Development and validation of a questionnaire to measure adherence to the mediterranean diet in korean adults

Yu Jin Kwon, Hyangkyu Lee, Yooeun Yoon, Hyung Mi Kim, Sang Hui Chu, Ji Won Lee

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


The Mediterranean diet (MD) has beneficial effects on cardiovascular diseases, cancer, and mortality. Although various attempts have been made for estimating adherence to the MD using diet quality indices, few studies involving validated questionnaires for estimating adherence have been performed in Asian populations. We aimed to develop and validate the Korean version of the Mediterranean Diet Adherence Screener (K-MEDAS) by including 211 participants that visited health check-up centers and 116 participants with overweight or hypercholesterolemia that visited obesity clinic. The participants completed both the K-MEDAS and a 106-item food frequency questionnaire (FFQ).We translated 13 questions and developed 1 question. Considering the agreement between the K-MEDAS and FFQ, nine of the 14 questions showed moderate or high kappa values (0.4). The total MD scores measured by the K-MEDAS and FFQ showed substantial concordance (intraclass correlation coeffcient = 0.678, 95% confidence interval: 0.520, 0.785). Multiple linear regression analyses revealed significant inverse associations betweenMDscore and the levels of serum total cholesterol, low-density lipoprotein cholesterol, and non-high-density lipoprotein cholesterol, after adjusting for confounding variables. We found that K-MEDAS is valid tool for assessing adherence to the MD in the Korean population.

Original languageEnglish
Article number1102
Issue number4
Publication statusPublished - 2020 Apr

Bibliographical note

Funding Information:
Funding: This work was supported by the Bio and Medical Technology Development Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT, and Future Planning (NRF-2018R1D1A1B07049223); the Technology Innovation Program (20002781, A Platform for Prediction and Management of Health Risk Based on Personal Big Data and Lifelogging) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea).

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Food Science
  • Nutrition and Dietetics


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