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Background The added value of preoperative PET/CT for the overall survival of patients with resectable non-small cell lung cancer (NSCLC) is unknown. Purpose To investigate the association of the use of preoperative PET/CT on survival of patients with resectable stage I-IIIB NSCLC. Materials and Methods In this retrospective study, patients with resectable stage I-IIIB NSCLC who underwent thoracic surgery from January 1, 2009, to December 31, 2018, from the Taiwan Cancer Registry were included. The last follow-up date was December 31, 2019. Patients were categorized into two groups according to whether they underwent preoperative metabolic imaging with fluorine 18 fluorodeoxyglucose PET/CT. Patients who did not undergo preoperative imaging were used as the control group. The primary outcome of interest was all-cause mortality. Patients in both groups were propensity score matched at a ratio of 1:1. Matching variables used were sex, age, histologic findings, American Joint Committee on Cancer clinical stage, cT stage, cN stage, current and past smoker history, adjuvant chemotherapy, adjuvant chemoradiation, Charlson comorbidity index, and hospital type. Survival curves were generated using the Kaplan-Meier method and compared using the log-rank test. Results In the matched cohort, 6754 patients (3349 men, mean age ± SD: 64 years ± 11) underwent PET/CT and 6754 did not (3362 men, mean age: 64 years ± 11). In adjusted analysis, patients with stage IIIA or IIIB NSCLC and preoperative PET/CT had a lower risk of death versus those without PET/CT (for stage IIIA: hazard ratio [HR] = 0.90 [95% CI: 0.79, 0.94]

An integrated multistage supply chain inventory model containing a single manufacturer and multiple retailers is proposed to consider deteriorating materials and finished products with imperfect production and inspection systems. The main purpose is to jointly determine the manufacturer’s production and delivery strategies and the retailers’ replenishment strategies to maximize the integrated total profit. First, the individual total profit functions of the manufacturer and multiple retailers are established and are integrated to form the total profit function of the supply chain system. Then, to address the model complexity, an algorithm is proposed to obtain the optimal solution. Several practical numerical examples are presented to demonstrate the solution procedure, and a sensitivity analysis is performed on the major parameters. From the numerical results, several findings that differ from those in the previous literature were observed. First, retailers with larger market scale, better cost control, and inspection capabilities guarantee higher integrated total profit. Second, increasing the deterioration rates of materials and finished products affect the order quantity of materials in various ways. Third, the manufacturer’s shipping strategy is rigid and not easily adjusted in the proposed model. The performance of the proposed model has several meaningful management implications.

Yen-Ling Chiu,1– 3 Mao-Jhen Jhou,4 Tian-Shyug Lee,4,5 Chi-Jie Lu,4– 6 Ming-Shu Chen7 1Graduate Institue of Medicine and Graduate School of Biomedical Informatics, Yuan Ze University, Taoyuan, 32003, Taiwan, Republic of China; 2Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, 10002, Taiwan, Republic of China; 3Department of Medical Research, Department of Medicine,Far Eastern Memorial Hospital, New Taipei, 22056, Taiwan, Republic of China; 4Graduate Institute of Business Administration, Fu Jen Catholic University, New Taipei, 242062, Taiwan, Republic of China; 5Artificial Intelligence Development Center, Fu Jen Catholic University, New Taipei City, 242062, Taiwan, Republic of China; 6Department of Information Management, Fu Jen Catholic University, New Taipei City, 242062, Taiwan, Republic of China; 7Department of Healthcare Administration,College of Healthcare and Management, Asia Eastern University of Science and Technology, New Taipei, 22061, Taiwan, Republic of ChinaCorrespondence: Chi-Jie Lu Fu Jen Catholic University, New Taipei 242062, Taiwan Email 059099@mail.fju.edu.twMing-Shu Chen Asia Eastern University of Science and Technology, TaiwanAsia Eastern University of Science and Technology, No.58, Sec. 2, Sichuan Rd, Pan-Chiao Dist., New Taipei, 22061, TaiwanEmail tree1013@gmail.comPurpose: As global aging progresses, the health management of chronic diseases has become an important issue of concern to governments. Influenced by the aging of its population and improvements in the medical system and healthcare in general, Taiwan’s population of patients with chronic kidney disease (CKD) has tended to grow year by year, including the incidence of high-risk cases that pose major health hazards to the elderly and middle-aged populations.Methods: This study analyzed the annual health screening data for 65,394 people from 2010 to 2015 sourced from the MJ Group – a major health screening center in Taiwan – including data for 18 risk indicators. We used five prediction model analysis methods, namely, logistic regression (LR) analysis, C5.0 decision tree (C5.0) analysis, stochastic gradient boosting (SGB) analysis, multivariate adaptive regression splines (MARS), and eXtreme gradient boosting (XGboost), with estimated glomerular filtration rate (e-GFR) data to determine G3a, G3b & G4 stage CKD risk factors.Results: The LR analysis (AUC=0.848), SGB analysis (AUC=0.855), and XGboost (AUC=0.858) generated similar classification performance levels and all outperformed the C5.0 and MARS methods. The study results showed that in terms of CKD risk factors, blood urea nitrogen (BUN) and uric acid (UA) were identified as the first and second most important indicators in the models of all five analysis methods, and they were also clinically recognized as the major risk factors. The results for systolic blood pressure (SBP), SGPT, SGOT, and LDL were similar to those of a related study. Interestingly, however, socioeconomic status-related education was found to be the third important indicator in all three of the better performing analysis methods, indicating that it is more important than the other risk indicators of this study, which had different levels of importance according to the different methods.Conclusion: The five prediction model methods can provide high and similar classification performance in this study. Based on the results of this study, it is recommended that education as the socioeconomic status should be an important factor for CKD, as high educational level showed a negative and highly significant correlation with CKD. The findings of this study should also be of value for further discussions and follow-up research.Keywords: chronic kidney disease, health screening, machine learning algorithms, risk indicators assessment, education

Objectives: This study aimed to validate the application of the 3 × 2 achievement goal model in sports. Motivations: In order to offer new perspectives on achievement goals, this study explores 3 × 2 achievement goals used in competitive sports, and the prediction of passion and psychological well-being for sports. Methods: The study sample consists of 406 college and university athletes, including 230 males and 176 females. Average age of the subjects was 20.34 years. Average length of years of sports participation was 8.23 years. Data were collected with a questionnaire that incorporated a 3 × 2 achievement goal scale, a sports passion scale, and the Psychological Well-Being Scale. Statistical Methods: Data were analyzed using descriptive statistics for fuzzy data, fuzzy correlation coefficients, and fuzzy regression models. Finding: 1. There was a correlation between every two of task-approach, task-avoidance, self-approach, self-avoidance, other-approach, other-avoidance, harmonious passion, obsessive passion, and psychological well-being. 2. Among college and university athletes, task-approach and self-approach positively influence harmonious passion; task-approach, self-approach, other-approach, and other-avoidance positively influence obsessive passion; task-avoidance negatively influences obsessive passion; task-approach and self-approach positively influence psychological well-being, and task-avoidance negatively influences psychological well-being. Innovations: Use of the 3 × 2 achievement goal scale is applicable to college sportsmen in Taiwan, and the research method uses fuzzy statistical analysis, which breaks through the barriers of traditional psychological survey methods, and will improve the research quality of the sample survey. This study provides new techniques for research on psychological trends in sports. Value: In the future, coaches and athletes should focus on task-approach and self-approach goals in order to enhance the college or university athletes’ harmonious passion for a positive impact on their psychological well-being when they engage in sports through their own free will.

BACKGROUND: To date,no data on the effect of adjuvant whole-breast radiotherapy (WBRT) on oncologic outcomes, such as all-cause death, locoregional recurrence (LRR), and distant metastasis (DM), are available forold (aged ≥80 years) and very old (≥90 years) women with breast invasive ductal carcinoma (IDC) receiving breast-conserving conservative surgery (BCS).PATIENTS AND METHODS: We enrolled old (≥80 yearsold) and very old (≥90 yearsold) women with breast IDC who had received BCS followed by adjuvant WBRT or no adjuvant WBRT. We groupedthem based on adjuvant WBRT status and compared their overall survival (OS), LRR, and DM outcomes. To reduce the effects of potential confounders when comparing all-cause mortality between the groups, propensity score matching was performed.RESULTS:Overall, 752 older women with IDC received BCS followed by adjuvant WBRT, and 752 with IDC received BCS with no adjuvant WBRT.In multivariable Cox regression analysis, the adjusted hazard ratio (aHR) and 95% confidence interval (95% CI) of all-cause death for adjuvant WBRT compared with no adjuvant WBRT in older women with IDC receiving BCS was 0.56 (0.44-0.70). The aHRs (95% CIs) of LRR and DM foradjuvant WBRT were 0.29 (0.19-0.45) and 0.45 (0.32-0.62), respectively, compared with no adjuvant WBRT.CONCLUSION: Adjuvant WBRT was associated with decreases in all-cause death, LRR, and DM in old (aged ≥80 years) and very old (aged ≥90 years) women with IDC compared with no adjuvant WBRT.Condensed Abstract: This study is the first to examine the effect of adjuvant whole-breast radiotherapy (WBRT) on oncologic outcomes such as all-cause death, locoregional recurrence (LRR), and distant metastasis (DM) in old (aged ≥80 years) and very old (aged ≥90 years) women with breast invasive ductal carcinoma (IDC) receiving breast-conserving surgery. After propensity score matching, adjuvant WBRT was associated with decreases in all-cause death, LRR, and DM in old and very old women with IDC compared with no use of adjuvant WBRT.

BACKGROUND To date, no data on the effect of adjuvant whole breast radiotherapy (WBRT) on oncologic outcomes, such as all-cause death, locoregional recurrence (LRR), and distant metastasis (DM), are available in women with left-side breast intraductal carcinoma (IDC) and heart failure with reduced ejection fraction (HFrEF). PATIENTS AND METHODS : We enrolled 294 women with left-breast IDC at clinical stages IA–IIIC and HFrEF receiving breast-conserving surgery (BCS) followed by adjuvant WBRT or non-adjuvant WBRT. We categorized them into two groups based on their adjuvant WBRT status and compared their overall survival (OS), LRR, and DM outcomes. We calculated the propensity score and applied inverse probability of treatment weighting (IPTW) to create a pseudo-study cohort. Furthermore, we performed a multivariate analysis of the propensity score–weighted population to obtain hazard ratios (HRs). RESULTS In the IPTW-adjusted model, adjuvant WBRT (adjusted HR [aHR]: 0.60; 95% confidence interval [CI]: 0.44–0.94) was a significant independent prognostic factor for all-cause death (P = 0.0424), and the aHR (95% CI) of LRR and DM for adjuvant WBRT was 0.33 (0.24–0.71; P = 0.0017) and 0.37 (0.22–0.63; P = 0.0004), respectively, compared with the no adjuvant WBRT group. The aHR (95% CI) of breast cancer death for adjuvant WBRT was 0.54 (0.44–0.85; P = 0.0201) compared with no adjuvant WBRT group. CONCLUSION Adjuvant WBRT was associated with a decrease in all-cause death, breast cancer death, LRR, and DM in women with left IDC and HFrEF compared with no adjuvant WBRT.

BACKGROUND: To date, no data on the effect of adjuvant whole breast radiotherapy (WBRT) on oncologic outcomes, such as all-cause death, locoregional recurrence (LRR), and distant metastasis (DM), are available in women with left-side breast intraductal carcinoma (IDC) and heart failure with reduced ejection fraction (HFrEF). PATIENTS AND METHODS: We enrolled 294 women with left-breast IDC at clinical stages IA–IIIC and HFrEF receiving breast-conserving surgery (BCS) followed by adjuvant WBRT or non-adjuvant WBRT. We categorized them into two groups based on their adjuvant WBRT status and compared their overall survival (OS), LRR, and DM outcomes. We calculated the propensity score and applied inverse probability of treatment weighting (IPTW) to create a pseudo-study cohort. Furthermore, we performed a multivariate analysis of the propensity score–weighted population to obtain hazard ratios (HRs).RESULTS: In the IPTW-adjusted model, adjuvant WBRT (adjusted HR [aHR]: 0.58; 95% confidence interval [CI]: 0.33–1.00) was a significant independent prognostic factor for all-cause death (P = 0.0494), and the aHR (95% CI) of LRR and DM for adjuvant WBRT was 0.25 (0.10–0.62; P = 0.0028) and 0.29 (0.14–0.60; P = 0.0007), respectively, compared with the nonadjuvant WBRT group. CONCLUSION: Adjuvant WBRT was associated with a decrease in all-cause death, LRR, and DM in women with left IDC and HFrEF compared with nonadjuvant WBRT.

Background To date, no data on the effect of adjuvant postmastectomy radiotherapy (PMRT) on oncologic outcomes, such as all-cause death, locoregional recurrence (LRR), and distant metastasis (DM), are available in women with left-side breast invasive ductal carcinoma (IDC) and heart failure with reduced ejection fraction (HFrEF). Patients and methods We enrolled 646 women with left-breast IDC at clinical stages I–IIIC and HFrEF receiving radical total mastectomy (TM) followed by adjuvant PMRT or non-adjuvant PMRT. We categorized them into two groups based on their adjuvant PMRT status and compared their overall survival (OS), LRR, and DM outcomes. We calculated the propensity score and applied inverse probability of treatment weighting (IPTW) to create a pseudo-study cohort. Furthermore, we performed a multivariate analysis of the propensity score–weighted population to obtain hazard ratios (HRs). Results In the IPTW-adjusted model, adjuvant PMRT (adjusted HR [aHR]: 0.52; 95% confidence interval [CI]: 0.37–0.74) was a significant independent prognostic factor for all-cause death (P = 0.0003), and the aHR (95% CI) of LRR and DM for adjuvant PMRT was 0.90 (0.79–0.96; P = 0.0356) and 0.89 (0.54–1.50; P = 0.6854), respectively, compared with the nonadjuvant PMRT group. Conclusion Adjuvant PMRT was associated with a decrease in all-cause death, and LRR in women with left IDC and HFrEF compared with nonadjuvant PMRT.

Background: Low-dose aspirin (100 mg) is widely used in preventing cardiovascular disease in chronic kidney disease (CKD) because its benefits outweighs the harm, however, its effect on clinical outcomes in patients with predialysis advanced CKD is still unclear. This study aimed to assess the effect of aspirin use on clinical outcomes in such group. Methods: Patients were selected from a nationwide diabetes database from January 2009 to June 2017, and divided into two groups, a case group with aspirin use (n = 3021) and a control group without aspirin use (n = 9063), by propensity score matching with a 1:3 ratio. The Cox regression model was used to estimate the hazard ratio (HR). Moreover, machine learning method feature selection was used to assess the importance of parameters in the clinical outcomes. Results: In a mean follow-up of 1.54 years, aspirin use was associated with higher risk for entering dialysis (HR, 1.15 [95%CI, 1.10–1.21]) and death before entering dialysis (1.46 [1.25–1.71]), which were also supported by feature selection. The renal effect of aspirin use was consistent across patient subgroups. Nonusers and aspirin users did not show a significant difference, except for gastrointestinal bleeding (1.05 [0.96–1.15]), intracranial hemorrhage events (1.23 [0.98–1.55]), or ischemic stroke (1.15 [0.98–1.55]). Conclusions: Patients with predialysis advanced CKD and anemia who received aspirin exhibited higher risk of entering dialysis and death before entering dialysis by 15% and 46%, respectively.

Knee osteoarthritis (OA) affects the quality of life (QOL) and balance control of elderly people; our study explored the balance factors that affected the QOL in patients with knee OA.To determine the balance factors that affected the QOL of patients with knee OA who attended general clinics.A total of 30 healthy controls and 60 patients with mild-to-moderate bilateral knee OA, all aged 55-75 years, were enrolled in our cross-sectional study. All participants were interviewed; the Medical Outcomes Study 36-Item Short-Form Health Survey was used to assess their QOL in eight dimensions, and the Balance Master System was used to evaluate their balance control according to six parameters. Descriptive statistics were used to reduce the data; an independentIn the OA group, significant negative correlations were observed between sway velocity and the physical health component (The sway velocity at the centre of gravity in balance control was a crucial factor for determining the QOL of patients with bilateral knee OA.Sway velocity is a key factor affecting the QOL and may provide a basis to formulate preventive actions and design treatment goals for patients with knee OA.

Developing an effective sports performance analysis process is an attractive issue in sports team management. This study proposed an improved sports outcome prediction process by integrating adaptive weighted features and machine learning algorithms for basketball game score prediction. The feature engineering method is used to construct designed features based on game-lag information and adaptive weighting of variables in the proposed prediction process. These designed features are then applied to the five machine learning methods, including classification and regression trees (CART), random forest (RF), stochastic gradient boosting (SGB), eXtreme gradient boosting (XGBoost), and extreme learning machine (ELM) for constructing effective prediction models. The empirical results from National Basketball Association (NBA) data revealed that the proposed sports outcome prediction process could generate a promising prediction result compared to the competing models without adaptive weighting features. Our results also showed that the machine learning models with four game-lags information and adaptive weighting of power could generate better prediction performance.

Background Knee osteoarthritis (OA) affects the quality of life (QOL) of elderly people, this study examines the demographic characteristics and QOL of patients with knee OA and identifies demographic characteristics that affect the QOL of these patients. Methods In this cross-sectional study, 30 healthy controls and 60 patients with mild-to-moderate bilateral knee OA aged between 55 and 75 years were enrolled. All participants completed a questionnaire containing questions on 10 demographic characteristics and the Medical Outcome Study 36-Item Short-Form Health Survey (SF-36), and their QOL scores in the eight dimensions of the SF-36 were evaluated. Results In the OA group, significant correlations were observed between monthly disposable income and physical and mental health components. Monthly disposable income was found to considerably affect the QOL of patients with knee OA. Conclusion Monthly disposable income is a crucial factor affecting the QOL of patients with bilateral knee OA. The findings of this study may provide a reference for formulating preventive strategies for healthy individuals and for future confirmatory research. Trial registration: This study was approved by the Ethics Committee of Fu Jen Catholic University (FJU-IRB NO: C107179).

Most patients face expensive healthcare management after coronary artery bypass grafting (CABG) surgery, which brings a substantial financial burden to the government. The National Health Insurance Research Database (NHIRD) is a complete database containing over 99% of individuals’ medical information in Taiwan. Our research used the latest data that selected patients who accepted their first CABG surgery between January 2014 and December 2017 (n = 12,945) to predict which factors will affect medical expenses, and built the prediction model using different machine learning algorithms. After analysis, our result showed that the surgical expenditure (X4) and 1-year medical expenditure before the CABG operation (X14), and the number of hemodialysis (X15), were the key factors affecting the 1-year medical expenses of CABG patients after discharge. Furthermore, the XGBoost and SVR methods are both the best predictive models. Thus, our research suggests enhancing the healthcare management for patients with kidney-related diseases to avoid costly complications. We provide helpful information for medical management, which may decrease health insurance burdens in the future.

Research has failed to resolve the dilemma experienced by localized prostate cancer patients who must choose between radical prostatectomy (RP) and external beam radiotherapy (RT). Because the Charlson Comorbidity Index (CCI) is a measurable factor that affects survival events, this research seeks to validate the potential of the CCI to improve the accuracy of various prediction models. Thus, we employed the Cox proportional hazard model and machine learning methods, including random forest (RF) and support vector machine (SVM), to model the data of medical records in the National Health Insurance Research Database (NHIRD). In total, 8581 individuals were enrolled, of whom 4879 had received RP and 3702 had received RT. Patients in the RT group were older and exhibited higher CCI scores and higher incidences of some CCI items. Moderate-to-severe liver disease, dementia, congestive heart failure, chronic pulmonary disease, and cerebrovascular disease all increase the risk of overall death in the Cox hazard model. The CCI-reinforced SVM and RF models are 85.18% and 81.76% accurate, respectively, whereas the SVM and RF models without the use of the CCI are relatively less accurate, at 75.81% and 74.83%, respectively. Therefore, CCI and some of its items are useful predictors of overall and prostate-cancer-specific survival and could constitute valuable features for machine-learning modeling.

Coronary artery bypass surgery grafting (CABG) is a commonly efficient treatment for coronary artery disease patients. Even if we know the underlying disease, and advancing age is related to survival, there is no research using the one year before surgery and operation-associated factors as predicting elements. This research used different machine-learning methods to select the features and predict older adults’ survival (more than 65 years old). This nationwide population-based cohort study used the National Health Insurance Research Database (NHIRD), the largest and most complete dataset in Taiwan. We extracted the data of older patients who had received their first CABG surgery criteria between January 2008 and December 2009 (n = 3728), and we used five different machine-learning methods to select the features and predict survival rates. The results show that, without variable selection, XGBoost had the best predictive ability. Upon selecting XGBoost and adding the CHA2DS score, acute pancreatitis, and acute kidney failure for further predictive analysis, MARS had the best prediction performance, and it only needed 10 variables. This study’s advantages are that it is innovative and useful for clinical decision making, and machine learning could achieve better prediction with fewer variables. If we could predict patients’ survival risk before a CABG operation, early prevention and disease management would be possible.

Background The relationship between sleep duration and physical fitness is one aspect of sleep health. Potential factors associated with sleep duration interfere with physical fitness performance, but the impact trends on physical fitness indicators remain unclear. Methods This study examined associations between sleep duration and physical fitness among young to middle-aged adults in Taiwan. A total of 42,781 Taiwanese adults aged 23–45 participated in the National Physical Fitness Examination Survey 2013 (NPFES-2013) in Taiwan between October 2013 and March 2014. A standardized structural questionnaire was used to record participants’ sleep duration, which was stratified as short ( Results By using analysis of covariance (ANCOVA), after sex grouping and age adjustment, we observed that sleep duration was significantly associated with obesity, functional fitness, and self-perception of health. The sleep duration for low obesity-related values (BMI, WHtR, and WHR) for men was 7–9 h/d, and that for women was 7–8 h/d. Sleeping more than 8 h/d showed poor functional fitness performances (BS and SR). For both sexes, sleep duration of 8–9 h/d was the optimal sleep duration for self-perceptions of health. Conclusions Our research found that there were wide and different associations of sleep duration with physical fitness and self-perception of health among Taiwanese adults aged 23–45, and there were differences in these associated manifestations between men and women. This study could be of great importance in regional public health management in Taiwan, and provide inspirations for clinical research on physical fitness.

The development of the core competence of physicians is related to the practice of medical quality. As the most important field for cultivating the core competence of physicians, how to achieve the construction and evaluation of core competence is an important issue for medical education and management. This study uses the large core competence framework proposed by the ACGME (Accreditation Council for Graduate Medical Education), and use Fuzzy AHP (FAHP) and DEMANTEL method to analyze the weight and priority, and the cause and effect cluster. Study result shows that the FAHP’s importance factor ranking is (1).patient care (C1) (27.83%), (2).medical knowledge (C2) (20.77%), (3).professionalism (C5) (17.93%), (4). Interpersonal and communication skills (C4) (17.41%), (5). practice-based learning and improvement (C3) (15.52%), and (6). systems-based practice (C6) (8.233%). In terms of DEMANTEL, the effect cluster include Patient Care (C1), Professionalism (C5) and Systems-based practice (C6), and the cause cluster includes Medical Knowledge (C2), Practice-based learning and improvement (C3) and Interpersonal and Communication skills (C4). According to finding, the patient care (C1) is the result of attitude, patience, and other five ACGME Core Competence Items. Therefore, the development of emergency physicians’ also needs humanities and ethics training and practice to follows the practice-based learning (C3). This study demonstrates to show on importance factor in emergency physician’s core competencies cultivate. Furthermore, the current findings can serve as a reference for future research in the other specialists physicians cultivate.

The safety and health of homeless people are important social issues. Metabolic syndrome (MetS) is a sub-health-risk phenomenon that has been severely aggravated worldwide in recent years. The purpose of this study was to investigate the prevalence and risk factors of MetS among the homeless in Taipei City, Taiwan. In this study, a convenience sampling was conducted at homeless counseling agencies in Taipei City from April 2018 to September 2018. A total of 297 homeless participants were recruited, from whom clinical indicators and questionnaire information were collected. Through statistical verification, analysis of variance (ANOVA), and logistic regression, we found the following main conclusions for homeless adults in Taipei: (1) The prevalence of MetS was estimated to be 53%, with 50% meeting four or more diagnostic conditions. (2) Dyslipidemia (high-density lipoprotein (HDL) deficiency and elevated triglyceride (TG)) showed the strongest association with the prevalence of MetS, more than 83% of people with HDL deficiency or hypertriglyceridemia had MetS. For the patient groups meeting more MetS diagnostic conditions, the values of high-density lipoprotein cholesterol (HDL-C), TG, and total cholesterol (TC) increased significantly. (3) The deterioration of MetS was significantly related to the high prevalence of hyperlipidemia (HL). (4) The homeless who were divorced, separated or widowed were more likely to suffer from MetS.