewed >48 billion times, and videos featuring food and/or drinks were viewed 1 billion times. Most food and/or drinks were unhealthy branded items (n = 263; 90.34%; eg, McDonald's), followed by unhealthy unbranded items (n = 12; 4.1%; eg, hot dogs), healthy unbranded items (n = 9; 3.1%; eg, fruit), and healthy branded items (n = 7; 2.4%; eg, Yoplait yogurt). CONCLUSIONS: Kid influencers generate millions of impressions for unhealthy food and drink brands through product placement. The Federal Trade Commission should strengthen regulations regarding product placement on YouTube videos featuring young children.