Comparison of Self-reported and Measured
BMI as Correlates of Disease Markers in
Mara A. McAdams,* Rob M. Van Dam,† and Frank B. Hu*†‡
MCADAMS, MARA A., ROB M. VAN DAM, AND
FRANK B. HU. Comparison of self-reported and measured
BMI as correlates of disease markers in U.S. adults.
Objective: 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.
Research Methods and Procedures: We analyzed data
from 10,639 National Health and Nutrition Education Study
III participants ?20 years of age to compare BMI calculated
from self-reported weight and height with BMI from tech-
nician-measured values and body fatness estimated from
bioelectrical impedance analysis in relation to systolic blood
pressure, fasting blood levels of glucose, high-density li-
poprotein-cholesterol, triglycerides, C-reactive protein, and
Results: 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). How-
ever, 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 cor-
related 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 tri-
glycerides and leptin. These correlations did not differ ap-
preciably by age, sex, ethnicity, or obesity status. Correla-
tions for percentage body fat estimated through bioelectrical
impedance analysis with these biomarkers were similar to
those for BMI.
Discussion: The accuracy of self-reported BMI is sufficient
for epidemiological studies using disease biomarkers, al-
though inappropriate for precise measures of obesity prev-
Key words: BMI, National Health and Nutrition Educa-
tion Study III, bioelectrical impedance analysis, self-
Many large epidemiological studies depend on self-re-
ported weight and height as surrogates for technician mea-
surements (1,2). Self-reported measures are more feasible to
collect for large population samples, less burdensome for
the study participants, and entail fewer costs than values
obtained by clinical measurements of height and weight.
Although there are many practical advantages of using
self-reported data, adiposity values calculated from these
measures, such as BMI, may be subject to inaccuracies
because of random and systematic errors, which in turn
affect the validity of the measures (3). For this reason, it is
important to quantify the degree to which self-reported
values agree with clinical measurements and whether these
participant-provided responses are sufficiently accurate to
be used in epidemiological studies.
More than two decades ago, Stunkard and Albaum (4)
reported a high accuracy of self-reported weights across
different ages and sexes. Also, Stewart (3) studied more
than 3000 subjects 14 to 61 years of age and found that
self-reported values are valid and reliable indicators of
measured weight and height, a finding that was confirmed
by subsequent studies (5–11). This work has expanded from
Received for review April 14, 2006.
Accepted in final form August 1, 2006.
The costs of publication of this article were defrayed, in part, by the payment of page
charges. This article must, therefore, be hereby marked “advertisement” in accordance with
18 U.S.C. Section 1734 solely to indicate this fact.
*Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts;
†Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts; and
‡Channing Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston,
Address correspondence to Frank B. Hu, Department of Nutrition, Harvard School of Public
Health, 665 Huntington Avenue, Boston, MA 02115.
Copyright © 2007 NAASO
188OBESITY Vol. 15 No. 1 January 2007
weight and height to BMI and to racial/ethnic subgroups
through larger, nationally representative U.S. studies (6,10).
Data from the Health and Nutrition Education Study III
(NHANES III)1has shown that there is an increasing prev-
alence of obesity in the United States (12), and this dataset
has been used to assess the validity of classification of
overweight and obesity through the use of self-reported
weight and height by ethnicity, sex, and age (6,7,10). Gil-
lum et al. (10) found a substantial underestimation of the
prevalence of obesity based on self-reported height and
weight in women and Mexican-American men.
We have found no studies that compared the correlations
of biomarkers of disease with BMI based on self-reports and
technician measurements. While traditional anthropometric
measures such as weight and BMI are often used in epide-
miological studies, measures such as bioelectrical imped-
ance analysis (BIA) are used with increasing frequency to
better distinguish between fat and lean tissue (13,14). The
aim of this study is to assess the validity of BMI based on
self-reports in a nationally representative sample of U.S.
adults (NHANES III) by 1) comparison with BMI based on
technician measurements and 2) comparison of correlations
for BMI based on self-reports, BMI based on technician
measurements, and percent body fat (PBF) based on BIA
with disease biomarkers.
Research Methods and Procedures
The NHANES III study was conducted between 1988 and
1994 by the National Center for Health Statistics of the
Centers for Disease Control and Prevention. This study was
designed to provide a nationally representative sample of
the U.S. population (?2 months of age) and to collect
information on the health status of U.S. civilian noninstitu-
tionalized populations. NHANES III sample design reflects
a stratified multistage probability design that included over-
sampling of Mexican-American and black populations. This
was done to produce statistically reliable health estimates
for the two largest ethnic minority groups in the United
States. The sampling method was similar to those used in
previous Health and Nutrition Surveys, and details of the
sampling methods and methodological information have
been previously published (15,16).
NHANES III consisted of a survey and clinical exami-
nation. All participants were interviewed at home (N ?
39,695), with 85.6% (n ? 33,994) invited to participate in
the clinical examination portion; 31,311 of those invited
received a clinical examination. The exam was performed in
a mobile examination center for all who were able and at
home for those who were unable to attend the mobile
Weight and height were measured by two methods: self-
reported and clinically examined. Self-reported measures
included in the at home survey, and clinical measurements
were collected at the clinical examination. Respondents
were asked, “How much do you weigh without clothes and
shoes,” and “How tall are you without shoes” (15). These
self-reported values were recorded in inch and pound units
and converted to metric units. Subsequently, trained health
technicians measured the weight and height of those partic-
ipants who attended the clinical examination, as described
previously (15). Height was measured to the nearest milli-
meter using a fixed stadiometer. Body weight was measured
in kilograms (to the second decimal place) by a self-zeroing
digital weight scale for adults dressed in underpants, a
disposable paper gown, paper pants, and foam slippers. A
Toledo 2181 self-zeroing digital weight scale (Toledo
Scale, Columbus, OH) was used at the mobile examination
center, and a SECA Integra Model 815 Scale (SECA, Ru-
mily, France) was used for the home examination. Both
scales were standardized (15). Measured values refer to
weight and height measured by a physician during the
For the first time in a NHANES study, bioelectrical
impedance resistance measures were also taken during the
clinical examination. To obtain PBF through BIA, patients
were instructed to lie on their backs while electrodes were
placed on their wrists and ankles. These electrodes delivered
a low-level alternating current (?1 mA) measured at dis-
tinct frequencies between 5 KHz and 1 MHz (15). PBF from
BIA was used as a measure of body fat composition that
may not be captured through BMI measures. PBF was
calculated using prediction equations (14). First fat-free
mass (FFM) was calculated through the Deurenberg predic-
tion equation (17):
FFM ? 0.672 ? 104Ht2(m)/BIA ? 3.1 Sex ? 3.9
(where M ? 1, F ? 0)
Total body fat (TBF) was defined as the difference between
weight and FFM. Finally, PBF was calculated as the ratio of
TBF to weight (kg).
PBF ? (Wt ? FFM)/Wt ? TBF/Wt
Those participating in the survey portion of NHANES III
were not told that they might be weighed and measured later
during the clinical examination. Blinding the participants to
the fact that they would later be clinically measured helps
ensure that the self-reported measures will be more similar
to self-reported weight and height collected in epidemiolog-
1Nonstandard abbreviations: NHANES III, National Health and Nutirtion Education Study
III; BIA, bioelectrical impedance analysis; PBF, percent body fat; FFM, fat-free mass; TBF,
total body fat; FBG, fasting blood levels of glucose; TG, triglyceride; HDLC, high-density
lipoprotein-cholesterol; SBP, systolic blood pressure; CRP, C-reactive protein; LEP, leptin;
CI, confidence interval.
Validity of Self-reported BMI, McAdams, Van Dam, and Hu
OBESITY Vol. 15 No. 1 January 2007 189
measures of weight and height were taken in close proxim-
ity to the measured values but were obtained without the
participants knowing they would subsequently be mea-
sured. Therefore, the self-reported values are similar to what
would be obtained in an epidemiological study with only
self-reported measures. Different biological measures
known to be predictive of obesity-related disorders were
used to examine the overall use of different anthropometric
measures. The blood levels of biomarkers such as FBG,
TGs, and HDLC, as well as SBP, reflect levels of adiposity
(24), which makes these variables useful to compare the
performance of different anthropometric measures (25).
This study suggests that self-reported BMI can provide
sufficiently accurate information in epidemiological studies
in which the primary outcomes are disease biomarkers or
obesity-related diseases. PBF calculated through BIA was
not superior to BMI as a predictor of biological markers
known to be associated with adiposity and risk for obesity-
related diseases. Although we found self-reported BMI to
be highly correlated with measured BMI, some underesti-
mation of true BMI occurs when BMI is based on self-
reports. We therefore conclude that in most epidemiological
studies of adiposity-related conditions, using self-reported
BMI will produce minimal bias for the measure of associ-
ation, although it can lead to some underestimation of the
population prevalence of obesity.
We thank those who dedicated their time to designing and
implementing NHANES III. Dr. Hu’s research is supported,
in part, by an American Heart Association Established In-
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