Is density of neighbourhood restaurants associated with BMI in rural Chinese adults? A longitudinal study from the China Health and Nutrition Survey - most popular side dishes in restaurants

Neighborhood availability at target restaurants is associated with weight status.
However, in the Chinese population, little is known about the relationship between restaurant use and obesity.
This study aims to explore the relationship between density and body mass index of nearby restaurants (BMI)in rural China.
Longitudinal study using data design from the China Health and Nutrition Survey (CHNS)was conducted.
Participants of 2004, 2006, 2009 and 2011 CHNS aged 18 and above were recruited separately
Layered random intercept-
Slope growth models for repeated BMI observations were estimated in the study.
The data came from rural communities in nine provinces in China.
There were also 11 women, 835 men, 12 women, 561 women-
Years assessed in this study.
Results The main outcome of this study was weight status.
It is defined as a BMI value, a continuous variable calculated by dividing by weight (kg)
Square by height (m2).
The results showed that among men, the increase in a nearby indoor restaurant was related to 0.
BMI increased by 01 kg/m2, and an increase in a fixed outdoor food stall was associated with 0.
BMI decreased by 01 kg/m2, while in women, an increase in a nearby indoor restaurant was associated with 0.
BMI increased by 005 kg/m2 and increased rapidly by 1-
The food restaurant and a fixed outdoor food stall are related to 0. 02 and 0.
BMI decreased by 004 kg/m2 respectively.
Conclusion The density of community restaurants is significantly associated with BMI in rural China.
The results show that it is necessary to provide healthy food choices and formulate relevant public health policies in order to solve the obesity problem of Chinese rural adults.
Neighborhood availability at target restaurants is associated with weight status.
However, in the Chinese population, little is known about the relationship between restaurant use and obesity.
This study aims to explore the relationship between density and body mass index of nearby restaurants (BMI)in rural China.
Longitudinal study using data design from the China Health and Nutrition Survey (CHNS)was conducted.
Participants of 2004, 2006, 2009 and 2011 CHNS aged 18 and above were recruited separately
Layered random intercept-
Slope growth models for repeated BMI observations were estimated in the study.
The data came from rural communities in nine provinces in China.
There were also 11 women, 835 men, 12 women, 561 women-
Years assessed in this study.
Results The main outcome of this study was weight status.
It is defined as a BMI value, a continuous variable calculated by dividing by weight (kg)
Square by height (m2).
The results showed that among men, the increase in a nearby indoor restaurant was related to 0.
BMI increased by 01 kg/m2, and an increase in a fixed outdoor food stall was associated with 0.
BMI decreased by 01 kg/m2, while in women, an increase in a nearby indoor restaurant was associated with 0.
BMI increased by 005 kg/m2 and increased rapidly by 1-
The food restaurant and a fixed outdoor food stall are related to 0. 02 and 0.
BMI decreased by 004 kg/m2 respectively.
Conclusion The density of community restaurants is significantly associated with BMI in rural China.
The results show that it is necessary to provide healthy food choices and formulate relevant public health policies in order to solve the obesity problem of Chinese rural adults.
In the past few decades, China has experienced tremendous economic and social changes that have affected their way of life, leading to the prevalence of obesity.
Between 1 and 2030, the number of overweight and obese adults in China is expected to be 0. 669 billion and 0. 141 billion, respectively.
Although the prevalence of overweight in China almost doubled between 1991 and 2004, it is becoming less concentrated in areas with higher levels of urbanization, and the degree of urbanization-
Over time, there has been a decrease in related inequalities.
3 for women living in communities with low initial urbanization scores, higher changes in urbanization levels are associated with a significant increase in the probability of subsequent overweight/obesityup time.
The Chinese diet is changing from traditional to advanced.
High energy density-fat and low-fibre diets. 5 ,6 The low-
The income population is defined as a population with limited social and economic resources, related to the gap in access to healthy food, with the largest decline in cereal food intake.
Due to rapid urbanization and socio-economic changes, the number of people eating out in China is increasing rapidly.
Between 2000 and 2008, food expenditure for eating out accounted for 14. 70% to 20. 61%.
With the increasing prevalence of obesity and modern eating behavior, especially among low-income people
Among the income crowd, the role of neighborhood food environment is getting more and more attention.
Some international studies have pointed out that the nutritional quality of foods consumed from home is much worse than those eaten or prepared at home because they contain higher fat and energy intake, reduce the intake of fiber and trace nutrients.
8-13 due to the excessive part size of the energy
Intensive food provided in restaurants, eating at home can lead to positive energy balance, leading to the current obesity epidemic in western countries.
14-18 different effects of restaurant food and fast food
Food intake on the body mass index (BMI)
Also found.
Eat out often, especially at buffet, buffet and fast food.
Food restaurants are linked to higher obesity rates.
20 studies emphasize fast-
The density of food restaurants is associated with higher individuals
BMI levels and risk of being obese21, 22;
However, the higher density
The service restaurant is related to the lower weight.
22 due to rapid urbanization and income growth, eating out accounts for a large part of China's diet.
In China, social and economic features highlight the huge differences between urban and rural areas.
Most of the research focuses on urban context, but there is little understanding of the rural population in China.
The reduction of agricultural labor force has led to prominent eating out in rural areas.
Compared with urban residents, the choice of restaurants for rural residents is limited.
Low levels of education and low levels of income are also potential factors contributing to inequality in the food environment.
Therefore, the study of evaluating Urban individuals cannot be applied in the rural context.
In this multi-level study, we looked at the Association of the density of nearby restaurants, which is defined as the number of fast restaurants
Nearby gourmet shops, indoor restaurants and fixed outdoor food stalls have high body mass index for adults in rural China.
In addition, we investigated the effects of the nearby food environment on the weight status of low-weight people
Income of Chinese population.
Methods the population data of this study came from the Survey of Health and Nutrition in China (CHNS)
, Covering nine provinces in China, starting in 1989, followed by 1993, 1997, 2000, 2004, 2006, 2009 and 2011 in 1991.
The survey was originally intended to study the impact of social and economic transformation in Chinese society on their health and nutritional status.
A total of 4400 households, comprising 19 000 persons.
Detailed information about CHNS can be found in the following link: Participants in this study were 2004, 2006, 2009 and 2011 rural Chinese adults aged 18 and over in CHNS.
835 men and 561 women-
The study included many years, while pregnant women, people with disabilities and people with missing values were excluded.
Qualified field staff measured the height and weight of the relevant variables using standard technology and equipment.
BMI is calculated by dividing it by weight (kg)
Square of height (m2).
We used BMI as a continuous variable to examine its association with the density of nearby restaurants. Individual-
Horizontal variables for the following individuals
This study included the level variables: age (years), gender (0=female; 1=male)
Marital status (
1 = married at present; 0=others)
Highest Degree (
0 = Junior High School or below junior high school; 1=high school;
2 = college degree or above)
Per capita household income (RMB/person per year)
Current smoking (0=no; 1=yes), drinking (0=no; 1=yes)
Motorcycle ownership (0=no; 1=yes)
Have a car (0=no; 1=yes)
And moderate/severe physical activity during working hours (0=no; 1=yes). The individual-
The level variable is time-
Different variables except gender.
Neighbourhood-
Horizontal variables we used a multi-dimensional index developed specifically for CHNS to capture the urbanization level of Chinese communities.
The index consists of 12 components, each of which is assigned 10 points and is summarized as a maximum of 120 points.
The index covers population density, transportation infrastructure, housing infrastructure, health infrastructure, availability of social services, communication infrastructure, education level, economic activity, education and income level traditional food market and the existence of Western food institutions.
The higher the index score, the higher the degree of urbanization.
To avoid the effects of confusion, traditional food markets and Western food institutions are excluded from research.
The study included three types of restaurants nearby: fast-
Food restaurant, indoor restaurant and fixed outdoor food stalls.
Using the community questionnaire, the community leader was asked about the number of restaurants currently operated by the community. Fast-
Food restaurants are defined as restaurants or fast food restaurants
Food chain restaurant serving Western food
McDonald's, KFC, Pizza Hut and other fashion food.
An indoor restaurant refers to a restaurant that operates indoors, or operates within a closed structure with a roof and well
Covered walls for cooking and eating indoors.
Food stalls refer to food stalls operated in fixed outdoor locations;
It may have a roof but no walls to cook and eat outdoors.
Statistical analysis using sas v. 9. 2 (
Cary SAS Institute, North Carolina, USA).
Descriptive statistics of individual demographic variables and BMI for men and women in each survey wave were analyzed, respectively, to illustrate the adjustment trend in the sample.
To study the different changes in interest rates over time, we used the difference test between any two consecutive waves of the City Index, fast-density
There are gourmet shops, indoor restaurants and fixed outdoor food stalls nearby.
We estimate
Layered random intercept-
Slope growth model for repeated BMI observations.
The year of investigation was coded 0, 1, 2 and 3 respectively, 2004, 2006, 2009 and 2011, respectively.
In Model 1, only the year of survey was included to study the effect of time on BMI growth. The individual-
Then, as the age grows, the level variable is added to the equation to estimate Model 2 (grand-mean centred)
Marital status (
Ref = not married at present)
Level of education (
Ref = junior high school and below)
Per capita household income (
Ref = low tertiles), drinking (ref=no), smoking (ref=no)
Moderate/severe physical activity (ref=no)
Motorcycle ownership (ref=no)
And car ownership (ref=no).
For Model 3, neighbors-
A horizontal predictor was added on Model 2.
These include fast-
Nearby gourmet shops, indoor restaurants and fixed outdoor food stalls, as well as the urbanization index tertiles.
The population data of this study come from the Survey of Health and Nutrition in China (CHNS)
, Covering nine provinces in China, starting in 1989, followed by 1993, 1997, 2000, 2004, 2006, 2009 and 2011 in 1991.
The survey was originally intended to study the impact of social and economic transformation in Chinese society on their health and nutritional status.
A total of 4400 households, comprising 19 000 persons.
Detailed information about CHNS can be found in the following link: Participants in this study were 2004, 2006, 2009 and 2011 rural Chinese adults aged 18 and over in CHNS.
835 men and 561 women-
The study included many years, while pregnant women, people with disabilities and people with missing values were excluded.
Qualified field staff measured the height and weight of the relevant variables using standard technology and equipment.
BMI is calculated by dividing it by weight (kg)
Square of height (m2).
We used BMI as a continuous variable to examine its association with the density of nearby restaurants. Individual-
Horizontal variables for the following individuals
This study included the level variables: age (years), gender (0=female; 1=male)
Marital status (
1 = married at present; 0=others)
Highest Degree (
0 = Junior High School or below junior high school; 1=high school;
2 = college degree or above)
Per capita household income (RMB/person per year)
Current smoking (0=no; 1=yes), drinking (0=no; 1=yes)
Motorcycle ownership (0=no; 1=yes)
Have a car (0=no; 1=yes)
And moderate/severe physical activity during working hours (0=no; 1=yes). The individual-
The level variable is time-
Different variables except gender.
Neighbourhood-
Horizontal variables we used a multi-dimensional index developed specifically for CHNS to capture the urbanization level of Chinese communities.
The index consists of 12 components, each of which is assigned 10 points and is summarized as a maximum of 120 points.
The index covers population density, transportation infrastructure, housing infrastructure, health infrastructure, availability of social services, communication infrastructure, education level, economic activity, education and income level traditional food market and the existence of Western food institutions.
The higher the index score, the higher the degree of urbanization.
To avoid the effects of confusion, traditional food markets and Western food institutions are excluded from research.
The study included three types of restaurants nearby: fast-
Food restaurant, indoor restaurant and fixed outdoor food stalls.
Using the community questionnaire, the community leader was asked about the number of restaurants currently operated by the community. Fast-
Food restaurants are defined as restaurants or fast food restaurants
Food chain restaurant serving Western food
McDonald's, KFC, Pizza Hut and other fashion food.
An indoor restaurant refers to a restaurant that operates indoors, or operates within a closed structure with a roof and well
Covered walls for cooking and eating indoors.
Food stalls refer to food stalls operated in fixed outdoor locations;
It may have a roof but no walls to cook and eat outdoors.
Statistical analysis using sas v. 9. 2 (
Cary SAS Institute, North Carolina, USA).
Descriptive statistics of individual demographic variables and BMI for men and women in each survey wave were analyzed, respectively, to illustrate the adjustment trend in the sample.
To study the different changes in interest rates over time, we used the difference test between any two consecutive waves of the City Index, fast-density
There are gourmet shops, indoor restaurants and fixed outdoor food stalls nearby.
We estimate
Layered random intercept-
Slope growth model for repeated BMI observations.
The year of investigation was coded 0, 1, 2 and 3 respectively, 2004, 2006, 2009 and 2011, respectively.
In Model 1, only the year of survey was included to study the effect of time on BMI growth. The individual-
Then, as the age grows, the level variable is added to the equation to estimate Model 2 (grand-mean centred)
Marital status (
Ref = not married at present)
Level of education (
Ref = junior high school and below)
Per capita household income (
Ref = low tertiles), drinking (ref=no), smoking (ref=no)
Moderate/severe physical activity (ref=no)
Motorcycle ownership (ref=no)
And car ownership (ref=no).
For Model 3, neighbors-
A horizontal predictor was added on Model 2.
These include fast-
Nearby gourmet shops, indoor restaurants and fixed outdoor food stalls, as well as the urbanization index tertiles.
Results The descriptive demographics of the sample population are shown in Table 1.
A total of 11 men and 835 men and 561 women-
The average age of men increased from 46 years in the years of all survey waves was analyzed. 93 to 51.
Women aged 46 are 30. 86 to 51. 07.
Nearly 85% of respondents are currently married, of whom about 80% are male and 87% are female junior high school or below.
Per capita household income in 2011 almost tripled compared to 2004.
The prevalence of alcohol consumption and smoking among men was high;
About 61% of people drink and 57% smoke.
In terms of moderate/severe physical activity, nearly 59% of men and 44% of women participated in moderate/severe physical activity during working hours.
View this table: View descriptive demographic data on BMI trends in rural Chinese adults in inline View popuptable 1, and the prevalence of men with BMI ≥ 25 increased from 19 to 25.
27% from 2004 to 26.
2011 was 91%, BMI from 1 ≥ 30. 98% to 4. 31%.
The prevalence of women with BMI ≥ 25 also increased from 23.
62% from 2004 to 27.
2011 was 74%, BMI from 3 ≥ 30. 97% to 5. 66%.
Figure 1 plots the percentage of BMI distribution, which indicates weight gain for both men and women during the survey.
Download the new tabDownload figureOpen powerpointFigure1 body mass index (BMI)
Distribution trend of rural adults in China (2004–2011).
About the neighborhood-
Horizontal features, Table 2 shows the growth of the urbanization index of rural communities, with the highest interval growth of 3.
66 from 2006 to 2009, and the other two changes accounted for about 1. 9 increases.
Density of fast-
Food restaurants are relatively low in rural China, while indoor restaurants and fixed outdoor food stalls are the most popular types of restaurants.
According to the survey, there was no significant difference in different types of restaurants around.
View this table: View changes in food environment in rural communities in China: 2004-2011 we estimate that there are three-
Horizontal random interception
Slope linear growth model of male BMI (table 3)and women (table 4)separately.
First, we included only the year of the survey in the model and found a positive correlation between male and female BMI (model 1).
And then in Model 2, we added the time.
Different individual characteristic variables.
Currently, married, highly educated, high family income, alcohol consumption and possession of motorcycles are positively correlated with an increase in male BMI, while smoking and moderate/severe physical activity are negatively correlated with BMI.
High age and current married are positive predictors of BMI for women;
However, higher levels of education and moderate/severe physical activity were significantly associated with lower BMI.
Finally, we evaluated Model 3 to test the community effect.
For men, the nearby variable index is significantly correlated, except for the rapid density
Food restaurant.
Studies have shown that a higher degree of urbanization is associated with an increase in BMI, that is, an increase in a nearby indoor restaurant is associated with 0.
BMI increased by 01 kg/m2, while an increase in a nearby fixed outdoor food stall was associated with 0.
BMI in rural males decreased by 01 kg/m2.
For women, all neighborhood variables were significantly associated with BMI.
The results showed that urbanization was positively correlated with BMI, that is, an increase in a nearby indoor restaurant was positively correlated with 0.
The BMI increased by 005 kg/m2, while an increase was made
Food restaurants or fixed outdoor food stalls are related to 0. 02 or 0.
BMI in rural women decreased by 004 kg/m2.
View this table: from three-
Test the horizontal linear growth model of rural male body mass index (N=11835)
View this table from three-
A horizontal linear growth model for examining the physical quality index of rural women (N=12u2005561)
2004-2011 discusses the upward trend of overweight/obesity among men and women, all age groups, rural/urban areas and all education-level groups over the past decades, with an increase in the number of men, individuals and rural residents aged 18-64 in the Chinese population.
In 2009, the prevalence of overweight, general obesity and abdominal obesity among 23 or 24 rural women was higher than that of urban women, although the trend of rural men in terms of weight status variables was almost similar to that of urban men.
Other studies also reported a downward trend in differences in health and nutritional status between urban and rural areas.
According to a study, among the lower gross domestic product (GDP (GDP)
The increase in per capita gross domestic product is associated with absolute annual changes in the prevalence of overweight/obesity, mainly in rural areas.
26. another study explained that the intake of grains decreased and the consumption of protein/fat increased
Rich food in urban and rural areas is due to low protein/fat prices
The food is rich compared to Rice.
Despite the growing obesity problem in rural China, it is unclear whether environmental risk factors are working.
Previous studies have focused on individual predictors such as lifestyle, physical activity, and eating patterns.
However, more research is currently under way to assess potential environmental factors that may lead to dietary behavior and health status.
Low barriers to obtaining higher energy density foods and low food prices may lead to higher energy and fat intake, which leads to a prevalence of obesity.
Urbanization in China has affected the lifestyle of local residents and may ultimately affect their diet.
Many of them have gradually changed their traditional Chinese diets, including those in rural communities, which are rich in beans, vegetables and coarse grains.
6 This study shows that the income of rural households in China is growing rapidly.
However, the population description shows that rural adults are still characterized by a low level of education and a high level of participation in moderate/severe physical activity.
Rural communities are significantly affected by urbanization.
However, our study found that the number of restaurants had nothing to do with timevaried changes.
There is a huge gap in rural development, which may be the cause of this phenomenon.
However, the results of this study only show trends in the overall rural restaurant environment, and therefore, this may underestimate regional differences.
In order to control the regional socio-economic mixed effects, we added the urbanization index to the final model.
In the rural community, traditional indoor restaurants and fixed outdoor food stalls are the main types of restaurants. type fast-
Catering restaurants account for only a small proportion.
The study found that time was positively associated with both rural men and women in all models.
As for individuals
In the horizontal variables, the BMI value of currently married adults is higher than that of unmarried individuals, while the BMI value of adults participating in moderate/severe physical activity is lower than that of adults without/low physical activity.
The level of education had the opposite effect on the BMI of men and women, with positive associations for men and negative associations for women, which was consistent with previous studies.
In addition, higher incomes, alcohol consumption and possession of motorcycles were associated with higher BMI, while smoking was associated with lower BMI, which was significant in men alone.
On the other hand, age is the main predictor of women, so the BMI of rural elderly women is higher than that of young women.
In rural areas, car ownership is not a statistically significant predictor of BMI.
We added neighbors.
In the model, we found that a large number of indoor restaurants led to an increase in BMI, although more fixed outdoor restaurants led to a decrease in BMI for rural men and women.
A negative correlation was found between the number of fast-
Nearby food restaurants and BMI for rural women.
The urbanization index was positively correlated with the BMI of rural adults, and the association between men was stronger.
Factors that may lead to this finding include the place of diet and the source of food, which may affect daily energy intake.
34 previous studies have shown that eating-away-from-
Compared with eating food at home, the total fat of home food is higher, and vitamin A, iron, fiber and calcium are lower.
However, the results of different types of restaurants in terms of weight status are also inconsistent.
19, 35 density of fast-
Food restaurants are associated with higher BMI, while high density
Service restaurants are associated with lower weight conditions.
Our findings show that they are inconsistent with previous research evidence on neighborhood restaurants and weight status of Chinese rural adults.
In most rural areas of China, men are the heads of households, the main source of household income, higher education and employment, and more social activities and eating out behavior than women. Frequent fast-
Food consumption is reported to be related to the low density of high-energy diets and essential trace nutrients, which may contribute to weight gain in developed countries.
Fast, however-
Food consumption is not popular in China, especially in rural areas, where prices are relatively high and opportunities are low.
37. it is reported that young women with higher incomes have a significant impact on Western countriesstyle fast-
Food consumption.
Women seem to be receptive to western eating patterns, while men prefer traditional eating patterns.
Low consumption of fast food may explain our results and find that there is no correlation between fast food nearby
Restaurants and BMI for rural Chinese men.
For women who consume fast food in rural areas, most of them have a higher socioeconomic status, meaning they have more knowledge and an intention to fight weight gain.
Indoor restaurants are usually full in China.
The restaurant serves a variety of dishes and alcoholic beverages.
They also play an important role in social activities.
When eating outside, people tend to eat larger portions and have more energy.
Dense food and increased alcohol intake compared to eating at home, reducing consumption of vegetables and fruits.
12. 13 among rural adults, the density of nearby indoor restaurants was positively correlated with BMI, indicating that the energy intake of indoor restaurants was high.
On the other hand, the fixed outdoor snack stalls mainly provide simple Chinese food such as pancakes, dumplings and noodles.
The food provided at a fixed outdoor food stall is characterized by convenience, cheap price, limited selection and low nutritional value.
Our results showed that the density of a nearby fixed outdoor food stall was negatively correlated with BMI.
In the past few decades, the rural population has increased dramatically. to-
Urban population flows in China.
Attracting more rural labor.
Employment in agriculture.
39. the intense workload and the limited eating environment have changed the non-
Rural workers are looking for convenient, cheap and convenient food as their own meals, most of which are found at a fixed outdoor snack bar.
Adults in rural areas will soon be looking at the weight status of their peers in urban areas.
Urbanization increases the likelihood of poor health, which is reflected in high fat consumption, according to a study.
40 due to low prices and adequate food supply, even the poor have the ability to buy foods with high fat content and animal origin.
Another study reported that additional income is related to higher income
Especially the fat diet of the poor.
5 Potential adverse effects of urbanization increase, partly due to lower processing costs and higher pricesfat, added-
Bigger sugarportion foods.
It is also important to note that changes in relative prices are the most important.
If the price of fat food and animals
SOURCE Food decreased compared to fresh vegetables, fruits and beans, and the latter had less attraction, especially for the poor.
5, 26 Finally, the results show that there is only a small correlation between the density and BMI of nearby restaurants, so it cannot be concluded as a causal relationship.
Several potential factors that could lead to this were not included in this study, such as work intensity, home location, and frequency of eating out.
There are many factors that affect the prevalence of obesity, and more research should be carried out in the future.
Conclusion The results of sour showed that BMI in rural Chinese adults was significantly correlated with the density of nearby restaurants.
These results have raised concerns about the health situation in rural areas.
For the poor, overweight and poor eating is a bigger burden than the rich in China.
Among rural Chinese adults, urbanization and neighborhood density in indoor restaurants are positive predictors of an increase in BMI.
Unlike most developed countries, fast-
Food restaurants in the community were linked to a decline in BMI among rural women and no association was found among men.
Fixed outdoor food stalls are a common restaurant in China, especially in rural areas, and are negatively correlated with BMI.
Rapid urbanization and rising incomes have changed the way of life in rural China.
However, their knowledge of health and nutrition remains limited in most rural areas.
In order to understand the impact of the nearby restaurant environment on individual dietary intake and dietary behavior, future research is needed.
The authors thank all site staff from the local CDC and participants from the health and nutrition survey in China (CHNS)
From 1989 to 2011.
They also thanked Dr. Zhang Jiguo, MS Zhang Jizhang and MS Jiang Hongru for their suggestions on the paper and for the help of the language editor of Leviana Chandra Huo MS.
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The study was conceived and supervised by Open.
The analysis was completed by WD and CS.
WD leaders write and prepare the manuscript for publication.
HW, ZW and YW assist in research design and partial data analysis.
Funding for this work is provided by the National Institute of Nutrition and Food Safety, the Center for Disease Control and Prevention of China, the population center of Carolina (5 R24 HD050924)
University of North Carolina, Chapel Hill, National Institutes of Health (NIH)(R01-
HD30880, DK056350, R24 HD050924 and R01-HD38700)
National Institutes of Health Fogarty International Center provides financial support for health and nutrition surveys in China (CHNS)
Data collection and analysis archives and future surveys from 1989 to 2011.
The publication was supported by a sub-agreement from the Bloomberg School of Public Health at Johns Hopkins University, funded by Grant No. 1U54hd070725-
01 funded by the office of director of NIH (OD)
Younis Kennedy Schrever National Institute for Children's Health and Human Development and the Office of Behavioral and Social Sciences Research.
There is no competitive interest.
Obtain patient consent.
Ethics approval the study has been approved by the Institutional Review Committee of the University of North Carolina at Chapel El Hill and the National Institute of Nutrition and Food Safety of the China Center for Disease Control and Prevention.
All participants gave written informed consent to their participation in the survey.
Uncommissioned source and peer review;
External peer review.