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Validation Information: Blue Mountains Eye Study (BMES) FFQ
Validity of carbohydrate, glycaemic index and glycaemic load data obtained using a semi-quantitative food-frequency questionnaire
Objective:To assess the ability of a food-frequency questionnaire (FFQ) to rank Australians according to their intake of total carbohydrate, sugar, starch, fibre, glycaemic index (GI) and glycaemic load (GL).
Design:Cross-sectional sample from a population cohort.
Setting:Two postcode areas west of Sydney, Australia.
Subjects:From 1992 to 1994, a total of 2868 older Australians provided dietary data using a 145-item Willett-derived FFQ. A representative sub-sample of 78 subjects completed three 4-day weighed food records (WFRs). Pearson and Spearman correlations, Bland–Altman plots and weighted kappa values were calculated.
Results:Compared with the WFR, the FFQ provided higher mean estimates of all nutrients except starch and GI. All Pearson and/or Spearman correlations were greater than 0.5, except for GL. For GI, sugar, starch and fibre, the regression lines from the Bland–Altman analysis indicated a non-significant linear trend (P50.07, P50.36, P50.28 and P50.10, respectively). For GL and total carbohydrate, however, there was a significant linear trend (P50.006 and P,0.0001, respectively), indicating that as the GL and carbohydrate intake of individuals increased, so did the magnitude of the error between the FFQ and WFR. Weighted kappa values all indicated moderate to good agreement, with the exception of GL which was only fair. The proportions of subjects correctly classified within one quintile for all of the nutrients were over 50% and gross misclassification was low (,10%).
Conclusion:This FFQ was able to rank individuals according to their intakes of total carbohydrate, sugar, starch, fibre and GI, but not as well for GL.
Total number of nutrients validated: 4
Not all of the nutrients validated in the validation studies are included in the table below, as statistical data was only selected to be displayed for a number of nutrients, this included:
- Saturated Fat
- Mono-unsaturated Fat
- Poly-unsaturated Fat
- Non‐starch polysaccharides(NSP)
- Folic Acid
- Vitamin B12
- Vitamin C
- Fruit & Vegetables
- Urinary Nitrogen
To find information on the other validated nutrients please read the validation study.
- Macronutrients: 4
- Micronutrients: 0
|Comparator||Lifestage||Sex||Nutrient Measured||Mean Difference||Standard Deviation||Correlation Coefficient||Cohen's Kappa Coefficient||Percentage Agreement||Percentage Agreement Categories||Lower Limits of Agreement||Upper Limits of Agreement|
|Weighed Food Diary||Adults, Elderly||Both||Carbohydrate (g)||14.8||N/C||0.43 (P); 0.44 (S)||0.43 (W)‡||39||5||-0.26‡||0.36‡|
|Total Sugar (g)||19.9||N/C||0.42 (P); 0.49 (S)||0.41 (W)‡||28||5||-0.41‡||0.72‡|
|Fibre (g)||5.2||N/C||0.52 (P); 0.59 (S)||0.73(W)‡||45.0||5||-0.35‡||0.66‡|
Some results have been calculated using statistical techniques based on the published data.
For further information on statistical terms click on Statistical tests used in validation studies
All correlations coefficients in the table are unadjusted unless stated otherwise. For adjusted correlation coefficients and other statistical methods used in the study e.g. paired t-tests, please read the validation articles.
- # Adjusted
- † Energy adjusted.
- ‡ For loge-transformed, energy-adjusted nutrient intakes.
- ^ Adjacent included.
- ᵟ Participants provided identical responses.
- (w) = Weighted.
Barclay AW, Flood VM, Brand-Miller JC, Mitchell P. Validity of carbohydrate, glycaemic index and glycaemic load data obtained using a semi-quantitative food-frequency questionnaire. Public health nutrition. 2008;11(6):573-80.