Wang Song*
1. Department of Colorectal Surgery,
Fudan University Shanghai Cancer Center, 270 Dong’an Road,
Shanghai, 200032, China.
2. Department of Oncology, Shanghai Medical College,
Fudan University, 270 Dong’an Road, Shanghai, 200032, China
Email: 10301010031@fudan.edu.cn
Abstract: Objective: By analyzing the social factors, life events, and emotional experiences of patients with colorectal cancer, this research aims to explore whether and how different factors affect the incidence of colorectal cancer, provide new concepts for the prevention and therapy of colorectal cancer, and furnish a scientific rationale for the development of effective prevention and treatment strategies. Method: 276 experimental subjects and 388 control subjects who visited a public tertiary hospital in China were selected to undergo a questionnaire survey from January 1, 2020 to December 31, 2024, and evaluated using the Psychological and Social Stress Scale and Perceived Stress Scale. The study delved into the causal relationship between colorectal cancer and social and psychological factors. Result: The questionnaire and scale used in the experiment passed the Cronbach’s coefficient test, Bartlett sphericity test, and Kaiser Meyer Olkin test, demonstrating high reliability. After smoking more than 20 cigarettes a day, there was a significant difference in the incidence of colorectal cancer (P<0.01), while there was no statistically significant difference in the type of alcohol consumption and the incidence of colorectal cancer (P>0.05). When the alcohol consumption level exceeded 15g/d, the risk of illness increased by at least 56.89%. Moreover, excessive consumption of smoked foods, pickled fish, and cured meat significantly increased the risk of disease, with odds ratios of 29.737 and 32.417. Psychological factors and stress reactions were intricately linked to the incidence of colorectal cancer. Long term exposure to life stress and mental stimulation increased the risk of disease by 3.244 times and 2.552 times, respectively. The research group scored 15.800 ± 4.800 for tension and 14.685 ± 2.609 for loss of control in the perceived stress scale, with a total score of 30.485 ± 6.384, significantly higher than the control group (P<0.05). Individuals with high psychological stress and those under excessive stress were 6.028 and 19.845 times more prone to developing cancer than those under normal stress, respectively. There was a significant correlation (P<0.05) between stress factors such as life events and emotional experiences and the incidence of colorectal cancer. In univariate analysis, the ratio of suppressed emotions reached 7.864, while in multivariate analysis, the ratio of anxious emotions was as high as 39.913. Conclusion: The study offered fresh perspectives on preventing and managing colorectal cancer, suggesting that when formulating effective prevention and treatment strategies, multiple factors such as social factors, lifestyle habits, and psychological factors should be comprehensively considered, providing new scientific basis for the medical and psychological research of colorectal cancer.
Keywords: Colorectal cancer; Mental health; Mental emotions; Multi-factor analysis; Way of life
INTRODUCTION
Colorectal cancer (CRC) denotes cancerous growths in the colonic mucosal epithelium and is a prevalent form of malignancy within the digestive tract, mainly including colon cancer and rectal cancer [1]. Currently, the overall incidence rate of CRC in China is 24/100000, the incidence rate of rectal cancer accounts for about 60% of the total number of CRC, and the population over 45 years old is the main group. In recent times, the incidence rate of CRC still shows an obvious upward trend, which is closely related to changes in people’s lifestyle and diet [2-3]. The clinical manifestations of CRC are diverse, with common symptoms being changes in bowel habits and stool characteristics. Patients may experience increased frequency of bowel movements, constipation or alternating constipation and diarrhea, accompanied by mucus or pus. In addition, there are systemic manifestations such as abdominal pain, intestinal obstruction, abdominal mass, anemia, emaciation, fatigue, and low-grade fever. At present, the treatment methods for CRC primarily encompass surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy. Radical surgery is the main treatment method, which achieves the goal of cure by clearing tumors and lymph nodes; Targeted therapy and immunotherapy are emerging treatment methods in recent years, which activate the patient’s own immune system to combat tumors [4-5].
Overall, considerable advancements have been achieved in the clinical therapy of CRC. However, the condition of CRC is relatively insidious, and most sufferers are diagnosed with advanced disease. After missing the treatment opportunity, routine clinical treatment does not substantially optimize the patient’s outlook and standard of living. Therefore, actively seeking preventive measures for CRC is particularly important. On the one hand, strengthening the screening and early diagnosis of CRC is an important means to improve treatment effectiveness and patients’ living standards. On the other hand, a deeper understanding of the pathogenesis of CRC is crucial in preventing its onset from the source. At present, existing research results have shown that high-risk factors for CRC include unreasonable dietary structure, unhealthy lifestyle habits, the influence of other chronic diseases, and certain genetic susceptibility [6-7]. In addition, Nardone O M et al. believed that inflammatory bowel disease is a contributing factor for increased CRC. Research found that there were unique molecular differences in colitis related CRC, leading to different event sequences and triggering cancer development [8]. Jain S M et al. also believed that persistent inflammation is a crucial factor in the occurrence of CRC. Based on comprehensive epidemiological and clinical studies, it was found that patients with ulcerative colitis and Crohn’s disease were more prone to developing CRC [9]. Li Q et al. found that the ecological imbalance of intestinal bacteria was an important factor in the occurrence of CRC, among which Clostridium difficile was a risk factor for CRC and could function as an indicator for early detection and prognosis forecasting of CRC, as well as a target for prevention and treatment [10]. Postwala et al. believed that genetic changes in signaling pathways such as Wnt/β-catenin and PI3K/Akt/mTOR occupy a key position in the pathogenesis of CRC, and non-coding RNA is an important participant in genetic regulation and CRC progression, which can be used as a diagnostic and prognostic biomarker [11]. The new biopsychosocial medical model believes that the emergence of diseases arises from the combined influence of biological, environmental, and societal factors. Especially psychological factors such as internal conflicts, life experiences, and emotional states have a significant impact on diseases. Persistent negative emotional states, including stress, anxiety, and depression, can impair an individual’s immune system function, thus elevating the likelihood of disease onset. Moreover, psychological factors may also affect individuals’ perception and coping strategies towards diseases, thereby influencing the development and outcome of the disease. Psychological factors have become a trigger for various diseases [12].
However, in previous studies exploring the relationship between psychological factors and the onset of CRC, cross-sectional surveys were often used, and subjective bias and induced questioning by investigators may increase the subjectivity of the survey results. Moreover, retrospective analysis of CRC patients is affected by time and memory interference, which cannot accurately reflect the true relationship between the onset of CRC and long-term psychological factors. Therefore, in order to further explore the pathogenesis of CRC, the study obtained longitudinal data through a survey questionnaire in the physical psychological social medicine model, and explored the causal relationship between different social factors, life events, emotional experiences, and CRC from the perspectives of social and psychological factors. This furnishes novel perspectives and ideas for the research of CRC medicine and psychology from the perspective of pathogenesis.
The research is divided into three sections. The first section introduces general information and research methods, including basic information about the research subjects, research methods, data processing, etc. The second section elaborates on the impact of different social factors, life events, and emotional experiences on the onset of CRC, and conducts univariate and multivariate regression analysis. The third section explores the influencing factors of CRC incidence under the biological psychological social model, summarizes the research results, and looks forward to future research directions.
1. General information and research methods
1.1 General Information
The research selected CRC patients who received treatment in the outpatient and inpatient departments of a public tertiary hospital in China from January 1, 2016 to December 31, 2019 as the experimental subjects. Healthy individuals without gastrointestinal and digestive system diseases who received treatment at the same hospital were chosen as controls in a 1:1 ratio based on gender and age matching. The survey was conducted from January 1, 2020 to December 31, 2024 to ensure long-term and effective follow-up records. A total of 276 experimental subjects and 388 control subjects were incorporated into the research.
The inclusion criteria for CRC patients are as follows: ① The patient’s age is between 18-70 years old, and there is no gender restriction; ② Patients need to reside in the study area for a long time and be able to independently complete visits or follow ups; ③ Patients meet the diagnostic criteria of CRC and are confirmed through pathological tissue examination; ④ Patients require comprehensive information including detailed medical, personal, and family histories, physical examination results, and complete postoperative pathological data. The exclusion criteria for CRC patients are as follows: ① The research subjects have not undergone histopathological examination; ② Patients who refuse to participate or are unable to ensure normal communication due to cultural or intellectual limitations; ③ Patients who have already experienced recurrence or metastasis, or patients with other serious systemic diseases; ④ Patients who have previously had other tumors; ⑤ Patients with specific diseases or genetic histories, such as familial adenomas or hereditary non polyposis colon cancer; ⑥ Patients with incomplete or inconsistent medical records.
The inclusion criteria for the control group (CG) are as follows: ① The age range is between 18-70 years old, with no gender restrictions. The age and gender should be matched one-to-one with the CRC patient group, and the age difference should not exceed five years; ② Patients need to reside in the study area for a long time and be able to independently complete visits or follow ups; ③ Patients must sign the informed consent form, acknowledging their agreement to participate in the study and undergo the necessary examinations and evaluations; ④ Patients have no history of gastrointestinal and digestive system diseases, including but not limited to CRC, colitis, intestinal polyps, etc. The exclusion criteria for the CG are as follows: ① Tumor patients; ② Patients with a history of gastrointestinal and digestive system diseases, such as CRC, colitis, intestinal polyps, etc; ③ Patients with major diseases or chronic diseases such as heart disease, diabetes and hypertension; ④ Patients with mental or neurological disorders such as depression, anxiety, schizophrenia, etc; ⑤ Patients who have used drugs that may affect gastrointestinal health for a long time or recently should be excluded.
1.2 Research methods
1.2.1 Questionnaire survey
In order to explore the relationship between social factors, life events, emotional experiences, and the onset of CRC in patients, identify possible risk factors and protective factors, a questionnaire survey was conducted from January 1, 2020 to December 31, 2024, after the subjects signed informed consent forms, to collect their basic information. The implementation of the questionnaire can be carried out through face-to-face interviews, telephone interviews, or online surveys, and various strategies can be used to improve the response rate of the questionnaire. The study provided training to investigators involved in questionnaire implementation to guarantee their familiarity with the questionnaire content and survey process. Meanwhile, the study emphasized ethical and privacy issues during the investigation process, maintaining patience and respect during the investigation process to ensure that patients can fully understand and answer the questions in the questionnaire. The questionnaire content is as follows: ① Basic demographic characteristics of society: age, gender, occupation, education level, marital status, place of residence, and economic status of the research subjects; ② Personal past disease history: chronic diseases such as hypertension, diabetes, heart disease, chronic lung disease, gastritis, gastric ulcer, irritable bowel syndrome, Crohn’s disease, chronic diarrhea, mucous bloody stool and other digestive system diseases, history of surgery, hospitalization and drug allergy; ③ Personal and family history of cancer; ④ Menstrual and marital history of female research subjects; ⑤ Dietary situation: whether there is a regular diet, whether there is a preference for certain foods, whether there is a preference for high oil and high salt foods, etc. The types and quantities of vegetables, fruits, meat, soy products, dairy products, etc. consumed daily; ⑥ Mental stress: whether one frequently experiences emotions such as anxiety, depression, tension, and recent stressful events; ⑦ Physical exercise situation: weekly exercise frequency, exercise method, and exercise time, whether regularly participating in leisure activities or social group activities.
1.2.2 Psychological stress investigation
The study first used the Psychosocial Stress Scale (PSS) to investigate the life events and emotional experiences of the subjects. The PSS questionnaire mainly includes four parts: life event, stress response, trait coping style, and social support, involving 44 items at three levels: life event (L), negative emotional experience (NE), positive emotional experience (PE), negative coping (NC), and positive coping (PC). The L item aims to evaluate various life events that an individual has experienced in the past period, such as family changes, job changes, interpersonal conflicts, etc. The NE item focuses on the negative emotional reactions that individuals experience when facing stressful events, such as anxiety, depression, anger, etc. The PE item aims to evaluate individuals’ positive emotional responses, such as optimism, hope, satisfaction, etc., when facing stressful events. The NC item focuses on the NC strategies that individuals adopt when facing stressful events, such as avoidance, denial, self blame, etc. The PCC item aims to evaluate the proactive coping strategies adopted by individuals when facing stressful events, such as seeking support, problem-solving, and adjusting cognition.
Meanwhile, the study used the Chinese Perceived Stress Scale (CPSS) to assess the psychological stress of the research subjects. The CPSS scale includes 14 test items in two dimensions: tension and loss of control. Tension mainly reflects an individual’s anxiety and unease when encountering stressors. The sense of loss of control focuses on an individual’s sense of powerlessness and despair in stressful situations. The CPSS scale employs a 5-point rating system, where higher ratings signify a greater perception of stress by individuals. 14 test items correspond to 5 options, representing different frequencies or degrees, and are assigned scores from 1 to 5 in sequence.
1.3 Data processing
The research requires data processing on the basic information of the research subjects, and the scoring situation is in Table 1.
Table 1 Assignment of points for data processing
| NO. | Scoring items | Difference | Assigned value | NO. | Rating | Difference | Assigned value |
| #01 | Sex | M | 1 | #15 | Educational attainment | Elementary and below | 1 |
| F | 1 | Middle school | 2 | ||||
| #02 | Weight | BMI≤18.5 | 1 | High school | 3 | ||
| 18.5＜BMI＜23 | 2 | Undergraduate and above | 4 | ||||
| BMI≥23 | 3 | #16 | Occupational class | Workers | 1 | ||
| #03 | Marital status | Married | 1 | Farmer | 2 | ||
| Unmarried | 2 | Management | 3 | ||||
| #04 | Age | <50 | 1 | Science and Health | 4 | ||
| 50≤age≤59 | 2 | Individual | 5 | ||||
| 60 ≤ age ≤ 69 | 3 | Other | 6 | ||||
| ≥70 | 4 | #17 | Cigarette smoking | Yes | 2 | ||
| #05 | Concomitant chronic disease status | Yes | 1 | No | 1 | ||
| No | 2 | #18 | Drinking wine | Yes | 2 | ||
| #06 | L | Score ≥3 | 1 | No | 1 | ||
| Score＜3 | 0 | #19 | Physical exercise | Yes | 2 | ||
| #07 | NE | Score≥3 | 1 | No | 1 | ||
| Score＜3 | 0 | #20 | Food flavors | Heavy salt | 1 | ||
| #08 | PC | Score≥3 | 1 | Moderate | 2 | ||
| Score＜3 | 0 | Light | 3 | ||||
| #09 | NC | Value≥3 | 1 | #21 | Frequency of fresh fruit intake | <once/week | 1 |
| Value＜3 | 0 | 1-3 /wk | 2 | ||||
| #10 | PE | Score≥3 | 1 | 4-7 /wk | 3 | ||
| Score＜3 | 0 | >7 /wk | 4 | ||||
| #11 | Frequency of intake of cured fish and cured meat | <once/week | 1 | #22 | Frequency of fresh vegetable intake | <once/week | 1 |
| 1-3 /wk | 2 | 1-3 /wk | 2 | ||||
| ≥4 /wk | 3 | 4-7 /wk | 3 | ||||
| #12 | Frequency of intake of smoked foods | <once/week | 1 | >7 /wk | 4 | ||
| 1-3 /wk | 2 | #23 | Frequency of intake of barbecued meats | <once/week | 1 | ||
| ≥4 /wk | 3 | 1-3 /wk | 2 | ||||
| #13 | Frequency of intake of milk and milk products | <once/week | 1 | 4-7 /wk | 3 | ||
| 1-3 /wk | 2 | >7 /wk | 4 | ||||
| ≥4 /wk | 3 | / | / | / | / | ||
| #14 | Frequency of intake of beans and soy products | <once/week | 1 | / | / | / | / |
| 1-3 /wk | 2 | / | / | / | / | ||
| ≥4 /wk | 3 | / | / | / | / |
1.4 Quality control
The study conducted quality control from three aspects: selection bias, information bias, and confounding bias. Selective bias control: The inclusion and exclusion criteria for research subjects are clearly defined, and the sample is ensured to be representative and homogeneous. The method of random sampling is used to select and divide experimental and CGs, to mitigate the impact of human factors on sample selection; The selection of research subjects is increased as much as possible to ensure that the research results have sufficient statistical validity. Information bias control: Standardized and unified measurement tools and questionnaires are used for data collection; The investigators involved in data collection are trained uniformly, and the order, method, and judgment criteria of questioning are standardized, so that the usage methods and precautions of measurement tools are familiarized to reduce measurement errors. During the data collection and analysis process, blind design was adopted to reduce the subjective factors of investigators and research subjects that may affect the research results. Finally, after the survey is completed, the questionnaire is checked to avoid any errors or omissions in information and obvious logical errors. Control of confounding bias: confounding factors are stratified at different levels to eliminate their impact on research results. This study conducted stratified analysis based on age and gender. Meanwhile, statistical methods such as multiple regression analysis were adopted, and the influence of multiple independent variables and confounding factors on the dependent variable was considered.
1.5 Statistical methods
The experimental data obtained were subjected to numerical statistical analysis using SPSS 25.0 software, with a significance level set . When P<0.05, it was considered statistically significant, when P<0.01, it was considered statistically significant, and when P>0.05, there was no statistically significant difference (SSD). The basic characteristics of social demographics were analyzed using descriptive statistics. Partial results were expressed in the form of “mean ± standard deviation”. For data not conforming to a normal distribution, the Mann-Whitney U test was applied, whereas for normally distributed data, the t-test was utilized. Single factor analysis used chi-square test, while multiple factor analysis used conditional logistic regression analysis. Odds Ratio (OR) and 95% Confidence Interval (95% CI) were employed to describe the strength and reliability of the association between variables. In addition, the data for statistical analysis needed to undergo preprocessing operations such as data cleaning, missing value processing, and outlier processing, and appropriate statistical methods should be selected based on the distribution characteristics and research objectives of the data.
2. Results
2.1 Quality inspection of scales
664 questionnaires were distributed and 594 were collected, with an effective rate of 89.46%. The study employed the Cronbach’s alpha (CA) coefficient to confirm the true reliability of the questionnaire sample. When the CA coefficient is greater than 0.6, the reliability is considered acceptable; When the CA coefficient is greater than 0.8, it indicates good reliability. In Table 2, the CA coefficient test value was 0.943, revealing that the scale had high reliability and the survey data was authentic and reliable. The Corrected Item Total Correlation (CITC) was greater than 0.2, indicating good consistency between the items and the overall scale.
Table 2 Results of the Cronbach’s alpha test
| Questionnaire indicators | Mean value of the scale | Scaled variance | CITC | CA |
| Sex | 11.055 | 23.494 | 0.503 | 0.943 |
| Weight | 11.515 | 23.716 | 0.324 | |
| Marital status | 11.335 | 23.909 | 0.369 | |
| Age | 11.736 | 25.788 | 0.643 | |
| Concomitant chronic disease status | 11.886 | 25.129 | 0.638 | |
| L | 11.286 | 24.722 | 0.376 | |
| NE | 11.066 | 24.196 | 0.670 | |
| PC | 11.423 | 25.843 | 0.384 | |
| NC | 11.635 | 24.782 | 0.691 | |
| PE | 11.848 | 24.290 | 0.578 | |
| Frequency of intake of cured fish and cured meat | 11.901 | 25.458 | 0.363 | |
| Frequency of intake of smoked foods | 11.379 | 23.884 | 0.468 | |
| Frequency of intake of milk and milk products | 11.228 | 24.829 | 0.434 | |
| Frequency of intake of beans and soy products | 11.232 | 24.963 | 0.439 | |
| Educational attainment | 11.942 | 23.867 | 0.303 | |
| Occupational class | 11.977 | 23.971 | 0.447 | |
| Cigarette smoking | 11.461 | 25.777 | 0.335 | |
| Drinking wine | 11.482 | 25.638 | 0.309 | |
| Physical exercise | 11.185 | 24.274 | 0.671 | |
| Food flavors | 11.773 | 25.056 | 0.363 | |
| Frequency of fresh fruit intake | 11.404 | 25.642 | 0.400 | |
| Frequency of fresh vegetable intake | 11.973 | 23.056 | 0.398 | |
| Frequency of intake of barbecued meats | 11.585 | 24.106 | 0.331 |
In addition, validity analysis was conducted based on Bartlett sphericity and Kaiser Meyer Olkin (KMO) test, and the experimental outcomes are in Table 3. In Table 3, the KMO test value was 0.903, which was close to 1, indicating that the variable data was suitable for factor analysis. The Bartlett sphericity test statistic was 1892.329, with a significance level of 0.000, P<0.001, rejecting the spherical hypothesis and assuming significant correlation (SC) between variables and that factor analysis was suitable.
Table 3 Results of validity analysis
| Validity test | ||
| KMO number of sample suitability quantities | / | 0.903 |
| Bartlett’s test of sphericity | Approximate chi-square | 1892.329 |
| Degrees of freedom | 287 | |
| Significance | 0.000 | |
2.2 Balance test
The experimental subjects who participated in the questionnaire survey all met the inclusion criteria, and subsequent data statistics were conducted using this group as the research object. The general situation of the research object is shown in Table 4. In Figure 4, there were no SSDs (P>0.05) in gender, age, educational level, occupational status, and marital status between the study group (SG) and the CG of CRC patients. The age and gender balance between the SG and the CG was better.
Table 4 Comparison of the general conditions of the study population
| Project | SG | CG | Consistency test | P-value | |
| Total | 276 | 388 | / | / | |
| Sex | Male | 156 | 203 | 16.975 | 0.876 |
| Female | 120 | 185 | |||
| Marital status | Married | 269 | 380 | 1.766 | 0.654 |
| Unmarried | 7 | 8 | |||
| Age | <50 | 43 | 56 | 17.970 | 0.746 |
| 50≤age≤59 | 66 | 86 | |||
| 60 ≤ age ≤ 69 | 87 | 113 | |||
| ≥70 | 80 | 133 | |||
| Concomitant chronic disease status | Yes | 246 | 342 | 4.896 | 1.273 |
| No | 30 | 46 | |||
| Educational attainment | Elementary and below | 87 | 102 | 7.975 | 0.106 |
| Middle School | 77 | 82 | |||
| High School | 79 | 128 | |||
| Undergraduate and above | 33 | 76 | |||
| Occupational class | Workers | 87 | 124 | 5.542 | 0.246 |
| Farmer | 47 | 103 | |||
| Management | 56 | 37 | |||
| Science and Health | 55 | 22 | |||
| Individual | 31 | 102 | |||
| Other | 87 | 124 | |||
2.3 Analysis of social factors
2.3.1 Single factor analysis of smoking, alcohol consumption, and CRC patients
The outcomes of the univariate analysis of smoking, alcohol consumption, and CRC patients are in Table 5. In Table 5, in the chi-square test based on non-smoking and alcohol consumption, there was no SSD (P>0.05) between smoking, alcohol consumption, and the incidence of CRC; However, there was an SSD (P<0.01) between the number of cigarettes smoked and the incidence of CRC. When smoking more than 20 cigarettes a day, the OR reached 4.651; In contrast, there was no SSD between the types of drinking and the incidence of CRC (P>0.05), but Baijiu would increase the risk of CRC, with an OR of 2.505.
Table 5 Univariate analysis of smoking, alcohol consumption and CRC
| Factor | Sum | SG | Sum | CG | |||||||
| P | OR | 95%CI | P | OR | 95%CI | ||||||
| Lower | Upper | Lower | Upper | ||||||||
| Smoking | No | 65 | / | 1.000 | / | / | 124 | / | 1.000 | / | / |
| Used to smoke | 55 | 0.868 | 0.837 | 0.367 | 2.062 | 52 | 0.945 | 1.295 | 0.482 | 3.535 | |
| Current smoker | 156 | 0.053 | 0.537 | 0.338 | 0.905 | 212 | 0.037 | 1.834 | 1.208 | 3.930 | |
| Number of smoked | ≤10 day | 79 | 0.146 | 0.411 | 0.124 | 1.864 | 96 | 0.119 | 2.397 | 0.864 | 6.766 |
| 10－20 day | 62 | 1.303 | 0.561 | 0.217 | 1.210 | 82 | 0.203 | 1.875 | 0.817 | 3.471 | |
| ≥20 day | 70 | 0.001 | 4.651 | 1.516 | 12.992 | 86 | 0.001 | 0.247 | 0.092 | 0.451 | |
| Alcohol | No Alcohol | 123 | / | 1.000 | / | / | 201 | / | 1.000 | / | / |
| Drinking alcohol | 153 | 0.083 | 0.653 | 0.395 | 1.187 | 187 | 2.363 | 1.697 | 0.921 | 2.966 | |
| Types of alcohol | White wine | 56 | 0.126 | 2.505 | 0.834 | 7.709 | 28 | 0.694 | 0.399 | 0.130 | 1.539 |
| Beer | 82 | 0.103 | 0.275 | 0.069 | 1.304 | 62 | 0.693 | 3.465 | 0.781 | 15.816 | |
| Wine | 15 | 1.000 | 0.894 | 0.154 | 3.439 | 97 | 1.000 | 1.575 | 0.298 | 6.045 | |
The impact analysis of different levels of alcohol consumption and smoking on CRC is shown in Figure 1. As shown in Figure 1 (a), there was no SSD (P>0.05) in the impact of smoking intensity on the incidence of CRC at various levels of alcohol consumption; As shown in Figure 1 (b), there was no SSD (P>0.05) in the effect of alcohol consumption level on the incidence of CRC under different smoking levels. However, when the alcohol consumption level exceeded 15g/d, the risk of CRC increased by at least 56.89%.
Figure 1 Effect of smoking and alcohol consumption on CRC
2.3.2 Univariate analysis of dietary factors and CRC patients
The outcomes of the univariate analysis of dietary factors and CRC patients are in Table 6. As shown in Table 6, dietary habits, flavors, smoked foods, pickled fish, cured meat, and grilled meat were all risk factors for CRC. Fruits, milk and dairy products, beans and soy products, and vegetables were protective factors in reducing the incidence of CRC. The likelihood of developing CRC was highest due to excessive consumption of smoked foods, with an OR value of 32.417.
Table 6 Univariate analysis of dietary factors and patients with CRC
| Diet | Regression coefficient | Standard error | Wald | P-value | OR-value | 95%CI | |
| Lower | Upper | ||||||
| Dietary habits | 2.282 | 0.322 | 11.509 | 0.001 | 3.058 | 1.651 | 8.710 |
| Dietary tastes | 2.935 | 0.364 | 10.950 | 0.002 | 3.263 | 1.649 | 7.456 |
| Fruits | -1.352 | 0.421 | 12.462 | 0.004 | 1.272 | 1.056 | 9.321 |
| Smoked foods | 2.561 | 0.583 | 14.300 | 0.004 | 32.417 | 1.407 | 11.123 |
| Cured fish, cured meat | 3.504 | 0.567 | 13.807 | 0.002 | 29.737 | 9.501 | 39.241 |
| Milk and dairy products | -2.441 | 0.511 | 18.911 | 0.004 | 1.758 | 1.232 | 7.661 |
| Beans and soy products | -2.226 | 0.431 | 16.945 | 0.002 | 2.366 | 1.831 | 11.037 |
| Vegetables | -2.420 | 0.724 | 10.826 | 0.005 | 2.350 | 1.515 | 10.604 |
| Grilled meats | 4.682 | 0.959 | 22.555 | 0.003 | 17.241 | 5.836 | 54.662 |
2.3.3 Exercise, body mass index, and CRC
The distribution of exercise and body mass index of the two groups of research subjects is shown in Figure 2. The physical exercise methods of the research subjects included running, walking, ball sports, etc., with an effective exercise duration of 30 minutes per session. As shown in Figure 2 (a), there was an SSD (P<0.05) between the SG and the CG in regard to weekly physical exercise. Meanwhile, as shown in Figure 2 (b), there was an SSD (P<0.05) in the distribution of body mass index between the two groups of research subjects.
Figure 2 Exercise, body mass index and CRC
Note:“*” denotes P<0.05 and “**” denotes P < 0.01.
The estimated results of exercise, body mass index, and risk of CRC are shown in Table 7. As shown in Table 7, the risk of CRC in obese individuals was 6.937 times higher than that in non-obese individuals, and the risk of CRC in non exercisers was 3.163 times higher than that in exercisers. Obesity and exercise were key factors affecting the incidence of CRC.
Table 7 Exercise, body mass index, and estimated risk of CRC development
| Category | Standard | SG | CG | P-value | OR-value | 95%CI | |
| Lower | Upper | ||||||
| Non-obese | BIM<28 | 78 | 296 | 0.000 | 6.937 | 3.526 | 11.228 |
| Obese | BIM≥28 | 198 | 92 | ||||
| Exercise | >4/wk | 59 | 243 | 0.000 | 3.163 | 1.552 | 12.268 |
| Non-exercise | ≤4/wk | 217 | 145 | ||||
2.4 Psychological factor analysis
2.4.1 Life stress, mental stimulation, and CRC
The study investigated the long-term stress and mental stimulation experienced by the subjects, and the results of the univariate analysis of their association with the onset of CRC are in Table 8. In Table 8, there was an SSD (P<0.05) in the level of life stress between the two groups of subjects. The risk of CRC increased by 3.244 times for those who experienced long-term stress, and by 2.552 times for those who experienced mental stimulation. It can be inferred that long-term life stress, frequent mental stimulation, low life satisfaction, and low social support could potentially be linked to a higher chance of CRC.
Table 8 Univariate analysis of life stress, mental stimulation and CRC development
| Category | Standard | SG | CG | P-value | OR-value | 95%CI | |
| Lower | Upper | ||||||
| Pressure of living | Never | 48 | 66 | 0.000 | 4.244 | 1.195 | 10.788 |
| Occasionally | 98 | 242 | |||||
| Often | 130 | 80 | |||||
| Mental stimulation | Yes | 217 | 245 | 0.002 | 3.552 | 1.268 | 12.164 |
| No | 171 | 143 | |||||
2.4.2 Statistical comparison of CPSS scale
The statistical comparison of CPSS scales for different groups of subjects is shown in Figure 3. In Figure 3 (a), there was an SSD (P<0.05) between the SG and the CG in regard to tension, loss of control, and CPSS scale scores. The SG scored 15.800 ± 4.800 for tension, 14.685 ± 2.609 for loss of control, and a total score of 30.485 ± 6.384, which was significantly higher than the CG. In Figure 3 (b), the SG was divided into a youth group and an elderly group. There were SSDs (P<0.05) in terms of tension, loss of control, and CPSS score. The youth group had higher scores in various aspects than the elderly group, and the total CPSS score reached 35.834 ± 2.533.
Figure 3 Statistical Comparison of CPSS Scales
2.4.3 Psychological stress and CRC
According to the CPSS scale score, psychological stress was divided into normal stress, high stress, and excessive stress. The chi square test was conducted on the two groups of subjects, and the outcomes are in Table 9. In Table 9, there was no SSD (P>0.05) in stress levels between CRC and rectal cancer patients among CRC patients; However, there was an SSD (P<0.05) in the comparison of pressure levels between the research group and the CG. The distribution of subjects with high or excessive pressure in the research group reached 45.652% and 35.507%, respectively. The results of univariate analysis showed that psychological stress was an important factor leading to the onset of CRC, with individuals under high stress and those under excessive stress being 6.028 and 19.845 times more prone to developing CRC than those under normal stress, respectively.
Table 9 Univariate analysis of psychological pressure and patients with CRC
| Pressure situation | Regression coefficient | Standard error | Wald | P-value | OR-value | 95%CI | |
| Lower | Upper | ||||||
| Larger | 1.645 | 0.435 | 30.610 | 0.021 | 6.028 | 2.861 | 9.661 |
| Excessive | 2.939 | 0.708 | 17.957 | 0.002 | 19.845 | 4.352 | 76.097 |
| Pressure condition | SG | Percentage | CG | Percentage | P-value | / | / |
| Normal | 52 | 18.841% | 212 | 54.649% | 0.000 | / | / |
| Large | 126 | 45.652% | 128 | 32.990% | / | / | |
| Excessive | 98 | 35.507% | 48 | 12.371% | / | / | |
| Pressure | Colon | Percentage | Rectum | Percentage | P-value | / | / |
| Normal | 32 | 11.594% | 20 | 7.246% | 0.989 | / | / |
| Large | 59 | 21.377% | 67 | 24.275% | / | / | |
| Excessive | 52 | 18.841% | 46 | 16.667% | / | / | |
2.5 PSS scale statistical results
2.5.1 Univariate analysis of stress factors
The univariate analysis of stress factors such as life events and emotional experiences in the PSS scale and CRC is shown in Table 10. In Table 10, there was an SC (P<0.05) between the occurrence of CRC and factors such as the death of family members, interpersonal communication barriers, child problems, major family illnesses, and personal health issues in life events. The OR values for the deaths of family members and major illnesses of family members were as high as 13.664 and 11.373, respectively. Among the emotional experience factors, depression, despair, anxiety, and happiness showed an SC with the onset of CRC (P<0.05). There was an SC (P<0.05) between avoiding, suppressing, and being alone in coping with emotions and the onset of CRC, with an OR value of 7.864 for suppressing emotions.
Table 10 Univariate analysis of stress factor and patients with CRC
| Stress factor | Wald | P-value | OR-value | 95%CI | ||
| Lower | Upper | |||||
| L2 | Death of a loved one | 5.809 | 0.009 | 13.664 | 1.763 | 21.608 |
| L4 | Interpersonal disorders | 8.775 | 0.039 | 10.274 | 2.735 | 55.691 |
| L9 | Child problems | 4.905 | 0.012 | 3.612 | 1.104 | 6.307 |
| L12 | Major family illness | 13.639 | 0.031 | 11.373 | 2.199 | 13.687 |
| L13 | Personal health problems | 5.616 | 0.033 | 2.570 | 1.581 | 8.823 |
| NE18 | Depression | 4.770 | 0.003 | 3.176 | 1.101 | 12.821 |
| NE23 | Despair | 6.361 | 0.043 | 4.343 | 1.854 | 4.617 |
| NE24 | Anxiety | 10.901 | 0.012 | 4.862 | 2.220 | 13.076 |
| PE16 | Cheerfulness | 4.640 | 0.043 | 0.661 | 1.402 | 4.446 |
| PC42 | Avoidance | 3.268 | 0.011 | 0.306 | 0.076 | 0.908 |
| NC35 | Repressed emotions | 2.974 | 0.003 | 7.864 | 1.194 | 14.532 |
| NC43 | Solitude | 8.325 | 0.004 | 7.177 | 1.132 | 11.175 |
2.5.2 Multi factor analysis of stress factors
The multifactorial analysis of stress factors such as life events and emotional experiences in the PSS scale and CRC is shown in Table 11. In Table 11, there was an SC (P<0.05) between the occurrence of CRC and factors such as the death of family members, interpersonal communication barriers, child problems, major family illnesses, and personal health issues in life events. The OR value for interpersonal communication disorders was as high as 21.839, and the OR value for major family diseases was as high as 15.454. Among the emotional experience factors, depression, despair, anxiety, happiness, as well as avoidance, suppression, and solitude in coping emotions, were significantly correlated with the onset of CRC (P<0.05), with an OR value of 39.913 for anxiety emotions.
Table 11 Multivariate analysis of stressors and CRC patients
| Stress factor | Wald | P-value | OR-value | 95%CI | ||
| Lower | Upper | |||||
| L2 | Death of a loved one | 3.407 | 0.038 | 14.692 | 1.447 | 20.984 |
| L4 | Interpersonal disorders | 4.480 | 0.025 | 21.839 | 1.202 | 30.396 |
| L9 | Child problems | 5.526 | 0.035 | 13.143 | 1.507 | 23.501 |
| L12 | Major family illness | 9.981 | 0.042 | 15.454 | 1.893 | 28.291 |
| L13 | Personal health problems | 10.417 | 0.014 | 4.431 | 0.657 | 15.039 |
| NE18 | Depression | 9.622 | 0.021 | 14.813 | 1.903 | 17.815 |
| NE23 | Despair | 11.803 | 0.010 | 21.959 | 1.927 | 33.425 |
| NE24 | Anxiety | 12.508 | 0.049 | 39.913 | 1.531 | 47.803 |
| PE16 | Cheerfulness | 14.112 | 0.009 | 0.308 | 0.223 | 8.706 |
| PC42 | Avoidance | 3.407 | 0.001 | 0.447 | 0.192 | 4.984 |
| NC35 | Repressed emotions | 7.480 | 0.015 | 5.839 | 2.202 | 10.396 |
| NC43 | Solitude | 9.526 | 0.045 | 1.143 | 1.007 | 13.501 |
2.5.3 Regression analysis of stress factor scores
The regression analysis results of different stress scores and CRC are in Table 12. In Table 12, there was no SC between the scores of different stress factors and the onset of CRC (P>0.05). When the total score of PSS scale was greater than 33 and ≤ 15, there was an SC with the incidence of CRC (P<0.05)
Table 12 Regression analysis of different stress scores with CRC
| Items | Wald | P-value | OR-value | 95%CI | ||
| Lower | Upper | |||||
| L | 10.921 | 0.146 | 1.359 | 0.399 | 6.408 | |
| NE | 10.780 | 0.105 | 2.857 | 0.487 | 6.014 | |
| PE | 13.920 | 0.204 | 1.489 | 0.308 | 8.790 | |
| NC | 7.563 | 0.404 | 2.929 | 0.448 | 9.408 | |
| PC | 8.016 | 0.302 | 1.286 | 0.709 | 7.867 | |
| Totals | Total score≤15 | 0.005 | 0.003 | 2.232 | 0.517 | 4.301 |
| 15<Total score≤33 | 0.000 | 0.504 | 0.727 | 0.571 | 5.981 | |
| Total score >33 | 0.005 | 0.001 | 1.034 | 0.857 | 8.160 | |
3. Discussion
CRC is a malignant tumor that occurs on the inner wall of the colon or rectum. Prevention, screening, and early diagnosis and treatment of CRC are effective measures to reduce the mortality rate of CRC in the population. In recent times, the incidence rate and mortality of CRC have been on the rise, occupying a high position in all malignant tumors. Moreover, the incidence rate in urban areas is significantly higher compared to rural regions, and a majority of patients are diagnosed at the middle to late stages of the disease. The diagnosis and treatment process of CRC involves surgery, chemotherapy, radiotherapy, and pathological evaluation. Early stage patients have a lower risk, and surgical resection can achieve basic cure; However, most late stage patients require systemic treatments such as chemotherapy, targeted therapy, and immunotherapy, resulting in lower survival rates. Therefore, early prevention and regular screening of CRC are particularly important [13-14]. The pathogenesis of CRC is a complex multifactorial and multi-step process involving multiple interactions such as genetics, epigenetics, environment, and microbiota. Conventional medical researchers believe that the combined effects of lifestyle and environmental factors, mutations in key genes, chronic inflammation and immune disorders, as well as the role of gut microbiota, may gradually promote the evolution from adenoma to cancer by activating pro cancer pathways, inhibiting tumor suppression mechanisms, reshaping the microenvironment, and evading immune surveillance [15]. For example, Niekamp et al. discussed and found that diet, gut microbiota, and their metabolites were crucial environmental factors influencing the progression of CRC. The main microbial metabolites, such as short chain fatty acids, bile acid derivatives, indole metabolites, etc., could regulate intestinal cells, affect intestinal barriers, immunity, chronic inflammation, and tumorigenesis [16]. Liu et al. comprehensively analyzed the effects of genetic, epigenetic, and tumor associated microbial factors on immune cell infiltration and the mechanism of CRC occurrence. Research found that the composition and structure of the tumor microbiome were the main factors affecting the survival rate differences of immune cell infiltration subtypes, and were associated with multiple immune cells and genes. Clostridium was enriched in insensitive CRC patients, which may affect the response to immune checkpoint blockade therapy. The importance of tumor associated microorganisms in CRC immunotherapy strategies and prognosis was emphasized [17].
In recent years, as medical science has progressed and people’s comprehension of health has deepened, under the biopsychosocial medical model, people have realized that the occurrence, development, and outcome of diseases are not only influenced by biological factors, but also closely related to psychological factors and social environment. Li C et al. pointed out that an individual’s psychological state, dietary habits, and exercise frequency are intricately linked to cancer risk and prognosis, and proposed “humanistic health management”, emphasizing self health management as the core, and creating tailored, comprehensive strategies for cancer prevention and management through comprehensive assessment of personal lifestyle habits, psychological and health status [18]. In addition, Christodoulidis G et al. pointed out that the incidence rate and mortality of cancer, especially gastrointestinal cancer, increased, and patients often faced psychological challenges, of which the prevalence of depression was as high as 57%. Depression not only affects the psychological state, but also promotes cancer progression by activating physiological mechanisms. Therefore, a comprehensive strategy is needed to tackle the psychological impact of cancer by implementing regional interventions and enhancing surveillance for depression [19].
However, previous studies on the relationship between psychological factors and cancer incidence have mostly used cross-sectional surveys, which are susceptible to subjective bias and induced questioning by investigators, leading to increased subjectivity in the results. Meanwhile, retrospective analysis of CRC patients is limited by time and memory interference, making it difficult to accurately reveal the true association between cancer incidence and long-term psychological factors [20-21]. In order to deepen the understanding of the pathogenesis of CRC, this study used a physical psychological social medicine model and collected longitudinal data through a survey questionnaire to explore the causal relationship between CRC and social and psychological factors. The research outcomes indicated that there was no SSD (P>0.05) between smoking, alcohol consumption, and the incidence of CRC. After smoking more than 20 cigarettes, there was an SSD (P<0.01) in the incidence of CRC, with an OR of 4.651. Moreover, Baijiu would increase the risk of CRC, with an OR of 2.505. The current medical consensus is that the carcinogenic chemicals inhaled during smoking may affect the colorectal mucosa, leading to cancer, while the alcohol metabolite acetaldehyde has carcinogenic effects and is one of the reasons why alcohol consumption increases the risk of CRC [22]. Existing studies show that dietary patterns significantly influence the risk of cancerr. Excessive consumption of red and processed meats raises the likelihood of developing cancer, while increasing the intake of fruits, vegetables, whole grains, and dietary fiber helps reduce the risk [23]. This is consistent with the research findings, which found that dietary habits, flavors, smoked foods, pickled fish, cured meat, and grilled meat were all risk factors for CRC. The risk of CRC was highest due to excessive consumption of smoked foods, with an OR value of 32.417. The study found that there were SSDs (P<0.05) in weekly physical exercise and body mass index distribution between the SG and the CG. Obese individuals had a 5.937-fold increased risk of developing CRC, while non-exercisers had a 2.163-fold increased risk of developing CRC. This was mainly because obesity promoted carcinogenesis through mechanisms such as insulin resistance, hyperinsulinemia, chronic low-grade inflammation, and oxidative stress [24-25].
In addition, the study found that there was an SSD (P<0.05) in the level of life stress between the SG and the CG. The risk of CRC increased by 3.244 times for those who experienced long-term stress, and by 2.552 times for those who experienced mental stimulation. The tension score of the research group was 15.800 ± 4.800, the loss of control score was 14.685 ± 2.609, and the total score was 30.485 ± 6.384. There was an SSD compared with the CG (P<0.05), and the scores of various items in the young group were higher than those in the elderly group; Psychological stress is also an important factor leading to the onset of CRC, with individuals under high and excessive stress being 6.028 and 19.845 times more likely to develop CRC than those under normal stress, respectively. Moreover, stress factors such as life events and emotional experiences showed an SC (P<0.05) with the onset of CRC in univariate and multivariate analysis. Life events such as the death of a loved one, interpersonal communication barriers, child problems, major family illnesses, and personal health issues, as well as emotional experience factors such as depression, despair, anxiety, happiness, and avoidance, suppression, and solitude in coping with emotions, all increased the risk of CRC. However, there was no SC (P>0.05) between the scores of different stress factors and the onset of CRC.
In short, there is a close relationship between psychological factors and the emergence and progression of CRC. By regulating emotions, maintaining a positive and optimistic attitude, and regularly undergoing intestinal examinations, the risk of CRC can be reduced. The research results can provide scientific basis for psychological intervention of CRC patients. By understanding patients’ life events and emotional experiences, personalized psychological intervention plans can be developed to help patients alleviate negative emotions such as anxiety and depression, and improve their quality of life. However, this study did not conduct an exclusion analysis for confounding factors, and future research can investigate this in more depth.
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