The possibilities of the use of N-of-1 and do-it-yourself trials in nutritional research.

BACKGROUND: N-of-1 designs gain popularity in nutritional research because of the improving technological possibilities, practical applicability and promise of increased accuracy and sensitivity, especially in the field of personalized nutrition. This move asks for a search of applicable statistical methods. OBJECTIVE: To demonstrate the differences of three popular statistical methods in analyzing treatment effects of data obtained in N-of-1 designs. METHOD: We compare Individual-participant data meta-analysis, frequentist and Bayesian linear mixed effect models using a simulation experiment. Furthermore, we demonstrate the merits of the Bayesian model including prior information by analyzing data of an empirical study on weight loss. RESULTS: The linear mixed effect models are to be preferred over the meta-analysis method, since the individual effects are estimated more accurately as evidenced by the lower errors, especially with lower sample sizes. Differences between Bayesian and frequentist mixed models were found to be small, indicating that they will lead to the same results without including an informative prior. CONCLUSION: For empirical data, the Bayesian mixed model allows the inclusion of prior knowledge and gives potential for population based and personalized inference.

Subjective feelings of appetite of wholegrain breakfasts evaluated under controlled, laboratory and 'at home' conditions.

BACKGROUND: Appetite regulating properties of foods are usually investigated under laboratory conditions, whereas in real life, foods are consumed under at home conditions. The objective of this study was to compare the acute effects of breakfasts when tested in a laboratory condition and in an at home condition. Appetite regulating properties of two bread breakfasts and two cereal breakfasts were also compared. SUBJECTS AND METHODS: In this randomized cross-over trial balanced for laboratory and at home test conditions, thirty-two women consumed five breakfasts, i.e. two bread breakfasts, two cereal breakfasts and one fried-egg breakfast. Visual analogue scales for measuring appetite were captured via an on-line scoring system and were analyzed as incremental area under the curve, as satiation phase and as satiety phase. RESULTS: Location effects were limited to two small effects only. An overall location effect in hunger feelings was observed (p = 0.040), which occurred specifically during the short satiation period (p = 0.0002) where hunger feelings scored higher under laboratory conditions. Similarly, a location effect was observed for desire to eat (p = 0.001); this was again higher under laboratory conditions. No other location effects were observed. Bread breakfasts did not differ in their appetite regulating properties. The Steel Cut oatmeal breakfast was reported to be more satiating (p = 0.001) as compared to the ready-to-eat cereal. CONCLUSIONS: Whereas the five breakfasts varied somewhat in their appetite regulating properties, evaluation under laboratory conditions overall did not result in different appetite scores compared to the at home conditions. This suggests that at home testing may be a useful alternative to laboratory test conditions for nutrition research.