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Feasibility and validity of a statistical adjustment to reduce self-report bias of height and weight in wave 1 of the Add Health study

Overview of attention for article published in BMC Medical Research Methodology, September 2016
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Title
Feasibility and validity of a statistical adjustment to reduce self-report bias of height and weight in wave 1 of the Add Health study
Published in
BMC Medical Research Methodology, September 2016
DOI 10.1186/s12874-016-0227-y
Pubmed ID
Authors

Janet M. Liechty, Xuan Bi, Annie Qu

Abstract

Bias in adolescent self-reported height and weight is well documented. Given the importance and widespread use of the National Longitudinal Study of Adolescent to Adult Health (Add Health) data for obesity research, we developed and tested the feasibility and validity of an empirically derived statistical correction for self-report bias in wave 1 (W1) of Add Health, a large panel study in the United States. Participants in grades 7-12 with complete height and weight data at W1 were included (n = 20,175). We used measured and self-reported (SR) height and weight and relevant biopsychosocial factors from wave 2 (W2) of Add Health (n = 14,190) to identify sources of bias and derive the most efficient sex-specific estimates of corrected height and weight. Measured, SR, and corrected W2 BMI values were calculated and compared, including sensitivity and specificity. Final correction equations were applied to W1. After correction, weight status misclassification rates among those who underestimated their weight status were reduced from 6.6 to 5.7 % for males and from 8.0 to 5.6 % for females compared to self-report; and the correlation between SR and measured BMI in W2 increased slightly from 0.92 to 0.93. Among females, correction procedures resulted in a 3.4 % increase in sensitivity to detect overweight/obesity (BMI ≥ 25) and 5.9 % increase in sensitivity for obesity (BMI ≥ 30). Findings suggest that application of the proposed statistical corrections can reduce bias of self-report height and weight in W1 of the Add Health data and may be useful in some analyses. In particular, the corrected BMI values improve sensitivity --the ability to detect a true positive-for overweight/obesity among females, which addresses a major concern about self-report bias in obesity research. However, the correction does not improve sensitivity to identify underweight or healthy weight adolescents and so should be applied selectively based on research questions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 22%
Student > Doctoral Student 4 17%
Student > Bachelor 4 17%
Student > Ph. D. Student 3 13%
Professor 2 9%
Other 3 13%
Unknown 2 9%
Readers by discipline Count As %
Nursing and Health Professions 4 17%
Social Sciences 4 17%
Psychology 4 17%
Medicine and Dentistry 3 13%
Economics, Econometrics and Finance 2 9%
Other 3 13%
Unknown 3 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 October 2016.
All research outputs
#14,861,841
of 22,889,074 outputs
Outputs from BMC Medical Research Methodology
#1,448
of 2,024 outputs
Outputs of similar age
#193,421
of 321,009 outputs
Outputs of similar age from BMC Medical Research Methodology
#28
of 45 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
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