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]


1. Introduction {#sec1-ijerph-15-02596}
===============

With the development of society, our concern about diseases has shifted from the traditional focus on diseases such as cancer to the prevalence of chronic diseases. Indeed, chronic diseases pose a serious threat to human health \[[@B1-ijerph-15-02596]\]. Gallbladder disease is a common chronic disease, and its prevalence varies from 4% to 73% in different regions \[[@B2-ijerph-15-02596]\], bringing serious financial burden to regional governments. Gallbladder diseases are common in the population, especially in some European countries and the United States \[[@B3-ijerph-15-02596],[@B4-ijerph-15-02596]\]. However, there have been few reports regarding the prevalence of gallbladder diseases in Asian countries.

Most of the studies on the related factors of gallbladder diseases have been conducted in western developed countries. Previous studies from the United States have suggested that smoking (both past and current) as well as saturated fat and cholesterol intakes are important risk factors. On the other hand, fruits, vegetables, and foods rich in dietary fiber act as protective factors against gallbladder diseases \[[@B5-ijerph-15-02596]\]. Another study from the United States confirmed that the protein intake is associated with lower risk of gallbladder diseases \[[@B6-ijerph-15-02596]\]. The results of the above studies show that diet and lifestyle habits may be associated with gallbladder diseases. In China, the largest developing country in the world, people's living standards have improved significantly in the past 10 years, and the health problems derived from lifestyle changes have attracted much attention. In particular, the incidence of gallbladder diseases has increased year by year. Therefore, in this study, we conduct a study to investigate the prevalence of gallbladder diseases in the northeastern Chinese population and the association of diet and lifestyle with gallbladder diseases. There have been some earlier studies showing that diabetes and dyslipidemia are related to the occurrence of gallbladder diseases \[[@B7-ijerph-15-02596],[@B8-ijerph-15-02596],[@B9-ijerph-15-02596]\]. Therefore, we also considered the relationship between several other common chronic diseases and gallbladder diseases in this study.

At present, there is no nationwide survey data on gallbladder diseases in China. Through the investigation of chronic diseases in Jilin Province, we aimed to determine the prevalence of gallbladder diseases in China and find possible association factors for gallbladder disease.

2. Materials and Methods {#sec2-ijerph-15-02596}
========================

2.1. Study Population {#sec2dot1-ijerph-15-02596}
---------------------

This study was part of a cross-sectional survey of chronic diseases in Jilin Province conducted from June 2012 to August 2012 \[[@B10-ijerph-15-02596],[@B11-ijerph-15-02596]\]. The resident population of Jilin Province was 27.5 million at the time. In order to ensure the representativeness of the survey samples, the differences in economic level, the uniformity of geographic coverage, and the feasibility of the survey were considered in different regions of the province. A multistage stratified random cluster sampling method was adopted. (For more information on crowd sampling, please refer to the articles previously published by our group \[[@B12-ijerph-15-02596]\].) According to the sampling plan, a total of 32 districts/counties in nine cities of the province were taken as investigation points. We considered stratification factors, such as urban and rural areas, gender, and age groups, and sampled them according to one thousandth of the province's total population. The number of planned survey samples was 23,050. However, due to the weather, the determined sample size was 21,449. In the end, 21,435 people completed the investigation. The response rate of subjects in this study was 93%.

Our study was conducted in accordance with the bioethics principles of the Declaration of Helsinki. The study was authorized by the Ethics Committee of Jilin University School of Public Health (Reference Number: 2012-R-011) and the Bureau of Public Health of Jilin Province (Reference Number: 2012-10). All participants voluntarily joined this study with informed consent.

2.2. Data Collection {#sec2dot2-ijerph-15-02596}
--------------------

Survey methods were divided into centralized investigation and household survey. The staff at the investigation points made an appointment according to the sample list. The investigators conducted one-on-one surveys with the research subjects. Then, a physical examination, blood glucose test, and blood sample collection were taken of the survey subjects. Within one week after the investigation ended, the investigation team fed back the results and the reports of the lipids test to the investigation points and informed respondents by telephone to collect them. Investigators participated in systematic training and conducted a preinvestigation before the formal investigation. All instruments were corrected before investigation. The survey was verified on site and afterwards to ensure its correctness. We used the parallel double input method to record the data.

The gallbladder diseases we studied included cholecystitis and gallstones. All patients with gallbladder diseases in the past year had been diagnosed by doctors in hospitals above the county level. Doctors diagnosed gallbladder diseases based on cholecystitis and gallstones according to the International Classification of Diseases, 10th Revision (ICD-10) definition. Annual prevalence was used to indicate the distribution of gallbladder disease in the past year. The sociodemographic factors and lifestyle of the respondents were collected by the investigators. People who "never drink" meant they have drunk no more than 12 glasses of alcohol throughout their life. "Never smokers" meant they have never smoked in their life or their total number of smokes did not exceed 100 cigarettes. "Former smokers" meant people who have smoked more than 100 cigarettes in their life but do not smoke now. Current smokers meant they have smoked more than 100 cigarettes in their life and still smoke \[[@B13-ijerph-15-02596]\].

According to the living standards of residents in Jilin Province, we divided the monthly income per capita of the family into three levels: low (\<1000 yuan/month), middle (1000--3000 yuan/month), and high income (≥3000 yuan/month). Regular diet referred to eating three meals a day on time. Taste of diet included salty, light, and suitable, and the subjects were allowed to choose their own preferences regarding their tastes. The consumption frequency of vegetables, fruits, meat products, seafood, soy products, and milk were divided into three categories: everyday, sometimes, and few or never. Sometimes eat referred to the intake of the abovementioned foods at a frequency of ≥2 times/week. Few or never eat referred to the frequency of ingestion of these foods being \<2 times/week. The above criteria came from the recommendations of the local health bureau.

Hypertension was defined as systolic blood pressure (SBP) of ≥140 mmHg or diastolic blood pressure (DBP) of ≥90 mmHg. Both SBP and DBP were taken as the average of two measurements, which were conducted at least 5 min apart \[[@B14-ijerph-15-02596]\]. Hyperlipidemia was defined as total cholesterol (TC) of ≥5.2 mmol/L, triglyceride (TG) of ≥1.7 mmol/L, high-density lipoprotein cholesterol (HDL-C) of \<1.0 mmol/L, or low-density lipoprotein cholesterol (LDL-C) of ≥3.4 mmol/L \[[@B15-ijerph-15-02596]\]. Diabetes was defined as a history of taking hypoglycemic agents and diabetic or fasting blood glucose of ≥7.0 mmol/L \[[@B16-ijerph-15-02596]\].

2.3. Statistical Analysis {#sec2dot3-ijerph-15-02596}
-------------------------

Data was input in the computer by Epidata (Version 3.1, Odense, Denmark) and analyzed by SPSS (Version 24.0, IBM SPSS, IBM Corp, Armonk, NY, USA). Categorical variables were expressed as frequency. Comparisons between groups with and without gallbladder diseases with regard to sociodemographic, life behaviors, and common chronic diseases were conducted using Rao--Scott x^2^ test. All the variables that significantly differed between the two groups in the univariate analyses were included in Model 2 (multivariate logistic regression) by stepwise method to examine their independent associations with gallbladder disease. Prevalence odds ratio (POR) with 95% confidence intervals (CIs) was calculated in Model 1 (univariate logistic regression) and Model 2. *p* \< 0.05 (two-sided) was considered as statistically significant.

3. Results {#sec3-ijerph-15-02596}
==========

The study involved 21,435 subjects, of whom 10,337 were males and 11,098 were females. The gender ratio (males: females) was 1:1.07, and the average age was 47.07 ± 13.41 years (46.16 ± 13.95 years in males and 47.91 ± 12.82 years in females). The annual prevalence of gallbladder diseases was 8.8% (males 4.4%, females 12.8%).

[Table 1](#ijerph-15-02596-t001){ref-type="table"} shows the relationship between sociodemographic characteristics, living behaviors, and common chronic diseases and gallbladder diseases according to the results of univariate analysis. Variables like gender, age, residence, education, family income, smoking habits, drinking, regular diet, taste of diet, eat breakfast every day, physical exercise, diabetes, hyperlipidemia, and hypertension were correlated with gallbladder diseases as was the intake frequency of fruit, meat, seafood, soy products and milk. In addition, we also analyzed the relationship between sleep time and gallbladder disease and found that sleep duration was also closely related to gallbladder diseases.

We included these significant factors in Model 2 by stepwise method. Our analyses revealed that female (POR = 3.13, 95% CIs: 2.76--3.55), older people (30--45 years (POR = 2.79, 95% CIs: 2.06--3.77), 45--60 years (POR = 4.26, 95% CIs: 3.17--5.73), 60--79 years (POR = 4.72, 95% CIs: 3.48--6.41)), people living in rural areas (POR = 1.65, 95% CIs: 1.49--1.82), smoking (current smoker (POR = 1.15, 95% CIs: 1.01--1.31), former smoker (POR = 1.37, 95% CIs: 1.13--1.66)), the consumption frequency of seafood (eat every day (POR = 0.77, 95% CIs: 0.63--0.93), sometimes eat (POR = 0.84, 95% CIs: 0.76--0.94)), and consumption frequency of soy products (eat every day (POR = 0.50, 95% CIs: 0.44--0.58), sometimes eat (POR = 0.56, 95% CIs: 0.48--0.65)) were associated with gallbladder diseases ([Table 2](#ijerph-15-02596-t002){ref-type="table"}).

4. Discussion {#sec4-ijerph-15-02596}
=============

Gallbladder diseases seriously affect the quality of life of patients. In this cross-sectional study, we investigated the annual prevalence of gallbladder diseases and related factors. The annual prevalence of adult gallbladder diseases in China's Jilin Province was 8.8% (4.4% for men and 12.8% for women). A survey based on America of gallbladder diseases also yielded similar results \[[@B17-ijerph-15-02596],[@B18-ijerph-15-02596]\], but the results of an investigation based on the prevalence of gallbladder diseases in India were lower than ours \[[@B19-ijerph-15-02596]\]. However, the two studies were very different from our research. Firstly, Americans are diverse, and there have previously been reports that ethnicity is also an important factor in the association of gallbladder diseases. Secondly, the Indian study included gallstones and gallbladder cancer, i.e., the definition of gallbladder diseases was different from ours. Therefore, the above two studies do not provide much reference to us, and a study for the Chinese population was necessary. Our findings are mainly applicable to the population of northern China but have an important reference value for the study of gallbladder diseases in other parts of China.

In line with most studies, we found females had a higher correlation with gallbladder diseases than males \[[@B5-ijerph-15-02596],[@B20-ijerph-15-02596]\]. Some researchers have found that the history of reproductive health, multiple births, and oral contraceptives increase the risk of gallbladder diseases \[[@B21-ijerph-15-02596],[@B22-ijerph-15-02596]\]. The reports from these literatures show that some female hormones make them more susceptible to gallbladder diseases than males. The reason for this phenomenon may also be the existence of some special genes in the female body, making them more susceptible to gallbladder diseases than males.

Few scholars have compared the prevalence of gallbladder diseases between city and rural areas. In this study, we found that there was a greater correlation between people living in rural areas and gallbladder diseases compared to those living in city areas. The reason for this result may be that, despite of the level of hygiene and medicine, people living in rural areas have a single diet compared to city people. In rural China, as people's living standards improve, more and more people are starting to eat more meat and regard this as a symbol of quality of life rather than paying attention to a reasonable mix of diet. It is well known that some specific diets usually have connection to certain diseases.

Elderly people were at higher risk of gallbladder diseases than young people. This conclusion was consistent with others studies \[[@B23-ijerph-15-02596],[@B24-ijerph-15-02596]\]. A possible reason for the result may be the marked aging of the function of organs, meaning resistance to the disease among the elderly is limited. There is also a possibility that older people suffer from a variety of chronic diseases at the same time, and other diseases promote the occurrence of gallbladder diseases.

In good agreement with other studies, we found that smoking is associated with gallbladder diseases. However, its biological mechanism remains unclear \[[@B25-ijerph-15-02596],[@B26-ijerph-15-02596]\]. Other studies have shown that smoking may affect serum lipid and lipoprotein concentrations, and these serological changes may be associated with gallbladder diseases \[[@B27-ijerph-15-02596]\]. In our study, we divided smoking habits into three categories: current smokers, former smokers, and never-smokers. We found that former smokers were 1.37 times more likely to have gallbladder diseases than those who had never smoked, and current smokers were 1.15 times more likely to have gallbladder diseases than those who had never smoked. The reason for these results may be that we did not count the duration of smoking in this survey. Therefore, there may have been cases where those who had quitted smoking had smoked for a longer period than those who are currently smoking. The mechanisms by which smoking is associated with gallbladder diseases are complex and require further study.

Our results suggested that the higher the frequency of intake of seafood and soy products, the lower was the likelihood of gallbladder diseases. Some studies have shown that vegetables protein intake is associated with lower risk of gallbladder diseases and that there is no association between animal protein intake and risk of gallbladder diseases \[[@B6-ijerph-15-02596],[@B28-ijerph-15-02596]\]. Seafood contains large amounts of unsaturated fatty acids, most of which are long-chain polyunsaturated fatty acids, and can reduce the cholesterol saturation in the bile, meaning the ability of bile to dissolve cholesterol is always within the normal range \[[@B29-ijerph-15-02596]\]. At the same time, seafood and soy products contain less triglycerides and cholesterol, which are also conducive to maintaining the normal metabolism of bile \[[@B30-ijerph-15-02596]\]. All these are good for maintaining the normal function of bile. Therefore, we believe that regular intake of seafood and soy products may reduce the occurrence of gallbladder disease.

Some studies have investigated the association between sleep duration and chronic diseases. Among them, sleep duration and gallbladder disease has been shown to be related \[[@B31-ijerph-15-02596]\]. In our study, we also included sleep duration in the univariate analysis. However, we did not find a similar association in multivariate analysis. The reason for this variance may be because previous studies only included people in the 18--59 age group.

This research comprised a large sample size, and the sample was also sufficiently representative. However, the study still had some limitations. First, this study was a cross-sectional study with the primary purpose being to describe the annual prevalence of gallbladder disease and to find possible associated factors; therefore, it did not test or validate the cause hypothesis. Second, although this was a large epidemiological survey, there were still some meaningful variables that were not included in the questionnaire. Third, some variables such as smoking, drinking, and some dietary factors were subjectively reported by the subjects and were not the result of objective testing, meaning there may have been some bias. Finally, the results of this study can only represent the annual prevalence of gallbladder disease in the population of northern China. Therefore, the results should be cautiously used when explaining the annual prevalence of gallbladder disease in other parts of the country.

5. Conclusions {#sec5-ijerph-15-02596}
==============

The results of our study suggest that demographic characteristics and dietary intake are associated with gallbladder disease. In particular, female and older people have significant correlations with gallbladder disease. At the same time, intake of seafood and soy products is also associated with gallbladder disease. A larger research is needed in the future to confirm these findings.

This research was supported by the Natural Science Foundation of China (grant no. 81673253), the Projects of International Cooperation and Exchanges NSFC (no. 81320108025), Norman Bethune Program of Jilin university (Grant Number: 2015227), and the Scientific Research Foundation of the Health Bureau of Jilin Province, China (Grant Number: 2011Z116). The authors would like to thank the teachers and students of Jilin University for their epidemiological investigation.

Q.K. and Q.Y. came up with the original idea for the study and carried out the design. G.K. and Q.Y. provided valuable insights regarding the methodological approach and organization of the manuscript. Q.K., G.K., R.L., and X.Z. carried out the statistical analysis and reviewed the consistency of data included in the paper. Q.K. drafted the manuscript. Y.Y. and Q.Y. revised the manuscript. All authors read and approved the final manuscript.

This research was funded by \[Natural Science Foundation of China\] grant number \[81673253\], \[Projects of International Cooperation and Exchanges NSFC\] grant number \[81320108025\], \[Norman Bethune Program of Jilin university\] grant number \[2015227\] and \[Scientific Research Foundation of the Health Bureau of Jilin Province, China\] grant number \[2011Z116\].

The authors declare that there is no conflict of interests.

ijerph-15-02596-t001_Table 1

###### 

Sociodemographic characteristics, living behaviors, and common chronic diseases among subjects with and without gallbladder diseases (univariate analysis).

  Variable                  No Gallbladder Diseases n (%)   Gallbladder Diseases n (%)   x^2^     *p*
  ------------------------- ------------------------------- ---------------------------- -------- ---------
  Female                    9681 (49.50%)                   1417 (75.50%)                464.77   \<0.001
  Age                                                                                    307.20   \<0.001
  18--29                    2466 (12.60%)                   49 (2.60%)                            
  30--44                    6112 (31.20%)                   416 (22.20%)                          
  45--59                    7375 (37.70%)                   902 (48.10%)                          
  60--79                    3606 (18.40%)                   509 (27.10%)                          
  Residence (Rural)         9110 (46.60%)                   1173 (62.50%)                174.47   \<0.001
  Education (year) \>9      8512(43.50%)                    562(30.00%)                  128.98   \<0.001
  Family income (yuan)                                                                   160.25   \<0.001
  \<1000                    7289 (37.30%)                   974 (51.90%)                          
  1000--3000                9477 (48.50%)                   713 (38.00%)                          
  \>3000                    2018 (10.30%)                   122 (6.50%)                           
  Other ^a^                 775 (4.00%)                     67 (3.60%)                            
  Smoking habits                                                                         42.41    \<0.001
  Never smoker              11738 (60.00%)                  1254 (66.80%)                         
  Current smoker            6259 (32.00%)                   464 (24.70%)                          
  Former smoker             1562 (8.00%)                    158 (8.04%)                           
  Drinking                  6484 (33.20%)                   344 (18.30%)                 173.06   \<0.001
  Regular diet              15748 (80.50%)                  1542 (82.20%)                3.10     0.078
  Taste of diet                                                                          7.94     0.019
  Suitable                  6817 (34.90%)                   636 (33.90%)                          
  Salty                     7437 (38.00%)                   675 (36.00%)                          
  Light                     5305 (27.10%)                   565 (30.10%)                          
  Staple food (Rice)        16709 (85.40%)                  1556 (82.90%)                8.40     0.004
  Eat breakfast every day   16164 (82.60%)                  1650 (88.00%)                34.39    \<0.001
  Fresh vegetables                                                                       6.40     0.041
  Few or never eat          295 (1.50%)                     32 (1.70%)                            
  Eat everyday              17482 (89.40%)                  1705 (90.90%)                         
  Sometimes eat             1782 (9.10%)                    139 (7.40%)                           
  Fruit                                                                                  29.15    \<0.001
  Few or never eat          3753 (19.20%)                   457 (24.40%)                          
  Eat everyday              10172 (52.00%)                  906 (48.30%)                          
  Sometimes eat             5634 (28.80%)                   513 (27.30%)                          
  Meat                                                                                   203.63   \<0.001
  Few or never eat          4348 (22.20%)                   677 (36.10%)                          
  Eat everyday              7003 (35.80%)                   464 (24.70%)                          
  Sometimes eat             8208 (42.00%)                   735 (39.20%)                          
  Seafood                                                                                105.73   \<0.001
  Few or never eat          8859 (45.30%)                   1078 (57.50%)                         
  Eat everyday              2135 (10.90%)                   134 (7.10%)                           
  Sometimes eat             8565 (43.80%)                   664 (35.40%)                          
  Soy products                                                                           176.27   \<0.001
  Few or never eat          1656 (8.50%)                    332 (17.70%)                          
  Eat everyday              12018 (61.40%)                  1002 (53.40%)                         
  Sometimes eat             5885 (30.10%)                   542 (28.90%)                          
  Milk                                                                                   67.03    \<0.001
  Few or never eat          12045 (61.60%)                  1335 (71.20%)                         
  Eat everyday              3214 (16.40%)                   228 (12.20%)                          
  Sometimes eat             4300 (22.00%)                   313 (16.70%)                          
  Physical exercise                                                                      40.40    \<0.001
  Often                     5749 (29.40%)                   637 (34.00%)                          
  Occasionally              4870 (24.90%)                   350 (18.70%)                          
  Never                     8940 (45.70%)                   889 (47.40%)                          
  Sleep duration                                                                         48.73    \<0.001
  \<7                       6923 (35.40%)                   816 (43.50%)                          
  7--8                      10549 (53.90%)                  887 (47.30%)                          
  \>9                       2087 (10.70%)                   173 (9.20%)                           
  Diabetes                  1156 (5.90%)                    191 (10.20%)                 53.02    \<0.001
  Hyperlipidemia            358 (1.80%)                     79 (4.20%)                   48.58    \<0.001
  Hypertension              3122 (16.00%)                   486 (25.90%)                 120.92   \<0.001

^a^ "Other" indicates that the subjects did not provide an answer.

ijerph-15-02596-t002_Table 2

###### 

Prevalence odds ratio and 95% confidence intervals for correlates of gallbladder diseases to no gallbladder diseases (multivariate logistic regression).

  Variable            Gallbladder Diseases (n = 1876)   Model 1   Model 2             
  ------------------- --------------------------------- --------- ------------------- -------------------
  Residence (Rural)   1173                              62.50     1.91 (1.74--2.11)   1.65 (1.49--1.82)
  Female              1417                              75.50     3.15 (2.83--3.51)   3.13 (2.76--3.55)
  Age                                                                                 
  18--29              49                                2.60      1.00                1.00
  30--44              416                               22.20     3.43 (2.54--4.62)   2.79 (2.06--3.77)
  45--59              902                               48.10     6.16 (4.60--8.24)   4.26 (3.17--5.73)
  60--79              509                               27.10     7.10 (5.28--9.57)   4.72 (3.48--6.41)
  Smoking habits                                                                      
  Never-smoker        1254                              66.80     1.00                1.00
  Current smoker      464                               24.70     0.69 (0.62--0.78)   1.15 (1.01--1.31)
  Former smoker       158                               8.04      0.95 (0.80--1.13)   1.37 (1.13--1.65)
  Seafood                                                                             
  Few or never eat    1078                              57.50     1.00                1.00
  Eat everyday        134                               7.10      0.52 (0.43--0.62)   0.77 (0.63--0.93)
  Sometimes eat       664                               35.40     0.64 (0.58--0.71)   0.84 (0.76--0.94)
  Soy products                                                                        
  Few or never eat    332                               17.70     1.00                1.00
  Eat everyday        1002                              53.40     0.42 (0.36--0.48)   0.50 (0.44--0.58)
  Sometimes eat       542                               28.90     0.46 (0.40--0.53)   0.56 (0.48--0.65)