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Perspective: Essential study quality descriptors for data from nutritional epidemiologic research

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Item Type:Article
Title:Perspective: Essential study quality descriptors for data from nutritional epidemiologic research
Creators Name:Yang, C. and Pinart, M. and Kolsteren, P. and Van Camp, J. and De Cock, N. and Nimptsch, K. and Pischon, T. and Laird, E. and Perozzi, G. and Canali, R. and Hoge, A. and Stelmach-Mardas, M. and Dragsted, L.O. and Palombi, S.M. and Dobre, I. and Bouwman, J. and Clarys, P. and Minervini, F. and De Angelis, M. and Gobbetti, M. and Tafforeau, J. and Coltell, O. and Corella, D. and De Ruyck, H. and Walton, J. and Kehoe, L. and Matthys, C. and De Baets, B. and De Tré, G. and Bronselaer, A. and Rivellese, A. and Giacco, R. and Lombardo, R. and De Clercq, S. and Hulstaert, N. and Lachat, C.
Abstract: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.
Keywords:Data Quality, Observational Study, Dietary Assessment, Nutritional Epidemiology, Data Interoperability
Source:Advances in Nutrition
Publisher:American Society for Nutrition
Page Range:639-651
Date:September 2017
Additional Information:This is a free access article, distributed under terms (http://www.nutrition.org/publications/guidelines-and-policies/license/) that permit unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Official Publication:https://doi.org/10.3945/an.117.015651
PubMed:View item in PubMed

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