Relative validation of the KiGGS Food Frequency Questionnaire among adolescents in Germany

Abstract

BackgroundThe aim of this study was to determine the relative validity of the self-administered Food Frequency Questionnaire (FFQ) "What do you eat?", which was used in the German National Health Interview and Examination Survey for Children and Adolescents (KiGGS 2003-2006).MethodsThe validation was conducted in the EsKiMo Nutrition Module, a subsample of KiGGS. The study population included 1,213 adolescents aged between 12 and 17. A modified diet history interview DISHES (Dietary Interview Software for Health Examination Studies) was used as the reference method. In order to compare the food groups, the data assessed with both instruments were aggregated to 40 similar food groups. The statistical analysis included calculating and comparing Spearman's correlation coefficients, calculating the mean difference between both methods, and ranking participants (quartiles) according to food group consumption, including weighted kappa coefficients. Correlations were also evaluated for relative body weight and socioeconomic status subgroups.ResultsIn the total study population the Spearman correlation coefficients ranged from 0.22 for pasta/rice to 0.69 for margarine; most values were 0.50 and higher. The mean difference ranged between 1.4% for milk and 100.3% for pasta/rice. The 2.5 percentiles and 97.5 percentiles indicated a wide range of differences. Classifications in the same and adjacent quartile varied between 70.1% for pasta/rice and 90.8% for coffee. For most groups, Cohen's weighted kappa showed values between 0.21 and 0.60. Only for white bread and pasta/rice were values less than 0.20. Most of the 40 food groups showed acceptable to good correlations in all investigated subgroups concerning age, sex, body weight and socio-economic status.ConclusionsThe KiGGS FFQ showed fair to moderate ranking validity except for pasta/rice and white bread. However, the ability to assess absolute intakes is limited. The correlation coefficients for most food items were similar for normal weight and overweight as well as for different socio-economic status groups. Overall, the results of the relative validity were comparable to FFQs from the current literature.

Development and validation of a food-based diet quality index for New Zealand adolescents

“…The main limitation of estimated records is the higher participant burden due to multiple-day recording which may discourage completion [60,61]. Despite careful preparation of the food record as an easy-to-carry booklet and provision of portion aids to facilitate accurate recordings, we acknowledge that misreporting may still occur given the limited motivation and possible poor portion size estimation among adolescents [62,63]. …”

Former Very Preterm Infants Show an Unfavorable Cardiovascular Risk Profile at a Preschool Age

“…A positive family history of CVD was defined as a diagnosis of coronary heart disease, angina, heart attack, congenital heart disease or stroke in first-degree male relative of child and/or parent under the age of 55 or first-degree female relative of child and/or parent under the age of 65 [11]. Information on childhood nutrition habits was gathered by means of an established standardized food frequency questionnaire (“What do you eat?”, kindly provided by the Robert Koch Institute, Berlin, Germany) [12]. Childhood nutrition was subsequently categorized as unfavorable, neutral or favorable for further analyses.…”

Associations between dietary patterns and biomarkers of nutrient status and cardiovascular risk factors among adolescents in Germany: results of the German Health Interview and Examination Survey for Children and Adolescents in Germany (KiGGS)

“…The development of the FFQ is described in detail elsewhere [35]. The FFQ was validated against the modified dietary history method DISHES (Dietary Interview Software for Health Examination Studies) and showed fair to moderate ranking validity for food intake amounts for most of the food items (Spearman correlation coefficients from .35 to .69 with most values above .50) [22]. The FFQ included questions on the average food consumption frequency, as well as the average consumed portion size, for 45 food items in the last few weeks.…”

“…This can be accomplished by investigating a priori-defined healthy eating indices, which are based on a judgement of appropriateness of the food intake. Previously, we analyzed the association between such dietary indices and biomarkers in the same population [22]. For the current study, we applied principal component analysis (PCA), which is a data driven method and results in patterns that more objectively represent prevailing eating habits of the population.…”