OBJECTIVE: To identify key predictors of fast-food consumption from a range of demographic, attitudinal, personality and lifestyle variables. METHODS: We analysed data from a nationwide survey (n = 20 527) conducted in Australia by Nielsen Media Research. Items assessing frequency of fast-food consumption at (1) eat in and (2) take away were regressed onto 12 demographic, seven media consumption, and 23 psychological and lifestyle variables, the latter derived from factor analysis of responses to 107 attitudinal and behavioural items. RESULTS: Stepwise multiple regression analyses explained 29.6% of the variance for frequency of take-away and 9.6% of the variance for frequency of eat-in consumption of fast foods. Predictors of more frequent consumption of fast food at take away (and, to a lesser extent, eat in) included lower age - especially under 45 years, relative indifference to health consequences of behaviour, greater household income, more exposure to advertising, greater receptiveness to advertising, lesser allocation of time for eating, and greater allocation of time to home entertainment. There were no effects for occupational status or education level. CONCLUSIONS: The effects for age suggest that fast-food take-away consumption is associated with a general cultural shift in eating practices; individual differences in attitudinal and lifestyle characteristics constitute additional, cumulative, predictive factors. The role of advertising and the reasons for the lesser explanatory value of the eat-in models are important targets for further research.
OBJECTIVE: To identify key predictors of fast-food consumption from a range of demographic, attitudinal, personality and lifestyle variables. METHODS: We analysed data from a nationwide survey (n = 20 527) conducted in Australia by Nielsen Media Research. Items assessing frequency of fast-food consumption at (1) eat in and (2) take away were regressed onto 12 demographic, seven media consumption, and 23 psychological and lifestyle variables, the latter derived from factor analysis of responses to 107 attitudinal and behavioural items. RESULTS: Stepwise multiple regression analyses explained 29.6% of the variance for frequency of take-away and 9.6% of the variance for frequency of eat-in consumption of fast foods. Predictors of more frequent consumption of fast food at take away (and, to a lesser extent, eat in) included lower age - especially under 45 years, relative indifference to health consequences of behaviour, greater household income, more exposure to advertising, greater receptiveness to advertising, lesser allocation of time for eating, and greater allocation of time to home entertainment. There were no effects for occupational status or education level. CONCLUSIONS: The effects for age suggest that fast-food take-away consumption is associated with a general cultural shift in eating practices; individual differences in attitudinal and lifestyle characteristics constitute additional, cumulative, predictive factors. The role of advertising and the reasons for the lesser explanatory value of the eat-in models are important targets for further research.
Authors: Alyse Davies; Virginia Chan; Adrian Bauman; Louise Signal; Cameron Hosking; Luke Gemming; Margaret Allman-Farinelli Journal: Eur J Nutr Date: 2020-09-04 Impact factor: 5.614
Authors: Lorna K Fraser; Kimberly L Edwards; Janet Cade; Graham P Clarke Journal: Int J Environ Res Public Health Date: 2010-05-06 Impact factor: 3.390
Authors: Lyndal Wellard-Cole; Jisu Jung; Judy Kay; Anna Rangan; Kathy Chapman; Wendy L Watson; Clare Hughes; Cliona Ni Mhurchu; Adrian Bauman; Luke Gemming; Kalina Yacef; Irena Koprinska; Margaret Allman-Farinelli Journal: JMIR Res Protoc Date: 2018-01-26
Authors: Thaisa M Cantu-Jungles; Lacey A McCormack; James E Slaven; Maribeth Slebodnik; Heather A Eicher-Miller Journal: Nutrients Date: 2017-09-30 Impact factor: 5.717