Dataset Information

Challenging the role of social norms regarding body weight as an explanation for weight, height, and BMI misreporting biases: development and application of a new approach to examining misreporting and misclassification bias in surveys.

ABSTRACT:

Background

Cultural pressures to be thin and tall are postulated to cause people to misreport their body weight and height towards more socially normative (i.e., desirable) values, but a paucity of direct evidence supports this idea. We developed a novel non-linear approach to examining weight, height, and BMI misreporting biases and used this approach to examine the association between socially non-normative weight and misreporting biases in adults.

Methods

The Survey of Lifestyles, Attitudes, and Nutrition 2007 (SLÁN 2007), a nationally representative survey of the Republic of Ireland (N = 1942 analyzed) was used. Self-reported weight (height) was classified as under-reported by ? 2.0 kg (2.0 cm), over-reported by ? 2.0 kg (2.0 cm), or accurately reported within 2.0 kg (2.0 cm) to account for technical errors of measurement and short-term fluctuations in measured weight (height). A simulation strategy was used to define self-report-based BMI as under-estimated by more than 1.40 kg/m2, over-estimated by more than 1.40 kg/m2, or accurately estimated within 1.40 kg/m2. Patterns of biases in self-reported weight, height, and BMI were explored. Logistic regression was used to identify factors associated with mis-estimated BMI and to calculate adjusted odds ratios (AOR) and 99% confidence intervals (99%CI).

Results

The patterns of bias contributing the most to BMI mis-estimation were consistently, in decreasing order of influence, (1) under-reported weight combined with over-reported height, (2) under-reported weight with accurately reported height, and (3) accurately reported weight with over-reported height. Average bias in self-report-based BMI was -1.34 kg/m2 overall and -0.49, -1.33, and -2.66 kg/m2 in normal, overweight, and obese categories, respectively. Despite the increasing degree of bias with progressively higher BMI categories, persons describing themselves as too heavy were, within any given BMI category, less likely to have under-estimated BMI (AOR 0.5, 99%CI: 0.3-0.8, P < 0.001), to be misclassified in a lower BMI category (AOR 0.3, 99%CI: 0.2-0.5, P < 0.001), to under-report weight (AOR 0.5, 99%CI: 0.3-0.7, P < 0.001), and to over-report height (OR 0.7, 99%CI: 0.6-1.0, P = 0.007).

Conclusions

A novel non-linear approach to examining weight, height, and BMI misreporting biases was developed. Perceiving oneself as too heavy appears to reduce rather than exacerbate weight, height, and BMI misreporting biases.

SUBMITTER: Brestoff JR

PROVIDER: S-EPMC3121629 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Publications

Challenging the role of social norms regarding body weight as an explanation for weight, height, and BMI misreporting biases: development and application of a new approach to examining misreporting and misclassification bias in surveys.

Brestoff Jonathan R JR Perry Ivan J IJ Van den Broeck Jan J

BMC public health 20110518

<h4>Background</h4>Cultural pressures to be thin and tall are postulated to cause people to misreport their body weight and height towards more socially normative (i.e., desirable) values, but a paucity of direct evidence supports this idea. We developed a novel non-linear approach to examining weight, height, and BMI misreporting biases and used this approach to examine the association between socially non-normative weight and misreporting biases in adults.<h4>Methods</h4>The Survey of Lifestyl ...[more]

PMID: 21592341

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Dataset Information

Challenging the role of social norms regarding body weight as an explanation for weight, height, and BMI misreporting biases: development and application of a new approach to examining misreporting and misclassification bias in surveys.

Background

Methods

Results

Conclusions

Publications

Challenging the role of social norms regarding body weight as an explanation for weight, height, and BMI misreporting biases: development and application of a new approach to examining misreporting and misclassification bias in surveys.

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