Beyond the looking glass - Socioeconomic differences in weight perception and weight control attempts among Korean women: Evidence from a national survey

Beyond the looking glass - Socioeconomic differences in weight perception and weight control attempts among Korean women: Evidence from a national survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Beyond the looking glass - Socioeconomic differences in weight perception and weight control attempts among Korean women: Evidence from a national survey Junhye Kwon, Eun-Young Lee, Jongnam Hwang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7966841/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Weight perception is an important factor for weight health as misperception of body weight could influence one’s ability to achieve healthy weight. It has been suggested that the perception of body weight may vary across gender and socioeconomic status (SES) strata. The primary purpose of this study was to examine the association between SES and weight perception among Korean women. The secondary aim was to assess whether weight perception is associated with weight control attempts after adjusting for SES. Methods A total of 7253 women (19–64 years old) who participated in the Korea National Health and Nutrition Examination Survey (KNHANES) 2016–2018 were included in our analysis. Actual weight status measured by body mass index (BMI; kg/m 2 ) and self-perceived weight status were used to classify respondents into three weight perception groups: under-estimation group, accurate-estimation group, and over-estimation group. Based on self-reported weight control attempts, respondents were divided into three groups: necessary control group, unnecessary control group, and no attempt group. Two separate multinomial logistic regressions were conducted. Results Lower educational attainment was associated with underestimation of body weight (RRR: 1.38, 95% CI: 1.00–1.90). Women with middle school education were less likely to overestimate their weight (RRR: 0.75, 95% CI: 0.61–0.93) while high school graduates were more likely to overestimate their weight (RRR: 1.16, 95% CI: 1.01–1.33). Weight perception weight control weight control attempt socioeconomic status Korea Introduction Obesity is a substantial public health concern around the world [ 1 ]. In South Korea (Korea thereafter), the prevalence of obesity has steadily increased over the past decade among the adult population [ 2 – 4 ]. A recent study using data from the national health checkup database showed that approximately 35.7% of the Korean adult population is either overweight or obese (Body mass index [BMI] ≥ 25 kg/m 2 ) [ 5 ]. This estimated prevalence is approximately 10% higher than the corresponding prevalence reported in 1998 [ 6 ]. Over the past decades, different trends of obesity rate by gender are observed in Korea. For women, the rate of overweight and obesity has remained relatively stable and high (23.9% in 2009 and 27.8% in 2023) over the past decades while the rate for men significantly increased (35.6% in 2009 and 45.6% in 2023) [ 7 ]. In addition to gender, previous studies suggested that socioeconomic status (SES) is an important predictor of obesity [ 8 – 10 ]. For instance, obesity is more prevalent among women with lower SES while among men, higher prevalence of obesity is observed in higher SES [ 11 ]. As obesity is an important risk factor in the development of chronic disease, gender and SES inequalities in obesity may relate to engendering another health inequality [ 8 , 12 ]. A growing body of literature suggests that weight perception is an important factor in preventing obesity and maintaining healthy weight [ 13 – 15 ]. Weight perception typically refers to “the degree of concordance between perceived and measured weight” [ 16 ] and it was suggested that the misperception of body weight is problematic as it affects the ability to achieve and maintain a healthy weight [ 17 – 19 ]. The perception of body weight may vary according to gender and SES [ 20 , 21 ]. For instance, women are more likely to worry about being overweight or obese while men tend to be less concerned about their weight [ 18 , 22 , 23 ]. With respect to SES and weight perception, higher income and higher educational attainment appear to be associated with a better understanding of weight appropriateness, suggesting that SES is a predictor of accurate understanding of body weight [ 15 , 24 – 26 ]. Differences in perception of body weight, which vary across SES groups, are closely linked to different weight control attempts, indicating that accurate perception of body weight leads healthy or necessary weight control [ 27 – 29 ]. Studies on weight control practices in the U.S. showed that a considerable number of clinically normal-weight (BMI between 18-25kg/m 2 ) individuals attempted or desired weight loss while a similar number of overweight individuals did not [ 15 , 28 ]. These results may support that actual weight status is not as a strong predictor of weight control attempts as it is expected, but self-perceived weight might be a more important predictor [ 23 ]. Despite the importance of better understanding accurate weight perception and weight control attempt by SES in managing and preventing obesity, there is limited evidence on these relationships among Korean women. A recent study on the Korean adult population suggested that both weight perception and weight control attempts could greatly differ by gender and SES [ 24 ]. Although this study provided some evidence on weight perception and weight control attempt in the Korean context, it examined only weight under-perception and unecessary weight control attempt by SES and gender. In the present study, we further included under-, accurate- and over-perception of individual’s body weight to examine 1) an association between SES and weight perception and 2) a link between weight perception and weight control attempt as well as a potential role of SES in weight control attempt among Korean women. Methods Data and study population This study used data from Korean National Health and Nutrition Examination Survey (KNHANES) 2016–2018 (wave 7), a nationally representative population-based survey. The KNHANES was conducted by the Ministry of Health and Welfare of Korea and the Korea Disease Control and Prevention Agency (KDCA), with the purpose of examining the general health and nutrition status of the Korean population. The data were collected from a multi-stage, clustered probability sample of non-institutionalized Korean civilians [ 30 ]. The KNHANES survey included four components: a health interview survey, a health behaviour survey, physical health examinations, and a nutrition survey. The survey information was collected through face-to-face interviews and a follow-up health examination was conducted. The heath examinations were performed by trained medical personnels who collected samples, data, and tested for chronic disease [ 30 ]. A total of 24269 individuals (women: 13198; men: 11071) were surveyed for the 2016–2018 wave. Our analysis included a total of 7253 women aged 19–64 years old, who participated in both the health examination and the health interview. We excluded respondents who did not complete both the examination and interview and those over 65 years old, as unintentional or involuntary weight loss is commonly observed in older adults [ 31 ]. Measures Weight perception : To determine self-perceived weight status, individuals were asked the following question: “Do you consider yourself to be very underweight, slightly underweight, ideal weight, slightly obese, or very obese?” For data analysis, self-perceived weight was classified into underweight ( very underweight and slightly underweight ), normal ( idea weight ) and obese ( slightly obese and very obese ) groups. For actual body weight status, we used respondents’ Body Mass Index (BMI), derived from measurements of height and weight collected during physical health examinations (Weight (kg)/Height (m) 2 ). The following cut off values were used to assign respondents to the corresponding BMI categories: obese weight (BMI ≥ 25); normal weight (BMI 18.5–24.9); and underweight (BMI < 18.5) [ 32 ]. The BMI classification was followed the World Health Organization (WHO) and KDCA criteria. Based on the BMI classification and self-perceived weight status, we reassigned individuals into three weight perception groups by assessing how correctly they perceived their weight in relation to their actual weight category: under-estimation, accurate estimation, and over-estimation . For example, if an individual perceived herself as being obese and her calculated BMI was also in the obese category, she was considered to have accurately estimated her weight whereas individuals with inaccurately estimated their weight were placed the under-estimation or over-estimation group in our analytic models. More details are presented in Table 1 . Table 1 Classification of Weight Perception by Actual BMI and Self-Perceived Weight Status Actual BMI Self-Perceived Weight Status Perception Classification Underweight very thin or slightly thin accurate normal, slightly overweight, or very overweight overestimated Normal weight normal accurate slightly overweight or very overweight overestimated Obese slightly overweight or very overweight accurate normal, slightly thin, or very thin underestimated Weight control attempt : Individuals were also asked about their experience of weight control attempt within the past year. The experience of weight control attempt was determined from the following question in the KNHANES: “ Within the past year, have you tried to control your weight? ”. The survey participants responded 1) Yes, to lose weight ; 2) Yes, to gain weight ; 3) Yes, to maintain weight ; 4) No, I did not . Based on an individual’s BMI and weight control experience, we assigned each individual into three groups: Unnecessary control, necessary control, and no control. Underweight individuals who attempted to gain weight were assigned to the necessary control group, while those who attempted to maintain or lose weight were placed in the unnecessary control group. Normal weight individuals who reported to maintain weight were included in the necessary control group, whereas those who attempted to either lose or gain weight were assigned to the unnecessary control group. Obese individuals who had attempted to lose weight were categorized as necessary control, while those who attempted to maintain or gain weight were considered to be in the unnecessary control group. Participants who reported no attempt to control their body weight—whether through loss, maintenance, or gain—were assigned to the no control group, regardless of BMI. Table 2 summarizes the classification of weight control attempts by respondents’ BMI status. Table 2 Classification of Weight Control Attempts by BMI Status Actual BMI Weight Control Attempt Group Classification Under weight Attempted to gain weight Necessary Control Attempted to maintain weight Unnecessary Control Attempted to lose weight Unnecessary Control No weight control attempt No Control Normal weight Attempted to maintain weight Necessary Control Attempted to lose weight Unnecessary Control Attempted to gain weight Unnecessary Control No weight control attempt No Control Obese Attempted to lose weight Necessary Control Attempted to maintain weight Unnecessary Control Attempted to gain weight Unnecessary Control No weight control attempt No Control Either no active weight control attempt (i.e., doing nothing about weight) or unnecessary weight control (i.e., attempts to gain weight in non-obese individuals, trying to maintain or even gain weight in obese individuals) was considered to be unhealthy patterns [ 24 , 26 – 27 ]. Participants who responded that they tried to control weight during the past year were also asked to indicate the methods used for weight control (i.e., diet, exercise, other methods). SES : Educational attainment and household income were used to indicate SES. Educational attainment was divided into three categories: completion of middle school or less, high school, and post-secondary education (i.e., college, university, and graduate school). In addition, we used age-sex adjusted monthly household income quartiles, which were defined by the KNAHNES survey [ 33 ]. Covariates : Demographic and health behaviour variables—age, residence region, smoking habit, high-risk drinking behaviour, and physical activity—were included as covariates. Age was divided into three categories: 19–34, 35–49, and 50–64 years old. In the KNHANES, residence region data were obtained using the 17 regional categories (i.e., Seoul, seven metropolitan cities, one special self-governing city and nine provinces). In this study, we classified the 17 regions into two regions (Metro Seoul and non-Metro Seoul) as geographical disparities are observed between these two regions. Specifically, the geographic-related social and health inequalities between these two regions are a well-known concern as more social and health resources are concentrated in the Metro Seoul region [ 34 , 35 ]. The Metro Seoul region included Seoul, Incheon metropolitan cities, and Gyeonggi province, in which approximately half of the entire Korean population dwell. For indicators of healthy behaviour, we included smoking habits, high-risk drinking behaviour, and physical activity. Current smoking habits were categorized into “Currently smoking” or “Currently not smoking.” Regarding high-risk drinking, those who drank more than five cups of alcohol at a single event and more than twice a week were defined as the high-risk drinking group. This classification of high-risk drinking behaviour was defined and provided by the KHNAHES [ 33 ]. Analysis We estimated two separate multinomial logistic regression analyses to explore SES and weight perception, and to assess the impact of weight perception on weight control attempts among Korean women. All analyses were conducted using STATA v.12 and the results were reported as relative risk ratio (RRR) and 95% confidence intervals (95% CIs). Differences were considered statistically significant at p < 0.05, and the population weight provided by KNHANES was applied to all regression models as it is suggested to use the weight to estimate a representation of the Korean population [ 30 ]. Results The characteristics of the study population by body weight perception are shown in Table 3 . Of 7253 Korean women, 8.2% of the women underestimated and 25.1% overestimated their body weight. A higher percentage of women aged 20–34 years, who had completed university and with higher income (Quartile 3 and 4) overestimated their body weight. More than 50% (estimated 2,712,195) of the women in the overestimation group had engaged in unnecessary weight control attempts. Table 3 General characteristics of Korean women Variable n % Age 19–24 1724 23.8 35–49 2700 37.2 50–64 2829 39.0 Education Middle school 1354 18.7 High school 2708 37.3 University 3191 44.0 Marriage Singe 2028 28.0 Married or partnered 5225 72.0 Household income Q1 (Lowest) 701 9.6 Q2 1766 24.4 Q3 2279 31.4 Q4 (Highest) 2507 34.6 Region Metro Seoul areas 2012 27.7 Non-Metro Seoul areas 5241 72.3 Self-rated health Very good & good 2108 29.1 Fair 3933 54.2 Very poor & poor 1212 16.7 Smoking Yes 458 6.3 No 7035 93.7 High-risk drinking Yes 500 6.9 No 6753 93.1 Weight perception Under-estimated 595 8.2 Accurate 4835 66.7 Over-estimated 1823 25.1 Weight control Necessary attempt 2616 36.1 Unnecessary attempt 2745 37.9 No attempts 1892 26.0 Total 7253 Table 4 presents the results of the multinomial regression, showing the relationship between SES and body weight perception. Educational attainment was associated with underestimated body weight, suggesting that women of lower educational attainment (completion of middle school or lower) were more likely to underestimate their body weight (RRR: 1.38, 95% CI: 1.00–1.90). Furthermore, women of the lowest educational attainment were less likely to overestimate their body weight (RRR: 0.75, 95% CI: 0.61–0.93) whereas those with the completion of high school showed higher likelihood of overestimating their body weight (RRR: 1.16, 95% CI: 1.01–1.33). Unlike educational level, household income was not a statistically significant predictor for either underestimated or overestimated body weight among Korean women. Those aged 50–64 years showed less likelihood of overestimating their body weight (RRR: 0.70, 95% CI: 0.58–0.89). The poor self-rated health and high-risk drinking behaviour were also associated with overestimated body weight. Table 4 Multinomial logistic regression examining an association between socioeconomic status and weight perception § Variable Underestimated group Overestimated group RRR 95% CI RRR 95% CI Education Middle school 1.38* 1.00–1.90 0.75* 0.61–0.93 High school 0.98 0.77–1.25 1.16* 1.01–1.33 Household income Q1 (Lowest) 1.13 0.77–1.65 0.88 0.67–1.17 Q2 1.03 0.79–1.35 0.96 0.81–1.13 Q3 (Highest) 1.05 0.82–1.34 0.93 0.80–1.08 Covariates Age 35–49 1.09 0.82–1.46 0.91 0.75–1.09 50–64 1.39 0.99–1.94 0.70* 0.58–0.89 Marriage Singe 1.11 0.86–1.44 0.98 0.84–1.15 Region Non-Metro Seoul 1.01 0.80–1.26 1.04 0.90–1.20 Self-rated health Fair 1.03 0.81–1.29 1.41* 1.22–1.64 Very poor & poor 1.01 0.74–1.37 1.33* 1.09–1.61 Smoking Yes 1.15 0.75–1.74 1.08 0.84–1.38 High-risk drinking Yes 0.75 0.47–1.19 1.26* 1.00–1.59 * P < 0.05 § Reference groups: Age (19–34), Education (Post-secondary), Income (Q4- Highest), Region (Metro-Seoul areas), Self-rated health (Very good and good), Smoking (No), High-risk drinking (No) Table 5 presents the relationship between weight perception and weight control attempts based on our multinomial logistic regression. Individuals who overestimated their body weight had higher risk of attempting in unnecessary weight control attempts (RRR: 5.37, 95% CI: 3.83–7.52). Compared to the younger group (age 19–34), older age group (age 35–59) were less likely to employ unnecessary weight control activities as compared to the accurate weight control attempt group. Table 5 Multinomial logistic regression examining an association between weight perception and weight control attempts § Variable Unnecessary attempt No attempt RRR 95% CI RRR 95% CI Weight perception Underestimated 0.67 0.40–1.10 1.41 0.86–2.32 Overestimated 5.37* 3.83–7.52 2.74* 1.91–3.96 Education Middle school 0.72* 0.56–0.94 1.05 0.81–1.35 High school 0.85 0.72–1.01 0.90 0.74–1.10 Household income Q1 (Lowest) 1.05 0.84–1.52 1.61* 1.23–2.09 Q2 0.78 0.74–1.27 1.17 0.96–1.42 Q3 (Highest) 0.86 0.71–1.10 1.10 0.92–1.32 Age 35–49 0.67* 0.55–0.82 0.79* 0.63–0.98 50–64 0.51* 0.41–0.63 0.66* 0.52–0.83 Marriage Singe 1.08 0.90–1.30 1.02 0.83–1.25 Region Non-Metro Seoul 0.95 0.82–1.10 1.00 0.84–1.18 Self-rated health Fair 0.85* 0.73–0.99 0.91 0.77–1.07 Very bad & bad 0.67* 0.55–0.82 0.85 0.68–1.05 Smoking Yes 1.13 0.84–1.52 1.27 0.95–1.69 High risk drinking Yes 0.97 0.74–1.27 1.06 0.80–1.40 * P < 0.05 § Reference groups: Age (19–34), Education (Post-secondary), Income (Q4- Highest), Region (Metro-Seoul areas) Self-rated health (Very good and good), Smoking (No), High-risk drinking (No) Women who overestimated their body weight were more likely to attempt to control their weight while those in the underestimation group showed less likelihood of participating in any weight control attempts. The lowest income quartile was also a predictor of not participating in any weight control attempts. Table 6 shows the results of the differences in weight control attempts by education and income across weight perception groups. Women with middle school education in the underestimation group were significantly more likely to engage in unnecessary weight control attempts (RRR: 2.44, 95% CI: 1.10–5.38), followed by those with high school education (RRR: 1.91, 95% CI: 1.03–3.55), compared to those with post-secondary education. Notably, those with the completion of high school in the overestimation group were less likely to engage in any weight control attempts (RRR: 0.65, 95% CI: 0.44–0.98). Table 6 Multinomial logistic regression examining differences in weight perceptions by education, income and weight control attempts § Variable Weight control attempts Unnecessary attempt No attempt RRR 95% CI RRR 95% CI Differences by education Underestimated Middle school 2.44* 1.10–5.38 1.03 0.53–2.02 High school 1.91* 1.03–3.55 1.03 0.54–1.96 Overestimated Middle school 1.7 0.96–2.99 1.43 0.82–2.51 High school 0.88 0.62–1.25 0.65* 0.44–0.98 Differences by income Underestimated Q1 0.99 0.36–2.73 1.28 0.49–3.33 Q2 1.86 0.89–3.86 1.88 0.97–3.66 Q3 1.53 0.82–2.88 1.91* 1.06–3.48 Overestimated Q1 1.18 0.53–2.66 1.06 0.48–2.34 Q2 1.54 0.96–2.48 1.01 0.60–1.71 Q3 1.34 0.86–2.08 1.29 0.81–2.06 * P < 0.05 § Reference groups: Education (Post-secondary), Income (Q4- Highest) Individuals in the underestimation group with middle-high income (Quartile 3) were significantly more likely not to engage in any weight control attempt (RRR: 1.91, 95% CI: 1.06–3.48) compared to the highest income quartile. Discussion The objectives of this study were to examine the associations between SES and weight perception and to investigate a role of weight perception on the relationship between SES and weight control attempts. Our study found that SES predicts perception of body weight and approaches to weight control attempts among Korean women. In relation to underestimating body weight, lower income and educational levels posed as a barrier to accurate perception of body weight. Similarly, the lowest income and educational levels also associated with underestimation of body weight. With respect to weight control attempts, weight misperception, both under- and over-estimation, was an important predictor of misleading to unnecessary weight control attempts, suggesting that accurate perception of body weight plays an important role in encouraging necessary weight control attempts among Korean women. Our findings are similar to the existing evidence primarily from Western countries, showing SES gradients in accurate understanding of body weight. A growing body of literature addresses that people with higher educational attainment and higher income have more accurate perceptions of their body weight [ 15 , 36 , 37 ]. However, this inverse relationship between SES and accurate perception of body weight was also observed in women [ 38 ]. Accompanied by the existing evidence, our findings support the conclusion that SES, in particular lower education, is a common predictor for underestimation of body weight among women across Western and developed East Asian countries [ 39 , 40 ]. The relationship between education and weight perception can be explained by close links between education and healthy lifestyle typically observed among women [ 41 , 42 ]. People with higher education are more likely to participate in health promoting behaviour as they have more interest in maintaining healthier lifestyle and better access to resources and information that motivates healthy behaviours [ 20 , 38 , 43 ]. Meanwhile, limited access to the resources necessary for engaging in healthy lifestyles (e.g., nutritionally adequate food, access to recreation centres, indoor gyms, or parks) and lack of knowledge of health promoting behaviours are observed in lower SES populations [ 44 – 46 ]. Consistent with previous findings [ 47 , 48 ], our results also indicate that underestimating of body weight is associated with more likelihood of attempting unnecessary weight control attempts. Previous studies noted that, due to the influence of Western culture and rapid economic development in Korea, the perspective of feminine beauty was shifted to slimness or thinness from a traditional value of ideal woman’s body type being plump [ 24 , 49 ]. In modern Korean society, this trend has intensified, particularly among female adolescents and young adults, driven by the pervasive influence of social media, celebrity culture, and the global spread of K-pop and K-beauty industries. Platforms like Instagram, YouTube, and TikTok increasingly promote highly curated and edited body images that reinforce unrealistic beauty standards [ 50 ]. At the same time, the rise of digital health tracking apps and diet-focused content has normalized restrictive eating and excessive weight monitoring [ 51 ]. These societal pressures, compounded by peer comparisons and fear of social stigma [ 24 , 52 , 53 ], may contribute to distorted body image and increase the risk of unhealthy weight control practices, even among individuals with normal or underweight BMI. The greater likelihood of attempting unnecessary weight control in the weight misperception group is problematic because they are more susceptible to adopting unnecessary and often unnecessary weight control activities. Indeed, a growing body of literature reports that Korean women are not satisfied with their body weights, and have, often unnecessary, a lifetime goal to be thin [ 7 , 24 , 54 , 55 ]. It has been found that the high level of weight concern or desire to be thin often leads women to eating pathology, often show as engaging in unhealthy forms of weight control, such as long-term fasting, self-induced vomiting, and extreme diet control [ 56 – 58 ]. Our findings, combined with the thin body preference, suggest that public health action should be made on diminishing widespread weight-related stigma particularly in women body [ 59 ]. In addition, it is important to guide Korean women to accurately perceive their body weight and to engage in necessary weight control attempts, including balanced diet and physical activity, when they clinically need to lose their weight. Our study further examined the differential effects of SES on weight control attempts across weight perception groups. The findings suggest that women with lower educational attainment in the underestimation group were more likely to engage in unnecessary weight control attempts also suggest that educational disparities may influence access to accurate health information and shape perceptions of healthy weight management. Recent studies have highlighted that limited health literacy is associated with poorer weight management outcomes and the adoption of maladaptive weight control attempts [ 60 , 61 ]. Notably, within the overestimation group, high school graduates were less likely to engage in any weight control attempts despite perceiving themselves as overweight. This discrepancy between perception and behavior indicates a potential mismatch between body image and motivation or capacity to act. Psychological factors, such as low self-efficacy, body dissatisfaction, or even social fatigue related to weight norms, may explain why some individuals who overestimate their weight choose not to engage in weight control efforts. This aligns with findings from recent research emphasizing the complex interplay between body image, perception, and health behaviours [ 62 ]. The result that middle-high income individuals (Quartile 3) in the underestimation group were significantly more likely not to engage in any weight control behavior compared to the highest income quartile. This challenges the common assumption that lower SES predicts lower health engagement. It is possible that individuals in this income category perceive themselves as less at risk or face time constraints and lifestyle demands that reduce their participation in weight-related health behaviours. These nuances highlight the need for a more layered understanding of how income interacts with weight perceptions and health actions, as suggested by recent studies exploring the socioeconomic determinants of health behaviours [ 63 ]. Age was also a predictor of weight control attempts among Korean women. In particular, those between the ages of 20 and 34 were more likely to engage in unnecessary weight control attempts than the other age groups. Pervasive social stigma around being overweight and obese among women [ 59 ], particularly in the younger generation could be linked to our findings, suggesting the growing obsession of being thin is a greater issue among Korean young women [ 49 ]. This could be explained by the strong societal emphasis on appearance, which causes an extreme obsession in body shape, and abnormal enthusiasm to pursue unnecessary and unhealthy weight loss strategies among young women regardless of their actual body weight [ 24 , 52 , 53 ]. Increasing awareness of necessary weight perception for lower SES groups may be important in order to reduce the SES-related gap in accurately understanding body weight in Korean women. In addition, emphasizing the importance of healthy body weight maintenance is important, especially for women who misperceive their body weight [ 27 ]. In sum, addressing the social stigma around being overweight and obese, and the importance of understanding and maintaining health body weight should become a public health priority in Korea. Promoting healthy body weight and accurate weight perception across different SES levels may have positive impact on preventing unnecessary weight control attempts among the Korean women adult population. Despite its importance, there are a limited number of studies examining socio-economic determinants of weight perception and weight control attempts among East Asian Populations. The results from this study provide preliminary understanding of the association between SES, perceived body weight, and weight control attempts among Korean women, which contribute to adding more evidence in East Asian populations for cross-cultural comparison with Western populations. Nonetheless, we have identified several limitations of this study. First, the design of the study was cross-sectional in nature, so our findings are unable to indicate a causal relationship. In order to fully assess the relationship between SES and perceived body weight, and weight control attempts; further longitudinal analysis is needed. Although individual’s BMI was calculated using directly measured height and weight, demographic and health behaviour information were self-reported. The individual’s response may have been influenced by their gender and socioeconomic status [ 64 ]. Conclusion Our study indicates that higher income and educational levels are predictors of accurate weight perception among Korean women. We also found that misperception of body weight increases one’s likelihood of engaging in unnecessary weight control attempts. These findings, combined with the existing literature, suggest that SES is a strong predictor of perceived weight and weight control attempts in both Western and high-income East Asian countries. Given that the high desire to be thin, regardless of actual weight status, among the Korean adult population, it is recommended that policy makers and health professionals promote the importance of understanding and maintaining a healthy body weight. Abbreviations SES Socioeconomic Status KNHANES Korea National Health and Nutrition Examination Survey BMI Body Mass Index KDAC Korea Disease Control and Prevention Agency WHO World Health Organization RRR Relative Risk Ratio Declarations Acknowledgement Authors are grateful to Dr. Calypse Agborasangaya, Alberta Health, Canada and the former ACHIEVE post-doctoral fellows at Map centre for Urban Health Solutions (formerly, Centre for Research on Inner City Health), St. Michael’s Hospital, Canada for useful comments and the language editing on an earlier version of this article. Authors’ contributions JK, EYL, and JH contributed to the design of the study. JK and EYL prepared the data. JK and JH analyzed and interpreted the results from data analyses. JK, EYL, and JH wrote and finalized the manuscript. The authors read and approved the final manuscript. Funding This study was funded by Wonkwang University in 2023. Availability of data and materials The datasets generated and /or analyzed during the current study are available from the Korea National Health and Nutrition Examination Survey (http://knhanes.cdc.go.kr/knhanes). Ethics approval and consent to participate All participants of the KNHANES were informed that they had been randomly selected to take part in the survey and that their data could be used for further analyses. Written informed consent was obtained from all individuals. The KNHANES protocol was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Korea Disease Control and Prevention Agency. Data from KNHANES wave 7 (2018) was collected with the approval of the Research Ethics Review Committee of the Korea Disease Control and Prevention Agency (KCDA) under the following reference numbers: 2018-01-03-P-A. For certain years (2016-2017), ethical approval was waived by the Act (Article 2, Paragraph 1) and Enforcement Regulation (Article 2, Paragraph 2, item 1) of the Bioethics and Safety Act. Consent for publication Not applicable. Competing interests None to declare. References Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, et al. Epidemic obesity and type 2 diabetes in Asia. Lancet. 2006;368:1681–8. Jang M, Berry D. Overweight, obesity, and metabolic syndrome in adults and children in South Korea: a review of the literature. Clin Nurs Res. 2011;20:276–91. Jeong SM, Jung JH, Yang YS, Kim W, Cho IY, Lee YB, Han K. 2023 obesity fact sheet: prevalence of obesity and abdominal obesity in adults, adolescents, and children in Korea from 2012 to 2021. 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Weight misperception in relation to weight-related attitudes and behaviors among overweight and obese US adults. Int J Behav Nutr Phys Act. 2011;8:20. Kweon S, Kim Y, Jang MJ, Kim Y, Kim K, Choi S, et al. Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol. 2014;43:69–77. Stajkovic S, Aitken EM, Holroyd-Leduc J. Unintentional weight loss in older adults. CMAJ. 2011;183:443–9. World Health Organization. Obesity: preventing and managing the global epidemic. WHO Tech Rep Ser. 2002;894:1–253. Korea Centers for Disease Control and Prevention (KCDC). The fifth Korea National Health and Nutrition Examination Survey data user guide. Cheongju: KCDC; 2012. Lee K. Distribution characteristics of the medical services in Korea. J Korean Geogr Soc. 2005;40:242–51. Hwang J, Shon C. Relationship between socioeconomic status and type 2 diabetes: results from Korea National Health and Nutrition Examination Survey (KNHANES) 2010–2012. BMJ Open. 2014;4:e005710. Gutiérrez-Fisac JL, López García E, Rodriguez-Artalejo F, Banegas JR, Guallar-Castillón P. Self-perception of being overweight in Spanish adults. Eur J Clin Nutr. 2002;56:866–72. Schieman S, Pudrovska T, Eccles R. Perceptions of body weight among older adults: analyses of the intersection of gender, race, and socioeconomic status. J Gerontol B Psychol Sci Soc Sci. 2007;62:S415–23. Wardle J, Griffith J. Socioeconomic status and weight control practices in British adults. J Epidemiol Community Health. 2001;55:185–90. Fang K, Li H, Ma A, Dong J, Xie J, Zhou Y, et al. Weight underestimation for adults in Beijing and its association with chronic disease awareness and weight management. Lipids Health Dis. 2018;17:225. Akgöz A, Gözüm S, Ilgaz A. A comparative study on perception of body weight of women from different socioeconomic levels. Health Care Women Int. 2017;38:861–72. Jeffery RW, French SA. Socioeconomic status and weight control practices among 20- to 45-year-old women. Am J Public Health. 1996;86:1005. Chung W, Lee S, Lim SJ, Kim J. Modifying effects of education on the association between lifestyle behaviors and the risk of obesity: evidence from South Korea. BMC Public Health. 2016;16:1–9. von Lengerke T, Mielck A. Body weight dissatisfaction by socioeconomic status among obese, preobese and normal weight women and men: results of the cross-sectional KORA Augsburg S4 population survey. BMC Public Health. 2012;12:342. Booth KM, Pinkston MM, Poston WSC. Obesity and the built environment. J Am Diet Assoc. 2005;105(5 Suppl 1):110–7. Gordon-Larsen P, Nelson MC, Page P, Popkin BM. Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics. 2006;117:417–24. Chang VW, Lauderdale DS. Income disparities in body mass index and obesity in the United States, 1971–2002. Arch Intern Med. 2005;165:2122–8. Haynes A, Kersbergen I, Sutin A, Daly M, Robinson E. A systematic review of the relationship between weight status perceptions and weight loss attempts, strategies, behaviours and outcomes. Obes Rev. 2018;19:347–63. Ferraro ZM, Patterson S, Chaput JP. Unhealthy weight control practices: culprits and clinical recommendations. Clin Med Insights Endocrinol Diabetes. 2015;8:7–11. Boo S. Misperception of body weight and associated factors. Nurs Health Sci. 2014;16:468–75. Lee HR, Lee HE, Choi J, Kim JH, Han HL. Social media use, body image, and psychological well-being: a cross-cultural comparison of Korea and the United States. J Health Commun. 2014;19:1343–58. Kwon S, Kim R, Lee JT, Kim J, Song S, Kim S, et al. Association of smartphone use with body image distortion and weight loss behaviors in Korean adolescents. JAMA Netw Open. 2022;5:e2213237. Craig PL, Caterson ID. Weight and perceptions of body image in women and men in a Sydney sample. Community Health Stud. 1990;14:373–83. Park B, Cho HN, Choi E, Seo DH, Kim S, Park YR, et al. Self-perceptions of body weight status according to age-groups among Korean women: a nationwide population-based survey. PLoS ONE. 2019;14:e0210486. Rhee SY, Park SW, Kim DJ, Woo J. Gender disparity in the secular trends for obesity prevalence in Korea: analyses based on the KNHANES 1998–2009. Korean J Intern Med. 2013;28:29–34. Khang YH, Yun SC. Trends in general and abdominal obesity among Korean adults: findings from 1998, 2001, 2005, and 2007 Korea National Health and Nutrition Examination Surveys. J Korean Med Sci. 2010;25:1582–8. Kim DS, Kim HS, Cho Y, Cho SI. The effects of actual and perceived body weight on unhealthy weight control behaviors and depressed mood among adult women in Seoul, Korea. J Prev Med Public Health. 2008;41:323–30. Neumark-Sztainer D, Paxton SJ, Hannan PJ, Haines J, Story M. Does body satisfaction matter? Five-year longitudinal associations between body satisfaction and health behaviors in adolescent females and males. J Adolesc Health. 2006;39:244–51. Eisenberg ME, Neumark-Sztainer D, Story M, Perry C. The role of social norms and friends' influences on unhealthy weight-control behaviors among adolescent girls. Soc Sci Med. 2005;60:1165–73. Sikorski C, Luppa M, Luck T, Riedel-Heller SG. Weight stigma gets under the skin—evidence for an adapted psychological mediation framework—a systematic review. Obesity. 2015;23:266–76. Chu YT, Huang RY, Chen TTW, Chen PF, Lee CC, Chiu SC, et al. Effect of health literacy and shared decision-making on choice of weight-loss plan among overweight or obese participants receiving a prototype artificial intelligence robot intervention facilitating weight-loss management decisions. Digit Health. 2022;8:20552076221136372. Bello CB, Balogun MO, Ogundipe L, Adebayo KO, Adeoye AO, Salami SO, et al. Influence of eHealth literacy and health promotion behavior on body mass index of workers in the public sector. Digit Health. 2024;10:23779608241274253. Frisco ML, Lybbert EA, Muller C, Grodsky E, Warren JR. Do high school experiences shape midlife body weight? Soc Sci Med. 2025;367:117693. Shahin L, Olesen TB, Olsen MH, Andersen BL, Kristensen PL, Thomsen MN, et al. The impact of education level on weight loss in a primary care-anchored eHealth lifestyle coaching program in Denmark: a randomized controlled trial. Nutrients. 2024;16:795. Hébert JR, Peterson KE, Hurley TG, Stoddard AM, Cohen N, Field AE, et al. The effect of social desirability trait on self-reported dietary measures among multi-ethnic female health center employees. Ann Epidemiol. 2001;11:417–27. Additional Declarations No competing interests reported. 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Socioeconomic differences in weight perception and weight control attempts among Korean women: Evidence from a national survey","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity is a substantial public health concern around the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In South Korea (Korea thereafter), the prevalence of obesity has steadily increased over the past decade among the adult population [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. A recent study using data from the national health checkup database showed that approximately 35.7% of the Korean adult population is either overweight or obese (Body mass index [BMI]\u0026thinsp;\u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This estimated prevalence is approximately 10% higher than the corresponding prevalence reported in 1998 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Over the past decades, different trends of obesity rate by gender are observed in Korea. For women, the rate of overweight and obesity has remained relatively stable and high (23.9% in 2009 and 27.8% in 2023) over the past decades while the rate for men significantly increased (35.6% in 2009 and 45.6% in 2023) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In addition to gender, previous studies suggested that socioeconomic status (SES) is an important predictor of obesity [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. For instance, obesity is more prevalent among women with lower SES while among men, higher prevalence of obesity is observed in higher SES [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As obesity is an important risk factor in the development of chronic disease, gender and SES inequalities in obesity may relate to engendering another health inequality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA growing body of literature suggests that weight perception is an important factor in preventing obesity and maintaining healthy weight [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Weight perception typically refers to \u0026ldquo;the degree of concordance between perceived and measured weight\u0026rdquo; [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and it was suggested that the misperception of body weight is problematic as it affects the ability to achieve and maintain a healthy weight [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The perception of body weight may vary according to gender and SES [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For instance, women are more likely to worry about being overweight or obese while men tend to be less concerned about their weight [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. With respect to SES and weight perception, higher income and higher educational attainment appear to be associated with a better understanding of weight appropriateness, suggesting that SES is a predictor of accurate understanding of body weight [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDifferences in perception of body weight, which vary across SES groups, are closely linked to different weight control attempts, indicating that accurate perception of body weight leads healthy or necessary weight control [\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Studies on weight control practices in the U.S. showed that a considerable number of clinically normal-weight (BMI between 18-25kg/m\u003csup\u003e2\u003c/sup\u003e) individuals attempted or desired weight loss while a similar number of overweight individuals did not [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These results may support that actual weight status is not as a strong predictor of weight control attempts as it is expected, but self-perceived weight might be a more important predictor [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDespite the importance of better understanding accurate weight perception and weight control attempt by SES in managing and preventing obesity, there is limited evidence on these relationships among Korean women. A recent study on the Korean adult population suggested that both weight perception and weight control attempts could greatly differ by gender and SES [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Although this study provided some evidence on weight perception and weight control attempt in the Korean context, it examined only weight under-perception and unecessary weight control attempt by SES and gender. In the present study, we further included under-, accurate- and over-perception of individual\u0026rsquo;s body weight to examine 1) an association between SES and weight perception and 2) a link between weight perception and weight control attempt as well as a potential role of SES in weight control attempt among Korean women.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eData and study population\u003c/p\u003e\u003cp\u003eThis study used data from Korean National Health and Nutrition Examination Survey (KNHANES) 2016\u0026ndash;2018 (wave 7), a nationally representative population-based survey. The KNHANES was conducted by the Ministry of Health and Welfare of Korea and the Korea Disease Control and Prevention Agency (KDCA), with the purpose of examining the general health and nutrition status of the Korean population. The data were collected from a multi-stage, clustered probability sample of non-institutionalized Korean civilians [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The KNHANES survey included four components: a health interview survey, a health behaviour survey, physical health examinations, and a nutrition survey. The survey information was collected through face-to-face interviews and a follow-up health examination was conducted. The heath examinations were performed by trained medical personnels who collected samples, data, and tested for chronic disease [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA total of 24269 individuals (women: 13198; men: 11071) were surveyed for the 2016\u0026ndash;2018 wave. Our analysis included a total of 7253 women aged 19\u0026ndash;64 years old, who participated in both the health examination and the health interview. We excluded respondents who did not complete both the examination and interview and those over 65 years old, as unintentional or involuntary weight loss is commonly observed in older adults [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMeasures\u003c/p\u003e\u003cp\u003e\u003cem\u003eWeight perception\u003c/em\u003e: To determine self-perceived weight status, individuals were asked the following question: \u003cem\u003e\u0026ldquo;Do you consider yourself to be very underweight, slightly underweight, ideal weight, slightly obese, or very obese?\u0026rdquo;\u003c/em\u003e For data analysis, self-perceived weight was classified into underweight (\u003cem\u003every underweight\u003c/em\u003e and \u003cem\u003eslightly underweight\u003c/em\u003e), normal (\u003cem\u003eidea weight\u003c/em\u003e) and obese (\u003cem\u003eslightly obese\u003c/em\u003e and \u003cem\u003every obese\u003c/em\u003e) groups. For actual body weight status, we used respondents\u0026rsquo; Body Mass Index (BMI), derived from measurements of height and weight collected during physical health examinations (Weight (kg)/Height (m)\u003csup\u003e2\u003c/sup\u003e). The following cut off values were used to assign respondents to the corresponding BMI categories: obese weight (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25); normal weight (BMI 18.5\u0026ndash;24.9); and underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The BMI classification was followed the World Health Organization (WHO) and KDCA criteria. Based on the BMI classification and self-perceived weight status, we reassigned individuals into three weight perception groups by assessing how correctly they perceived their weight in relation to their actual weight category: \u003cem\u003eunder-estimation, accurate estimation, and over-estimation\u003c/em\u003e. For example, if an individual perceived herself as being obese and her calculated BMI was also in the obese category, she was considered to have accurately estimated her weight whereas individuals with inaccurately estimated their weight were placed the under-estimation or over-estimation group in our analytic models. More details are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClassification of Weight Perception by Actual BMI and Self-Perceived Weight Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActual BMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-Perceived Weight Status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePerception Classification\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003every thin or slightly thin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eaccurate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enormal, slightly overweight, or very overweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eoverestimated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNormal weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eaccurate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eslightly overweight or very overweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eoverestimated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eObese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eslightly overweight or very overweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eaccurate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enormal, slightly thin, or very thin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eunderestimated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eWeight control attempt\u003c/em\u003e: Individuals were also asked about their experience of weight control attempt within the past year. The experience of weight control attempt was determined from the following question in the KNHANES: \u0026ldquo;\u003cem\u003eWithin the past year, have you tried to control your weight?\u003c/em\u003e\u0026rdquo;. The survey participants responded 1) \u003cem\u003eYes, to lose weight\u003c/em\u003e; 2) \u003cem\u003eYes, to gain weight\u003c/em\u003e; 3) \u003cem\u003eYes, to maintain weight\u003c/em\u003e; 4) \u003cem\u003eNo, I did not\u003c/em\u003e. Based on an individual\u0026rsquo;s BMI and weight control experience, we assigned each individual into three groups: Unnecessary control, necessary control, and no control. Underweight individuals who attempted to gain weight were assigned to the necessary control group, while those who attempted to maintain or lose weight were placed in the unnecessary control group. Normal weight individuals who reported to maintain weight were included in the necessary control group, whereas those who attempted to either lose or gain weight were assigned to the unnecessary control group. Obese individuals who had attempted to lose weight were categorized as necessary control, while those who attempted to maintain or gain weight were considered to be in the unnecessary control group. Participants who reported no attempt to control their body weight\u0026mdash;whether through loss, maintenance, or gain\u0026mdash;were assigned to the no control group, regardless of BMI. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the classification of weight control attempts by respondents\u0026rsquo; BMI status.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClassification of Weight Control Attempts by BMI Status\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eActual BMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWeight Control Attempt\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup Classification\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eUnder weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to gain weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to maintain weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnnecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to lose weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnnecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo weight control attempt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNormal weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to maintain weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to lose weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnnecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to gain weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnnecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo weight control attempt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eObese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to lose weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to maintain weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnnecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttempted to gain weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnnecessary Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo weight control attempt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo Control\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eEither no active weight control attempt (i.e., doing nothing about weight) or unnecessary weight control (i.e., attempts to gain weight in non-obese individuals, trying to maintain or even gain weight in obese individuals) was considered to be unhealthy patterns [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Participants who responded that they tried to control weight during the past year were also asked to indicate the methods used for weight control (i.e., diet, exercise, other methods).\u003c/p\u003e\u003cp\u003e\u003cem\u003eSES\u003c/em\u003e: Educational attainment and household income were used to indicate SES. Educational attainment was divided into three categories: completion of middle school or less, high school, and post-secondary education (i.e., college, university, and graduate school). In addition, we used age-sex adjusted monthly household income quartiles, which were defined by the KNAHNES survey [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eCovariates\u003c/em\u003e: Demographic and health behaviour variables\u0026mdash;age, residence region, smoking habit, high-risk drinking behaviour, and physical activity\u0026mdash;were included as covariates. Age was divided into three categories: 19\u0026ndash;34, 35\u0026ndash;49, and 50\u0026ndash;64 years old. In the KNHANES, residence region data were obtained using the 17 regional categories (i.e., Seoul, seven metropolitan cities, one special self-governing city and nine provinces). In this study, we classified the 17 regions into two regions (Metro Seoul and non-Metro Seoul) as geographical disparities are observed between these two regions. Specifically, the geographic-related social and health inequalities between these two regions are a well-known concern as more social and health resources are concentrated in the Metro Seoul region [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The Metro Seoul region included Seoul, Incheon metropolitan cities, and Gyeonggi province, in which approximately half of the entire Korean population dwell. For indicators of healthy behaviour, we included smoking habits, high-risk drinking behaviour, and physical activity. Current smoking habits were categorized into \u0026ldquo;Currently smoking\u0026rdquo; or \u0026ldquo;Currently not smoking.\u0026rdquo; Regarding high-risk drinking, those who drank more than five cups of alcohol at a single event and more than twice a week were defined as the high-risk drinking group. This classification of high-risk drinking behaviour was defined and provided by the KHNAHES [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAnalysis\u003c/p\u003e\u003cp\u003eWe estimated two separate multinomial logistic regression analyses to explore SES and weight perception, and to assess the impact of weight perception on weight control attempts among Korean women. All analyses were conducted using STATA v.12 and the results were reported as relative risk ratio (RRR) and 95% confidence intervals (95% CIs). Differences were considered statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and the population weight provided by KNHANES was applied to all regression models as it is suggested to use the weight to estimate a representation of the Korean population [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe characteristics of the study population by body weight perception are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Of 7253 Korean women, 8.2% of the women underestimated and 25.1% overestimated their body weight. A higher percentage of women aged 20\u0026ndash;34 years, who had completed university and with higher income (Quartile 3 and 4) overestimated their body weight. More than 50% (estimated 2,712,195) of the women in the overestimation group had engaged in unnecessary weight control attempts.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGeneral characteristics of Korean women\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1724\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2700\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2829\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarriage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSinge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried or partnered\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHousehold income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ1 (Lowest)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e701\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1766\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ4 (Highest)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2507\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMetro Seoul areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Metro Seoul areas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-rated health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery good \u0026amp; good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3933\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery poor \u0026amp; poor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1212\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-risk drinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight perception\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnder-estimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e595\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAccurate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4835\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOver-estimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight control\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNecessary attempt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnnecessary attempt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo attempts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents the results of the multinomial regression, showing the relationship between SES and body weight perception. Educational attainment was associated with underestimated body weight, suggesting that women of lower educational attainment (completion of middle school or lower) were more likely to underestimate their body weight (RRR: 1.38, 95% CI: 1.00\u0026ndash;1.90). Furthermore, women of the lowest educational attainment were less likely to overestimate their body weight (RRR: 0.75, 95% CI: 0.61\u0026ndash;0.93) whereas those with the completion of high school showed higher likelihood of overestimating their body weight (RRR: 1.16, 95% CI: 1.01\u0026ndash;1.33). Unlike educational level, household income was not a statistically significant predictor for either underestimated or overestimated body weight among Korean women. Those aged 50\u0026ndash;64 years showed less likelihood of overestimating their body weight (RRR: 0.70, 95% CI: 0.58\u0026ndash;0.89). The poor self-rated health and high-risk drinking behaviour were also associated with overestimated body weight.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultinomial logistic regression examining an association between socioeconomic status and weight perception\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eUnderestimated group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eOverestimated group\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRRR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRRR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.38*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00\u0026ndash;1.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.75*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.61\u0026ndash;0.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.77\u0026ndash;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.16*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.01\u0026ndash;1.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHousehold income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ1 (Lowest)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.77\u0026ndash;1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.67\u0026ndash;1.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.79\u0026ndash;1.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.81\u0026ndash;1.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ3 (Highest)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u0026ndash;1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.80\u0026ndash;1.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eCovariates\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u0026ndash;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.75\u0026ndash;1.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.99\u0026ndash;1.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.70*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.58\u0026ndash;0.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarriage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSinge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.86\u0026ndash;1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.84\u0026ndash;1.15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Metro Seoul\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.80\u0026ndash;1.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.90\u0026ndash;1.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-rated health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.81\u0026ndash;1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.41*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.22\u0026ndash;1.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery poor \u0026amp; poor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.74\u0026ndash;1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.33*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.09\u0026ndash;1.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.75\u0026ndash;1.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.84\u0026ndash;1.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh-risk drinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.47\u0026ndash;1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.26*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00\u0026ndash;1.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e*\u003c/sup\u003e P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003e Reference groups: Age (19\u0026ndash;34), Education (Post-secondary), Income (Q4- Highest), Region (Metro-Seoul areas),\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eSelf-rated health (Very good and good), Smoking (No), High-risk drinking (No)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the relationship between weight perception and weight control attempts based on our multinomial logistic regression. Individuals who overestimated their body weight had higher risk of attempting in unnecessary weight control attempts (RRR: 5.37, 95% CI: 3.83\u0026ndash;7.52). Compared to the younger group (age 19\u0026ndash;34), older age group (age 35\u0026ndash;59) were less likely to employ unnecessary weight control activities as compared to the accurate weight control attempt group.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultinomial logistic regression examining an association between weight perception and weight control attempts\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eUnnecessary attempt\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eNo attempt\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRRR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRRR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight perception\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnderestimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.40\u0026ndash;1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.86\u0026ndash;2.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverestimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.37*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.83\u0026ndash;7.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.74*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.91\u0026ndash;3.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.72*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.56\u0026ndash;0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.81\u0026ndash;1.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.72\u0026ndash;1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.74\u0026ndash;1.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHousehold income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ1 (Lowest)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.84\u0026ndash;1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.61*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.23\u0026ndash;2.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.74\u0026ndash;1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.96\u0026ndash;1.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ3 (Highest)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.71\u0026ndash;1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.92\u0026ndash;1.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.67*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.55\u0026ndash;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.79*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.63\u0026ndash;0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.51*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.41\u0026ndash;0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.66*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.52\u0026ndash;0.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarriage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSinge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.90\u0026ndash;1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.83\u0026ndash;1.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Metro Seoul\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82\u0026ndash;1.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.84\u0026ndash;1.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-rated health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.85*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.73\u0026ndash;0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.77\u0026ndash;1.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery bad \u0026amp; bad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.67*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.55\u0026ndash;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.68\u0026ndash;1.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.84\u0026ndash;1.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.95\u0026ndash;1.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh risk drinking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.74\u0026ndash;1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.80\u0026ndash;1.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e* P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003e Reference groups: Age (19\u0026ndash;34), Education (Post-secondary), Income (Q4- Highest), Region (Metro-Seoul areas)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eSelf-rated health (Very good and good), Smoking (No), High-risk drinking (No)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWomen who overestimated their body weight were more likely to attempt to control their weight while those in the underestimation group showed less likelihood of participating in any weight control attempts. The lowest income quartile was also a predictor of not participating in any weight control attempts.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the results of the differences in weight control attempts by education and income across weight perception groups. Women with middle school education in the underestimation group were significantly more likely to engage in unnecessary weight control attempts (RRR: 2.44, 95% CI: 1.10\u0026ndash;5.38), followed by those with high school education (RRR: 1.91, 95% CI: 1.03\u0026ndash;3.55), compared to those with post-secondary education. Notably, those with the completion of high school in the overestimation group were less likely to engage in any weight control attempts (RRR: 0.65, 95% CI: 0.44\u0026ndash;0.98).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultinomial logistic regression examining differences in weight perceptions by education, income and weight control attempts\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e\u003cp\u003eWeight control attempts\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnnecessary attempt\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003eNo attempt\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRRR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eRRR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDifferences by education\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderestimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.44*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.10\u0026ndash;5.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.53\u0026ndash;2.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.91*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e1.03\u0026ndash;3.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.54\u0026ndash;1.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverestimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.96\u0026ndash;2.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.82\u0026ndash;2.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.62\u0026ndash;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.65*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.44\u0026ndash;0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDifferences by income\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderestimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.36\u0026ndash;2.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.49\u0026ndash;3.33\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.89\u0026ndash;3.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.97\u0026ndash;3.66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.82\u0026ndash;2.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.91*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.06\u0026ndash;3.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverestimated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.53\u0026ndash;2.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.48\u0026ndash;2.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.96\u0026ndash;2.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.60\u0026ndash;1.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQ3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e0.86\u0026ndash;2.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.81\u0026ndash;2.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e* P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003e Reference groups: Education (Post-secondary), Income (Q4- Highest)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIndividuals in the underestimation group with middle-high income (Quartile 3) were significantly more likely not to engage in any weight control attempt (RRR: 1.91, 95% CI: 1.06\u0026ndash;3.48) compared to the highest income quartile.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe objectives of this study were to examine the associations between SES and weight perception and to investigate a role of weight perception on the relationship between SES and weight control attempts. Our study found that SES predicts perception of body weight and approaches to weight control attempts among Korean women. In relation to underestimating body weight, lower income and educational levels posed as a barrier to accurate perception of body weight. Similarly, the lowest income and educational levels also associated with underestimation of body weight. With respect to weight control attempts, weight misperception, both under- and over-estimation, was an important predictor of misleading to unnecessary weight control attempts, suggesting that accurate perception of body weight plays an important role in encouraging necessary weight control attempts among Korean women.\u003c/p\u003e\u003cp\u003eOur findings are similar to the existing evidence primarily from Western countries, showing SES gradients in accurate understanding of body weight. A growing body of literature addresses that people with higher educational attainment and higher income have more accurate perceptions of their body weight [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, this inverse relationship between SES and accurate perception of body weight was also observed in women [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Accompanied by the existing evidence, our findings support the conclusion that SES, in particular lower education, is a common predictor for underestimation of body weight among women across Western and developed East Asian countries [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe relationship between education and weight perception can be explained by close links between education and healthy lifestyle typically observed among women [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. People with higher education are more likely to participate in health promoting behaviour as they have more interest in maintaining healthier lifestyle and better access to resources and information that motivates healthy behaviours [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Meanwhile, limited access to the resources necessary for engaging in healthy lifestyles (e.g., nutritionally adequate food, access to recreation centres, indoor gyms, or parks) and lack of knowledge of health promoting behaviours are observed in lower SES populations [\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConsistent with previous findings [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], our results also indicate that underestimating of body weight is associated with more likelihood of attempting unnecessary weight control attempts. Previous studies noted that, due to the influence of Western culture and rapid economic development in Korea, the perspective of feminine beauty was shifted to slimness or thinness from a traditional value of ideal woman\u0026rsquo;s body type being plump [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. In modern Korean society, this trend has intensified, particularly among female adolescents and young adults, driven by the pervasive influence of social media, celebrity culture, and the global spread of K-pop and K-beauty industries. Platforms like Instagram, YouTube, and TikTok increasingly promote highly curated and edited body images that reinforce unrealistic beauty standards [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. At the same time, the rise of digital health tracking apps and diet-focused content has normalized restrictive eating and excessive weight monitoring [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. These societal pressures, compounded by peer comparisons and fear of social stigma [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], may contribute to distorted body image and increase the risk of unhealthy weight control practices, even among individuals with normal or underweight BMI.\u003c/p\u003e\u003cp\u003eThe greater likelihood of attempting unnecessary weight control in the weight misperception group is problematic because they are more susceptible to adopting unnecessary and often unnecessary weight control activities. Indeed, a growing body of literature reports that Korean women are not satisfied with their body weights, and have, often unnecessary, a lifetime goal to be thin [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. It has been found that the high level of weight concern or desire to be thin often leads women to eating pathology, often show as engaging in unhealthy forms of weight control, such as long-term fasting, self-induced vomiting, and extreme diet control [\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Our findings, combined with the thin body preference, suggest that public health action should be made on diminishing widespread weight-related stigma particularly in women body [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. In addition, it is important to guide Korean women to accurately perceive their body weight and to engage in necessary weight control attempts, including balanced diet and physical activity, when they clinically need to lose their weight.\u003c/p\u003e\u003cp\u003eOur study further examined the differential effects of SES on weight control attempts across weight perception groups. The findings suggest that women with lower educational attainment in the underestimation group were more likely to engage in unnecessary weight control attempts also suggest that educational disparities may influence access to accurate health information and shape perceptions of healthy weight management. Recent studies have highlighted that limited health literacy is associated with poorer weight management outcomes and the adoption of maladaptive weight control attempts [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNotably, within the overestimation group, high school graduates were less likely to engage in any weight control attempts despite perceiving themselves as overweight. This discrepancy between perception and behavior indicates a potential mismatch between body image and motivation or capacity to act. Psychological factors, such as low self-efficacy, body dissatisfaction, or even social fatigue related to weight norms, may explain why some individuals who overestimate their weight choose not to engage in weight control efforts. This aligns with findings from recent research emphasizing the complex interplay between body image, perception, and health behaviours [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe result that middle-high income individuals (Quartile 3) in the underestimation group were significantly more likely not to engage in any weight control behavior compared to the highest income quartile. This challenges the common assumption that lower SES predicts lower health engagement. It is possible that individuals in this income category perceive themselves as less at risk or face time constraints and lifestyle demands that reduce their participation in weight-related health behaviours. These nuances highlight the need for a more layered understanding of how income interacts with weight perceptions and health actions, as suggested by recent studies exploring the socioeconomic determinants of health behaviours [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAge was also a predictor of weight control attempts among Korean women. In particular, those between the ages of 20 and 34 were more likely to engage in unnecessary weight control attempts than the other age groups. Pervasive social stigma around being overweight and obese among women [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], particularly in the younger generation could be linked to our findings, suggesting the growing obsession of being thin is a greater issue among Korean young women [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This could be explained by the strong societal emphasis on appearance, which causes an extreme obsession in body shape, and abnormal enthusiasm to pursue unnecessary and unhealthy weight loss strategies among young women regardless of their actual body weight [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIncreasing awareness of necessary weight perception for lower SES groups may be important in order to reduce the SES-related gap in accurately understanding body weight in Korean women. In addition, emphasizing the importance of healthy body weight maintenance is important, especially for women who misperceive their body weight [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In sum, addressing the social stigma around being overweight and obese, and the importance of understanding and maintaining health body weight should become a public health priority in Korea. Promoting healthy body weight and accurate weight perception across different SES levels may have positive impact on preventing unnecessary weight control attempts among the Korean women adult population.\u003c/p\u003e\u003cp\u003eDespite its importance, there are a limited number of studies examining socio-economic determinants of weight perception and weight control attempts among East Asian Populations. The results from this study provide preliminary understanding of the association between SES, perceived body weight, and weight control attempts among Korean women, which contribute to adding more evidence in East Asian populations for cross-cultural comparison with Western populations. Nonetheless, we have identified several limitations of this study. First, the design of the study was cross-sectional in nature, so our findings are unable to indicate a causal relationship. In order to fully assess the relationship between SES and perceived body weight, and weight control attempts; further longitudinal analysis is needed. Although individual\u0026rsquo;s BMI was calculated using directly measured height and weight, demographic and health behaviour information were self-reported. The individual\u0026rsquo;s response may have been influenced by their gender and socioeconomic status [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study indicates that higher income and educational levels are predictors of accurate weight perception among Korean women. We also found that misperception of body weight increases one\u0026rsquo;s likelihood of engaging in unnecessary weight control attempts. These findings, combined with the existing literature, suggest that SES is a strong predictor of perceived weight and weight control attempts in both Western and high-income East Asian countries. Given that the high desire to be thin, regardless of actual weight status, among the Korean adult population, it is recommended that policy makers and health professionals promote the importance of understanding and maintaining a healthy body weight.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSES Socioeconomic Status\u003c/p\u003e\n\u003cp\u003eKNHANES\u003cstrong\u003e\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eKorea National Health and Nutrition Examination Survey\u003c/p\u003e\n\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Body Mass Index\u003c/p\u003e\n\u003cp\u003eKDAC Korea Disease Control and Prevention Agency\u003c/p\u003e\n\u003cp\u003eWHO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;World Health Organization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRRR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Relative Risk Ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors are grateful to Dr. Calypse Agborasangaya, Alberta Health, Canada and the former ACHIEVE post-doctoral fellows at Map centre for Urban Health Solutions (formerly, Centre for Research on Inner City Health), St. Michael\u0026rsquo;s Hospital, Canada for useful comments and the language editing on an earlier version of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJK, EYL, and JH contributed to the design of the study. JK and EYL\u0026nbsp;prepared the data.\u0026nbsp;JK and JH\u0026nbsp;analyzed and interpreted the results from data analyses.\u0026nbsp;JK, EYL, and JH wrote and finalized the manuscript.\u0026nbsp;The authors read and approved the final\u0026nbsp;manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Wonkwang University in 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and /or analyzed during the current study are available from the Korea National Health and Nutrition Examination Survey (http://knhanes.cdc.go.kr/knhanes).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants of the KNHANES were informed that they had been randomly selected to take part in the survey and that their data could be used for further analyses. Written informed consent was obtained from all individuals. The KNHANES protocol was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of the Korea Disease Control and Prevention Agency. Data from KNHANES wave 7 (2018) was collected with the approval of the Research Ethics Review Committee of the Korea Disease Control and Prevention Agency (KCDA) under the following reference numbers: 2018-01-03-P-A. For certain years (2016-2017), ethical approval was waived by the Act (Article 2, Paragraph 1) and Enforcement Regulation (Article 2, Paragraph 2, item 1) of the Bioethics and Safety Act.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, et al. Epidemic obesity and type 2 diabetes in Asia. Lancet. 2006;368:1681\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJang M, Berry D. Overweight, obesity, and metabolic syndrome in adults and children in South Korea: a review of the literature. 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Ann Epidemiol. 2001;11:417\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-health-population-and-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"johp","sideBox":"Learn more about [Journal of Health, Population and Nutrition](http://jhpn.biomedcentral.com/)","snPcode":"41043","submissionUrl":"https://submission.nature.com/new-submission/41043/3","title":"Journal of Health, Population and Nutrition","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Weight perception, weight control, weight control attempt, socioeconomic status, Korea","lastPublishedDoi":"10.21203/rs.3.rs-7966841/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7966841/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eWeight perception is an important factor for weight health as misperception of body weight could influence one\u0026rsquo;s ability to achieve healthy weight. It has been suggested that the perception of body weight may vary across gender and socioeconomic status (SES) strata. The primary purpose of this study was to examine the association between SES and weight perception among Korean women. The secondary aim was to assess whether weight perception is associated with weight control attempts after adjusting for SES.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA total of 7253 women (19\u0026ndash;64 years old) who participated in the Korea National Health and Nutrition Examination Survey (KNHANES) 2016\u0026ndash;2018 were included in our analysis. Actual weight status measured by body mass index (BMI; kg/m\u003csup\u003e2\u003c/sup\u003e) and self-perceived weight status were used to classify respondents into three weight perception groups: under-estimation group, accurate-estimation group, and over-estimation group. Based on self-reported weight control attempts, respondents were divided into three groups: necessary control group, unnecessary control group, and no attempt group. Two separate multinomial logistic regressions were conducted.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eLower educational attainment was associated with underestimation of body weight (RRR: 1.38, 95% CI: 1.00\u0026ndash;1.90). Women with middle school education were less likely to overestimate their weight (RRR: 0.75, 95% CI: 0.61\u0026ndash;0.93) while high school graduates were more likely to overestimate their weight (RRR: 1.16, 95% CI: 1.01\u0026ndash;1.33).\u003c/p\u003e","manuscriptTitle":"Beyond the looking glass - Socioeconomic differences in weight perception and weight control attempts among Korean women: Evidence from a national survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 18:03:11","doi":"10.21203/rs.3.rs-7966841/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-26T04:17:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T23:07:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149967943838900783668630961527309704477","date":"2026-04-06T04:31:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"57208550140804737893709497389732571733","date":"2026-04-05T12:26:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238790472365644315410286136615747655355","date":"2026-03-19T13:52:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-12T18:05:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303275507143768330192179013108684081987","date":"2025-11-06T08:06:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-04T11:39:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-29T14:24:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-29T14:21:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Health, Population and Nutrition","date":"2025-10-28T07:54:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-health-population-and-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"johp","sideBox":"Learn more about [Journal of Health, Population and Nutrition](http://jhpn.biomedcentral.com/)","snPcode":"41043","submissionUrl":"https://submission.nature.com/new-submission/41043/3","title":"Journal of Health, Population and Nutrition","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f3687291-8771-433f-936d-a1d38156af94","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-11-13T18:03:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-13 18:03:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7966841","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7966841","identity":"rs-7966841","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}