論文

査読有り
2019年6月

Handling missing data in an FFQ: multiple imputation and nutrient intake estimates

PUBLIC HEALTH NUTRITION
  • Mari Ichikawa
  • ,
  • Akihiro Hosono
  • ,
  • Yuya Tamai
  • ,
  • Miki Watanabe
  • ,
  • Kiyoshi Shibata
  • ,
  • Shoko Tsujimura
  • ,
  • Kyoko Oka
  • ,
  • Hitomi Fujita
  • ,
  • Naoko Okamoto
  • ,
  • Mayumi Kamiya
  • ,
  • Fumi Kondo
  • ,
  • Ryozo Wakabayashi
  • ,
  • Taiji Noguchi
  • ,
  • Tatsuya Isomura
  • ,
  • Nahomi Imaeda
  • ,
  • Chiho Goto
  • ,
  • Tamaki Yamada
  • ,
  • Sadao Suzuki

22
8
開始ページ
1351
終了ページ
1360
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1017/S1368980019000168
出版者・発行元
CAMBRIDGE UNIV PRESS

Objective We aimed to examine missing data in FFQ and to assess the effects on estimating dietary intake by comparing between multiple imputation and zero imputation. Design We used data from the Okazaki Japan Multi-Institutional Collaborative Cohort (J-MICC) study. A self-administered questionnaire including an FFQ was implemented at baseline (FFQ1) and 5-year follow-up (FFQ2). Missing values in FFQ2 were replaced by corresponding FFQ1 values, multiple imputation and zero imputation. Setting A methodological sub-study of the Okazaki J-MICC study. Participants Of a total of 7585 men and women aged 35-79 years at baseline, we analysed data for 5120 participants who answered all items in FFQ1 and at least 50% of items in FFQ2. Results Among 5120 participants, the proportion of missing data was 3 center dot 7%. The increasing number of missing food items in FFQ2 varied with personal characteristics. Missing food items not eaten often in FFQ2 were likely to represent zero intake in FFQ1. Most food items showed that the observed proportion of zero intake was likely to be similar to the probability that the missing value is zero intake. Compared with FFQ1 values, multiple imputation had smaller differences of total energy and nutrient estimates, except for alcohol, than zero imputation. Conclusions Our results indicate that missing values due to zero intake, namely missing not at random, in FFQ can be predicted reasonably well from observed data. Multiple imputation performed better than zero imputation for most nutrients and may be applied to FFQ data when missing is low.

Web of Science ® 被引用回数 : 1

リンク情報
DOI
https://doi.org/10.1017/S1368980019000168
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000466562700002&DestApp=WOS_CPL

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