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      Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006

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      1 , , 2
      BMC Public Health
      BioMed Central

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          Abstract

          Background

          The Body Mass Index (BMI) based on self-reported height and weight ("self-reported BMI") in epidemiologic studies is subject to measurement error. However, because of the ease and efficiency in gathering height and weight information through interviews, it remains important to assess the extent of error present in self-reported BMI measures and to explore possible adjustment factors as well as valid uses of such self-reported measures.

          Methods

          Using the combined 2001-2006 data from the continuous National Health and Nutrition Examination Survey, discrepancies between BMI measures based on self-reported and physical height and weight measures are estimated and socio-demographic predictors of such discrepancies are identified. Employing adjustments derived from the socio-demographic predictors, the self-reported measures of height and weight in the 2001-2006 National Health Interview Survey are used for population estimates of overweight & obesity as well as the prediction of health risks associated with large BMI values. The analysis relies on two-way frequency tables as well as linear and logistic regression models. All point and variance estimates take into account the complex survey design of the studies involved.

          Results

          Self-reported BMI values tend to overestimate measured BMI values at the low end of the BMI scale (< 22) and underestimate BMI values at the high end, particularly at values > 28. The discrepancies also vary systematically with age (younger and older respondents underestimate their BMI more than respondents aged 42-55), gender and the ethnic/racial background of the respondents. BMI scores, adjusted for socio-demographic characteristics of the respondents, tend to narrow, but do not eliminate misclassification of obese people as merely overweight, but health risk estimates associated with variations in BMI values are virtually the same, whether based on self-report or measured BMI values.

          Conclusion

          BMI values based on self-reported height and weight, if corrected for biases associated with socio-demographic characteristics of the survey respondents, can be used to estimate health risks associated with variations in BMI, particularly when using parametric prediction models.

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          Most cited references14

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          Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.

          Obesity and diabetes are increasing in the United States. To estimate the prevalence of obesity and diabetes among US adults in 2001. Random-digit telephone survey of 195 005 adults aged 18 years or older residing in all states participating in the Behavioral Risk Factor Surveillance System in 2001. Body mass index, based on self-reported weight and height and self-reported diabetes. In 2001 the prevalence of obesity (BMI > or =30) was 20.9% vs 19.8% in 2000, an increase of 5.6%. The prevalence of diabetes increased to 7.9% vs 7.3% in 2000, an increase of 8.2%. The prevalence of BMI of 40 or higher in 2001 was 2.3%. Overweight and obesity were significantly associated with diabetes, high blood pressure, high cholesterol, asthma, arthritis, and poor health status. Compared with adults with normal weight, adults with a BMI of 40 or higher had an odds ratio (OR) of 7.37 (95% confidence interval [CI], 6.39-8.50) for diagnosed diabetes, 6.38 (95% CI, 5.67-7.17) for high blood pressure, 1.88 (95% CI,1.67-2.13) for high cholesterol levels, 2.72 (95% CI, 2.38-3.12) for asthma, 4.41 (95% CI, 3.91-4.97) for arthritis, and 4.19 (95% CI, 3.68-4.76) for fair or poor health. Increases in obesity and diabetes among US adults continue in both sexes, all ages, all races, all educational levels, and all smoking levels. Obesity is strongly associated with several major health risk factors.
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            Dose-response and trend analysis in epidemiology: alternatives to categorical analysis.

            Standard categorical analysis is based on an unrealistic model for dose-response and trends and does not make efficient use of within-category information. This paper describes two classes of simple alternatives that can be implemented with any regression software: fractional polynomial regression and spline regression. These methods are illustrated in a problem of estimating historical trends in human immunodeficiency virus incidence. Fractional polynomial and spline regression are especially valuable when important nonlinearities are anticipated and software for more general nonparametric regression approaches is not available.
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              Accuracy of self-reported body weight, height and waist circumference in a Dutch overweight working population

              Background In population studies, body mass index (BMI) is generally calculated from self-reported body weight and height. The self-report of these anthropometrics is known to be biased, resulting in a misclassification of BMI status. The aim of our study is to evaluate the accuracy of self-reported weight, height and waist circumference among a Dutch overweight (Body Mass Index [BMI] ≥ 25 kg/m2) working population, and to determine to what extent the accuracy was moderated by sex, age, BMI, socio-economic status (SES) and health-related factors. Methods Both measured and self-reported body weight and body height were collected in 1298 healthy overweight employees (66.6% male; mean age 43.9 ± 8.6 years; mean BMI 29.5 ± 3.4 kg/m2), taking part in the ALIFE@Work project. Measured and self-reported waist circumferences (WC) were available for a sub-group of 250 overweight subjects (70.4% male; mean age 44.1 ± 9.2 years; mean BMI 29.6 ± 3.0 kg/m2). Intra Class Correlation (ICC), Cohen's kappa and Bland Altman plots were used for reliability analyses, while linear regression analyses were performed to assess the factors that were (independently) associated with the reliability. Results Body weight was significantly (p < 0.001) under-reported on average by 1.4 kg and height significantly (p < 0.001) over-reported by 0.7 cm. Consequently, BMI was significantly (p < 0.001) under-reported by 0.7 kg/m2. WC was significantly (p < 0.001) over-reported by 1.1 cm. Although the self-reporting of anthropometrics was biased, ICC's showed high concordance between measured and self-reported values. Also, substantial agreement existed between the prevalences of BMI status and increased WC based on measured and self-reported data. The under-reporting of BMI and body weight was significantly (p < 0.05) affected by measured weight, height, SES and smoking status, and the over-reporting of WC by age, sex and measured WC. Conclusion Results suggest that self-reported BMI and WC are satisfactorily accurate for the assessment of the prevalence of overweight/obesity and increased WC in a middle-aged overweight working population. As the accuracy of self-reported anthropometrics is affected by measured weight, height, WC, smoking status and/or SES, results for these subgroups should be interpreted with caution. Due to the large power of our study, the clinical significance of our statistical significant findings may be limited. Trial Registration ISRCTN04265725
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                Author and article information

                Journal
                BMC Public Health
                BMC Public Health
                BioMed Central
                1471-2458
                2009
                19 November 2009
                : 9
                : 421
                Affiliations
                [1 ]College of Nursing, Michigan State University, W-149 Owen Graduate Center, East Lansing, Michigan 48825-1109, USA
                [2 ]CDC/National Center for Health Statistics, 3311 Toledo Rd. Room 2331, Hyattsville, MD 20782, USA
                Article
                1471-2458-9-421
                10.1186/1471-2458-9-421
                2784464
                19922675
                dbea280e-b614-41a3-a453-e5f275518dcd
                Copyright ©2009 Stommel and Schoenborn; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 January 2009
                : 19 November 2009
                Categories
                Research article

                Public health
                Public health

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