Dataset Information

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

ABSTRACT:

Objective

To compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.

Methods

We 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.

Results

The 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.

Conclusions

Our 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.

SUBMITTER: Cui Z

PROVIDER: S-EPMC5127553 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

Cui Zhaohui Z Stevens June J Truesdale Kimberly P KP Zeng Donglin D French Simone S Gordon-Larsen Penny P

PloS one 20161129 11

<h4>Objective</h4>To compare alternative models for the imputation of BMIM (measured weight in kilograms/measured height in meters squared) in a longitudinal study.<h4>Methods</h4>We 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 t ...[more]

PMID: 27898706

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Project description:BackgroundChildren with familial dysautonomia (FD) are smaller and grow more slowly than the general population. It is unknown whether this abnormal growth is due to comorbidities that patients with FD live with, or if it is a direct effect of the disease-causing homozygous ELP-1 mutations. Here, we created growth curves for weight, height, and body mass index (BMI) in male and female children with FD to monitor the nutritional status of patients with FD.MethodsWe used the New York University (NYU) FD Registry which includes data from 680 individuals with FD who were followed longitudinally since birth. We generated sex-specific FD growth charts for three age ranges (birth to 36 months, 2 to 20 years, and 2 to 40 years) and compared them to the general population. We generated Kaplan-Meier curves to test the hypothesis that FD patients with low BMI had shorter survival than the rest of the cohort.ResultsGrowth charts generated from 591 individuals with FD show that these patients grow more slowly, reach less height, and gain less weight than the general population. The impact of FD on height was more pronounced in girls than in boys. However, both groups showed markedly low weights, which resulted in low BMI. Low weight, but not height, is already evident at birth. In a subpopulation of FD patients, we found that treatment with growth hormone or spinal fusion surgery helped patients achieve the expected growth characteristic of FD patients, but these treatments did not lead FD patients to achieve the growth pattern of the general population. Contrary to our hypothesis, low BMI had no impact on patient survival.ConclusionsPediatric patients with FD have lower height, weight, and BMI compared to the general pediatric population, but this does not appear to affect survival. Growth curves specific to the FD population are an important tool to monitor growth and nutritional status in pediatric patients with FD when the general population growth curves are of limited use.

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Dataset Information

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

Objective

Methods

Results

Conclusions

Publications

Prediction of Body Mass Index Using Concurrently Self-Reported or Previously Measured Height and Weight.

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