Longitudinal change in food habits between adolescence (11–12 years) and adulthood (32–33 years): the ASH30 Study

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Abstract
Background Links between diet in childhood and the prevention of disease in adulthood have been established. This longitudinal dietary survey provided quantitative evidence of dietary change from adolescence to adulthood, in Northumberland, England. Objective To report longitudinal dietary change in 198 respondents between the ages of 12 and 33 years, to explore dietary ‘tracking’ between the same time points and to describe the effects of gender, socio-economic status and location on dietary change. Methods A longitudinal study recorded dietary change from adolescence to adulthood. Two 3-day food diaries were collected in 1980 and 2000 from the same 198 respondents. Foods consumed were assigned to the five categories in the Balance of Good Health (BGH). Demographic and socio-economic information were obtained in 1980 and 2000. Results Intakes of foods containing fat and/ or sugar and milk and dairy foods decreased (p < 0.01 and p < 0.031, respectively), while intakes of fruits and vegetables increased (p < 0.01). Intakes of bread, other cereals and potatoes (p = 0.002, r = +0.219); fruits and vegetables (p < 0.01, r = +0.256) and meat, fish and alternatives (p = 0.026, r = +0.158) ‘tracked’ from adolescence to adulthood. Men had increased intake from meat, fish and alternatives and decreased milk and dairy foods more than female respondents (p = 0.003 and p = 0.019). Respondents who had moved away from Northumberland had a greater increase in intake of fruits and vegetables compared with those who remained in the local (p = 0.010). Individuals who had moved to a lower socio-economic group had increased their intake of bread, other cereals and potatoes (p = 0.040). Conclusion Food intake changed considerably in a direction more in the line with current dietary recommendations. Food intake in adolescence was a significant, but not strong, predictor of intake in adulthood. Dietary change is influenced by variables including gender, location and socio-economic status.

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