Health fitness, physical activity, and quality of life in patients undergoing first chemotherapy for lung cancer: a cross-sectional study

Health fitness, physical activity, and quality of life in patients undergoing first chemotherapy for lung cancer: a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Health fitness, physical activity, and quality of life in patients undergoing first chemotherapy for lung cancer: a cross-sectional study Jiahui Xu, Hui Lu, Tingting Fang, Huihong Wang, Ying Chen, Jianing Hua, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6168386/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract In this study, we examined determinants of health fitness and physical activity levels in 372 patients with lung cancer undergoing their first chemotherapy at a tertiary hospital in Wuxi, China, and their impact on quality of life (QoL). Standardized measures were used to asses body composition, muscular function, cardiorespiratory fitness, and flexibility. Physical activity was measured using the International Physical Activity Questionnaire, and QoL was evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Lung Cancer 43. Higher physical activity levels correlated with better global health but were associated with increased symptom burden and functional limitations. Muscle mass, grip strength, and 6-minute walk distance were positively linked to global health but negatively associated with symptom and functional scales. Females reported higher symptom burdens and lower functional scores. Multivariate analysis identified gender, education, comorbidities, disease stage, and activity levels as key QoL predictors. Improved fitness and physical activity were associated with better QoL. Early identification of patients with low activity and poor fitness can guide tailored interventions to enhance functional capacity and well-being. These findings emphasize the importance of integrating fitness assessments and personalized exercise into lung cancer management to improve treatment outcomes and QoL. Health sciences/Health care/Health services Health sciences/Health care/Quality of life Lung cancer Health fitness Physical activity Quality of life Influencing factors Introduction Lung cancer remains a leading cause of cancer-related mortality worldwide, despite recent advances in treatment that have improved 5-year survival rates 1 – 2 . Over 70% of patients are diagnosed with advanced 3 , inoperable lung cancer, for which chemotherapy is a primary treatment modality. However, chemotherapy often induces side effects such as fatigue, muscle weakness, and dyspnea, which can significantly impair patients' physical activity levels and overall quality of life (QoL). Furthermore, patients with lung cancer experience a more severe symptom burden than other cancers 4 . Studies have shown that physical activity can mitigate the toxicity of anti-tumor therapies 5 , improve patient tolerance, and enhance the efficacy of traditional treatments. The American College of Sports Medicine and the American Cancer Society 6 – 7 recommend that patients with cancer engage in at least 150 min of moderate-intensity or 75 min of high-intensity physical activity per week, along with resistance training twice weekly. Despite these guidelines, a significant proportion of patients with lung cancer undergoing chemotherapy fail to meet these recommendations, with 74% reporting insufficient physical activity levels 8 – 10 . Physical fitness is an indicator of the overall assessment of physical functioning during daily physical activities. It is an important component of QoL, and its recovery contributes to the improvement of functional status and social activities in patients with tumor 11 . Key assessment indicators include body composition, cardiorespiratory fitness, muscular function, and flexibility. Patients with lung cancer may experience a decline in cardiopulmonary function and metabolic disturbances due to the disease itself. Furthermore, tumor treatments and a lack of physical activity can lead to impaired muscle function, subsequently affecting overall health and fitness levels 12 – 13 . Individuals who transition from a sedentary lifestyle to achieving optimal physical fitness can reduce their mortality rate by 44%. In contrast, patients with poor physical fitness who do not implement any intervention measures face the highest mortality rates 14 . The predominant demographic of patients with lung cancer consists of individuals who are inactive or lead sedentary lifestyles. Assessment of physical function in patients receiving chemotherapy for malignant lymphoma indicated that while right grip strength diminished post-chemotherapy, other physical performance metrics (left grip strength, bilateral knee extension, and the 6-minute walk test) exhibited no significant changes. This observation suggests that exercise interventions could play a crucial role in mitigating the decline of specific physical function parameters during chemotherapy 15 . Similarly, childhood cancer survivors experience significant setbacks in physical abilities and cardiorespiratory fitness compared with children without a history of cancer. Those who survived central nervous system tumors during childhood showed significant decline in fitness and overall QoL, particularly in the five years leading up to and following their treatment 16 . In patients with breast cancer and hematologic malignancies, exercise programs focusing on muscle strength, cardiorespiratory fitness, and body composition have been shown to significantly improve QoL. These programs help patients navigate treatment and recovery more effectively 17 – 18 . In this study, we aimed to assess the health and fitness status of oncology patients and identify determinants of their physical activity levels. The goal was to establish a scientific foundation for developing personalized exercise plans tailored to these patients. By exploring how such programs can enhance QoL, we may enhance the overall survival experience for patients with cancer and increase their life satisfaction and well-being. The primary aim of this research was to examine the determinants affecting health fitness and physical activity levels among patients undergoing chemotherapy for lung cancer, with the goal of establishing a foundation for developing personalized exercise therapy programs in the future. Furthermore, we sought to assess the impact of health fitness and physical activity levels on their QoL, along with the disease-related and socio-demographic factors associated with QoL outcomes. Methods Study design and participants In this cross-sectional study, we sampled patients with lung cancer undergoing chemotherapy from the oncology treatment center of a tertiary general hospital in Wuxi, China. Patients with lung cancer who started their first round of chemotherapy between June 2024 and December 2024 were selected using convenience sampling. Inclusion criteria included patients who were 18 years of age and older, had a diagnosis of primary lung cancer, and were about to start their first round of chemotherapy. In addition, they had to be in good health, with normal vital signs, and willing to cooperate with the health assessments during the study. Exclusion criteria included patients with severe physical, cognitive, or speech impairments. We obtained approval from the Ethics Committee (approval number: LS2023086) and ensured registration in the Chinese Clinical Trial Registry (registration number: ChiCTR2400081003). Prior to participation, each participant provided written informed consent form. Measures Socio-Demographic and Clinical Data Socio-demographic information, including sex, age, education level, residence, marital status, primary caregiver, household income, medical payment method, and employment status, was collected using a custom questionnaire. Clinical data, including disease stage, surgical history, hemoglobin concentration, white blood cell count, platelet count, ultrasensitive C-reactive protein, and albumin levels, were extracted from medical records. Health Fitness Assessment Techniques All measurement devices were standardized instruments and equipment mandated for the national physical fitness evaluation in China. (1) Body composition : Evaluated using metrics such as body weight, body mass index (BMI), and muscle mass. We utilized bioelectrical impedance analysis (BIA) technology from the TANITA body composition analyzer to gather data on body composition (Model Number: MC-780MA), manufactured by Dongguan Bida Health Equipment, Japan. (2) Muscular function : Assessed through upper limb muscle strength and lower limb muscle strength. 1) Upper limb muscle strength : Grip strength was conducted using an electronic grip strength meter (EH201R) in the ward. Patients were instructed to stand with their arm relaxed and hanging naturally, gripping the device firmly with their fingers positioned snugly on the handle. During the assessment, the grip strength gauge was maintained at a specified distance from the body, and patients were prohibited from bending their arm, waist, or moving their feet while applying force. A rest period of 2 min was allowed between each of the two tests, with the highest score recorded for evaluation. 2) Lower limb muscle strength : Evaluated using a five-repitition sit-to-stand test. A 40 cm high back chair and a timer were used. Patients sat with legs shoulder-width apart and arms crossed. Upon the tester's 'start' command, patients performed five 'stand up-sit down' actions as quickly as possible. The timer stopped after the fifth repetition. (3) Cardiorespiratory fitness : Assessed using the 6-min walking distance test. Patients stood at the starting point of a 50-meter course to prepare. Upon the tester’s ‘start’ command, patients began walking. When the ‘stop’ command was given, patients remained in place, and the tester measured and recorded the distance in meters (m units). (4) Flexibility : Hip flexibility was used for assessment, measured using a seated forward flexion test. Patients sat on a cushion with legs together and knees straight. The patients slowly pushed a block forward with their longest finger along a scale. When it was impossible to continue to push forward, the tester measured the distance in cm, using the toes as the starting point. International Physical Activity Questionnaire(IPAQ) The International Physical Activity Questionnaire (IPAQ) is a prominent tool utilized globally for assessing physical activity levels, recognized for its validity. In this study, we used the Chinese version of IPAQ, translated and adapted by Wang Jie 19 . It comprises 27 items that prompt respondents to indicate the frequency and duration of daily exercise, as well as to detail their physical activity over the past week across various domains, including leisure and recreation, household tasks, transportation methods, and occupational activities 20 . The duration (in minutes) spent at each intensity of physical activity was multiplied by its corresponding metabolic equivalent of task (MET) value (walking = 3.3, moderate intensity = 4, high intensity = 8). The MET-minutes from each intensity level were aggregated to calculate the total physical activity energy expenditure (in MET-minutes) for the previous week. A weekly total physical activity level of ≥ 1500 MET-min was classified as high; a level between 600 and 1500 MET-min was considered moderate; and a level of < 600 MET-min was deemed low 21 . European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 43(EORTC QLQ-LC43) This scale was developed by the European Organisation for Research and Treatment of Cancer (EORTC) and consists of the core QoL scale for oncology patients, EORTC QLQ-C30, and the patient-specific subscale for lung cancer, EORTC QLQ-LC13. In this study, we used the Chinese version of the EORTC QLQ-LC43, translated and adapted by Wan Chonghua 22 . The EORTC QLQ-C30 instrument comprises 30 items across five domains: physical, emotional, role functioning, cognitive, and social, with a Cronbach's alpha of 0.83. The EORTC QLQ-LC13 tool includes 13 items specifically addressing the symptoms and side effects associated with lung cancer. The Cronbach's alpha coefficients for both scales exceed 0.70, indicating their reliability and suitability for use with Chinese patients with lung cancer 23 . Statistical analysis We utilized Excel 2010 for data entry and aggregation, while statistical analysis was performed using SPSS 26.0. To characterize the demographic, sociological attributes, and disease-related factors (such as disease stage, total white blood cell count, platelet count, ultrasensitive C-reactive protein, and albumin levels) of the respondents, categorical data were represented as rates or proportions. For continuous data, mean ± standard deviation was used for measures conforming to a normal distribution, and interquartile range (IQR: P 25 -P 75 ) was used for non-normally distributed data. Determinants affecting health fitness status, physical activity levels, and QoL among patients with lung cancer were analyzed using independent samples t-tests, analysis of variance, and non-parametric methods (Mann-Whitney U-test and Kruskal-Wallis H-test). Non-parametric tests were specifically employed for data exhibiting heterogeneity. Multivariate linear regression was used to perform a multifactorial analysis of the determinants affecting physical activity levels and QoL among patients with lung cancer. Two-tailed tests were conducted, with a p-value of 0.05 set as the significance level. Results Participant characteristics Out of 438 eligible patients, 405 were included in the study (response rate: 92.47%). Among these, 33 were excluded due to incomplete responses, resulting in a final sample size of 372 patients. The mean age of participants was 64.1 years, with 77.96% being male. The most frequent cancer types were adenocarcinoma (48.66%) and squamous cell carcinoma (23.12%). The majority of patients (63.44%) had a moderate level of physical activity. Unifactorial analysis of factors affecting patients' quality of life Univariate analysis revealed statistically significant associations between primary caregiver status, smoking status, physical exercise level, and EORTC QLQ-LC43 scores (all P < 0.05). Among the covariates analyzed, age demonstrated a significant influence on EORTC QLQ-LC13 scores ( P = 0.005), with younger patients (18-45years) exhibiting a greater symptom burden than older cohorts. Gender-specific analysis indicated that female patients scored lower on global health status and functioning scales but reported higher symptom scale scores relative to male counterparts ( P = 0.001). Educational attainment emerged as a significant factor, with patients holding bachelor's degrees or higher qualifications demonstrating superior functional outcomes ( P = 0.011), albeit with increased symptom burden and lung cancer-specific symptoms. While no significant differences were observed in global health status, functional scales, or symptom scales ( P > 0.05), residential status significantly impacted EORTC QLQ-LC13 scores ( P < 0.001), with rural residents reporting elevated symptom burden compared with urban and town dwellers. Socioeconomic analysis revealed that income level significantly correlated with global health status ( P < 0.001), with higher income brackets associated with improved global health outcomes. However, no significant associations were found with functional scales, symptom scales, or EORTC QLQ-LC13 scores ( P > 0.05). Multiple factors, including medical payment method, employment status, occupational history, alcohol consumption patterns, comorbidities, and living arrangements, demonstrated significant effects across functional scales ( P < 0.05), symptom scales ( P < 0.05), and EORTC QLQ-LC13 scores ( P < 0.05). Clinical characteristics, particularly diagnosis type and lung cancer staging, significantly influenced global health status ( P 0.05), suggesting minimal impact on symptom reporting or functional status assessment within this patient population. (Table 1). Table 1. Influencing factors of mean scores on scales and items of EORTC QLQ⁃C30 and EORTCQLQ⁃LC13 for patients ( N = 372 ). Variables Global Health Status Functional Scales Symptom Scales EORTC QLQ⁃LC13 Age 18~ 66.67(58.33,83.33) 35.33(21.33,40.33) 51.85(41.98,57.41) 14.44(4.44, 20.00) 45~ 66.67(50.00,83.33) 35.67(25.75,56.33) 45.06(38.73,53.70) 10.00(5.56, 14.16) 60~ 66.67(50.00,75.00) 35.00(25.67,51.33) 49.08(40.74,58.02) 12.22(7.78, 18.89) ≥ 75 58.33(41.67,75.00) 39.00(32.33,51.33) 52.47(43.21,59.26) 8.89(6.67, 24.44) Test 1) 5.227 1.035 1.642 12.752 P value 0.156 0.793 0.650 0.005 Gender Male 66.67(50.00,83.33) 33.67(23.00,46.33) 46.30(39.97,57.41) 11.11(6.67, 17.78) Female 50.00(39.59,66.67) 43.67(32.00,60.25) 53.70(45.06,66.05) 11.11(7.78, 18.89) Test 2) −2.986 −4.259 −3.258 −0.321 P value 0.003 < 0.001 0.001 0.748 Education Level Primary school or below 66.67(43.75,75.00) 39.33(26.00,52.34) 51.85(40.12,59.26) 14.44(8.06, 24.44) Junior high school 66.67(50.00,83.33) 35.33(25.67,51.67) 45.68(40.74,56.49) 10.00(6.67, 16.12) Senior high school 66.67(50.00,83.33) 31.33(26.00,34.00) 46.30(39.51,53.70) 7.78(3.33, 14.44) College 62.50(58.33,83.33) 35.33(21.67,55.58) 54.32(40.13,61.57) 17.78(11.11, 20.00) Bachelor's degree or above 33.33(33.33,91.67) 95.33(35.67,95.33) 109.88(45.68,109.88) 56.67(5.56, 56.67) Test 1) 1.905 13.014 10.471 21.152 P value 0.753 0.011 0.033 < 0.001 Residence Urban 66.67(50.00,83.33) 35.00(24.67,51.59) 46.61(40.74,58.02) 11.11(6.67, 16.67) Town 66.67(50.00,75.00) 37.50(25.92,51.67) 49.08(40.12,55.71) 10.00(5.56, 16.67) Rural 66.67(41.67,75.00) 37.33(28.67,52.67) 52.47(41.98,59.26) 16.67(10.00, 24.44) Other provinces 66.67(66.67,83.33) 40.33(27.67,40.33) 43.83(43.83,52.47) 2.22(2.22, 4.44) Test 1) 3.755 1.972 3.506 31.238 P value 0.289 0.578 0.320 < 0.001 Marital Status Unmarried 75.00(58.33,83.33) 29.33(27.67,35.33) 50.00(41.98,52.47) 4.44(4.44, 10.00) Married 66.67(50.00,75.00) 35.33(26.00,51.33) 49.38(40.74,57.72) 11.11(7.78, 17.78) Divorced 66.67(33.33,100.00) 40.33(14.67,86.67) 43.83(30.86,77.78) 4.44(2.22, 27.78) Widowed 50.00(33.33,87.50) 33.00(18.92,86.67) 53.70(35.65,77.78) 10.00(1.67, 27.78) Test 1) 2.462 2.015 0.309 6.200 P value 0.482 0.569 0.958 0.102 Primary Caregiver Spouse 66.67(50.00,75.00) 35.33(25.67,54.33) 51.85(40.74,58.02) 12.22(7.78, 17.78) Children 66.67(50.00,66.67) 38.33(27.67,51.33) 49.38(43.21,58.02) 11.11(6.67, 20.00) Parents 100.00(83.33,100.00) 6.67(6.67,27.33) 29.63(29.63,37.04) 0.00(0.00, 5.56) Siblings 83.33(83.33,83.33) 27.67(27.67,27.67) 52.47(52.47,52.47) 4.44(4.44, 4.44) None 58.33(56.25,64.58) 35.33(31.75,39.00) 47.53(40.44,56.02) 10.00(9.72, 11.39) Test 1) 17.120 12.728 14.324 17.154 P value 0.002 0.013 0.006 0.002 Monthly Household Income 5K 66.67(58.33,83.33) 32.67(24.67,48.33) 48.15(38.58,61.42) 11.11(3.33, 17.78) Test 1) 16.563 3.362 4.528 4.183 P value < 0.001 0.186 0.104 0.124 Medical Payment Method Self-pay 66.67(50.00,83.33) 27.67(26.00,38.33) 52.47(36.42,55.56) 4.44(1.11, 14.44) Urban Resident Medical Insurance 66.67(50.00,75.00) 33.83(25.25,42.33) 45.06(40.12,52.16) 10.00(6.67, 16.67) Employee Medical Insurance 66.67(41.67,83.33) 39.33(26.00,52.34) 53.70(40.74,66.05) 12.22(7.78, 18.89) Other 66.67(50.00,83.33) 37.67(27.33,51.33) 52.47(43.21,58.02) 13.33(8.89, 25.00) Test 1) 0.536 7.092 13.810 9.976 P value 0.911 0.069 0.003 0.019 Employment Status Currently employed 58.33(33.33,83.33) 26.33(21.33,51.67) 43.83(35.80,57.41) 7.78(1.11, 14.44) Retired 66.67(50.00,75.00) 35.00(25.67,51.00) 46.91(40.74,57.41) 11.11(7.78, 17.78) Unemployed 41.67(16.67,70.84) 37.33(32.75,69.00) 53.09(50.00,70.99) 20.00(10.00, 27.78) Farming 66.67(50.00,66.67) 39.00(26.59,52.67) 53.09(43.21,60.49) 13.33(8.89, 17.50) Test 1) 6.380 9.996 10.803 19.774 P value 0.095 0.019 0.013 < 0.001 Occupation or Pre-retirement Occupation National,Party,Enterprise Leaders 66.67(41.67,75.00) 38.67(30.00,67.67) 51.85(44.44,74.69) 13.33(7.78, 24.45) Professionals 66.67(50.00,66.67) 39.33(27.75,54.67) 45.68(40.74,59.87) 11.11(7.78, 16.67) Production,Transportation Workers 66.67(50.00,83.33) 35.00(16.00,54.33) 45.06(35.80,53.70) 8.89(7.78, 20.00) Commercial, Service Workers 50.00(45.83,93.75) 31.00(14.92,35.33) 46.91(29.63,53.24) 11.11(2.50, 16.67) Agriculture,Forestry,Fishery Workers 58.33(50.00,83.33) 44.33(33.67,56.33) 52.47(39.51,59.88) 13.33(6.12, 19.17) Clerical Workers 83.33(66.67,83.33) 23.00(22.67,33.33) 41.98(35.80,50.00) 10.00(4.44, 11.11) Military 66.67(66.67,66.67) 62.67(62.67,62.67) 72.22(72.22,72.22) 33.33(33.33, 33.33) Other 50.00(50.00,79.17) 29.33(20.67,33.67) 53.70(43.83,54.32) 13.33(5.56, 18.34) Unemployed 54.17(33.33,66.67) 32.17(25.25,56.50) 49.08(41.83,62.19) 11.11(8.34, 18.06) Test 1) 13.330 50.012 23.326 16.109 P value 0.101 < 0.001 0.003 0.041 Alcohol Consumption Yes 66.67(43.75,75.00) 40.33(30.00,60.25) 53.70(40.90,66.05) 13.33(10.00, 25.56) No 66.67(50.00,75.00) 35.00(25.67,48.33) 46.91(40.74,56.02) 11.11(5.84, 17.50) Test 2) −0.462 −2.638 −2.486 −2.862 P value 0.644 0.008 0.013 0.004 Smoking Yes 58.33(50.00,66.67) 39.00(30.25,56.42) 52.16(40.74,61.27) 13.33(7.78, 20.00) No 66.67(50.00,83.33) 32.17(23.00,45.67) 46.91(40.12,53.70) 10.00(5.56, 16.67) Test 2) −2.448 −4.289 −2.946 −3.303 P value 0.014 < 0.001 0.003 0.001 Comorbidities Yes 66.67(50.00,75.00) 38.50(28.67,55.92) 51.85(41.52,60.34) 13.33(7.78, 19.72) No 66.67(50.00,83.33) 31.33(22.75,46.33) 45.68(39.51,54.32) 10.00(5.56, 16.67) Test 2) −1.056 −3.255 −2.730 −3.164 P value 0.291 0.001 0.006 0.002 Living Arrangement Living with spouse 66.67(50.00,83.33) 35.33(23.00,48.33) 45.68(39.51,56.79) 11.11(7.78, 18.89) Living with children 58.33(50.00,66.67) 38.33(27.67,54.67) 51.85(43.21,60.19) 11.11(7.23, 17.78) Living alone 50.00(50.00,56.25) 30.50(25.67,41.09) 53.70(44.91,54.63) 7.78(5.56, 10.00) Test 1) 5.725 2.620 6.453 3.862 P value 0.057 0.270 0.040 0.145 Disease Stage Stage I 75.00(66.67,85.42) 35.67(15.00,42.33) 41.36(39.51,45.68) 7.23(0.00, 20.00) Stage II 75.00(54.17,83.33) 23.34(22.67,40.25) 37.66(35.80,52.78) 10.56(10.00, 11.11) Stage III 66.67(50.00,83.33) 31.33(23.00,48.33) 48.15(40.12,57.41) 10.00(6.67, 16.67) Stage IV 58.33(50.00,75.00) 38.33(28.67,53.42) 51.85(43.21,59.42) 12.22(7.78, 18.06) Test 1) 11.058 12.751 10.975 2.315 P value 0.011 0.005 0.012 0.510 Surgery Yes 62.50(50.00,83.33) 35.33(22.75,50.58) 51.85(39.51,58.95) 11.11(7.78, 16.67) No 66.67(50.00,75.00) 36.00(27.67,52.17) 47.84(40.90,57.41) 12.22(6.67, 18.89) Test 2) −1.547 −1.312 −0.125 −1.161 P value 0.122 0.189 0.901 0.246 Diagnosis Large Cell Neuroendocrine Carcinoma 66.67(58.33,75.00) 35.33(26.75,51.42) 48.15(38.89,58.18) 10.00(6.67, 12.22) Squamous Cell Carcinoma 66.67(50.00,83.33) 30.00(22.92,40.33) 45.68(40.12,55.87) 10.56(5.56, 14.44) Adenocarcinoma 58.33(41.67,79.17) 38.67(26.33,55.84) 51.85(39.51,60.49) 11.11(6.67, 18.89) Adenosquamous Carcinoma 50.00(16.67,66.67) 33.00(30.00,56.33) 59.26(45.68,76.54) 24.44(5.56, 24.44) Small Cell Lung Cancer 66.67(50.00,66.67) 36.00(29.08,51.33) 50.00(43.21,57.41) 13.89(8.89, 17.78) Test 1) 17.532 8.186 5.711 12.257 P value 0.002 0.085 0.222 0.016 Physical Activity Level High 79.17(50.00,83.33) 23.00(19.83,33.25) 40.12(35.80,52.00) 10.00(4.44, 12.22) Moderate 66.67(50.00,75.00) 37.33(29.33,53.42) 51.85(43.21,61.11) 12.78(7.78, 18.89) Low 50.00(41.67,58.33) 52.17(42.33,60.25) 53.09(43.83,58.49) 14.44(10.28, 25.28) Test 1) 31.573 82.037 48.058 21.346 P value < 0.001 < 0.001 < 0.001 < 0.001 Signifcant values ( P < 0.05) are marked in bold. 1)Kruskal Wallis Test ; 2) Mann-Whitney U Test . Quality of life outcomes The QLQ-C30 scale had the lowest score of 35.33 (IQR: 25.67, 51.33) for the functioning domain and the highest score of 66.67 (IQR: 50, 75) for global health status. Dyspnea, coughing, and alopecia symptoms scored the highest for each domain of the QLQ-LC13, with scores of 33.33 (IQR: 11.11, 44.44), 33.33 (IQR: 0.00, 33.33), and 33.33 (IQR: 0.00, 33.33) scores, respectively, as shown in Table 2 . Table 2 Scores of Quality of Life Domains in 372 Lung Cancer Patients Undergoing First Chemotherapy. EORTC QLQ-C30 Score EORTC QLQ-LC13 Score Global Health Status 66.67(50,75) Dyspnoea 33.33(11.11,44.44) Functional Scales 35.33(25.67,51.33) Coughing 33.33(0.00,33.33) Symptom Scales 49.69(40.74,58.02) Haemoptysis 0.00(0.00,0.00) Sore mouth 0.00(0.00,0.00) Dysphagia 0.00(0.00,0.00) Peripheral neutopathy 0.00(0.00,0.00) Alopecia 33.33(0.00,33.33) Pain in chest 0.00(0.00,33.33) Pain in arm or shoulder 0.00(0.00,0.00) Pain in other parts 0.00(0.00,0.00) Status of patients' health, fitness, and physical activity levels Patients with lung cancer receiving chemotherapy for the first time had a BMI score of 23.51 (IQR: 21.32, 24.97), a muscle mass score of 27.40 (IQR: 21.43, 34.90), a grip strength score of 20.10 (IQR: 16.60, 24.98), a 5-repitition sit-to-stand test score of 12.40 (IQR: 9.78, 16.00), a 6-min walk distance score of 326.00 (IQR: 280.00, 381.50), and a seated forward bend distance score of 26.50 (IQR: 20.00, 37.00). The overall physical activity level of this group was low to moderate, with 90 patients (24.19%) at a high physical activity level, 236 (63.44%) at a moderate physical activity level, and 46 (12.37%) at a low physical activity level. Correlation analysis of the quality of life of patients Analysis of QoL correlations in 372 patients with lung cancer undergoing chemotherapy for the first time revealed an important and complex relationship between health fitness measures and physical activity levels. The correlation analysis revealed distinct patterns between physical fitness measures and health-related QoL (HRQoL) outcomes. Muscle mass demonstrated a weak yet statistically significant positive association with Global Health Status (r = 0.110, P < 0.05), while exhibiting moderate inverse relationships with both Functional Scales (r = -0.368, P < 0.001) and Symptom Scales (r = -0.183, P < 0.001). Grip strength exhibited positive correlations with Global Health Status (r = 0.260, P < 0.001) and negative correlations with Functional Scales (r = -0.246, P < 0.001) and Symptom Scales (r = -0.184, P < 0.001). Notably, the 6-min walk distance showed a positive correlation with Global Health Status (r = 0.263, P < 0.001) and negative correlations with both Functional Scales (r = -0.408, P < 0.001) and Symptom Scales (r = -0.457, P < 0.001). Physical activity levels demonstrated a significant pattern, with positive correlations with Global Health Status (r = 0.291, P < 0.001) alongside negative correlations with Functional Scales and Symptom Scales (r = -0.407 and − 0.287, respectively; all P 0.05), indicating limited relevance to HRQoL outcomes in this population. These findings collectively suggest that while enhanced health fitness measures and activity levels are associated with improved global health perceptions, they may simultaneously correlate with compromised functional capacity and increased symptom burden. This highlights the complex interplay between physical fitness parameters and QoL outcomes. For further details, refer to Table S1 . Multiple linear regression analysis of factors influencing patients' quality of life Influencing factors with statistically significant differences in univariate analyses of variance, along with age, were included as independent variables, while scale scores were included as dependent variables in multiple linear regression analyses. The influencing factors of global health status in the QLQ-C30 scale included gender, education level, primary caregiver, employment status, smoking status, comorbidities, living arrangement, disease stage, physical activity level, and 6-min walk distance ( P < 0.05). Female patients had better functional scales (B = 11.405, P < 0.001). Patients with employee medical insurance (B = 7.307, P = 0.002) and other payment methods (B = 5.487, P = 0.042) also had better functional scales. The absence of comorbidities was associated with better functional scales (B = 10.251, P < 0.001). Patients in Stage II had slightly lower functional scales (B = -7.674, P = 0.038). Higher physical activity levels were associated with better functional scales (B = 11.066, P = 0.013), while lower muscle mass was associated with worse functional scales (B = -0.377, P = 0.002). Multivariate analysis identified several significant predictors of symptom burden (all P < 0.05) in chemotherapy-naïve patients with lung cancer, including sex, educational attainment, monthly household income, primary caregiver status, disease stage, comorbidity index, physical activity level, 6-min walk distance and seated forward bend test performance. The EORTC QLQ-LC13 scores demonstrated significant associations with multiple clinical and demographic variables, including chronological age, educational attainment, primary caregiver status, occupational history (including pre-retirement occupation), and diagnostic characteristics (all P < 0.05). Only statistically significant factors are listed in the table. (Table 3). Table 3. Multivariate regression analysis results on the quality of life in patients ( N = 372 ). Variables B Exp(B) 95%CI P value Global Health Status Gender (Female) −17.173 −0.357 (−21.769,−12.577) < 0.001** Education Level Primary school or below 6.922 0.151 (2.137, 11.707) 0.005* Senior high school 12.61 0.195 (5.911, 19.308) < 0.001** College 25.977 0.192 (12.446, 39.507) < 0.001** Primary Caregiver Children −6.965 −0.138 (−11.885,−2.046) 0.006* Siblings −29.122 −0.254 (−40.153,−18.092) < 0.001** None −26.474 −0.292 (−35.236,−17.712) < 0.001** Employment Status Unemployed −12.586 −0.188 (−19.704,−5.467) 0.001* Farming −7.307 −0.165 (−12.042,−2.573) 0.003* Smoking (No) 7.515 0.172 (3.114, 11.916) 0.001* Comorbidities (No) 11.814 0.251 (7.146, 16.481) < 0.001** Living Arrangement Living with children −4.965 −0.110 (−9.578,−0.352) 0.035* Disease Stage Stage I 34.202 0.534 (28.384, 40.019) < 0.001** Stage II 24.77 0.363 (18.650, 30.891) < 0.001** Physical Activity Level High 16.707 0.184 (7.784, 25.630) < 0.001** Low −12.693 −0.290 (−17.004,−8.383) < 0.001** 6-minute Walk Distance 0.041 0.182 (0.018, 0.064) < 0.001** Functional Scales Gender (Female) 11.405 0.257 (7.022, 15.788) < 0.001** Medical Payment Method Employee Medical Insurance 7.307 0.174 (2.600, 12.014) 0.002* Other 5.487 0.116 (0.193, 10.781) 0.042* Comorbidities (No) 10.251 0.236 (5.932, 14.570) < 0.001** Disease Stage (Stage II ) −7.674 −0.122 (−14.924,−0.425) 0.038* Physical Activity Level (High) 11.066 0.132 (2.310, 19.823) 0.013* Muscle Mass −0.377 −0.17 (−0.611,−0.144) 0.002* Symptom Scales Gender (Female) 7.311 0.193 (3.521, 11.101) < 0.001** Education Level Senior high school −5.861 −0.116 (−11.246,−0.477) 0.033* College −12.787 −0.121 (−23.664,−1.911) 0.021* Primary Caregiver (None) 9.344 0.131 (2.011, 16.677) 0.013* Monthly Household Income (<1K) 5.765 0.120 (0.760, 10.769) 0.024* Smoking (No) −4.266 −0.124 (−7.747,−0.785) 0.016* Comorbidities (No) −7.844 −0.212 (−11.544,−4.145) < 0.001** Disease Stage Stage I −8.81 −0.175 (−14.603,−3.018) 0.003* Stage II −7.758 −0.145 (−13.853,−1.663) 0.013* Physical Activity Level High −8.337 −0.117 (−15.796,−0.879) 0.029* Low 3.869 0.112 (0.266, 7.472) 0.035* 6-minute Walk Distance −0.033 −0.182 (−0.051,−0.015) < 0.001** Sitting Forward Bend Distance −0.197 −0.117 (−0.366,−0.028) 0.022* EORTC QLQ⁃LC13 Age 18~ −9.845 −0.101 (−19.634,−0.056) 0.049* 45~ −8.488 −0.156 (−14.018,−2.958) 0.003* ≥ 75 10.985 0.169 (4.425, 17.544) 0.001* Education Level (College) −14.035 −0.105 (−27.771,−0.299) 0.045* Primary Caregiver (Children) 6.847 0.138 (1.668, 12.025) 0.010* Occupation or Pre-retirement Occupation (Military) 46.201 0.111 (3.594, 88.808) 0.034* Diagnosis (Adenosquamous Carcinoma) 12.968 0.118 (1.610, 24.325) 0.025* * P < 0.05; ** P < 0.001 Discussion The unifactorial analysis revealed several significant associations between demographic, socioeconomic, and clinical factors and the QoL of patients with lung cancer, as measured by the EORTC QLQ-C30 and QLQ-LC13 scales. Age emerged as a critical determinant, with younger patients (18–45 years) reporting a higher symptom burden compared with older cohorts ( P = 0.005). This finding aligns with that of previous studies suggesting that younger patients may experience more aggressive disease progression or heightened psychological distress, contributing to increased symptom severity. Epidemiological investigations consistently demonstrate a significant age-dependent disparity in psychological adaptation to illness 24 – 26 , with older patients exhibiting greater emotional resilience and lower disease-related distress scores compared with their younger counterparts. This phenomenon may be attributed to the differential psychosocial burden distribution, wherein younger patients frequently encounter substantial occupational and familial obligations. Gender-specific differences were also notable, with female patients scoring lower on global health status and functioning scales but reporting higher symptom scale scores than their male counterparts ( P = 0.001). This finding was also reported by Yifan et al. 27 . This disparity may be attributed to gender-related variations in symptom perception and reporting, as well as potential differences in coping mechanisms. Educational attainment significantly influenced functional outcomes, with patients holding bachelor's degrees or higher qualifications demonstrating superior functional scales ( P = 0.011). However, this group also reported increased symptom burden, possibly due to greater awareness of their condition or higher expectations regarding health outcomes 28 . Residential status further impacted QoL, with rural residents experiencing elevated symptom burden compared to urban and town dwellers ( P < 0.001). This could be linked to limited access to healthcare resources and delayed diagnosis in rural areas, exacerbating symptom severity. Socioeconomic factors, particularly income level, were significantly associated with global health status ( P < 0.001), with higher income brackets correlating with improved health outcomes. This finding underscores the role of economic stability in accessing timely and effective medical care, which can significantly influence QoL. Furthermore, clinical characteristics such as disease stage and diagnosis type significantly impacted global health status ( P < 0.05), highlighting the importance of early detection and tailored treatment strategies in improving patient outcomes. The QLQ-C30 and QLQ-LC13 scales revealed that global health status was relatively higher than functional and symptom scales, with dyspnea, coughing, and alopecia being the most prominent symptoms. Contrary to the observations of Yifan et al. 27 , their study found that chest pain was more pronounced in patients hospitalized after lung cancer surgery. This difference could be attributed to distinct characteristics of the population they studied, which included patients who experienced more pronounced postoperative pain in the first five days after lung cancer surgery. These findings suggests that while patients may perceive their overall health status as moderately good, they continue to experience significant functional limitations and symptom burden, particularly in domains related to respiratory and physical functioning. This pathophysiological phenomenon is primarily attributable to the tumor-mediated destruction of alveolar architecture and bronchial obstruction, which collectively contribute to impaired pulmonary function, manifested as compromised gas exchange efficiency and restricted airflow dynamics 29 . This study highlights the health fitness, and QoL challenges faced by patients with lung cancer undergoing first-time chemotherapy. While most patients had a normal BMI, declines in muscle mass and grip strength suggest early sarcopenia and fatigue, consistent with prior findings 30 – 31 . Physical activity levels were predominantly low to moderate (87.81% combined), underscoring the need for interventions to improve activity levels and mitigate chemotherapy’s adverse effects. QoL assessments revealed moderate global health status but significant functional impairment, aligning with the physical and emotional burden of the treatment 32 . Dyspnea and coughing were the most prevalent symptoms, reflecting common respiratory complications. Alopecia and chest pain further emphasized the chemotherapy’s physiological toll. Other symptoms were minimal, possibly due to early treatment stages or effective management. These findings advocate for integrated supportive care, including physical rehabilitation and symptom management, to enhance QoL and treatment outcomes in this population. The correlation analysis further underscores the intricate interplay between health fitness and HRQoL outcomes. Notably, muscle mass, grip strength, and 6-min walk distance demonstrated significant associations with global health status, functional scales, and symptom scales. Muscle mass, while weakly associated with global health status, showed inverse relationships with functional and symptom scales, indicating that higher muscle mass may be linked to better functional capacity and reduced symptom burden. This result was also confirmed in older populations 33 – 34 . However, the current evidence base remains substantially limited regarding the quantitative association between musculoskeletal strength metrics and HRQoL outcomes in rheumatoid arthritis populations, with a notable lack of robust longitudinal data elucidating this clinically relevant relationship 35 . Similarly, grip strength and 6-min walk distance exhibited positive correlations with global health status but negative correlations with functional and symptom scales. This suggests that improved physical fitness may enhance patients' perception of their overall health, even as they experience functional decline and increased symptom severity. Physical activity levels presented a particularly interesting pattern, with positive correlations with global health status and significant negative correlations with functional and symptom scales. It is plausible that patients who engage in higher levels of physical activity may perceive themselves as healthier, despite experiencing significant functional limitations and symptom exacerbation. This finding aligns with that of previous research suggesting that physical activity can improve psychological well-being and global health perceptions, even in the presence of physical decline 36 . Interestingly, BMI and the 5-repetition sit-to-stand test showed weak and non-significant associations with all measured scales, indicating that these measures may have limited relevance to HRQoL outcomes in this population. This contrasts with previous studies that have highlighted 37 the importance of BMI and lower body strength in cancer-related outcomes, suggesting that the relationship between physical fitness and HRQoL may be context-specific and influenced by the type and stage of cancer. The multivariate regression analysis further elucidated the complex interplay of factors influencing QoL. Female gender, higher education levels, and the absence of comorbidities were associated with better functional scales. This may be attributed to better access to resources and health literacy among more educated female patients. This findings align with the findings of Julia et al. 38 , who also suggested that patients with less education felt they had less control over their cancer disease, leading to poorer health-related QoL. In contrast, advanced disease stages and lower physical activity levels were linked to worse outcomes. A possible explanation for this is that patients with low physical activity levels sit for longer periods of each day, increasing the risk of complications after oncological treatment and thereby reducing QoL. Increasing physical activity in such patients may help to improve QoL, particularly in terms of social functioning 39 . Notably, higher physical activity levels (B = 16.707, P < 0.001) and greater 6-min walk distance (B = 0.041, P < 0.001) were significant predictors of better global health and functional scales, emphasizing the importance of physical fitness in QoL. These findings emphasize the multifaceted nature of QoL in patients with lung cancer, highlighting the interplay between physical, socioeconomic, and clinical factors. Interventions targeting physical activity levels and the management of chemotherapy-related comorbidities in lung cancer may significantly improve QoL in this population. Future studies should explore the longitudinal effects of these factors and evaluate tailored supportive care strategies to optimize patient prognosis during chemotherapy. From the above discussion, it can be concluded that significant gender differences exist in symptom perception, functional status, and QoL. Female patients reported a higher symptom burden and lower functional scores, whereas male patients demonstrated higher levels of physical activity. This difference may be related to gender-based variations in muscle mass, social roles, and coping mechanisms. Objective physical fitness indicators such as muscle mass, grip strength, and 6-min walking distance, were directly associated with HRQoL (health-related quality of life) in patients with lung cancer and were found to be significantly correlated with global health status, functional scores, and symptom burden. In particular, 6-min walking distance was identified as a significant predictor of function and QoL. Clinical interventions should focus on gender specificity, providing more psychological support and symptom management strategies for female patients, while encouraging male patients to maintain physical activity to improve functional status. Simultaneously, physical fitness assessments should be emphasized and integrated into the routine management of patients with lung cancer. Exercise interventions designed to enhance muscle mass and functional capacity may significantly improve the QoL and treatment outcomes of patients with poor physical fitness. Strengths and limitations We investigated the health fitness and physical activity levels of patients with lung cancer who received chemotherapy for the first time, providing a clearer explanation of the relationship between these indicators. Few previous studies have reported such findings. Since the object of this study was selected in one hospital, the object of the study is single, and the multi-center and large sample study can be carried out in the future to obtain more research data. However, since health fitness indicators are physiological and physical activity levels are dynamic, a longitudinal trajectory study could offer deeper insights into their direct relationship. Future longitudinal studies should be conducted to further enrich research in this area and promote tailored exercise interventions for patients undergoing lung cancer chemotherapy to enhance their QoL. Conclusion Patients with lung cancer undergoing their first chemotherapy sessions often report varying levels of overall health fitness, particularly in muscle strength and cardiorespiratory endurance, which significantly influence their ability to engage in physical activities. Enhanced physical fitness and increased participation in physical activities have been shown to improve their QoL. Early identification of patients with inadequate physical activity levels and poor physical fitness can enable healthcare professionals to uncover the underlying mechanisms of physical fitness changes by examining the correlation between fitness levels and activity engagement. This understanding will be crucial for designing targeted interventions aimed at boosting fitness and enhancing QoL for these patients. Declarations Competing interests The authors declare no competing interests. Ethical approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Affiliated Hospital of Jiangnan University (filenumber: LS2023086). Funding Major Project of Nursing Research Project of Wuxi Nursing Society (Z202303); Nursing Research Topic Development Project of Chinese Medical Association Journal 2022–2023 (CMAPH-NRD2022003);Top Wuxi Health Committee Program (M20 2238). Author Contribution Conception and design of the research: Jiahui Xu; Hui Lu; Tingting Fang; Acquisition of data: Jiahui Xu; Dongyan Cai; Ping Cai; Yuqing Zhou; Hui Su; Analysis and interpretation of the data: Jianing Hua; Yaoyao Hu; Statistical analysis: Jiahui Xu; Hui Lu; Tingting Fang; Obtaining financing: Hui Lu; Ping Cai; Writing of the manuscript: Jiahui Xu; Hui Lu; Huihong Wang; Tingting Fang; Critical revision of the manuscript for intellectual content: Huihong Wang; Ying Chen; Dongyan Cai; Ping Cai; Yuqing Zhou; Hui Su1. All authors read and approved the final draft. Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. Additional information Correspondence and requests for materials should be addressed to Hui Lu. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References Thai, A. 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Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYBACfvbm4x8+VNjIsbE3HyBOi2TPsTTGGWfSjPl5jiUQp8XgRo4ZM2/b4cSZM3IMiHTZgQSzhzPOMCduOJDz8cYbBjs53QYCOhgbDqQbfKhgM95w4OxmyzkMycZmBwhoYQbqkZxxhkd2w8HebdI8DAcStxHSwgbUI83bJsG44TDPM+K08LAxswG1GCjObONhI06LBFCP4YwzCcBAZjO2nGNAhF/s77//+OBDxX85NvnHD2+8qbCTI6gFzUpiowZJC6k6RsEoGAWjYEQAAP/UR2waOMq9AAAAAElFTkSuQmCC","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":true,"prefix":"","firstName":"Hui","middleName":"","lastName":"Lu","suffix":""},{"id":434504423,"identity":"049358a9-9161-45c4-abd3-94ec79227ac3","order_by":2,"name":"Tingting Fang","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Tingting","middleName":"","lastName":"Fang","suffix":""},{"id":434504424,"identity":"efbf4dd7-d375-413e-9dc5-14954c7b3ea9","order_by":3,"name":"Huihong Wang","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Huihong","middleName":"","lastName":"Wang","suffix":""},{"id":434504425,"identity":"9d8dcd92-73e8-44a4-9f58-fd26aa9adbb5","order_by":4,"name":"Ying Chen","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Chen","suffix":""},{"id":434504426,"identity":"88c3c349-5a0b-4719-a9a6-804dbdc2875c","order_by":5,"name":"Jianing Hua","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Jianing","middleName":"","lastName":"Hua","suffix":""},{"id":434504427,"identity":"ec593daf-7966-479b-a035-873981da9bf5","order_by":6,"name":"Yaoyao Hu","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Yaoyao","middleName":"","lastName":"Hu","suffix":""},{"id":434504428,"identity":"7470ed8f-f4a1-4876-bfe2-e00efa204885","order_by":7,"name":"Dongyan Cai","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Dongyan","middleName":"","lastName":"Cai","suffix":""},{"id":434504429,"identity":"7672f04f-e042-4715-a4f6-6f6322731a8a","order_by":8,"name":"Ping Cai","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Cai","suffix":""},{"id":434504430,"identity":"8342cc2c-5667-4ee1-a2a4-175b5cb89a00","order_by":9,"name":"Yuqing Zhou","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Yuqing","middleName":"","lastName":"Zhou","suffix":""},{"id":434504431,"identity":"a5449eef-0afd-41ed-87cc-8ce9cdee8466","order_by":10,"name":"Hui Su","email":"","orcid":"","institution":"Affiliated Hospital of Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Su","suffix":""}],"badges":[],"createdAt":"2025-03-06 08:08:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6168386/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6168386/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-06834-9","type":"published","date":"2025-07-01T15:58:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86179122,"identity":"50adb7a7-dc82-4286-8894-acbb14e31de9","added_by":"auto","created_at":"2025-07-07 16:16:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2235814,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6168386/v1/414f7fa9-fe43-45ba-9235-9ea74c4a60b6.pdf"},{"id":79427310,"identity":"1be71fc5-3a03-43fa-a850-b0ada34860b8","added_by":"auto","created_at":"2025-03-28 09:54:07","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27648,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryInformation.doc","url":"https://assets-eu.researchsquare.com/files/rs-6168386/v1/24522b0e48681ab2addbd929.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health fitness, physical activity, and quality of life in patients undergoing first chemotherapy for lung cancer: a cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer remains a leading cause of cancer-related mortality worldwide, despite recent advances in treatment that have improved 5-year survival rates\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Over 70% of patients are diagnosed with advanced\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, inoperable lung cancer, for which chemotherapy is a primary treatment modality. However, chemotherapy often induces side effects such as fatigue, muscle weakness, and dyspnea, which can significantly impair patients' physical activity levels and overall quality of life (QoL). Furthermore, patients with lung cancer experience a more severe symptom burden than other cancers\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Studies have shown that physical activity can mitigate the toxicity of anti-tumor therapies\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, improve patient tolerance, and enhance the efficacy of traditional treatments. The American College of Sports Medicine and the American Cancer Society\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e recommend that patients with cancer engage in at least 150 min of moderate-intensity or 75 min of high-intensity physical activity per week, along with resistance training twice weekly. Despite these guidelines, a significant proportion of patients with lung cancer undergoing chemotherapy fail to meet these recommendations, with 74% reporting insufficient physical activity levels\u003csup\u003e\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePhysical fitness is an indicator of the overall assessment of physical functioning during daily physical activities. It is an important component of QoL, and its recovery contributes to the improvement of functional status and social activities in patients with tumor\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Key assessment indicators include body composition, cardiorespiratory fitness, muscular function, and flexibility. Patients with lung cancer may experience a decline in cardiopulmonary function and metabolic disturbances due to the disease itself. Furthermore, tumor treatments and a lack of physical activity can lead to impaired muscle function, subsequently affecting overall health and fitness levels\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Individuals who transition from a sedentary lifestyle to achieving optimal physical fitness can reduce their mortality rate by 44%. In contrast, patients with poor physical fitness who do not implement any intervention measures face the highest mortality rates\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The predominant demographic of patients with lung cancer consists of individuals who are inactive or lead sedentary lifestyles. Assessment of physical function in patients receiving chemotherapy for malignant lymphoma indicated that while right grip strength diminished post-chemotherapy, other physical performance metrics (left grip strength, bilateral knee extension, and the 6-minute walk test) exhibited no significant changes. This observation suggests that exercise interventions could play a crucial role in mitigating the decline of specific physical function parameters during chemotherapy\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Similarly, childhood cancer survivors experience significant setbacks in physical abilities and cardiorespiratory fitness compared with children without a history of cancer. Those who survived central nervous system tumors during childhood showed significant decline in fitness and overall QoL, particularly in the five years leading up to and following their treatment\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In patients with breast cancer and hematologic malignancies, exercise programs focusing on muscle strength, cardiorespiratory fitness, and body composition have been shown to significantly improve QoL. These programs help patients navigate treatment and recovery more effectively\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. In this study, we aimed to assess the health and fitness status of oncology patients and identify determinants of their physical activity levels. The goal was to establish a scientific foundation for developing personalized exercise plans tailored to these patients. By exploring how such programs can enhance QoL, we may enhance the overall survival experience for patients with cancer and increase their life satisfaction and well-being.\u003c/p\u003e \u003cp\u003eThe primary aim of this research was to examine the determinants affecting health fitness and physical activity levels among patients undergoing chemotherapy for lung cancer, with the goal of establishing a foundation for developing personalized exercise therapy programs in the future. Furthermore, we sought to assess the impact of health fitness and physical activity levels on their QoL, along with the disease-related and socio-demographic factors associated with QoL outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eIn this cross-sectional study, we sampled patients with lung cancer undergoing chemotherapy from the oncology treatment center of a tertiary general hospital in Wuxi, China. Patients with lung cancer who started their first round of chemotherapy between June 2024 and December 2024 were selected using convenience sampling.\u003c/p\u003e \u003cp\u003eInclusion criteria included patients who were 18 years of age and older, had a diagnosis of primary lung cancer, and were about to start their first round of chemotherapy. In addition, they had to be in good health, with normal vital signs, and willing to cooperate with the health assessments during the study. Exclusion criteria included patients with severe physical, cognitive, or speech impairments. We obtained approval from the Ethics Committee (approval number: LS2023086) and ensured registration in the Chinese Clinical Trial Registry (registration number: ChiCTR2400081003). Prior to participation, each participant provided written informed consent form.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSocio-Demographic and Clinical Data\u003c/h2\u003e \u003cp\u003eSocio-demographic information, including sex, age, education level, residence, marital status, primary caregiver, household income, medical payment method, and employment status, was collected using a custom questionnaire. Clinical data, including disease stage, surgical history, hemoglobin concentration, white blood cell count, platelet count, ultrasensitive C-reactive protein, and albumin levels, were extracted from medical records.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHealth Fitness Assessment Techniques\u003c/h3\u003e\n\u003cp\u003eAll measurement devices were standardized instruments and equipment mandated for the national physical fitness evaluation in China.\u003c/p\u003e \u003cp\u003e(1)\u003cem\u003eBody composition\u003c/em\u003e: Evaluated using metrics such as body weight, body mass index (BMI), and muscle mass.\u003c/p\u003e \u003cp\u003eWe utilized bioelectrical impedance analysis (BIA) technology from the TANITA body composition analyzer to gather data on body composition (Model Number: MC-780MA), manufactured by Dongguan Bida Health Equipment, Japan.\u003c/p\u003e \u003cp\u003e(2)\u003cem\u003eMuscular function\u003c/em\u003e: Assessed through upper limb muscle strength and lower limb muscle strength.\u003c/p\u003e \u003cp\u003e1) \u003cem\u003eUpper limb muscle strength\u003c/em\u003e: Grip strength was conducted using an electronic grip strength meter (EH201R) in the ward. Patients were instructed to stand with their arm relaxed and hanging naturally, gripping the device firmly with their fingers positioned snugly on the handle. During the assessment, the grip strength gauge was maintained at a specified distance from the body, and patients were prohibited from bending their arm, waist, or moving their feet while applying force. A rest period of 2 min was allowed between each of the two tests, with the highest score recorded for evaluation.\u003c/p\u003e \u003cp\u003e2) \u003cem\u003eLower limb muscle strength\u003c/em\u003e: Evaluated using a five-repitition sit-to-stand test. A 40 cm high back chair and a timer were used. Patients sat with legs shoulder-width apart and arms crossed. Upon the tester's 'start' command, patients performed five 'stand up-sit down' actions as quickly as possible. The timer stopped after the fifth repetition.\u003c/p\u003e \u003cp\u003e(3)\u003cem\u003eCardiorespiratory fitness\u003c/em\u003e: Assessed using the 6-min walking distance test. Patients stood at the starting point of a 50-meter course to prepare. Upon the tester\u0026rsquo;s \u0026lsquo;start\u0026rsquo; command, patients began walking. When the \u0026lsquo;stop\u0026rsquo; command was given, patients remained in place, and the tester measured and recorded the distance in meters (m units).\u003c/p\u003e \u003cp\u003e(4)\u003cem\u003eFlexibility\u003c/em\u003e: Hip flexibility was used for assessment, measured using a seated forward flexion test. Patients sat on a cushion with legs together and knees straight. The patients slowly pushed a block forward with their longest finger along a scale. When it was impossible to continue to push forward, the tester measured the distance in cm, using the toes as the starting point.\u003c/p\u003e\n\u003ch3\u003eInternational Physical Activity Questionnaire(IPAQ)\u003c/h3\u003e\n\u003cp\u003eThe International Physical Activity Questionnaire (IPAQ) is a prominent tool utilized globally for assessing physical activity levels, recognized for its validity. In this study, we used the Chinese version of IPAQ, translated and adapted by Wang Jie \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. It comprises 27 items that prompt respondents to indicate the frequency and duration of daily exercise, as well as to detail their physical activity over the past week across various domains, including leisure and recreation, household tasks, transportation methods, and occupational activities\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The duration (in minutes) spent at each intensity of physical activity was multiplied by its corresponding metabolic equivalent of task (MET) value (walking\u0026thinsp;=\u0026thinsp;3.3, moderate intensity\u0026thinsp;=\u0026thinsp;4, high intensity\u0026thinsp;=\u0026thinsp;8). The MET-minutes from each intensity level were aggregated to calculate the total physical activity energy expenditure (in MET-minutes) for the previous week. A weekly total physical activity level of \u0026ge;\u0026thinsp;1500 MET-min was classified as high; a level between 600 and 1500 MET-min was considered moderate; and a level of \u0026lt;\u0026thinsp;600 MET-min was deemed low\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEuropean Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 43(EORTC QLQ-LC43)\u003c/h2\u003e \u003cp\u003eThis scale was developed by the European Organisation for Research and Treatment of Cancer (EORTC) and consists of the core QoL scale for oncology patients, EORTC QLQ-C30, and the patient-specific subscale for lung cancer, EORTC QLQ-LC13. In this study, we used the Chinese version of the EORTC QLQ-LC43, translated and adapted by Wan Chonghua\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The EORTC QLQ-C30 instrument comprises 30 items across five domains: physical, emotional, role functioning, cognitive, and social, with a Cronbach's alpha of 0.83. The EORTC QLQ-LC13 tool includes 13 items specifically addressing the symptoms and side effects associated with lung cancer. The Cronbach's alpha coefficients for both scales exceed 0.70, indicating their reliability and suitability for use with Chinese patients with lung cancer\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe utilized Excel 2010 for data entry and aggregation, while statistical analysis was performed using SPSS 26.0. To characterize the demographic, sociological attributes, and disease-related factors (such as disease stage, total white blood cell count, platelet count, ultrasensitive C-reactive protein, and albumin levels) of the respondents, categorical data were represented as rates or proportions. For continuous data, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation was used for measures conforming to a normal distribution, and interquartile range (IQR: P\u003csub\u003e25\u003c/sub\u003e-P\u003csub\u003e75\u003c/sub\u003e) was used for non-normally distributed data.\u003c/p\u003e \u003cp\u003eDeterminants affecting health fitness status, physical activity levels, and QoL among patients with lung cancer were analyzed using independent samples t-tests, analysis of variance, and non-parametric methods (Mann-Whitney U-test and Kruskal-Wallis H-test). Non-parametric tests were specifically employed for data exhibiting heterogeneity. Multivariate linear regression was used to perform a multifactorial analysis of the determinants affecting physical activity levels and QoL among patients with lung cancer. Two-tailed tests were conducted, with a p-value of 0.05 set as the significance level.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eParticipant characteristics\u003c/h2\u003e \u003cp\u003eOut of 438 eligible patients, 405 were included in the study (response rate: 92.47%). Among these, 33 were excluded due to incomplete responses, resulting in a final sample size of 372 patients.\u003c/p\u003e \u003cp\u003eThe mean age of participants was 64.1 years, with 77.96% being male. The most frequent cancer types were adenocarcinoma (48.66%) and squamous cell carcinoma (23.12%). The majority of patients (63.44%) had a moderate level of physical activity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eUnifactorial analysis of factors affecting patients' quality of life\u003c/h2\u003e \u003cp\u003eUnivariate analysis revealed statistically significant associations between primary caregiver status, smoking status, physical exercise level, and EORTC QLQ-LC43 scores (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Among the covariates analyzed, age demonstrated a significant influence on EORTC QLQ-LC13 scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), with younger patients (18-45years) exhibiting a greater symptom burden than older cohorts. Gender-specific analysis indicated that female patients scored lower on global health status and functioning scales but reported higher symptom scale scores relative to male counterparts (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Educational attainment emerged as a significant factor, with patients holding bachelor's degrees or higher qualifications demonstrating superior functional outcomes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), albeit with increased symptom burden and lung cancer-specific symptoms. While no significant differences were observed in global health status, functional scales, or symptom scales (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), residential status significantly impacted EORTC QLQ-LC13 scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with rural residents reporting elevated symptom burden compared with urban and town dwellers. Socioeconomic analysis revealed that income level significantly correlated with global health status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with higher income brackets associated with improved global health outcomes. However, no significant associations were found with functional scales, symptom scales, or EORTC QLQ-LC13 scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Multiple factors, including medical payment method, employment status, occupational history, alcohol consumption patterns, comorbidities, and living arrangements, demonstrated significant effects across functional scales (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), symptom scales (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and EORTC QLQ-LC13 scores (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Clinical characteristics, particularly diagnosis type and lung cancer staging, significantly influenced global health status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Notably, marital status showed no statistical significance in relation to surgical status across all QoL domains (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), suggesting minimal impact on symptom reporting or functional status assessment within this patient population. (Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;1.\u003c/b\u003e Influencing factors of mean scores on scales and items of EORTC QLQ⁃C30 and EORTCQLQ⁃LC13 for patients ( \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;372 ).\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlobal Health Status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFunctional Scales\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymptom Scales\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEORTC QLQ⁃LC13\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18~\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(58.33,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(21.33,40.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(41.98,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.44(4.44, 20.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45~\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.67(25.75,56.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.06(38.73,53.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(5.56, 14.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60~\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.00(25.67,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.08(40.74,58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.22(7.78, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(41.67,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.00(32.33,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47(43.21,59.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.89(6.67, 24.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.67(23.00,46.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.30(39.97,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(6.67, 17.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(39.59,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.67(32.00,60.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.70(45.06,66.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e2)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;4.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;3.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(43.75,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.33(26.00,52.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(40.12,59.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.44(8.06, 24.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJunior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(25.67,51.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.68(40.74,56.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(6.67, 16.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.33(26.00,34.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.30(39.51,53.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.78(3.33, 14.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.50(58.33,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(21.67,55.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.32(40.13,61.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.78(11.11, 20.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33.33(33.33,91.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95.33(35.67,95.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e109.88(45.68,109.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56.67(5.56, 56.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.00(24.67,51.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.61(40.74,58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(6.67, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.50(25.92,51.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.08(40.12,55.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(5.56, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(41.67,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.33(28.67,52.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47(41.98,59.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.67(10.00, 24.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther provinces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(66.67,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.33(27.67,40.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.83(43.83,52.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.22(2.22, 4.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.00(58.33,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.33(27.67,35.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.00(41.98,52.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.44(4.44, 10.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(26.00,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.38(40.74,57.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 17.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(33.33,100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.33(14.67,86.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.83(30.86,77.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.44(2.22, 27.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(33.33,87.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.00(18.92,86.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.70(35.65,77.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(1.67, 27.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Caregiver\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(25.67,54.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(40.74,58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.22(7.78, 17.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.33(27.67,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.38(43.21,58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(6.67, 20.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.00(83.33,100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.67(6.67,27.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.63(29.63,37.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00(0.00, 5.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiblings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83.33(83.33,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.67(27.67,27.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47(52.47,52.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.44(4.44, 4.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(56.25,64.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(31.75,39.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.53(40.44,56.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(9.72, 11.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly Household Income\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(37.50,81.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.67(24.17,59.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.32(43.21,59.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.78(8.06, 17.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1K\u0026thinsp;~\u0026thinsp;5K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(41.67,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(26.00,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.91(40.74,56.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(58.33,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.67(24.67,48.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.15(38.58,61.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(3.33, 17.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical Payment Method\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-pay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.67(26.00,38.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47(36.42,55.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.44(1.11, 14.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban Resident Medical Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.83(25.25,42.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.06(40.12,52.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(6.67, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployee Medical Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(41.67,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.33(26.00,52.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.70(40.74,66.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.22(7.78, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.67(27.33,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47(43.21,58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(8.89, 25.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(33.33,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.33(21.33,51.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.83(35.80,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.78(1.11, 14.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.00(25.67,51.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.91(40.74,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 17.78)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.67(16.67,70.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.33(32.75,69.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.09(50.00,70.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.00(10.00, 27.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.00(26.59,52.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.09(43.21,60.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(8.89, 17.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.019\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation or Pre-retirement Occupation\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNational,Party,Enterprise Leaders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(41.67,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.67(30.00,67.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(44.44,74.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(7.78, 24.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfessionals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.33(27.75,54.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.68(40.74,59.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProduction,Transportation Workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.00(16.00,54.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.06(35.80,53.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.89(7.78, 20.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommercial, Service Workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(45.83,93.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.00(14.92,35.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.91(29.63,53.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(2.50, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgriculture,Forestry,Fishery Workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.33(33.67,56.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.47(39.51,59.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(6.12, 19.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClerical Workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83.33(66.67,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.00(22.67,33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.98(35.80,50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(4.44, 11.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMilitary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(66.67,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.67(62.67,62.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72.22(72.22,72.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.33(33.33, 33.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(50.00,79.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.33(20.67,33.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.70(43.83,54.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(5.56, 18.34)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.17(33.33,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.17(25.25,56.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.08(41.83,62.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(8.34, 18.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.041\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol Consumption\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(43.75,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.33(30.00,60.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.70(40.90,66.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(10.00, 25.56)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.00(25.67,48.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.91(40.74,56.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(5.84, 17.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e2)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;2.638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;2.862\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(50.00,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.00(30.25,56.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.16(40.74,61.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(7.78, 20.00)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.17(23.00,45.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.91(40.12,53.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(5.56, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e2)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;4.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;3.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.50(28.67,55.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(41.52,60.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.33(7.78, 19.72)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.33(22.75,46.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.68(39.51,54.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(5.56, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e2)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;3.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;3.164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving Arrangement\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with spouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(23.00,48.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.68(39.51,56.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(50.00,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.33(27.67,54.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(43.21,60.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.23, 17.78)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(50.00,56.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.50(25.67,41.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.70(44.91,54.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.78(5.56, 10.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.862\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.040\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease Stage\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.00(66.67,85.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.67(15.00,42.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.36(39.51,45.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.23(0.00, 20.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.00(54.17,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.34(22.67,40.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.66(35.80,52.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.56(10.00, 11.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31.33(23.00,48.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.15(40.12,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(6.67, 16.67)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.33(28.67,53.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(43.21,59.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.22(7.78, 18.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.50(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(22.75,50.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(39.51,58.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(7.78, 16.67)\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.00(27.67,52.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.84(40.90,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.22(6.67, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e2)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;1.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;1.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;1.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosis\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLarge Cell Neuroendocrine Carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(58.33,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.33(26.75,51.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.15(38.89,58.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(6.67, 12.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSquamous Cell Carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.00(22.92,40.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.68(40.12,55.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.56(5.56, 14.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.33(41.67,79.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.67(26.33,55.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(39.51,60.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.11(6.67, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdenosquamous Carcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(16.67,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.00(30.00,56.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.26(45.68,76.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.44(5.56, 24.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall Cell Lung Cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,66.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.00(29.08,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.00(43.21,57.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.89(8.89, 17.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Activity Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79.17(50.00,83.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.00(19.83,33.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.12(35.80,52.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.00(4.44, 12.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50.00,75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.33(29.33,53.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.85(43.21,61.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.78(7.78, 18.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.00(41.67,58.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.17(42.33,60.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.09(43.83,58.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.44(10.28, 25.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTest\u003c/b\u003e\u003csup\u003e\u003cb\u003e1)\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSignifcant values (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) are marked in bold.\u003c/p\u003e\u003cp\u003e1)Kruskal Wallis Test ; 2) Mann-Whitney U Test .\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eQuality of life outcomes\u003c/h2\u003e \u003cp\u003eThe QLQ-C30 scale had the lowest score of 35.33 (IQR: 25.67, 51.33) for the functioning domain and the highest score of 66.67 (IQR: 50, 75) for global health status. Dyspnea, coughing, and alopecia symptoms scored the highest for each domain of the QLQ-LC13, with scores of 33.33 (IQR: 11.11, 44.44), 33.33 (IQR: 0.00, 33.33), and 33.33 (IQR: 0.00, 33.33) scores, respectively, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eScores of Quality of Life Domains in 372 Lung Cancer Patients Undergoing First Chemotherapy.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEORTC QLQ-C30\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEORTC QLQ-LC13\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal Health Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.67(50,75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDyspnoea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.33(11.11,44.44)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFunctional Scales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.33(25.67,51.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoughing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.33(0.00,33.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptom Scales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.69(40.74,58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHaemoptysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSore mouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDysphagia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePeripheral neutopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlopecia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.33(0.00,33.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePain in chest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,33.33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePain in arm or shoulder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePain in other parts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00(0.00,0.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStatus of patients' health, fitness, and physical activity levels\u003c/h2\u003e \u003cp\u003ePatients with lung cancer receiving chemotherapy for the first time had a BMI score of 23.51 (IQR: 21.32, 24.97), a muscle mass score of 27.40 (IQR: 21.43, 34.90), a grip strength score of 20.10 (IQR: 16.60, 24.98), a 5-repitition sit-to-stand test score of 12.40 (IQR: 9.78, 16.00), a 6-min walk distance score of 326.00 (IQR: 280.00, 381.50), and a seated forward bend distance score of 26.50 (IQR: 20.00, 37.00). The overall physical activity level of this group was low to moderate, with 90 patients (24.19%) at a high physical activity level, 236 (63.44%) at a moderate physical activity level, and 46 (12.37%) at a low physical activity level.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis of the quality of life of patients\u003c/h2\u003e \u003cp\u003eAnalysis of QoL correlations in 372 patients with lung cancer undergoing chemotherapy for the first time revealed an important and complex relationship between health fitness measures and physical activity levels. The correlation analysis revealed distinct patterns between physical fitness measures and health-related QoL (HRQoL) outcomes.\u003c/p\u003e \u003cp\u003eMuscle mass demonstrated a weak yet statistically significant positive association with Global Health Status (r\u0026thinsp;=\u0026thinsp;0.110, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while exhibiting moderate inverse relationships with both Functional Scales (r = -0.368, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Symptom Scales (r = -0.183, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Grip strength exhibited positive correlations with Global Health Status (r\u0026thinsp;=\u0026thinsp;0.260, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and negative correlations with Functional Scales (r = -0.246, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Symptom Scales (r = -0.184, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, the 6-min walk distance showed a positive correlation with Global Health Status (r\u0026thinsp;=\u0026thinsp;0.263, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and negative correlations with both Functional Scales (r = -0.408, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Symptom Scales (r = -0.457, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Physical activity levels demonstrated a significant pattern, with positive correlations with Global Health Status (r\u0026thinsp;=\u0026thinsp;0.291, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) alongside negative correlations with Functional Scales and Symptom Scales (r = -0.407 and \u0026minus;\u0026thinsp;0.287, respectively; all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Interestingly, BMI and the 5-repetition sit-to-stand test showed generally weak and non-significant associations with all measured scales (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating limited relevance to HRQoL outcomes in this population. These findings collectively suggest that while enhanced health fitness measures and activity levels are associated with improved global health perceptions, they may simultaneously correlate with compromised functional capacity and increased symptom burden. This highlights the complex interplay between physical fitness parameters and QoL outcomes. For further details, refer to Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMultiple linear regression analysis of factors influencing patients' quality of life\u003c/h2\u003e \u003cp\u003eInfluencing factors with statistically significant differences in univariate analyses of variance, along with age, were included as independent variables, while scale scores were included as dependent variables in multiple linear regression analyses. The influencing factors of global health status in the QLQ-C30 scale included gender, education level, primary caregiver, employment status, smoking status, comorbidities, living arrangement, disease stage, physical activity level, and 6-min walk distance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Female patients had better functional scales (B\u0026thinsp;=\u0026thinsp;11.405, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients with employee medical insurance (B\u0026thinsp;=\u0026thinsp;7.307, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and other payment methods (B\u0026thinsp;=\u0026thinsp;5.487, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042) also had better functional scales. The absence of comorbidities was associated with better functional scales (B\u0026thinsp;=\u0026thinsp;10.251, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Patients in Stage II had slightly lower functional scales (B = -7.674, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038). Higher physical activity levels were associated with better functional scales (B\u0026thinsp;=\u0026thinsp;11.066, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), while lower muscle mass was associated with worse functional scales (B = -0.377, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). Multivariate analysis identified several significant predictors of symptom burden (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in chemotherapy-na\u0026iuml;ve patients with lung cancer, including sex, educational attainment, monthly household income, primary caregiver status, disease stage, comorbidity index, physical activity level, 6-min walk distance and seated forward bend test performance. The EORTC QLQ-LC13 scores demonstrated significant associations with multiple clinical and demographic variables, including chronological age, educational attainment, primary caregiver status, occupational history (including pre-retirement occupation), and diagnostic characteristics (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Only statistically significant factors are listed in the table. (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;3.\u003c/b\u003e Multivariate regression analysis results on the quality of life in patients ( \u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;372 ).\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExp(B)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eGlobal Health Status\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e(Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;17.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;21.769,\u0026minus;12.577)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.137, 11.707)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(5.911, 19.308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.977\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(12.446, 39.507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Caregiver\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;6.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;11.885,\u0026minus;2.046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiblings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;29.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;40.153,\u0026minus;18.092)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;26.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;35.236,\u0026minus;17.712)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment 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 \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\u003e\u0026minus;12.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;19.704,\u0026minus;5.467)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarming\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;7.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;12.042,\u0026minus;2.573)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e(No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.114, 11.916)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e(No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(7.146, 16.481)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving Arrangement\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;4.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;9.578,\u0026minus;0.352)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease Stage\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(28.384, 40.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(18.650, 30.891)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Activity Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(7.784, 25.630)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;12.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;17.004,\u0026minus;8.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-minute Walk Distance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.018, 0.064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFunctional Scales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e(Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(7.022, 15.788)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical Payment Method\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployee Medical Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.600, 12.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.193, 10.781)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.042*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e(No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(5.932, 14.570)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease Stage\u003c/b\u003e(Stage II )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;7.674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;14.924,\u0026minus;0.425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.038*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Activity Level\u003c/b\u003e(High)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.310, 19.823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMuscle Mass\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;0.611,\u0026minus;0.144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptom Scales\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e(Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.521, 11.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSenior high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;5.861\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;11.246,\u0026minus;0.477)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.033*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;12.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;23.664,\u0026minus;1.911)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Caregiver\u003c/b\u003e(None)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(2.011, 16.677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly Household Income\u003c/b\u003e(\u0026lt;1K)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.760, 10.769)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking\u003c/b\u003e(No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;4.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;7.747,\u0026minus;0.785)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.016*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e(No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;7.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;11.544,\u0026minus;4.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease Stage\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;8.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;14.603,\u0026minus;3.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;7.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;13.853,\u0026minus;1.663)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhysical Activity Level\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;8.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;15.796,\u0026minus;0.879)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.029*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.266, 7.472)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6-minute Walk Distance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;0.051,\u0026minus;0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSitting Forward Bend Distance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;0.366,\u0026minus;0.028)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEORTC QLQ⁃LC13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18~\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;9.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;19.634,\u0026minus;0.056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.049*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45~\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;8.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;14.018,\u0026minus;2.958)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(4.425, 17.544)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e(College)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;14.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(\u0026minus;27.771,\u0026minus;0.299)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Caregiver\u003c/b\u003e(Children)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.668, 12.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation or Pre-retirement Occupation\u003c/b\u003e(Military)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.594, 88.808)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.034*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosis\u003c/b\u003e(Adenosquamous Carcinoma)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.610, 24.325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.025*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe unifactorial analysis revealed several significant associations between demographic, socioeconomic, and clinical factors and the QoL of patients with lung cancer, as measured by the EORTC QLQ-C30 and QLQ-LC13 scales. Age emerged as a critical determinant, with younger patients (18\u0026ndash;45 years) reporting a higher symptom burden compared with older cohorts (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005). This finding aligns with that of previous studies suggesting that younger patients may experience more aggressive disease progression or heightened psychological distress, contributing to increased symptom severity. Epidemiological investigations consistently demonstrate a significant age-dependent disparity in psychological adaptation to illness\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, with older patients exhibiting greater emotional resilience and lower disease-related distress scores compared with their younger counterparts. This phenomenon may be attributed to the differential psychosocial burden distribution, wherein younger patients frequently encounter substantial occupational and familial obligations. Gender-specific differences were also notable, with female patients scoring lower on global health status and functioning scales but reporting higher symptom scale scores than their male counterparts (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). This finding was also reported by Yifan et al.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. This disparity may be attributed to gender-related variations in symptom perception and reporting, as well as potential differences in coping mechanisms. Educational attainment significantly influenced functional outcomes, with patients holding bachelor's degrees or higher qualifications demonstrating superior functional scales (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011). However, this group also reported increased symptom burden, possibly due to greater awareness of their condition or higher expectations regarding health outcomes\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Residential status further impacted QoL, with rural residents experiencing elevated symptom burden compared to urban and town dwellers (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This could be linked to limited access to healthcare resources and delayed diagnosis in rural areas, exacerbating symptom severity. Socioeconomic factors, particularly income level, were significantly associated with global health status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with higher income brackets correlating with improved health outcomes. This finding underscores the role of economic stability in accessing timely and effective medical care, which can significantly influence QoL. Furthermore, clinical characteristics such as disease stage and diagnosis type significantly impacted global health status (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), highlighting the importance of early detection and tailored treatment strategies in improving patient outcomes.\u003c/p\u003e \u003cp\u003eThe QLQ-C30 and QLQ-LC13 scales revealed that global health status was relatively higher than functional and symptom scales, with dyspnea, coughing, and alopecia being the most prominent symptoms. Contrary to the observations of Yifan et al.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, their study found that chest pain was more pronounced in patients hospitalized after lung cancer surgery. This difference could be attributed to distinct characteristics of the population they studied, which included patients who experienced more pronounced postoperative pain in the first five days after lung cancer surgery. These findings suggests that while patients may perceive their overall health status as moderately good, they continue to experience significant functional limitations and symptom burden, particularly in domains related to respiratory and physical functioning. This pathophysiological phenomenon is primarily attributable to the tumor-mediated destruction of alveolar architecture and bronchial obstruction, which collectively contribute to impaired pulmonary function, manifested as compromised gas exchange efficiency and restricted airflow dynamics\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study highlights the health fitness, and QoL challenges faced by patients with lung cancer undergoing first-time chemotherapy. While most patients had a normal BMI, declines in muscle mass and grip strength suggest early sarcopenia and fatigue, consistent with prior findings\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Physical activity levels were predominantly low to moderate (87.81% combined), underscoring the need for interventions to improve activity levels and mitigate chemotherapy\u0026rsquo;s adverse effects. QoL assessments revealed moderate global health status but significant functional impairment, aligning with the physical and emotional burden of the treatment\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Dyspnea and coughing were the most prevalent symptoms, reflecting common respiratory complications. Alopecia and chest pain further emphasized the chemotherapy\u0026rsquo;s physiological toll. Other symptoms were minimal, possibly due to early treatment stages or effective management. These findings advocate for integrated supportive care, including physical rehabilitation and symptom management, to enhance QoL and treatment outcomes in this population.\u003c/p\u003e \u003cp\u003eThe correlation analysis further underscores the intricate interplay between health fitness and HRQoL outcomes. Notably, muscle mass, grip strength, and 6-min walk distance demonstrated significant associations with global health status, functional scales, and symptom scales. Muscle mass, while weakly associated with global health status, showed inverse relationships with functional and symptom scales, indicating that higher muscle mass may be linked to better functional capacity and reduced symptom burden. This result was also confirmed in older populations\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. However, the current evidence base remains substantially limited regarding the quantitative association between musculoskeletal strength metrics and HRQoL outcomes in rheumatoid arthritis populations, with a notable lack of robust longitudinal data elucidating this clinically relevant relationship\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Similarly, grip strength and 6-min walk distance exhibited positive correlations with global health status but negative correlations with functional and symptom scales. This suggests that improved physical fitness may enhance patients' perception of their overall health, even as they experience functional decline and increased symptom severity. Physical activity levels presented a particularly interesting pattern, with positive correlations with global health status and significant negative correlations with functional and symptom scales. It is plausible that patients who engage in higher levels of physical activity may perceive themselves as healthier, despite experiencing significant functional limitations and symptom exacerbation. This finding aligns with that of previous research suggesting that physical activity can improve psychological well-being and global health perceptions, even in the presence of physical decline\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Interestingly, BMI and the 5-repetition sit-to-stand test showed weak and non-significant associations with all measured scales, indicating that these measures may have limited relevance to HRQoL outcomes in this population. This contrasts with previous studies that have highlighted\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e the importance of BMI and lower body strength in cancer-related outcomes, suggesting that the relationship between physical fitness and HRQoL may be context-specific and influenced by the type and stage of cancer.\u003c/p\u003e \u003cp\u003eThe multivariate regression analysis further elucidated the complex interplay of factors influencing QoL. Female gender, higher education levels, and the absence of comorbidities were associated with better functional scales. This may be attributed to better access to resources and health literacy among more educated female patients. This findings align with the findings of Julia et al.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, who also suggested that patients with less education felt they had less control over their cancer disease, leading to poorer health-related QoL. In contrast, advanced disease stages and lower physical activity levels were linked to worse outcomes. A possible explanation for this is that patients with low physical activity levels sit for longer periods of each day, increasing the risk of complications after oncological treatment and thereby reducing QoL. Increasing physical activity in such patients may help to improve QoL, particularly in terms of social functioning\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Notably, higher physical activity levels (B\u0026thinsp;=\u0026thinsp;16.707, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and greater 6-min walk distance (B\u0026thinsp;=\u0026thinsp;0.041, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significant predictors of better global health and functional scales, emphasizing the importance of physical fitness in QoL. These findings emphasize the multifaceted nature of QoL in patients with lung cancer, highlighting the interplay between physical, socioeconomic, and clinical factors.\u003c/p\u003e \u003cp\u003eInterventions targeting physical activity levels and the management of chemotherapy-related comorbidities in lung cancer may significantly improve QoL in this population. Future studies should explore the longitudinal effects of these factors and evaluate tailored supportive care strategies to optimize patient prognosis during chemotherapy.\u003c/p\u003e \u003cp\u003eFrom the above discussion, it can be concluded that significant gender differences exist in symptom perception, functional status, and QoL. Female patients reported a higher symptom burden and lower functional scores, whereas male patients demonstrated higher levels of physical activity. This difference may be related to gender-based variations in muscle mass, social roles, and coping mechanisms. Objective physical fitness indicators such as muscle mass, grip strength, and 6-min walking distance, were directly associated with HRQoL (health-related quality of life) in patients with lung cancer and were found to be significantly correlated with global health status, functional scores, and symptom burden. In particular, 6-min walking distance was identified as a significant predictor of function and QoL. Clinical interventions should focus on gender specificity, providing more psychological support and symptom management strategies for female patients, while encouraging male patients to maintain physical activity to improve functional status. Simultaneously, physical fitness assessments should be emphasized and integrated into the routine management of patients with lung cancer. Exercise interventions designed to enhance muscle mass and functional capacity may significantly improve the QoL and treatment outcomes of patients with poor physical fitness.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eWe investigated the health fitness and physical activity levels of patients with lung cancer who received chemotherapy for the first time, providing a clearer explanation of the relationship between these indicators. Few previous studies have reported such findings. Since the object of this study was selected in one hospital, the object of the study is single, and the multi-center and large sample study can be carried out in the future to obtain more research data. However, since health fitness indicators are physiological and physical activity levels are dynamic, a longitudinal trajectory study could offer deeper insights into their direct relationship. Future longitudinal studies should be conducted to further enrich research in this area and promote tailored exercise interventions for patients undergoing lung cancer chemotherapy to enhance their QoL.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePatients with lung cancer undergoing their first chemotherapy sessions often report varying levels of overall health fitness, particularly in muscle strength and cardiorespiratory endurance, which significantly influence their ability to engage in physical activities. Enhanced physical fitness and increased participation in physical activities have been shown to improve their QoL. Early identification of patients with inadequate physical activity levels and poor physical fitness can enable healthcare professionals to uncover the underlying mechanisms of physical fitness changes by examining the correlation between fitness levels and activity engagement. This understanding will be crucial for designing targeted interventions aimed at boosting fitness and enhancing QoL for these patients.\u003c/p\u003e "},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Affiliated Hospital of Jiangnan University (filenumber: LS2023086).\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003e Major Project of Nursing Research Project of Wuxi Nursing Society (Z202303); Nursing Research Topic Development Project of Chinese Medical Association Journal 2022\u0026ndash;2023 (CMAPH-NRD2022003);Top Wuxi Health Committee Program (M20 2238).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConception and design of the research: Jiahui Xu; Hui Lu; Tingting Fang; Acquisition of data: Jiahui Xu; Dongyan Cai; Ping Cai; Yuqing Zhou; Hui Su; Analysis and interpretation of the data: Jianing Hua; Yaoyao Hu; Statistical analysis: Jiahui Xu; Hui Lu; Tingting Fang; Obtaining financing: Hui Lu; Ping Cai; Writing of the manuscript: Jiahui Xu; Hui Lu; Huihong Wang; Tingting Fang; Critical revision of the manuscript for intellectual content: Huihong Wang; Ying Chen; Dongyan Cai; Ping Cai; Yuqing Zhou; Hui Su1. All authors read and approved the final draft.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u003c/strong\u003e and requests for materials should be addressed to Hui Lu.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s note\u003c/strong\u003e Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThai, A. A., Solomon, B. J., Sequist, L. V., Gainor, J. F., \u0026amp; Heist, R. S. 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Physical Activity, Sitting Time, and Quality of Life among Breast and Gynaecology Cancer Survivors. \u003cem\u003eAsian Pac J Cancer Prev.\u003c/em\u003e\u003cstrong\u003e22\u003c/strong\u003e(8), 2399-2408. https://doi.org/10.31557/APJCP.202 1.22.8.2399 (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lung cancer, Health fitness, Physical activity, Quality of life, Influencing factors","lastPublishedDoi":"10.21203/rs.3.rs-6168386/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6168386/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn this study, we examined determinants of health fitness and physical activity levels in 372 patients with lung cancer undergoing their first chemotherapy at a tertiary hospital in Wuxi, China, and their impact on quality of life (QoL). Standardized measures were used to asses body composition, muscular function, cardiorespiratory fitness, and flexibility. Physical activity was measured using the International Physical Activity Questionnaire, and QoL was evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Lung Cancer 43. Higher physical activity levels correlated with better global health but were associated with increased symptom burden and functional limitations. Muscle mass, grip strength, and 6-minute walk distance were positively linked to global health but negatively associated with symptom and functional scales. Females reported higher symptom burdens and lower functional scores. Multivariate analysis identified gender, education, comorbidities, disease stage, and activity levels as key QoL predictors. Improved fitness and physical activity were associated with better QoL. Early identification of patients with low activity and poor fitness can guide tailored interventions to enhance functional capacity and well-being. These findings emphasize the importance of integrating fitness assessments and personalized exercise into lung cancer management to improve treatment outcomes and QoL.\u003c/p\u003e","manuscriptTitle":"Health fitness, physical activity, and quality of life in patients undergoing first chemotherapy for lung cancer: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-28 09:54:02","doi":"10.21203/rs.3.rs-6168386/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-28T06:58:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-25T01:22:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33951554252728299506543831552195820649","date":"2025-05-16T14:46:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-09T07:27:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28535454174797350729150402843714633229","date":"2025-04-22T07:44:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-26T21:25:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-26T21:23:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-19T05:27:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T04:56:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-19T04:55:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4816d5fb-a418-492c-8801-97f5739e0845","owner":[],"postedDate":"March 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46267977,"name":"Health sciences/Health care/Health services"},{"id":46267978,"name":"Health sciences/Health care/Quality of life"}],"tags":[],"updatedAt":"2025-07-07T16:05:12+00:00","versionOfRecord":{"articleIdentity":"rs-6168386","link":"https://doi.org/10.1038/s41598-025-06834-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-01 15:58:03","publishedOnDateReadable":"July 1st, 2025"},"versionCreatedAt":"2025-03-28 09:54:02","video":"","vorDoi":"10.1038/s41598-025-06834-9","vorDoiUrl":"https://doi.org/10.1038/s41598-025-06834-9","workflowStages":[]},"version":"v1","identity":"rs-6168386","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6168386","identity":"rs-6168386","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}