McAdams MA, Van Dam RM, Hu FB. Comparison of self-reported and measured BMI as correlates of disease markers in US adults. Obesity 15, 188-196

Department of Nutrition , Harvard University, Cambridge, Massachusetts, United States
Obesity (Impact Factor: 3.73). 02/2007; 15(1):188-96. DOI: 10.1038/oby.2007.504
Source: PubMed


The purpose of this study is to evaluate the validity of BMI based on self-reported data by comparison with technician-measured BMI and biomarkers of adiposity.
We analyzed data from 10,639 National Health and Nutrition Education Study III participants > or =20 years of age to compare BMI calculated from self-reported weight and height with BMI from technician-measured values and body fatness estimated from bioelectrical impedance analysis in relation to systolic blood pressure, fasting blood levels of glucose, high-density lipoprotein-cholesterol, triglycerides, C-reactive protein, and leptin.
BMI based on self-reported data (25.07 kg/m2) was lower than BMI based on technician measurements (25.52 kg/m2) because of underreporting weight (-0.56 kg; 95% confidence interval, -0.71, -0.41) and overreporting height (0.76 cm; 95% confidence interval, 0.64, 0.88). However, the correlations between self-reported and measured BMI values were very high (0.95 for whites, 0.93 for blacks, and 0.90 for Mexican Americans). In terms of biomarkers, self-reported and measured BMI values were equally correlated with fasting blood glucose (r = 0.43), high-density lipoprotein-cholesterol (r = -0.53), and systolic blood pressure (r = 0.54). Similar correlations were observed for both measures of BMI with plasma concentrations of triglycerides and leptin. These correlations did not differ appreciably by age, sex, ethnicity, or obesity status. Correlations for percentage body fat estimated through bioelectrical impedance analysis with these biomarkers were similar to those for BMI.
The accuracy of self-reported BMI is sufficient for epidemiological studies using disease biomarkers, although inappropriate for precise measures of obesity prevalence.

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    • "Comparing the mean BMI levels in our study at ages 32 and 42 to a recent Finnish report using large population-based surveys and standardized protocols for measuring height and weight suggests that this underestimation has been small[37]. Nevertheless, since BMI was used as a continuous measure in the analyses, the bias due to its underestimation has likely been only modest or negligible[38]. "
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    ABSTRACT: Purpose: This study examined the developmental trajectories of self-esteem and body mass index (BMI) from adolescence to mid-adulthood and the way the association between self-esteem and BMI changed during a 26-year follow-up. Methods: Participants of a Finnish cohort study in 1983 at 16 years (N = 2194) were followed up at ages 22 (N = 1656), 32 (N = 1471), and 42 (N = 1334) using postal questionnaires. Measures at each time point covered self-esteem and self-reported weight and height. Analyses were done using latent growth curve models (LGM) and difference scores. Results: In LGM analyses among females both the initial levels (r = -0.13) and slopes (r = -0.26) of the self-esteem and BMI trajectories correlated negatively. Among males, there were no significant correlations between self-esteem and BMI growth factors. The association between increasing BMI and decreasing self-esteem among females was strongest between ages 22 and 32 (r = -0.16), while among males, increases in BMI and self-esteem correlated positively (r = 0.11) during that period. Among females, cross-sectional correlations between self-esteem and BMI showed an increasing trend (p < 0.001) from age 16 (r = -0.07) to age 42 (r = -0.17), whereas among males negative correlation (r = -0.08) emerged only in mid-adulthood at age 42. Conclusion: Among females, higher and increasing BMI is associated with lower and more slowly increasing self-esteem. This association is not restricted to adolescent years but persists and gets stronger in mid-adulthood. Among males, associations are weaker but indicate more age-related differences. The results highlight the need for interventions that tackle weight-related stigma and discrimination, especially among women with higher body weight and size.
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    • "On the contrary, the number of patients using fibrate was reduced but the overall control of triglyceride improved with dropping of mean TG from 1.7 to 1.4 mmol/L, and more patients achieving target of TG <1.7 mmol/L. One of the hypotheses may be the partial triglyceride lowering effect of statin which was prescribed extensively[28,29], or the associated reduction in BMI[30,31]. "
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    ABSTRACT: Background: Number of diabetic patients under public primary care in Hong Kong rose from 150,157 (2009) to 173,015 (2013). This study aimed to track the 5-year change of their outcomes and care standard after the introduction of quality enhancement programmes. Methods: Longitudinal study was conducted on a group of diabetic patients who received continuous care under public primary care between 2009 and 2013. Socio-demographic and clinical data was retrieved from central database. The standard of care in terms of proportion of patients achieving haemoglobin A1c (HbA1c), systolic and diastolic blood pressure (SBP and DBP), and low density lipoprotein-cholesterol (LDL-C) target levels, mean parameter changes, and 5-year cumulative incidence of major complications were assessed. Outcomes between 2009 and 2013 were compared by McNemar's test for proportion of patients treated to targets and paired t-test for continuous outcome parameters. Results: A group of 127,977 diabetic patients who had continuous follow-up between 2009 and 2013 were assessed. A significantly higher proportions of patients achieving targets of HbA1c (<7 %), SBP (<130 mmHg), DBP (<80 mmHg), LDL-C (<2.6 mmol/L), triglyceride (<1.7 mmol/L), and high density lipoprotein-cholesterol (>1.0 or 1.3 mmol/L) were observed (p < 0.001). There was a significant drop in the mean values of HbA1c (7.2-7.0 %), SBP (136.9-131.3 mmHg), DBP (75.4-72.1 mmHg), LDL-C (3.1-2.4 mmol/L), triglyceride (1.7-1.4 mmol/L), and body mass index (25.6-25.3 kg/m(2)). More patients (0.6 % raised to 3.5 %) used insulin in addition to their oral anti-diabetic drugs for their management, and a significant boost (from 9.0 to 55.0 %) was on statin use. 5-year cumulative incidence of any major diabetic complication was 6.2 %. Conclusions: Standard of public primary care for diabetic patients enhanced from 2009 to 2013, as reflected by the improvement in outcomes of care. It could be related to the implementation of the territory-wide quality enhancement programmes in all public primary care clinics since 2009, with coverage increasing from 3.1 % (2009) to 81.9 % (2013). Clinical trial number and registry: NCT02034695,
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    • "This requires that they not only be aware of their actual weight, but also have a good sense of what their ideal body weight should be. Previous studies have already demonstrated the lack of accuracy with patients' self-reported weight [10] [11] [12]. The focus of this study was to measure patients' insight to their target ideal weight. "
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    ABSTRACT: Objective: Despite much effort, obesity remains a significant public health problem. One of the main contributing factors is patients' perception of their target ideal body weight. This study aimed to assess this perception. Methods: The study took place in an urban area, with the majority of participants in the study being Hispanic (65.7%) or African-American (28.0%). Patients presented to an outpatient clinic were surveyed regarding their ideal body weight and their ideal BMI calculated. Subsequently they were classified into different categories based on their actual measured BMI. Their responses for ideal BMI were compared. Results: In 254 surveys, mean measured BMI was 31.71 ± 8.01. Responses to ideal BMI had a range of 18.89-38.15 with a mean of 25.96 ± 3.25. Mean (±SD) ideal BMI for patients with a measured BMI of <18.5, 18.5-24.9, 25-29.9, and ≥30 was 20.14 ± 1.46, 23.11 ± 1.68, 25.69 ± 2.19, and 27.22 ± 3.31, respectively. These differences were highly significant (P < 0.001, ANOVA). Conclusions: Most patients had an inflated sense of their target ideal body weight. Patients with higher measured BMI had higher target numbers for their ideal BMI. Better education of patients is critical for obesity prevention programs.
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