Face Validity of Observed Meal Patterns Reported with 7-Day Diet Diaries in a Large Population-Based Cohort Using Diurnal Variation in Concentration Biomarkers of Dietary Intake.
Nutrients 2021 ; 14: .
Lentjes MAH, Oude Griep LM, Mulligan AA, Montgomery S, Wareham NJ, Khaw KT
DOI : 10.3390/nu14020238
PubMed ID : 35057419
PMCID : PMC8780432
URL : https://www.mdpi.com/2072-6643/14/2/238
In a cross-sectional analysis of a population-based cohort (United Kingdom, = 21,318, 1993-1998), we studied how associations between meal patterns and non-fasting triglyceride and glucose concentrations were influenced by the hour of day at which the blood sample was collected to ascertain face validity of reported meal patterns, as well as the influence of reporting bias (assessed using formula of energy expenditure) on this association. Meal size (i.e., reported energy content), mealtime and meal frequency were reported using pre-structured 7-day diet diaries. In ANCOVA, sex-specific means of biomarker concentrations were calculated by hour of blood sample collection for quartiles of reported energy intake at breakfast, lunch and dinner (meal size). Significant interactions were observed between breakfast size, sampling time and triglyceride concentrations and between lunch size, sampling time and triglyceride, as well as glucose concentrations. Those skipping breakfast had the lowest triglyceride concentrations in the morning and those skipping lunch had the lowest triglyceride and glucose concentrations in the afternoon, especially among acceptable energy reporters. Eating and drinking occasion frequency was weakly associated with glucose concentrations in women and positively associated with triglyceride concentrations in both sexes; stronger associations were observed for larger vs. smaller meals and among acceptable energy reporters. Associations between meal patterns and concentration biomarkers can be observed when accounting for diurnal variation and underreporting. These findings support the use of 7-day diet diaries for studying associations between meal patterns and health.