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

Research output: Contribution to journalArticle

Abstract

Background: 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. Methods: 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. Results: 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). Conclusions: 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.

Original languageEnglish (US)
Pages (from-to)1-10
Number of pages10
JournalBMC Medical Research Methodology
Volume16
Issue number1
DOIs
StatePublished - Sep 22 2016

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Self Report
Weights and Measures
Health
Obesity
Research
Thinness
Longitudinal Studies
Sensitivity and Specificity

Keywords

  • Add Health
  • Body mass index
  • Epidemiology
  • Obesity
  • Overweight
  • Self-report bias
  • Self-report vs. measured
  • Self-reported weight
  • Statistical adjustment
  • Statistical correction

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics

Cite this

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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",
abstract = "Background: 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. Methods: 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. Results: 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). Conclusions: 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.",
keywords = "Add Health, Body mass index, Epidemiology, Obesity, Overweight, Self-report bias, Self-report vs. measured, Self-reported weight, Statistical adjustment, Statistical correction",
author = "Liechty, {Janet M.} and Xuan Bi and Annie Qu",
year = "2016",
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day = "22",
doi = "10.1186/s12874-016-0227-y",
language = "English (US)",
volume = "16",
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journal = "BMC Medical Research Methodology",
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publisher = "BioMed Central",
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TY - JOUR

T1 - Feasibility and validity of a statistical adjustment to reduce self-report bias of height and weight in wave 1 of the Add Health study

AU - Liechty, Janet M.

AU - Bi, Xuan

AU - Qu, Annie

PY - 2016/9/22

Y1 - 2016/9/22

N2 - Background: 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. Methods: 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. Results: 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). Conclusions: 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.

AB - Background: 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. Methods: 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. Results: 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). Conclusions: 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.

KW - Add Health

KW - Body mass index

KW - Epidemiology

KW - Obesity

KW - Overweight

KW - Self-report bias

KW - Self-report vs. measured

KW - Self-reported weight

KW - Statistical adjustment

KW - Statistical correction

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