Warning: fopen(/home/virtual/epih/journal/upload/ip_log/ip_log_2024-03.txt): failed to open stream: Permission denied in /home/virtual/lib/view_data.php on line 83 Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 84 Differences in accuracy of height, weight, and body mass index between self-reported and measured using the 2018 Korea Community Health Survey data
Skip Navigation
Skip to contents

Epidemiol Health : Epidemiology and Health

OPEN ACCESS
SEARCH
Search

Articles

Page Path
HOME > Epidemiol Health > Volume 44; 2022 > Article
Original Article
Differences in accuracy of height, weight, and body mass index between self-reported and measured using the 2018 Korea Community Health Survey data
Yoonsil Ko1orcid, Sunhye Choi1orcid, Jisoo Won1orcid, Yeon-Kyeng Lee2orcid, Dong-Hyun Kim3orcid, Seon Kui Lee1orcid
Epidemiol Health 2022;44:e2022024.
DOI: https://doi.org/10.4178/epih.e2022024
Published online: February 19, 2022

1Division of Chronic Disease Control, Bureau of Chronic Disease Prevention and Control, Korea Disease Control and Prevention Agency, Cheongju, Korea

2Division of Healthcare Association Infection Control, Bureau of Healthcare Safety and Immunization, Korea Disease Control and Prevention Agency, Cheongju, Korea

3Department of Social and Preventive Medicine, Hallym University College of Medicine, Graduate School of Public Health, Chuncheon, Korea

Correspondence: Seon Kui Lee Division of Chronic Disease Control, Bureau of Chronic Disease Prevention and Control, Korea Disease Control and Prevention Agency, 187 Osongsaengmyeong 2-ro, Heungduk-gu, Cheongju 28159, Korea E-mail: byuly74@korea.kr
• Received: September 6, 2021   • Accepted: December 15, 2021

©2022, Korean Society of Epidemiology

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 8,917 Views
  • 391 Download
  • 8 Web of Science
  • 5 Crossref
  • 4 Scopus
  • OBJECTIVES
    This study aimed to determine an effective survey method for the accurate calculation of obesity prevalence by comparing the self-reported and measured height, weight, and body mass index (BMI) using the 2018 Korea Community Healthy Survey (CHS) data.
  • METHODS
    Raw data from the 2018 CHS were used to analyze the differences, correlation, and agreement between self-reported and measured height, weight, and BMI.
  • RESULTS
    The self-reported height was over-reported than the measured height (0.59 cm greater for men and 0.71 cm greater for women), while the self-reported weight was under-reported than the measured weight (0.55 kg less for men and 0.67 kg less for women). Subsequently, the self-reported BMI was under-estimated (0.35 kg/m2 lower for men and 0.49 kg/m2 lower for women) compared with the measured BMI. The kappa statistic and agreement between measured and self-reported values per BMI category (underweight, normal, overweight, and obesity) were 0.82 and 79.6%, respectively.
  • CONCLUSIONS
    The prevalence of obesity should be calculated using the measured values provided in the CHS in order to promote local health projects based on accurate evidence.
Overweight and obesity are defined as abnormal or excessive accumulation of fat that may impair one’s health [1]. In general, obesity is indirectly measured based on the body mass index (BMI, kg/m2), which is calculated as weight in kilograms divided by height in meters squared. BMI is used to classify overweight (≥ 25 kg/m2) and obesity (≥ 30 kg/m2) in adults.
As of 2016, more than 1.9 billion adults worldwide aged ≥ 18 years were overweight, and more than 650 million of them, accounting for 13% of the world’s adult population, were obese (men: 11%, women: 15%). This number has increased almost three-fold compared with that reported in 1975 [1]. In Korea, as of 2019, the prevalence of obesity among adults (BMI ≥ 25 kg/m2) was 33.8% (≥ 19 years old, standardized), showing a continuous increase [2]. Obesity is a key risk factor for the development of non-communicable diseases such as type 2 diabetes, cardiovascular disease, hypertension, stroke, and various cancers, and the comorbidities of obesity not only increases the socioeconomic burden, but also decreases the quality of life [3]. The World Health Organization announced the “Global strategy on diet, physical activity, and health” during the 57th Annual Meeting in 2004. This agency is making continuous efforts to prevent and manage obesity, a global health problem [4]. As obesity is a preventable disease [1], continuous policies should be established to investigate the exact prevalence of obesity, and effective preventive strategies should be implemented.
In Korea, the National Health and Nutrition Examination Survey (NHANES) and Community Health Survey (CHS) were conducted to assess the regional and national prevalence of obesity. The data obtained from these surveys were used as evidence for the establishment and evaluation of the national and local government policies to prevent and manage obesity. In the NHANES, the prevalence of obesity was calculated by measuring the height and weight of 10,000 individuals. The CHS targeted 230,000 individuals in order to calculate the self-reported obesity rate since 2008 due to convenience and cost. However, in 2018, body measurements were obtained to calculate the prevalence of obesity.
According to several previous studies, BMI measurements based on self-reported data were used instead of the actual measurements in many large-scale epidemiological studies for their relative convenience and efficiency. However, such self-reported data were shown to be inaccurate as they contain errors such as underreported weight and overreported height by the participants [5-10]. In certain studies, the correlation coefficient between self-reported and actual values was greater than 0.8 [10-19]. In studies conducted in Korea examining the accuracy of self-reported height and weight, it was recommended that the actual measurement values should be used for evaluation of obesity [20] and the height, weight, and obesity rate must be calculated based on the actual data [10]. Additionally, other studies reported that the self-reported values were accurate for use in clinical and public health studies; however, the studies were only conducted in visitors and inpatients of hospital examination centers [19,21]. Therefore, this study conducted a comparative analysis of the prevalence of obesity calculated using the self-reported and measured values of height and weight from the data of the 2018 CHS to suggest a more accurate method for calculation of obesity prevalence.
This study was conducted using raw data from the 2018 CHS. This survey was conducted in 254 public health centers nationwide. Each public health center visits 900 individuals for interviews every year from August to October in order to investigate the health of local residents. In the 2018 survey, a total of 228,340 individuals participated. Those who “refused to respond” or responded “do not know” and the outliers (height: < 50 or > 200 cm; weight: < 20 or > 130 kg; and BMI: < 10 or > 50 kg/m2) were excluded; hence, a total of 214,640 participants were included in the final analysis, of whom 183,211 participants obtained their own body measurements. Individuals who could not stand still and pregnant women were excluded from undergoing body measurements.
The 2018 CHS was the only survey in which self-reported and actual body measurements of height and weight were simultaneously investigated. Prior to the body measurements, the participants were asked the following question: “What are your height and weight?”
To measure the height and weight during household visits, convenient tools without a large range of error for measurements were selected. The ultrasonic extensometers (InLab S50; InBody Co., Seoul, Korea), and CAS HE-58 (CAS, Yangju, Korea) were used to evaluate height and weight, respectively. The height was measured twice with the participant in a standing position, and the mean value was used for analysis. The weight was measured once. The reliability and effectiveness of the ultrasonic extensometer have been previously demonstrated [22].
Statistical analysis
SAS version 9.4 (SAS Institute Inc., Cary, NC, USA) was used to perform all statistical analyses. In this complex sample study, a stratified analysis was conducted by gender and age groups (19- 29, 30-39, 40-49, 50-59, 60-69, and ≥ 70 years old). A p-value of less than 0.05 was considered significant. Paired t-test was conducted to calculate the mean and 95% confidence interval (CI) and compared the differences between self-reported and measured values of height, weight, and BMI. Pearson’s correlation analysis was conducted to determine the correlation between the self-reported and measured values, and Bland-Altman analysis was conducted to compare the differences between the two values. The participants were categorized into four BMI groups based on the self-reported and measured values ( < 18.5, 18.5-22.9, 23.0-24.9, and ≥ 25.0 kg/m2), and the kappa statistic was assessed to evaluate the agreement by a group. To compensate for the possible errors of measured values obtained using the ultrasonic extensometer, 0.4 cm was subtracted from the height for analysis.
Ethics statement
This study was not subject to deliberation by the research ethics committee because it was conducted directly or commissioned by the state or local government to review and evaluate public welfare or service programs (Enforcement Rule of Bioethics and Safety Act, Article 2).
Participants’ general characteristics
The general characteristics of individuals who participated in both the self-administered questionnaire survey and body measurements and those who participated in the self-administered questionnaire survey, but not in the body measurements were compared.
Young men participants who had high income, a high level of education, a professional or office occupation, were unmarried, dong area residents, had a second-generation household type, and were obese (based on self-report) were significantly more likely to complete the self-administered questionnaire and not participate in body measurements (Table 1).
Comparison of self-reported and measured height, weight, and body mass index values
The correlation coefficients between the measured and self-reported height, weight, and BMI values were 0.96, 0.98, and 0.93, respectively, showing high correlations (Figures 1-3).
The Bland-Altman plot comparing the difference between the measured and self-reported values showed the largest difference between the two values (measured values and self-reported values) when the average self-reported height was 125-150 cm. When the average self-reported height was greater than 150 cm, the difference tended to decrease. The mean of the difference (-0.97) between the measured and self-reported values was close to 0. The 95% CI (limits of agreement) were -6.26 to 4.31 using the formula of mean± 2*standard deviation (SD) and -8.91 to 6.96 using the formula of mean± 3*SD (Figure 1). The difference between the measured and self-reported weight values was the greatest when the mean of measured and self-reported height values was 75-100 kg. When the mean of the two values was less than 75 kg or greater than 100 kg, the difference tended to decrease. The mean of the difference (0.52) between the measured and self-reported values was close to 0. The 95% CI were -4.80 to 5.84 using the formula of mean ± 2*SD and -7.50 to 8.50 using the formula of mean± 3*SD (Figure 2). The difference between the measured and self-reported BMI values was the greatest when the mean of the measured and self-reported values was 30-40. When the mean of the two values was less than 30 or greater than 40, the difference tended to decrease. The mean of the difference (0.49) between the measured and self-reported values was close to 0. The 95% CI values were -1.20 to 2.98 using the formula of mean ± 2*SD and -3.24 to 4.23 using the formula of mean± 3*SD (Figure 3).
The self-reported height values were 0.59 cm and 0.71 cm greater than the measured values for men and women, respectively. In particular, both men and women tended to report height values greater than the actual measurements as the age increased. Men aged 30-39 years, 50-59 years, and ≥ 70 years reported height values 0.26 cm, 0.65 cm, and 1.70 cm greater than the actual measured height values, respectively. Women aged 30-39 years, 50-59 years, and ≥ 70 years reported height values 0.20 cm, 0.75 cm, and 2.17 cm greater than the actual measured height values, respectively. In men aged 19-29 years, the difference between measured and self-reported values was minimal. However, in women aged 19-29 years, the self-reported height was 0.11 cm lesser than the actual measured height (Table 2).
In men and women, the self-reported weight values were 0.55 kg and 0.67 kg lesser than the actual measured weight, respectively. The difference between self-reported and measured weight values was greater in middle-aged and older participants. The difference decreased significantly in participants aged ≥ 70 years. In men aged 30-39 years, 50-59 years, and ≥ 70 years, the self-reported weight values were 0.72 kg, 0.58 kg, and 0.06 kg lesser than the actual measured weight, respectively. In women aged 30-39 years, 50-59 years, and ≥ 70 years, the self-reported weight values were 0.74 kg, 0.75 kg, and 0.37 kg lesser than the actual measured weight, respectively. In all age groups, women self-reported lower weight than men (Table 2).
The self-reported BMI values were 0.35 kg/m2 and 0.49 kg/m2 lesser than the actual measured BMI for men and women, respectively. In both men and women, the self-reported values tended to be lesser than the actual measured BMI as the age increased. In men aged 30-39 years, 50-59 years, and ≥ 70 years, the self-reported BMI values were 0.31 kg/m2, 0.38 kg/m2, and 0.49 kg/m2 lesser than the actual measured BMI, respectively. In women aged 30-39 years, 50-59 years, and ≥ 70 years, the self-reported BMI values were 0.34 kg/m2, 0.53 kg/m2, and 0.83 kg/m2 lesser than the actual measured BMI, respectively (Table 2).
Agreement between the measured and self-reported body mass index values per category
Agreement between the measured and self-reported BMI values was analyzed by category (underweight, normal, overweight, and obesity). The kappa statistics of 0.82 and 79.6% agreement were observed. In the underweight category, a 73.8% agreement was found between the measured and self-reported BMI values. In normal, overweight, and obesity categories, the agreement rates were 81.8%, 67.3%, and 92.6%. The agreement between measured and self-reported BMI values was the highest in the obesity group. In addition, the agreement rates and kappa statistics were higher in men than in women (Table 3).
Herein, we observed that the self-reported height and weight were over-reported and under-reported than the measured value, respectively. As a result, the self-reported BMI was underestimated than the measured BMI. In particular, men and women showed opposite findings on the difference between the measured and self-reported height values. When men reach the age of 19 years, they undergo body measurement as part of the requirements for army enlistment and are updated on their latest height. By contrast, most women only measure their height in school, leading to differences and errors between the measured and self-reported height values. Additionally, the self-reported and measured values were only evaluated simultaneously during the CHS in 2018. In particular, the self-reported obesity rate increased by 3.2%p from 28.6% in 2017 to 31.8% in 2018 [23]. This increase was approximately four times greater than the average increase of 0.9%p in the last five years from 2013, which reflects the honest responses of the participants in the self-administered questionnaires.
Consistent with our finding, in a study of 2,198 participants on the accuracy of self-reported height, weight, and BMI in the CHS, Jeong et al. [10] showed that both men and women over-reported their height, (men: 0.48 cm, women: 0.38 cm), under-reported their weight (men: -0.74 kg, women: -1.23 kg), and under-reported their BMI (men: 0.39 kg/m2, women: 0.60 kg/m2). In a comparison of the self-reported results of the 2010 CHS and measured prevalence of obesity in the 2010 KNHANES, Park et al. [24] reported that obesity and overweight were underestimated by 8.6%p and 7.8%p, respectively, in the CHS. Ki et al. [25] compared the estimates of the CHS and measured values of the KNHANES from 2010 and 2015 and observed absolute differences between the two surveys (8.9%p in 2010, 8.7%p in 2011, 8.8%p in 2012, 8.3%p in 2013, 6.6%p in 2014, and 8.2%p in 2015). Additionally, Kim et al. [26] compared the differences between measured values in the 2018 KNHANES and CHS. Although no significant difference was found, height and weight were under-reported in the CHS than in the KNHANES, while not difference was observed in BMI values between the two surveys.
Among the Organization for Economic Cooperation and Development countries, only 20, including Korea, provided both the measured and self-reported prevalence of obesity, 4 provided the measured values alone, and 13 provided the self-reported values alone. In a comparison of obesity prevalence in countries that provided the measured and self-reported values, significant differences were observed in the prevalence of obesity [26]. In Korea, the prevalence of obesity, defined as BMI of ≥ 30 kg/m2, were 5.9% based on the measured values and 4.3% based on the selfreported values in 2018, showing a difference of 1.6%p. Similarly, in the United States, the prevalence of obesity were 40.0% based on the measured values and 30.2% based on the self-reported values in 2016, showing a difference of 9.8%p [27].
Based on these findings, in order to develop effective methods and standardized surveys for monitoring the prevalence of obesity in Korea, considering that the CHS was only used for establishing and evaluating the Community Health Plans, accurate regional statistics are essential; take into account the survey conditions and cost-effectiveness, measurement surveys with cycles need to be conducted. In particular, external quality control by experts must be implemented for measurement surveys in order to improve the accuracy and reliability. Our findings also showed that young men who had high income, had high levels of education, and were unmarried did not undergo body measurements. Thus, in future body measurement surveys, calculating the prevalence of obesity using the height and weight values from the National Health Insurance Service health examination data may also be considered. However, this must be preceded by an amendment of laws and regulations on the personal information collected for the use of resident registration numbers and review of consent for data link agreements between institutions.
In conclusion, there was a significant difference between selfreported and measured values of the CHS. The measured values, rather than the self-reported values, were similar to the KNHANES results. This study is meaningful as it compared the self-reported and measured height and weight values of the 2018 CHS to accurately calculate the prevalence of obesity and suggest an efficient survey method. Therefore, to accurately calculate the prevalence of obesity in the CHS, BMI may be assessed using the measured height and weight values. In large-scale surveys, use of self-administered questionnaires, which are cost-effective, may lead to the underestimation of results. However, continuous monitoring using consistent standards and survey methods may help collect meaningful statistical data to compare the time series trends in the obesity rate. As the CHS provides basic regional health statistic data for establishing and evaluating Community Health Plans, the prevalence of obesity should be calculated using the measured values for use by local governments to promote community health projects based on more accurate statistical data.
Korean version is available at https://www.e-epih.org/.

CONFLICT OF INTEREST

The authors have no conflicts of interest to declare for this study.

FUNDING

None.

AUTHOR CONTRIBUTIONS

Conceptualization: Lee YK, Ko Y, Choi S, Won J. Data curation: Won J, Ko Y. Formal analysis: Ko Y. Funding acquisition: None. Project administration: Kim DH, Lee YK, Lee SK. Visualization: Ko Y, Choi S. Writing – original draft: Choi S, Ko Y, Won J. Writing – review & editing: Choi S, Lee YK, Kim DH, Lee SK.

We are grateful to the CHS participants. We also thank the 17 cities and provinces, 254 public health centers and 35 responsible university for conducting the investigation and supporting for the survey.
Figure 1.
Correlation distribution and Bland-Altman plot of the measured (A) and self-reported (B) height values.
epih-44-e2022024f1.jpg
Figure 2.
Correlation distribution and Bland-Altman plot of the measured (A) and self-reported (B) weight values.
epih-44-e2022024f2.jpg
Figure 3.
Correlation distribution and Bland-Altman plot of the measured (A) and self-reported (B) body mass index (BMI) values.
epih-44-e2022024f3.jpg
Table 1.
Participants’ general characteristics
Characteristics Participate in both interview and measurement1 Participate in interview only
Total 167,003 (73.1) 44,472 (19.5)
Gender
 Men 77,048 (46.1) 21,627 (48.6)
 Women 89,955 (53.9) 22,845 (51.4)
Age (yr)
 19-29 17,285 (10.4) 5,713 (12.8)
 30-39 20,582 (12.3) 7,078 (15.9)
 40-49 27,271 (16.3) 9,047 (20.3)
 50-59 34,052 (20.4) 9,502 (21.4)
 60-69 33,110 (19.8) 7,247 (16.3)
 ≥70 34,703 (20.8) 5,885 (13.2)
Income (104 Korean won)
 <100 24,109 (14.8) 3,705 (9.0)
 100-199 26,428 (16.3) 5,462 (13.3)
 200-299 25,201 (15.5) 6,440 (15.7)
 300-399 24,059 (14.8) 6,723 (16.4)
 400-499 18,707 (11.5) 5,220 (12.7)
 500-599 19,650 (12.1) 6,050 (14.7)
 ≥600 24,268 (14.9) 7,489 (18.2)
Education
 Less than elementary school 37,496 (22.5) 5,633 (12.7)
 Less than middle school 20,239 (12.1) 4,228 (9.5)
 Less than high school 49,109 (29.4) 14,162 (32.0)
 Less than college 54,460 (32.7) 18,389 (41.5)
 Graduate school or higher 5,490 (3.3) 1,889 (4.3)
Occupation
 Management‧profession 17,236 (10.3) 5,872 (13.2)
 Office worker 14,657 (8.8) 5,314 (12.0)
 Sales‧service 20,882 (12.5) 6,563 (14.8)
 Agriculture‧forestry‧fishing 19,120 (11.5) 3,353 (7.6)
 Manipulation of technical‧devices 15,983 (9.6) 4,596 (10.4)
 Simple labor 16,140 (9.7) 3,420 (7.7)
 Soldier 574 (0.3) 154 (0.3)
 Others (housewife, student, or no occupation) 62,246 (37.3) 15,074 (34.0)
Marital status
 Married (with spouse) 114,710 (68.7) 30,187 (68.1)
 Other (widow, divorce, etc.) 27,079 (16.2) 5,466 (12.3)
 Unmarried 25,062 (15.0) 8,671 (19.6)
Area
 Urban 95,776 (57.3) 28,877 (64.9)
 Rural 71,227 (42.7) 15,595 (35.1)
Generation type
 1st generation 78,933 (47.3) 17,967 (40.4)
 2nd generation 76,396 (45.7) 23,029 (51.8)
 3rd generation and over 11,671 (7.0) 3,441 (7.7)
Self-reported obesity
 Obesity (25.0 ≤BMI) 51,135 (30.7) 14,224 (32.0)1
 Normal (18.5≤BMI<25.0) 108,845 (65.2) 28,444 (64.0)1
 Underweight (BMI<18.5) 6,852 (4.1) 1,786 (4.0)1

Values are presented as number (%).

KRW, Korean won; BMI, body mass index.

1 Participants who provided both self-reported and measured values, including those who had outlier values.

Table 2.
Comparison of self-reported and measured height, weight, and BMI values
Variables Self-reported
Measured
Difference1
n Mean±SE n Mean±SE Mean (95% CI) p-value
Height (cm)
Men (yr)
 Total 78,260 171.62±2.94 78,260 171.03±3.13 -0.59 (-0.61, -0.57) <0.001
 19-29 8,515 174.49±7.02 8,515 174.46±7.15 -0.03 (-0.07, 0.00) 0.068
 30-39 9,866 174.78±6.29 9,866 174.52±6.51 -0.26 (-0.30, -0.22) <0.001
 40-49 13,016 172.76±5.85 13,016 172.33±6.03 -0.43 (-0.47, -0.39) <0.001
 50-59 15,459 170.32±5.47 15,459 169.67±5.67 -0.65 (-0.68, -0.62) <0.001
 60-69 15,420 168.16±5.83 15,420 167.14±6.09 -1.02 (-1.06, -0.98) <0.001
 ≥70 15,984 166.26±6.30 15,984 164.55±6.48 -1.70 (-1.77, -1.64) <0.001
Women (yr)
 Total 93,124 158.58±2.64 93,124 157.87±2.82 -0.71 (-0.73, -0.69) <0.001
 19-29 9,437 161.51±6.23 9,437 161.62±6.33 0.11 (0.08, 0.14) <0.001
 30-39 11,462 161.63±5.54 11,462 161.43±5.65 -0.20 (-0.22, -0.17) <0.001
 40-49 15,054 159.98±5.10 15,054 159.59±5.22 -0.39 (-0.42, -0.36) <0.001
 50-59 19,276 157.79±4.60 19,276 157.04±4.80 -0.75 (-0.78, -0.72) <0.001
 60-69 18,336 155.89±4.91 18,336 154.59±5.11 -1.30 (-1.35, -1.26) <0.001
 ≥70 19,559 153.08±6.01 19,559 150.92±5.79 -2.17 (-2.24, -2.10) <0.001
Weight (kg)
Men (yr)
 Total 80,502 71.96±5.44 80,502 72.52±5.65 0.55 (0.53, 0.58) <0.001
 19-29 8,584 73.63±16.70 8,584 74.22±17.36 0.59 (0.53, 0.65) <0.001
 30-39 10,025 77.08±12.94 10,025 77.80±13.37 0.72 (0.67, 0.78) <0.001
 40-49 13,236 74.17±11.15 13,236 74.83±11.44 0.67 (0.62, 0.71) <0.001
 50-59 15,788 70.86±9.75 15,788 71.44±10.19 0.58 (0.53, 0.62) <0.001
 60-69 15,833 67.95±9.47 15,833 68.46±9.81 0.51 (0.45, 0.56) <0.001
 ≥70 17,036 64.23±9.78 17,036 64.30±10.26 0.06 (0.00, 0.13) 0.069
Women (yr)
 Total 97,337 57.28±3.78 97,337 57.95±3.97 0.67 (0.65, 0.69) <0.001
 19-29 9,106 55.92±11.82 9,106 56.58±12.80 0.67 (0.61, 0.72) <0.001
 30-39 11,086 57.81±10.00 11,086 58.55±10.49 0.74 (0.70, 0.78) <0.001
 40-49 14,679 57.87±8.54 14,679 58.65±8.95 0.78 (0.74, 0.82) <0.001
 50-59 19,377 58.21±7.24 19,377 58.96±7.62 0.75 (0.72, 0.79) <0.001
 60-69 19,179 58.07±7.82 19,179 58.71±8.18 0.64 (0.60, 0.69) <0.001
 ≥70 23,910 55.37±7.71 23,910 55.74±7.96 0.37 (0.32, 0.42) <0.001
BMI (kg/m2)
Men (yr)
 Total 76,771 24.38±1.59 76,771 24.73±1.68 0.35 (0.35, 0.36) <0.001
 19-29 8,321 24.11±5.06 8,321 24.31±5.28 0.20 (0.18, 0.22) <0.001
 30-39 9,670 25.16±3.79 9,670 25.47±3.96 0.31 (0.29, 0.33) <0.001
 40-49 12,812 24.81±3.35 12,812 25.16±3.47 0.35 (0.33, 0.37) <0.001
 50-59 15,217 24.39±2.90 15,217 24.77±3.07 0.38 (0.37, 0.40) <0.001
 60-69 15,158 23.99±2.90 15,158 24.47±3.06 0.48 (0.45, 0.50) <0.001
 ≥70 15,593 23.25±3.22 15,593 23.74±3.34 0.49 (0.46, 0.52) <0.001
Women (yr)
 Total 89,649 22.84±1.50 89,649 23.33±1.60 0.49 (0.48, 0.50) <0.001
 19-29 8,912 21.44±4.23 8,912 21.66±4.42 0.22 (0.20, 0.24) <0.001
 30-39 10,843 22.13±3.68 10,843 22.47±3.88 0.34 (0.32, 0.36) <0.001
 40-49 14,370 22.63±3.23 14,370 23.05±3.39 0.42 (0.40, 0.44) <0.001
 50-59 18,725 23.38±2.72 18,725 23.91±2.92 0.53 (0.52, 0.55) <0.001
 60-69 17,837 23.90±3.12 17,837 24.58±3.33 0.68 (0.65, 0.70) <0.001
 ≥70 18,962 23.77±3.22 18,962 24.60±3.35 0.83 (0.80, 0.87) <0.001

BMI, body mass index; SE, standard error; CI, confidence interval.

1 Difference=measured value minus self-reported value.

Table 3.
Agreement between measured and self-reported body mass index (BMI) values per category
Measured BMI Self-reported BMI1
Agreement (%) Kappa (p-value)
Underweight Normal Overweight Obesity Total
Total 6,836 (100) 67,439 (100) 41,186 (100) 50,959 (100) 166,420 79.6 0.82 (<0.001)
Underweight 5,047 (73.8) 1,765 (2.6) 37 (0.1) 17 (0.0) 6,866
Normal 1,703 (24.9) 55,158 (81.8) 3,991 (9.7) 493 (1.0) 61,345
Overweight 51 (0.7) 9,210 (13.7) 27,736 (67.3) 3,280 (6.4) 40,277
Obesity 35 (0.5) 1,306 (1.9) 9,422 (22.9) 47,169 (92.6) 57,932
Men 1,983 (100) 25,600 (100) 21,315 (100) 27,873 (100) 76,771 80.5 0.82 (<0.001)
Underweight 1,403 (70.8) 557 (2.2) 20 (0.1) 7 (0.0) 1,987
Normal 554 (27.9) 19,665 (76.8) 1,411 (6.6) 196 (0.7) 21,826
Overweight 14 (0.7) 4,880 (19.1) 14,500 (68.0) 1,438 (5.2) 20,832
Obesity 12 (0.6) 498 (1.9) 5,384 (25.3) 26,232 (94.1) 32,126
Women 4,853 (100) 41,839 (100) 19,871 (100) 23,086 (100) 89,649 78.8 0.80 (<0.001)
Underweight 3,229 (66.5) 657 (1.6) 11 (0.1) 8 (0.0) 3,905
Normal 1,549 (31.9) 33,437 (79.9) 1,333 (6.7) 232 (1.0) 36,551
Overweight 48 (1.0) 6,643 (15.9) 12,184 (61.3) 1,069 (4.6) 19,944
Obesity 27 (0.6) 1,102 (2.6) 6,343 (31.9) 21,777 (94.3) 29,249

Values are presented as number (%).

1 Underweight (<18.5 kg/m2), normal (18.5-22.9 kg/m2), overweight (23.0-24.9 kg/m2), and obesity (≥25.0 kg/m2).

  • 1. World Health Organization. Obesity and overweight; 2021 [cited 2021 Sep 1]. Available from: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.
  • 2. Korea Disease Control and Prevention Agency. Korea health statistics 2019: Korea National Health and Nutrition Examination Survey (KNHANES VIII-1). Cheongju: Korea Disease Control and Prevention Agency; 2020. p 109 (Korean).
  • 3. Korean Society for the Study of Obesity. Obesity common sense [cited 2021 Sep 1]. Available from: http://general.kosso.or.kr/html/?pmode=obesityDisease (Korean).
  • 4. World Health Organization. Global strategy on diet, physical activity and health-2004 [cited 2021 Sep 1]. Available from: https://www.who.int/publications/i/item/9241592222.
  • 5. Lu S, Su J, Xiang Q, Zhou J, Wu M. Accuracy of self-reported height, weight, and waist circumference in a general adult Chinese population. Popul Health Metr 2016;14:30.ArticlePubMedPMCPDF
  • 6. Gildner TE, Barrett TM, Liebert MA, Kowal P, Snodgrass JJ. Does BMI generated by self-reported height and weight measure up in older adults from middle-income countries? Results from the study on global AGEing and adult health (SAGE). BMC Obes 2015;2:44.ArticlePubMedPMCPDF
  • 7. Yong V, Saito Y. How accurate are self-reported height, weight, and BMI among community-dwelling elderly Japanese?: evidence from a national population-based study. Geriatr Gerontol Int 2012;12:247-256.ArticlePubMed
  • 8. Babiarczyk B, Sternal D. Accuracy of self-reported and measured anthropometric data in the inpatient population. Int J Nurs Pract 2015;21:813-819.ArticlePubMed
  • 9. Lois K, Kumar S, Williams N, Birrell L. Can self-reported height and weight be relied upon? Occup Med (Lond) 2011;61:590-592.ArticlePubMed
  • 10. Jeong JY, Kim DH, Kim KY, Ryu SY, Lee SY, Park YS. Accuracy of self-reported height, weight and body mass index in Community Health Survey in South Korea. J Health Info Stat 2017;42:241-249 (Korean).ArticlePDF
  • 11. Lin CJ, DeRoo LA, Jacobs SR, Sandler DP. Accuracy and reliability of self-reported weight and height in the Sister Study. Public Health Nutr 2012;15:989-999.ArticlePubMedPMC
  • 12. Burton NW, Brown W, Dobson A. Accuracy of body mass index estimated from self-reported height and weight in mid-aged Australian women. Aust N Z J Public Health 2010;34:620-623.ArticlePubMedPDF
  • 13. Dekkers JC, van Wier MF, Ariëns GA, Hendriksen IJ, Pronk NP, Smid T, et al. Comparative effectiveness of lifestyle interventions on cardiovascular risk factors among a Dutch overweight working population: a randomized controlled trial. BMC Public Health 2011;11:49.ArticlePubMedPMCPDF
  • 14. Poston WS, Jitnarin N, Haddock CK, Jahnke SA, Day RS. Accuracy of self-reported weight, height and BMI in US firefighters. Occup Med (Lond) 2014;64:246-254.ArticlePubMed
  • 15. Yoong SL, Carey ML, D’Este C, Sanson-Fisher RW. Agreement between self-reported and measured weight and height collected in general practice patients: a prospective study. BMC Med Res Methodol 2013;13:38.ArticlePubMedPMCPDF
  • 16. Xie YJ, Ho SC, Liu ZM, Hui SS. Comparisons of measured and self-reported anthropometric variables and blood pressure in a sample of Hong Kong female nurses. PLoS One 2014;9:e107233.ArticlePubMedPMC
  • 17. Tang W, Aggarwal A, Moudon AV, Drewnowski A. Self-reported and measured weights and heights among adults in Seattle and King County. BMC Obes 2016;3:11.ArticlePubMedPMCPDF
  • 18. Skeie G, Mode N, Henningsen M, Borch KB. Validity of self-reported body mass index among middle-aged participants in the Norwegian Women and Cancer study. Clin Epidemiol 2015;7:313-323.ArticlePubMedPMC
  • 19. Lee DH, Shin A, Kim J, Yoo KY, Sung J. Validity of self-reported height and weight in a Korean population. J Epidemiol 2011;21:30-36.ArticlePubMedPMC
  • 20. Song YM, Yoon JL. The accuracy of self-reported weight and height. Korean J Epidemiol 1995;17:257-268 (Korean).
  • 21. Kim NY, Shin MH, Nam SJ, Yang JH. Validity of self-reported weight, height and body mass index in a hospital based breast cancer case-control study. Korean J Health Promot Dis Prev 2004;4:45-51 (Korean).
  • 22. Cho SH, Cho YG, Park HA, Bong AR. Reliability and validity of an ultrasonic device for measuring height in adults. Korean J Fam Med 2021;42:376-381.ArticlePubMedPMCPDF
  • 23. Korea Disease Control and Prevention Agency. Korea community health at a glance 2020: Korea Community Health Survey (KCHS), 2020. Cheongju: Korea Disease Control and Prevention Agency; 2021. p 45 (Korean).
  • 24. Park YR, Cho YG, Kang JH, Park HA, Kim KW, Hur YI, et al. Comparison of obesity and overweight prevalence among Korean adults according to Community Health Survey and Korea National Health and Nutrition Examination Survey. Korean J Obes 2014;23:64-68 (Korean).Article
  • 25. Ki JS, Kim H. Comparison of estimates and time series stability of Korea Community Health Survey and Korea National Health and Nutrition Examination Survey. Epidemiol Health 2019;41:e2019012.ArticlePubMedPMC
  • 26. Kim S, Park E. Differences in height, weight, BMI, and obesity rate between 2018 Community Health and Korea National Health and Nutrition Examination Surveys. J Health Info Stat 2020;45:281-287 (Korean).ArticlePDF
  • 27. Organisation for Economic Cooperation and Development. Non-medical determinants of health [cited 2021 Sep 1]. Available from: https://stats.oecd.org/Index.aspx?DataSetCode=HEALTH_LVNG.

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Consistency between self-reported disease diagnosis and clinical assessment and under-reporting for chronic conditions: data from a community-based study in Xi’an, China
      Haobiao Liu, Yanru Zhao, Lichun Qiao, Congying Yang, Ying Yang, Tianxiao Zhang, Qian Wu, Jing Han
      Frontiers in Public Health.2024;[Epub]     CrossRef
    • Comparison of self-reported and measured height and weight in patients with psoriasis
      Simona Mastroeni, Francesca Sampogna, Claudia Uras, Mara De Angelis, Roberta Fusari, Nidia Melo Salcedo, Sabatino Pallotta, Damiano Abeni
      Archives of Dermatological Research.2023; 315(7): 2023.     CrossRef
    • Accuracy of Assessing Weight Status in Adults by Structured Observation
      Tânia Jorge, Sofia Sousa, Isabel do Carmo, Nuno Lunet, Patrícia Padrão
      Applied Sciences.2023; 13(14): 8185.     CrossRef
    • Changes in health behaviors and obesity of Korean adolescents before and during the COVID-19 pandemic: a special report using the Korea Youth Risk Behavior Survey
      Chang-Mo Oh, Yangha Kim, Jieun Yang, Sunhye Choi, Kyungwon Oh
      Epidemiology and Health.2023; 45: e2023018.     CrossRef
    • Tobacco consumption, sales, and output as monitoring indicators in the era of the tobacco endgame: a Korean example
      Hana Kim, Hee-kyoung Nam, Heewon Kang
      Epidemiology and Health.2023; 45: e2023030.     CrossRef

    Figure
    Related articles

    Epidemiol Health : Epidemiology and Health