ArticleBMC medical research methodology2016
Feasibility and validity of a statistical adjustment to reduce self-report bias of height and weight in wave 1 of the Add Health study.
Article in BMC medical research methodology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
2 citing papers in PubMed.
- Use of Small-Area Estimates to Describe County-Level Geographic Variation in Prevalence of Extreme Obesity Among US Adults.JAMA network open · 2020Article
- Correction of self-reported BMI based on objective measurements: a Belgian experience.Archives of public health = Archives belges de sante publique · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundBias 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.
methodsParticipants 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.
resultsAfter 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).
conclusionsFindings 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.