A preliminary study of active compared with passive imputation of missing body mass index values among non-Hispanic white youths

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Sibylle Kranz (Creator)

David A. Wagstaff (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Background: Addressing missing data on body weight height or oth is a challenge many researchers face. In calculating the body ass index (BMI) of study participants researchers need to impute he missing data. bjective: A multiple imputation through a chained equations approach was used to determine whether one should first impute the missing anthropometric data and then calculate BMI or use an imputation model to obtain BMI. esign: The present study used computer simulation to address the uestion of how to calculate BMI when there is missing data on weight and height. The simulated data reflected data gathered on non-Hispanic white youths (n ¼ 905) aged 2–18 y who participated in the 1999–2000 National Health and Nutrition Examination Survey (NHANES). esults: The simulation indicated that it made little difference in the accuracy with which the youths’ mean BMIs were estimated when the data were missing completely at random. However the use of a model to impute BMI was favored slightly when the data were missing at random and the imputation model included the variable used to determine missingness. onclusion: The present findings extend the use of passive imputation nd the use of multiple imputation through a chained equations approach to an area of critical public health importance. Am J Clin Nutr 2009;89:1025–30. Originally published American Journal of Clinical Nutrition Vol. 89 No. 4 Apr 2009

Additional Information

Publication

Other

American Journal of Clinical Nutrition. 89:4(April 2009) p. 1025-1030.

Language: English

Date: 2011

Keywords

Body mass index, missing values, imputation

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