Novel Sources of Data for Monitoring Food and Nutrition
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Novel sources of data for monitoring food and nutrition Novel sources of data are those that were not collected for statistical purposes and are not generally used for these purposes. This report explores novel sources of data that can be used to monitor food and nutrition, including market share data, purchase data, electronic payment data, location data, and app and wearable device data. It also provides some example analyses using purchase data, electronic payment data and location data. aihw.gov.au Stronger evidence, better decisions, improved health and welfare Novel sources of data for monitoring food and nutrition Australian Institute of Health and Welfare Canberra Cat. no. PHE 280 The Australian Institute of Health and Welfare is a major national agency whose purpose is to create authoritative and accessible information and statistics that inform decisions and improve the health and welfare of all Australians. © Australian Institute of Health and Welfare 2020 This product, excluding the AIHW logo, Commonwealth Coat of Arms and any material owned by a third party or protected by a trademark, has been released under a Creative Commons BY 3.0 (CC-BY 3.0) licence. Excluded material owned by third parties may include, for example, design and layout, images obtained under licence from third parties and signatures. We have made all reasonable efforts to identify and label material owned by third parties. You may distribute, remix and build upon this work. However, you must attribute the AIHW as the copyright holder of the work in compliance with our attribution policy available at <www.aihw.gov.au/copyright/>. The full terms and conditions of this licence are available at <http://creativecommons.org/licenses/by/3.0/au/>. A complete list of the Institute’s publications is available from the Institute’s website <www.aihw.gov.au>. ISBN 978-1-76054-767-7 (PDF) ISBN 978-1-76054-768-4 (Print) Suggested citation Australian Institute of Health and Welfare 2020. Novel sources of data for monitoring food and nutrition. Cat. no. PHE 280. Canberra: AIHW. Australian Institute of Health and Welfare Board Chair Chief Executive Officer Mrs Louise Markus Mr Barry Sandison Any enquiries relating to copyright or comments on this publication should be directed to: Australian Institute of Health and Welfare GPO Box 570 Canberra ACT 2601 Tel: (02) 6244 1000 Email: [email protected] This publication is printed in accordance with ISO 14001 (Environmental Management Systems) and ISO 9001 (Quality Management Systems). The paper is sourced from sustainably managed certified forests. Please note that there is the potential for minor revisions of data in this report. Please check the online version at <www.aihw.gov.au> for any amendments. Contents Summary ...............................................................................................................................v 1 Introduction ...................................................................................................................1 A food and nutrition monitoring framework ...................................................................... 1 Traditional data for food and nutrition monitoring ............................................................. 2 Food supply ...............................................................................................................2 Food purchasing and acquisition ............................................................................... 3 Food and physical activity behaviours ....................................................................... 4 Nutritional status ........................................................................................................5 Novel data for food and nutrition monitoring .................................................................... 6 This report .......................................................................................................................6 2 Market share data ..........................................................................................................7 Potential uses ..................................................................................................................7 Examples of use ........................................................................................................7 How could the findings be used? ..................................................................................... 8 Data quality .....................................................................................................................9 3 Purchase data .............................................................................................................. 10 Potential uses ................................................................................................................ 10 Examples of use ...................................................................................................... 11 How could the findings be used? ................................................................................... 13 Data quality ................................................................................................................... 13 4 Electronic payment data ............................................................................................. 15 Potential uses ................................................................................................................ 15 Examples of use ...................................................................................................... 16 How could the findings be used? ................................................................................... 16 Data quality ................................................................................................................... 16 5 Location data ............................................................................................................... 18 Potential uses ................................................................................................................ 18 Examples of use ...................................................................................................... 19 How could the findings be used? ................................................................................... 20 Data quality ................................................................................................................... 20 6 App and wearable device data .................................................................................... 21 Potential uses ................................................................................................................ 21 Examples of use ...................................................................................................... 21 iii How could the findings be used? ................................................................................... 22 Data quality ................................................................................................................... 23 7 Example analyses ........................................................................................................ 24 Example analysis 1: Purchase data ............................................................................... 26 General methods ..................................................................................................... 26 General considerations for interpretation of purchase data analysis ........................ 27 Example analysis: Energy purchased from discretionary foods ............................... 28 Example analysis: Acceptable macronutrient distribution ranges ............................. 29 Example analysis: Leading contributors to purchased energy, saturated fat and sodium ........................................................................................................... 30 Example analysis 2a: Electronic payment data .............................................................. 33 General methods ..................................................................................................... 33 General considerations for interpretation of electronic payment data ....................... 35 Example analysis: Average monthly spend on dining out ........................................ 37 Example analysis: Average monthly dining out transaction frequency ..................... 42 Example analysis: Average dining out transaction value .......................................... 48 Example analysis 2b: Electronic payment data .............................................................. 53 General methods ..................................................................................................... 53 General considerations for interpretation of electronic payment data ....................... 54 Example analysis: Average annual fast food spend ................................................. 55 Example analysis: Average annual fast food transaction frequency ......................... 58 Example analysis: Average fast food transaction spend .......................................... 61 Example analysis 3: Location data ................................................................................ 66 General methods ..................................................................................................... 66 General considerations for interpretation of location data analysis........................... 67 Example analysis: Density