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Abstract

Background:

Cancer remains a significant public health problem in China, with new cases and cancer-related deaths increasing in recent years. This study examines the dietary habits, smoking, and alcohol consumption patterns among Chinese patients with cancer, and explores factors influencing these lifestyle behaviors.

Methods:

Secondary data analysis was conducted on a cross-sectional survey of 287 cancer patients from an oncology outpatient clinic in central China. Patients self-reported their current dietary habits, smoking, and alcohol use and recalled their habits prior to their cancer diagnosis. Responses were assessed using a Likert scale ranging from “never = 0” to “often = 3.” The survey specifically measured the frequency of consuming red meat, seafood, milk, tofu, spicy foods, and “balanced yin-yang foods,” as well as alcohol consumption and smoking. Data were analyzed using descriptive statistics, Wilcoxon signed rank tests, and logistic regression.

Results:

Patients reported significant reductions in smoking and alcohol consumption post-diagnosis, with a 60% decrease compared to pre-diagnosis levels. Dietary changes included reduced intake of red meat, seafood, tofu, spicy foods, and milk, alongside increased adherence to a balanced yin-yang diet. Both Cultural/TCM beliefs and symptom-related factors significantly shape those lifestyle behaviors. The influence of TCM was particularly notable. Patients with strong TCM beliefs were associated with reduced alcohol consumption and decreased intake of seafood, tofu, and milk.

Conclusions:

Following a cancer diagnosis, Chinese patients made significantnotable changes to their smoking, alcohol consumption, and dietary habits; adopting healthier lifestyle behaviors. Oncology physicians and nurses should adhere to updated clinical guidelines on nutrition in cancer survivorship and integrate TCM principles to provide tailored lifestyle education and support.

Keywords

cancer lifestyle dietary habits smoking alcohol consumption traditional Chinese medicine

Background

Cancer remains a significant public health problem in China, with new cancer cases and cancer-related deaths continuing to rise compared to previous years¹ Many cancer cases and related deaths are attributed to potentially modifiable lifestyle factors, including diet, alcohol consumption, smoking, and physical activity.² High adherence to established nutrition and physical activity cancer prevention guidelines has been consistently associated with significant reductions of 10% to 61% in overall cancer incidence and mortality across various cancer types.^3,4 Healthy diets and regular exercise have demonstrated numerous benefits, including prolonged survival, improved quality of life, and reduced cancer recurrence among survivors.⁵

The National Comprehensive Cancer Network (NCCN) and the American Cancer Society recommend that patients eat a healthy diet pattern with a preference for plant-based diet patterns.^5,6 In the Chinese diet, topics such as red meat, seafood, milk, tofu, spicy food, and yin-yang dietary balance are both controversial and culturally significant, as many Chinese people believe that regulating the intake of these foods can reduce cancer risk and mortality. Research has shown that high red meat consumption is positively associated with an increased risk of multiple cancers.⁷ Similarly, seafood intake has been linked to higher mercury levels, potentially elevating colorectal cancer risk, although the relationship between specific seafood and cancer remains uncertain.⁸ The effect of dairy on cancer risk is also inconsistent. However, a recent 11-year prospective study involving 0.5 million Chinese participants found higher dairy intake to be associated with increased risks of liver cancer, female breast cancer, and possibly lymphoma.⁹ A common misconception persists that soy products increase cancer risk, despite evidence demonstrating that soy consumption reduces overall cancer risk and mortality.^10,11 The relationship between spicy food and cancer risk is mixed. While some studies suggest capsaicin, the active compound in chili peppers, may possess anti-cancer properties,¹² others indicate that frequent consumption of spicy, or hot foods elevate the risk of esophageal or gastric cancer over time. In Traditional Chinese Medicine (TCM), yin and yang foods help balance the body’s energy. Eating the right balance of these foods “yang” foods (which are typically warm or hot in nature, such as red meat and spicy dishes) with “yin” foods (which are cool or cold in nature, such as fruits, leafy vegetables, and dairy products) is considered vital for maintaining internal equilibrium, maintain health and preventing illness.^13,14 Given the limited research on these dietary habits among cancer patients in China, further study is essential.

Smoking is another predominant cancer risk factor in China, where tobacco use is notably high, particularly among men.¹⁵ Tobacco smoking is estimated to account for more than 20% of all cancer deaths in this country¹⁶ Smoking significantly increases the risk of several cancers, including lung, esophageal, and head and neck cancers.^15,17 Similarly, alcohol consumption contributes to rising cancer prevalence in China, with a notable link to liver cancer associated with heavy drinking and obesity.^18,19 Cancer survivorship guidelines consistently emphasize the importance of quitting smoking and limiting alcohol consumption to reduce all-cause mortality among patients with cancer.^5,6,10 Smoking and alcohol use among cancer survivors in China remain critical health concerns. This underscores the need for continued examination of these behaviors.

Despite growing evidence supporting the importance of lifestyle changes (eg, dietary habits, smoking, and alcohol use) in cancer populations globally, the factors influencing these lifestyle behaviors among cancer survivors are not fully understood. Sociodemographic factorsaffect dietary and substance use behaviors among survivors.²⁰ Depression and anxiety have been linked to increased smoking and alcohol consumption, potentially exacerbating health issues for cancer patients.²¹ Treatment-related side effects, such as altered taste, reduced appetite, nausea, vomiting, and constipation, also impact eating habits.²² Additionally, cultural beliefs and traditions significantly shape dietary choices among cancer survivors.²³ In the Chinese population, many cancer patients believe in the effects of TCM and use herbs, acupuncture, and moxibustion, during treatment.²⁴ Systematic reviews and meta-analyses have shown that Chinese herbal medicine, when used as an adjuvant or complementary therapy, can significantly reduce the side effects of chemotherapy and radiotherapy, inhibit tumor growth, enhance chemotherapy response, and improve patients’ quality of life.^25,26 It is common for Chinese cancer patients to use traditional Chinese medicine (TCM) alongside conventional treatments such as chemotherapy, surgery, and radiotherapy. In a survey of 525 cancer patients across 35 hospitals in Central China, over 90% reported using Chinese patent medicine.²⁷ However, few studies have explored the impact of TCM and cultural beliefs on dietary habits, smoking, and alcohol use among Chinese cancer survivors. Addressing these gaps in knowledge could lead to more personalized and effective strategies for improving cancer survivorship through lifestyle modifications.

Therefore, it is crucial to study the lifestyles behaviors, including dietary habits, smoking, and alcohol use among Chinese cancer patients, identify potential changes before and after cancer diagnosis, and explore the factors influencing these lifestyle behaviors post-cancer diagnosis.

Methods

Research Design, Patient Recruitment, and Protection of Human Subjects

This study employed a secondary data analysis approach, utilizing existing research data to address a new research question distinct from the original study. The original data came from a cross-sectional survey designed to investigate common Traditional Chinese Medicine (TCM) approaches, the perceived effectiveness of TCM in symptom relief and/or quality of life improvement among Chinese patients with cancer receiving outpatient care, and the potential effects of sociodemographic and clinical variables (eg, cancer stage, comorbidities, treatments) on the specific choices of TCM. Findings from the original study were published previously.²⁴

Although lifestyle behavior variables, such as diet, smoking, alcohol consumption, and exercise, were collected in the original study, they were not included as key research variables. In this secondary analysis, researchers focused on these lifestyle behaviors, examining dietary habits, smoking, alcohol consumption, and their potential influencing factors.

A total of 287 patients were recruited from the oncology outpatient clinic of a teaching hospital in central China. Of the 362 eligible patients, 302 (83.4%) agreed to participate. After excluding 15 participants who withdrew or returned incomplete questionnaires, the final sample size was 287, which has adequate power according to the simulation study by Taylor et al.²⁸ The detailed sample size calculation result was published previously.²⁴ The study protocol was approved by the Institutional Review Board of the teaching hospital and the affiliated university of the corresponding author. Eligible participants were required to self-identify as Chinese, be aged 18 years or older, have a current cancer diagnosis, and possess the ability to speak and understand Mandarin Chinese. Patients who did not meet these criteria were excluded. Data collection was carried out by a research assistant trained in medical ethics, who remained present in the outpatient clinic during the entire process. The amount of missing data was minimal, as the research assistant checked each questionnaire on-site at the time of completion. In rare cases where item-level data were missing, values were resolved by referencing other responses from the same participant, based on logical or clinical consistency. No statistical imputation methods were applied.

Measurement

The variables included sociodemographics, clinical information, TCM beliefs, smoking and alcohol use, dietary habits, and symptom distress. The researcher team, in consulting with 2 TCM practitioners, developed their own questionnaire to assess TCM beliefs, smoking, alcohol use, and dietary habits, given that there are no satisfactory instruments that assess TCM beliefs and lifestyles above. A 0 to 3 Likert scale was used because the Likert scale is one of the most reliable ways to measure opinions, perceptions, and behaviors. The corresponding author had experience developing a 0 to 3 Likert scale to measure the effectiveness of mindful sitting meditation in patients with cancer.²⁹ Symptom distress was assessed by The Simplified Chinese version of the Memorial Symptom Assessment Scale—Short Form (MSAS-SF-SC).

Sociodemographic, Clinical Information, and Culture/Traditional Chinese Medicine

Sociodemographic and clinical characteristics included age, gender, health insurance status, ethnic group, income, marital status, education level, employment status, family income, comorbidities, type and stage of cancer, cancer recurrence or metastasis status, and treatment information (eg, surgery, chemotherapy, radiation). Beliefs in TCM for cancer were assessed on a 0 to 3 scale, with 0 representing “not believe at all” and 3 representing “strongly believe.” Patients also indicated whether they used herbs for cancer management (Yes or No). Detailed assessments of TCM beliefs and practices were previously reported.²⁴

Diet Habits

Patients self-reported their current (post-diagnosis) dietary habits and recalled their pre-diagnosis habits using a 4-point Likert scale: 0 = never, 1 = occasionally (eg, social or less than once per week), 2 = sometimes (eg, 1-3 times per week), and 3 = often (eg, daily or nearly daily).The survey assessed the frequency of consuming culturally significant food groups, including red meat, seafood, milk, tofu, spicy food, and foods associated with yin-yang balance. Patients also provided a narrative summary describing changes in their dietary habits.

Smoking and Alcohol Use

Patients self-reported the frequency of their current and pre-diagnosis alcohol consumption and smoking behaviors, also assessed using a 4-point Likert scale: 0 = never, 1 = occasionally (eg, social or less than once per week), 2 = sometimes (eg, 1-3 times per week), and 3 = often (eg, daily or nearly daily).

Symptoms

The Simplified Chinese version of the Memorial Symptom Assessment Scale—Short Form (MSAS-SF-SC) was used to evaluate the prevalence and distress of symptoms among cancer patients. Chang et al³⁰ developed the English version of the MSAS-SF based on Portenoy’s original MSAS, and Fu et al³¹ validated the Simplified Chinese version. There are 32 symptoms in total. Psychosocial symptoms included difficulty concentrating, feeling down, feeling unlike oneself, sadness, worry, nervousness, and irritability. Gastrointestinal (GI) symptoms included lack of appetite, taste changes, dry mouth, nausea, vomiting, diarrhea, constipation, difficulty swallowing, and bloating. All symptoms were assessed using a Likert scale ranging from “never = 0” to “very much/almost all the time = 4.”

Data Analysis Methods

Deidentified data were imported into IBM SPSS 29 for statistical analysis. Descriptive statistics (eg, frequency, range, mean, standard deviation, and median) were used to summarize sociodemographic, clinical, and cultural (TCM) characteristics, psychological and GI symptoms, and the frequency of smoking, alcohol use, and dietary habits. The Wilcoxon Signed Rank test was used to compare changes in dietary habits, smoking, and alcohol use before and after cancer diagnosis as these variables were measured on an ordinal frequency scale ranging from 0 to 3. Potential predictors of current (post-diagnosis) lifestyle behaviors were first examined using t-tests, ANOVA, or correlational analyses, depending on the level of measurement for each predictor. Specifically, categorical variables (eg, gender), ordinal variables (eg, education level), and continuous variables (eg, age) were analyzed using the appropriate statistical tests to explore their associations with the outcome variables: smoking, alcohol use, and dietary habits. Predictors that showed statistically significant relationships in the initial analyses were then included in separate ordinal logistic regression models, with current (post-diagnosis) smoking, alcohol use, and dietary habits each modeled as individual outcome variables. This approach enabled the identification of unique predictors associated with each specific lifestyle behavior following a cancer diagnosis. To improve model parsimony and address potential multicollinearity, we applied a stepwise backward elimination approach, removing non-significant variables iteratively based on likelihood ratio tests, and model fit statistics (eg, AIC). Only predictors that remained statistically significant in the final model (P < .05) are reported.

Results

Sociodemographic, Clinical Characteristics, and Traditional Chinese Medicine

The study included 287 participants with a nearly balanced gender distribution (52.6% female and 47.4% male). The mean age of participants was 58.8 years (SD = 11.0), and the median duration since cancer diagnosis was 5 months. A majority of participants lived in rural areas (57.5%). More than 60% of patients reported a monthly family income of less than 3000 CNY (USD 420) and more than 90% had a family income of less than 5000 CNY, which was comparable to the national average monthly family income USD342 from 2020 to 2023³². The most common cancer types were lung cancer (32.7%), gastrointestinal cancer (27.2%), and breast or gynecological cancers (26.8%). Advanced-stage cancers (Stage III and IV) comprised 59.8% of cases, and 69.3% of participants were undergoing active treatment such as chemotherapy, targeted therapy, or radiation. Traditional Chinese Medicine (TCM) was widely used, with 50.3% of participants reporting a strong belief in its efficacy, and 84.3% using herbal medicine for cancer management. Additional sociodemographic and clinical characteristics are detailed in a previous publication,²³ while selected characteristics are summarized in Table 1.

Table 1.

Selected Sociodemographic, Clinical, and Culture/TCM Characteristic of the Subjects.

Variables	Frequency (percent %)
Gender
Female	151 (52.6)
Male	136 (47.4)
Hometown
Rural	165 (57.5)
Urban	122 (42.5)
Monthly family income (CNY)
0-2999	182 (63.1)
3000-4999	82 (28.6)
5000 and above	20 (8.4)
Working status
Working	146 (50.9)
Not working	138 (48.1)
Type of cancer
Lung cancer	93 (32.7)
Gastrointestinal cancer	83 (27.2)
Breast and Gyn cancer	76 (26.8)
Others	32 (11.2)
Cancer stage
III and IV	152 (59.8)
I and II	71 (27.9)
No stage	31 (12.2)
Recurrence of cancer
Yes	56 (19.5)
No	231 (80.5)
Active treatment
Yes	199 (69.3)
No	88 (30.7)
Belief in TCM for cancer
Strong	144 (50.3)
Somewhat	121 (42)
A little	22 (7.7)
Not at all	0

Smoking and Alcohol Consumption

Smoking and Drinking Alcohol Post-Cancer Diagnosis

As shown in Table 2, participants reported infrequent smoking and alcohol consumption after their cancer diagnosis. The mean smoking frequency was 0.48 (SD = 0.67), and the mean alcohol consumption frequency was 0.45 (SD = 0.57), reflecting generally low frequency and suggesting that, on average, participants reported smoking or drinking alcohol between “never” and “occasionally” after their cancer diagnosis.

Table 2.

Eating Habits, Smoking, and Alcohol Consumption Post-cancer Diagnosis.

Behavior/food (range 0-3)	Mean (SD)
Smoking	0.48 (0.67)
Drinking alcohol	0.45 (0.57)
Red meat consumption	1.57 (0.95)
Seafood consumption	0.56 (0.65)
Spicy food consumption	1.06 (0.75)
Tofu consumption	1.56 (0.96)
Milk consumption	1.53 (1.00)
“Balanced yin-yang food”	2.42 (0.82)

Predictors of Smoking and Drinking Alcohol Post-Cancer Diagnosis

Ordinal logistic regression analysis identified significant associations between psychological and cultural factors/TCM beliefs and self-reported smoking and alcohol consumption (Table 3). Feeling sad was a strong predictor of smoking behavior (OR = 1.94, 95% CI = 1.06-3.53, P = .031), with patients experiencing higher levels of sadness nearly twice as likely to smoke as those with lower sadness levels. A trend was observed suggesting that stronger beliefs in TCM were associated with decreased smoking (OR = 0.62, CI = −1.019 to 0.46, P = .073), though this relationship warrants further investigation with a larger sample size.

Table 3.

Factors Predicting Smoking and Alcohol Drinking Post-cancer Diagnosis Using Ordinal Logistic Regression.

Outcome	Parameter	Estimate (B)	Standard error	Wald	P-value	Odds ratio (Exp(B))	95% Confidence interval
Smoking	Feeling sad	0.663	0.307	4.651	.031	1.94	(1.06, 3.53)
Alcohol drinking	BeliefTCM_CA	−0.620	0.278	4.955	.026	0.54	(0.31, 0.93)
	CA = stage	−2.41	0.124	3.806	.051	0.36	(0.10, 1.31)

Abbreviations: BeliefTCM_CA, belief in TCM for cancer.

Cultural beliefs and clinical factors also significantly influenced self-reported alcohol consumption. Stronger belief in TCM was associated with reduced alcohol consumption (OR = 0.54, 95% CI = 0.31-0.93, P = .026), with participants holding stronger TCM beliefs being 46% less likely to consume alcohol than those with weaker beliefs. Additionally, advanced-stage cancer (Stage III or IV) was associated with a 64% reduction in alcohol consumption compared to early-stage cancer (OR = 0.36, 95% CI = 0.10-1.31, P = .051). This reduction may reflect greater health awareness or stricter adherence to medical advice.

Change in Smoking and Alcohol Consumption Pre- and Post-Cancer Diagnosis

Significant reductions (around 60%) in patient-reported smoking and alcohol consumption were observed following cancer diagnosis (Figure 1). Wilcoxon Signed Rank tests confirmed these reductions as statistically significant (P < .05).

Figure 1.

Change of eating habits, smoking and alcohol consumption before and after cancer diagnosis.

Dietary Behaviors

Dietary Habits Post-Cancer Diagnosis

As modifiable lifestyle behaviors, dietary habits, smoking, and alcohol use were examined together to assess their relative frequencies post-cancer diagnosis. While these behaviors differ in nature and health impact, comparing their frequency provides context for understanding how Chinese cancer patients prioritize different aspects of lifestyle modification post-diagnosis. Compared to smoking and alcohol consumption (Table 2), participants reported higher frequencies of consuming red meat (mean = 1.57, SD = 0.95), tofu (mean = 1.56, SD = 0.96), and milk (mean = 1.53, SD = 1.00). Maintaining a balanced yin-yang diet was the most common habit, with a mean score of 2.42 (SD = 0.82).

Predictors of Dietary Habits Post-Cancer Diagnosis

Multiple factors influenced self-reported dietary behaviors (Table 4). Urban residency was associated with lower red meat consumption (OR = 0.51, 95% CI = 0.264-0.967, P = .039) and higher tofu consumption (OR = 2.05, 95% CI = 1.072-3.926, P = .03). Older age was associated with reduced spicy food consumption (OR = 0.97, 95% CI = 0.939-0.998, P = .036), while non-working participants were more likely to consume spicy food (OR = 1.86, 95% CI = 1.024-3.377, P = .042). Gender differences were evident, as males were less likely to follow a balanced yin-yang diet (OR = 0.33, 95% CI = 0.138-0.777, P = .011).

Table 4.

Factors Predicting Diet Habits Post-cancer Diagnosis Using Ordinal Logistic Regression.

Outcome	Parameters	Estimate (B)	Standard error	Wald	P-value	Odds ratio (Exp(B))	95% Confidence interval
Red meat consumption	LengthDiag	0.017	0.007	5.794	.016	1.02	(1.003, 1.031)
	CA_Stage	0.247	0.115	4.662	.031	1.28	(1.023, 1.604)
	Constipation	0.327	0.156	4.365	.037	1.39	(1.020, 1.884)
	L_Appetit	−0.404	0.162	6.255	.012	0.67	(0.486, 0.916)
	HomeTown = 0^a	−0.682	0.331	4.25	.039	0.51	(0.264, 0.967)
	Recurent = 0^b	1.506	0.456	10.91	<.001	4.51	(1.845, 9.057)
	ActiveTx = 0^c	−0.804	0.337	5.69	.017	0.45	(0.231, 0.867)
Seafood consumption	BeliefTCM_CA	−0.559	0.268	4.365	.037	0.57	(0.338, 0.965)
Seafood consumption	Income	0.514	0.264	3.792	.052	1.67	(0.997, 2.804)
Spicy food consumption	Age	−0.032	0.015	4.38	.036	0.97	(0.939, 0.998)
	LengthDiag	0.016	0.008	4.29	.038	1.02	(1.001, 1.032)
	Working = 0^d	0.62	0.304	4.153	.042	1.86	(1.024, 3.377)
Tofu consumption	BeliefTCM_CA	−0.504	0.244	4.272	.039	0.6	(0.376, 0.974)
	Constipation	−0.389	0.159	6.023	.014	0.68	(0.497, 0.925)
	FoodTaste	−0.349	0.179	3.782	.052	0.71	(0.496, 1.003)
	HomeTown = 0^a	0.719	0.331	4.718	.03	2.05	(1.072, 3.926)
	CancerType = 1^e	−0.307	0.563	0.298	.585	0.74	(0.244, 2.217)
	CancerType = 2^e	−1.172	0.599	3.831	.05	0.31	(0.096, 0.998)
	CancerType = 3^e	−0.32	0.557	0.331	.565	0.73	(0.244, 2.160)
	PostCA_Herb = 0^f	−1.301	0.469	7.7	.006	0.27	(0.109, 0.683)
Milk consumption	LengthDiag	0.014	0.006	4.746	.029	1.01	(1.001, 1.026)
	BeliefTCM_CA	−0.691	0.242	8.176	.004	0.5	(0.312, 0.805)
	L_Appetit	−0.284	0.135	4.41	.036	0.75	(0.578, 0.981)
	CancerType = 1^e	−0.986	0.502	3.863	.049	0.37	(0.139, 0.997)
	CancerType = 2^e	−0.712	0.57	1.561	.212	0.49	(0.160, 1.499)
	CancerType = 3^e	−0.868	0.511	2.884	.089	0.42	(0.154, 1.143)
Balanced Yin-Yang diet	LengthDiag	0.018	0.009	4.122	.042	1.02	(1.001, 1.035)
	CA_Stage	0.362	0.127	8.068	.005	1.44	(1.119, 1.843)
	Nausea	0.567	0.276	4.224	.04	1.76	(1.026, 3.029)
	FoodTaste	0.495	0.232	4.561	.033	1.64	(1.041, 2.583)
	Sex=0^g	−1.115	0.441	6.409	.011	0.33	(0.138, 0.777)
	Recurent = 0^b	1.403	0.514	7.465	.006	4.07	(1.487, 11.125)

Abbreviations: LengthDiag, length of cancer diagnosis; BeliefTCM_CA, belief in _TCM for cancer; CA_Stage, stage of cancer; L_Appetit, lack of appetite; FoodTaste, change in food taste; ActiveTx, active treatment; PostCA_Herb, use of herbs after cancer diagnosis.

The reference group is 1, hometown is rural. 0 is for urban.

The reference group is 1, cancer is recurrent. 0 is for nonrecurrent.

The reference group is 1, patient is in active treatment. 0 is for not in active treatment.

The reference group is 1, patient is working. 0 is for not working status.

The reference group is 4, other cancer except lung cancer, breast & gyn cancer, and GI cancers.1 is lung cancer, 2 is breast & Gyn cancer, 3 is GI cancer.

The reference group is 1, patient use herbs after cancer diagnosis. 0 is for not use herbs after cancer diagnosis.

The reference group is 1, female. 0 is for male.

Gastrointestinal symptoms also played a key role in self-reported dietary habits. Lack of appetite was associated with reduced consumption of red meat (OR = 0.67, 95% CI = 0.486-0.916, P = .012) and milk (OR = 0.75, 95% CI = 0.578-0.981, P = .036). Constipation was linked to increased red meat consumption (OR = 1.39, 95% CI = 1.020-1.884, P = .037) but reduced tofu intake (OR = 0.68, 95% CI = 0.497-0.925, P = .014). Taste changes increased adherence to a balanced yin-yang diet (OR = 1.64, 95% CI = 1.041-2.583, P = .033), while nausea was positively associated with balanced diet adherence (OR = 1.76, 95% CI = 1.026-3.029, P = .04). Beliefs in TCM were negatively associated with the consumption of seafood (OR = 0.57, 95% CI = 0.338-0.965, P = .037), tofu (OR = 0.6, 95% CI = 0.376-0.974, P = .039), and milk (OR = 0.5, 95% CI = 0.312-0.805, P = .004).

Change in Dietary Habits Pre- and Post-Cancer Diagnosis

Significant changes in patient-reported dietary habits were observed following cancer diagnosis (Figure 1). Wilcoxon Signed Rank tests showed statistically significant reductions (P < .05) in the consumption of red meat, seafood, spicy foods, tofu, and milk. Conversely, there was a significant increase (P < .05) in the consumption of balanced yin-yang food. Narrative responses frequently included phrases such as “more plant-based” and “less oil, spicy, and salty foods,” indicating a shift toward healthier dietary patterns post-diagnosis.

Discussion

The majority of patients in this study were female, resided in rural areas, were diagnosed with advanced-stage cancer, and had low monthly family incomes. Limited access to early cancer screening and diagnostic services in rural China likely contributed to these findings.³³ As the teaching hospital is located in the capital city of Hunan Province, many rural patients travel to the city for cancer treatment. A strong belief in Traditional Chinese Medicine (TCM) was observed among participants, with 50.3% reporting a strong belief in TCM and 84.3% using herbal medicine for cancer management. These findings highlight the widespread acceptance and utilization of TCM among Chinese cancer patients.^24,34

Patients in this study reported minimal smoking after their cancer diagnosis, consistent with prior research showing that cancer survivors tend to have lower smoking rates compared to the general population.^35,36 For instance, only 7.8% of cancer survivors in Korea were current smokers, significantly lower than the smoking prevalence reported in Western studies, which ranges from 15% to 32%.³⁷ In contrast, alcohol consumption among cancer survivors remains prevalent. For example, 38.3% of gastric cancer survivors who lived ≥2 years post-diagnosis continued drinking alcohol.³⁸ Similarly, 34% to 57% of head and neck cancer patients reported ongoing alcohol use after diagnosis, underscoring the persistence of alcohol consumption throughout the cancer trajectory.³⁹ The lower prevalence of alcohol use in this study could be attributed to the short median duration since diagnosis (5 months). Research suggests that alcohol use may increase among survivors as more time passes after diagnosis.³⁸ Significant reductions in both smoking and alcohol consumption post-diagnosis were observed, consistent with findings in the literature. However, to the authors’ knowledge, no specific smoking or alcohol cessation programs were available for cancer patients at the hospital where the study was conducted. Future studies should investigate the psychological, cultural, and healthcare-related factors contributing to reductions in smoking and alcohol consumption among Chinese cancer survivors, to better understand what drives these changes, and how to sustain them through targeted, culturally appropriate interventions.

The association between sadness and increased smoking aligns with research indicating that depressive symptoms can hinder smoking cessation efforts among cancer patients^40,41 Emotional distress often influences smoking behavior, potentially serving as a coping mechanism. Cultural factors also play a role; for instance, cancer survivors in France often denied an association between alcohol and cancer risk, reflecting the strong cultural influence on lifestyle behaviors.⁴² This study found a relationship between strong TCM beliefs and reduced alcohol consumption, underscoring the cultural impact on health behaviors. Although alcohol is a known carcinogen and strongly linked to increased cancer risk, the 2022 American Cancer Society guideline notes that systematic reviews on the relationship between postdiagnosis alcohol intake and cancer-specific or overall mortality are limited, especially for cancers other than breast cancer. Nevertheless, current guidelines recommend minimizing or avoiding alcohol consumption in cancer survivors to reduce recurrence risk and improve overall health outcomes.^5,6 Addressing psychological well-being and cultural beliefs is crucial for developing effective interventions targeting smoking and alcohol use among cancer patients. In particular, integrating culturally relevant frameworks, such as traditional Chinese medicine beliefs, into intervention design may improve patient engagement and reinforce health-promoting behaviors.

Compared to smoking and alcohol consumption, participants reported higher intake of red meat and seafood, both of which are animal-based food groups. According to the American Cancer Society and National Comprehensive Cancer Network guidelines, cancer survivors should prioritize a plant-based diet and limit red and processed meat consumption.^5,6 The Lifestyle Medicine Toolkit for Cancer Risk Reduction & Survivorship also emphasizes the importance of minimally processed, plant-based diets for cancer risk reduction and survivorship.¹⁰ Previous studies suggest that many cancer patients receive limited or non-specific lifestyle advice from healthcare professionals during treatment.⁴³ Like other cancer survivors in China,⁴⁴ participants in this study may not fully recognize the benefits of plant-based diets and continue consuming less healthy foods. Enhanced education and tailored interventions that align with established dietary guidelines are essential for improving dietary behaviors among cancer survivors.

This study observed culture-sensitive dietary changes among Chinese cancer patients post-diagnosis. The reduction in spicy food consumption may reflect the cultural belief that spicy foods increase cancer risk.⁴⁵ More research is needed to clarify the relationship between spicy food and cancer risks. The slight decrease in tofu consumption contrasts with recommendations encouraging soy intake for cancer survivors.^5,6,10 Soy products like tofu are rich in protein and isoflavones, which may have protective effects against certain cancers. Oncology healthcare professionals should provide updated guidance on the benefits of soy products to address misconceptions. Increased consumption of “balanced yin-yang food” aligns with TCM principles emphasizing dietary balance to harmonize the body’s energies during cancer treatment.⁴⁶ This shift reflects a cultural preference for TCM practices aimed at restoring equilibrium and enhancing well-being. Future research should explore the characteristics of yin and yang foods and how patients balance them, enabling healthcare providers to incorporate this traditional concept into education on healthy lifestyles for cancer survivors.

Dietary habits are influenced by multiple factors, with symptoms such as constipation and lack of appetite playing a significant role. For instance, patients experiencing constipation tended to consume more red meat, which can worsen the condition and were less likely to consume tofu, a food that may help alleviate it.⁴⁷ These findings underscore the importance of dietary education in effectively addressing physical discomfort like constipation. Interestingly, taste changes and nausea were associated with greater adherence to a balanced diet, suggesting that patients may proactively adopt balanced dietary patterns as a coping mechanism for these symptoms. Additionally, the influence of Traditional Chinese Medicine (TCM) beliefs on dietary choices was particularly notable. Patients with strong TCM beliefs were less likely to consume seafood, tofu, and milk. This highlights the need for healthcare professionals to understand TCM cultural frameworks when offering dietary guidance. TCM philosophy often shapes dietary practices, with specific foods being avoided based on their perceived properties, such as “cold” or “damp.”⁴⁸ For example, seafood and milk, considered “cold” foods in TCM, may be restricted in cases of gastrointestinal discomfort or other “cold” conditions.⁴⁹ By acknowledging and incorporating TCM cultural beliefs, healthcare providers can deliver more culturally sensitive and effective dietary interventions.

Limitations

This study has several limitations. First, dietary habits, smoking, and alcohol consumption were not assessed comprehensively using a standardized instrument. While culturally relevant foods such as tofu and spicy dishes were included, the survey did not address certain unhealthy items (eg, processed meat, sugar) or other food groups such as poultry, fruits, and vegetables. Future studies should employ validated and culturally sensitive tools to achieve a more robust dietary assessment. Although the dietary assessment utilized a self-developed questionnaire, it successfully captured common dietary practices among Chinese individuals—such as consuming spicy food and tofu and maintaining a balanced yin-yang diet. These culturally specific insights, often underrepresented in English-language literature, provide valuable information not only for Chinese physicians but also for Western healthcare providers managing Chinese immigrant cancer patients. Second, the reliance on self-reported data for diet, smoking, alcohol, and TCM beliefs is a standard limitation in behavioral research. While practical, it introduces the risk of biases, such as recall bias and social desirability bias and future research should use strategies for minimizing bias, such as ensuring anonymity in the assessment and using validated measures that are known to reduce such biases. Third, the study’s cross-sectional design limits the ability to infer causal relationships. Finally, the participants were recruited from a single teaching hospital in a capital city, potentially limiting the generalizability of findings to cancer patients from other hospital settings or regions and the findings could not be representative of all cancer patients in China.

Conclusion

Following a cancer diagnosis, many Chinese patients in this study reported reductions in smoking, alcohol consumption, and certain unhealthy dietary habits. However, these behavioral improvements were not consistent across all participants and occurred without structured intervention or education. A considerable proportion continued to engage in unhealthy behaviors, such as frequent red meat consumption or avoidance of soy products due to misconceptions. These findings highlight the potential for dietary and behavioral interventions to reinforce positive changes, correct misinformation, and promote sustainable lifestyle improvements. Interventions should aim not only to reduce harmful behaviors but also to encourage the adoption of culturally appropriate healthy practices, such as balanced yin-yang dietary patterns and plant-based food choices. By aligning educational content with patients’ cultural beliefs and addressing symptom-related dietary decisions, such interventions could support long-term survivorship and improved health outcomes. Additionally, we recommend that oncology physicians and nurses stay informed on the latest clinical guidelines for nutrition in cancer survivorship. By addressing dietary misconceptions and offering practical, culturally sensitive lifestyle advice, healthcare professionals can contribute to both the physical and psychological well-being of cancer survivors, ultimately improving their quality of life.

Footnotes

Acknowledgements

We thank the patients and staff at the oncology outpatient clinic for their participation and support.

ORCID iD

Shan Liu

Ethical Considerations

This study was approved by the Institutional Review Board of The third Xiang-Ya Hospital of Central South University, Changsha, China (No: 2019-S442), and the Institutional Review Board of Adelphi University, Garden City, USA (No: 060419).

Consent to Participate

All participants provided written informed consent prior to participating.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was partially funded by the Adelphi University Faculty Development Grant.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

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Diet Habits,Smoking,and Alcohol Consumption Among Chinese Patients with Cancer

Abstract

Background:

Methods:

Results:

Conclusions:

Keywords

Background

Methods

Research Design, Patient Recruitment, and Protection of Human Subjects

Measurement

Sociodemographic, Clinical Information, and Culture/Traditional Chinese Medicine

Diet Habits

Smoking and Alcohol Use

Symptoms

Data Analysis Methods

Results

Sociodemographic, Clinical Characteristics, and Traditional Chinese Medicine

Smoking and Alcohol Consumption

Smoking and Drinking Alcohol Post-Cancer Diagnosis

Predictors of Smoking and Drinking Alcohol Post-Cancer Diagnosis

Change in Smoking and Alcohol Consumption Pre- and Post-Cancer Diagnosis

Dietary Behaviors

Dietary Habits Post-Cancer Diagnosis

Predictors of Dietary Habits Post-Cancer Diagnosis

Change in Dietary Habits Pre- and Post-Cancer Diagnosis

Discussion

Limitations

Conclusion

Footnotes

Acknowledgements

ORCID iD

Ethical Considerations

Consent to Participate

Funding

Declaration of Conflicting Interests

Data Availability Statement

References