Evidence map›Paper›PMID 27406874›Full record

ArticlePublic health nutrition2017

Evaluating the healthiness of chain-restaurant menu items using crowdsourcing: a new method.

Lenard I Lesser, Leslie Wu, Timothy B Matthiessen, Harold S Luft

Erratum issuedAbstract read
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Article in Public health nutrition, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Lenard I Lesser1One Medical Group,130 Sutter Street, Floor 2, San Francisco, CA 94104,USA.
Leslie Wu1One Medical Group,130 Sutter Street, Floor 2, San Francisco, CA 94104,USA.
Timothy B Matthiessen2Independent Dietitian,Oakland, CA,USA.
Harold S Luft1One Medical Group,130 Sutter Street, Floor 2, San Francisco, CA 94104,USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo 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.

designUsing 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.

resultsIn 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).

conclusionsAn algorithm incorporating crowdsourcing and a dietitian can quickly and efficiently analyse restaurant menus, allowing public health researchers to analyse the healthiness of menu items.

Indexed as

CrowdsourcingDiet, HealthyFood QualityRestaurantsFruitHumansMenu PlanningNutritionistsPilot ProjectsPublic HealthVegetablesComputer scienceMethodsNutritional analysisRestaurant food

Identifiers

PMID27406874
PMCPMC10261592

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.