Statistical modelling of usual intake

Design aspects of 24 h recall assessments may affect the estimates of protein and potassium intake in dietary surveys

Objective

To evaluate the impact of different modes of administration (face-to-face v. telephone), recall days (first v. second), days of the week (weekday v. weekend) and interview days (1 d later v. 2 d later) on bias in protein and K intakes collected with 24 h dietary recalls (24-HDR).

Design

Two non-consecutive 24-HDR (collected with standardised EPIC-Soft software) were used to estimate protein and K intakes by a face-to-face interview at the research centres and a telephone interview, and included all days of the week. Two 24 h urine collections were used to determine biomarkers of protein and K intake. The bias in intake was defined as the ratio between the 24-HDR estimate and the biomarker.

Setting

Five centres in Belgium, Czech Republic, France, the Netherlands and Norway in the European Food Consumption Validation (EFCOVAL) study.

Subjects

About 120 adults (aged 45–65 years) per centre.

Results

The bias in protein intake in the Czech Republic and Norway was smaller for telephone than face-to-face interviews (P = 0·01). The second 24-HDR estimates of protein intake in France and K intake in Belgium had a larger bias than the first 24-HDR (P = 0·01 and 0·04, respectively). In the Czech Republic, protein intake estimated during weekends and K intake estimated during weekdays had a larger bias than during other days of the week (P = 0·01). In addition, K intake collected 2 d later in the Czech Republic was likely to be overestimated.

Conclusions

The biases in protein and K intakes were comparable between modes of administration, recall days, days of the week and interview days in some, but not all, study centres.

Uncertainty in intake due to portion size estimation in 24-hour recalls varies between food groups

Portion size estimation is expected to be one of the largest sources of uncertainty in dietary assessment of the individual. Therefore, we demonstrated a method to quantify uncertainty due to portion size estimation in the usual intake distributions of vegetables, fruit, bread, protein, and potassium. Dutch participants of the European Food Consumption Validation study completed 2 nonconsecutive 24-h recall interviews. In short, the uncertainty analysis consists of Monte Carlo simulations drawing values for portion size from lognormal uncertainty distributions. The uncertainty of the usual intake distribution and accompanying parameters (IQR and the shrinkage factor) were estimated. For the food groups, portion size uncertainty had the greatest effect for vegetables and the least for fruit: the relative 95% uncertainty interval (UI) of the IQR of the usual intake distribution was 0.61-1.35 for vegetables, 0.77-1.24 for bread, and 0.99-1.10 for fruit. For protein and potassium, the resulting relative width of the UI of the IQR for portion size uncertainty are similar: 0.88-1.14 for protein and 0.86-1.14 for potassium. Furthermore, a sensitivity analysis illustrated the importance of the specified uncertainty distributions. The examples show that uncertainty in portion sizes may be more important for some foods such as vegetables. This may reflect differential quantification errors by food groups that deserve further consideration. In conclusion, the presented methodology allows the important quantification of portion size uncertainty and extensions to include other sources of uncertainty is straightforward.