Evaluating the healthiness of chain-restaurant menu items using crowdsourcing
A new method
Bibliographic Data
| ID | 15097578 |
|---|---|
| Authors | Lenard I Lesser (0000-0002-0713-6707, corresponding author), Leslie Wu (0000-0001-9542-740X), Timothy B Matthiessen (Film Independent), Harold S Luft (0000-0002-4696-2745, University of California, San Francisco) |
| Year | 2017 |
| Volume | 20 |
| Issue | 1 |
| Pages | 18-24 |
| Publication date | 2017-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Health Nutrition (JOURNAL) |
| Journal identifiers | ISSN: 1368-9800 • E-ISSN: 1475-2727 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s1368980016001804 |
| PMID | 27406874 |
| OpenAlex | W2462123273 |
| Language | EN |
| Citations received | 2 |
| References cited | 16 |
Objective To develop a technology-based method for evaluating the nutritional quality of chain-restaurant menus to increase the efficiency and lower the cost of large-scale data analysis of food items. Design Using a Modified Nutrient Profiling Index (MNPI), we assessed chain-restaurant items from the MenuStat database with a process involving three steps: (i) testing ‘extreme’ scores; (ii) crowdsourcing to analyse fruit, nut and vegetable (FNV) amounts; and (iii) analysis of the ambiguous items by a registered dietitian. Results In applying the approach to assess 22 422 foods, only 3566 could not be scored automatically based on MenuStat data and required further evaluation to determine healthiness. Items for which there was low agreement between trusted crowd workers, or where the FNV amount was estimated to be >40 %, were sent to a registered dietitian. Crowdsourcing was able to evaluate 3199, leaving only 367 to be reviewed by the registered dietitian. Overall, 7 % of items were categorized as healthy. The healthiest category was soups (26 % healthy), while desserts were the least healthy (2 % healthy). Conclusions An algorithm incorporating crowdsourcing and a dietitian can quickly and efficiently analyse restaurant menus, allowing public health researchers to analyse the healthiness of menu items
Advertising · Business · Chain (unit · Crowdsourcing · World Wide Web · Computer Science · Consumer Attitudes and Food Labeling · Food Safety and Hygiene · Nutritional Studies and Diet
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,22 |
| Citation span | 2017 - 2019 (3) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |