You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Introduction
============

Gastric cancer, the majority of which is gastric adenocarcinoma (GaC), is the 5^th^ most commonly diagnosed malignancy and the 3^rd^ leading cause of cancer mortality in both sexes combined worldwide, with \~1,034,000 new cases and \~783,000 deaths in 2018 [@B1]. Its incidence is highest in Eastern Asia [@B2]. In China, gastric cancer was estimated to affect \~679,000 patients and to cause 498,000 deaths in 2015, and was both the 2^nd^ most commonly diagnosed cancer and the 2^nd^ leading cause of cancer death in both sexes combined [@B3].

*Helicobacter pylori* (*Hp*) is the major risk factor for GaC, contributing to \~90% of new cases of non-cardia GaC [@B4], [@B5]. Some unhealthy dietary habits (*e.g.*, food preservation by salting and low fruit/vegetable intake), alcohol consumption, and tobacco smoking have also been shown to be associated with a higher risk of GaC [@B1], [@B6]-[@B13]. Notably, results on the associations of GaC with some factors (*e.g.*, drinking, smoking, and red meat intake) remain controversial [@B1], [@B6]-[@B16], and many other preventable risk factors have not yet been well established.

This study aimed to comprehensively investigate the easily-modifiable lifestyle and eating habits associated with GaC and to offer evidence for disease prevention. Our findings can potentially aid to identify people at high risk of GaC and be used for risk-adapted screening.

Methods
=======

Participants
------------

Consecutive patients with first primary microscopically-confirmed GaC diagnosed in the First Affiliated Hospital of Anhui Medical University (FAHAMU) between July 2016 and August 2018 were included in this case-control study. Patients with previous malignancies, with cancers other than GaC, with other benign gastric diseases, with diseases impairing memory (*e.g.*, dementia), with severe dysfunction of important organs, or with severe systematic unfitness were excluded. They were matched by sex, age, height, and socioeconomic status at a 1:1 ratio with healthy controls confirmed not to have any gastric disorders except superficial gastritis. Since many patients with GaC are diagnosed at an advanced stage and are usually significantly thinner compared to the healthy controls and their pre-disease conditions, weight was not included as a matching factor. All participants did not have previous symptomatic reflux, and had fridges for food preservation. Individuals with any first-degree relative having GaC were excluded. Informed consents were obtained from all participants. This study was approved by the Internal Review Board of FAHAMU.

Collected information
---------------------

Participants were requested to carefully respond to a valid, uniform, and standardized questionnaire and to report their regular, habitual, customary, long-lasting conditions (before having obvious digestive symptoms in GaC patients). To ensure the validity and completeness of the responses, the completion of each questionnaire was supervised by one of the trained authors, who only explained items neutrally when necessary but did not offer any directive or indicative clues.

Information on participant characteristics (sex, age, height, weight, education level, marital status, alcohol drinking, smoking, and passive smoking) and comorbidities (hepatitis, diabetes, hypertension, and allergy) were first collected. Tumor location and differentiation were retrieved for patients. All participants were further requested to report the following: Number of people living and eating together with; eating and cooking habits; drinking water source; frequency score (FS) for intake of pork, chicken, beef, fish, processed meat, pickled food, dried food, smoked/baked food, vegetables/fruit, beans, stewed food, fried food, cereals, tuber crops, kelps, and dairy products; FS for use of yellow rice wine, soy sauce, vinegar, monosodium glutamate, chicken essence, onion/garlic, pepper, and ginger; FS for intake of thick (*e.g.*, thick soup and milk) and thin liquid (*e.g.*, water and juice) before, during, and after meal; FS for several eating habits (swallowing hot food without adequate cooling, not sufficiently chewing, overeating, doing other things while eating, eating deteriorated food, eating overnight food, eating within 0.5 hours after sports, eating midnight snack, and having milk before sleep); FS for eating at home, eating at canteen, and eating box lunch; FS for several sleeping habits (going to bed regularly, dreaming, and afternoon nap); FS for and time of housework and exercise per day; preference score (PS) for sour, sweet, bitter, spicy, and salty tastes; regularity score (RS) for having breakfast, lunch, and supper; degree of satiety and food intake per meal; rest hours after meal; nighttime and noontime sleeping hours; and quality of sleep.

FS was defined as: 0, never; 1, ≤1 time per month; 2, 2-3 times per month; 3, 1-2 times per week; 4, 3-4 times per week; 5, 5-6 times per week; 6, 1 time per day; 7, 2 times per day; 8, 3 times per day; 9, ≥4 times per day. The frequency was modified from the Food Frequency Questionnaire [@B17]. PS ranged from 1 (extremely dislike) to 7 (extremely like) with an increment of 1. RS ranged from 1 (very regular) to 5 (very irregular) with an increment of 1.

Statistical analyses
--------------------

The paired *t* and *χ^2^* tests were used for comparing continuous and categorical variables between groups, respectively. Associations of GaC versus control with the investigated factors were first computed in basic models using the multivariable conditional logistic regression for paired samples adjusting for sex, age, and height, and the significant factors were then all incorporated into a final multivariable logistic model also adjusting for sex, age, and height. Subgroup analyses were further performed for cardia and non-cardia cancers, respectively. Statistical significance was defined by 2-sided *P*\<0.05. Data analyses were performed using R 3.5.1 (<https://www.r-project.org/>).

Results
=======

Participant characteristics
---------------------------

Initially 628 questionnaires were collected. After excluding the unqualified ones and their pairs, finally 604 cases (n~Patients~=302; n~Controls~=302) were analyzed. Male proportions in both groups were 69%. The mean ages in the patient and control groups were 60 ± 11 and 59 ± 11 years, respectively. Mean heights were 165 ± 7 and 164 ± 7 cm for patients and controls, respectively. For patients, the proportions of tumors located at the gastric cardia, fundus/body, antrum/pylorus, and whole stomach were 46%, 23%, 29%, and 2%, respectively, and the proportions of well-differentiated, moderately-differentiated, and poorly-differentiated/undifferentiated cancers were 5%, 25%, and 70%, respectively.

Basic models
------------

Compared to uneducated patients, patients going to primary school (OR=0.55), middle school (OR=0.41), high school (OR=0.45), and college/university (OR=0.25) were significantly associated with less often GaC (Table [1](#T1){ref-type="table"}). Alcohol drinking was significantly associated with more frequent GaC (OR=2.46), and per 1 higher FS the odds for GaC increased by 0.10. Smoking was associated with more often GaC (OR=2.26), and the odds for GaC increased by 0.17 per 1 higher FS. The FS for passive smoking was also significantly associated with GaC (OR=1.21). No significant associations of GaC with marital status, or histories of hepatitis, diabetes, hypertension, or allergy were observed.

Regarding food and liquid intake (Table [2](#T2){ref-type="table"}), the FS for intake of pork (OR=0.89), beef (OR=0.84), fish (OR=0.82), and egg (OR=0.84) was significantly inversely associated with GaC. Particularly, the number of eggs eaten per day was significantly negatively associated with GaC (OR=0.74), and not eating any eggs per day was associated with a higher proportion of GaC compared to eating 1 egg per day (OR=2.17). The FS for having processed meat (OR=1.23), pickled food (OR=1.21), dried food (OR=1.26), and smoked/baked food (OR=1.19) was significantly positively associated with GaC. Having vegetables/fruit, beans, cereals, tuber crops, and kelps decreased the odds for GaC by 0.34, 0.25, 0.18, 0.17, and 0.24 per every additional PS, respectively. The FS for use of yellow rice wine (OR=0.81), soy sauce (OR=0.89), vinegar (OR=0.84), onion/garlic (OR=0.81), pepper (OR=0.85), and ginger (OR=0.79) was significantly inversely associated with GaC, while the FS for use of monosodium glutamate (OR=1.09) and chicken essence (OR=1.07) was positively associated with GaC. The PS for sour (OR=0.86), bitter (OR=0.70), and spicy tastes (OR=0.82) was significantly less frequently associated with GaC.

Concerning eating and living habits (Table [3](#T3){ref-type="table"}), the number of people living or eating together with was not significantly associated with GaC. Compared to people having majorly vegetables for food, those keeping a balanced diet (OR=2.17) and having majorly meat (OR=3.77) were significantly more likely to have GaC. The majorly frying cooking habit was significantly associated with a higher possibility of GaC compared to majorly steaming/boiling (OR=2.67). Drinking well water was significantly associated with GaC compared to tap water (OR=2.36). The RS for breakfast (OR=1.54), lunch (OR=1.77), and supper (OR=1.78) was significantly positively associated with GaC, while no significant association was shown for degree of satiety. Higher FS for thin liquid intake before meal (OR=1.13), both thick (OR=1.13) and thin liquid intake during meal (OR=1.12), and thin liquid intake after meal (OR=1.19) was associated with increased odds for GaC, while higher FS for thick liquid intake after meal was associated with less frequent GaC (OR=0.89). The FS for overeating (OR=1.47), not sufficiently chewing (OR=1.16), doing other things while eating (OR=1.13), swallowing hot food without adequate cooling (OR=1.25), eating deteriorated food (OR=1.87), eating overnight food (OR=1.16), eating within 0.5 hours after sports (OR=1.13), and eating midnight snack (OR=1.54) was all significantly positively associated with GaC, while there was no significantly association between GaC and having milk before sleep. While eating at home was significantly associated with less frequent GaC (OR=0.88 per 1 FS), eating at canteen was significantly associated with more often GaC (OR=1.12 per 1 FS). The FS for eating box lunch was not significantly associated with GaC. No significant associations were observed for rest hours after meal, or nighttime or noontime sleep hours. Compared to good sleep quality, moderate (OR=1.88) and poor quality (OR=2.81) were associated with increased odds for GaC. The more often one goes to bed regularly and has afternoon nap, the decreased odds for GaC (OR=0.80 and 0.93 per 1 FS, respectively). No significant associations of GaC with housework or exercise were observed.

Final multivariable model
-------------------------

In the final multivariable model (Table [4](#T4){ref-type="table"}), participants receiving primary school (OR=0.27) or middle school education (OR=0.21) had significantly less often GaC compared to those uneducated. Compared to people keeping a balanced diet, those having majorly vegetables had significantly less frequently GaC (OR=0.23). The majorly frying cooking habit was significantly associated with a higher incidence of GaC compared to the majorly steaming/boiling habit (OR=10.23). Compared to people having good sleep quality, those complaining about poor sleep quality had significantly more often GaC (OR=3.18). The more often one smoked, the more often he/she had GaC (OR=1.28 per 1 FS). Higher FS for having pickled food was significantly associated with more frequent GaC (OR=1.41), while having more frequently vegetables/fruit (OR=0.60), beans (OR=0.73), or kelps (OR=0.72) was significantly associated with less often GaC. A greater PS for sour (OR=0.77) or bitter taste (OR=0.50) was significantly associated with less frequent GaC. The FS for thin liquid intake after meal (OR=1.27), swallowing hot food without adequate cooling (OR=1.21), doing other things while eating (OR=1.23), eating overnight food (OR=1.25), and eating midnight snack (OR=1.49) was all significantly positively associated with GaC, while going to bed regularly was significantly associated with less often GaC (OR=0.81 per 1 FS).

The association patterns for cardia and non-cardia cancers were mostly similar with the whole cases, only with few exceptions. For cardia cancers, The FS for having eggs was significantly associated with less often GaC (OR=0.32). The FS for eating vegetables/fruit was more strongly associated with reduced cardia carcinoma frequency (OR=0.16) compared to overall and non-cardia carcinomas. The FS for vinegar use (OR=0.65) and the PS for spicy taste (OR=0.57) were only significantly negatively associated with non-cardia cancers. More frequent pepper use was only significantly associated with less often cardia cancers (OR=0.47), and more often thin liquid intake during meal (OR=2.27), more often chewing insufficiently (OR=2.69), more frequently eating deteriorated food (OR=7.84), and more irregular supper intake (OR=6.37) were only significantly associated with more frequent cardia cancers.

Discussion
==========

This study comprehensively reported eating and living habits associated with GaC in a large Chinese population, offering further insights into potentially modifiable factors and providing important evidence for making GaC-preventive strategies. Furthermore, some differences in association patterns and/or strengths between cardia and non-cardia cancers were found for some factors.

We found that people receiving primary or middle school education had significantly less often GaC compared to uneducated people, which is consistent with some previous studies showing that better education was associated with reduced GaC risk [@B18], [@B19].

Better education could help to form and keep healthy eating and living habits, while well-educated people might face greater pressure in this competitive modern era. The associations for those receiving high school and college/university education were insignificant in overall patients and most subgroups, which could be partly explained by the small case numbers in these groups. People having majorly vegetables for food had significantly less frequent GaC, which is also supported by previous studies [@B20], [@B21]. Furthermore, we found that more frequent vegetable/fruit intake was significantly associated with a reduced frequency of cardia cancer but not of non-cardia cancer. Previous evidence remains controversial regarding the association between red meat intake and GaC risk [@B16], and The Netherlands Cohort Study did not show a significant association [@B15]. The insignificance for the habit of majorly meat intake in our study might be partly explained by the paucity of participants in that group. The majorly frying cooking habit, which could generate various carcinogenic substances in a temperature-dependent manner, was associated with a higher overall GaC incidence compared to majorly steaming/boiling. We found that poor sleep quality was significantly associated with a higher GaC incidence compared to good quality. Notably, sleep quality could be influenced by various factors like time to go to bed and psychiatric status. We further found that the frequency of going to bed regularly was significantly associated with a reduced risk of GaC especially non-cardia cancer. Our finding that smoking was associated with GaC in a dose-dependent manner was well supported by previous literature [@B22]; however, we did not observe a significant association for alcohol drinking frequency, on which previous evidence remains controversial [@B14].

The frequency of pickled food intake, a well-recognized risk factor for GaC [@B23], was associated with increased risks of both cardia and non-cardia cancers. Interestingly, more frequent egg intake was significantly associated with a reduced risk of cardia cancer but not of non-cardia cancer. While higher frequencies of intake of beans and kelps were both significantly associated with a decreased overall GaC risk, beans intake was significantly associated with non-cardia cancer and kelps intake with cardia cancer. More often vinegar use was significantly associated with a reduced non-cardia cancer risk, and a greater preference for sour taste was significantly associated with a lower overall GaC risk. We previously reported that distal GaC was mostly associated with hypoacidity [@B24], and adequate acidification of inner-stomach environment might be protective against malignancy, possibly by inhibiting growth and proliferation of organisms. More frequent pepper use was associated with a lower incidence of cardia cancer, and a greater preference of spicy taste was significantly associated with a lower cardia cancer risk. However, an early study [@B25] reported that Chili pepper consumption was positively associated with GaC risk. The discrepancies from our findings could be possibly due to the different strains between Asia and South America. Notably, a greater preference for bitter taste was significantly associated with reduced incidences of both cardia and non-cardia cancers. The associations with various food and seasoning intake and flavor preference offer important clues for easy GaC-preventative strategy making, which should be further validated by prospective studies.

Some specific eating habits were further found to be associated with GaC risk through multivariable analysis. The more often one had thin liquid during meal, the more probably he/she had cardia adenocarcinoma, while more frequent thin liquid intake after meal was significantly associated with an increased risk of non-cardia cancer. Thin liquid intake during/after meal could dilute the gastric liquid, thus increasing the burden of stomach. Notably, we did not observe a significant association for thick liquid intake. Swallowing hot food without adequate cooling was associated with an increased GaC risk, which might be due to the damaging effect of heat to gastric mucosa. Insufficiently chewing was associated with an increased GaC risk, which could be attributed to the increased digestive burden for the stomach. Doing other things while eating could reduce the blood flow to the stomach, potentially causing the organ to be more vulnerable. The frequencies of eating deteriorated and overnight food, which might contain increased carcinogenic microorganisms and chemical compounds, were both associated with an increased GaC risk. Among 3 meals in a day, only the irregularity degree of supper was significantly associated with cardia cancer. A short interval between having supper and going to bed could induce and accelerate reflux, a risk factor for cardia cancer. Accordingly, eating midnight snack was significantly associated with an increased GaC risk. Nearly all of these potential GaC risk factors could be modifiable. If prospectively validated, GaC-preventative strategies could be accordingly made.

This case-control study was limited by its retrospective observational nature. The associations observed do not suggest causality, and should be validated in prospective cohorts. Recall bias could affect the accuracy of the results. There could be other risk factors that have not been accounted for in this study (*e.g.*, depression). *Hp* infection status was not adjusted for in this study, considering that the measure for cancer patients might not reflect the real pre-cancer status. Some originally *Hp*-infected patients may have the infection status turn negative during the development of cancer. Furthermore, it would be difficult to know the exact duration of infection which might differ largely between the patient and control groups. The case numbers in some subgroups were not large enough to obtain statistical significance, and larger relevant studies are encouraged. Notably, the risk factors for GaC in Western people could be different from those in Asian people. Molecular and genetic risk factors could potentially further help to identify people at risk.

Our study is a large comprehensive investigation on various easily modifiable factors potentially causing GaC in Asian people. Further subgroup analyses according to tumor location were conducted. While some identified GaC-associated factors have been reported previously, there are various newly detected modifiable and preventable eating and living habits, which provide important informative clues for future investigations and which will contribute greatly to GaC prevention if validated prospectively. Once validated, the findings can serve as references for making effective population-based strategies to prevent GaC. Through health education campaigns to raise the public awareness of the modifiable and preventable factors associated with GaC, it can be expected that a significant proportion of GaC cases can be avoided in a cost-effective manner, especially for individuals without *Hp* infection who may have poorer prognosis if developing GaC [@B26]. Our evidence-based findings provide novel clues to help to identify people at a high risk of GaC which can be potentially used for risk-adapted screening and which may contribute to early diagnosis. Modifying the validated factors may even help to prolong survival and improve quality of life for patients with GaC, and further studies in these aspects are needed.

In conclusion, education level, sleep quality, smoking, the frequencies of use of several foods and seasonings, the preference for specific tastes, and various eating and living habits were significantly associated with GaC, with some location-specific differences. Our findings offer important hints for further prospective investigations and for easy effective GaC-preventative strategy making.

The authors would most sincerely thank the reviewers and editors for critically reviewing this paper and for the constructive and thoughtful comments and suggestions.

Funding
=======

This work was supported by National College Students\' Innovation and Entrepreneurship Training Program (9021446101) and National Natural Science Foundation of China (81572350). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Authors\' contributions
=======================

Huang L, Chen L, Gui ZX, Liu S, Wei ZJ, and Xu AM designed the research; Huang L, Chen L, Gui ZX, Liu S, and Wei ZJ performed the research; Huang L analyzed and interpreted the data, and wrote the manuscript; Chen L, Gui ZX, Liu S, Wei ZJ, and Xu AM critically reviewed the paper.

Ethics approval and consent to participate
==========================================

This study was approved by the Institutional Review Board of First Affiliated Hospital of Anhui Medical University. Written informed consent was obtained from each investigated individual. No individual patient data were reported.

Availability of data and materials
==================================

The data that support the findings of this study are available from our center but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.

Grant support
=============

This work was supported by National College Students\' Innovation and Entrepreneurship Training Program (9021446101) and National Natural Science Foundation of China (81572350). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

###### 

Basic participant characteristics

  Variable                  Value/comment^1^     *Controls*       *Patients*       OR (95% CI)^2^     *P~trend~*
  ------------------------- -------------------- ---------------- ---------------- ------------------ ------------
  Education                 Uneducated           64 (21)          91 (32)          1.00 (ref.)        0.001
                            Primary school       84 (28)          82 (29)          0.55 (0.34-0.88)   
                            Middle school        85 (29)          69 (24)          0.41 (0.25-0.67)   
                            High school          32 (11)          28 (10)          0.45 (0.24-0.85)   
                            College/university   33 (11)          17 (6)           0.25 (0.12-0.52)   
  Marital status            Married              269 (89)         259 (87)         1.00 (ref.)        0.322
                            Single               33 (11)          38 (13)          1.29 (0.78-2.15)   
  Migrant                   No                   258 (85)         167 (62)         1.00 (ref.)        \<0.001
                            Yes                  44 (15)          102 (38)         3.66 (2.37-5.66)   
  History of hepatitis      No                   296 (98)         260 (96)         1.00 (ref.)        0.310
                            Yes                  6 (2)            10 (4)           1.72 (0.60-4.90)   
  History of diabetes       No                   273 (90)         247 (94)         1.00 (ref.)        0.164
                            Yes                  29 (10)          16 (6)           0.63 (0.33-1.21)   
  History of hypertension   No                   224 (74)         212 (79)         1.00 (ref.)        0.112
                            Yes                  78 (26)          55 (21)          0.72 (0.48-1.08)   
  History of allergy        No                   293 (97)         258 (96)         1.00 (ref.)        0.260
                            Yes                  9 (3)            12 (4)           1.68 (0.68-4.15)   
  Alcohol drinking          No                   172 (57)         94 (32)          1.00 (ref.)        \<0.001
                            Yes                  129 (43)         199 (68)         2.46 (1.70-3.57)   
                            Frequency score      2 ± 3; 0 (0-3)   3 ± 3; 2 (0-5)   1.10 (1.03-1.19)   0.008
  Smoking                   No                   106 (35)         49 (17)          1.00 (ref.)        \<0.001
                            Yes                  195 (65)         242 (83)         2.26 (1.51-3.39)   
                            Frequency score      2 ± 3; 0 (0-1)   4 ± 4; 3 (0-9)   1.17 (1.10-1.23)   \<0.001
  Passive smoking           Frequency score      1 ± 2; 0 (0-2)   3 ± 3; 2 (0-5)   1.21 (1.13-1.30)   \<0.001

Categorical variables are shown as count (percentage \[%\]), and continuous variables as mean ± standard deviation.

^1^Frequency score assignment was as follows: 0, never; 1, ≤1 time per month; 2, 2-3 times per month; 3, 1-2 times per week; 4, 3-4 times per week; 5, 5-6 times per week; 6, 1 time per day; 7, 2 times per day; 8, 3 times per day; 9, ≥4 times per day.

^2^Odds ratio (OR) with 95% confidence interval (CI) for the association of each variable with gastric cancer versus control was calculated using multivariable logistic regression with adjustment for sex and age. Significant ORs are marked in bold. ref., reference.

###### 

Food and liquid intake

  Variable               Value/comment^1^   *Controls*       *Patients*       OR (95% CI)^2^     *P~trend~*
  ---------------------- ------------------ ---------------- ---------------- ------------------ ------------
  Pork                   Frequency score    4 ± 2; 4 (3-6)   4 ± 2; 4 (3-6)   0.89 (0.81-0.98)   0.019
  Chicken                Frequency score    3 ± 1; 3 (2-3)   2 ± 2; 2 (1-3)   0.95 (0.85-1.07)   0.401
  Beef                   Frequency score    2 ± 1; 1 (1-2)   1 ± 1; 1 (1-2)   0.84 (0.72-0.97)   0.021
  Fish                   Frequency score    3 ± 1; 3 (2-3)   2 ± 1; 2 (1-3)   0.82 (0.72-0.92)   0.001
  Egg                    Frequency score    4 ± 2; 5 (3-6)   4 ± 2; 4 (2-5)   0.84 (0.76-0.92)   \<0.001
  Eggs per day           As continuous      1 ± 1; 1 (1-1)   1 ± 1; 1 (1-1)   0.74 (0.55-0.98)   0.037
                         0                  40 (13)          65 (23)          2.17 (1.38-3.40)   0.003
                         1                  229 (76)         181 (63)         1.00 (ref.)        
                         ≥2                 33 (11)          41 (14)          1.35 (0.81-2.25)   
  Processed meat         Frequency score    1 ± 1; 0 (0-1)   1 ± 1; 1 (0-2)   1.23 (1.08-1.40)   0.002
  Pickled food           Frequency score    3 ± 2; 2 (1-5)   4 ± 2; 4 (2-6)   1.21 (1.12-1.31)   \<0.001
  Dried food             Frequency score    1 ± 1; 1 (0-2)   2 ± 2; 2 (1-3)   1.26 (1.12-1.41)   \<0.001
  Smoked/baked food      Frequency score    1 ± 1; 0 (0-1)   1 ± 1; 0 (0-1)   1.19 (1.02-1.38)   0.028
  Vegetables and fruit   Frequency score    6 ± 1; 6 (6-7)   5 ± 2; 6 (4-7)   0.66 (0.59-0.73)   \<0.001
  Beans                  Frequency score    4 ± 2; 4 (3-5)   3 ± 2; 3 (2-4)   0.75 (0.67-0.84)   \<0.001
  Stewed food            Frequency score    2 ± 1; 1 (1-2)   2 ± 1; 1 (1-2)   1.03 (0.91-1.18)   0.638
  Fried food             Frequency score    1 ± 1; 1 (1-2)   2 ± 1; 1 (1-2)   1.07 (0.95-1.21)   0.265
  Cereals                Frequency score    3 ± 2; 3 (2-4)   2 ± 2; 2 (1-3)   0.82 (0.75-0.91)   \<0.001
  Tuber crops            Frequency score    3 ± 2; 3 (2-4)   3 ± 2; 3 (2-3)   0.83 (0.75-0.93)   0.001
  Kelps                  Frequency score    2 ± 1; 2 (1-3)   2 ± 1; 2 (1-2)   0.76 (0.67-0.86)   \<0.001
  Yellow rice wine       Frequency score    4 ± 2; 4 (2-6)   3 ± 2; 2 (0-4)   0.81 (0.75-0.87)   \<0.001
  Soy sauce              Frequency score    5 ± 2; 6 (4-6)   5 ± 2; 5 (4-6)   0.89 (0.81-0.97)   0.009
  Vinegar                Frequency score    4 ± 2; 5 (3-6)   3 ± 2; 3 (2-6)   0.84 (0.78-0.91)   \<0.001
  Monosodium glutamate   Frequency score    3 ± 3; 1 (0-6)   3 ± 3; 3 (0-6)   1.09 (1.02-1.16)   0.006
  Chicken essence        Frequency score    3 ± 3; 2 (0-6)   3 ± 3; 4 (0-6)   1.07 (1.01-1.14)   0.033
  Onion and garlic       Frequency score    6 ± 2; 6 (5-6)   5 ± 2; 5 (3-7)   0.81 (0.74-0.89)   \<0.001
  Pepper                 Frequency score    5 ± 2; 5 (3-6)   4 ± 2; 4 (2-6)   0.85 (0.79-0.92)   \<0.001
  Ginger                 Frequency score    5 ± 2; 6 (5-6)   5 ± 2; 5 (3-6)   0.79 (0.72-0.86)   \<0.001
  Dairy product          Frequency score    1 ± 2; 0 (0-3)   1 ± 2; 1 (0-2)   1.01 (0.92-1.09)   0.999
  Sour taste             Preference score   3 ± 2; 2 (2-4)   3 ± 1; 2 (2-4)   0.86 (0.77-0.97)   0.010
  Sweet taste            Preference score   4 ± 2; 4 (2-5)   4 ± 2; 4 (2-5)   0.91 (0.82-1.01)   0.077
  Bitter taste           Preference score   3 ± 1; 2 (2-4)   2 ± 1; 2 (1-3)   0.70 (0.61-0.80)   \<0.001
  Spicy taste            Preference score   4 ± 2; 4 (3-5)   4 ± 2; 4 (2-5)   0.82 (0.74-0.91)   \<0.001
  Salty taste            Preference score   4 ± 1; 4 (4-5)   4 ± 2; 4 (3-5)   0.98 (0.88-1.10)   0.747

Categorical variables are shown as count (percentage \[%\]), and continuous variables as mean ± standard deviation.

^1^Frequency score assignment was as follows: 0, never; 1, ≤1 time per month; 2, 2-3 times per month; 3, 1-2 times per week; 4, 3-4 times per week; 5, 5-6 times per week; 6, 1 time per day; 7, 2 times per day; 8, 3 times per day; 9, ≥4 times per day. Preference score ranged from 1 (extremely dislike) to 7 (extremely like).

^2^Odds ratio (OR) with 95% confidence interval (CI) for the association of each variable with gastric cancer versus control was calculated using multivariable logistic regression with adjustment for sex and age. Significant ORs are marked in bold.

ref., reference.

###### 

Eating and living habits

  Variable                                       Value/comment^1^           *Controls*       *Patients*       OR (95% CI)^2^     *P~trend~*
  ---------------------------------------------- -------------------------- ---------------- ---------------- ------------------ ------------
  No. of people living together with             As continuous              3 ± 2; 2 (1-4)   3 ± 2; 2 (1-4)   1.10 (1.00-1.21)   0.060
  No. of people eating together with             As continuous              2 ± 2; 2 (1-4)   3 ± 2; 2 (1-4)   1.05 (0.96-1.15)   0.295
  Eating habit                                   Majorly vegetables         139 (46)         70 (25)          1.00 (ref.)        \<0.001
                                                 Balanced                   142 (47)         165 (59)         2.17 (1.49-3.15)   
                                                 Majorly meat               19 (6)           43 (15)          3.77 (2.00-7.10)   
  Cooking habit                                  Majorly steaming/boiling   280 (93)         241 (83)         1.00 (ref.)        \<0.001
                                                 Majorly frying             22 (7)           51 (17)          2.67 (1.55-4.59)   
  Drinking water                                 Well water                 47 (16)          88 (30)          2.36 (1.57-3.55)   \<0.001
                                                 Tap water                  253 (84)         201 (70)         1.00 (ref.)        
  Breakfast                                      Regularity score           2 ± 1; 1 (1-1)   2 ± 1; 2 (1-3)   1.54 (1.33-1.79)   \<0.001
  Lunch                                          Regularity score           1 ± 1; 1 (1-1)   2 ± 1; 2 (1-3)   1.77 (1.48-2.11)   \<0.001
  Supper                                         Regularity score           1 ± 1; 1 (1-1)   2 ± 1; 2 (1-3)   1.78 (1.50-2.12)   \<0.001
  Degree of satiety                              As continuous              8 ± 4            8 ± 2            0.99 (0.93-1.06)   0.800
  Food intake                                    On diet                    42 (14)          30 (11)          0.78 (0.46-1.32)   0.593
                                                 Normal                     195 (66)         182 (68)         1.00 (ref.)        
                                                 Overeating                 59 (20)          56 (21)          1.05 (0.69-1.61)   
  Overeating                                     Frequency score            0 ± 1; 0 (0-1)   1 ± 2; 0 (0-2)   1.47 (1.28-1.68)   \<0.001
  Thick liquid intake before meal                Frequency score            1 ± 2; 0 (0-1)   1 ± 2; 0 (0-2)   1.05 (0.95-1.15)   0.342
  Thin liquid intake before meal                 Frequency score            1 ± 2; 0 (0-1)   2 ± 3; 1 (0-3)   1.13 (1.05-1.21)   0.001
  Thick liquid intake during meal                Frequency score            1 ± 2; 0 (0-1)   2 ± 2; 1 (0-3)   1.13 (1.03-1.22)   0.006
  Thin liquid intake during meal                 Frequency score            1 ± 2; 0 (0-1)   2 ± 2; 1 (0-3)   1.12 (1.04-1.21)   0.004
  Thick liquid intake after meal                 Frequency score            2 ± 3; 1 (0-5)   2 ± 2; 1 (0-3)   0.89 (0.83-0.96)   0.002
  Thin liquid intake after meal                  Frequency score            1 ± 3; 0 (0-2)   3 ± 3; 2 (0-5)   1.19 (1.11-1.27)   \<0.001
  Not sufficiently chewing                       Frequency score            2 ± 2; 1 (0-4)   3 ± 3; 2 (0-5)   1.16 (1.08-1.23)   \<0.001
  Doing other things while eating                Frequency score            1 ± 2; 0 (0-1)   2 ± 2; 0 (0-2)   1.13 (1.04-1.22)   0.005
  Swallowing hot food without adequate cooling   Frequency score            1 ± 2; 0 (0-2)   3 ± 3; 2 (0-5)   1.25 (1.16-1.35)   \<0.001
  Eating deteriorated food                       Frequency score            0 ± 1; 0 (0-0)   1 ± 1; 0 (0-1)   1.87 (1.48-2.35)   \<0.001
  Eating overnight food                          Frequency score            2 ± 2; 2 (0-4)   3 ± 3; 3 (1-5)   1.16 (1.06-1.26)   0.001
  Eating within 0.5 h after sports               Frequency score            1 ± 2; 0 (0-2)   2 ± 2; 1 (0-3)   1.13 (1.03-1.23)   0.008
  Rest hours after meal                          As continuous              1 ± 1; 1 (0-1)   1 ± 1; 1 (1-1)   1.05 (0.82-1.34)   0.723
  Eating midnight snack                          Frequency score            0 ± 1; 0 (0-0)   1 ± 2; 0 (0-1)   1.54 (1.29-1.83)   \<0.001
  Eating at home                                 Frequency score            7 ± 2; 8 (7-8)   7 ± 2; 8 (6-8)   0.88 (0.81-0.96)   0.004
  Eating at canteen                              Frequency score            1 ± 2; 0 (0-0)   1 ± 2; 0 (0-1)   1.12 (1.02-1.22)   0.017
  Eating box lunch                               Frequency score            1 ± 2; 0 (0-1)   1 ± 2; 1 (0-2)   1.06 (0.96-1.17)   0.256
  Milk before sleep                              Frequency score            1 ± 2; 0 (0-1)   1 ± 1; 0 (0-1)   0.93 (0.84-1.03)   0.183
  Nighttime sleep hours                          As continuous              8 ± 1; 8 (7-8)   8 ± 1; 8 (7-8)   0.94 (0.84-1.06)   0.341
  Noontime sleep hours                           As continuous              1 ± 1; 1 (1-2)   1 ± 1; 1 (0-2)   0.99 (0.81-1.23)   0.957
  Sleep quality                                  Good                       94 (31)          46 (17)          1.00 (ref.)        \<0.001
                                                 Moderate                   90 (30)          82 (31)          1.88 (1.17-3.02)   
                                                 Poor                       115 (38)         140 (52)         2.81 (1.80-4.39)   
  Going to bed regularly                         Frequency score            5 ± 2; 6 (4-6)   4 ± 2; 4 (1-6)   0.80 (0.74-0.87)   \<0.001
  Dreaming                                       Frequency score            3 ± 2; 3 (1-5)   3 ± 2; 3 (2-5)   1.02 (0.94-1.11)   0.608
  Afternoon nap                                  Frequency score            4 ± 2; 4 (1-6)   3 ± 2; 4 (1-6)   0.93 (0.87-1.00)   0.048
  Heavy housework                                Frequency score            3 ± 3; 3 (1-6)   3 ± 3; 2 (1-6)   1.00 (0.94-1.07)   0.925
  Light housework                                Frequency score            5 ± 2; 5 (3-6)   4 ± 3; 5 (2-6)   1.01 (0.94-1.09)   0.724
  Housework hours per day                        As continuous              2 ± 2; 2 (1-4)   3 ± 2; 2 (1-3)   1.06 (0.98-1.15)   0.158
  Exercise                                       Frequency score            3 ± 3; 3 (0-6)   3 ± 3; 3 (0-5)   0.95 (0.89-1.01)   0.081
  Exercise hours per day                         As continuous              2 ± 3; 1 (0-3)   2 ± 3; 1 (0-3)   1.02 (0.96-1.09)   0.491

Categorical variables are shown as count (percentage \[%\]), and continuous variables as mean ± standard deviation.

^1^Regularity score ranged from 1 (very regular) to 5 (very irregular). Frequency score assignment was as follows: 0, never; 1, ≤1 time per month; 2, 2-3 times per month; 3, 1-2 times per week; 4, 3-4 times per week; 5, 5-6 times per week; 6, 1 time per day; 7, 2 times per day; 8, 3 times per day; 9, ≥4 times per day.

^2^Odds ratio (OR) with 95% confidence interval (CI) for the association of each variable with gastric cancer versus control was calculated using multivariable logistic regression with adjustment for sex and age. Significant ORs are marked in bold. ref., reference.

###### 

Factors associated with gastric cancer using full multivariable-adjusted model, overall and by location

  Variable                                       Value/comment^1^           Overall gastric cancer   Cardia cancer   Non-cardia cancer                                        
  ---------------------------------------------- -------------------------- ------------------------ --------------- ---------------------- ------------ -------------------- ------------
                                                                            OR (95% CI)^2^           *P~trend~*      OR (95% CI)^2^         *P~trend~*   OR (95% CI)^2^       *P~trend~*
  Education                                      Uneducated                 1.00 (ref.)              0.014           1.00 (ref.)            0.079        1.00 (ref.)          0.012
                                                 Primary school             0.27 (0.09-0.78)                         0.03 (\<0.01-0.83)                  0.11 (0.02-0.64)     
                                                 Middle school              0.21 (0.06-0.72)                         \<0.01 (\<0.01-0.12)                0.21 (0.03-1.34)     
                                                 High school                1.51 (0.38-6.03)                         0.09 (\<0.01-4.27)                  1.81 (0.24-14.00)    
                                                 College/university         0.46 (0.10-2.12)                         0.20 (\<0.01-15.73)                 0.05 (\<0.01-0.66)   
  Eating habit                                   Majorly vegetables         0.23 (0.09-0.56)         0.003           0.03 (\<0.01-0.44)     0.037        0.11 (0.02-0.46)     0.011
                                                 Balanced                   1.00 (ref.)                              1.00 (ref.)                         1.00 (ref.)          
                                                 Majorly meat               0.34 (0.10-1.19)                         0.32 (0.01-9.57)                    0.43 (0.07-2.62)     
  Cooking habit                                  Majorly steaming/boiling   1.00 (ref.)              0.001                                                                    
                                                 Majorly frying             10.23 (2.70-38.80)                                                                                
  Sleep quality                                  Good                       1.00 (ref.)              0.015                                                                    
                                                 Moderate                   1.01 (0.38-2.70)                                                                                  
                                                 Poor                       3.18 (1.23-8.23)                                                                                  
  Smoking                                        Frequency score            1.28 (1.12-1.46)         \<0.001         1.64 (1.12-2.41)       0.012        1.32 (1.07-1.61)     0.009
  Egg                                            Frequency score                                                     0.32 (0.12-0.83)       0.019                             
  Pickled food                                   Frequency score            1.41 (1.16-1.71)         \<0.001         2.00 (1.10-3.63)       0.023        1.55 (1.12-2.14)     0.008
  Vegetables and fruit                           Frequency score            0.60 (0.46-0.79)         \<0.001         0.16 (0.06-0.45)       0.001        0.73 (0.51-1.05)     0.094
  Beans                                          Frequency score            0.73 (0.55-0.97)         0.032                                               0.54 (0.35-0.86)     0.009
  Kelps                                          Frequency score            0.72 (0.54-0.96)         0.026           0.24 (0.09-0.61)       0.003                             
  Vinegar                                        Frequency score                                                                                         0.65 (0.46-0.92)     0.015
  Pepper                                         Frequency score            0.84 (0.68-1.03)         0.090           0.47 (0.26-0.83)       0.010                             
  Sour taste                                     Preference score           0.77 (0.59-1.00)         0.047                                                                    
  Bitter taste                                   Preference score           0.50 (0.36-0.69)         \<0.001         0.14 (0.05-0.41)       \<0.001      0.38 (0.22-0.65)     0.001
  Spicy taste                                    Preference score                                                                                        0.57 (0.38-0.86)     0.008
  Thin liquid intake during meal                 Frequency score                                                     2.27 (1.12-4.61)       0.024                             
  Thin liquid intake after meal                  Frequency score            1.27 (1.06-1.52)         0.008                                               1.45 (1.12-1.87)     0.005
  Swallowing hot food without adequate cooling   Frequency score            1.21 (1.00-1.47)         0.045                                               1.44 (1.07-1.95)     0.017
  Supper                                         Regularity score                                                    6.37 (1.20-33.88)      0.030                             
  Not sufficiently chewing                       Frequency score            1.18 (1.00-1.40)         0.058           2.69 (1.48-4.86)       0.001                             
  Doing other things while eating                Frequency score            1.23 (1.01-1.50)         0.041                                               1.50 (1.10-2.05)     0.011
  Eating deteriorated food                       Frequency score            1.37 (0.95-1.96)         0.093           7.84 (2.32-26.49)      0.001                             
  Eating overnight food                          Frequency score            1.25 (1.03-1.52)         0.025                                               1.57 (1.13-2.18)     0.007
  Eating midnight snack                          Frequency score            1.49 (1.09-2.03)         0.013           3.57 (1.04-12.30)      0.044        2.04 (1.22-3.41)     0.007
  Going to bed regularly                         Frequency score            0.81 (0.68-0.96)         0.018                                               0.74 (0.56-0.96)     0.025

1Frequency score assignment was as follows: 0, never; 1, ≤1 time per month; 2, 2-3 times per month; 3, 1-2 times per week; 4, 3-4 times per week; 5, 5-6 times per week; 6, 1 time per day; 7, 2 times per day; 8, 3 times per day; 9, ≥4 times per day. Preference score ranged from 1 (extremely dislike) to 7 (extremely like). Regularity score ranged from 1 (very regular) to 5 (very irregular).

2Odds ratio (OR) with 95% confidence interval (CI) for the association of each variable with cancer (overall, cardia, and non-cardia) versus control was calculated using multivariable logistic regression with adjustment for sex, age, and all significant variables identified in the preliminary models adjusting for sex and age only. Results with P \< 0.10 are shown, and significant ORs with P \< 0.05 are marked in bold. ref., reference.

[^1]: \*Lei Huang, Lei Chen, Zhong-Xuan Gui, and Shun Liu contributed equally to this work.

[^2]: Competing Interests: The authors have declared that no competing interest exists.