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1.  Validation of self-reported height and weight in fifth-grade Korean children 
Nutrition Research and Practice  2013;7(4):326-329.
Height and weight are important indicators to calculate Body Mass Index (BMI); measuring height and weight directly is the most exact method to get this information. However, it is ineffective in terms of cost and time on large population samples. The aim of our study was to investigate the validity of self-reported height and weight data compared to our measured data in Korean children to predict obese status. Four hundred twenty-two fifth-grade (mean age 10.5 ± 0.5 years) children who had self-reported and measured height and weight data were final subjects for this study. Overweight/obese was defined as a BMI of or above the 85th percentile of the gender-specific BMI for age in the 2007 Korean National Growth Charts or a BMI of 25 or higher (underweight : < 5th, normal : ≥ 5th to < 85th, overweight : ≥ 85th to < 95th). The differences between self-reported and measured data were tested using paired t-test. Differences based on overweight/obese status were tested using analysis of variance (ANOVA) and linear trends. Pearson's correlation and Cohen's kappa were tested to examine agreements between the self-reported and measured data. Although measured and self-reported height, weight and BMI were significantly different and children tended to overreport their height and underreport their weight, the correlation between the two methods of height, weight and BMI were high (r = 0.956, 0.969, 0.932, respectively; all P < 0.001), and both genders reported their overweight/non-overweight status accurately (Cohen's kappa = 0.792, P < 0.001). Although there were differences between the self-reported and our measured methods, the self-reported weight and height was valid enough to classify overweight/obesity status correctly, especially in non-overweight/obese children. Due to bigger underestimation of weight and overestimation of height in obese children, however, we need to be aware that the self-reported anthropometric data were less accurate in overweight/obese children than in non-overweight/obese children.
PMCID: PMC3746168  PMID: 23964321
Self-report; measure; height; weight; children
2.  Agreement between self-reported and measured weight and height collected in general practice patients: a prospective study 
Self-reported weight and height is frequently used to quantify overweight and obesity. It is however, associated with limitations such as bias and poor agreement, which may be a result of social desirability or difficulties with recall. Methods to reduce these biases would improve the accuracy of assessment of overweight and obesity using patient self-report. The level of agreement between self-reported and measured weight and height has not been widely examined in general practice patients.
Consenting patients, presenting for care within four hour sessions, were randomly allocated to the informed or uninformed group. Participants were notified either a) prior to (informed group), or b) after (uninformed group) reporting their weight and height using a touchscreen computer questionnaire, that they would be measured. The differences in accuracy of self-report between the groups were examined by comparing mean differences, intraclass correlations (ICCs), Bland Altman plot with limits of agreement (LOAs) and Cohen’s kappa. Overall agreement was assessed using similar statistical methods.
Of consenting participants, 32% were aged between 18–39 years, 42% between 40–64 years and 25% were 65 years and above. The informed group (n = 172) did not report their weight and height more accurately than the uninformed group (n = 160). Mean differences between self-reported and measured weight (p = 0.4004), height (p = 0.5342) and body mass index (BMI) (p = 0.4409) were not statistically different between the informed and uninformed group. Overall, there were small mean differences (−1.2 kg for weight, 0.8 for height and −0.6 kg/m2 for BMI) and high ICCs (>0.9) between self-reported and measured values. A substantially high kappa (0.70) was obtained when using self-reported weight and height relative to measured values to quantify the proportion underweight, normal weight, overweight or obese. While the average bias of self-reported weight and height as estimates of the measured quantities is small, the LOAs indicate that substantial discrepancies occur at the individual level.
Informing patients that their weight and height would be measured did not improve accuracy of reporting. The use of self-reported weight and height for surveillance studies in this setting appears acceptable; however this measure needs to be interpreted with care when used for individual patients.
PMCID: PMC3599990  PMID: 23510189
Obesity; Family practice; Weight
3.  Accuracy of self-reported body weight, height and waist circumference in a Dutch overweight working population 
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.
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.
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.
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
PMCID: PMC2605752  PMID: 18957077
4.  Validity of Self-Reported Weight and Height of Adolescents, Its Impact on Classification into BMI-Categories and the Association with Weighing Behaviour 
This paper investigated the validity of self-reported height and weight of adolescents for the diagnosis of underweight, overweight and obesity and the influence of weighing behaviour on the accuracy. A total of 982 adolescents reported their height, weight, weighing behaviour and eating patterns in a questionnaire. Afterwards, their height and weight were measured and their Body Mass Index (BMI)-categories were determined using age- and gender-specific BMI cut-off points. Both girls and boys underreported their weight, whilst height was overestimated by girls and underestimated by boys. Cohen’s d indicated that these misreportings were in fact trivial. The prevalence of underweight was overestimated when using the self-reported BMI for classification, whilst the prevalence of overweight and obesity was underestimated. Gender and educational level influenced the accuracy of the adolescents’ self-reported BMI. Weighing behaviour only positively influenced the accuracy of the self-reported weight and not height or BMI. In summary, adolescents’ self-reported weight and height cannot replace measured values to determine their BMI-category, and thus the latter are highly recommended when investigating underweight, overweight and obesity in adolescents.
PMCID: PMC2790101  PMID: 20054463
height; weight; body mass index; validity; adolescents; weighing behaviour
5.  Validity of Web-Based Self-Reported Weight and Height: Results of the Nutrinet-Santé Study 
With the growing scientific appeal of e-epidemiology, concerns arise regarding validity and reliability of Web-based self-reported data.
The objectives of the present study were to assess the validity of Web-based self-reported weight, height, and resulting body mass index (BMI) compared with standardized clinical measurements and to evaluate the concordance between Web-based self-reported anthropometrics and face-to-face declarations.
A total of 2513 participants of the NutriNet-Santé study in France completed a Web-based anthropometric questionnaire 3 days before a clinical examination (validation sample) of whom 815 participants also responded to a face-to-face anthropometric interview (concordance sample). Several indicators were computed to compare data: paired t test of the difference, intraclass correlation coefficient (ICC), and Bland–Altman limits of agreement for weight, height, and BMI as continuous variables; and kappa statistics and percent agreement for validity, sensitivity, and specificity of BMI categories (normal, overweight, obese).
Compared with clinical data, validity was high with ICC ranging from 0.94 for height to 0.99 for weight. BMI classification was correct in 93% of cases; kappa was 0.89. Of 2513 participants, 23.5% were classified overweight (BMI≥25) with Web-based self-report vs 25.7% with measured data, leading to a sensitivity of 88% and a specificity of 99%. For obesity, 9.1% vs 10.7% were classified obese (BMI≥30), respectively, leading to sensitivity and specificity of 83% and 100%. However, the Web-based self-report exhibited slight underreporting of weight and overreporting of height leading to significant underreporting of BMI (P<.05) for both men and women: –0.32 kg/m2 (SD 0.66) and –0.34 kg/m2 (SD 1.67), respectively. Mean BMI underreporting was –0.16, –0.36, and –0.63 kg/m2 in the normal, overweight, and obese categories, respectively. Almost perfect agreement (ie, concordance) was observed between Web-based and face-to-face report (ICC ranged from 0.96 to 1.00, classification agreement was 98.5%, and kappa 0.97).
Web-based self-reported weight and height data from the NutriNet-Santé study can be considered as valid enough to be used when studying associations of nutritional factors with anthropometrics and health outcomes. Although self-reported anthropometrics are inherently prone to biases, the magnitude of such biases can be considered comparable to face-to-face interview. Web-based self-reported data appear to be an accurate and useful tool to assess anthropometric data.
PMCID: PMC3742400  PMID: 23928492
anthropometry; body weight; obesity; self-report; weights and measures; validation studies
6.  Validity of self-reported height and weight among adolescents: the importance of reporting capability 
This study proposes a new approach for investigating bias in self-reported data on height and weight among adolescents by studying the relevance of participants’ self-reported response capability. The objectives were 1) to estimate the prevalence of students with high and low self-reported response capability for weight and height in a self-administrated questionnaire survey among 11–15 year old Danish adolescents, 2) to estimate the proportion of missing values on self-reported height and weight in relation to capability for reporting height and weight, and 3) to investigate the extent to which adolescents’ response capability is of importance for the accuracy and precision of self-reported height and weight. Also, the study investigated the impact of students’ response capability on estimating prevalence rates of overweight.
Data was collected by a school-based cross-sectional questionnaire survey among students aged 11–15 years in 13 schools in Aarhus, Denmark, response rate =89%, n = 2100. Response capability was based on students’ reports of perceived ability to report weight/height and weighing/height measuring history. Direct measures of height and weight were collected by school health nurses.
One third of the students had low response capability for weight and height, respectively, and every second student had low response capability for BMI. The proportion of missing values on self-reported weight and height was significantly higher among students who were not weighed and height measured recently and among students who reported low recall ability. Among both boys and girls the precision of self-reported height and weight tended to be lower than among students with low response capability. Low response capability was related to BMI (z-score) and overweight prevalence among girls. These findings were due to a larger systematic underestimation of weight among girls who were not weighed recently (−1.02 kg, p < 0.0001) and among girls with low recall ability for weight (−0.99 kg, p = 0.0024).
This study indicates that response capability may be relevant for the accuracy of girls’ self-reported measurements of weight and height. Consequently, by integrating items on response capability in survey instruments, participants with low capability can be identified. Similar analyses based on other and less selected populations are recommended.
PMCID: PMC3711890  PMID: 23805955
Height/weight; Self-reports; Validity; Response capability; Adolescents
7.  Accuracy and usefulness of BMI measures based on self-reported weight and height: findings from the NHANES & NHIS 2001-2006 
BMC Public Health  2009;9:421.
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.
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.
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.
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.
PMCID: PMC2784464  PMID: 19922675
8.  Measurement matters in the association between early adolescent depressive symptoms and body mass index 
General hospital psychiatry  2008;30(5):458-466.
To examine associations between depressive symptoms and body mass over one year during early adolescence and to assess how the associations might differ depending upon whether self-reported or directly measured height and weight were used.
Participants were 446 sixth-grade Seattle students. Depressive symptoms were assessed using the Mood and Feelings Questionnaire. Regression models were used to examine whether baseline depression status was associated with 12-month BMI (using self-reported height and weight), and whether baseline overweight status was associated with 12-month depressive symptom score. Analyses were re-run among a sub-sample (n = 165) who had height and weight directly measured.
Using BMI derived from self-reported values, depressed males had a significantly lower BMI than non-depressed males, while depressed females had a significantly higher BMI than non-depressed females, after adjusting for covariates. Among a sub-sample using measured height and weight values, however, depression was no longer associated with BMI in either gender. Baseline overweight status did not predict 12-month depression score.
Observed associations between depression and subsequent BMI were explained by differential misclassification of self-reported height and weight by depression status and gender. Direct measurement of height and weight may be necessary to ensure validity in studies of adolescent depression and weight-related outcomes.
PMCID: PMC2566776  PMID: 18774430
Depression; body mass; overweight/obesity; adolescence; differential misclassification
9.  Correction of Body-Mass Index Using Body-Shape Perception and Socioeconomic Status in Adolescent Self-Report Surveys 
PLoS ONE  2014;9(5):e96768.
To propose a simple correction of body-mass index (BMI) based on self-reported weight and height (reported BMI) using gender, body shape perception and socioeconomic status in an adolescent population.
341 boys and girls aged 17–18 years were randomly selected from a representative sample of 2165 French adolescents living in Paris surveyed in 2010. After an anonymous self-administered pen-and-paper questionnaire asking for height, weight, body shape perception (feeling too thin, about the right weight or too fat) and socioeconomic status, subjects were measured and weighed. BMI categories were computed according to Cole’s cut-offs. Reported BMIs were corrected using linear regressions and ROC analyses and checked with cross-validation and multiple imputations to handle missing values. Agreement between actual and corrected BMI values was estimated with Kappa indexes and Intraclass correlation coefficients (ICC).
On average, BMIs were underreported, especially among girls. Kappa indexes between actual and reported BMI were low, especially for girls: 0.56 95%CI = [0.42–0.70] for boys and 0.45 95%CI = [0.30–0.60] for girls. The regression of reported BMI by gender and body shape perception gave the most balanced results for both genders: the Kappa and ICC obtained were 0.63 95%CI = [0.50–0.76] and 0.67, 95%CI = [0.58–0.74] for boys; 0.65 95%CI = [0.52–0.78] and 0.74, 95%CI = [0.66–0.81] for girls. The regression of reported BMI by gender and socioeconomic status led to similar corrections while the ROC analyses were inaccurate.
Using body shape perception, or socioeconomic status and gender is a promising way of correcting BMI in self-administered questionnaires, especially for girls.
PMCID: PMC4028195  PMID: 24844229
10.  Accuracy and reliability of self-reported weight and height in the Sister Study 
Public health nutrition  2011;15(6):989-999.
To assess accuracy and reliability of self-reported weight and height and identify factors associated with reporting accuracy.
Analysis of self-reported and measured weight and height from participants in the Sister Study (2003–2009), a nationwide cohort of 50,884 women aged 35–74 in the United States with a sister with breast cancer.
Weight and height were reported via computer-assisted telephone interview (CATI) and self-administered questionnaires, and measured by examiners.
Early enrollees in the Sister Study. There were 18,639 women available for the accuracy analyses and 13,316 for the reliability analyses.
Using weighted kappa statistics, comparisons were made between CATI responses and examiner measures to assess accuracy and CATI and questionnaire responses to assess reliability. Polytomous logistic regression evaluated factors associated with over- or under-reporting. Compared to measured values, agreement was 96% for reported height (±1 inch; weighted kappa 0.84) and 67% for weight (±3 pounds; weighted kappa 0.92). Obese women [body mass index (BMI) ≥30 kg/m2)] were more likely than normal weight women to under-report weight by ≥5% and underweight women (BMI <18.5 kg/m2) were more likely to over-report. Among normal and overweight women (18.5 kgm2≤ BMI <30 kgm2), weight cycling and lifetime weight difference ≥50 pounds were associated with over-reporting.
U.S. women in the Sister Study were reasonably reliable and accurate in reporting weight and height. Women with normal-range BMI reported most accurately. Overweight and obese women and those with weight fluctuations were less accurate, but even among obese women, few under-reported their weight by >10%.
PMCID: PMC3511620  PMID: 22152926
self-report; weight; height; accuracy; reliability; women
11.  The Use of Stunkard’s Figure Rating Scale to Identify Underweight and Overweight in Chinese Adolescents 
PLoS ONE  2012;7(11):e50017.
To compare the performance of Stunkard’s current body size (CBS) with self-reported body mass index (BMI), waist circumference (WC) and waist to stature ratio (WSR) in predicting weight status in Chinese adolescents, and to determine the CBS cutoffs for overweight/obesity and underweight.
This cross-sectional study was conducted in a sample of 5,418 secondary school students (45.2% boys; mean age 14.7 years). Height and weight were measured by trained teachers or researchers. Subjects were classified as underweight, normal weight, or overweight/obese according to the International Obesity Task Force cutoffs. Subjects were asked to select the figure that best resembled their CBS on the Stunkard’s figure rating scale. Self-reported height, weight, WC and WSR were also obtained. The performance of CBS, self-reported BMI, WC and WSR as a weight status indicator was analysed by sex-specific receiver operating characteristic curves. The optimal CBS cutoffs for underweight and overweight/obesity were determined based on the Youden Index.
Principal Findings
Apart from self-reported BMI, CBS had the greatest area under curve (AUC) for underweight in boys (0.82) and girls (0.81). For overweight/obesity, CBS also had a greater AUC (0.85) than self-reported WC and WSR in boys, and an AUC (0.81) comparable to self-reported WC and WSR in girls. In general, CBS values of 3 and 5 appeared to be the optimal cutoffs for underweight and overweight/obesity, respectively, in different sex-age subgroups.
CBS is a potentially useful indicator to assess weight status of adolescents when measured and self-reported BMI are not available.
PMCID: PMC3506537  PMID: 23189177
12.  How Accurate is Web-Based Self-Reported Height, Weight, and Body Mass Index in Young Adults? 
Web-based approaches are an effective and convenient medium to deliver eHealth interventions. However, few studies have attempted to evaluate the accuracy of online self-reported weight, and only one has assessed the accuracy of online self-reported height and body mass index (BMI).
This study aimed to validate online self-reported height, weight, and calculated BMI against objectively measured data in young Australian adults.
Participants aged 18-35 years were recruited via advertisements on social media sites and reported their current height and weight as part of an online survey. They then subsequently had the same measures objectively assessed by a trained researcher.
Self-reported height was significantly overestimated by a mean of 1.36 cm (SD 1.93; P<.001), while self-reported weight was significantly underestimated by –0.55 kg (SD 2.03; P<.001). Calculated BMI was also underestimated by –0.56 kg/m2 (SD 0.08; P<.001). The discrepancy in reporting resulted in the misclassification of the BMI category of three participants. Measured and self-reported data were strongly positively correlated (height: r=.98, weight: r=.99, BMI: r=.99; P<.001). When accuracy was evaluated by BMI category and gender, weight remained significantly underreported by females (P=.002) and overweight/obese participants (P=.02).
There was moderate to high agreement between self-reported and measured anthropometric data. Findings suggest that online self-reported height and weight can be a valid method of collecting anthropometric data.
PMCID: PMC3906650  PMID: 24398335
Internet; height; weight; body mass index; self-report
13.  Anthropometric measurements and body silhouette of women: validity and perception 
To examine the validity of self-reported values for current anthropometric measurements and factors related to misreporting.
E3N, a prospective cohort study of cancer risk factors conducted in France, part of the European Prospective Investigation on Cancer. E3N comprises 100,000 women, born between 1925 and 1950, followed with self-administered questionnaires sent every 18 to 24 months starting in 1990.
152 women for the validation study of self-reported anthropometric measurements and 91,815 women selected to evaluate factors affecting misreporting of body silhouette.
Statistical analysis
Paired t tests, Pearson and Spearman correlations were applied to evaluate the validity of self-reported measures, and analysis of variance and logistic regression were used to assess the factors influencing misreporting silhouette.
The correlation coefficients between self- and external measurements were very high. All but sitting height (r=0.56) were more than 0.80, with weight and bust (nipples) measurements correlation coefficients attaining 0.94. The correlation between body mass index (BMI), measured by the technician and the self-reported silhouette, was 0.78. Small height was always associated with misclassification. Specific factors related to a more favorable perception of body silhouette were being overweight, small height, younger age and a lower level of education. These women were also more frequently unmarried, more physically active and had had a slender body shape during adolescence. Results denoting a less favorable perception of body shape were reversed.
Self-reported measurements (made with or without help) are valid measures in epidemiological studies. Body silhouettes are simple and useful indicators of body mass index. However they should be interpreted with caution in certain instances, especially for overweight subjects.
PMCID: PMC2020514  PMID: 12487540
Aged; Anthropometry; Body Height; Body Image; Body Mass Index; Body Weight; Educational Status; Europe; Female; Humans; Logistic Models; Middle Aged; Prospective Studies; Questionnaires; Reproducibility of Results; weight; height; body mass index; body silhouettes; anthropometric measurements
14.  Change in the Body Mass Index Distribution for Women: Analysis of Surveys from 37 Low- and Middle-Income Countries 
PLoS Medicine  2013;10(1):e1001367.
Using cross-sectional surveys, Fahad Razak and colleagues investigate how the BMI (body mass index) distribution is changing for women in low- and middle-income countries.
There are well-documented global increases in mean body mass index (BMI) and prevalence of overweight (BMI≥25.0 kg/m2) and obese (BMI≥30.0 kg/m2). Previous analyses, however, have failed to report whether this weight gain is shared equally across the population. We examined the change in BMI across all segments of the BMI distribution in a wide range of countries, and assessed whether the BMI distribution is changing between cross-sectional surveys conducted at different time points.
Methods and Findings
We used nationally representative surveys of women between 1991–2008, in 37 low- and middle-income countries from the Demographic Health Surveys ([DHS] n = 732,784). There were a total of 96 country-survey cycles, and the number of survey cycles per country varied between two (21/37) and five (1/37). Using multilevel regression models, between countries and within countries over survey cycles, the change in mean BMI was used to predict the standard deviation of BMI, the prevalence of underweight, overweight, and obese. Changes in median BMI were used to predict the 5th and 95th percentile of the BMI distribution. Quantile-quantile plots were used to examine the change in the BMI distribution between surveys conducted at different times within countries. At the population level, increasing mean BMI is related to increasing standard deviation of BMI, with the BMI at the 95th percentile rising at approximately 2.5 times the rate of the 5th percentile. Similarly, there is an approximately 60% excess increase in prevalence of overweight and 40% excess in obese, relative to the decline in prevalence of underweight. Quantile-quantile plots demonstrate a consistent pattern of unequal weight gain across percentiles of the BMI distribution as mean BMI increases, with increased weight gain at high percentiles of the BMI distribution and little change at low percentiles. Major limitations of these results are that repeated population surveys cannot examine weight gain within an individual over time, most of the countries only had data from two surveys and the study sample only contains women in low- and middle-income countries, potentially limiting generalizability of findings.
Mean changes in BMI, or in single parameters such as percent overweight, do not capture the divergence in the degree of weight gain occurring between BMI at low and high percentiles. Population weight gain is occurring disproportionately among groups with already high baseline BMI levels. Studies that characterize population change should examine patterns of change across the entire distribution and not just average trends or single parameters.
Please see later in the article for the Editors' Summary
Editors' Summary
The number of obese people (individuals who have an excessive amount of body fat) is rapidly increasing in many countries. Globally, there were about 200 million obese adults in 1995; by 2010, 475 million adults were obese and another billion were classified as overweight. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Compared to people with a healthy weight (a BMI between 18.5 and 24.9 kg/m2), obese individuals and overweight individuals (who have a BMI between 25.0 and 29.9 kg/m2) have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. At the same time in many developing countries substantial numbers of people are underweight (BMI <18.5 kg/m2) or have chronic energy deficiency (BMI <16.0 kg/m2) and are at risk of increased risk of dying due to infectious disease or respiratory problems.
Why Was This Study Done?
The global obesity epidemic is usually described in terms of increases in the average BMI or in the prevalence of obesity (the proportion of the population whose BMI is above 30.0 kg/m2). Such descriptions assume that the BMIs of fat and thin people are increasing at the same rate and that the shape of the population's BMI distribution curve remains constant. However, as average BMI and the prevalence of obesity can increase it is unclear how the prevalence of underweight changes. This is potentially important for the health of the population because underweight individuals, like obese individuals, tend to die younger than healthy weight individuals, particularly in low-income countries. In this study, the researchers use repeated cross-sectional survey data collected from low- and middle-income countries in the Demographic and Health Surveys (DHS) to examine changes in BMI in women across the BMI distribution between 1991 and 2008. Repeated cross-sectional surveys collect data from a population at multiple time points from different individuals drawn from the same population, DHS are a data collection and surveillance project that help developing countries track health and population trends.
What Did the Researchers Do and Find?
The researchers used statistical models to analyze data from DHS surveys of more than 730,000 women living in 37 low- and middle-income countries (two to five surveys per country). Increasing average BMI was associated with an increase in the standard deviation of BMI (a measure of the dispersion of BMI in the population) both across and within countries over time. With increasing average BMI, the BMI at both the 5th and 95th percentile increased; 90% of the BMIs in a population lie between these percentiles so these BMI values indicate the spread of the BMI distribution. However, the BMI at the 95th percentile increased about 2.5 times faster than the BMI at the 5th percentile. Moreover, with increasing average BMI, the prevalence of overweight and obesity increased faster than the decline in the prevalence of underweight. Finally, quantile-quantile plots for each country (a graphical method that compares two distributions) revealed a consistent pattern of unequal weight gain across the BMI distribution as average BMI increased, with pronounced weight gains at the obese end of the distribution and little change at the underweight end.
What Do These Findings Mean?
These findings show that increases in average BMI are associated with an increased spread of BMI across and within populations. Consequently, changes in average BMI or single measurements such as the prevalence of overweight do not capture the divergence in the degree of weight gain occurring between that part of the population that has a low BMI and that part that has a high BMI. In other words, at least for the low- and middle-income countries included in this study, population weight gain is occurring disproportionately among groups with high baseline BMI levels. The researchers suggest, therefore, that the characterization of the BMI of populations over time should examine the patterns of change across the whole BMI distribution. Moreover, rather than a single broad population strategy for weight control, optimum health outcomes, they suggest, might be achieved by a strategy that includes targeted interventions to reduce weight in high BMI segments of the population and to increase weight in low BMI segments.
Additional Information
Please access these Web sites via the online version of this summary at
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish)
The World Health Organization provides information on obesity (in several languages); Malri's story describes the health risks faced by an obese child
The UK National Health Service Choices website also provides detailed information about obesity and a link to a personal story about losing weight
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
MedlinePlus has links to further information about obesity (in English and Spanish)
PMCID: PMC3545870  PMID: 23335861
15.  Applying a correction procedure to the prevalence estimates of overweight and obesity in the German part of the HBSC study 
BMC Research Notes  2014;7:181.
Prevalence rates for overweight and obesity based on self-reported height and weight are underestimated, whereas the prevalence rate for underweight is slightly overestimated. Therefore a correction is needed. Aim of this study is to apply correction procedures to the prevalence rates developed on basis of (self-reported and measured) data from the representative German National Health Interview and Examination Survey for Children and Adolescents (KiGGS) to (self-reported) data from the German Health Behaviour in School Aged Children (HBSC) study to determine whether correction leads to higher prevalence estimates of overweight and obesity as well as lower prevalence rates for underweight.
BMI classifications based on self-reported and measured height and weight from a subsample of the KiGGS study (2,565 adolescents aged 11–15) were used to estimate two different correction formulas. The first and the second correction function are described. Furthermore, the both formulas were applied to the prevalence rates from the HBSC study (7,274 adolescents aged 11–15) which are based on self-reports collected via self-administered questionnaires.
After applying the first correction function to self-reported data of the HBSC study, the prevalence rates of overweight and obesity increased from 5.5% to 7.8% (compared to 10.4% in the KiGGS study) and 2.7% to 3.8% (compared to 7.8% in the KiGGS study), respectively, whereas the corrected prevalence rates of underweight and severe underweight decreased from 8.0% to 6.7% (compared to 5.7% in the KiGGS study) and from 5.5% to 3.3% (compared to 2.4% in the KiGGS study), respectively. Application of the second correction function, which additionally considers body image, led to further slight corrections with an increase of the prevalence rates for overweight to 7.9% and for obese to 3.9%.
Subjective BMI can be used to determine the prevalence of overweight and obesity among children and adolescents. Where there is evidence of bias, the prevalence estimates should be corrected using conditional probabilities that link measured and subjectively assessed BMI from a representative validation study. These corrections may be improved further by considering body image as an additional influential factor.
PMCID: PMC3986913  PMID: 24670124
Prevalence rates weight status; Self-reports; Corrected prevalence rates; Overweight; Body image
16.  Validity of Self-Reported Height and Weight in a Korean Population 
Journal of Epidemiology  2011;21(1):30-36.
Accessible public information on self-reported height and weight is not widely used in studies of obesity, mainly because of the questionable validity of body mass index (BMI) values calculated from these data. To assess the utility of self-reported measurement, we compared self-reported and standard measurements of height and weight in a Korean population that is leaner than Western populations.
A cross-sectional comparison of self-reported and measured height and weight was conducted among a population of participants in a cancer screening program. A total of 557 men and 1010 women aged 30 to 70 years were included in the current analysis.
Self-reported height was higher than measured values in both men and women. Self-reported weight was higher than measured weight in women, but was not different in men. BMI calculated from measured values was higher than BMI derived from self-reported height and weight among men. Younger age was a predictor of accuracy in self-reported height, and higher weight and BMI were predictors of under-reporting of weight. The prevalence of obesity based on self-reported values was lower than the true prevalence of obesity. With respect to classifying individuals as obese, the specificity and sensitivity of BMI calculated from self-reported values were very high for both sexes.
Self-reported height and weight were reasonably valid in this study population.
PMCID: PMC3899514  PMID: 20953091
validity; height; weight; body mass index; self-report
17.  Validity of instruction leaflets for parents to measure their child's weight and height at home: results obtained from a randomised controlled trial 
BMJ Open  2014;4(2):e003768.
To compare the validity of parent-reported height, weight and body mass index (BMI) values of children (aged 4–10 years), when measured at home by means of newly developed instruction leaflets in comparison with simple estimated parental reports.
Randomised controlled trial with control and intervention group using simple randomisation.
Belgian children and their parents recruited via schools (multistage cluster sampling design).
164 Belgian children (53% male; participation rate 62%).
Parents completed a questionnaire including questions about the height and weight of their child. Parents in the intervention group received instruction leaflets to measure their child's weight and height. Classes were randomly allocated to the intervention and control groups. Nurses measured height and weight following standardised procedures up to 2 weeks after parental reports.
Outcome measures
Weight, height and BMI category of the child were derived from the index measurements and the parental reports.
Mean parent-reported weight was slightly more underestimated in the intervention group than in the control group relative to the index weights. However, for all three parameters (weight, height and BMI), correlations between parental reports and nurse measurements were higher in the intervention group. Sensitivity for underweight and overweight/obesity was respectively, 75% and 60% in the intervention group, and 67% and 43% in the control group. Weighed κ for classifying children in the correct BMI category was 0.30 in the control group and was 0.51 in the intervention group.
Although mean parent-reported weight was slightly more underestimated in the intervention than in the control group, correlations were higher and there was considerably less misclassification into valid BMI categories for the intervention group. This pattern suggests that most of the parental deviations from the index measurements were probably due to random errors of measurement and that diagnostic measures could improve by encouraging parents to measure their children's weight and height at home by means of instruction leaflets.
PMCID: PMC3918984  PMID: 24508849
Nutrition & Dietetics; Paediatrics; Preventive Medicine; Public Health; Statistics & Research Methods
18.  Physical Activity Attenuates the Genetic Predisposition to Obesity in 20,000 Men and Women from EPIC-Norfolk Prospective Population Study 
PLoS Medicine  2010;7(8):e1000332.
Shengxu Li and colleagues use data from a large prospective observational cohort to examine the extent to which a genetic predisposition toward obesity may be modified by living a physically active lifestyle.
We have previously shown that multiple genetic loci identified by genome-wide association studies (GWAS) increase the susceptibility to obesity in a cumulative manner. It is, however, not known whether and to what extent this genetic susceptibility may be attenuated by a physically active lifestyle. We aimed to assess the influence of a physically active lifestyle on the genetic predisposition to obesity in a large population-based study.
Methods and Findings
We genotyped 12 SNPs in obesity-susceptibility loci in a population-based sample of 20,430 individuals (aged 39–79 y) from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with an average follow-up period of 3.6 y. A genetic predisposition score was calculated for each individual by adding the body mass index (BMI)-increasing alleles across the 12 SNPs. Physical activity was assessed using a self-administered questionnaire. Linear and logistic regression models were used to examine main effects of the genetic predisposition score and its interaction with physical activity on BMI/obesity risk and BMI change over time, assuming an additive effect for each additional BMI-increasing allele carried. Each additional BMI-increasing allele was associated with 0.154 (standard error [SE] 0.012) kg/m2 (p = 6.73×10−37) increase in BMI (equivalent to 445 g in body weight for a person 1.70 m tall). This association was significantly (pinteraction = 0.005) more pronounced in inactive people (0.205 [SE 0.024] kg/m2 [p = 3.62×10−18; 592 g in weight]) than in active people (0.131 [SE 0.014] kg/m2 [p = 7.97×10−21; 379 g in weight]). Similarly, each additional BMI-increasing allele increased the risk of obesity 1.116-fold (95% confidence interval [CI] 1.093–1.139, p = 3.37×10−26) in the whole population, but significantly (pinteraction = 0.015) more in inactive individuals (odds ratio [OR] = 1.158 [95% CI 1.118–1.199; p = 1.93×10−16]) than in active individuals (OR = 1.095 (95% CI 1.068–1.123; p = 1.15×10−12]). Consistent with the cross-sectional observations, physical activity modified the association between the genetic predisposition score and change in BMI during follow-up (pinteraction = 0.028).
Our study shows that living a physically active lifestyle is associated with a 40% reduction in the genetic predisposition to common obesity, as estimated by the number of risk alleles carried for any of the 12 recently GWAS-identified loci.
Please see later in the article for the Editors' Summary
Editors' Summary
In the past few decades, the global incidence of obesity—defined as a body mass index (BMI, a simple index of weight-for-height that uses the weight in kilograms divided by the square of the height in meters) of 30 and over, has increased so much that this growing public health concern is now commonly referred to as the “obesity epidemic.” Once considered prevalent only in high-income countries, obesity is an increasing health problem in low- and middle-income countries, particularly in urban settings. In 2005, at least 400 million adults world-wide were obese, and the projected figure for 2015 is a substantial increase of 300 million to around 700 million. Childhood obesity is also a growing concern. Contributing factors to the obesity epidemic are a shift in diet to an increased intake of energy-dense foods that are high in fat and sugars and a trend towards decreased physical activity due to increasingly sedentary lifestyles.
However, genetics are also thought to play a critical role as genetically predisposed individuals may be more prone to obesity if they live in an environment that has abundant access to energy-dense food and labor-saving devices.
Why Was This Study Done?
Although recent genetic studies (genome-wide association studies) have identified 12 alleles (a DNA variant that is located at a specific position on a specific chromosome) associated with increased BMI, there has been no convincing evidence of the interaction between genetics and lifestyle. In this study the researchers examined the possibility of such an interaction by assessing whether individuals with a genetic predisposition to increased obesity risk could modify this risk by increasing their daily physical activity.
What Did the Researchers Do and Find?
The researchers used a population-based cohort study of 25,631 people living in Norwich, UK (The EPIC-Norfolk study) and identified individuals who were 39 to 79 years old during a health check between 1993 and 1997. The researchers invited these people to a second health examination. In total, 20,430 individuals had baseline data available, of which 11,936 had BMI data at the second health check. The researchers used genotyping methods and then calculated a genetic predisposition score for each individual and their occupational and leisure-time physical activities were assessed by using a validated self-administered questionnaire. Then, the researchers used modeling techniques to examine the main effects of the genetic predisposition score and its interaction with physical activity on BMI/obesity risk and BMI change over time. The researchers found that each additional BMI-increasing allele was associated with an increase in BMI equivalent to 445 g in body weight for a person 1.70 m tall and that the size of this effect was greater in inactive people than in active people. In individuals who have a physically active lifestyle, this increase was only 379 g/allele, or 36% lower than in physically inactive individuals in whom the increase was 592 g/allele. Furthermore, in the total sample each additional obesity-susceptibility allele increased the odds of obesity by 1.116-fold. However, the increased odds per allele for obesity risk were 40% lower in physically active individuals (1.095 odds/allele) compared to physically inactive individuals (1.158 odds/allele).
What Do These Findings Mean?
The findings of this study indicate that the genetic predisposition to obesity can be reduced by approximately 40% by having a physically active lifestyle. The findings of this study suggest that, while the whole population benefits from increased physical activity levels, individuals who are genetically predisposed to obesity would benefit more than genetically protected individuals. Furthermore, these findings challenge the deterministic view of the genetic predisposition to obesity that is often held by the public, as they show that even the most genetically predisposed individuals will benefit from adopting a healthy lifestyle. The results are limited by participants self-reporting their physical activity levels, which is less accurate than objective measures of physical activity.
Additional Information
Please access these Web sites via the online version of this summary at
This study relies on the results of previous genome-wide association studies The National Human Genome Research Institute provides an easy-to-follow guide to understanding such studies
The International Association for the Study of Obesity aims to improve global health by promoting the understanding of obesity and weight-related diseases through scientific research and dialogue
The International Obesity Taskforce is the research-led think tank and advocacy arm of the International Association for the Study of Obesity
The Global Alliance for the Prevention of Obesity and Related Chronic Disease is a global action program that addresses the issues surrounding the prevention of obesity
The National Institutes of Health has its own obesity task force, which includes 26 institutes
PMCID: PMC2930873  PMID: 20824172
19.  Comparison of BMI Derived from Parent-Reported Height and Weight with Measured Values: Results from the German KiGGS Study 
The use of parent-reported height and weight is a cost-efficient instrument to assess the prevalence of children’s weight status in large-scale surveys. This study aimed to examine the accuracy of BMI derived from parent-reported height and weight and to identify potential predictors of the validity of BMI derived from parent-reported data. A subsample of children aged 2–17 years (n = 9,187) was taken from the 2003–2006 cross-sectional German KiGGS study. Parent-reported and measured height and weight were collected and BMI was calculated. Besides descriptive analysis, linear regression models with BMI difference and logistic regression models with weight status misclassification as dependent variables were calculated. Height differences varied by gender and were generally small. Weight and BMI were under-reported in all age groups, the under-reporting getting stronger with increasing age. Overall, the proportion for overweight and obesity based on parental and measured reports differed slightly. In the youngest age group, the proportion of overweight children was overestimated, while it was underestimated for older children and adolescents. Main predictors of the difference between parent reported and measured values were age, gender, weight status and parents’ perception of the child’s weight. In summary, the exclusive use of uncorrected parental reports for assessment of prevalence rates of weight status is not recommended.
PMCID: PMC3315268  PMID: 22470314
children and adolescents; parental reports; height; weight; BMI; overweight
20.  Measuring the accuracy of self-reported height and weight in a community-based sample of young people 
Self-reported anthropometric data are commonly used to estimate prevalence of obesity in population and community-based studies. We aim to: 1) Determine whether survey participants are able and willing to self-report height and weight; 2) Assess the accuracy of self-reported compared to measured anthropometric data in a community-based sample of young people.
Participants (16–29 years) of a behaviour survey, recruited at a Melbourne music festival (January 2011), were asked to self-report height and weight; researchers independently weighed and measured a sub-sample. Body Mass Index was calculated and overweight/obesity classified as ≥25kg/m2. Differences between measured and self-reported values were assessed using paired t-test/Wilcoxon signed ranks test. Accurate report of height and weight were defined as <2cm and <2kg difference between self-report and measured values, respectively. Agreement between classification of overweight/obesity by self-report and measured values was assessed using McNemar’s test.
Of 1405 survey participants, 82% of males and 72% of females self-reported their height and weight. Among 67 participants who were also independently measured, self-reported height and weight were significantly less than measured height (p=0.01) and weight (p<0.01) among females, but no differences were detected among males. Overall, 52% accurately self-reported height, 30% under-reported, and 18% over-reported; 34% accurately self-reported weight, 52% under-reported and 13% over-reported. More females (70%) than males (35%) under-reported weight (p=0.01). Prevalence of overweight/obesity was 33% based on self-report data and 39% based on measured data (p=0.16).
Self-reported measurements may underestimate weight but accurately identified overweight/obesity in the majority of this sample of young people.
PMCID: PMC3561081  PMID: 23170838
Body height; Body weight; Body mass index; Overweight; Obesity self-report; Validity; Young people
21.  Glycolipid metabolic status of overweight/obese adolescents aged 9- to 15-year-old and the BMI-SDS/BMI cut-off value of predicting dyslipidemiain boys, Shanghai, China: a cross-sectional study 
The prevalence of adolescents’ obesity and overweight has dramatically elevated in China. Obese children were likely to insulin resistance and dyslipidemia, which are risk factors of cardiovascular diseases. However there was no cut-off point of anthropometric values to predict the risk factors in Chinese adolescents. The present study was to investigate glycolipid metabolism status of adolescents in Shanghai and to explore the correlations between body mass index standard deviation score (BMI-SDS) and metabolic indices, determine the best cut-off value of BMI-SDS to predict dyslipidemia.
Fifteen schools in Shanghai’s two districts were chosen by cluster sampling and primary screening was done in children aged 9-15 years old. After screening of bodyweight and height, overweight and obese adolescents and age-matched children with normal body weight were randomly recruited in the study. Anthropometric measurements, biochemical measurements of glycolipid profiles were done. SPSS19.0 was used to analyze the data. Receiver operating characteristic (ROC) curves were made and the best cut-off values of BMI-SDS to predict dyslipidemia were determined while the Youden indices were maximum.
Five hundred and thirty-eight adolescents were enrolled in this research, among which 283 have normal bodyweight, 115 were overweight and 140 were obese. No significant differences of the ages among 3 groups were found. There were significant differences of WC-SDS (p<0.001), triacylglycerol (p<0.05), high and low density lipoprotein cholesterol (p<0.01), fasting insulin (p<0.01) and C-peptide (p<0.001) among 3 groups. Significant difference of fasting glucose was only found between normal weight and overweight group. Significant difference of total cholesterol was found between obese and normal weight group. There was no significant difference of glycated hemoglobin among 3 groups. The same tendency was found in boys but not in girls. Only HDL-C reduced and TG increased while BMI elevated in girls. The best cut-off value of BMI-SDS was 1.22 to predict dyslipidemia in boys. The BMI cut-off was 21.67 in boys.
Overweight and obese youths had reduced insulin sensitivity and high prevalence of dyslipidemia.When BMI-SDS elevated up to 1.22 and BMI was higher than 21.67 in boys, dyslipidemia may happen.
PMCID: PMC3766195  PMID: 23984682
Adolescents; Children; Lipid metabolism; Obesity; Overweight; BMI-SDS; China
22.  Validity of a self-reported measure of familial history of obesity 
Nutrition Journal  2008;7:27.
Familial history information could be useful in clinical practice. However, little is known about the accuracy of self-reported familial history, particularly self-reported familial history of obesity (FHO).
Two cross-sectional studies were conducted. The aims of study 1 was to compare self-reported and objectively measured weight and height whereas the aims of study 2 were to examine the relationship between the weight and height estimations reported by the study participants and the values provided by their family members as well as the validity of a self-reported measure of FHO. Study 1 was conducted between 2004 and 2006 among 617 subjects and study 2 was conducted in 2006 among 78 participants.
In both studies, weight and height reported by the participants were significantly correlated with their measured values (study 1: r = 0.98 and 0.98; study 2: r = 0.99 and 0.97 respectively; p < 0.0001). Estimates of weight and height for family members provided by the study participants were strongly correlated with values reported by each family member (r = 0.96 and 0.95, respectively; p < 0.0001). Substantial agreement between the FHO reported by the participants and the one obtained by calculating the BMI of each family members was observed (kappa = 0.72; p < 0.0001). Sensitivity (90.5%), specificity (82.6%), positive (82.6%) and negative (90.5%) predictive values of FHO were very good.
A self-reported measure of FHO is valid, suggesting that individuals are able to detect the presence or the absence of obesity in their first-degree family members.
PMCID: PMC2543037  PMID: 18783616
23.  Self-Reported Versus Measured Height and Weight in Hispanic and Non-Hispanic Menopausal Women 
Journal of Women's Health  2011;20(4):599-604.
Height and weight information is commonly used in clinical trials and in making therapeutic decisions in medical practice. In both settings, the data are often obtained by self-report. If erroneous, this practice could lead to inaccuracies in estimating renal function and medication doses or to inaccurate outcomes of research studies. Previous publications have reported lack of reliability of self-reported weight and height in the general population but have not addressed age-specific and ethnicity-specific subgroups in the U.S. population. The inaccuracy of self-reported weight and height could be particularly significant in times of considerable changes in body weight, such as at menopause, which is often associated with weight gain.
We assessed the validity of self-reported height and weight in 428 women within the first 5 years of menopause, 70.6% of whom were Hispanic.
Participants overestimated their height by 2.2±3.5 cm (mean±standard deviation [SD]) and underestimated their weight by 1.5±2.9 kg. As a group, based on self-reported measures, 33.3% were misclassified with respect to body mass index (BMI) category, and the difference between measured BMI and self-reported BMI was similar between Hispanic white and non-Hispanic white women, positively related to measured weight, and inversely related to measured height, years from menopause, and multiple parity.
From the public health perspective, inaccurate self-report could lead to a considerable underestimation of the current obesity prevalence rates. In our study population, the prevalence of obesity (BMI ≥30 kg/m2) was 6.3% based on self-reported values and 18% based on measured height and weight, representing a 3-fold underestimation.
PMCID: PMC3115416  PMID: 21413893
24.  Accuracy of the estimated prevalence of obesity from self reported height and weight in an adult Scottish population 
STUDY OBJECTIVE—To determine whether self reported heights and weights from Scottish adults can provide an accurate assessment of obesity prevalence in the population.
DESIGN—Standardised clinic measurements of weight and height were compared against self reported values on a postal questionnaire in the fourth Scottish MONICA cross sectional study.
SETTING—A sex and five year age band stratified random population sample drawn from general practitioner registers in north Glasgow in 1995. Response rate 63% for men and 62% for women.
PARTICIPANTS—A total of 865 men and 971 women aged between 25 and 64 years.
RESULTS—Men and women under-reported their weight by a mean (SD) of 0.63 (3.45) kg and 0.95 (2.64) kg respectively, and their height by a mean (SD) of 1.3 (2.50) cm and 1.7 (2.37) cm respectively. Estimated body mass index, BMI (kg/m2) varied from true (measured) BMI by +0.19 (1.40) for men and by +0.17 (1.34) for women. The only age/sex group in which BMI was under-estimated from self reports (mean 0.2) was the 55-64 year old women. Prediction equations that explained 90% (men) and 88% (women) of the difference between self reported and measured height included age and self reported weight. The equivalent prediction equations for weight explained 93% of the difference between self reported and measured weight for men and included smoking and diabetic status, while for women 96% of the variance was explained with no further variables being significant. Sensitivity and specificity for determining clinical obesity (BMI⩾30) were 83% and 96% respectively for men, and 89% and 97% for women.
CONCLUSIONS—This Scottish population was unique in the under-reporting of height as well as weight, which resulted in BMI estimates with low error. These data suggest that self reported weights and heights would be satisfactory for the monitoring of obesity prevalence in Scotland.

Keywords: obesity measurement; obesity prevalence; self reports
PMCID: PMC1731630  PMID: 10715748
25.  Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: the Third National Health and Nutrition Examination Survey 
Nutrition Journal  2005;4:27.
Few data have been published on the validity of classification of overweight and obesity based on self-reported weight in representative samples of Hispanic as compared to other American populations despite the wide use of such data.
To test the null hypothesis that ethnicity is unrelated to bias of mean body mass index (BMI) and to sensitivity of overweight or obesity (BMI >= 25 kg/m2) derived from self-reported (SR) versus measured weight and height using measured BMI as the gold standard.
Cross-sectional survey of a large national sample, the Third National Health and Nutrition Examination Survey (NHANES III) conducted in 1988–1994.
American men and women aged 20 years and over (n = 15,025).
SR height, weight, cigarette smoking, health status, and socio-demographic variables from home interview and measured weight and height.
In women and Mexican American (MA) men SR BMI underestimated true prevalence rates of overweight or obesity. For other men, no consistent difference was seen. Sensitivity of SR was similar in non-Hispanic European Americans (EA) and non-Hispanic African Americans (AA) but much lower in MA. Prevalence of obesity (BMI >= 30 kg/m2) is consistently underestimated by self-report, the gap being greater for MA than for other women, but similar for MA and other men. The mean difference between self-reported and measured BMI was greater in MA (men -0.37, women -0.76 kg/m2) than in non-Hispanic EA (men -0.22, women -0.62 kg/m2). In a regression model with the difference between self-reported and measured BMI as the dependent variable, MA ethnicity was a significant (p < 0.01) predictor of the difference in men and in women. The effect of MA ethnicity could not be explained by socio-demographic variables, smoking or health status.
Under-estimation of the prevalence of overweight or obesity based on height and weight self-reported at interview varied significantly among ethnic groups independent of other variables.
PMCID: PMC1262765  PMID: 16209706
Overweight; Obesity; Hispanics; Mexican Americans; Body weight; Blacks

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