TY - JOUR T1 - Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research. JF - Adv Nutr Y1 - 2017 A1 - Yang, Chen A1 - Pinart, Mariona A1 - Kolsteren, Patrick A1 - Van Camp, John A1 - De Cock, Nathalie A1 - Nimptsch, Katharina A1 - Pischon, Tobias A1 - Laird, Eamon A1 - Perozzi, Giuditta A1 - Canali, Raffaella A1 - Hoge, Axelle A1 - Stelmach-Mardas, Marta A1 - Dragsted, Lars Ove A1 - Palombi, Stéphanie Maria A1 - Dobre, Irina A1 - Bouwman, Jildau A1 - Clarys, Peter A1 - Minervini, Fabio A1 - De Angelis, Maria A1 - Gobbetti, Marco A1 - Jean Tafforeau A1 - Coltell, Oscar A1 - Corella, Dolores A1 - De Ruyck, Hendrik A1 - Walton, Janette A1 - Kehoe, Laura A1 - Matthys, Christophe A1 - De Baets, Bernard A1 - De Tré, Guy A1 - Bronselaer, Antoon A1 - Rivellese, Angela A1 - Giacco Rosalba A1 - Lombardo, Rosario A1 - De Clercq, Sofian A1 - Hulstaert, Niels A1 - Lachat, Carl AB -

Pooled analysis of secondary data increases the power of research and enables scientific discovery in nutritional epidemiology. Information on study characteristics that determine data quality is needed to enable correct reuse and interpretation of data. This study aims to define essential quality characteristics for data from observational studies in nutrition. First, a literature review was performed to get an insight on existing instruments that assess the quality of cohort, case-control, and cross-sectional studies and dietary measurement. Second, 2 face-to-face workshops were organized to determine the study characteristics that affect data quality. Third, consensus on the data descriptors and controlled vocabulary was obtained. From 4884 papers retrieved, 26 relevant instruments, containing 164 characteristics for study design and 93 characteristics for measurements, were selected. The workshop and consensus process resulted in 10 descriptors allocated to "study design" and 22 to "measurement" domains. Data descriptors were organized as an ordinal scale of items to facilitate the identification, storage, and querying of nutrition data. Further integration of an Ontology for Nutrition Studies will facilitate interoperability of data repositories.

VL - 8 CP - 5 U1 - http://www.ncbi.nlm.nih.gov/pubmed/28916566?dopt=Abstract M3 - 10.3945/an.117.015651 ER -