Circulating Polyunsaturated Fatty Acids as Biomarkers for Dietary Intake across Subgroups: The CODAM and Hoorn Studies.

AIMS: To evaluate whether participant characteristics and way of expressing circulating fatty acids (FA) influence the strengths of associations between self-reported intake and circulating levels of linoleic acid (LA), alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). METHODS: Cross-sectional analyses were performed in pooled data from the CODAM (n = 469) and Hoorn (n = 702) studies. Circulating FA were measured by gas liquid chromatography and expressed as proportions (% of total FA) and concentrations (µg/mL). Dietary intakes were calculated from a validated food frequency questionnaire. Effects of participant characteristics on associations between dietary and circulating FA were calculated using interaction analyses. RESULTS: Standardized regression coefficients between dietary FA and proportions of circulating FA (% of total FA) were LA ß = 0.28, ALA ß = 0.13, EPA ß = 0.34, and DHA ß = 0.45. Body mass index (BMI), waist circumference, and presence of CVD influenced associations for LA; gender influenced LA, EPA, and DHA; alcohol intake influenced LA and DHA; and glucose tolerance status influenced ALA (p values interaction <0.05). Coefficients for circulating FA as concentrations were LA ß = 0.19, ALA ß = 0.10, EPA ß = 0.31, and DHA ß = 0.41. CONCLUSIONS: This study suggests that characteristics such as BMI, alcohol intake, and expressing circulating FA as proportions or concentrations, influence associations between dietary and circulating FA.

Adverse events recording in electronic health record systems in primary care.

BACKGROUND: Adequate record keeping of medication adverse events in electronic health records systems is important for patient safety. Events that remain unrecorded cannot be communicated from one health professional to another. In the absence of a gold standard, we investigate the variation between Dutch general practices in the extent to which they record medication adverse events. METHODS: Data were derived from electronic health records (EHR) of Dutch general practices participating in NIVEL Primary Care Database (NIVEL-PCD) in 2014, including 308 general practices with a total practice population of 1,256,049 listed patients. Medication adverse events were defined as recorded ICPC-code A85 (adverse effect medical agent). Between practice variation was studied using multilevel logistic regression analysis corrected for age, gender, number of different medicines prescriptions and number of chronic diseases. RESULTS: In 2014 there were 8330 patients with at least one medication adverse event recorded. This corresponds to 6.9 medication adverse events per 1000 patients and is higher for women, elderly, patients with polypharmacy and for patients with comorbidity. Corrected for these patient characteristics the median odds ratio (MOR = 1.92) suggests an almost twofold difference between general practices in recorded medication adverse events. CONCLUSION: Our results suggest that improvement in terms of uniformity in recording medication adverse events is possible, preventing potential damage for patients. We suggest that creating a learning health system by individual practice feedback on the number of recordings of adverse events would help practitioners to improve their recording habits.