Health-related behaviors of adult male cancer survivors in Korea: A propensity score matching analysis of data from the Korean National Health and Nutrition Examination Survey VII-VIII (2016– 2021)

Health-related behaviors of adult male cancer survivors in Korea: A propensity score matching analysis of data from the Korean National Health and Nutrition Examination Survey VII-VIII (2016– 2021) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Health-related behaviors of adult male cancer survivors in Korea: A propensity score matching analysis of data from the Korean National Health and Nutrition Examination Survey VII-VIII (2016– 2021) Hyein Jung, Yoonjoo Choi, Byungmi Kim This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3960425/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Feb, 2025 Read the published version in Supportive Care in Cancer → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose Studies that have compared the overall health behaviors of male survivors of cancer and the population without cancer in South Korea are limited. Therefore, we aimed to compare the quality of life and health-related behaviors of cancer survivors and the population without cancer in South Korea. Methods This cross-sectional, matched case-control study recruited Korean males aged 19–80 years from the Korea National Health and Nutrition Examination Survey (KNHANES) VIII. Of the 11,760 participants, 349 cancer survivors and 1,047 controls without cancer were matched by 1:3 propensity score matching using age, cohabitation, household income, education level, employment status, type of job, and private insurance. Height, weight, smoking status, drinking status, and physical activity status were also recorded. Results The cancer survivors had lower odds of being overweight and higher odds of being former smokers and drinkers than the controls after adjusting for potential confounders. The cancer survivors and controls showed no significant differences in physical activity or food consumption. No significant differences were noted among the young adults. However, the middle-aged and older male cancer survivors were more likely to be overweight and obese, respectively. The middle-aged survivors were also more likely to be former smokers, while the older survivors were more likely to be former drinkers. Conclusion The cancer survivors were more likely to have a normal weight, be past smokers, or be former drinkers. Education on cancer prevention is required to improve health-related behaviors and prevent secondary cancer. cancer survival propensity score matching KNHANES South Korean Figures Figure 1 Figure 2 Figure 3 Introduction Cancer Statistics in Korea reported 254,718 new cancer cases in 2019, and the 5-year relative survival rate for all patients diagnosed with cancer in the last five years was 70.7% [ 1 ]. There were approximately more than 2 million cancer survivors in South Korea in 2020. They accounted for 4.4% of the entire South Korean population. Further, almost 50% of the cancer survivors were 50 years or older in 2019 [ 1 , 2 ]. While the incidence of cancer in Korea was projected to decrease gradually within the last two decades, it was anticipated that 37.9% of individuals would be diagnosed with any type of cancer when surviving up to life expectancy in the Korean population [ 1 , 3 ]. Moreover, there has been a consistent and substantial increase in the relative survival rates of individuals diagnosed with cancer [ 1 ]. Cancer survivors are defined differently across countries and situations. The most widely used definition delineates it as an ongoing journey commencing at the point of diagnosis and persisting throughout the lifespan [ 4 ]. Long-term cancer survivors have an increased risk of secondary cancers and comorbidities such as cardiovascular disease and type 2 diabetes mellitus [ 5 , 6 ]. The development of cancer and cancer-related death is associated with obesity and unhealthy behaviors such as smoking, alcohol drinking, unhealthy diet, and lack of physical activity [ 7 ]. Therefore, it is important to establish a comprehensive cancer control strategy for cancer survivors to encourage healthy lifestyle behaviors and improve their quality of life. The 10 Action Codes of Cancer Prevention in Korea recommend not smoking and avoiding smoke-filled environments; consuming enough fruits and vegetables; maintaining a healthy balanced diet; limiting salt, burnt or charred food, and alcohol consumption; maintaining body weight within a healthy range; and engaging in at least 30 min of regular and moderate physical activity to promote the overall prevention of cancer in the general population [ 8 ]. However, adherence to these guidelines is poorer in men than in women. In previous reports, only 0.5% of men had healthy lifestyles [ 9 ]. Compared with women with lower smoking and drinking rates, men generally engage more in unhealthy behaviors, and education and intervention are needed more often for men than for women. A previous study also showed that almost half of Korean male smokers continued to smoke and more than 60% continued alcohol drinking even after a cancer diagnosis [ 10 , 11 ]. Adherence to exercise guidelines is also low among cancer survivors, especially in older age groups [ 12 ]. Changing modifiable risk factors may help reduce cancer treatment complications, recurrence, and the risks of other common diseases. The number of patients who survive for more than five years after a cancer diagnosis is increasing, emphasizing the need for research on cancer survivors with a focus on improving their health behavior and quality of life. A better understanding of the differences between the behaviors of men and women cancer survivors in different age groups is also necessary to improve survival. However, few studies have compared the overall health behaviors of male cancer survivors and the population without cancer in South Korea, and studies analyzing recent data are scarce. Therefore, we aimed to evaluate the differences in the modifiable health-related variables between survivors of cancer and the general population included in the KNHANES 2016–2021 using propensity score matching (PSM) analysis. Materials and methods Database source and study population This comparative study included participants from the Korea National Health and Nutrition Examination Survey (KNHANES) VII-VIII (2016–2021). The KNHANES, initiated in 1998, is a population-based cross-sectional cohort study conducted annually by the Korea Centers for Disease Control and Prevention (KCDC) to monitor health risk trends, chronic disease prevalence, and nutritional status. The KNHANES protocol was described in a previous study [ 13 ], and all KNHANES databases were accessed from the website ( https://knhanes.kdca.go.kr/knhanes/ ). A total of 46,828 participants were screened in KNHANES 2016–2021. Among them, those who were aged less than 19 years (n = 8,748), were women (n = 21,179), were missing in the cancer survey (n = 1,788), were missing values for smoking status, alcohol drinking, physical activity, height, weight, and dietary intake (n = 2,902), were missing values for number of cohabitants, household income, education level, employment status, type of job, and private insurance (n = 178), and had cancer during the observation period (n = 273) were excluded. Finally, we identified 11,760 males who met our inclusion criteria; after 1:3 propensity score matching, 1,396 participants (349 cancer survivors and 1,047 individuals without cancer) remained (Fig. 1 ). All participants provided written informed consent, and the study protocol was approved by the Institutional Review Board of the National Cancer Center, Republic of Korea (IRB no. NCC2023-0253). Cancer survivors Data on the cancer diagnosis, type, and treatment status were collected by a trained interviewer using a structured questionnaire. Participants who had been diagnosed with any type of cancer and completed cancer treatment at the time of the survey were categorized as cancer survivors. They answered “yes,” “no,” and “no” to the following questions, respectively: “Have you been diagnosed with any types of cancer by a doctor?”; “Are you currently suffering from cancer?”; and “Are you currently on cancer treatment?” The cancer types included gastric, liver, colorectal, breast, cervical, lung, and thyroid. Outcome variables Health-related modifiable variables, including BMI, smoking, alcohol, food and nutrient intake, and physical activity, have been identified as major lifestyle factors associated with cancer risk by organizations such as the International Agency for Research on Cancer (IARC), American Institute for Cancer Research (AICR), and National Cancer Center in Korea [ 8 , 14 , 15 ]. BMI (kg/m 2 ) was calculated by dividing the weight by the square of height; the measurements were performed using a digital weighing scale and a stadiometer. Data on smoking status, alcohol consumption, and physical activity were obtained using structured self-reported questionnaires. Dietary intake was measured using the 24-hour dietary recall method completed by the participants. The BMIs were categorized into underweight (BMI < 18.5 kg/m 2 ), normal (18.5 kg/m² ≤ BMI < 23 kg/m²), overweight (23 kg/m² ≤ BMI < 25 kg/m²), and obese (25 kg/m² ≤ BMI). The smoking statuses were as follows: never smoked, past smoker, and current smoker. E-cigarette users were categorized as current smokers who used e-cigarettes daily or occasionally. Based on alcohol consumption, the participants were categorized into non-drinkers, past drinkers, and current drinkers. The high-risk drinkers were males who reported consuming averages of ≥ 7 drinks at a sitting, with a frequency of at least 2 times/week. Physically active participants were categorized as those who performed moderate-intensity physical activity for at least 150 min per week, high-intensity physical activity for at least 75 min per week, or a combination of moderate and high-intensity activities; 1 min of high-intensity activity was equivalent to 2 min of moderate-intensity activity. The consumption of food groups and nutrients was estimated using the Korean Food Composition Table prepared by the Rural Development Administration National Institute of Agricultural Science [ 16 ]. The food groups comprised grain, legumes/beans, vegetables, mushrooms, fruits, seaweed, meat, eggs, fish and shellfish, and milk/dairy products. The nutrient intake included total energy, carbohydrates, protein, fat, sugars, and sodium. Covariates To control for potential confounders, we investigated the variables of interest, including demographic characteristics and employment-related variables. The sociodemographic and lifestyle questionnaire items used for PSM included age (19–29, 30–39, 40–49, 50–59, 60–69, and above 70), number of cohabitants (0, 1, 2, 3, and 3 or more), household income level (quartiles), education level (under elementary school, middle school, high school, above college), employment status (employed or unemployed), type of occupations (managers/professionals/related, office jobs, service or sales, skilled agricultural/forestry/fishery, equipment/machine operating/assembling, elementary workers, and unemployed), and private insurance (have or none). Statistical analyses The participants were divided into two groups: cancer survivors and those without cancer. The chi-squared test and t-test were applied to the categorical and continuous variables to compare the cancer survivors and participants without cancer. Logistic regression was used to determine the odds ratios (ORs) and 95% confidence intervals (CIs) to evaluate the associations between BMI, smoking, alcohol consumption, physical activity, and diet and cancer survival. Unadjusted logistic regression was used to determine crude ORs, while multivariable logistic regression was used to determine the adjusted ORs for age, number of cohabitants, household income, education level, employment status, job type, and private insurance. PSM was used to match pairs of cancer survivors and participants without cancer. The propensity scores were calculated using a multivariate logistic regression model. The confounding variables used for matching included age, number of cohabitants, household income, educational level, employment status, job type, and private insurance. The cancer survivors were matched with the participants without cancer using 1:3 ratio matching, and the standard mean differences (SMD) were lower than 0.1 after matching. Statistical analysis was performed using SAS statistical software (version 9.4; SAS Institute Inc., Cary, NC, USA), and P < 0.05 denoted statistical significance. Results General characteristics of the participants Table 1 shows the general characteristics of the cancer survivors and participants without cancer before and after PSM. Of the 11,760 participants, 349 answered that they had been diagnosed with cancer and their treatment had ended; they were currently not undergoing cancer treatment. The average age of the participants was 51.7 ± 17.1 years before matching and 67.9 ± 10.7 years after matching. Before PSM, the variables used to match the cancer survivors and participants without cancer showed differences (all P < 0.0001). The cancer survivors were more likely to be older, lived with one cohabitant, had a lower income or education level, were unemployed, and did not have private insurance than the participants. However, there were no significant differences between them after PSM. Among the 349 male cancer survivors, 30.7%, 22.6%, 8.9%, 5.4%, 2.0%, and 35.0% had stomach, colorectal, thyroid, lung, liver, and other cancers, respectively. Table 1 Characteristics of the cancer survivors and the participants without cancer before and after PSM Before PSM (n = 11,760) After 1:3 PSM (n = 1,396) Participants without cancer (n = 11,411) Cancer survivors (n = 349) P- value Participants without cancer (n = 1,047) Cancer survivors (n = 349) P- value Age 19–29 1,524 (19.1) 2 (0.8) < .0001 6 (1.1) 2 (0.8) 0.9222 30–39 1,733 (18.9) 5 (3.4) 15 (2.6) 5 (3.4) 40–49 2,041 (20.9) 17 (8.3) 51 (7.3) 17 (8.3) 50–59 2,053 (20.1) 38 (15.5) 114 (18.5) 38 (15.5) 60–69 2,077 (10.9) 96 (25.0) 288 (24.6) 96 (25.0) > 70 1,983 (10.0) 191 (47.0) 573 (45.9) 191 (47.0) Number of cohabitants Living alone 1,413 (11.3) 44 (8.3) < .0001 151 (11.8) 44 (8.3) 0.2656 1 3,675 (25.3) 197 (50.3) 565 (46.7) 197 (50.3) 2 2,857 (28.0) 57 (20.7) 193 (23.5) 57 (20.7) 3 or more 3,466 (35.5) 51 (20.6) 138 (18.1) 51 (20.6) Household income Lowest 1,898 (12.4) 115 (26.5) < .0001 327 (26.6) 115 (26.5) 0.2994 Lower middle 2,721 (22.3) 86 (20.9) 294 (26.5) 86 (20.9) Upper middle 3,198 (29.9) 73 (23.8) 211 (21.4) 73 (23.8) Highest 3,594 (35.4) 75 (28.8) 215 (25.5) 75 (28.8) Education level Under elementary school 1,540 (8.3) 97 (21.2) < .0001 291 (23.4) 97 (21.2) 0.8720 Middle school 1,111 (7.2) 52 (13.5) 156 (13.9) 52 (13.5) High school 4,006 (37.7) 91 (25.8) 273 (25.3) 91 (25.8) Above college 4,754 (46.8) 109 (39.5) 327 (37.4) 109 (39.5) Employment status Employed 8,209 (75.1) 159 (53.1) < .0001 477 (51.4) 159 (53.1) 0.6177 Type of job Managers, professionals, and related 1,863 (18.6) 28 (11.6) < .0001 83 (10.6) 28 (11.6) 0.0651 Office jobs 1,377 (13.9) 26 (11.9) 45 (6.2) 26 (11.9) Service or sales 1,146 (11.9) 14 (4.8) 44 (6.1) 14 (4.8) Skilled agricultural, forestry, and fishery 668 (3.4) 31 (7.0) 102 (6.3) 31 (7.0) Equipment, machine operating, and assembling 2,205 (19.9) 29 (9.0) 117 (13.8) 29 (9.0) Elementary workers 950 (7.3) 31 (8.9) 86 (8.3) 31 (8.9) Unemployed 3,202 (24.9) 190 (46.9) 570 (48.6) 190 (46.9) Private insurance Yes 8,898 (82.9) 183 (61.8) < .0001 568 (60.8) 183 (61.8) 0.7717 No 2,513 (17.1) 166 (38.2) 479 (39.2) 166 (38.2) Cancer site Stomach cancer 107 (30.7) 107 (30.7) Liver cancer 7 (2.0) 7 (2.0) Colorectal cancer 79 (22.6) 79 (22.6) Lung cancer 19 (5.4) 19 (5.4) Thyroid cancer 31 (8.9) 31 (8.9) Other cancer 122 (35.0) 122 (35.0) n (weighted %); PSM: propensity score matching. Covariate balance before and after PSM The 1:3 PSM generated data from 349 cancer survivors and 1,047 controls. Figure 2 presents the SMDs of the balancing covariates before and after PSM using a love plot to show the matching effect. Before the PSM, most SMDs were observed to deviate from zero. After PSM, the love plot showed that all SMDs were less than the absolute value of 0.1. That is, the standardized difference between the cancer survivors and participants without cancer decreased significantly after matching, and the SMD values were all less than 0.1, confirming that the two groups were balanced. Comparison of health-related variables of the cancer survivors and controls The differences between the health-related variables of the cancer survivors and the participants without cancer are shown in Table 2 . The chi-squared test showed significant differences between the BMIs, smoking statuses, and alcohol consumption of the two groups after PSM (all P < 0.05). The results of the t-test for food and nutrient intake showed that only carbohydrate intake differed for the two groups. The cancer survivors were more likely to have a normal weight, previous history of smoking, previous history of drinking, and higher intake of carbohydrates than participants without cancer. However, we found no significant differences in e-cigarette use, physical activity, food intake, or intake of other nutrients. Table 2 BMI, smoking, alcohol drinking, physical activity, and daily food and nutrient intake of the participants without cancer and cancer survivors Before PSM (n = 11,760) After 1:3 PSM (n = 1,396) Participants without cancer (n = 11,411) Cancer survivor (n = 349) P- value Participants without cancer (n = 1,047) Cancer survivor (n = 349) P- value BMI Underweight 289 (2.6) 14 (4.1) < .0001 32 (2.7) 14 (4.1) < .0001 Normal 3,310 (28.3) 148 (42.9) 315 (28.4) 148 (42.9) Overweight 3,004 (25.9) 82 (20.9) 330 (31.5) 82 (20.9) Obese 4,808 (43.2) 105 (32.1) 370 (37.4) 105 (32.1) Smoking status Never smoked 2,856 (27.4) 58 (15.1) < .0001 220 (21.6) 58 (15.1) 0.0016 Former smoker 4,849 (38.5) 233 (66.9) 576 (54.2) 233 (66.9) Current smoker 3,706 (34.1) 58 (18.0) 251 (24.2) 58 (18.0) Using E-Cigarettes Never and past smoked 7,705 (65.9) 291 (82.0) < .0001 796 (75.8) 291 (82.0) 0.2176 No 3,399 (30.7) 57 (17.3) 245 (23.4) 57 (17.3) Yes 307 (3.4) 1 (0.7) 6 (0.8) 1 (0.7) Alcohol drinking Non-drinker 505 (3.6) 22 (4.4) < .0001 85 (7.6) 22 (4.4) 0.0075 Past drinker 1,569 (11.9) 94 (26.6) 218 (19.3) 94 (26.6) Current drinker 9,337 (84.4) 233 (69.0) 744 (73.1) 233 (69.0) High-risk drinking Non-drinker 505 (3.6) 22 (4.4) 0.1221 85 (7.6) 22 (4.4) 0.1454 No 8,764 (76.8) 282 (80.7) 835 (79.5) 282 (80.7) Yes 2,142 (19.5) 45 (14.9) 127 (12.8) 45 (14.9) Physical activity Active 6145 (50.3) 207 (54.9) 0.1588 627 (56.5) 207 (54.9) 0.6481 Inactive 5266 (49.7) 142 (45.1) 420 (43.5) 142 (45.1) Food intake (g/day) Grain 319.4 ± 2.0 313.8 ± 8.7 0.6089 298.6 ± 5.4 313.8 ± 8.7 0.0850 Legumes/beans 40.2 ± 1.0 62.9 ± 9.8 < .0001 53.9 ± 3.5 62.9 ± 9.8 0.1885 Vegetables 337.3 ± 2.4 374.3 ± 13 0.0116 360 ± 8.4 374.3 ± 13 0.2933 Mushroom 6.8 ± 0.3 7.0 ± 1.4 0.8786 5.3 ± 1 7.0 ± 1.4 0.2103 Fruit 135.1 ± 2.6 194.7 ± 13.8 0.0001 186.2 ± 8.6 194.7 ± 13.8 0.5564 Seaweed 28.8 ± 1.0 41.5 ± 5.9 0.0379 34.3 ± 3.9 41.5 ± 5.9 0.2878 Meat 164.1 ± 2.5 97.6 ± 8.8 < .0001 108.5 ± 6.3 97.6 ± 8.8 0.2370 Eggs 34.5 ± 0.6 27.6 ± 3.2 0.0407 28.1 ± 1.6 27.6 ± 3.2 0.8644 Fish and shellfish 116.8 ± 1.9 143.8 ± 10.8 0.0175 121.7 ± 6.6 143.8 ± 10.8 0.0505 Milk and dairy product 81.9 ± 1.8 57.5 ± 6.2 0.0150 63.8 ± 4.6 57.5 ± 6.2 0.3852 Nutrient intake Total energy (kcal/day) 2321.7 ± 12.1 2121.7 ± 49.8 0.0019 2068.4 ± 32.3 2121.7 ± 49.8 0.2890 Carbohydrate (g/day) 320.7 ± 1.5 325.7 ± 7.2 0.5393 311 ± 4.1 325.7 ± 7.2 0.0322 Protein (g/day) 86.4 ± 0.5 75.5 ± 2.3 0.0003 74.1 ± 1.4 75.5 ± 2.3 0.5294 Fat (g/day) 57.0 ± 0.5 42.5 ± 2.1 < .0001 42.6 ± 1.4 42.5 ± 2.1 0.9480 Carbohydrate (% of energy) 57.9 ± 0.2 63.5 ± 0.8 < .0001 62.8 ± 0.6 63.5 ± 0.8 0.3896 Protein (% of energy) 14.9 ± 0.1 14.1 ± 0.2 0.0101 14.2 ± 0.1 14.1 ± 0.2 0.7114 Fat (% of energy) 21.1 ± 0.1 17.2 ± 0.5 < .0001 17.5 ± 0.3 17.2 ± 0.5 0.5431 Sugars (g/day) 10.1 ± 0.2 8.9 ± 1.2 0.3824 7.8 ± 0.6 8.9 ± 1.2 0.2633 Sodium (mg/day) 4041.9 ± 25.9 3876.7 ± 135.1 0.2542 3718.6 ± 72.1 3876.7 ± 135.1 0.2095 PSM: propensity score matching; BMI: body mass index. Multivariate logistic regression analysis showed differences in the proportions of participants who were overweight and had a previous history of smoking and drinking among the cancer survivors and the participants without cancer (Table 3 ). More survivors of cancer than participants without cancer were overweight (OR, 0.421; 95% CI, 0.289–0.614; P = 0.0006) after PSM and adjustment for potential covariates. Compared with that of the never-smoked group, the OR for the cancer survivors who were former smokers was 1.783 (95% CI: 1.226–2.592, P = 0.0005). The cancer survivors had a significantly higher OR for being former drinkers (OR: 2.362; 95% CI: 1.275–4.373, P = 0.0020) than for being non-drinkers. The ORs and 95% CI for those with obesity and high-risk drinkers were 0.553 (0.383–0.796) and 2.154 (1.038–4.471), respectively. However, the differences were not statistically significant. Table 3 ORs of health-related variables for cancer survivors before and after PSM Before PSM (n = 11,760) After PSM (n = 1,396) Crude OR P- value Adjusted OR P- value Crude OR P- value Adjusted OR P- value BMI Underweight 1.039 (0.561–1.925) 0.1166 1.094 (0.585–2.045) 0.1571 0.995 (0.474–2.090) 0.2136 1.072 (0.516–2.224) 0.1304 Normal ref (1.000) ref (1.000) ref (1.000) ref (1.000) Overweight 0.533 (0.388–0.733) 0.0187 0.553 (0.398–0.767) 0.0077 0.438 (0.302–0.637) 0.0015 0.421 (0.289–0.614) 0.0006 Obese 0.490 (0.365–0.659) 0.0016 0.624 (0.452–0.862) 0.0747 0.569 (0.400–0.809) 0.1271 0.553 (0.383–0.796) 0.0953 Smoking status Never smoked ref (1.000) ref (1.000) ref (1.000) ref (1.000) Past smoker 3.145 (2.281–4.336) < .0001 1.798 (1.294–2.498) < .0001 1.761 (1.215–2.552) 0.0004 1.783 (1.226–2.592) 0.0005 Current smoker 0.956 (0.624–1.466) 0.0006 1.126 (0.724–1.753) 0.3514 1.062 (0.664–1.697) 0.2574 1.122 (0.694–1.813) 0.3852 Alcohol drinking Non-drinker ref (1.000) ref (1.000) ref (1.000) ref (1.000) Former drinker 1.829 (1.052–3.179) < .0001 2.143 (1.217–3.772) 0.0026 2.374 (1.293–4.361) 0.0022 2.362 (1.275–4.373) 0.0020 Current drinker 0.670 (0.402–1.118) < .0001 1.476 (0.868–2.510) 0.9618 1.624 (0.923–2.859) 0.7655 1.581 (0.874–2.860) 0.8809 High-risk drinking Non-drinker ref (1.000) ref (1.000) ref (1.000) ref (1.000) Moderate drinker 0.862 (0.518–1.434) 0.6012 1.642 (0.973–2.772) 0.1981 1.746 (1.001–3.047) 0.2420 1.751 (0.983–3.121) 0.3387 High drinker 0.625 (0.343–1.141) 0.0680 1.760 (0.925–3.351) 0.1747 1.996 (0.999–3.991) 0.1080 2.154 (1.038–4.471) 0.0716 Physical activity Active ref (1.000) ref (1.000) ref (1.000) ref (1.000) Inactive 0.833 (0.645–1.075) 0.1598 1.211 (0.932–1.575) 0.1523 1.068 (0.805–1.416) 0.6482 1.061 (0.792–1.423) 0.6893 Reference group for logistic analysis: non-cancer controls; PSM: propensity score matching; BMI: body mass index. Odds ratio (OR) adjusted for age, number of cohabitants, household income, education level, employment status, job type, and private insurance. Comparison of the health-related variables stratified by age The results of the age-stratified analysis after PSM are shown in Fig. 3 . The participants were divided into young (19–49 years), middle-aged (50–64 years), and older (65 years or older) groups. The middle-aged and older cancer survivors were less likely to be overweight (OR: 0.357, 95% CI: 0.167–0.764 for middle-aged and OR: 0.455, 95% CI: 0.287–0.721 for older adults) and obese (OR: 0.444, 95% CI: 0.219–0.901 for middle-aged and OR: 0.635, 95% CI = 0.408–0.987 for older adults) than the participants without cancer after multivariable adjustments. However, only the difference in the likelihood of being overweight was significant ( P < 0.05). The middle-aged cancer survivors had higher ORs for being former smokers (OR: 3.538, 95% CI: 1.303–9.607), while the older survivors had higher ORs for being former drinkers (OR: 2.508, 95% CI: 1.219–5.162). However, there were no significant differences among the young adults. Discussion This study compared the health-related factors, including BMI, smoking and alcohol consumption, food intake, and nutrient intake, for the cancer survivors and participants without cancer using PSM. Using data from the KNHANES, we found that the cancer survivors had normal weights, were more likely to be former smokers and drinkers, and had high carbohydrate consumption. The age-stratified analysis showed no differences between the young survivors and the participants without cancer. However, the middle-aged and older survivors had normal weight. The middle-aged survivors were also more likely to be former smokers while the older survivors were more likely to be former drinkers. A previous analysis of the KNHANES IV–V (2007–2012) showed higher rates of former smokers and drinkers [ 17 ], which was consistent with our results that cancer survivors were more likely to adopt healthy behaviors. A previous study reported that the odds ratios of current drinking and smoking were lower for the cancer survivors than for the participants without a history of cancer; however, sex was not analyzed [ 17 ]. In our study, the ORs for current drinking and smoking were not different among the cancer survivors. The proportion of cancer survivors who were currently smoking in this study was 18%. While this was lower than the proportion of currently smoking participants who had not had cancer, caution should be exercised because there was evidence that smoking may increase the risk of second primary cancers in survivors of cancers [ 18 ]. Our study also showed that the proportion of former smokers was higher among the cancer survivors than among the participants who had not had cancer. However, there were no differences in e-cigarette use after PSM [ 19 ]. This is attributed to the lack of awareness of the harm caused by e-cigarettes. Therefore, effort should be made to create awareness about the adverse effects of e-cigarettes, although they have a lower addiction rate than regular cigarettes [ 20 ]. Alcohol consumption is a significant health issue associated with several types of cancer, including oral, liver, and colorectal [ 21 ]. Alcohol consumption among survivors of cancer is also highly associated with the risk of recurrence, secondary cancers, and increased mortality [ 22 , 23 ]. In this study, 69% of cancer survivors still consumed alcohol, and this rate was higher than that reported in previous studies [ 24 ]. This may be related to the high rate of rejecting rules and the difficulty in following selected recommendations for avoiding alcohol consumption to prevent cancer in the Korean National Cancer Prevention Awareness and Practice Survey in 2021 [ 25 ]. Further studies are needed to identify the reasons for the increasing number of current drinkers among cancer survivors. In a previous study involving the 2007–2013 KNHANES, the proportion of high-risk drinkers was 16.3% [ 11 ]. The proportion of high-risk drinkers among cancer survivors who had consumed alcohol previously was slightly lower, at 14.9%, in this study. However, as this was still higher than the high-risk drinking rate of 12.8% for the participants who had not had cancer after matching, education is necessary for the risks associated with alcohol consumption, as well as high-risk drinking. Of the male cancer survivors, 54.0% engaged in physical activity, while 45.0% were inactive. The levels of physical activity among the participants who had not had cancer did not also differ, which is consistent with the reports of previous studies [ 24 , 26 ]. Physical activity during and after cancer treatment can reduce fatigue, prevent cancer recurrence, improve survival, and positively impact quality of life [ 27 , 28 ]. Moreover, sedentary behavior is associated with a higher risk of cancer-related mortality [ 29 ]. Considering the positive impact of physical activity on the quality of life and the associated reduction of the risk of comorbidities, the government should encourage physical activity. This study also showed that male cancer survivors have lower odds of being overweight or obese. Being overweight or obese is associated with better survival for some types of cancer [ 30 ]; in a meta-analysis of obesity and cancer survival, adiposity was not associated with the risks of 10 cancer types, including breast, colorectal, and gastroesophageal cancers [ 31 ]. However, the results of a cohort study that followed 1,614,583 person-years in South Korea showed that male cancer survivors with obesity exhibited an increased incidence of secondary cancers, which was slightly higher than that of the first primary cancer risk in the overall cohort [ 32 ]. Another meta-analysis showed that obesity after colorectal cancer diagnosis was associated with a high risk of all-cause mortality [ 33 ]. Given the complications associated with survival after cancer and other obesity-relate8d comorbidities, it is important to maintain a healthy body weight throughout life. There were no significant differences in the food and nutrient intake between the cancer survivors and participants without cancer, except for daily carbohydrate consumption. The differences in carbohydrate intake in our study may be related to the higher intake of grains, fruits, and vegetables in cancer survivors than in the non-cancer population. However, the percentage of energy intake from carbohydrates did not differ. According to the 2020 Dietary Reference Intake for Koreans, the proportions of energy from carbohydrates, protein, and fat were 55–65%, 7–20%, and 15–30%, respectively [ 34 ], and this study showed appropriate ratios of carbohydrate, protein, and fat for both two groups. Nevertheless, caution should be exercised with sugar and salt intake and healthy eating patterns should be adopted. Evidence from several studies in a meta-analysis showed that healthier diet habits, such as high consumption of fruits, vegetables, whole grains, fiber, and higher diet quality, were associated with better prognoses for survivors of some types of cancer [ 35 , 36 ] and prevention of cancer in the general population [ 37 – 39 ]. In addition, the intake of refined carbohydrates was associated with a higher risk of some types of cancer, whereas fiber and whole grains were associated with a lower risk of cancer [ 40 , 41 ]. However, the consumption of red, processed, and sugary beverages is associated with greater risks of cancer and mortality [ 42 – 44 ]. Therefore, it is important to promote healthier dietary habits, policies, and programs and consider them in conjunction with other lifestyle behaviors. South Korea has a higher chance of long-term survival after cancer diagnosis now than in the past [ 1 ]. To improve treatment efficacy, individual behavior, physical activity, and dietary consumption are important. Survivors of cancer should attempt lifestyle changes to enhance their health, quality of life, and survival [ 14 ]. It is also necessary to provide appropriate interventions for cancer survivors through healthcare programs. The strengths of this study are as follows: First, it used a population-based probabilistic sample from 192 cities in South Korea, which could improve the representativeness of the Korean population. Second, we adjusted for potential confounders in the statistical model to control for confounding effects. Third, we used the 1:3 PSM method to reduce confounding variables in the cross-sectional analysis. The presence of household members, especially single-person households, household income levels, employment status, and types of occupations that can affect health behavior were included in the PSM analysis to reduce the differences and selective biases of the case and control groups. The balance of covariates for the cancer survivors and individuals without cancer provided better insights into the differences in health-related behaviors between the two groups. However, this study has few limitations. There was no information on the cancer stage and that on the number of years elapsed since the end of treatment was not provided. Additionally, self-reported cancers may lead to the underestimation of the prevalence of actual cancers. The cross-sectional study design restricted the establishment of temporal differences between the two groups. Finally, our sample was small. However, we used PSM to minimize distortion and generalization of the data, and additional research is needed to verify our findings. Conclusions The findings of this study indicate that the cancer survivors were more likely to have normal weight, be former smokers, and be former drinkers than participants without cancer. However, there were no significant differences in other behaviors. Therefore, we suggest that survivors of cancer change their health-related behaviors to prevent cancer recurrence and improve their quality of life. Further studies are needed to link the cohort data with cancer diagnosis records and stages to evaluate changes in health-related behaviors and factors that may affect the behaviors of long-term cancer survivors. Declarations Author contribution Conceptualization, B.K; methodology, B.K; validation, B.K; formal analysis, H.J; writing-original draft preparation, H.J and Y.C; writing-review and editing, H.J, Y.C, and B.K. supervision, B.K, project administration, B.K. All authors have read and agreed to the published version of the manuscript. Funding This research was supported by the National Cancer Center Research Grant 2311440-2. Conflicts of Interest/Competing Interests The authors declare no competing interests. Ethics Approval The survey protocol and secondary use of the data were approved by the Institutional Review Board of the National Cancer Center, Republic of Korea (IRB no. NCC2023-0253) Data Availability Statement The survey data from KNHANES VII-VIII can be accessed and downloaded from the KNHANES homepage ( https://knhanes.kdca.go.kr/knhanes/main.do, accessed on January 5, 2024). Consent to Participate All participants provided informed written consent before participating in the study. Consent for Publication Not applicable References Kang MJ et al. (2022) Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2019. Cancer Res Treat 54(2):330–344. https://doi.org/10.4143/crt.2022.128 Yang YS et al. (2022) Prediction of cancer survivors’ mortality risk in Korea: a 25-year nationwide prospective cohort study. Epidemiol Health 44:e2022075. https://doi.org/10.4178/epih.e2022075 Jung KW et al. (2023) Prediction of cancer incidence and mortality in Korea, 2023. Cancer Res Treat 55(2):400–407. https://doi.org/10.4143/crt.2023.448 Marzorati C, Riva S, Pravettoni G (2017) Who is a cancer survivor? A systematic review of published definitions. J Cancer Educ 32(2):228–237. https://doi.org/10.1007/s13187-016-0997-2 Cao X et al. (2023) Association of frailty with the incidence risk of cardiovascular disease and type 2 diabetes mellitus in long-term cancer survivors: a prospective cohort study. BMC Med 21(1):74. https://doi.org/10.1186/s12916-023-02774-1 Donin N et al. (2016) Risk of second primary malignancies among cancer survivors in the United States, 1992 through 2008. Cancer 122(19):3075–3086. https://doi.org/10.1002/cncr.30164 Kerr J, Anderson C, Lippman SM (2017) Physical activity, sedentary behaviour, diet, and cancer: an update and emerging new evidence. Lancet Oncol 18(8):e457–e471. https://doi.org/10.1016/S1470-2045(17)30411-4 Korea Ministry of Health and Welfare and National Cancer Center Korea (2006). 10 action codes of cancer prevention Accessed 2024 Jan 8. https://www.cancer.go.kr/lay1/S1T200C203/contents.do Oh JK et al. (2023) Adherence to cancer prevention guidelines and cancer incidence and mortality: A population-based cohort study. Cancer Res Treat 55(1):15–27. https://doi.org/10.4143/crt.2021.1031 Koo HY et al. (2020) Prevalence and predictors of sustained smoking after a cancer diagnosis in Korean men. Cancer Res Treat 52(1):139–148. https://doi.org/10.4143/crt.2018.609 Ko H, Song YM, Shin JY (2017) Factors associated with alcohol drinking behavior of cancer survivors: the Korean National Health and Nutrition Examination Survey. Drug Alcohol Depend 171:9–15. https://doi.org/10.1016/j.drugalcdep.2016.11.024 Park JH et al. (2021) Physical activity of Korean cancer survivors is associated with age and sex. Korean J Intern Med 36(Suppl 1):S225–S234. https://doi.org/10.3904/kjim.2019.240 Kweon S et al. (2014) Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol 43(1):69–77. https://doi.org/10.1093/ije/dyt228 Clinton SK, Giovannucci EL, Hursting SD (2020) The World Cancer Research Fund/American Institute for Cancer Research Third expert report on diet, nutrition, physical activity, and cancer: impact and future directions. J Nutr 150(4):663–671. https://doi.org/10.1093/jn/nxz268 World Health Organization preventing cancer . Accessed 2024 Jan 31. https://www.who.int/activities/preventing-cancer Rural Development Administration, National Institute of Agricultural Science. Korean Food Composition Table, 9th revision. http://koreanfood.rda.go.kr/eng/fctFoodSrchEng/engMain Park B et al. (2015) Health behaviors of cancer survivors in nationwide cross-sectional survey in Korea: higher alcohol drinking, lower smoking, and physical inactivity pattern in survivors with higher household income. Med (Baltim) 94(31):e1214. https://doi.org/10.1097/MD.0000000000001214 Phua ZJ, MacInnis RJ, Jayasekara H (2022) Cigarette smoking and risk of second primary cancer: a systematic review and meta-analysis. Cancer Epidemiol 78:102160. https://doi.org/10.1016/j.canep.2022.102160 Paek J, Son S, Choi YJ (2022) E-cigarette and cigarette use among cancer survivors versus general population: a case-control study in Korea. J Cancer Surviv 16(4):741–750. https://doi.org/10.1007/s11764-021-01067-x Rohde JA et al. (2020) E-cigarette health harm awareness and discouragement: implications for health communication. Nicotine Tob Res 22(7):1131–1138. https://doi.org/10.1093/ntr/ntz194 Oh SW (2020) Problem drinking in cancer survivors. Korean J Fam Med 41(4):205–206. https://doi.org/10.4082/kjfm.41.4E Schwedhelm C et al. (2016) Effect of diet on mortality and cancer recurrence among cancer survivors: a systematic review and meta-analysis of cohort studies. Nutr Rev 74(12):737–748. https://doi.org/10.1093/nutrit/nuw045 Shi M et al. (2023) Alcohol consumption among adults with a cancer diagnosis in the all of US research program. JAMA Netw Open 6(8):e2328328. https://doi.org/10.1001/jamanetworkopen.2023.28328 Oh MG et al. (2013) Health behaviors of cancer survivors: the fourth Korea National health and nutrition examination survey (KNHANES IV, 2007–09). Jpn J Clin Oncol 43(10):981–987. https://doi.org/10.1093/jjco/hyt118 Oh JK et al. (2022) Awareness of and practice toward cancer prevention recommendations: results of the Korean National Cancer Prevention Awareness and Practice Survey in 2021. Epidemiol Health 44:e2022068. https://doi.org/10.4178/epih.e2022068 Lee J et al. (2021) Intensity- and domain-specific physical activity levels between cancer survivors and non-cancer diagnosis individuals: a propensity score matching analysis. Support Care Cancer 29(2):661–668. https://doi.org/10.1007/s00520-020-05514-w Brandenbarg D et al. (2018) The effect of physical activity on fatigue among survivors of colorectal cancer: a systematic review and meta-analysis. Support Care Cancer 26(2):393–403. https://doi.org/10.1007/s00520-017-3920-4 Liu Y et al. (2023) Active for life after cancer: association of physical activity with cancer patients’ interpersonal competence, quality of life, and survival beliefs. Behav Sci (Basel) 13(6). https://doi.org/10.3390/bs13060449 Hamblen AJ et al. (2023) Physical activity and dietary considerations for prostate cancer patients: future research directions. Proc Nutr Soc 82(3):298–304. https://doi.org/10.1017/S0029665123000046 Ekelund U et al. (2019) Do the associations of sedentary behaviour with cardiovascular disease mortality and cancer mortality differ by physical activity level? A systematic review and harmonised meta-analysis of data from 850 060 participants. Br J Sports Med 53(14):886–894. https://doi.org/10.1136/bjsports-2017-098963 Lee DH, Giovannucci EL (2019) The obesity paradox in cancer: epidemiologic insights and perspectives. Curr Nutr Rep 8(3):175–181. https://doi.org/10.1007/s13668-019-00280-6 Cheng E et al. (2022) Adiposity and cancer survival: a systematic review and meta-analysis. Cancer Causes Control 33(10):1219–1246. https://doi.org/10.1007/s10552-022-01613-7 Park SM et al. (2016) Prediagnosis body mass index and risk of secondary primary cancer in male cancer survivors: A large cohort study. J Clin Oncol 34(34):4116–4124. https://doi.org/10.1200/JCO.2016.66.4920 Lee J et al. (2015) Association between body mass index and prognosis of colorectal cancer: a meta-analysis of prospective cohort studies. PLOS ONE 10(3):e0120706. https://doi.org/10.1371/journal.pone.0120706 Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention (2021) The Korean Nutrition Society. Application of Dietary Reference Intakes for Koreans 2020. Castro-Espin C, Agudo A (2022) The role of diet in prognosis among cancer survivors: A systematic review and meta-analysis of dietary patterns and diet interventions. Nutrients 14(2). https://doi.org/10.3390/nu14020348 Hurtado-Barroso S et al. (2020) Vegetable and fruit consumption and prognosis among cancer survivors: A systematic review and meta-analysis of cohort studies. Adv Nutr 11(6):1569–1582. https://doi.org/10.1093/advances/nmaa082 Schwingshackl L et al. (2017) Adherence to Mediterranean diet and risk of cancer: an updated systematic review and meta-analysis. Nutrients 9(10). https://doi.org/10.3390/nu9101063 Sakai M et al. (2022) Fruit and vegetable consumption and risk of esophageal cancer in the Asian region: a systematic review and meta-analysis. Esophagus 19(1):27–38. https://doi.org/10.1007/s10388-021-00882-6 Yan H et al. (2022) Fruit and vegetable consumption and the risk of prostate cancer: A systematic review and meta-analysis. Nutr Cancer 74(4):1235–1242. https://doi.org/10.1080/01635581.2021.1952445 Tao J et al. (2021) Role of dietary carbohydrates on risk of lung cancer. Lung Cancer 155:87–93. https://doi.org/10.1016/j.lungcan.2021.03.009 Azeem S et al. (2015) Diet and colorectal cancer risk in Asia–a systematic review. Asian Pac J Cancer Prev 16(13):5389–5396. https://doi.org/10.7314/apjcp.2015.16.13.5389 Choi Y, et al. (2013) Consumption of red and processed meat and esophageal cancer risk: meta-analysis. World J Gastroenterol 19(7):1020–1029. https://doi.org/10.3748/wjg.v19.i7.1020 Li Y et al. (2021) Consumption of sugar-sweetened beverages and fruit juice and human cancer: a systematic review and dose-response meta-analysis of observational studies. J Cancer 12(10):3077–3088. https://doi.org/10.7150/jca.51322 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Feb, 2025 Read the published version in Supportive Care in Cancer → Version 1 posted Editorial decision: Revision requested 14 Jun, 2024 Reviews received at journal 14 Jun, 2024 Reviewers agreed at journal 28 May, 2024 Reviews received at journal 27 May, 2024 Reviewers agreed at journal 11 Apr, 2024 Reviewers invited by journal 19 Mar, 2024 Editor assigned by journal 19 Mar, 2024 Submission checks completed at journal 21 Feb, 2024 First submitted to journal 16 Feb, 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3960425","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":274026358,"identity":"8c5b3b13-e406-4669-b45b-f514c4f08467","order_by":0,"name":"Hyein Jung","email":"","orcid":"","institution":"National Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Hyein","middleName":"","lastName":"Jung","suffix":""},{"id":274026359,"identity":"7849c992-c517-4f50-811b-763f2381ea5c","order_by":1,"name":"Yoonjoo Choi","email":"","orcid":"","institution":"National Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Yoonjoo","middleName":"","lastName":"Choi","suffix":""},{"id":274026360,"identity":"4e75796e-916c-4d69-a64f-d2d6a0e3d7ff","order_by":2,"name":"Byungmi Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACCQkG9o8fKmzkYAIGxGhhY5Y4k2ZMmhYG3pbDiQ1Ea5Gc3Z32QLLhcPp29sMPmCsqGIzNGwhokZY5u92gcEd67s6eNAPGM2cYzGQOENAiJ5G7QULyjHXuhhs8DIyNbQw2EoQcBtbC28acbgDW8o8ILdISuduAWpwTIFoaGMwIapGcc3azMTCQDTecSTM42HBMwpigFonbvRsfAqNS3uD44YcPG2psDGcQ0oICDgCNIEnDKBgFo2AUjAIcAABwqDxZo2sA+gAAAABJRU5ErkJggg==","orcid":"","institution":"National Cancer Center","correspondingAuthor":true,"prefix":"","firstName":"Byungmi","middleName":"","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2024-02-16 05:22:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3960425/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3960425/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00520-025-09200-7","type":"published","date":"2025-02-07T15:57:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":51511836,"identity":"a711a3cb-b011-4a4c-8974-80561796786b","added_by":"auto","created_at":"2024-02-22 21:10:44","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":255942,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart for the selection of the study population\u003c/p\u003e\n\u003cp\u003eKNHANES: Korea National Health and Nutrition Examination Survey\u003c/p\u003e","description":"","filename":"Figure11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3960425/v1/b333a1fcbf4be2fbfcf6f3c5.jpg"},{"id":51511838,"identity":"94ee79ea-ab93-4322-82ab-ae235e78e45e","added_by":"auto","created_at":"2024-02-22 21:10:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":313397,"visible":true,"origin":"","legend":"\u003cp\u003ePropensity score matching effect evaluated using the love plot\u003c/p\u003e\n\u003cp\u003eWhite diamonds indicate the standard mean differences after matching, and black dots indicate those after matching\u003c/p\u003e","description":"","filename":"Figure12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3960425/v1/1f13fa035d10117f9b9547ca.jpg"},{"id":51511837,"identity":"f432576d-1628-44d9-a23b-5420a635d0a2","added_by":"auto","created_at":"2024-02-22 21:10:44","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":311218,"visible":true,"origin":"","legend":"\u003cp\u003eAge-stratified adjusted odds ratios of survivors of cancer and the participants without cancer according to the health-related behaviors after PSM\u003c/p\u003e\n\u003cp\u003ePSM: propensity score matching; BMI: body mass index; N/A: not available; Ref.: reference; Reference of ORs is non-cancer population.; Adjusted ORs were adjusted for age, number of cohabitants, household income, education level, employment status, type of job, and private insurance; * asterisks indicate \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05\u003c/p\u003e","description":"","filename":"Figure13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3960425/v1/3d2f26f4d73c021e1d9c608b.jpg"},{"id":75931207,"identity":"d0732929-f7b5-4eb2-8148-e06920d9d8c3","added_by":"auto","created_at":"2025-02-10 16:14:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2245098,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3960425/v1/b72b91fa-95c4-48b9-97b2-046148924e3c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health-related behaviors of adult male cancer survivors in Korea: A propensity score matching analysis of data from the Korean National Health and Nutrition Examination Survey VII-VIII (2016– 2021)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer Statistics in Korea reported 254,718 new cancer cases in 2019, and the 5-year relative survival rate for all patients diagnosed with cancer in the last five years was 70.7% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. There were approximately more than 2\u0026nbsp;million cancer survivors in South Korea in 2020. They accounted for 4.4% of the entire South Korean population. Further, almost 50% of the cancer survivors were 50 years or older in 2019 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While the incidence of cancer in Korea was projected to decrease gradually within the last two decades, it was anticipated that 37.9% of individuals would be diagnosed with any type of cancer when surviving up to life expectancy in the Korean population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Moreover, there has been a consistent and substantial increase in the relative survival rates of individuals diagnosed with cancer [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCancer survivors are defined differently across countries and situations. The most widely used definition delineates it as an ongoing journey commencing at the point of diagnosis and persisting throughout the lifespan [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Long-term cancer survivors have an increased risk of secondary cancers and comorbidities such as cardiovascular disease and type 2 diabetes mellitus [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The development of cancer and cancer-related death is associated with obesity and unhealthy behaviors such as smoking, alcohol drinking, unhealthy diet, and lack of physical activity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, it is important to establish a comprehensive cancer control strategy for cancer survivors to encourage healthy lifestyle behaviors and improve their quality of life.\u003c/p\u003e \u003cp\u003eThe 10 Action Codes of Cancer Prevention in Korea recommend not smoking and avoiding smoke-filled environments; consuming enough fruits and vegetables; maintaining a healthy balanced diet; limiting salt, burnt or charred food, and alcohol consumption; maintaining body weight within a healthy range; and engaging in at least 30 min of regular and moderate physical activity to promote the overall prevention of cancer in the general population [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, adherence to these guidelines is poorer in men than in women. In previous reports, only 0.5% of men had healthy lifestyles [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Compared with women with lower smoking and drinking rates, men generally engage more in unhealthy behaviors, and education and intervention are needed more often for men than for women. A previous study also showed that almost half of Korean male smokers continued to smoke and more than 60% continued alcohol drinking even after a cancer diagnosis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Adherence to exercise guidelines is also low among cancer survivors, especially in older age groups [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChanging modifiable risk factors may help reduce cancer treatment complications, recurrence, and the risks of other common diseases. The number of patients who survive for more than five years after a cancer diagnosis is increasing, emphasizing the need for research on cancer survivors with a focus on improving their health behavior and quality of life. A better understanding of the differences between the behaviors of men and women cancer survivors in different age groups is also necessary to improve survival. However, few studies have compared the overall health behaviors of male cancer survivors and the population without cancer in South Korea, and studies analyzing recent data are scarce. Therefore, we aimed to evaluate the differences in the modifiable health-related variables between survivors of cancer and the general population included in the KNHANES 2016\u0026ndash;2021 using propensity score matching (PSM) analysis.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDatabase source and study population\u003c/h2\u003e \u003cp\u003eThis comparative study included participants from the Korea National Health and Nutrition Examination Survey (KNHANES) VII-VIII (2016\u0026ndash;2021). The KNHANES, initiated in 1998, is a population-based cross-sectional cohort study conducted annually by the Korea Centers for Disease Control and Prevention (KCDC) to monitor health risk trends, chronic disease prevalence, and nutritional status. The KNHANES protocol was described in a previous study [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and all KNHANES databases were accessed from the website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://knhanes.kdca.go.kr/knhanes/\u003c/span\u003e\u003cspan address=\"https://knhanes.kdca.go.kr/knhanes/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA total of 46,828 participants were screened in KNHANES 2016\u0026ndash;2021. Among them, those who were aged less than 19 years (n\u0026thinsp;=\u0026thinsp;8,748), were women (n\u0026thinsp;=\u0026thinsp;21,179), were missing in the cancer survey (n\u0026thinsp;=\u0026thinsp;1,788), were missing values for smoking status, alcohol drinking, physical activity, height, weight, and dietary intake (n\u0026thinsp;=\u0026thinsp;2,902), were missing values for number of cohabitants, household income, education level, employment status, type of job, and private insurance (n\u0026thinsp;=\u0026thinsp;178), and had cancer during the observation period (n\u0026thinsp;=\u0026thinsp;273) were excluded. Finally, we identified 11,760 males who met our inclusion criteria; after 1:3 propensity score matching, 1,396 participants (349 cancer survivors and 1,047 individuals without cancer) remained (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll participants provided written informed consent, and the study protocol was approved by the Institutional Review Board of the National Cancer Center, Republic of Korea (IRB no. NCC2023-0253).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCancer survivors\u003c/h2\u003e \u003cp\u003eData on the cancer diagnosis, type, and treatment status were collected by a trained interviewer using a structured questionnaire. Participants who had been diagnosed with any type of cancer and completed cancer treatment at the time of the survey were categorized as cancer survivors. They answered \u0026ldquo;yes,\u0026rdquo; \u0026ldquo;no,\u0026rdquo; and \u0026ldquo;no\u0026rdquo; to the following questions, respectively: \u0026ldquo;Have you been diagnosed with any types of cancer by a doctor?\u0026rdquo;; \u0026ldquo;Are you currently suffering from cancer?\u0026rdquo;; and \u0026ldquo;Are you currently on cancer treatment?\u0026rdquo; The cancer types included gastric, liver, colorectal, breast, cervical, lung, and thyroid.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003eHealth-related modifiable variables, including BMI, smoking, alcohol, food and nutrient intake, and physical activity, have been identified as major lifestyle factors associated with cancer risk by organizations such as the International Agency for Research on Cancer (IARC), American Institute for Cancer Research (AICR), and National Cancer Center in Korea [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. BMI (kg/m\u003csup\u003e2\u003c/sup\u003e) was calculated by dividing the weight by the square of height; the measurements were performed using a digital weighing scale and a stadiometer. Data on smoking status, alcohol consumption, and physical activity were obtained using structured self-reported questionnaires. Dietary intake was measured using the 24-hour dietary recall method completed by the participants. The BMIs were categorized into underweight (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e), normal (18.5 kg/m\u0026sup2; \u0026le; BMI\u0026thinsp;\u0026lt;\u0026thinsp;23 kg/m\u0026sup2;), overweight (23 kg/m\u0026sup2; \u0026le; BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m\u0026sup2;), and obese (25 kg/m\u0026sup2; \u0026le; BMI). The smoking statuses were as follows: never smoked, past smoker, and current smoker. E-cigarette users were categorized as current smokers who used e-cigarettes daily or occasionally. Based on alcohol consumption, the participants were categorized into non-drinkers, past drinkers, and current drinkers. The high-risk drinkers were males who reported consuming averages of \u0026ge;\u0026thinsp;7 drinks at a sitting, with a frequency of at least 2 times/week. Physically active participants were categorized as those who performed moderate-intensity physical activity for at least 150 min per week, high-intensity physical activity for at least 75 min per week, or a combination of moderate and high-intensity activities; 1 min of high-intensity activity was equivalent to 2 min of moderate-intensity activity. The consumption of food groups and nutrients was estimated using the Korean Food Composition Table prepared by the Rural Development Administration National Institute of Agricultural Science [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The food groups comprised grain, legumes/beans, vegetables, mushrooms, fruits, seaweed, meat, eggs, fish and shellfish, and milk/dairy products. The nutrient intake included total energy, carbohydrates, protein, fat, sugars, and sodium.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eTo control for potential confounders, we investigated the variables of interest, including demographic characteristics and employment-related variables. The sociodemographic and lifestyle questionnaire items used for PSM included age (19\u0026ndash;29, 30\u0026ndash;39, 40\u0026ndash;49, 50\u0026ndash;59, 60\u0026ndash;69, and above 70), number of cohabitants (0, 1, 2, 3, and 3 or more), household income level (quartiles), education level (under elementary school, middle school, high school, above college), employment status (employed or unemployed), type of occupations (managers/professionals/related, office jobs, service or sales, skilled agricultural/forestry/fishery, equipment/machine operating/assembling, elementary workers, and unemployed), and private insurance (have or none).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eThe participants were divided into two groups: cancer survivors and those without cancer. The chi-squared test and t-test were applied to the categorical and continuous variables to compare the cancer survivors and participants without cancer. Logistic regression was used to determine the odds ratios (ORs) and 95% confidence intervals (CIs) to evaluate the associations between BMI, smoking, alcohol consumption, physical activity, and diet and cancer survival. Unadjusted logistic regression was used to determine crude ORs, while multivariable logistic regression was used to determine the adjusted ORs for age, number of cohabitants, household income, education level, employment status, job type, and private insurance. PSM was used to match pairs of cancer survivors and participants without cancer. The propensity scores were calculated using a multivariate logistic regression model. The confounding variables used for matching included age, number of cohabitants, household income, educational level, employment status, job type, and private insurance. The cancer survivors were matched with the participants without cancer using 1:3 ratio matching, and the standard mean differences (SMD) were lower than 0.1 after matching. Statistical analysis was performed using SAS statistical software (version 9.4; SAS Institute Inc., Cary, NC, USA), and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 denoted statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eGeneral characteristics of the participants\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the general characteristics of the cancer survivors and participants without cancer before and after PSM. Of the 11,760 participants, 349 answered that they had been diagnosed with cancer and their treatment had ended; they were currently not undergoing cancer treatment. The average age of the participants was 51.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1 years before matching and 67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7 years after matching. Before PSM, the variables used to match the cancer survivors and participants without cancer showed differences (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The cancer survivors were more likely to be older, lived with one cohabitant, had a lower income or education level, were unemployed, and did not have private insurance than the participants. However, there were no significant differences between them after PSM. Among the 349 male cancer survivors, 30.7%, 22.6%, 8.9%, 5.4%, 2.0%, and 35.0% had stomach, colorectal, thyroid, lung, liver, and other cancers, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the cancer survivors and the participants without cancer before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM (n\u0026thinsp;=\u0026thinsp;11,760)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter 1:3 PSM (n\u0026thinsp;=\u0026thinsp;1,396)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants without cancer\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;11,411)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCancer survivors\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParticipants without cancer\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,047)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCancer survivors \u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,524 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e0.9222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,733 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,041 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (8.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,053 (20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e114 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38 (15.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,077 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e288 (24.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96 (25.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,983 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e573 (45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e191 (47.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of cohabitants\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,413 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.2656\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,675 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e565 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e197 (50.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,857 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e193 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57 (20.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,466 (35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51 (20.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHousehold income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLowest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,898 (12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e327 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e115 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.2994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLower middle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,721 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e294 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86 (20.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper middle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,198 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (23.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73 (23.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,594 (35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e215 (25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75 (28.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder elementary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,540 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e291 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.8720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,111 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e156 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52 (13.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,006 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e273 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91 (25.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbove college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,754 (46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (39.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e327 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e109 (39.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,209 (75.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159 (53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e477 (51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e159 (53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of job\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManagers, professionals, and related\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,863 (18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e0.0651\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOffice jobs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,377 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26 (11.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService or sales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,146 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSkilled agricultural, forestry, and fishery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e668 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (7.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquipment, machine operating, and assembling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,205 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29 (9.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElementary workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e950 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (8.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,202 (24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190 (46.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e570 (48.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e190 (46.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrivate insurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,898 (82.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183 (61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e568 (60.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e183 (61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.7717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,513 (17.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166 (38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e479 (39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e166 (38.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCancer site\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStomach cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e107 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColorectal cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e122 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003en (weighted %); PSM: propensity score matching.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCovariate balance before and after PSM\u003c/h2\u003e \u003cp\u003eThe 1:3 PSM generated data from 349 cancer survivors and 1,047 controls. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the SMDs of the balancing covariates before and after PSM using a love plot to show the matching effect. Before the PSM, most SMDs were observed to deviate from zero. After PSM, the love plot showed that all SMDs were less than the absolute value of 0.1. That is, the standardized difference between the cancer survivors and participants without cancer decreased significantly after matching, and the SMD values were all less than 0.1, confirming that the two groups were balanced.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eComparison of health-related variables of the cancer survivors and controls\u003c/h2\u003e \u003cp\u003eThe differences between the health-related variables of the cancer survivors and the participants without cancer are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The chi-squared test showed significant differences between the BMIs, smoking statuses, and alcohol consumption of the two groups after PSM (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The results of the t-test for food and nutrient intake showed that only carbohydrate intake differed for the two groups. The cancer survivors were more likely to have a normal weight, previous history of smoking, previous history of drinking, and higher intake of carbohydrates than participants without cancer. However, we found no significant differences in e-cigarette use, physical activity, food intake, or intake of other nutrients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBMI, smoking, alcohol drinking, physical activity, and daily food and nutrient intake of the participants without cancer and cancer survivors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM (n\u0026thinsp;=\u0026thinsp;11,760)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter 1:3 PSM (n\u0026thinsp;=\u0026thinsp;1,396)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants without cancer\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;11,411)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCancer survivor\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParticipants without cancer\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,047)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCancer survivor\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e289 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,310 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e315 (28.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e148 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,004 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e330 (31.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,808 (43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e370 (37.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,856 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e220 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.0016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,849 (38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e576 (54.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e233 (66.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,706 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e251 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58 (18.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUsing E-Cigarettes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever and past smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,705 (65.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e291 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e796 (75.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e291 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,399 (30.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e245 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol drinking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e505 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.0075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,569 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e218 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94 (26.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9,337 (84.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233 (69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e744 (73.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e233 (69.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh-risk drinking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e505 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.1221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.1454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,764 (76.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282 (80.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e835 (79.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e282 (80.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,142 (19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (14.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6145 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.1588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e627 (56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e207 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.6481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5266 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e142 (45.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e420 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e142 (45.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFood intake (g/day)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e319.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e313.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e298.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e313.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0850\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegumes/beans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1885\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVegetables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e337.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e374.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e360\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e374.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2933\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMushroom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e194.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e194.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5564\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeaweed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0379\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2878\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e108.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEggs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.8644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish and shellfish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e143.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilk and dairy product\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.8\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3852\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNutrient intake\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal energy (kcal/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2321.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2121.7\u0026thinsp;\u0026plusmn;\u0026thinsp;49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2068.4\u0026thinsp;\u0026plusmn;\u0026thinsp;32.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2121.7\u0026thinsp;\u0026plusmn;\u0026thinsp;49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate (g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e320.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e311\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e325.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0322\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5294\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat (g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate (% of energy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3896\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (% of energy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat (% of energy)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.5431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSugars (g/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2633\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (mg/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4041.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3876.7\u0026thinsp;\u0026plusmn;\u0026thinsp;135.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3718.6\u0026thinsp;\u0026plusmn;\u0026thinsp;72.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3876.7\u0026thinsp;\u0026plusmn;\u0026thinsp;135.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.2095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ePSM: propensity score matching; BMI: body mass index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultivariate logistic regression analysis showed differences in the proportions of participants who were overweight and had a previous history of smoking and drinking among the cancer survivors and the participants without cancer (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). More survivors of cancer than participants without cancer were overweight (OR, 0.421; 95% CI, 0.289\u0026ndash;0.614; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0006) after PSM and adjustment for potential covariates. Compared with that of the never-smoked group, the OR for the cancer survivors who were former smokers was 1.783 (95% CI: 1.226\u0026ndash;2.592, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0005). The cancer survivors had a significantly higher OR for being former drinkers (OR: 2.362; 95% CI: 1.275\u0026ndash;4.373, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0020) than for being non-drinkers. The ORs and 95% CI for those with obesity and high-risk drinkers were 0.553 (0.383\u0026ndash;0.796) and 2.154 (1.038\u0026ndash;4.471), respectively. However, the differences were not statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eORs of health-related variables for cancer survivors before and after PSM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eBefore PSM (n\u0026thinsp;=\u0026thinsp;11,760)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eAfter PSM (n\u0026thinsp;=\u0026thinsp;1,396)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCrude OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.039 (0.561\u0026ndash;1.925)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.094 (0.585\u0026ndash;2.045)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.995 (0.474\u0026ndash;2.090)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.072 (0.516\u0026ndash;2.224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.1304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.533 (0.388\u0026ndash;0.733)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.553 (0.398\u0026ndash;0.767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.438 (0.302\u0026ndash;0.637)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.421 (0.289\u0026ndash;0.614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.490 (0.365\u0026ndash;0.659)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.624 (0.452\u0026ndash;0.862)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.569 (0.400\u0026ndash;0.809)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.553 (0.383\u0026ndash;0.796)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePast smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.145 (2.281\u0026ndash;4.336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.798 (1.294\u0026ndash;2.498)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.761 (1.215\u0026ndash;2.552)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.783 (1.226\u0026ndash;2.592)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.956 (0.624\u0026ndash;1.466)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.126 (0.724\u0026ndash;1.753)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.3514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.062 (0.664\u0026ndash;1.697)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.122 (0.694\u0026ndash;1.813)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.3852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol drinking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormer drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.829 (1.052\u0026ndash;3.179)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.143 (1.217\u0026ndash;3.772)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.374 (1.293\u0026ndash;4.361)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.362 (1.275\u0026ndash;4.373)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.670 (0.402\u0026ndash;1.118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.476 (0.868\u0026ndash;2.510)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.9618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.624 (0.923\u0026ndash;2.859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.7655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.581 (0.874\u0026ndash;2.860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.8809\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh-risk drinking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.862 (0.518\u0026ndash;1.434)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.642 (0.973\u0026ndash;2.772)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.746 (1.001\u0026ndash;3.047)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.751 (0.983\u0026ndash;3.121)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.3387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.625 (0.343\u0026ndash;1.141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.760 (0.925\u0026ndash;3.351)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.996 (0.999\u0026ndash;3.991)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.154 (1.038\u0026ndash;4.471)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical activity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eref (1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.833 (0.645\u0026ndash;1.075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.211 (0.932\u0026ndash;1.575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.068 (0.805\u0026ndash;1.416)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.6482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.061 (0.792\u0026ndash;1.423)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.6893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eReference group for logistic analysis: non-cancer controls; PSM: propensity score matching; BMI: body mass index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eOdds ratio (OR) adjusted for age, number of cohabitants, household income, education level, employment status, job type, and private insurance.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eComparison of the health-related variables stratified by age\u003c/h2\u003e \u003cp\u003eThe results of the age-stratified analysis after PSM are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The participants were divided into young (19\u0026ndash;49 years), middle-aged (50\u0026ndash;64 years), and older (65 years or older) groups. The middle-aged and older cancer survivors were less likely to be overweight (OR: 0.357, 95% CI: 0.167\u0026ndash;0.764 for middle-aged and OR: 0.455, 95% CI: 0.287\u0026ndash;0.721 for older adults) and obese (OR: 0.444, 95% CI: 0.219\u0026ndash;0.901 for middle-aged and OR: 0.635, 95% CI\u0026thinsp;=\u0026thinsp;0.408\u0026ndash;0.987 for older adults) than the participants without cancer after multivariable adjustments. However, only the difference in the likelihood of being overweight was significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The middle-aged cancer survivors had higher ORs for being former smokers (OR: 3.538, 95% CI: 1.303\u0026ndash;9.607), while the older survivors had higher ORs for being former drinkers (OR: 2.508, 95% CI: 1.219\u0026ndash;5.162). However, there were no significant differences among the young adults.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study compared the health-related factors, including BMI, smoking and alcohol consumption, food intake, and nutrient intake, for the cancer survivors and participants without cancer using PSM. Using data from the KNHANES, we found that the cancer survivors had normal weights, were more likely to be former smokers and drinkers, and had high carbohydrate consumption. The age-stratified analysis showed no differences between the young survivors and the participants without cancer. However, the middle-aged and older survivors had normal weight. The middle-aged survivors were also more likely to be former smokers while the older survivors were more likely to be former drinkers.\u003c/p\u003e \u003cp\u003eA previous analysis of the KNHANES IV\u0026ndash;V (2007\u0026ndash;2012) showed higher rates of former smokers and drinkers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which was consistent with our results that cancer survivors were more likely to adopt healthy behaviors. A previous study reported that the odds ratios of current drinking and smoking were lower for the cancer survivors than for the participants without a history of cancer; however, sex was not analyzed [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In our study, the ORs for current drinking and smoking were not different among the cancer survivors.\u003c/p\u003e \u003cp\u003eThe proportion of cancer survivors who were currently smoking in this study was 18%. While this was lower than the proportion of currently smoking participants who had not had cancer, caution should be exercised because there was evidence that smoking may increase the risk of second primary cancers in survivors of cancers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our study also showed that the proportion of former smokers was higher among the cancer survivors than among the participants who had not had cancer. However, there were no differences in e-cigarette use after PSM [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This is attributed to the lack of awareness of the harm caused by e-cigarettes. Therefore, effort should be made to create awareness about the adverse effects of e-cigarettes, although they have a lower addiction rate than regular cigarettes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlcohol consumption is a significant health issue associated with several types of cancer, including oral, liver, and colorectal [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Alcohol consumption among survivors of cancer is also highly associated with the risk of recurrence, secondary cancers, and increased mortality [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this study, 69% of cancer survivors still consumed alcohol, and this rate was higher than that reported in previous studies [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This may be related to the high rate of rejecting rules and the difficulty in following selected recommendations for avoiding alcohol consumption to prevent cancer in the Korean National Cancer Prevention Awareness and Practice Survey in 2021 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Further studies are needed to identify the reasons for the increasing number of current drinkers among cancer survivors. In a previous study involving the 2007\u0026ndash;2013 KNHANES, the proportion of high-risk drinkers was 16.3% [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The proportion of high-risk drinkers among cancer survivors who had consumed alcohol previously was slightly lower, at 14.9%, in this study. However, as this was still higher than the high-risk drinking rate of 12.8% for the participants who had not had cancer after matching, education is necessary for the risks associated with alcohol consumption, as well as high-risk drinking.\u003c/p\u003e \u003cp\u003eOf the male cancer survivors, 54.0% engaged in physical activity, while 45.0% were inactive. The levels of physical activity among the participants who had not had cancer did not also differ, which is consistent with the reports of previous studies [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Physical activity during and after cancer treatment can reduce fatigue, prevent cancer recurrence, improve survival, and positively impact quality of life [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Moreover, sedentary behavior is associated with a higher risk of cancer-related mortality [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Considering the positive impact of physical activity on the quality of life and the associated reduction of the risk of comorbidities, the government should encourage physical activity.\u003c/p\u003e \u003cp\u003eThis study also showed that male cancer survivors have lower odds of being overweight or obese. Being overweight or obese is associated with better survival for some types of cancer [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]; in a meta-analysis of obesity and cancer survival, adiposity was not associated with the risks of 10 cancer types, including breast, colorectal, and gastroesophageal cancers [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, the results of a cohort study that followed 1,614,583 person-years in South Korea showed that male cancer survivors with obesity exhibited an increased incidence of secondary cancers, which was slightly higher than that of the first primary cancer risk in the overall cohort [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Another meta-analysis showed that obesity after colorectal cancer diagnosis was associated with a high risk of all-cause mortality [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Given the complications associated with survival after cancer and other obesity-relate8d comorbidities, it is important to maintain a healthy body weight throughout life.\u003c/p\u003e \u003cp\u003eThere were no significant differences in the food and nutrient intake between the cancer survivors and participants without cancer, except for daily carbohydrate consumption. The differences in carbohydrate intake in our study may be related to the higher intake of grains, fruits, and vegetables in cancer survivors than in the non-cancer population. However, the percentage of energy intake from carbohydrates did not differ. According to the 2020 Dietary Reference Intake for Koreans, the proportions of energy from carbohydrates, protein, and fat were 55\u0026ndash;65%, 7\u0026ndash;20%, and 15\u0026ndash;30%, respectively [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and this study showed appropriate ratios of carbohydrate, protein, and fat for both two groups. Nevertheless, caution should be exercised with sugar and salt intake and healthy eating patterns should be adopted. Evidence from several studies in a meta-analysis showed that healthier diet habits, such as high consumption of fruits, vegetables, whole grains, fiber, and higher diet quality, were associated with better prognoses for survivors of some types of cancer [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and prevention of cancer in the general population [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In addition, the intake of refined carbohydrates was associated with a higher risk of some types of cancer, whereas fiber and whole grains were associated with a lower risk of cancer [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, the consumption of red, processed, and sugary beverages is associated with greater risks of cancer and mortality [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, it is important to promote healthier dietary habits, policies, and programs and consider them in conjunction with other lifestyle behaviors.\u003c/p\u003e \u003cp\u003eSouth Korea has a higher chance of long-term survival after cancer diagnosis now than in the past [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. To improve treatment efficacy, individual behavior, physical activity, and dietary consumption are important. Survivors of cancer should attempt lifestyle changes to enhance their health, quality of life, and survival [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. It is also necessary to provide appropriate interventions for cancer survivors through healthcare programs.\u003c/p\u003e \u003cp\u003eThe strengths of this study are as follows: First, it used a population-based probabilistic sample from 192 cities in South Korea, which could improve the representativeness of the Korean population. Second, we adjusted for potential confounders in the statistical model to control for confounding effects. Third, we used the 1:3 PSM method to reduce confounding variables in the cross-sectional analysis. The presence of household members, especially single-person households, household income levels, employment status, and types of occupations that can affect health behavior were included in the PSM analysis to reduce the differences and selective biases of the case and control groups. The balance of covariates for the cancer survivors and individuals without cancer provided better insights into the differences in health-related behaviors between the two groups. However, this study has few limitations. There was no information on the cancer stage and that on the number of years elapsed since the end of treatment was not provided. Additionally, self-reported cancers may lead to the underestimation of the prevalence of actual cancers. The cross-sectional study design restricted the establishment of temporal differences between the two groups. Finally, our sample was small. However, we used PSM to minimize distortion and generalization of the data, and additional research is needed to verify our findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe findings of this study indicate that the cancer survivors were more likely to have normal weight, be former smokers, and be former drinkers than participants without cancer. However, there were no significant differences in other behaviors. Therefore, we suggest that survivors of cancer change their health-related behaviors to prevent cancer recurrence and improve their quality of life. Further studies are needed to link the cohort data with cancer diagnosis records and stages to evaluate changes in health-related behaviors and factors that may affect the behaviors of long-term cancer survivors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contribution\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, B.K; methodology, B.K; validation, B.K; formal analysis, H.J; writing-original draft preparation, H.J and Y.C; writing-review and editing, H.J, Y.C, and B.K. supervision, B.K, project administration, B.K. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Cancer Center Research Grant 2311440-2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflicts of Interest/Competing Interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics Approval\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey protocol and secondary use of the data were approved by the Institutional Review Board of the National Cancer Center, Republic of Korea (IRB no. NCC2023-0253)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Availability Statement\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survey data from KNHANES VII-VIII can be accessed and downloaded from the KNHANES homepage ( https://knhanes.kdca.go.kr/knhanes/main.do, accessed on January 5, 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent to Participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided informed written consent before participating in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKang MJ et al. (2022) Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2019. Cancer Res Treat 54(2):330\u0026ndash;344. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4143/crt.2022.128\u003c/span\u003e\u003cspan address=\"10.4143/crt.2022.128\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang YS et al. (2022) Prediction of cancer survivors\u0026rsquo; mortality risk in Korea: a 25-year nationwide prospective cohort study. Epidemiol Health 44:e2022075. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4178/epih.e2022075\u003c/span\u003e\u003cspan address=\"10.4178/epih.e2022075\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJung KW et al. (2023) Prediction of cancer incidence and mortality in Korea, 2023. Cancer Res Treat 55(2):400\u0026ndash;407. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4143/crt.2023.448\u003c/span\u003e\u003cspan address=\"10.4143/crt.2023.448\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarzorati C, Riva S, Pravettoni G (2017) Who is a cancer survivor? A systematic review of published definitions. J Cancer Educ 32(2):228\u0026ndash;237. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13187-016-0997-2\u003c/span\u003e\u003cspan address=\"10.1007/s13187-016-0997-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao X et al. (2023) Association of frailty with the incidence risk of cardiovascular disease and type 2 diabetes mellitus in long-term cancer survivors: a prospective cohort study. BMC Med 21(1):74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12916-023-02774-1\u003c/span\u003e\u003cspan address=\"10.1186/s12916-023-02774-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonin N et al. (2016) Risk of second primary malignancies among cancer survivors in the United States, 1992 through 2008. Cancer 122(19):3075\u0026ndash;3086. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cncr.30164\u003c/span\u003e\u003cspan address=\"10.1002/cncr.30164\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKerr J, Anderson C, Lippman SM (2017) Physical activity, sedentary behaviour, diet, and cancer: an update and emerging new evidence. Lancet Oncol 18(8):e457\u0026ndash;e471. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1470-2045(17)30411-4\u003c/span\u003e\u003cspan address=\"10.1016/S1470-2045(17)30411-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKorea Ministry of Health and Welfare and National Cancer Center Korea (2006). 10 action codes of cancer prevention Accessed 2024 Jan 8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cancer.go.kr/lay1/S1T200C203/contents.do\u003c/span\u003e\u003cspan address=\"https://www.cancer.go.kr/lay1/S1T200C203/contents.do\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh JK et al. (2023) Adherence to cancer prevention guidelines and cancer incidence and mortality: A population-based cohort study. Cancer Res Treat 55(1):15\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4143/crt.2021.1031\u003c/span\u003e\u003cspan address=\"10.4143/crt.2021.1031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoo HY et al. (2020) Prevalence and predictors of sustained smoking after a cancer diagnosis in Korean men. Cancer Res Treat 52(1):139\u0026ndash;148. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4143/crt.2018.609\u003c/span\u003e\u003cspan address=\"10.4143/crt.2018.609\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKo H, Song YM, Shin JY (2017) Factors associated with alcohol drinking behavior of cancer survivors: the Korean National Health and Nutrition Examination Survey. Drug Alcohol Depend 171:9\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.drugalcdep.2016.11.024\u003c/span\u003e\u003cspan address=\"10.1016/j.drugalcdep.2016.11.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark JH et al. (2021) Physical activity of Korean cancer survivors is associated with age and sex. Korean J Intern Med 36(Suppl 1):S225\u0026ndash;S234. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3904/kjim.2019.240\u003c/span\u003e\u003cspan address=\"10.3904/kjim.2019.240\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKweon S et al. (2014) Data resource profile: the Korea National Health and Nutrition Examination Survey (KNHANES). Int J Epidemiol 43(1):69\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ije/dyt228\u003c/span\u003e\u003cspan address=\"10.1093/ije/dyt228\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClinton SK, Giovannucci EL, Hursting SD (2020) The World Cancer Research Fund/American Institute for Cancer Research Third expert report on diet, nutrition, physical activity, and cancer: impact and future directions. J Nutr 150(4):663\u0026ndash;671. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jn/nxz268\u003c/span\u003e\u003cspan address=\"10.1093/jn/nxz268\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization \u003cem\u003epreventing cancer\u003c/em\u003e. Accessed 2024 Jan 31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/activities/preventing-cancer\u003c/span\u003e\u003cspan address=\"https://www.who.int/activities/preventing-cancer\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRural Development Administration, National Institute of Agricultural Science. Korean Food Composition Table, 9th revision. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://koreanfood.rda.go.kr/eng/fctFoodSrchEng/engMain\u003c/span\u003e\u003cspan address=\"http://koreanfood.rda.go.kr/eng/fctFoodSrchEng/engMain\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark B et al. (2015) Health behaviors of cancer survivors in nationwide cross-sectional survey in Korea: higher alcohol drinking, lower smoking, and physical inactivity pattern in survivors with higher household income. Med (Baltim) 94(31):e1214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/MD.0000000000001214\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000001214\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePhua ZJ, MacInnis RJ, Jayasekara H (2022) Cigarette smoking and risk of second primary cancer: a systematic review and meta-analysis. Cancer Epidemiol 78:102160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.canep.2022.102160\u003c/span\u003e\u003cspan address=\"10.1016/j.canep.2022.102160\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaek J, Son S, Choi YJ (2022) E-cigarette and cigarette use among cancer survivors \u003cem\u003eversus\u003c/em\u003e general population: a case-control study in Korea. J Cancer Surviv 16(4):741\u0026ndash;750. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11764-021-01067-x\u003c/span\u003e\u003cspan address=\"10.1007/s11764-021-01067-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRohde JA et al. (2020) E-cigarette health harm awareness and discouragement: implications for health communication. Nicotine Tob Res 22(7):1131\u0026ndash;1138. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ntr/ntz194\u003c/span\u003e\u003cspan address=\"10.1093/ntr/ntz194\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh SW (2020) Problem drinking in cancer survivors. Korean J Fam Med 41(4):205\u0026ndash;206. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4082/kjfm.41.4E\u003c/span\u003e\u003cspan address=\"10.4082/kjfm.41.4E\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwedhelm C et al. (2016) Effect of diet on mortality and cancer recurrence among cancer survivors: a systematic review and meta-analysis of cohort studies. Nutr Rev 74(12):737\u0026ndash;748. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nutrit/nuw045\u003c/span\u003e\u003cspan address=\"10.1093/nutrit/nuw045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi M et al. (2023) Alcohol consumption among adults with a cancer diagnosis in the all of US research program. JAMA Netw Open 6(8):e2328328. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jamanetworkopen.2023.28328\u003c/span\u003e\u003cspan address=\"10.1001/jamanetworkopen.2023.28328\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh MG et al. (2013) Health behaviors of cancer survivors: the fourth Korea National health and nutrition examination survey (KNHANES IV, 2007\u0026ndash;09). Jpn J Clin Oncol 43(10):981\u0026ndash;987. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jjco/hyt118\u003c/span\u003e\u003cspan address=\"10.1093/jjco/hyt118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh JK et al. (2022) Awareness of and practice toward cancer prevention recommendations: results of the Korean National Cancer Prevention Awareness and Practice Survey in 2021. Epidemiol Health 44:e2022068. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4178/epih.e2022068\u003c/span\u003e\u003cspan address=\"10.4178/epih.e2022068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J et al. (2021) Intensity- and domain-specific physical activity levels between cancer survivors and non-cancer diagnosis individuals: a propensity score matching analysis. Support Care Cancer 29(2):661\u0026ndash;668. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00520-020-05514-w\u003c/span\u003e\u003cspan address=\"10.1007/s00520-020-05514-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrandenbarg D et al. (2018) The effect of physical activity on fatigue among survivors of colorectal cancer: a systematic review and meta-analysis. Support Care Cancer 26(2):393\u0026ndash;403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00520-017-3920-4\u003c/span\u003e\u003cspan address=\"10.1007/s00520-017-3920-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y et al. (2023) Active for life after cancer: association of physical activity with cancer patients\u0026rsquo; interpersonal competence, quality of life, and survival beliefs. Behav Sci (Basel) 13(6). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/bs13060449\u003c/span\u003e\u003cspan address=\"10.3390/bs13060449\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamblen AJ et al. (2023) Physical activity and dietary considerations for prostate cancer patients: future research directions. Proc Nutr Soc 82(3):298\u0026ndash;304. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0029665123000046\u003c/span\u003e\u003cspan address=\"10.1017/S0029665123000046\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEkelund U et al. (2019) Do the associations of sedentary behaviour with cardiovascular disease mortality and cancer mortality differ by physical activity level? A systematic review and harmonised meta-analysis of data from 850 060 participants. Br J Sports Med 53(14):886\u0026ndash;894. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bjsports-2017-098963\u003c/span\u003e\u003cspan address=\"10.1136/bjsports-2017-098963\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee DH, Giovannucci EL (2019) The obesity paradox in cancer: epidemiologic insights and perspectives. Curr Nutr Rep 8(3):175\u0026ndash;181. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13668-019-00280-6\u003c/span\u003e\u003cspan address=\"10.1007/s13668-019-00280-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng E et al. (2022) Adiposity and cancer survival: a systematic review and meta-analysis. Cancer Causes Control 33(10):1219\u0026ndash;1246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10552-022-01613-7\u003c/span\u003e\u003cspan address=\"10.1007/s10552-022-01613-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark SM et al. (2016) Prediagnosis body mass index and risk of secondary primary cancer in male cancer survivors: A large cohort study. J Clin Oncol 34(34):4116\u0026ndash;4124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1200/JCO.2016.66.4920\u003c/span\u003e\u003cspan address=\"10.1200/JCO.2016.66.4920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J et al. (2015) Association between body mass index and prognosis of colorectal cancer: a meta-analysis of prospective cohort studies. PLOS ONE 10(3):e0120706. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0120706\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0120706\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Health and Welfare, Korea Centers for Disease Control and Prevention (2021) The Korean Nutrition Society. Application of Dietary Reference Intakes for Koreans 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastro-Espin C, Agudo A (2022) The role of diet in prognosis among cancer survivors: A systematic review and meta-analysis of dietary patterns and diet interventions. Nutrients 14(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/nu14020348\u003c/span\u003e\u003cspan address=\"10.3390/nu14020348\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHurtado-Barroso S et al. (2020) Vegetable and fruit consumption and prognosis among cancer survivors: A systematic review and meta-analysis of cohort studies. Adv Nutr 11(6):1569\u0026ndash;1582. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/advances/nmaa082\u003c/span\u003e\u003cspan address=\"10.1093/advances/nmaa082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwingshackl L et al. (2017) Adherence to Mediterranean diet and risk of cancer: an updated systematic review and meta-analysis. Nutrients 9(10). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/nu9101063\u003c/span\u003e\u003cspan address=\"10.3390/nu9101063\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakai M et al. (2022) Fruit and vegetable consumption and risk of esophageal cancer in the Asian region: a systematic review and meta-analysis. Esophagus 19(1):27\u0026ndash;38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10388-021-00882-6\u003c/span\u003e\u003cspan address=\"10.1007/s10388-021-00882-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYan H et al. (2022) Fruit and vegetable consumption and the risk of prostate cancer: A systematic review and meta-analysis. Nutr Cancer 74(4):1235\u0026ndash;1242. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/01635581.2021.1952445\u003c/span\u003e\u003cspan address=\"10.1080/01635581.2021.1952445\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTao J et al. (2021) Role of dietary carbohydrates on risk of lung cancer. Lung Cancer 155:87\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lungcan.2021.03.009\u003c/span\u003e\u003cspan address=\"10.1016/j.lungcan.2021.03.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzeem S et al. (2015) Diet and colorectal cancer risk in Asia\u0026ndash;a systematic review. Asian Pac J Cancer Prev 16(13):5389\u0026ndash;5396. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7314/apjcp.2015.16.13.5389\u003c/span\u003e\u003cspan address=\"10.7314/apjcp.2015.16.13.5389\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoi Y, et al. (2013) Consumption of red and processed meat and esophageal cancer risk: meta-analysis. World J Gastroenterol 19(7):1020\u0026ndash;1029. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3748/wjg.v19.i7.1020\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v19.i7.1020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Y et al. (2021) Consumption of sugar-sweetened beverages and fruit juice and human cancer: a systematic review and dose-response meta-analysis of observational studies. J Cancer 12(10):3077\u0026ndash;3088. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7150/jca.51322\u003c/span\u003e\u003cspan address=\"10.7150/jca.51322\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"cancer, survival, propensity score matching, KNHANES, South Korean","lastPublishedDoi":"10.21203/rs.3.rs-3960425/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3960425/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eStudies that have compared the overall health behaviors of male survivors of cancer and the population without cancer in South Korea are limited. Therefore, we aimed to compare the quality of life and health-related behaviors of cancer survivors and the population without cancer in South Korea.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional, matched case-control study recruited Korean males aged 19\u0026ndash;80 years from the Korea National Health and Nutrition Examination Survey (KNHANES) VIII. Of the 11,760 participants, 349 cancer survivors and 1,047 controls without cancer were matched by 1:3 propensity score matching using age, cohabitation, household income, education level, employment status, type of job, and private insurance. Height, weight, smoking status, drinking status, and physical activity status were also recorded.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cancer survivors had lower odds of being overweight and higher odds of being former smokers and drinkers than the controls after adjusting for potential confounders. The cancer survivors and controls showed no significant differences in physical activity or food consumption. No significant differences were noted among the young adults. However, the middle-aged and older male cancer survivors were more likely to be overweight and obese, respectively. The middle-aged survivors were also more likely to be former smokers, while the older survivors were more likely to be former drinkers.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe cancer survivors were more likely to have a normal weight, be past smokers, or be former drinkers. Education on cancer prevention is required to improve health-related behaviors and prevent secondary cancer.\u003c/p\u003e","manuscriptTitle":"Health-related behaviors of adult male cancer survivors in Korea: A propensity score matching analysis of data from the Korean National Health and Nutrition Examination Survey VII-VIII (2016– 2021)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-22 21:10:40","doi":"10.21203/rs.3.rs-3960425/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-15T00:54:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-14T13:57:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"273273405865435096594801671911847028072","date":"2024-05-28T20:46:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-28T01:04:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"551a14c3-bab4-4583-b8bd-4f538f7a616f","date":"2024-04-11T07:10:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-20T00:41:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-19T19:23:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-02-21T06:41:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2024-02-16T05:16:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bb8ff7f4-9f80-4670-82e2-df86f0556a7b","owner":[],"postedDate":"February 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-10T16:08:59+00:00","versionOfRecord":{"articleIdentity":"rs-3960425","link":"https://doi.org/10.1007/s00520-025-09200-7","journal":{"identity":"supportive-care-in-cancer","isVorOnly":false,"title":"Supportive Care in Cancer"},"publishedOn":"2025-02-07 15:57:58","publishedOnDateReadable":"February 7th, 2025"},"versionCreatedAt":"2024-02-22 21:10:40","video":"","vorDoi":"10.1007/s00520-025-09200-7","vorDoiUrl":"https://doi.org/10.1007/s00520-025-09200-7","workflowStages":[]},"version":"v1","identity":"rs-3960425","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3960425","identity":"rs-3960425","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}