AdHealth:A feasibility study to measure digital food marketing to adolescents through Facebook

OBJECTIVE: To test the feasibility of a browser extension to estimate the exposure of adolescents to (un)healthy food and beverage advertisements on Facebook and the persuasive techniques used to market these foods and&nbsp;beverages. DESIGN: A Chrome browser extension (AdHealth) was developed to automatically collect advertisements seen by participants on their personal Facebook accounts. Information was extracted and sent to a web server by parsing the Document Object Model tree representation of Facebook web pages. Key information retrieved included the advertisement type seen and duration of each ad sighting. The WHO-Europe Nutrient Profile Model was used to classify the healthiness of products advertised as permitted (healthy) or not permitted (unhealthy) to be advertised to&nbsp;children. SETTING: Auckland, New&nbsp;Zealand. PARTICIPANTS: Thirty-four Facebook users aged 16-18&nbsp;years. RESULTS: The browser extension retrieved 4973 advertisements from thirty-four participants, of which 204 (4 %) were food-related, accounting for 1·1 % of the exposure duration. Of those food advertisements, 98 % were classified as not permitted, and 33·7 and 31·9 %, respectively, of those featured promotional characters or premium offers. The mean rate of exposure to not permitted food was 4·8 (sd = 2·5) advertisements per hour spent on&nbsp;Facebook. CONCLUSIONS: Using a Chrome extension to monitor exposure to unhealthy food and beverage advertisements showed that the vast majority of advertisements were for unhealthy products, despite numerous challenges to implementation. Further efforts are needed to develop tools for use across other social media platforms and mobile devices, and policies to protect young people from digital food&nbsp;advertising.</p

\u27Traffic-light\u27 nutrition labelling and \u27junk-food\u27 tax : a modelled comparison of cost-effectiveness for obesity prevention

Introduction: Cost-effectiveness analyses are important tools in efforts to prioritise interventions for obesity prevention.Modelling facilitates evaluation of multiple scenarios with varying assumptions. This study compares the cost-effectiveness ofconservative scenarios for two commonly proposed policy-based interventions: front-of-pack &lsquo;traffic-light&rsquo; nutrition labelling(traffic-light labelling) and a tax on unhealthy foods (&lsquo;junk-food&rsquo; tax).Methods: For traffic-light labelling, estimates of changes in energy intake were based on an assumed 10% shift in consumptiontowards healthier options in four food categories (breakfast cereals, pastries, sausages and preprepared meals) in 10% of adults. For the &lsquo;junk-food&rsquo; tax, price elasticities were used to estimate a change in energy intake in response to a 10% price increase in seven food categories (including soft drinks, confectionery and snack foods). Changes in population weight and body mass index by sex were then estimated based on these changes in population energy intake, along with subsequent impacts on disability-adjusted life years (DALYs). Associated resource use was measured and costed using pathway analysis, based on a health sector perspective (with some industry costs included). Costs and health outcomes were discounted at 3%. The cost-effectiveness of each intervention was modelled for the 2003 Australian adult population.Results: Both interventions resulted in reduced mean weight (traffic-light labelling: 1.3 kg (95% uncertainty interval (UI): 1.2;1.4); &lsquo;junk-food&rsquo; tax: 1.6 kg (95% UI: 1.5; 1.7)); and DALYs averted (traffic-light labelling: 45 100 (95% UI: 37 700; 60 100);&lsquo;junk-food&rsquo; tax: 559 000 (95% UI: 459 500; 676 000)). Cost outlays were AUD81 million (95% UI: 44.7; 108.0) for traffic-lightlabelling and AUD18 million (95% UI: 14.4; 21.6) for &lsquo;junk-food&rsquo; tax. Cost-effectiveness analysis showed both interventions were&lsquo;dominant&rsquo; (effective and cost-saving).Conclusion: Policy-based population-wide interventions such as traffic-light nutrition labelling and taxes on unhealthy foods arelikely to offer excellent &lsquo;value for money&rsquo; as obesity prevention measures.<br /

The cost-effectiveness of removing television advertising of high-fat and/or high-sugar food and beverages to Australian children

Objective: To model the health benefits and cost-effectiveness of banning television (TV) advertisements in Australia for energy-dense, nutrient-poor food and beverages during children\u27s peak viewing times.Methods: Benefits were modelled as changes in body mass index (BMI) and disability-adjusted life years (DALYs) saved. Intervention costs (AUD$) were compared with future health-care cost offsets from reduced prevalence of obesity-related health conditions. Changes in BMI were assumed to be maintained through to adulthood. The comparator was current practice, the reference year was 2001, and the discount rate for costs and benefits was 3$ 3.70 (95% uncertainty interval (UI) $2.40,$7.70) per DALY. Total DALYs saved were 37 000 (95% UI 16 000, 59 000). When the present value of potential savings in future health-care costs was considered (AUD$300m (95$130m, $480m), the intervention was \u27dominant\u27, because it resulted in both a health gain and a cost offset compared with current practice.Conclusions: Although recognizing the limitations of the available evidence, restricting TV food advertising to children would be one of the most cost-effective population-based interventions available to governments today. Despite its economic credentials from a public health perspective, the initiative is strongly opposed by food and advertising industries and is under review by the current Australian government.<br /