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Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research
Author(s) -
Chen Yang,
Mariona Pinart,
Patrick Kolsteren,
John Van Camp,
Nathalie De Cock,
Kathariimptsch,
Tobias Pischon,
Éamon Laird,
Giuditta Perozzi,
Raffaella Canali,
Axelle Hoge,
Marta Stelmach-Mardas,
Lars Ove Dragsted,
Stéphanie Maria Palombi,
Irina Dobre,
Jildau Bouwman,
Peter Clarys,
Fabio Minervini,
Maria De Angelis,
Marco Gobbetti,
Jean Tafforeau,
Óscar Coltell,
Dolores Corella,
Hendrik De Ruyck,
Janette Walton,
Laura Kehoe,
Christophe Matthys,
Bernard De Baets,
Guy De Tré,
Antoon Bronselaer,
Angela A. Rivellese,
Rosalba Giacco,
Rosario Lombardo,
Sofian De Clercq,
Niels Hulstaert,
Carl Lachat
Publication year - 2017
Publication title -
advances in nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.362
H-Index - 90
eISSN - 2156-5376
pISSN - 2161-8313
DOI - 10.3945/an.117.015651
Subject(s) - computer science , data quality , observational study , quality (philosophy) , identification (biology) , data science , interoperability , nutritional epidemiology , data mining , information retrieval , medicine , epidemiology , world wide web , engineering , metric (unit) , philosophy , operations management , botany , epistemology , biology , pathology
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.

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