| Literature DB >> 32235580 |
Charlene Elliott1, Emily Truman1.
Abstract
Child-targeted food marketing is a significant public health concern, prompting calls for its regulation. Product packaging is a powerful form of food marketing aimed at children, yet no published studies examine the range of literature on the topic or the "power" of its marketing techniques. This study attempts such a task. Providing a systematic scoping review of the literature on child-targeted food packaging, we assesses the nutritional profile of these foods, the types of foods examined, and the creative strategies used to attract children. Fifty-seven full text articles were reviewed. Results identify high level trends in methodological approaches (content analysis, 38%), outcomes measured (exposure, 44%) and with respect to age. Studies examining the nutritional profile of child-targeted packaged foods use various models, classifying from anywhere from 41% to 97% of products as unhealthy. Content analyses track the prevalence of child-targeted techniques (cartoon characters as the most frequently measured), while other studies assess their effectiveness. Overall, this scoping review offers important insights into the differences between techniques tracked and those measured for effectiveness in existing literature, and identifies gaps for future research around the question of persuasive power-particularly when it comes to children's age and the specific types of techniques examined.Entities:
Keywords: childhood obesity; children; exposure; food marketing; food packaging; marketing techniques; nutrition; power; youth
Mesh:
Year: 2020 PMID: 32235580 PMCID: PMC7230356 DOI: 10.3390/nu12040958
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1Literature search flow chart.
Summary of main characteristics of included studies (n = 57).
| Methods | Object of Study | Child Population Age Ranges | Outcomes Measured * |
|---|---|---|---|
| Content Analysis (22) | Physical Food Packaging (42) | Between 2-12 years (24) | Exposure (25) |
* some studies measure more than one outcome.
Content analyses that use nutrient profiling criteria (n = 21) and key findings.
| Study | Criteria Used | Product Sample Size | Food Types Analyzed | Key Findings on Nutritional Profile of Sample | Most Prevalent Food Type in Sample |
|---|---|---|---|---|---|
| Chapman et al., 2006 [ | New South Wales (NSW) Healthy School Canteen Strategy (NSW Dept. of Health and NSW Dept. of Education and Training) & CHOICE magazine (Australian Consumers Association) | 231 | Sweet biscuits, snack foods, confectionery, chips/savoury snacks, cereals, dairy snacks, ice cream | 82% of promotions used to sell unhealthy foods | Confectionery (35% of sample) |
| Elliott, 2008 [ | Center for Science in the Public Interest (CSPI) criteria for ‘Poor Nutritional Quality’ (PNQ) | 367 | Dry goods (i.e., cereals, fruit snacks, drinks), meat, dairy, refrigerated and frozen, beverages, produce | 89% of products are poor nutritional quality | Dry goods (61% of sample) |
| Elliott, 2008 [ | Center for Science in the Public Interest (CSPI) criteria for ‘Poor Nutritional Quality’ (PNQ) | 367 | Dry goods, dairy, produce, refrigerated and frozen foods | 89% of products are poor nutritional quality | Dry goods (61% of sample) |
| Page et al., 2008 [ | Nutrition info (grams of sugar per serving, calories per serving, percent calories from sugar) | 122 | Ready-to-eat cereals | Mean % of calories from sugar: 34% | Not applicable (entire sample is cereal only) |
| Harris et al., 2010 [ | Institute of Medicine (IOM) Nutrition Standards for Foods in Schools guidelines (US) | 397 | Cereal, fruit snack, meal products, frozen desserts, candy, cookies, other breakfast products, yoghurt and yoghurt drinks, crackers, juice and juice drinks, savoury snacks, fruit and vegetables, other | 18.4% of products classified as healthy | Cereal (19% of sample) |
| Hebden et al., 2011 [ | Food Standards Australia and New Zealand (FSANZ) Nutrient Profiling Scoring Criterion | 352 | Chocolate, confectionery, high sugar/high fat spreads, yogurt, cheese, milk, snack food, breakfast cereals, noodles, ice cream, iced confection, sweet and savoury baked goods, sugar-sweetened beverages, powdered flavour additives, canned and frozen meals, fruit and vegetables products, meat/poultry/fish/eggs | 74% of products were less healthy | Chocolate & confectionary (36% of sample) |
| Bragg et al., 2012 [ | Nutrient Profiling Model (UK) | 102 | Beverages, snacks, cereal, dessert, condiments, bread, dairy, meat | 88.7% of food products were unhealthy | Beverages (48% of sample) |
| Elliott, 2012 [ | Center for Science in the Public Interest (CSPI) criteria for ‘Poor Nutritional Quality’ (PNQ) * | 354 | Dry goods, dairy, produce, frozen food | 91% of “regular” child-oriented products have high levels of sugar, fat or sodium | Dry goods (63% of sample) |
| Elliott, 2012 [ | American Heart Association recommendations on sugar | 354 | Dry goods, dairy, produce, frozen/refrigerated foods | 73% of foods derive over 20% of their calories from sugar | Dry goods (67% of sample) |
| Mehta et al., 2012 [ | Australian Guide to Healthy Eating | 157 | Core products (canned/packaged meals, meat and meat alternatives, fruits and fruit products, vegetables and vegetable products, breads/cereal/rice/pasta/noodles, dairy, water), Non-core products (chocolate and confectionery, cakes/muffins/biscuits/pies/pastries, snack foods, fast-food restaurant meals, soft drinks, ice cream and iced confection, sugary breakfast cereals, fruit juice and fruit drinks, frozen/fried potato products, baby and toddler food) | 75% of products are non-core foods | Confectionery and chocolate (27% of sample) |
| Chacon et al., 2013 [ | Nutrient Profiling Model (UK) | 69 | Savory snacks, pastries and cookies, sweetened beverages (i.e., fruit drinks, energy drinks, sports drinks), soft drinks, dairy products, cereals, ice cream and frozen desserts, light soft drinks, fruit and vegetable snacks or water. | 97.1% of food products were unhealthy | Pastries & cookies (37.5% of sample) |
| Devi et al., 2014 [ | Food Standards Australia and New Zealand (FSANZ) Nutrient Profiling Scoring Criterion | 247 | Breakfast cereals | Kid’s cereal had lower serving size, higher sugar and energy content compared to other cereals | Not applicable (entire sample is cereal only) |
| Giménez et al., 2017 [ | Pan American Health Organization Nutrient Profile Model | 180 | Candy and chocolate, cookies and pastries, dairy products, breakfast cereals, instant foods, soft drinks and juices, savory snacks, frozen ready-to-eat foods, other (meat product, fruit puree, mayonnaise) | 97% of products are ultra-processed | Candy and chocolate (25% of sample) |
| Mediano Stolze et al., 2018 [ | Nutrition info (total sugars and energy recorded, tax status also recorded–Chilean law: 18% tax if >6.25 g of sugar, 10% tax if < 6.25 g of sugar) | 1005 | Beverages | 42% of beverages fall into 10% tax rate (moderate sugar, less than or equal to 6.25 mg/100 mL); | Fruit-flavoured drinks (29% of sample) |
| Pulker et al., 2018 [ | NOVA System | 230 | Breakfast cereals, snacks and confectionery items, selected beverages, condiments, liquid breakfast meal replacements | 94% of products are ultra-processed | Not provided |
| Soo et al., 2018 [ | Nutrient Profiling Model (UK) | 106 | Breakfast cereals | NPI mean score for cereals is 10.5 (less healthy) | Not applicable (sample is cereal only) |
| Aerts & Smits, 2019 [ | Nutrient Profiling Model (UK) | 372 | Savoury spreads, dairy products, chocolate, cacao powder, cereals, soft candy, cookies, cereal bars, sweet spreads, pasta, ice cream, potato products, fish sticks, crisps, hard candy | 89.2% of food products were unhealthy | Candy (18% of sample) |
| Chen et al., 2019 [ | WHO recommendations on sugar, saturated fatty acid | 607 | Snacks (cookies, breads, RTE cereals, puddings or jellies), Drinks (fruit/vegetable drinks, flavoured milks, fermented milks, soy and rice milks, milk teas). | 80% of snacks high in sugar, 54% high in fat | Cookies (29% of sample) |
| Elliott, 2019 [ | Center for Science in the Public Interest (CSPI) criteria for ‘Poor Nutritional Quality’ (PNQ) & WHO REGIONAL OFFICE FOR EUROPE model | 354/374 | Dairy, dry goods, produce, meat, refrigerated and frozen foods, beverages | 88.7% of products are poorly nutritious in 2009 | Dry goods (64% of sample) |
| García et al., 2019 [ | OFCOM Nutrient Profiling Model | 332 | Ready-to-eat cereals, cereal bars, fruit juices, juice drinks, smoothies, dairy and dairy alternatives, ready meals, fruit snacks | 41% of products are less healthy | Dairy and dairy alternatives (23% of sample) |
| Mediano Stolze et al., 2019 [ | Nutrition info (sugars, fats, sodium, energy–“high-in”–exceeds 2016 Chilean nutrient thresholds–vs. “non high-in”) | 168/146 | Spanish Language Breakfast Cereals | 79% of products pre-implementation are high-in | Not provided |
* This study also uses the American Heart Association recommendations.
Figure 2Frequency of child-targeted food packaging indicators tracked by content analyses (n = 22).
Figure 3Frequency of child-targeted food packaging indicators examined in studies other than content analyses (n = 35).
Summary of findings comparing most prevalent techniques with most effective techniques.
| Most Prevalent Packaging Techniques in Content Analyses (n = 21) | Most Effective Packaging Techniques in All Other Studies (n = 23) |
|---|---|