Bias in protein and potassium intake collected with 24-h recalls (EPIC-Soft) is rather comparable across European populations

Purpose: We investigated whether group-level bias of a 24-h recall estimate of protein and potassium intake, as compared to biomarkers, varied across European centers and whether this was influenced by characteristics of individuals or centers. Methods: The combined data from EFCOVAL and EPIC studies included 14 centers from 9 countries (n = 1,841). Dietary data were collected using a computerized 24-h recall (EPIC-Soft). Nitrogen and potassium in 24-h urine collections were used as reference method. Multilevel linear regression analysis was performed, including individual-level (e.g., BMI) and center-level (e.g., food pattern index) variables. Results: For protein intake, no between-center variation in bias was observed in men while it was 5.7% in women. For potassium intake, the between-center variation in bias was 8.9% in men and null in women. BMI was an important factor influencing the biases across centers (p <0.01 in all analyses). In addition, mode of administration (p = 0.06 in women) and day of the week (p = 0.03 in men and p = 0.06 in women) may have influenced the bias in protein intake across centers. After inclusion of these individual variables, between-center variation in bias in protein intake disappeared for women, whereas for potassium, it increased slightly in men (to 9.5%). Center-level variables did not influence the results. Conclusion: The results suggest that group-level bias in protein and potassium (for women) collected with 24-h recalls does not vary across centers and to a certain extent varies for potassium in men. BMI and study design aspects, rather than center-level characteristics, affected the biases across center

Risk of hyperkalemia in patients with moderate chronic kidney disease initiating angiotensin converting enzyme inhibitors or angiotensin receptor blockers : a randomized study

Background: Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers are renoprotective but both may increase serum potassium concentrations in patients with chronic kidney disease (CKD). The proportion of affected patients, the optimum follow-up period and whether there are differences between drugs in the development of this complication remain to be scertained. Methods: In a randomized, double-blind, phase IV, controlled, crossover study we recruited 30 patients with stage 3 CKD under restrictive eligibility criteria and strict dietary control. With the exception of withdrawals, each patient was treated with olmesartan and enalapril separately for 3 months each, with a 1-week wash-out period between treatments. Patients were clinically assessed on 10 occasions via measurements of serum and urine samples. We used the Cochran-Mantel-Haenszel statistics for comparison of categorical data between groups. Comparisons were also made using independent two-sample t-tests and Welch's t-test. Analysis of variance (ANOVA) was performed when necessary. We used either a Mann-Whitney or Kruskal-Wallis test if the distribution was not normal or the variance not homogeneous. Results: Enalapril and olmesartan increased serum potassium levels similarly (0.3 mmol/L and 0.24 mmol/L respectively). The percentage of patients presenting hyperkalemia higher than 5 mmol/L did not differ between treatments: 37% for olmesartan and 40% for enalapril. The mean e-GFR ranged 46.3 to 48.59 ml/mint/1.73 m2 in those treated with olmesartan and 46.8 to 48.3 ml/mint/1.73 m2 in those with enalapril and remained unchanged at the end of the study. The decreases in microalbuminuria were also similar (23% in olmesartan and 29% in enalapril patients) in the 4 weeks time point. The percentage of patients presenting hyperkalemia, even after a two month period, did not differ between treatments. There were no appreciable changes in sodium and potassium urinary excretion. Conclusions: Disturbances in potassium balance upon treatment with either olmesartan or enalapril are frequent and without differences between groups. The follow-up of these patients should include control of potassium levels, at least after the first week and the first and second month after initiating treatment

Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology

Introduction: The use of innovative technologies is deemed to improve dietary assessment in various research settings. However, their relative merits in nutritional epidemiological studies, which require accurate quantitative estimates of the usual intake at individual level, still need to be evaluated. Objective: To report on the inventory of available innovative technologies for dietary assessment and to critically evaluate their strengths and weaknesses as compared with the conventional methodologies (i.e. Food Frequency Questionnaires, food records, 24-hour dietary recalls) used in epidemiological studies. Methods: A list of currently available technologies was identified from English-language journals, using PubMed and Web of Science. The search criteria were principally based on the date of publication (between 1995 and 2011) and pre-defined search keywords. Results: Six main groups of innovative technologies were identified ('Personal Digital Assistant-', 'Mobile-phone-', 'Interactive computer-', 'Web-', 'Camera- and tape-recorder-' and 'Scan- and sensor-based' technologies). Compared with the conventional food records, Personal Digital Assistant and mobile phone devices seem to improve the recording through the possibility for 'real-time' recording at eating events, but their validity to estimate individual dietary intakes was low to moderate. In 24-hour dietary recalls, there is still limited knowledge regarding the accuracy of fully automated approaches; and methodological problems, such as the inaccuracy in self-reported portion sizes might be more critical than in interview-based applications. In contrast, measurement errors in innovative web-based and in conventional paper-based Food Frequency Questionnaires are most likely similar, suggesting that the underlying methodology is unchanged by the technology. Conclusions: Most of the new technologies in dietary assessment were seen to have overlapping methodological features with the conventional methods predominantly used for nutritional epidemiology. Their main potential to enhance dietary assessment is through more cost- and time-effective, less laborious ways of data collection and higher subject acceptance, though their integration in epidemiological studies would need additional considerations, such as the study objectives, the target population and the financial resources available. However, even in innovative technologies, the inherent individual bias related to self-reported dietary intake will not be resolved. More research is therefore crucial to investigate the validity of innovative dietary assessment technologies