Prevalence and socio-demographic predictors of dietary goal attainment in an older population.
OBJECTIVE
To describe the measured dietary intakes and anthropometry of a large, free-living population of middle-aged and older Australians who participated in the Australian Blue Mountains Eye Study (BMES), and to identify the socio-demographic characteristics associated with attainment or non-attainment of dietary goals.


METHODS
Anthropometry and dietary intakes were compared with current population dietary goals and Recommended Dietary Intakes for 2,873 people (79% of eligible residents) aged > or = 49 years who participated in the BMES. Nutrient intakes were measured by a validated food frequency questionnaire.


RESULTS
Nutrients for which mean intakes deviated most from nutrition goals included: percentages of energy from total and saturated fat, carbohydrate and alcohol (men), as well as absolute intakes of calcium, zinc and fibre. More than half the men (60%) and women (54%) were overweight or obese. Several micro-nutrient goals were more likely to be met in households where the respondents and/or their spouses were independent. Married men were more likely to meet goals for fibre and iron, but less likely to meet the goal for cholesterol. Several goals were more likely to be met by men and women who had qualifications after leaving school, those with higher job status and non-pensioners, suggesting an socio-economic status dimension.


CONCLUSIONS
These results indicate that over- rather than under-nutrition is more prevalent among community-dwelling older people, although under-nutrition should not be overlooked. Particular sub-groups that are less likely to meet some dietary goals may require targeting in community nutrition interventions.
Webb
K L
KL
Department of Public Health and Community Medicine, University of Sydney, Westmead Hospital, New South Wales. karenw@cmed.wh.su.edu.au
Schofield
W N
WN
Lazarus
R
R
Smith
W
W
Mitchell
P
P
Leeder
S R
SR
D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D000886:Anthropometry; D001315:Australia; D004032:Diet / Q000592:standards* / Q000639:trends; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys; D009752:Nutritional Status; D011237:Predictive Value of Tests; D015995:Prevalence; D017678:Sex Distribution; D012959:Socioeconomic Factors