ArticlePloS one2016
Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Refining an algorithm-powered just-in-time adaptive weight control intervention: A randomized controlled trial evaluating model performance and behavioral outcomes.Health informatics journal · 2020Trial
- Optimizing Self-Monitoring in a Digital Weight Loss Intervention (Spark): Protocol for a Factorial Randomized Trial.JMIR research protocols · 2025Article
- How does BMI correlate with menarche onset? Evidence from the Italian HBSC cross-sectional study.BMC women's health · 2025Article
- Perceptions of weight status and energy balance behaviors among patients with non-alcoholic fatty liver disease.Scientific reports · 2022Article
- Why primary obesity is a disease?Journal of translational medicine · 2019Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
objectiveTo compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.
methodsWe used data from 11,008 adults examined at wave III (2001-2002) and wave IV (2007-2008) in the National Longitudinal Study of Adolescent to Adult Health. Participants were asked their height and weight before being measured. Equations to predict wave IV BMIM were developed in an 80% random subsample and evaluated in the remaining participants. The validity of models that included BMI constructed from previously measured height and weight (BMIPM) was compared to the validity of models that used BMI calculated from concurrently self-reported height and weight (BMISR). The usefulness of including demographics and perceived weight category in those models was also examined.
resultsThe model that used BMISR, compared to BMIPM, as the only variable produced a larger R2 (0.913 vs. 0.693), a smaller root mean square error (2.07 vs. 3.90 kg/m2) and a lower bias between normal-weight participants and those with obesity (0.98 vs. 4.24 kg/m2). The performance of the model containing BMISR alone was not substantially improved by the addition of demographics, perceived weight category or BMIPM.
conclusionsOur work is the first to show that concurrent self-reports of height and weight may be more useful than previously measured height and weight for imputation of missing BMIM when the time interval between measures is relatively long. Other time frames and alternatives to in-person collection of self-reported data need to be examined.
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Registered trials
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