Alyse Davies1, Virginia Chan2, Adrian Bauman3, Louise Signal4, Cameron Hosking5, Luke Gemming2, Margaret Allman-Farinelli2. 1. Nutrition and Dietetics Group, Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia. alyse.davies@sydney.edu.au. 2. Nutrition and Dietetics Group, Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia. 3. Prevention Research Centre, School of Public Health, The University of Sydney, Sydney, NSW, 2006, Australia. 4. Department of Public Health, Health Promotion & Policy Research Unit, University of Otago, Wellington South, PO Box 7343, Wellington, 6242, New Zealand. 5. Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia.
Abstract
PURPOSE: Young adults are vulnerable to weight gain and dietary behaviours such as 'eating on the run' are likely contributors. The objective of this study was to examine eating and drinking behaviours during transport journeys in a sample of young adults using wearable cameras that take continuous images every 30 s. METHODS: Seventy-eight 18-30 year olds wore an Autographer wearable camera for three consecutive days. Image coding schedules were designed to assess physical activity (included transportation) and diet. For the general description of data, frequency analysis was calculated as image number (percentage) and mean (± SD) or median (IQR) when appropriate. RESULTS: A total of 281,041 images were coded and 32,529 (14%) of images involved transport. The median (IQR) camera wear time was 8 h per day (7-9 h). The camera images identified 52 participants (67%) either eating or drinking during transport (excluding water). A total of 143 eating and drinking occasions were identified, averaging 3 occasions per person over the three study days. Fifty five (38%) eating episodes were identified by the camera images of which 27 (49%) were discretionary and 88 (62%) drinking episodes were identified of which (45%) were discretionary. CONCLUSION: This study confirms that transport is a potential setting for intervention. Young adults are consuming discretionary food and beverages during transport which may contribute to energy-dense diets and compromise diet quality. Substituting unhealthy with healthy food advertising and potentially prohibiting eating and drinking whilst on public transport is suggested.
PURPOSE: Young adults are vulnerable to weight gain and dietary behaviours such as 'eating on the run' are likely contributors. The objective of this study was to examine eating and drinking behaviours during transport journeys in a sample of young adults using wearable cameras that take continuous images every 30 s. METHODS: Seventy-eight 18-30 year olds wore an Autographer wearable camera for three consecutive days. Image coding schedules were designed to assess physical activity (included transportation) and diet. For the general description of data, frequency analysis was calculated as image number (percentage) and mean (± SD) or median (IQR) when appropriate. RESULTS: A total of 281,041 images were coded and 32,529 (14%) of images involved transport. The median (IQR) camera wear time was 8 h per day (7-9 h). The camera images identified 52 participants (67%) either eating or drinking during transport (excluding water). A total of 143 eating and drinking occasions were identified, averaging 3 occasions per person over the three study days. Fifty five (38%) eating episodes were identified by the camera images of which 27 (49%) were discretionary and 88 (62%) drinking episodes were identified of which (45%) were discretionary. CONCLUSION: This study confirms that transport is a potential setting for intervention. Young adults are consuming discretionary food and beverages during transport which may contribute to energy-dense diets and compromise diet quality. Substituting unhealthy with healthy food advertising and potentially prohibiting eating and drinking whilst on public transport is suggested.
Entities:
Keywords:
Dietary behaviours; Physical activity; Transportation; Wearable cameras; Young adults
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