JMIR Publications

ABSTRACT

Background:

Hand transcribing nutrient composition data from websites requires extensive human resources and is prone to error. As a result, there are limited nutrient composition data on food prepared out-of-home in the UK. Such data are crucial for understanding and monitoring the out-of-home food environment, which aids policymaking. Automated data collection from publicly available sources offers a potential low-resource solution to address this gap.

Objective:

In this paper, we describe the first UK longitudinal nutritional database of food prepared out-of-home, MenuTracker. As large chains will be required to display calorie information on their UK menus from April 2022, we also aimed to identify which chains reported their nutritional information online in November 2021. In a case study to demonstrate the utility of MenuTracker, we estimated the proportions of menu items exceeding recommended energy and nutrient intake (e.g., >600 kcal per meal).

Methods:

We have collated nutritional composition data of menu items sold by large chain restaurants quarterly since March 2021. Large chains were defined as those with 250 employees or more (those covered by the new calorie labelling policy) or belonging to the top 100 restaurants based on sales volume. We developed scripts in Python to automate the data collection process from business websites. Various techniques were used to harvest web data and extract data from nutritional tables in PDF format.

Results:

Automated Python programs reduced approximately 85% of manual work, totalling 500 hours saved for each wave of data collection. As of January 2022, MenuTracker has 76,405 records from 88 large out-of-home food chains at four different time points (i.e., March, June, September, and December) in 2021. In constructing the database, we found that a quarter (24.5%) of large chains, which are likely to be subject to the UK’s calorie menu labelling regulations, provided their nutritional information online in November 2021. Across these chains, 24.7% of menu items exceeded the UK government’s recommendation of a maximum of 600 kcal for a single meal. Comparable figures were 46.4% for saturated fat, 34.7% for total fat, 17.6% for carbohydrates, 17.8% for sugar, and 35.2% for salt. Furthermore, 0.7%-7.1% of the menu items exceeded the maximum daily recommended intake for these nutrients.

Conclusions:

MenuTracker is a valuable resource that harnesses the power of data science techniques to utilise publicly available data online. Researchers, policymakers, and consumers can use MenuTracker to understand and assess foods available from restaurants. The methods employed in development are available online and can be used to establish similar databases elsewhere.