Prediction model for weight control experience in Korean men with obesity in their 30s and 40s

Prediction model for weight control experience in Korean men with obesity in their 30s and 40s | 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 Article Prediction model for weight control experience in Korean men with obesity in their 30s and 40s Myeunghee Han This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4149509/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted 17 You are reading this latest preprint version Abstract Background Obesity is an abnormal and potentially dangerous condition caused by excess body fat accumulation. The number of people with obesity is increasing worldwide. Obesity is the primary cause of various diseases; therefore, it is crucial to make efforts to control and maintain a healthy body weight. Identifying the factors that influence men with obesity to attempt to control and not control their weight is essential. The objective of this study was to create a prediction model for weight control experience among Korean men in their 30s and 40s. Methods We analyzed data from the 2022 Community Health Survey and included 12,311 men who were overweight or obese. The men were divided into two groups based on their weight control experience: 1) Yes group (n = 9,405) and 2) No group (n = 2,906). Chi-square and independent t-tests were used to compare general and health-related characteristics between the groups. Decision tree analysis was used to build a prediction model for weight control experience. A split-sample test was conducted to validate the model. Results Several predictive models were generated based on the total number of participants, age, and body mass index as the first separating factors. The major factors affecting weight control among men with obesity in their 30s and 40s in Korea include subjective body shape, age, body mass index, education level, completion of hypertension management education, awareness of blood glucose levels, and smoking status. Subjective body shape was confirmed to significantly affect weight control experience. Conclusions It is necessary to support individuals in maintaining and managing an ideal weight by promoting a desirable perception of their body shape. In addition, there is an urgent need to provide obesity prevention and management education to those who have no weight control experience, particularly those at high risk, as identified in this study. Health sciences/Health care Health sciences/Risk factors adult men overweight obesity weight control CHS decision tree Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION 1.1 Background Obesity is an abnormal and potentially dangerous condition caused by excess body fat accumulation [ 1 ]. The degree of obesity can be determined by calculating the body mass index (BMI), with a BMI of ≥ 25 indicating overweight and a BMI of ≥ 30 indicating obesity [ 2 ]. The number of people with obesity is increasing worldwide, with approximately 800 million people being obese and 670 million of them being adults, indicating serious problems [ 2 ]. According to the analysis of obesity data by the Korean Society for the Study of Obesity in 2023, the obesity rate in men and women has increased over the past 10 years, from 2012 to 2021 [ 3 ]. Women showed a narrow increase in the obesity rate, from 23.4% in 2012 to 27.8% in 2021, whereas men showed an increase of approximately 1.3 times, from 37.3% in 2012 to 49.2% in 2021, with one out of two men being obese. Men in their 30s had the highest rate of obesity at 55.4%, followed by men in their 40s at 54.1% [ 3 ]. Obesity is the leading cause of various diseases, including high blood pressure, diabetes, cardiovascular disease, stroke, breast cancer, and colon cancer [ 4 , 5 ]. Therefore, it is crucial to make efforts to control and maintain a healthy body weight. However, according to a report, while 30% of women with average weight think they are obese and try to lose weight, over half of men with obesity do not try to lose weight despite being aware of their condition [ 6 ]. Identifying the factors that influence weight control attempts among men with obesity and also identifying high-risk groups who do not attempt to lose weight is essential. This information is necessary to prioritize the prevention and management of obesity. While the following study did not specifically relate to weight control in men with obesity in their 30s and 40s, prior research has revealed that individuals with obesity usually attempt weight control based on their subjective perception of their body rather than their BMI [ 7 ]. Moreover, people with higher social and economic status are generally more interested in their health. In the context of obesity, individuals often try to manage their weight as a way of controlling their health [ 8 ]. Those who perceive themselves to be in good health usually attempt weight control more often than those who perceive themselves to be in poor health [ 9 ]. Education level also affects weight control experiences, as individuals with higher education levels tend to manage their weight more [ 8 , 9 ]. The obesity rate among men in their 30s and 40s in South Korea is rapidly increasing. Despite the urgent need for weight management, the current research on weight control in individuals with obesity has focused only on adolescents [ 10 , 11 ], women [ 12 – 14 ], and college students [ 15 , 16 ]. Therefore, we aimed to propose a model predicting the weight management experience of men in their 30s and 40s who are overweight and obese using the 2022 Community Health Survey (CHS) data. 1.2 Purpose of study This study was conducted to identify the factors that predict weight control experiences among men who are overweight and obese in their 30s and 40s in Korea. The specific objectives were as follows: 1) Compare the general characteristics of individuals based on their weight control experiences 2) Compare the health-related characteristics of individuals based on their weight control experiences 3) Identify the pathways that predict the weight control experiences of the participants 4) Identify the pathways that predict the weight control experiences of the participants based on age 5) Identify the pathways that predict the weight control experiences of the participants based on BMI 2. METHODS 2.1 Study design This empirical analysis utilized cross-sectional secondary data from the 2022 CHS [ 17 ] to construct a model predicting weight control experience among Korean men who are overweight or obese in their 30s and 40s. 2.2 Study data and participants In 2022, the Korea Centers for Disease Control and Prevention conducted the CHS to collect data from the community, establish health care plans, and develop health initiatives. The survey was conducted from August 16 to October 31, 2022, and involved adults aged ≥ 19 years. Trained interviewers visited the sampled households and conducted face-to-face interviews using electronic questionnaires to collect the data. This study focused on the BMI of male participants (n = 106,119) aged 30–49 (n = 28,388) out of the total 231,785 participants in the 2022 CHS. Among them, 12,311 responded to questions regarding their weight control experiences in the overweight (n = 11,386) and obese (n = 2,706) groups. The participants were divided into two groups: a weight control experience group (Yes group, n = 9,405) and a non-weight control experience group (No group, n = 2,906). 2.3 Measures The description of this research tool was extracted from the Guidelines for Using Raw Data from the 2022 CHS [ 17 ]. 1) General characteristics The general characteristics of the participants included the following: age (30s [30–39 years], 40s [40–49 years]), level of education (high school graduation or below, 2-year/3-year college graduation or above), economic activity (yes, no), marital status (spouse present, spouse absent [unmarried, divorced, separated, widowed]), place of residence (neighborhood, rural area), household type (single-person, multi-person), recipient of basic livelihood security benefits (yes, no), household income (monthly, in ten thousand won), happiness (1 [very dissatisfied]–10 [very satisfied]), and quality of life (EuroQol-5 Dimension) [ 18 ]. 2) Health-related characteristics The variables related to health characteristics and lifestyle habits of the participants included: 1) subjective health status (poor, fair, good), 2) BMI (overweight, obese), 3) body shape perception (skinny, average, obese), 4) current smoking status (yes, no), 5) amount of cigarettes smoked per day (< 15, ≥ 15), 6) alcohol consumption (yes, no), 7) frequency of alcohol consumption in the past year (never, < 1 time/month, about once a month, 2–4 times a month, 2–3 times a week, ≥ 4 times a week), 8) amount of alcohol consumed per session (1–6 cups, 7–10 cups, etc.), 9) frequency of binge drinking in the past month (never, < 1 time/month, about once a month, about once a week, almost every day), 10) frequency of breakfast consumption per week (0, 1–2, 3–4, 5–7), 11) awareness of nutrition labeling (yes, no), 12) understanding of nutrition labeling (yes, no), 13) use of nutrition labeling (yes, no), 14) food safety (adequate and diverse food intake, adequate but not diverse food intake, occasional food shortage, frequent food shortage), 15) frequency of vigorous exercise per week, 16) duration of vigorous exercise per session (hours), 17) frequency of moderate-intensity exercise per week, 18) duration of moderate-intensity exercise per session (hours), 19) number of days walked per week, 20) duration of walking per day (hours), 21) presence of depression (Patient Health Questionnaire-9, out of 10), 22) stress level (almost never, slightly, moderately, very much), 23) history of high blood pressure diagnosis (yes, no), 24) awareness of blood pressure readings (yes, no), 25) experience with education on high blood pressure management (yes, no), 26) presence of diabetes (yes, no), 27) awareness of blood glucose readings (yes, no), 28) experience with education on diabetes management (yes, no), and finally, 29) utilization of health care facilities (yes, no) [ 17 ]. 2.4 Ethical statement Based on the Enforcement Rules of the Act on Life Ethics and Safety regulations, the 2022 CHS data is considered public data and not subject to review for human research, and informed consent was not required. Therefore, this study was exempted from review by the university’s Institutional Review Board (IRB No. 1041495-202403-HR-04-01). 2.5 Statistical methods This study utilized SPSS version 29.0 for data analysis. The chi-square and independent t-tests were used to compare the general and health-related characteristics between the two groups. Decision tree analysis was used to predict the experience of weight control. Decision tree analysis is a useful method for big data analysis. The advantage of this method is that the data analysis results are implemented through a tree structure, making interpretation easy and highly visible [19]. This study’s data consisted of categorical and continuous variables; therefore, Chi-squared Automatic Interaction Detection, an algorithm reflecting both characteristics, was selected for analysis. In addition, the decision tree analysis settings were a maximum level of 3, a parent node of 100, and a child node of 50 [20]. We conducted a decision tree analysis for all participants, age, and BMI as the first splits. The significance level of this study was p<.05 [21]. 3. RESULTS 3.1. General characteristics A total of 9,405 participants (76.4%) had experience with weight control, whereas 2,906 (23.6%) had no experience. Comparing the two groups, the percentage of participants in their 40s was significantly higher among those without experience (63.8%; p<.001), and participants with a college degree or higher accounted for a high percentage of those with experience (76.0%; p<.001). The weight control group had a significantly higher percentage of employed individuals (p=.021) and those living in urban areas (p<.001). The percentages of participants living with other family members and those receiving basic livelihood support were significantly higher among those without experience (p=.006 and p<.001, respectively). The weight control group had a significantly higher average monthly income of 496.38 million won compared with 469.40 million won for those without experience (p<.001). The happiness index (life satisfaction) was significantly higher in the weight control group, with an average score of 7.24, compared with 6.96 for those without experience (p<.001). The quality of life was also significantly higher in the weight control group, with an average score of 0.94, compared with 0.93 for those without experience (p=.033). Both groups had a higher percentage of married individuals, with no significant difference between them (p=.145) (Table1). Table 1. General characteristics (N=12,311) Characteristics Categories Total (N=12,311) Experience in controlling body weight p-value Yes group (n=9405, 76.4) No group (n=2906, 23.6) Age 30’s 5535(45.0) 4482(47.7) 1053(36.2) <.001 40’s 6776(55.0) 4923(52.3) 1853(63.8) Education level ≤High school 3345(27.2) 2256(24.0) 1089(37.5) <.001 ≥College 8962(72.8) 7146(76.0) 1816(62.5) Economic activity No 819(6.7) 598(6.4) 221(7.6) .021 Yes 11492(93.3) 8807(93.6) 2685(92.4) Marital status Single 4460(36.2) 3374(35.9) 1086(37.4) .145 Married 7851(63.8) 6031(64.1) 1820(62.6) Residence area City 8359(67.9) 6484(68.9) 1875(64.5) <.001 Province 3952(32.1) 2921(31.1) 1031(35.5) Household type Single 1840(14.9) 1452(15.4) 388(13.4) .006 Other 10471(85.1) 7953(84.6) 2518(86.6) Basic livelihood recipients No 12106(98.3) 9273(98.6) 2833(97.5) <.001 Yes 205(1.7) 132(1.4) 73(2.5) Household income (10,000won,month) 490.08±281.11 496.38±980.47 469.40±682.27 <.001 Happiness 7.18±1.67 7.24±..63 6.96±..79 <.001 EQ-5D 0.93±0.05 0.94±0.04 0.93±..06 .033 3.2. Health-related characteristics The comparison of health characteristics between the weight control experienced and non-experienced groups is shown in Table 2 . The subjective health level was the highest in the weight control experienced group, with 50.1% responding as “good.” In contrast, the weight control non-experienced group showed the highest response rate of “average” at 46.2%, indicating a significant difference (p<.001). The obesity rate was significantly higher in the weight control experienced group (21.3%) than in the non-experienced group (17.3%; p<.001). The weight control experienced group had the highest rate of feeling obese, while the non-experienced group had the highest smoking rate at 65.0% (p<.001). The weight control experienced group showed the highest alcohol consumption rate at 95.0% (p=.028). The weight control experienced group had the highest frequency of drinking twice a month at 31.3%, whereas the non-experienced group had the highest frequency of drinking 2–3 times a week, showing a significant difference (p<.001). For high-risk drinking, the weight control experienced group showed a significantly higher rate of 31.2% for once a week than the non-experienced group at 29.9% (p<.001). Both groups had a higher rate of not having breakfast (p=.002), while the weight control experienced group had the highest rate of recognizing nutrition labeling at 69.8% (p<.001). The rate of not understanding nutrition labeling was high in both groups, but the weight control non-experienced group showed the highest rate at 75.4% (p<.001). Both groups had a high rate of using nutrition labeling, but the weight control experienced group had the highest rate of 82.7% (p<.001). Both groups had a high rate of consuming sufficient amounts and a variety of foods for food safety, but the weight control experienced group had the highest rate at 77.3% (p<.001). During one week, the frequency of high-intensity physical activity was higher in the weight control group who implemented the program, with an average of 1.36 days compared with the non-implementing group’s 0.82 days (p<.001). Additionally, the high-intensity physical activity time was significantly higher in the weight control implementing group, with an average of 1.26 hours (p<.001). The frequency of moderate-intensity physical activity was also significantly higher in the weight control implementing group (average of 1.65 days) compared with the non-implementing group’s 1.28 days (p<.001). The moderate-intensity physical activity time was higher in the non-implementing group, with an average of 1.15 hours compared with the implementing group’s 1.04 hours (p<.001). The weight control implementing group also walked more days (p<.001) and for a longer period (p<.001) than the non-implementing group. Both groups had a stress level of “feeling a lot” at a rate of over 50% (p=.025), and the weight control implementing group had a higher percentage of individuals with high blood pressure at 84.3% (p<.001). The percentage of individuals who were aware of their blood pressure was higher in the weight control non-implementing group at 36.5% (p<.001), and the percentage of those who had completed blood pressure management education was higher in the weight control implementing group at 40.7% (p<.001). The percentage of individuals diagnosed with diabetes was higher in the weight control non-implementing group at 7.6% (p=.030), and the percentage of those who were aware of their blood glucose levels was higher in the weight control implementing group at 32.3% (p<.001). The percentage of those who completed diabetes management education was higher in the weight control non-implementing group (65.2%, p<.001), and the weight control implementing group had a higher percentage of individuals who utilized health care facilities (47.0%, p=.002). No significant differences were observed between the two groups in terms of smoking status (p=.069), alcohol consumption (p=.470), or depression (p=.139). Table 2. Health-related characteristics (N=12,311) Characteristics Categories Total (N=12,311) Experience in controlling body weight p-value Yes group (n=9405, 76.4) No group (n=2906, 23.6) Subjective health status Bad 851(6.9) 626(6.7) 225(7.7) <.001 Average 5405(43.9) 4064(43.2) 1341(46.2) Good 6055(49.2) 4715(50.1) 1340(46.1) Body Mass Index(kg/m 2 ) Overweight 9803(79.6) 7399(78.7) 2404(82.7) <.001 Obesity 2508(20.4) 2006(21.3) 502(17.3) Body shape perception Thin 37(0.3) 18(0.2) 19(0.7) <.001 Average 1922(1.6) 1149(12.2) 773(26.6) Obesity 10352(84.1) 8238(87.6) 2114(72.7) Smoking* No 3798(43.8) 3034(46.7) 764(35.0) <.001 Yes 4880(56.2) 3463(53.3) 1417(65.0) Amount of cigarettes <15 1923(15.6) 1438(15.3) 485(16.7) .069 ≥15 10388(84.4) 7967(84.7) 2421(83.3) Drinking No 650(5.3) 473(5.0) 177(6.1) .028 Yes 12661(94.7) 8932(95.0) 2729(93.9) Frequency of drinking* None 1129(9.7) 856(9.6) 273(10.0) <.001 <1/month 1528(13.1) 1201(13.4) 327(12.0) 1/month 1418(12.2) 1069(12.0) 349(12.8) 2-4/month 1418(30.2) 2800(31.3) 717(26.3) 2-3/week 3093(26.5) 2367(26.5) 726(26.6) ≥4/week 976(8.4) 639(7.2) 337(12.3) Amount of drinking(7cups)* 1-6cups 4519(42.9) 3481(43.1) 1038(42.3) .470 7-10cups 6013(57.1) 4595(56.9) 1418(57.7) Binge drinking* None 1879(17.8) 1429(17.7) 450(18.3) <.001 <1/month 2004(19.0) 1569(19.4) 435(17.7) 1/month 2599(21.1) 2027(25.1) 572(23.3) 1/week 3251(30.9) 2516(31.2) 735(29.9) Daily 10532(7.6) 535(6.6) 264(10.7) Days of breakfast None 5208(42.3) 3945(41.9) 1263(43.5) .002 1-2/week 1399(11.4) 1081(11.5) 318(10.9) 3-4/week 1308(10.6) 1053(11.2) 255(8.8) 5-7/week 4396(35.7) 3326(35.4) 1070(36.8) Awareness of nutrition label* No 3970(32.3) 2839(30.2) 1131(39.0) <.001 Yes 8328(67.7) 6561(69.8) 1767(61.0) Comprehension of nutrition label No 5029(60.4) 3696(56.3) 1333(75.4) <.001 Yes 3298(39.6) 2864(43.7) 434(24.6) Use of nutrition label* No 611(18.5) 496(17.3) 115(26.5) <.001 Yes 2686(81.5) 2367(82.7) 319(73.5) Food security* Sufficient quantity and variety 9411(76.5) 7274(77.3) 2137(73.6) <.001 Sufficient quantity but no variety 2635(21.4) 1952(20.8) 683(23.5) Sometimes not enough food 219(1.8) 149(1.6) 70(2.4) Often insufficient food 45(0.4) 30(0.3) 15(0.5) Days of strenuous physical activity(week) 1.23±1.90 1.36±..94 0.82±.873 <.001 Time of strenuous physical activity(hour) 1.19±..55 1.17±..54 1.26±..54 <.001 Days of moderate physical activity(week) 1.56±..16 1.65±..16 1.28±..13 <.001 Time of moderate physical activity(hour) 1.06±..47 1.04±..46 1.15±..13 <.001 Days of walking(week) 4.17±..63 4.36±..55 3.58±2.80 <.001 Time of walking(hour) 0.79±..36 0.80±.806 0.76±..37 <.001 Depression* No 11948(97.2) 9141(97.3) 2807(96.8) .139 Yes 348(2.8) 254(2.7) 94(3.2) Stress level Rare 582(4.7) 444(4.7) 138(4.7) .025 Little 3100(25.2) 2408(25.6) 692(23.8) Much 6892(56.0) 5271(56.0) 1621(55.8) Very much 1737(14.1) 1282(13.6) 4555(15.7) Hypertension No 10133(82.3) 7682(81.7) 2451(84.3) <.001 Yes 2718(17.7) 1723(18.3) 455(15.7) Awareness of blood pressure level* No 3614(29.4) 6836(72.8) 1838(63.5) <.001 Yes 8674(70.6) 2556(27.2) 1058(36.5) Experience of hypertension management education No 1341(61.6) 1021(59.3) 320(70.3) <.001 Yes 836(38.4) 701(40.7) 135(29.7) Diabetes No 11485(93.3) 8880(93.6) 2685(92.4) .030 Yes 286(6.7) 605(6.4) 221(7.6) Awareness of blood sugar level No 8481(69.2) 6338(67.7) 2143(74.3) <.001 Yes 3772(30.8) 3030(32.3) 742(25.7) Experience of diabetes management education No 395(47.8) 318(52.6) 77(34.8) <.001 Yes 431(52.2) 287(47.4) 144(65.2) Use of health institutions No 6617(53.8) 4983(53.0) 1634(56.2) .002 *missing data 3.3. Prediction model for weight control experience The prediction model for weight control experience in the target group is presented in Figure 1 . Subjective body shape perception significantly impacted weight control experience (△p<.001, F=365.67). In cases where individuals perceived themselves as obese (Node 1), 79.6% had experienced weight control, with differences in weight control experience observed based on education level (△p<.001, F=123.43). The weight control attempt rate was 82.2% for those with a college degree or higher (Node 3) and 72.1% for those with a high school degree or lower. For individuals with a college degree or higher, there was a significant difference in weight control experience based on smoking status (△p<.001, F=63.27), with 84.6% of non-smokers having tried weight control compared with 77.3% of smokers. For those with a high school degree or lower (Node 4), completing high blood pressure management education had a significant impact on weight control experience (△p<.001, F=18.272). The weight control attempt rate was 84.5% for those who completed high blood pressure management education and 75.5% for those who did not. Individuals who perceived themselves to be average or below average in terms of subjective body shape perception (Node 2) had different experiences with weight control depending on their education level (Δp<.001, F=46.31). Among those with a college degree or higher, 65.1% had experienced weight control, whereas among those with a high school diploma or lower, only 49.3% had experienced weight control. Among those with a college degree or higher, there were differences in weight control experiences by age (Δp<.001, F=24.43), with 59.3% of those in their 40s and 72.6% of those in their 30s having experienced weight control. Among those with a high school diploma or less (Node 6), there were differences in weight control experiences depending on whether they were aware of their blood glucose levels (Δp<.001, F=17.83). Among those unaware of their blood glucose levels (Node 14), 44.7% had experienced weight control, whereas among those who were aware of their blood glucose levels (Node 15), 63.5% had done so. Individuals who perceived themselves as obese, with a college degree or higher, and did not smoke had the highest rate of weight control (84.6%). On the contrary, individuals who perceived themselves as having an average or below-average weight, had a high school education or lower, and were unaware of their blood glucose levels had the highest rate of not controlling their weight at 55.3%. 3.4. Prediction model for weight control experience by age The analysis of whether the participants had experience controlling their weight was categorized based on age, and the results are shown in Figure 2 . Age was found to be a significant factor affecting weight control experience (△p<.001, F=117.00), where 72.7% of those in their 40s (Node 1) and 81.0% in their 30s (Node 2) had experienced weight control. For those in their 40s, there were differences in weight control experience because of their physical condition (△p<.001, F=262.60). Among those who considered themselves obese (Node 3), 76.8% had experienced weight control, whereas 54.1% of those who considered themselves average or below had experienced weight control. Among those aware of their blood pressure (Node 7), 79.2% had experienced weight control. In contrast, among those who were unaware of their blood pressure (Node 8), 68.6% had experienced weight control; this difference was statistically significant (△p<.001, F=18.272). Among those whose physical condition was average or below (Node 4), there were differences in weight control experience depending on whether they were aware of their blood glucose levels (△p<.001, F=19.480). Among those unaware of their blood glucose levels (Node 9), 49.9% had experienced weight control, whereas among those who were aware of their blood glucose levels (Node 10), 63.3% had experienced weight control. It was found that men in their 30s had different experiences with weight control owing to their physical condition (Δp<0.001, F=77.126). Among those who considered themselves obese (Node 5), 82.8% had experienced weight control, whereas among those who considered themselves to have average or below weight (Node 6), 69.0% had experienced weight control. Regarding those who considered themselves obese, education level had an impact on weight control experiences (Δp<0.001, F=46.98). Those with a college degree or higher (Node 11) had an 84.6% rate of weight control attempts, whereas those who graduated from high school or below had a 75.2% rate. Similarly, among those who considered themselves average or below, education level also impacted weight control experiences (Δp<0.001, F=14.97). Those with a college degree or higher (Node 13) had a 72.6% rate of weight control attempts, whereas those who had graduated from high school or below had a 56.7% rate. The study found that, among those in their 30s who considered themselves obese and had a college degree or higher, the attempt rate for weight control was the highest at 84.6%. Conversely, among those in their 40s who considered themselves average or below weight and were unaware of their blood glucose levels, the rate of not attempting weight control was the highest at 50.1%. 3.5. Prediction model for weight control experience by BMI We categorized the participants based on their experience with weight management using BMI as the first criterion, and the results are shown in Figure 3 . BMI significantly impacted weight management experience (△p<.001, F=46.98). Among those who were overweight, 75.5% attempted to manage their weight, compared with 80.0% of those who were obese. For those who were overweight (Node 1), there was a difference in weight management experience based on physical condition (△p<.001, F=320.46). Among those who perceived themselves as obese (Node 3), 79.3% had attempted weight management if they thought they were average or below. A difference was observed in weight management experience based on education level for those who perceived themselves as obese (Node 3) (△p<.001, F=105.39). Those with a college degree or higher (Node 7) and those with a high school diploma or less (Node 8) had 82.0% and 71.2% weight management experience, respectively. For those who perceived themselves as having an average or below average physical condition (Node 4), there was also a difference in weight management experience based on education level (△p<.001, F=49.07). Those with a college degree or higher (Node 9) and those with a high school diploma or less (Node 10) had 65.2% and 48.5% weight management experience, respectively. Differences were observed in weight control experiences based on the education level of individuals with obesity (Node 2) (△p<.001, F=23.61). A total of 82.5% of those who had graduated from university or higher (Node 5) and 73.9% of those who had graduated from high school or lower (Node 6) had experience with weight control. Among those who graduated from university or higher (Node 5), there were differences in weight control experiences based on smoking status. Of those who did not currently smoke (Node 11), 84.9% had experienced weight control, whereas 78.0% of those who smoked had experienced weight control. The rate of weight control experiences was highest for those who were obese, graduated from a university or higher, and did not currently smoke, with a rate of 84.9%. On the contrary, the rate of not controlling weight was highest for those who were overweight, perceived themselves as having an average or lower weight, and graduated from high school or lower, with a rate of 51.5%. 3.6. Validation of prediction models The validity of the predictive model derived in this study is shown in Table 3 . The risk estimate of the training data for the predictive model derived from all participants was .227, indicating a 77.3% probability of the predictive model being classified properly. The accuracy of the predictive models derived by setting age and BMI as the first separators were 76.9% and 76.7%, respectively, indicating a high probability of all three models being properly classified. Table 3. Validation of prediction model Model Sample Risk Estimate(RE) Standard Error Total Training .227 .005 Test .239 .005 Age Training .231 .005 Test .230 .005 Body Mass Index Training .233 .005 Test .239 .005 4. DISCUSSION We aimed to analyze and predict the weight control experiences of men who were overweight or obese in their 30s and 40s in a local community in 2022. We developed a model to predict weight control based on the collected data. In the predictive model created without specifying the first split, the high-risk group that did not control their weight had a physical self-image of an average or below-average weight, a high school education or lower, did not attempt weight control in 55.3% of cases, and did not know their blood glucose level. In the predictive model derived by setting age as the first split, in the case of those in their 40s, those who considered themselves to have normal or below-average weight had the highest percentage of not attempting weight control (50.1%) when they did not know their blood glucose levels. In the predictive model with BMI as the first split, the highest percentage of people who did not attempt weight control was 51.5%, who felt overweight, had an average or below-average weight, and had a high school education or less. A notable finding of this study is that subjective body perception is closely related to weight control experience. Although this study was not conducted on Korean men with obesity in their 30s and 40s, previous studies have shown that the difference between BMI and body perception is closely related to weight management [22]. According to previous studies that explored the factors influencing weight control behavior among the obese, the most significant factor influencing weight control was subjective weight perception rather than objective indicators such as BMI [7]. A systematic literature review on the relationship between body perception and weight control behavior among adults who were overweight aged ≥55 found that those who perceived themselves as overweight were more likely to manage their weight through intermittent diet or exercise [23]. A significant relationship exists between maintaining a healthy weight and managing obesity; however, research on this topic in South Korea is inadequate. Previous studies have focused on children, teenagers, and female college students [22]. The results of this study also revealed that the body perceptions of men with obesity had a significant impact on their efforts to control their weight. Therefore, it is crucial to support these individuals in accurately perceiving their obesity and recognizing their body shape to manage their weight more effectively. We showed that 50.1% of the individuals in their 40s who believed they had normal or below-average weight and did not know their blood glucose levels did not attempt to control their weight. Previous studies have shown that individuals aged 40–59 have a 1.211 times higher likelihood of attempting to control their weight than those aged 19–39 [24]. This suggests that middle-aged individuals are more interested in improving their appearance and are motivated to control their weight. However, a study by Bouzas et al. [23] found that as individuals age, their interest in their body shape decreases, and their expectations regarding their weight decrease as well. Therefore, further research is needed to determine the impact of age on weight control attempts and the various factors that affect weight control attempts within the same age group. Our results also revealed that individuals with higher education levels were more likely to attempt weight control. This is consistent with previous studies that have shown a similar trend. Therefore, it is important to identify the educational levels of individuals who do not attempt weight control and provide educational programs that consider this factor to promote the importance and methods of weight control.Although not directly revealed in this study, research has shown that individuals with higher socioeconomic status who are obese are more interested in personal health [8]. This indicates they are more likely to manage their weight to maintain good health. Additionally, one study found that subjective health status significantly impacted weight control efforts [9]. Those who perceived their health as good were more likely to make efforts to control their weight than those who perceived their health as poor. Therefore, further research is necessary to accurately identify the factors influencing weight control experiences in men with obesity in their 30s and 40s. This study has several limitations that should be considered in future research. First, there is a lack of research on obesity and weight control among Korean men in their 30s and 40s, making it difficult to accurately compare and analyze the results of this study. Second, the data used in this study were secondary and might not have included all factors affecting weight control. Third, the obesity of the study participants was classified by BMI and did not consider indicators such as waist circumference and body fat percentage, which can accurately classify obesity. Fourth, BMI was calculated using self-reported weight and height; therefore, the BMI might not have been accurate. Finally, only weight control experience was confirmed, and the type of weight control could not be distinguished. 5. CONCLUSIONS We identified several factors influencing the weight management experiences of men with obesity in their 30s and 40s. These factors included self-perception of body shape, education level, age, BMI, blood glucose level, and completion of hypertension management education. In particular, we found that the self-perception of body shape significantly impacted the weight management experience. Therefore, accurately determining one’s weight and recognizing one’s body shape are essential for effective weight management. The study suggests that individuals who have not had experience with weight management but are at high risk should be targeted first. Community efforts are necessary to help these individuals achieve and maintain a healthy weight. LIST OF ABBREVIATIONS BMI, body mass index; CHS, Community Health Survey. DECLARATIONS Ethics approval and consent to participate The data used in this study was from the 2022 CHS, deemed public data by the Enforcement Rules of the Act on Life Ethics and Safety. Therefore, this study was exempted from review by the university’s Institutional Review Board (IRB No. 1041495-202403-HR-04-01), and informed consent was not required. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The author reports that there are no conflicts of interest in this work. Funding None Acknowledgements This study did not receive any financial support from funding agencies. Data availability statement 2022 CHS was public data provided by the Korea Centers for Disease Control and Prevention. Data can be obtained from https://chs.kdca.go.kr/chs/rdr/rdrInfoDownMain.do after receiving approval from the institution. Authors’ contributions Study concept and design: HMH; acquisition of data: HMH; analysis and interpretation of data: HMH; drafting of the manuscript: HMH ; critical revision of the manuscript: HMH; statistical analysis: HMH; obtained funding: HMH; administrative, technical, or material support: HMH; and study supervision: HMH. REFERENCES World Health Organization. Obesity [Internet]. WHO. 2021 [cited 2024 Mar 14]. Available from: https://www.who.int/news-room/facts-in-pictures/detail/6-facts-on-obesity World Health Organization. World Obesity Day 2022- Accelerating action to stop obesity [Internet]. 2023 [cited 2023 Jan 13]. Available from: https://www.who.int/news/item/04-03-2022-world-obesity-day-2022-accelerating-action-to-stop-obesity Obesity KS for the S of. Obesity in Numbers(2023) No. 1 [Internet]. Korean Society for the Study of Obesity. 2023 [cited 2024 Mar 14]. Available from: https://general.kosso.or.kr/html/?pmode=BBBS0001300004&page=1&smode=view&seq=1388&searchValue=&searchTitle=strTitle Kim J, Lee S, Lee H, Shim K, Choi S. Association between weight control methods and depressive symptoms among Korean adults according to age and sex. Korean J Fam Med. 2019;9(5):460–6. Bray G. Medical consequences of obesity. J Clin Endocrinol Metab. 2004;89(6):2583–9. Shin E. Korean man who is obese but doesn’t lose weight vs. Korean woman who is underweight but diets. Health Chosun [Internet]. 2024 Jan 5; Available from: https://m.health.chosun.com/svc/news_view.html?contid=2024010500585 Kim B, Lee Y. The relationship of food behaviors with body image and BMI of female college students in jeonbuk province. Korean J Hum Ecol. 2000;9(2):231–43. Lim Y, Park N, Jeon S, Jeong S, Tserendejid Z, Park H. Analysis of weight control behaviors by body image perception among Korean women in different age groups: Using the 2010 Korea national health and nutrition examination survey data. Korean J Community Nutr. 2015;20(2):141–50. Gu Y, Jeong J, Jeong J, Lee H. Comparison of factors affecting weight control experiences by perception types of body shape. Korean J Heal Educ Promot. 2019;36(4):77–87. Kim Y, Lee Y, Lee Y. Relationship between convergence awareness for healthy weight management and eating behavior, creativity and convergence competency of adolescents. J Nutr Heal. 2022;55(3):376–89. Kang J, Lee J. The Effects of Difference between Body Mass Index and Body weight perception on weight control behavior, physical, stress, and smoke in Korean Adolescents: Based on the Korea National Health and Nutrition Examination Survey 2013-2018. J Korea Soc Wellness. 2022;425–31. Choi K, Kim H, Han S, Tak J. A qualitative study on the successful weight control process by improving eating habits for middle age female. Korean J Heal Psychol. 2020;25(4):667–98. Seong G, Pae M. Consumption of weight-control or health functional foods, dietary habits, and weight perception according to the Body Mass Index of adult women in the Chungcheong Area. Korean J Community Nutr. 2022;27(2):81–93. So E. Factors Associated with Weight Control Intention Among Korean Women. J Humanit Soc Scienes 21. 2021;12(1):1783–92. Lee S, Ko K, Kim N. A qualitative study on failed weight-loss experiences of college students with obesity and overweight. Lee Sook Youn, Ko Keum Bok, Kim Nahyun. 2020;37(2):43–55. Lee J, Chung S, Rho J. A study on the weight control behavior according to cluster types of the motivation to use social media among university students in the Jeonbuk area. J Nutr Heal. 2023;56(2):203–16. Korea Disease Control and Prevention Aency. Community Health Survey 2022 raw data usage guidelines [Internet]. Korea Disease Control and Prevention Aency. 2022 [cited 2024 Mar 2]. Available from: https://chs.kdca.go.kr/chs/mnl/mnlBoardMain.do Nam H, Kim K, Kwon S. Research Report for estimated weight for Quality of Life Survey(EQ-5D). 2007. Choi J, Han H, Kang H, Kim Y. Data mining decision tree by using answer Tree. Seoul; 1998. Seo J., Kim M. A Prediction Model for Quality of Life by Resilience in Disaster Female Victims. Korean J Adult Nurs. 2021;33(6):639–48. Jung M, Kim J. Influence of social capital on depression of older adults living in rural area: a cross-sectional study using the 2019 Korea Cmmunity Health Survey. J Korean Acad Nurs. 2022;52(2):144–56. Kim E, Hwang I, Song Y. Relationship between weight perception and lifestyle according to demographic socioeconomic factors in Korean adults. J Korean Acad Rural Heal Nurs. 2012;7(2):51–8. Bouzas C, Del Mar Bibloni M, Tur J. Relationship between body image and body weight control in overweight ≥55-year-old adults: a systematic review. Int J Environ Res Public Health. 2019;16(9):1622. Seo J, Ma H, Kim S, Kim J, Shin M, Yang Y. Effects of the difference between actual body condition and body image perception on nutrient intake, weight control and mental health in Korean adults: Based on the 5th Korea National Health and Nutrition Examination Survey. J Nutr Heal. 2016;49(3):153–64. Joh H, Oh J, Lee H, Kawachi I. Gender and socioeconomic status in relation to weight perception and weight control behavior in Korean adults. Obes Facts. 2013;6(1):17–27. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 13 Jun, 2024 Reviews received at journal 25 May, 2024 Reviews received at journal 17 May, 2024 Reviews received at journal 15 May, 2024 Reviews received at journal 13 May, 2024 Reviews received at journal 08 May, 2024 Reviewers agreed at journal 08 May, 2024 Reviewers agreed at journal 08 May, 2024 Reviewers agreed at journal 06 May, 2024 Reviewers agreed at journal 06 May, 2024 Reviewers agreed at journal 06 May, 2024 Reviewers agreed at journal 06 May, 2024 Reviewers invited by journal 06 May, 2024 Editor assigned by journal 03 May, 2024 Editor invited by journal 02 Apr, 2024 Submission checks completed at journal 02 Apr, 2024 First submitted to journal 22 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4149509","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":286831198,"identity":"b6681791-0b28-4ca7-b643-09ec841fa046","order_by":0,"name":"Myeunghee Han","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYDCCAwwMEkCqnrG9wYA0LQnMPQegWtiI1cI+I4FILXzHewxvV1TcyeOd+XjjZ94chjx++Qb8WiTPnDG2PHPmWbHk7LRiad5tDMWSbQRsMbiRu02yse0w48bZOQYgLYkbjhHScv8tRMv+m2eMf4O07Ceo5QYvWEti4wweM4gthLwveSb/s2XDmWfGjD1pZZZzt0kkzjiWgF8L3/FjiTcbKu7IMbYf3nzj7TabxP7mAwSsgQC4KgmilKNoGQWjYBSMglGACQARIkvi8jLfOwAAAABJRU5ErkJggg==","orcid":"","institution":"Dongyang University","correspondingAuthor":true,"prefix":"","firstName":"Myeunghee","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2024-03-22 11:50:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4149509/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4149509/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-70833-5","type":"published","date":"2024-08-29T15:57:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54166181,"identity":"b7411541-ef53-4d2a-a8bf-116310354a8f","added_by":"auto","created_at":"2024-04-05 13:30:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27610,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction model of weight control experience\u003c/p\u003e\n\u003cp\u003efigure 1 presented a decision tree of weight control experience in Korean male with age of 30-40s. Individuals who perceived themselves as obese, with a college degree or higher, and did not smoke had the highest rate of weight control (84.6%). On the contrary, individuals who perceived themselves as having an average or below-average weight, had a high school education or lower, and were unaware of their blood glucose levels had the highest rate of not controlling their weight at 55.3%.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4149509/v1/bcffb4a0a63776c9ab3519bf.png"},{"id":54166182,"identity":"c8531bf7-6527-4c60-b528-4d03ac9b9752","added_by":"auto","created_at":"2024-04-05 13:30:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23626,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction model for weight control experience by age\u003c/p\u003e\n\u003cp\u003efigure 2 presented a decision tree of weight control experience by age in Korean male with age of 30-40s. Among those in their 30s who considered themselves obese and had a college degree or higher, the attempt rate for weight control was the highest at 84.6%. Conversely, among those in their 40s who considered themselves average or below weight and were unaware of their blood glucose levels, the rate of not attempting weight control was the highest at 50.1%.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4149509/v1/b99fae32207dca86377ea642.png"},{"id":54166183,"identity":"0c56416d-7aa9-423c-910a-dfb23ee42584","added_by":"auto","created_at":"2024-04-05 13:30:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23721,"visible":true,"origin":"","legend":"\u003cp\u003ePrediction model of weight control experience by BMI\u003c/p\u003e\n\u003cp\u003efigure 3 presented a decision tree of weight control experience by BMI in Korean male with age of 30-40s. The rate of weight control experiences was highest for those who were obese, graduated from a university or higher, and did not currently smoke, with a rate of 84.9%. On the contrary, the rate of not controlling weight was highest for those who were overweight, perceived themselves as having an average or lower weight, and graduated from high school or lower, with a rate of 51.5%.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4149509/v1/14d73b008432b58477c92d32.png"},{"id":63820831,"identity":"9cf0de7c-da78-4f06-9625-8cb257950f2f","added_by":"auto","created_at":"2024-09-02 16:09:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":852887,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4149509/v1/7ca61396-4b17-4231-bb53-f5074efc23c2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction model for weight control experience in Korean men with obesity in their 30s and 40s","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\n \u003ch2\u003e1.1 Background\u003c/h2\u003e\n \u003cp\u003eObesity is an abnormal and potentially dangerous condition caused by excess body fat accumulation [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e]. The degree of obesity can be determined by calculating the body mass index (BMI), with a BMI of \u0026ge;\u0026thinsp;25 indicating overweight and a BMI of \u0026ge;\u0026thinsp;30 indicating obesity [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e]. The number of people with obesity is increasing worldwide, with approximately 800\u0026nbsp;million people being obese and 670\u0026nbsp;million of them being adults, indicating serious problems [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to the analysis of obesity data by the Korean Society for the Study of Obesity in 2023, the obesity rate in men and women has increased over the past 10 years, from 2012 to 2021 [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]. Women showed a narrow increase in the obesity rate, from 23.4% in 2012 to 27.8% in 2021, whereas men showed an increase of approximately 1.3 times, from 37.3% in 2012 to 49.2% in 2021, with one out of two men being obese. Men in their 30s had the highest rate of obesity at 55.4%, followed by men in their 40s at 54.1% [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eObesity is the leading cause of various diseases, including high blood pressure, diabetes, cardiovascular disease, stroke, breast cancer, and colon cancer [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, it is crucial to make efforts to control and maintain a healthy body weight. However, according to a report, while 30% of women with average weight think they are obese and try to lose weight, over half of men with obesity do not try to lose weight despite being aware of their condition [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. Identifying the factors that influence weight control attempts among men with obesity and also identifying high-risk groups who do not attempt to lose weight is essential. This information is necessary to prioritize the prevention and management of obesity.\u003c/p\u003e\n \u003cp\u003eWhile the following study did not specifically relate to weight control in men with obesity in their 30s and 40s, prior research has revealed that individuals with obesity usually attempt weight control based on their subjective perception of their body rather than their BMI [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]. Moreover, people with higher social and economic status are generally more interested in their health. In the context of obesity, individuals often try to manage their weight as a way of controlling their health [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]. Those who perceive themselves to be in good health usually attempt weight control more often than those who perceive themselves to be in poor health [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]. Education level also affects weight control experiences, as individuals with higher education levels tend to manage their weight more [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe obesity rate among men in their 30s and 40s in South Korea is rapidly increasing. Despite the urgent need for weight management, the current research on weight control in individuals with obesity has focused only on adolescents [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e], women [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e], and college students [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. Therefore, we aimed to propose a model predicting the weight management experience of men in their 30s and 40s who are overweight and obese using the 2022 Community Health Survey (CHS) data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e1.2 Purpose of study\u003c/h2\u003e\n \u003cp\u003eThis study was conducted to identify the factors that predict weight control experiences among men who are overweight and obese in their 30s and 40s in Korea. The specific objectives were as follows:\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e1) Compare the general characteristics of individuals based on their weight control experiences\u003c/p\u003e\n\u003cp\u003e2) Compare the health-related characteristics of individuals based on their weight control experiences\u003c/p\u003e\n\u003cp\u003e3) Identify the pathways that predict the weight control experiences of the participants\u003c/p\u003e\n\u003cp\u003e4) Identify the pathways that predict the weight control experiences of the participants based on age\u003c/p\u003e\n\u003cp\u003e5) Identify the pathways that predict the weight control experiences of the participants based on BMI\u003c/p\u003e"},{"header":"2. METHODS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e2.1 Study design\u003c/h2\u003e\n\u003cp\u003eThis empirical analysis utilized cross-sectional secondary data from the 2022 CHS [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e] to construct a model predicting weight control experience among Korean men who are overweight or obese in their 30s and 40s.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e2.2 Study data and participants\u003c/h2\u003e\n\u003cp\u003eIn 2022, the Korea Centers for Disease Control and Prevention conducted the CHS to collect data from the community, establish health care plans, and develop health initiatives. The survey was conducted from August 16 to October 31, 2022, and involved adults aged\u0026thinsp;\u0026ge;\u0026thinsp;19 years. Trained interviewers visited the sampled households and conducted face-to-face interviews using electronic questionnaires to collect the data.\u003c/p\u003e\n\u003cp\u003eThis study focused on the BMI of male participants (n\u0026thinsp;=\u0026thinsp;106,119) aged 30\u0026ndash;49 (n\u0026thinsp;=\u0026thinsp;28,388) out of the total 231,785 participants in the 2022 CHS. Among them, 12,311 responded to questions regarding their weight control experiences in the overweight (n\u0026thinsp;=\u0026thinsp;11,386) and obese (n\u0026thinsp;=\u0026thinsp;2,706) groups. The participants were divided into two groups: a weight control experience group (Yes group, n\u0026thinsp;=\u0026thinsp;9,405) and a non-weight control experience group (No group, n\u0026thinsp;=\u0026thinsp;2,906).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e2.3 Measures\u003c/h2\u003e\n\u003cp\u003eThe description of this research tool was extracted from the Guidelines for Using Raw Data from the 2022 CHS [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e1) General characteristics\u003c/h3\u003e\n\u003cp\u003eThe general characteristics of the participants included the following: age (30s [30\u0026ndash;39 years], 40s [40\u0026ndash;49 years]), level of education (high school graduation or below, 2-year/3-year college graduation or above), economic activity (yes, no), marital status (spouse present, spouse absent [unmarried, divorced, separated, widowed]), place of residence (neighborhood, rural area), household type (single-person, multi-person), recipient of basic livelihood security benefits (yes, no), household income (monthly, in ten thousand won), happiness (1 [very dissatisfied]\u0026ndash;10 [very satisfied]), and quality of life (EuroQol-5 Dimension) [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003e2) Health-related characteristics\u003c/h3\u003e\n\u003cp\u003eThe variables related to health characteristics and lifestyle habits of the participants included: 1) subjective health status (poor, fair, good), 2) BMI (overweight, obese), 3) body shape perception (skinny, average, obese), 4) current smoking status (yes, no), 5) amount of cigarettes smoked per day (\u0026lt;\u0026thinsp;15, \u0026ge;\u0026thinsp;15), 6) alcohol consumption (yes, no), 7) frequency of alcohol consumption in the past year (never, \u0026lt;\u0026thinsp;1 time/month, about once a month, 2\u0026ndash;4 times a month, 2\u0026ndash;3 times a week, \u0026ge;\u0026thinsp;4 times a week), 8) amount of alcohol consumed per session (1\u0026ndash;6 cups, 7\u0026ndash;10 cups, etc.), 9) frequency of binge drinking in the past month (never, \u0026lt;\u0026thinsp;1 time/month, about once a month, about once a week, almost every day), 10) frequency of breakfast consumption per week (0, 1\u0026ndash;2, 3\u0026ndash;4, 5\u0026ndash;7), 11) awareness of nutrition labeling (yes, no), 12) understanding of nutrition labeling (yes, no), 13) use of nutrition labeling (yes, no), 14) food safety (adequate and diverse food intake, adequate but not diverse food intake, occasional food shortage, frequent food shortage), 15) frequency of vigorous exercise per week, 16) duration of vigorous exercise per session (hours), 17) frequency of moderate-intensity exercise per week, 18) duration of moderate-intensity exercise per session (hours), 19) number of days walked per week, 20) duration of walking per day (hours), 21) presence of depression (Patient Health Questionnaire-9, out of 10), 22) stress level (almost never, slightly, moderately, very much), 23) history of high blood pressure diagnosis (yes, no), 24) awareness of blood pressure readings (yes, no), 25) experience with education on high blood pressure management (yes, no), 26) presence of diabetes (yes, no), 27) awareness of blood glucose readings (yes, no), 28) experience with education on diabetes management (yes, no), and finally, 29) utilization of health care facilities (yes, no) [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Ethical statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the Enforcement Rules of the Act on Life Ethics and Safety regulations, the 2022 CHS data is considered public data and not subject to review for human research, and informed consent was not required. Therefore, this study was exempted from review by the university\u0026rsquo;s Institutional Review Board (IRB No. 1041495-202403-HR-04-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized SPSS version 29.0 for data analysis. The chi-square and independent t-tests were used to compare the general and health-related characteristics between the two groups. Decision tree analysis was used to predict the experience of weight control. Decision tree analysis is a useful method for big data analysis. The advantage of this method is that the data analysis results are implemented through a tree structure, making interpretation easy and highly visible [19]. This study\u0026rsquo;s data consisted of categorical and continuous variables; therefore, Chi-squared Automatic Interaction Detection, an algorithm reflecting both characteristics, was selected for analysis. In addition, the decision tree analysis settings were a maximum level of 3, a parent node of 100, and a child node of 50 [20]. We conducted a decision tree analysis for all participants, age, and BMI as the first splits. The significance level of this study was p\u0026lt;.05 [21].\u003c/p\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1. General characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 9,405 participants (76.4%) had experience with weight control, whereas 2,906 (23.6%) had no experience. Comparing the two groups, the percentage of participants in their 40s was significantly higher among those without experience (63.8%; p\u0026lt;.001), and participants with a college degree or higher accounted for a high percentage of those with experience (76.0%; p\u0026lt;.001). The weight control group had a significantly higher percentage of employed individuals (p=.021) and those living in urban areas (p\u0026lt;.001). The percentages of participants living with other family members and those receiving basic livelihood support were significantly higher among those without experience (p=.006 and p\u0026lt;.001, respectively). The weight control group had a significantly higher average monthly income of 496.38 million won compared with 469.40 million won for those without experience (p\u0026lt;.001). The happiness index (life satisfaction) was significantly higher in the weight control group, with an average score of 7.24, compared with 6.96 for those without experience (p\u0026lt;.001). The quality of life was also significantly higher in the weight control group, with an average score of 0.94, compared with 0.93 for those without experience (p=.033). Both groups had a higher percentage of married individuals, with no significant difference between them (p=.145) (Table1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. \u003c/strong\u003eGeneral characteristics (N=12,311)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=12,311)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.229235880398672%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eExperience in controlling body weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=9405, 76.4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=2906, 23.6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003e30\u0026rsquo;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e5535(45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e4482(47.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e1053(36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003e40\u0026rsquo;s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e6776(55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e4923(52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e1853(63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026le;High school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e3345(27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e2256(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e1089(37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;College\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e8962(72.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e7146(76.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e1816(62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eEconomic activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e819(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e598(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e221(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e11492(93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e8807(93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e2685(92.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e4460(36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e3374(35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e1086(37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e.145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e7851(63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e6031(64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e1820(62.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eResidence area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003eCity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e8359(67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e6484(68.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e1875(64.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003eProvince\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e3952(32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e2921(31.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e1031(35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHousehold type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e1840(14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e1452(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e388(13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e10471(85.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e7953(84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e2518(86.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.93355481727575%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eBasic livelihood\u003c/p\u003e\n \u003cp\u003erecipients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.940199335548172%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.11295681063123%\"\u003e\n \u003cp\u003e12106(98.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e9273(98.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.614617940199336%\"\u003e\n \u003cp\u003e2833(97.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.784053156146179%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.480916030534353%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.681933842239186%\"\u003e\n \u003cp\u003e205(1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e132(1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.918575063613233%\"\u003e\n \u003cp\u003e73(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.770382695507486%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHousehold income\u003c/p\u003e\n \u003cp\u003e(10,000won,month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.139767054908486%\"\u003e\n \u003cp\u003e490.08\u0026plusmn;281.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.640599001663894%\"\u003e\n \u003cp\u003e496.38\u0026plusmn;980.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.640599001663894%\"\u003e\n \u003cp\u003e469.40\u0026plusmn;682.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.808652246256239%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.770382695507486%\" colspan=\"2\"\u003e\n \u003cp\u003eHappiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.139767054908486%\"\u003e\n \u003cp\u003e7.18\u0026plusmn;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.640599001663894%\"\u003e\n \u003cp\u003e7.24\u0026plusmn;..63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.640599001663894%\"\u003e\n \u003cp\u003e6.96\u0026plusmn;..79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.808652246256239%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.770382695507486%\" colspan=\"2\"\u003e\n \u003cp\u003eEQ-5D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.139767054908486%\"\u003e\n \u003cp\u003e0.93\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.640599001663894%\"\u003e\n \u003cp\u003e0.94\u0026plusmn;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.640599001663894%\"\u003e\n \u003cp\u003e0.93\u0026plusmn;..06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.808652246256239%\"\u003e\n \u003cp\u003e.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Health-related characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe comparison of health characteristics between the weight control experienced and non-experienced groups is shown in \u003cstrong\u003eTable 2\u003c/strong\u003e. The subjective health level was the highest in the weight control experienced group, with 50.1% responding as \u0026ldquo;good.\u0026rdquo; In contrast, the weight control non-experienced group showed the highest response rate of \u0026ldquo;average\u0026rdquo; at 46.2%, indicating a significant difference (p\u0026lt;.001). The obesity rate was significantly higher in the weight control experienced group (21.3%) than in the non-experienced group (17.3%; p\u0026lt;.001). The weight control experienced group had the highest rate of feeling obese, while the non-experienced group had the highest smoking rate at 65.0% (p\u0026lt;.001). The weight control experienced group showed the highest alcohol consumption rate at 95.0% (p=.028). The weight control experienced group had the highest frequency of drinking twice a month at 31.3%, whereas the non-experienced group had the highest frequency of drinking 2\u0026ndash;3 times a week, showing a significant difference (p\u0026lt;.001). For high-risk drinking, the weight control experienced group showed a significantly higher rate of 31.2% for once a week than the non-experienced group at 29.9% (p\u0026lt;.001). Both groups had a higher rate of not having breakfast (p=.002), while the weight control experienced group had the highest rate of recognizing nutrition labeling at 69.8% (p\u0026lt;.001). The rate of not understanding nutrition labeling was high in both groups, but the weight control non-experienced group showed the highest rate at 75.4% (p\u0026lt;.001). Both groups had a high rate of using nutrition labeling, but the weight control experienced group had the highest rate of 82.7% (p\u0026lt;.001). Both groups had a high rate of consuming sufficient amounts and a variety of foods for food safety, but the weight control experienced group had the highest rate at 77.3% (p\u0026lt;.001).\u003c/p\u003e\n\u003cp\u003eDuring one week, the frequency of high-intensity physical activity was higher in the weight control group who implemented the program, with an average of 1.36 days compared with the non-implementing group\u0026rsquo;s 0.82 days (p\u0026lt;.001). Additionally, the high-intensity physical activity time was significantly higher in the weight control implementing group, with an average of 1.26 hours (p\u0026lt;.001). The frequency of moderate-intensity physical activity was also significantly higher in the weight control implementing group (average of 1.65 days) compared with the non-implementing group\u0026rsquo;s 1.28 days (p\u0026lt;.001). The moderate-intensity physical activity time was higher in the non-implementing group, with an average of 1.15 hours compared with the implementing group\u0026rsquo;s 1.04 hours (p\u0026lt;.001). The weight control implementing group also walked more days (p\u0026lt;.001) and for a longer period (p\u0026lt;.001) than the non-implementing group. Both groups had a stress level of \u0026ldquo;feeling a lot\u0026rdquo; at a rate of over 50% (p=.025), and the weight control implementing group had a higher percentage of individuals with high blood pressure at 84.3% (p\u0026lt;.001). The percentage of individuals who were aware of their blood pressure was higher in the weight control non-implementing group at 36.5% (p\u0026lt;.001), and the percentage of those who had completed blood pressure management education was higher in the weight control implementing group at 40.7% (p\u0026lt;.001). The percentage of individuals diagnosed with diabetes was higher in the weight control non-implementing group at 7.6% (p=.030), and the percentage of those who were aware of their blood glucose levels was higher in the weight control implementing group at 32.3% (p\u0026lt;.001). The percentage of those who completed diabetes management education was higher in the weight control non-implementing group (65.2%, p\u0026lt;.001), and the weight control implementing group had a higher percentage of individuals who utilized health care facilities (47.0%, p=.002). No significant differences were observed between the two groups in terms of smoking status (p=.069), alcohol consumption (p=.470), or depression (p=.139).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Health-related characteristics (N=12,311)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.833333333333332%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.166666666666668%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=12,311)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.833333333333332%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eExperience in controlling body weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.166666666666666%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=9405, 76.4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo group\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=2906, 23.6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"3\"\u003e\n \u003cp\u003eSubjective health\u003c/p\u003e\n \u003cp\u003estatus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eBad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e851(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e626(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e225(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e5405(43.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e4064(43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1341(46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e6055(49.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e4715(50.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1340(46.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eBody Mass Index(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e9803(79.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e7399(78.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2404(82.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e2508(20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2006(21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e502(17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"3\"\u003e\n \u003cp\u003eBody shape perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eThin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e37(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e18(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e19(0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eAverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1922(1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1149(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e773(26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e10352(84.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e8238(87.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2114(72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eSmoking*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e3798(43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e3034(46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e764(35.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e4880(56.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e3463(53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1417(65.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eAmount of\u003c/p\u003e\n \u003cp\u003ecigarettes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003e\u0026lt;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1923(15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1438(15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e485(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e\u0026ge;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e10388(84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e7967(84.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2421(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eDrinking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e650(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e473(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e177(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e12661(94.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e8932(95.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2729(93.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"6\"\u003e\n \u003cp\u003eFrequency of\u003c/p\u003e\n \u003cp\u003edrinking*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1129(9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e856(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e273(10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"6\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e\u0026lt;1/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1528(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1201(13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e327(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e1/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1418(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1069(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e349(12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e2-4/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1418(30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2800(31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e717(26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e2-3/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e3093(26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2367(26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e726(26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e\u0026ge;4/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e976(8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e639(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e337(12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eAmount of\u003c/p\u003e\n \u003cp\u003edrinking(7cups)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003e1-6cups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e4519(42.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e3481(43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1038(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e.470\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e7-10cups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e6013(57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e4595(56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1418(57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"5\"\u003e\n \u003cp\u003eBinge drinking*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1879(17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1429(17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e450(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e\u0026lt;1/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e2004(19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1569(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e435(17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e1/month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e2599(21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2027(25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e572(23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e1/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e3251(30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2516(31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e735(29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eDaily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e10532(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e535(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e264(10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"4\"\u003e\n \u003cp\u003eDays of breakfast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e5208(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e3945(41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1263(43.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"4\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e1-2/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1399(11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1081(11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e318(10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e3-4/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1308(10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1053(11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e255(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003e5-7/week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e4396(35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e3326(35.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1070(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eAwareness of\u003c/p\u003e\n \u003cp\u003enutrition label*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e3970(32.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2839(30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1131(39.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e8328(67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e6561(69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1767(61.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eComprehension of nutrition label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e5029(60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e3696(56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1333(75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e3298(39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2864(43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e434(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eUse of nutrition\u003c/p\u003e\n \u003cp\u003elabel*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e611(18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e496(17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e115(26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e2686(81.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2367(82.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e319(73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eFood security*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\" valign=\"top\"\u003e\n \u003cp\u003eSufficient quantity and variety\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e9411(76.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e7274(77.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2137(73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\" valign=\"top\"\u003e\n \u003cp\u003eSufficient quantity but no variety\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e2635(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1952(20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e683(23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\" valign=\"top\"\u003e\n \u003cp\u003eSometimes not enough food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e219(1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e149(1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e70(2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\" valign=\"top\"\u003e\n \u003cp\u003eOften insufficient food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e45(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e30(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e15(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.89482470784641%\" colspan=\"2\"\u003e\n \u003cp\u003eDays of strenuous physical activity(week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1.23\u0026plusmn;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.36\u0026plusmn;..94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e0.82\u0026plusmn;.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.89482470784641%\" colspan=\"2\"\u003e\n \u003cp\u003eTime of strenuous physical activity(hour)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1.19\u0026plusmn;..55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.17\u0026plusmn;..54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.26\u0026plusmn;..54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.89482470784641%\" colspan=\"2\"\u003e\n \u003cp\u003eDays of moderate physical activity(week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1.56\u0026plusmn;..16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.65\u0026plusmn;..16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.28\u0026plusmn;..13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.89482470784641%\" colspan=\"2\"\u003e\n \u003cp\u003eTime of moderate physical activity(hour)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1.06\u0026plusmn;..47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.04\u0026plusmn;..46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1.15\u0026plusmn;..13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.89482470784641%\" colspan=\"2\"\u003e\n \u003cp\u003eDays of walking(week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e4.17\u0026plusmn;..63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e4.36\u0026plusmn;..55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e3.58\u0026plusmn;2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.89482470784641%\" colspan=\"2\"\u003e\n \u003cp\u003eTime of walking(hour)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e0.79\u0026plusmn;..36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e0.80\u0026plusmn;.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e0.76\u0026plusmn;..37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eDepression*\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e11948(97.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e9141(97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2807(96.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e.139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e348(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e254(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e94(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"4\"\u003e\n \u003cp\u003eStress level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eRare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e582(4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e444(4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e138(4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"4\"\u003e\n \u003cp\u003e.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eLittle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e3100(25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2408(25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e692(23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eMuch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e6892(56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e5271(56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1621(55.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eVery much\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e1737(14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1282(13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e4555(15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e10133(82.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e7682(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2451(84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e2718(17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1723(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e455(15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eAwareness of\u003c/p\u003e\n \u003cp\u003eblood pressure\u003c/p\u003e\n \u003cp\u003elevel*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e3614(29.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e6836(72.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1838(63.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e8674(70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e2556(27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e1058(36.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eExperience of\u003c/p\u003e\n \u003cp\u003ehypertension management education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e1341(61.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1021(59.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e320(70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e836(38.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e701(40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e135(29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e11485(93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e8880(93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2685(92.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e286(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e605(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e221(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eAwareness of\u003c/p\u003e\n \u003cp\u003eblood sugar level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e8481(69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e6338(67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e2143(74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e3772(30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e3030(32.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e742(25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\" rowspan=\"2\"\u003e\n \u003cp\u003eExperience of\u003c/p\u003e\n \u003cp\u003ediabetes management education\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e395(47.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e318(52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e77(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.641509433962263%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.1455525606469%\"\u003e\n \u003cp\u003e431(52.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e287(47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.606469002695416%\"\u003e\n \u003cp\u003e144(65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.871452420701168%\"\u003e\n \u003cp\u003eUse of health institutions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.023372287145243%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19365609348915%\"\u003e\n \u003cp\u003e6617(53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e4983(53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.859766277128548%\"\u003e\n \u003cp\u003e1634(56.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.191986644407345%\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*missing data\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Prediction model for weight control experience\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prediction model for weight control experience in the target group is presented in \u003cstrong\u003eFigure 1\u003c/strong\u003e. Subjective body shape perception significantly impacted weight control experience (△p\u0026lt;.001, F=365.67). In cases where individuals perceived themselves as obese (Node 1), 79.6% had experienced weight control, with differences in weight control experience observed based on education level (△p\u0026lt;.001, F=123.43). The weight control attempt rate was 82.2% for those with a college degree or higher (Node 3) and 72.1% for those with a high school degree or lower. For individuals with a college degree or higher, there was a significant difference in weight control experience based on smoking status (△p\u0026lt;.001, F=63.27), with 84.6% of non-smokers having tried weight control compared with 77.3% of smokers. For those with a high school degree or lower (Node 4), completing high blood pressure management education had a significant impact on weight control experience (△p\u0026lt;.001, F=18.272). The weight control attempt rate was 84.5% for those who completed high blood pressure management education and 75.5% for those who did not.\u003c/p\u003e\n\u003cp\u003eIndividuals who perceived themselves to be average or below average in terms of subjective body shape perception (Node 2) had different experiences with weight control depending on their education level (\u0026Delta;p\u0026lt;.001, F=46.31). Among those with a college degree or higher, 65.1% had experienced weight control, whereas among those with a high school diploma or lower, only 49.3% had experienced weight control. Among those with a college degree or higher, there were differences in weight control experiences by age (\u0026Delta;p\u0026lt;.001, F=24.43), with 59.3% of those in their 40s and 72.6% of those in their 30s having experienced weight control. Among those with a high school diploma or less (Node 6), there were differences in weight control experiences depending on whether they were aware of their blood glucose levels (\u0026Delta;p\u0026lt;.001, F=17.83). Among those unaware of their blood glucose levels (Node 14), 44.7% had experienced weight control, whereas among those who were aware of their blood glucose levels (Node 15), 63.5% had done so.\u003c/p\u003e\n\u003cp\u003eIndividuals who perceived themselves as obese, with a college degree or higher, and did not smoke had the highest rate of weight control (84.6%). On the contrary, individuals who perceived themselves as having an average or below-average weight, had a high school education or lower, and were unaware of their blood glucose levels had the highest rate of not controlling their weight at 55.3%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4. Prediction model for weight control experience by age\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of whether the participants had experience controlling their weight was categorized based on age, and the results are shown in \u003cstrong\u003eFigure 2\u003c/strong\u003e. Age was found to be a significant factor affecting weight control experience (△p\u0026lt;.001, F=117.00), where 72.7% of those in their 40s (Node 1) and 81.0% in their 30s (Node 2) had experienced weight control. For those in their 40s, there were differences in weight control experience because of their physical condition (△p\u0026lt;.001, F=262.60). Among those who considered themselves obese (Node 3), 76.8% had experienced weight control, whereas 54.1% of those who considered themselves average or below had experienced weight control. Among those aware of their blood pressure (Node 7), 79.2% had experienced weight control. In contrast, among those who were unaware of their blood pressure (Node 8), 68.6% had experienced weight control; this difference was statistically significant (△p\u0026lt;.001, F=18.272). Among those whose physical condition was average or below (Node 4), there were differences in weight control experience depending on whether they were aware of their blood glucose levels (△p\u0026lt;.001, F=19.480). Among those unaware of their blood glucose levels (Node 9), 49.9% had experienced weight control, whereas among those who were aware of their blood glucose levels (Node 10), 63.3% had experienced weight control.\u003c/p\u003e\n\u003cp\u003eIt was found that men in their 30s had different experiences with weight control owing to their physical condition (\u0026Delta;p\u0026lt;0.001, F=77.126). Among those who considered themselves obese (Node 5), 82.8% had experienced weight control, whereas among those who considered themselves to have average or below weight (Node 6), 69.0% had experienced weight control. Regarding those who considered themselves obese, education level had an impact on weight control experiences (\u0026Delta;p\u0026lt;0.001, F=46.98). Those with a college degree or higher (Node 11) had an 84.6% rate of weight control attempts, whereas those who graduated from high school or below had a 75.2% rate. Similarly, among those who considered themselves average or below, education level also impacted weight control experiences (\u0026Delta;p\u0026lt;0.001, F=14.97). Those with a college degree or higher (Node 13) had a 72.6% rate of weight control attempts, whereas those who had graduated from high school or below had a 56.7% rate. The study found that, among those in their 30s who considered themselves obese and had a college degree or higher, the attempt rate for weight control was the highest at 84.6%. Conversely, among those in their 40s who considered themselves average or below weight and were unaware of their blood glucose levels, the rate of not attempting weight control was the highest at 50.1%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Prediction model for weight control experience by BMI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe categorized the participants based on their experience with weight management using BMI as the first criterion, and the results are shown in \u003cstrong\u003eFigure 3\u003c/strong\u003e. BMI significantly impacted weight management experience (△p\u0026lt;.001, F=46.98). Among those who were overweight, 75.5% attempted to manage their weight, compared with 80.0% of those who were obese. For those who were overweight (Node 1), there was a difference in weight management experience based on physical condition (△p\u0026lt;.001, F=320.46). Among those who perceived themselves as obese (Node 3), 79.3% had attempted weight management if they thought they were average or below. A difference was observed in weight management experience based on education level for those who perceived themselves as obese (Node 3) (△p\u0026lt;.001, F=105.39). Those with a college degree or higher (Node 7) and those with a high school diploma or less (Node 8) had 82.0% and 71.2% weight management experience, respectively. For those who perceived themselves as having an average or below average physical condition (Node 4), there was also a difference in weight management experience based on education level (△p\u0026lt;.001, F=49.07). Those with a college degree or higher (Node 9) and those with a high school diploma or less (Node 10) had 65.2% and 48.5% weight management experience, respectively.\u003c/p\u003e\n\u003cp\u003eDifferences were observed in weight control experiences based on the education level of individuals with obesity (Node 2) (△p\u0026lt;.001, F=23.61). A total of 82.5% of those who had graduated from university or higher (Node 5) and 73.9% of those who had graduated from high school or lower (Node 6) had experience with weight control. Among those who graduated from university or higher (Node 5), there were differences in weight control experiences based on smoking status. Of those who did not currently smoke (Node 11), 84.9% had experienced weight control, whereas 78.0% of those who smoked had experienced weight control. The rate of weight control experiences was highest for those who were obese, graduated from a university or higher, and did not currently smoke, with a rate of 84.9%. On the contrary, the rate of not controlling weight was highest for those who were overweight, perceived themselves as having an average or lower weight, and graduated from high school or lower, with a rate of 51.5%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6. Validation of prediction models\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe validity of the predictive model derived in this study is shown in \u003cstrong\u003eTable 3\u003c/strong\u003e. The risk estimate of the training data for the predictive model derived from all participants was .227, indicating a 77.3% probability of the predictive model being classified properly. The accuracy of the predictive models derived by setting age and BMI as the first separators were 76.9% and 76.7%, respectively, indicating a high probability of all three models being properly classified.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Validation of prediction model\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk Estimate(RE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard Error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.166666666666668%\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\"\u003e\n \u003cp\u003e.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5%\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.166666666666668%\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\"\u003e\n \u003cp\u003e.230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5%\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.53061224489796%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody Mass Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.428571428571427%\"\u003e\n \u003cp\u003eTraining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.489795918367346%\"\u003e\n \u003cp\u003e.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.551020408163264%\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.166666666666668%\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\"\u003e\n \u003cp\u003e.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.5%\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eWe aimed to analyze and predict the weight control experiences of men who were overweight or obese in their 30s and 40s in a local community in 2022. We developed a model to predict weight control based on the collected data. In the predictive model created without specifying the first split, the high-risk group that did not control their weight had a physical self-image of an average or below-average weight, a high school education or lower, did not attempt weight control in 55.3% of cases, and did not know their blood glucose level. In the predictive model derived by setting age as the first split, in the case of those in their 40s, those who considered themselves to have normal or below-average weight had the highest percentage of not attempting weight control (50.1%) when they did not know their blood glucose levels. In the predictive model with BMI as the first split, the highest percentage of people who did not attempt weight control was 51.5%, who felt overweight, had an average or below-average weight, and had a high school education or less.\u003c/p\u003e\n\u003cp\u003eA notable finding of this study is that subjective body perception is closely related to weight control experience. Although this study was not conducted on Korean men with obesity in their 30s and 40s, previous studies have shown that the difference between BMI and body perception is closely related to weight management [22]. According to previous studies that explored the factors influencing weight control behavior among the obese, the most significant factor influencing weight control was subjective weight perception rather than objective indicators such as BMI [7]. A systematic literature review on the relationship between body perception and weight control behavior among adults who were overweight aged \u0026ge;55 found that those who perceived themselves as overweight were more likely to manage their weight through intermittent diet or exercise [23]. \u003c/p\u003e\n\u003cp\u003eA significant relationship exists between maintaining a healthy weight and managing obesity; however, research on this topic in South Korea is inadequate. Previous studies have focused on children, teenagers, and female college students [22]. The results of this study also revealed that the body perceptions of men with obesity had a significant impact on their efforts to control their weight. Therefore, it is crucial to support these individuals in accurately perceiving their obesity and recognizing their body shape to manage their weight more effectively. We showed that 50.1% of the individuals in their 40s who believed they had normal or below-average weight and did not know their blood glucose levels did not attempt to control their weight. Previous studies have shown that individuals aged 40\u0026ndash;59 have a 1.211 times higher likelihood of attempting to control their weight than those aged 19\u0026ndash;39 [24]. This suggests that middle-aged individuals are more interested in improving their appearance and are motivated to control their weight. However, a study by Bouzas et al. [23] found that as individuals age, their interest in their body shape decreases, and their expectations regarding their weight decrease as well. Therefore, further research is needed to determine the impact of age on weight control attempts and the various factors that affect weight control attempts within the same age group. Our results also revealed that individuals with higher education levels were more likely to attempt weight control. This is consistent with previous studies that have shown a similar trend. Therefore, it is important to identify the educational levels of individuals who do not attempt weight control and provide educational programs that consider this factor to promote the importance and methods of weight control.Although not directly revealed in this study, research has shown that individuals with higher socioeconomic status who are obese are more interested in personal health [8]. This indicates they are more likely to manage their weight to maintain good health. Additionally, one study found that subjective health status significantly impacted weight control efforts [9]. Those who perceived their health as good were more likely to make efforts to control their weight than those who perceived their health as poor. Therefore, further research is necessary to accurately identify the factors influencing weight control experiences in men with obesity in their 30s and 40s.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations that should be considered in future research. First, there is a lack of research on obesity and weight control among Korean men in their 30s and 40s, making it difficult to accurately compare and analyze the results of this study. Second, the data used in this study were secondary and might not have included all factors affecting weight control. Third, the obesity of the study participants was classified by BMI and did not consider indicators such as waist circumference and body fat percentage, which can accurately classify obesity. Fourth, BMI was calculated using self-reported weight and height; therefore, the BMI might not have been accurate. Finally, only weight control experience was confirmed, and the type of weight control could not be distinguished.\u003c/p\u003e"},{"header":"5. CONCLUSIONS","content":"\u003cp\u003eWe identified several factors influencing the weight management experiences of men with obesity in their 30s and 40s. These factors included self-perception of body shape, education level, age, BMI, blood glucose level, and completion of hypertension management education. In particular, we found that the self-perception of body shape significantly impacted the weight management experience. Therefore, accurately determining one\u0026rsquo;s weight and recognizing one\u0026rsquo;s body shape are essential for effective weight management. The study suggests that individuals who have not had experience with weight management but are at high risk should be targeted first. Community efforts are necessary to help these individuals achieve and maintain a healthy weight.\u003c/p\u003e"},{"header":"LIST OF ABBREVIATIONS","content":"\u003cp\u003e\u003cstrong\u003eBMI,\u0026nbsp;\u003c/strong\u003ebody mass index;\u003cstrong\u003e\u0026nbsp;CHS,\u0026nbsp;\u003c/strong\u003eCommunity Health Survey.\u003c/p\u003e"},{"header":"DECLARATIONS","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study was from the 2022 CHS, deemed public data by the Enforcement Rules of the Act on Life Ethics and Safety. Therefore, this study was exempted from review by the university\u0026rsquo;s Institutional Review Board (IRB No. 1041495-202403-HR-04-01), and informed consent was not required.\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\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author reports that there are no conflicts of interest in this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not receive any financial support from funding agencies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e2022 CHS was public data provided by the Korea Centers for Disease Control and Prevention. Data can be obtained from https://chs.kdca.go.kr/chs/rdr/rdrInfoDownMain.do after receiving approval from the institution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept and design: HMH; acquisition of data: HMH; analysis and interpretation of data: HMH; drafting of the manuscript: HMH ; critical revision of the manuscript: HMH; statistical analysis: HMH; obtained funding: HMH; administrative, technical, or material support: HMH; and study supervision: HMH.\u003c/p\u003e"},{"header":"REFERENCES","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Obesity [Internet]. WHO. 2021 [cited 2024 Mar 14]. Available from: https://www.who.int/news-room/facts-in-pictures/detail/6-facts-on-obesity\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. World Obesity Day 2022- Accelerating action to stop obesity [Internet]. 2023 [cited 2023 Jan 13]. Available from: https://www.who.int/news/item/04-03-2022-world-obesity-day-2022-accelerating-action-to-stop-obesity\u003c/li\u003e\n\u003cli\u003eObesity KS for the S of. Obesity in Numbers(2023) No. 1 [Internet]. Korean Society for the Study of Obesity. 2023 [cited 2024 Mar 14]. Available from: https://general.kosso.or.kr/html/?pmode=BBBS0001300004\u0026amp;page=1\u0026amp;smode=view\u0026amp;seq=1388\u0026amp;searchValue=\u0026amp;searchTitle=strTitle\u003c/li\u003e\n\u003cli\u003eKim J, Lee S, Lee H, Shim K, Choi S. Association between weight control methods and depressive symptoms among Korean adults according to age and sex. Korean J Fam Med. 2019;9(5):460\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eBray G. Medical consequences of obesity. J Clin Endocrinol Metab. 2004;89(6):2583\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eShin E. Korean man who is obese but doesn\u0026rsquo;t lose weight vs. Korean woman who is underweight but diets. Health Chosun [Internet]. 2024 Jan 5; Available from: https://m.health.chosun.com/svc/news_view.html?contid=2024010500585\u003c/li\u003e\n\u003cli\u003eKim B, Lee Y. The relationship of food behaviors with body image and BMI of female college students in jeonbuk province. Korean J Hum Ecol. 2000;9(2):231\u0026ndash;43. \u003c/li\u003e\n\u003cli\u003eLim Y, Park N, Jeon S, Jeong S, Tserendejid Z, Park H. Analysis of weight control behaviors by body image perception among Korean women in different age groups: Using the 2010 Korea national health and nutrition examination survey data. Korean J Community Nutr. 2015;20(2):141\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eGu Y, Jeong J, Jeong J, Lee H. Comparison of factors affecting weight control experiences by perception types of body shape. Korean J Heal Educ Promot. 2019;36(4):77\u0026ndash;87. \u003c/li\u003e\n\u003cli\u003eKim Y, Lee Y, Lee Y. Relationship between convergence awareness for healthy weight management and eating behavior, creativity and convergence competency of adolescents. J Nutr Heal. 2022;55(3):376\u0026ndash;89. \u003c/li\u003e\n\u003cli\u003eKang J, Lee J. The Effects of Difference between Body Mass Index and Body weight perception on weight control behavior, physical, stress, and smoke in Korean Adolescents: Based on the Korea National Health and Nutrition Examination Survey 2013-2018. J Korea Soc Wellness. 2022;425\u0026ndash;31. \u003c/li\u003e\n\u003cli\u003eChoi K, Kim H, Han S, Tak J. A qualitative study on the successful weight control process by improving eating habits for middle age female. Korean J Heal Psychol. 2020;25(4):667\u0026ndash;98. \u003c/li\u003e\n\u003cli\u003eSeong G, Pae M. Consumption of weight-control or health functional foods, dietary habits, and weight perception according to the Body Mass Index of adult women in the Chungcheong Area. Korean J Community Nutr. 2022;27(2):81\u0026ndash;93. \u003c/li\u003e\n\u003cli\u003eSo E. Factors Associated with Weight Control Intention Among Korean Women. J Humanit Soc Scienes 21. 2021;12(1):1783\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eLee S, Ko K, Kim N. A qualitative study on failed weight-loss experiences of college students with obesity and overweight. Lee Sook Youn, Ko Keum Bok, Kim Nahyun. 2020;37(2):43\u0026ndash;55. \u003c/li\u003e\n\u003cli\u003eLee J, Chung S, Rho J. A study on the weight control behavior according to cluster types of the motivation to use social media among university students in the Jeonbuk area. J Nutr Heal. 2023;56(2):203\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eKorea Disease Control and Prevention Aency. Community Health Survey 2022 raw data usage guidelines [Internet]. Korea Disease Control and Prevention Aency. 2022 [cited 2024 Mar 2]. Available from: https://chs.kdca.go.kr/chs/mnl/mnlBoardMain.do\u003c/li\u003e\n\u003cli\u003eNam H, Kim K, Kwon S. Research Report for estimated weight for Quality of Life Survey(EQ-5D). 2007. \u003c/li\u003e\n\u003cli\u003eChoi J, Han H, Kang H, Kim Y. Data mining decision tree by using answer Tree. Seoul; 1998. \u003c/li\u003e\n\u003cli\u003eSeo J., Kim M. A Prediction Model for Quality of Life by Resilience in Disaster Female Victims. Korean J Adult Nurs. 2021;33(6):639\u0026ndash;48. \u003c/li\u003e\n\u003cli\u003eJung M, Kim J. Influence of social capital on depression of older adults living in rural area: a cross-sectional study using the 2019 Korea Cmmunity Health Survey. J Korean Acad Nurs. 2022;52(2):144\u0026ndash;56. \u003c/li\u003e\n\u003cli\u003eKim E, Hwang I, Song Y. Relationship between weight perception and lifestyle according to demographic socioeconomic factors in Korean adults. J Korean Acad Rural Heal Nurs. 2012;7(2):51\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eBouzas C, Del Mar Bibloni M, Tur J. Relationship between body image and body weight control in overweight \u0026ge;55-year-old adults: a systematic review. Int J Environ Res Public Health. 2019;16(9):1622. \u003c/li\u003e\n\u003cli\u003eSeo J, Ma H, Kim S, Kim J, Shin M, Yang Y. Effects of the difference between actual body condition and body image perception on nutrient intake, weight control and mental health in Korean adults: Based on the 5th Korea National Health and Nutrition Examination Survey. J Nutr Heal. 2016;49(3):153\u0026ndash;64. \u003c/li\u003e\n\u003cli\u003eJoh H, Oh J, Lee H, Kawachi I. Gender and socioeconomic status in relation to weight perception and weight control behavior in Korean adults. Obes Facts. 2013;6(1):17\u0026ndash;27.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"adult, men, overweight, obesity, weight control, CHS, decision tree","lastPublishedDoi":"10.21203/rs.3.rs-4149509/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4149509/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eObesity is an abnormal and potentially dangerous condition caused by excess body fat accumulation. The number of people with obesity is increasing worldwide. Obesity is the primary cause of various diseases; therefore, it is crucial to make efforts to control and maintain a healthy body weight. Identifying the factors that influence men with obesity to attempt to control and not control their weight is essential. The objective of this study was to create a prediction model for weight control experience among Korean men in their 30s and 40s.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analyzed data from the 2022 Community Health Survey and included 12,311 men who were overweight or obese. The men were divided into two groups based on their weight control experience: 1) Yes group (n\u0026thinsp;=\u0026thinsp;9,405) and 2) No group (n\u0026thinsp;=\u0026thinsp;2,906). Chi-square and independent t-tests were used to compare general and health-related characteristics between the groups. Decision tree analysis was used to build a prediction model for weight control experience. A split-sample test was conducted to validate the model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSeveral predictive models were generated based on the total number of participants, age, and body mass index as the first separating factors. The major factors affecting weight control among men with obesity in their 30s and 40s in Korea include subjective body shape, age, body mass index, education level, completion of hypertension management education, awareness of blood glucose levels, and smoking status. Subjective body shape was confirmed to significantly affect weight control experience.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIt is necessary to support individuals in maintaining and managing an ideal weight by promoting a desirable perception of their body shape. In addition, there is an urgent need to provide obesity prevention and management education to those who have no weight control experience, particularly those at high risk, as identified in this study.\u003c/p\u003e","manuscriptTitle":"Prediction model for weight control experience in Korean men with obesity in their 30s and 40s","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-05 13:30:06","doi":"10.21203/rs.3.rs-4149509/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-14T03:18:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-25T12:34:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-17T19:16:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-15T12:46:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-13T12:47:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-08T15:21:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"abf2b265-88c5-47cc-901c-55fd80e50dc1","date":"2024-05-08T12:50:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"453307e9-4a67-44d4-b71e-fcf7f0a6377e","date":"2024-05-08T09:57:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0a3679ea-e02f-4d87-ba65-9cffe55689b7","date":"2024-05-06T20:05:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"35ec6831-a6e9-4ad8-9000-f865fce9dac6","date":"2024-05-06T14:42:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8d36ed4a-2bfa-4bdd-95df-3b236a786b5e","date":"2024-05-06T09:50:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0d2f1992-8c59-4412-8082-12da1d2f7115","date":"2024-05-06T07:49:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-06T07:34:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-03T12:28:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-02T12:19:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-02T05:17:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-03-22T11:49:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"acdae7e4-7ddc-4b0a-afba-9d1d48e91c29","owner":[],"postedDate":"April 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":30192648,"name":"Health sciences/Health care"},{"id":30192649,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-09-02T15:59:49+00:00","versionOfRecord":{"articleIdentity":"rs-4149509","link":"https://doi.org/10.1038/s41598-024-70833-5","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-29 15:57:08","publishedOnDateReadable":"August 29th, 2024"},"versionCreatedAt":"2024-04-05 13:30:06","video":"","vorDoi":"10.1038/s41598-024-70833-5","vorDoiUrl":"https://doi.org/10.1038/s41598-024-70833-5","workflowStages":[]},"version":"v1","identity":"rs-4149509","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4149509","identity":"rs-4149509","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}