DOI: https://doi.org/10.21203/rs.3.rs-1509951/v1
With food industry developing so fast around the world and food delivery becomes popular among young adults, people today tend to have meals that are not prepared at home. However, it reminds people to rethink about their body health especially gastric health. In this case, we decided to find out the association between the frequency of having meals not home prepared and the risk of having stomach or intestinal illness. We assumed that people who had meals away from home would be more likely to suffer from gastric diseases. 19,293 adults over twenty years old participated in diet and health questionnaires according to NHANES database from 2011 to 2018. Multivariable regression was used to measure the association between the frequency of having meals out and the risk of having gastric diseases by using Empower Stats. According to the p values and odds ratio values given by Empower Stats, no significant association between the exposure variable and the outcome variable was found. Thus, we drew a conclusion that there was no association between the frequency of eating out and the risk of having gastric diseases.
In recent years, there have been many changes on the dietary structure and eating behaviors of people all over the world [1, 2]. People tend to eat outside instead of preparing meals at home, as the restaurant industry develops fast and take-out food makes people’s life more convenient. This phenomenon can be particularly observed among young children [3]. It reminds people to pay more attention to their eating behaviors and gastric health. Taking Chronic Gastritis as an example, it is one of the most common diseases around the world and hundreds of millions of people suffer from it. Recently, the prevalence of Chronic Gastritis even reaches to 90% [4, 5, 6]. The number alarms us to pay more attention to our gastrointestinal health, especially when considering something to eat or drink.
There have been some former studies which have focused on the association between the frequency of having meals out with overweight and obesity among young children. One showed that having meals out for three times or more had a significant effect on boys with overweight and obesity [7]. The other showed that eating out had become a common trend among school children in some metropolises [8]. Another issue should be taken into consideration is the food safety or whether it would cause diseases or not. A previous study found sandwiches purchased away from home had increased phthalates compared with food prepared at home [9]. Another study connected the dining out behavior to the risk of diabetes mellitus and dyslipidemia among adults [10]. However, the association between eating out and gastric illnesses is unclear.
This study aimed to find out the correlation between the frequency of dining out and the risk of having gastric illnesses based on the data from the National Health and Nutrition Examination Survey (NHANES). It was assumed that people who had eaten out more frequently would have a bigger risk to suffer a gastric illness, whose specific performances are diarrhea and vomiting.
There were a total of 19,293 participants (both males and females) aged over 20 years old who had participated in NHANES during a period from 2011 to 2018 included in the analysis [11]. A flow chart for the screening (Fig. 1) is below. The exposure variable was related to the frequency of having meals that were not prepared at home. All the data were obtained from the questionnaires taken by asking participants several questions such as how many meals they had got that were prepared away from home in places such as restaurants, fast food places, food stands, grocery stores or from vending machines [12]. We defined out-of-home meals as the consumption of meals away from home which are independent of the place of purchase [13].
The outcome variable was also measured by questionnaires, in which participants were asked whether they had a stomach or intestinal illness with vomiting or diarrhea. The outcomes are described by ‘yes’ or ‘no’ replied by the participants. Additional demographic covariates included in the analysis were selected based on known associations with the outcome variables [14, 15]. Multivariable regression was used to evaluate the association between the exposure and outcome variables, adjusting for gender, age, race, education level, marital status, income, body mass index (BMI), and several actions taken to lose weight.
The detail description of 19,293 surveyed participants was shown in Table 1, based on the NHANES database.
of meals not home prepared |
0 or 1 time/ week |
2 times/ week |
3 or 4 times/ week |
≥ 5 times/ week |
p-value |
|
---|---|---|---|---|---|---|
n |
4505 |
3210 |
5475 |
6103 |
||
BMI |
28.5 ± 7.9 |
28.9 ± 7.7 |
29.5 ± 7.8 |
29.4 ± 7.6 |
< 0.001 |
|
having stomach or intestinal illness |
yes |
307 (6.8%) |
227 (7.1%) |
392 (7.2%) |
437 (7.2%) |
0.899 |
cycle |
2011–2012 |
1151 (25.5%) |
729 (22.7%) |
1186 (21.7%) |
1529 (25.1%) |
< 0.001 |
2013–2014 |
1161 (25.8%) |
875 (27.3%) |
1390 (25.4%) |
1583 (25.9%) |
||
2015–2016 |
1135 (25.2%) |
819 (25.5%) |
1433 (26.2%) |
1495 (24.5%) |
||
2017–2018 |
1058 (23.5%) |
787 (24.5%) |
1466 (26.8%) |
1496 (24.5%) |
||
gender |
male |
2054 (45.6%) |
1377 (42.9%) |
2522 (46.1%) |
3510 (57.5%) |
< 0.001 |
female |
2451 (54.4%) |
1833 (57.1%) |
2953 (53.9%) |
2593 (42.5%) |
||
age |
21–40 |
883 (19.6%) |
903 (28.1%) |
1880 (34.3%) |
2748 (45.0%) |
< 0.001 |
41–60 |
1506 (33.4%) |
1051 (32.7%) |
1823 (33.3%) |
2120 (34.7%) |
||
> 60 |
2116 (47.0%) |
1256 (39.1%) |
1772 (32.4%) |
1235 (20.2%) |
||
race |
Mexican American |
639 (14.2%) |
512 (16.0%) |
742 (13.6%) |
709 (11.6%) |
< 0.001 |
Other Hispanic |
606 (13.5%) |
300 (9.3%) |
542 (9.9%) |
540 (8.8%) |
||
Non-Hispanic White |
1389 (30.8%) |
1315 (41.0%) |
2183 (39.9%) |
2455 (40.2%) |
||
Non-Hispanic Black |
1087 (24.1%) |
561 (17.5%) |
1249 (22.8%) |
1471 (24.1%) |
||
Non-Hispanic Asian |
638 (14.2%) |
401 (12.5%) |
566 (10.3%) |
677 (11.1%) |
||
Other Race - Including Multi-Racial |
146 (3.2%) |
121 (3.8%) |
193 (3.5%) |
251 (4.1%) |
||
education |
below high school |
799 (17.7%) |
364 (11.3%) |
340 (6.2%) |
245 (4.0%) |
< 0.001 |
high school |
760 (16.9%) |
442 (13.8%) |
644 (11.8%) |
590 (9.7%) |
||
above high school |
2946 (65.4%) |
2404 (74.9%) |
4491 (82.0%) |
5268 (86.3%) |
||
marriage |
married or living with partner |
2509 (55.7%) |
2038 (63.5%) |
3434 (62.7%) |
3433 (56.3%) |
< 0.001 |
others |
1996 (44.3%) |
1172 (36.5%) |
2041 (37.3%) |
2670 (43.7%) |
||
income |
<$20,000 |
1503 (33.4%) |
765 (23.8%) |
1043 (19.1%) |
1052 (17.2%) |
< 0.001 |
≥$20,000 |
2665 (59.2%) |
2270 (70.7%) |
4133 (75.5%) |
4766 (78.1%) |
||
missing |
337 (7.5%) |
175 (5.5%) |
299 (5.5%) |
285 (4.7%) |
||
ate less to lose weight |
yes |
1057 (23.5%) |
879 (27.4%) |
1662 (30.4%) |
1825 (29.9%) |
< 0.001 |
missing |
3448 (76.5%) |
2331 (72.6%) |
3813 (69.6%) |
4278 (70.1%) |
||
exercised to lose weight |
yes |
949 (21.1%) |
887 (27.6%) |
1667 (30.4%) |
1959 (32.1%) |
< 0.001 |
missing |
3556 (78.9%) |
2323 (72.4%) |
3808 (69.6%) |
4144 (67.9%) |
||
drank a lot of water to lose weight |
yes |
695 (15.4%) |
656 (20.4%) |
1270 (23.2%) |
1429 (23.4%) |
< 0.001 |
missing |
3810 (84.6%) |
2554 (79.6%) |
4205 (76.8%) |
4674 (76.6%) |
In Table 2, there was no relationship between having meals not home prepared and stomach or intestinal illness in the univariate analysis. we used the OR (95%CI) value to describe the association between the two variables. We found there were relationship between gender, race, education level, marital status, income, BMI, ate less to lose weight and drank a lot of water.
Characteristic |
Statistics |
Univariable analysis |
||
---|---|---|---|---|
Odds ratio(95% CI) |
p-value |
|||
gender |
male |
9463 (49.0489%) |
Ref(1) |
|
female |
9830 (50.9511%) |
0.7117 (0.6365, 0.7959) |
< 0.000001 |
|
cycle |
2011–2012 |
4595 (23.8169%) |
Ref(1) |
|
2013–2014 |
5009 (25.9628%) |
0.8755 (0.7467, 1.0264) |
0.101209 |
|
2015–2016 |
4882 (25.3045%) |
0.9342 (0.7944, 1.0985) |
0.41019 |
|
2017–2018 |
4807 (24.9158%) |
0.8227 (0.7020, 0.9641) |
0.015892 |
|
age |
21–40 |
6414 (33.2452%) |
Ref(1) |
|
41–60 |
6500 (33.6910%) |
1.0359 (0.9064, 1.1838) |
0.605018 |
|
> 60 |
6379 (33.0638%) |
1.0806 (0.9438, 1.2373) |
0.261587 |
|
race |
Mexican American |
2602 (13.4868%) |
Ref(1) |
|
Other Hispanic |
1988 (10.3043%) |
0.9052 (0.7226, 1.1339) |
0.386278 |
|
Non-Hispanic White |
7342 (38.0553%) |
0.8964 (0.7528, 1.0674) |
0.219625 |
|
Non-Hispanic Black |
4368 (22.6403%) |
1.0350 (0.8535, 1.2552) |
0.726488 |
|
Non-Hispanic Asian |
2282 (11.8281%) |
1.3794 (1.0843, 1.7548) |
0.008809 |
|
Other Race - Including Multi-Racial |
711 (3.6853%) |
0.6986 (0.5214, 0.9358) |
0.016198 |
|
education |
below high school |
1741 (9.0240%) |
Ref(1) |
|
high school |
2430 (12.5952%) |
0.7739 (0.6092, 0.9832) |
0.035846 |
|
above high school |
15103 (78.2823%) |
0.9299 (0.7608, 1.1366) |
0.478082 |
|
missing |
19 (0.0985%) |
1.2494 (0.1653, 9.4433) |
0.829178 |
|
marital status |
married and living with partner |
11408 (59.1303%) |
Ref(1) |
|
others |
7873 (40.8075%) |
0.7709 (0.6902, 0.8610) |
0.000004 |
|
missing |
12 (0.0622%) |
0.7465 (0.0962, 5.7903) |
0.779702 |
|
income |
<$20,000 |
4363 (22.6144%) |
Ref(1) |
|
≥$20,000 |
13834 (71.7048%) |
1.4351 (1.2687, 1.6235) |
< 0.000001 |
|
missing |
1096 (5.6808%) |
1.6141 (1.2288, 2.1203) |
0.00058 |
|
BMI |
29.1178 ± 7.7649 |
0.9876 (0.9808, 0.9945) |
0.000426 |
|
ate less to lose weight |
yes |
5423 (28.1086%) |
Ref(1) |
|
missing |
13870 (71.8914%) |
1.1941 (1.0604, 1.3448) |
0.003423 |
|
exercised to lose weight |
yes |
5462 (28.3108%) |
Ref(1) |
|
missing |
13831 (71.6892%) |
1.0519 (0.9319, 1.1873) |
0.413106 |
|
drank a lot of water |
yes |
4050 (20.9921%) |
Ref(1) |
|
missing |
15243 (79.0079%) |
1.2469 (1.0966, 1.4179) |
0.000762 |
In Table 3, multivariable logistic regression was applied to analyze the connection between the exposure variable and the outcome variable, which was described by Model 1 (no covariates adjusted), Model 2 (adjusted covariates: age, sex, race) and Model 3 (all covariates adjusted). We divided the participants into four groups based on the frequency of having meals that were not prepared at home, which were Q1(0 or 1 time/ week), Q2(2 times/ week), Q3(3 or 4 times/ week), Q4(≥ 5 times/ week). The P value between the two variables is 0.23 in Model 3, which showed that stomach or intestinal illness was not closely associated with the frequency of having not-home-prepared meals. (odds ratio [OR] 1.0007, 95% confidence interval [CI] (0.9984,1.0031); Table 2). Also, there were no relationship between gender, race, education level, marital status, income, BMI, ate less to lose weight and drank a lot of water.
Model 1, OR(95%Cl) |
Model 2, OR(95%Cl) |
Model 3, OR(95%Cl) |
|
---|---|---|---|
Of meals not home prepared |
|||
0 or 1 time/ week |
Reference (1) |
Reference (1) |
Reference (1) |
2 times/ week |
0.96(0.80,1.15) |
0.99(0.83,1.19) |
0.96(0.80,1.15) |
3 or 4 times/ week |
0.95(0.81,1.11) |
0.98(0.84,1.14) |
0.94(0.80,1.10) |
≥ 5 times/ week |
0.95(0.82,1.10) |
0.95(0.81,1.11) |
0.92(0.77,1.07) |
p for trend |
0.49 |
0.48 |
0.23 |
In Table 4 we stratified the participants based on several factors including gender, age, race, family income, education level, marital status, BMI and ways to lose weight. In conclusion, the youngers were more likely to have gastric diseases if they frequently had meals away from home. People with lower education level, such as below high school, were more likely to have gastric diseases if frequently eating out. When stratified by races, we found that the Blacks and the other Hispanics were more likely to suffer gastric illness while Asians were less likely compared to other races. We could also find that the risk of having gastric diseases almost had nothing to do with ages and marital status.
Model 1, OR(95%Cl) |
Model 2, OR(95%Cl) |
Model 3, OR(95%Cl) |
||
---|---|---|---|---|
gender |
male |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
female |
1.00(0.98,1.03) |
1.01(0.98,1.03) |
1.00(0.98,1.03) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
age |
21–40 |
1.00(1.00,1.00) |
1.01(0.98,1.03) |
1.01(0.97,1.04) |
41–60 |
1.00(1.00,1.00) |
1.00(0.98,1.03) |
1.00(0.97,1.04) |
|
> 60 |
1.00(1.00,1.00) |
1.00(1.00,1.01) |
1.00(1.00,1.04) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
race |
Mexican American |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
Other Hispanic |
1.02(1.00,1.07) |
1.01(0.96,1.06) |
1.02(0.97,1.07) |
|
Non-Hispanic White |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
Non-Hispanic Black |
1.03(1.00,1.06) |
1.03(0.99,1.06) |
1.02(0.98,1.06) |
|
Non-Hispanic Asian |
0.98(0.93,1.02) |
0.96(0.92,1.01) |
0.96(0.91,1.01) |
|
Other Race - Including Multi-Racial |
1.01(0.95,1.07) |
1.00(0.96,1.05) |
1.00(0.98,1.02) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
education |
below high school |
0.99(0.93,1.06) |
0.96(0.90,1.03) |
0.96(0.90,1.03) |
high school |
1.00(1.00,1.01) |
1.00(1.00,1.01) |
1.00(1.00,1.01) |
|
above high school |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
missing |
6040772.75(0.00, Inf) |
0.33(0.00, Inf) |
0.02 (0.00, Inf) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
marital status |
married and living with partner |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
others |
1.01(1.00,1.03) |
1.00(1.00,1.02) |
1.00(1.00,1.01) |
|
missing |
1.09(0.44,2.65) |
0.00(0.00, Inf) |
0.00(0.00, Inf) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
income |
<$20,000 |
1.00(1.00,1.01) |
1.00(1.00,1.00) |
1.00(1.00,1.01) |
≥$20,000 |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
missing |
1.00(0.94,1.07) |
1.02(0.95,1.10) |
1.03(0.96,1.11) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
BMI |
20.7223 ± 4.9527 |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
26.1963 ± 1.0921 |
1.00(1.00,1.01) |
1.00(1.00,1.01) |
1.00(1.00,1.01) |
|
30.3024 ± 1.3955 |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
39.0306 ± 6.0475 |
1.02(1.00,1.04) |
1.01(1.00,1.04) |
1.01(0.98,1.04) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
ate less to lose weight |
yes |
1.00(0.98,1.03) |
1.00(0.98,1.03) |
1.00(0.98,1.03) |
missing |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
drank a lot of water |
yes |
1.01(1.00,1.05) |
1.01(0.98,1.04) |
1.01(0.98,1.05) |
missing |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
|
total |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
1.00(1.00,1.00) |
Using data from NHANES database, we examined the frequency of dining out, the risk of having gastrointestinal illnesses among different groups of people and the association between them. Although the results showed no significant association between the two things, we made some analysis on it and drew some conclusions.
As the world economy growing rapidly, food industry also develops faster and thus people’s alternatives to dining increase [16]. People today not only have meals at restaurants or food stands, but also order food online, which gives them more alternatives when considering something to eat or drink. Since it brings too much convenience for those who are unwilling or unable to prepare meals by themselves, people would rather just stay at home and have their food delivered to their hands easily [17].
Using Fig. 2, we tried to demonstrate the association between having meals not prepared at home and gastric diseases. People have food passed through their mouth and esophagus into the stomach. The mechanical activity of the gastrointestinal tract helps to store and digest food [18]. There are three explanations about the association. First, most fast food is rich in energy so people who frequently eat it will get too much fat intake, which does harm to their health. Second, when we prepare meals at home, we may pay more attention to the amount of salt added into the food. However, we cannot control the salt content when eating out in some restaurants or food stands. We learned from a former study that high salt intake could be associated with an increased risk of atrophic gastritis with intestinal metaplasia [19]. Third, a study showed that among people’s sodium dietary intake, sodium added to food outside the home accounted for about 70%. Too much sodium intake is associated with gastric cancer [20, 21]. In a word, since nutrient intake and absorption are necessary for the survival of living organisms and has evolved into the specific task of the gastrointestinal system, we should pay more attention to the nutrient contents when choosing places to eat and sources of food [22].
By adding other single factors, we found some differences among people with different genders, ages, races and family incomes. According to Table 1, we can conclude that males showed more tendency on having meals out than females, which may due to males’ greater preference for fatty food and females’ paying more attention to their weight and figure [23, 24, 25]. When taking ages into consideration, it is obvious that younger persons show greater preference for food that are not home prepared than the older ones [26, 27]. That is mainly because young people’ s lifestyle has changed a lot due to the rapid development of society [28]. When taking races into consideration, Non-Hispanic Black and White show more preference for eating out. In single factor analysis, we can also learn that the Non-Hispanic Black are more likely to have stomach or intestinal illness than other races. This may be related to different eating habits of people from different areas around the world. For example, in some areas the prices of beef are lower than that of vegetables. For this reason, people with lower income tend to have beef rather than vegetables that can prevent people from stomach cancer [29]. Additionally, people who prefer eating beef that is not fully cooked may be more likely to develop gastric diseases. A former study told us that Salmonella may be transmitted from cattle to human through raw or undercooked beef [30]. Finally, we can conclude that people with more family income tend to eat out compared with the lower ones, which is defined by the amount of $20,000. But people with higher income are less likely to have gastric diseases mainly because they pay more attention to food quality and nutrient balance. It reflects that people’ s dining-out behaviors can be influenced by economic level [31].
Different individuals do not have the same definition of stomach or intestinal illness, which we mention here includes some small symptoms of diarrhea and vomiting. This may be the reason why our research did not come out as a positive outcome. People sometimes neglect the symptom of a chronic illness and do not take it seriously, which may limit the number of people who suffer from such kind of disease during the survey. However, a previous study based on Chinese population found that stomach and gastric distension were related to the eating behaviors of eating out in restaurants [32]. This result was the hypothesis we raised, but found totally not the same situation in the USA. This might be the difference of food safety and the huge gap of cooking habits between the east and the west. Another study showed that carbohydrate digestibility could influence people’ gastric health [33]. Dietary carbohydrate is one of the most important sources of nutrition, whose digestion and absorption rely on a complex process. It begins with starch hydrolysis by pancreatic amylase in small intestinal lumen. Further digestion occurs on the surface of the intestinal cell [34]. Thus, having food with poor digestibility when dining out can affect people’ s stomach and intestinal health, even cause gastric diseases. Furthermore, a previous study showed that there was association between poverty and gastric cancer, so we can predict that people with lower income tend to have higher risk of developing gastric diseases [35].
Some previous studies focused on the impact of dining out on body weight, BMI, metabolic syndrome [36] and cumulative phthalates inside human body [37] and obtained positive outcomes. Eating too much food that is not prepared at home is harmful to human body to some extent. The studies showed us that unbalanced nutrients, too much fat or salt intake and irregular dining times are the mainly problems people must be concerned about when choosing something to eat. Also, it is said that food away from home tends to higher in energy density but lower in fruits and vegetables [38, 39, 40, 41]. Additionally, the problem we study today is related to food safety. As delivery food becomes more and more popular especially among young people, it is hard not to worry about the food quality. Since it is difficult for food consumers to tell whether the food is safe and healthy to eat, people may gradually develop some chronic diseases if frequently eating out and harmful substances accumulating in their bodies. Most studies highlighted the dietary factors of patients suffering from gastric cancer [42, 43]. Since our research shows that there is no significant association between dining out and gastric illness, we can assume that people today are more concerned about food safety and trying to develop a new lifestyle with healthy eating behaviors. Besides, more restaurants in America are attempting to provide a balanced diet and high-quality food for consumers. In this case, people gain enough energy from food and keep healthy at the same time, no matter they have meals that are prepared at home or not.
There are some advantages of our research. First, we get to learn the prevalence of having meals out and the risk of having gastric illness among American adults. It can be a good reference for those who want to observe the eating behaviors among adults in America. Second, it can raise people’s awareness of food safety and nutrition intake in daily life. It is said that frequency of eating out may be related to high BMI, insulin resistance, triglycerides and low HDL-cholesterol concentrations [44]. It may be difficult for someone to have meals prepared at home all the time, but no matter how the food is prepared, the most essential point is to guarantee the food quality and keep nutrition balanced. There are also some limitations of our research. For instance, the data we collected measuring the frequency of having meals out are limited to just one week. Whereas, having stomach or intestinal illness is a long cumulative process. Thus, there may be a mismatch between the exposure variable and the outcome variable. Another drawback is that we did not give a clear definition of the stomach or intestinal illness, which vary from chronic to acute. This may limit our data showing the number of persons who suffer from such kind of disease.
In parallel with the rapid development of society and technology, we should always broaden our scope of knowledge and try to accept new concepts in daily life. As restaurant industry growing faster, we should pay more attention to our eating behaviors and healthy lifestyles. The government and educational institute also have the responsibility to advocate and educate some knowledge about healthy diet and life to people, especially to younger children [45]. And future research should be done on exploring the best way or frequency to eating out, considering people with different genders, ages, health conditions and so on.
In conclusion, our study finds no significant association between frequency of eating out and having gastric diseases. It shows us that most of the restaurants in America are concerned about the food quality. What’s more, people today pay more attention to nutrients intake and food security. Still, there should be more researches focusing on food quality and nutrient intake to be done to raise people’s awareness of food safety and advocate people to build a healthy eating diet.
Author Contributions: Conceptualization, L.W., L.M., X.Z., X.W. and J.H.; methodology, L.W., L.M., X.Z., X.W. and J.H.; software, L.W., L.M., X.Z., X.W. and J.H.; validation, L.W., L.M., X.Z., X.W. and J.H.; formal analysis, L.W., L.M., X.Z., X.W. and J.H.; investigation, L.W., L.M., X.Z., X.W. and J.H.; resources, L.W., L.M., X.Z., X.W. and J.H.; data curation, L.W., L.M., X.Z., X.W. and J.H.; writing—original draft preparation, L.W., L.M., X.Z., X.W. and J.H.; writing—review and editing, L.W., L.M., X.Z., X.W. and J.H.; visualization, L.W., L.M., X.Z., X.W. and J.H.; supervision, L.W., L.M., X.Z., X.W. and J.H.; project administration, L.W., L.M., X.Z., X.W. and J.H.; funding acquisition, L.W., L.M., X.Z., X.W. and J.H. All authors have read and agreed to the published version of the manuscript.
Funding: The Education Reform Foundation of Central South University (No. 2021JY188) and The Education Reform Foundation of Hunan Province (HNJG-2021-0322), National Natural Science Foundation of China (No. 81802208), Natural Science Foundation of Hunan Province (No. 2021JJ40922), and Foundation of Health Commission of Hunan Province (No. 202204074821) fund this study.
Institutional Review Board Statement:
Ethical approval: National Center For Health Statistics (NCHS) Research Ethics Review Board (ERB) provided approval of the survey protocol.
Informed Consent Statement: All participants of National Health and Nutrition Examination Survey (NHANES) provided informed consent.
Data Availability Statement: Data supporting reported results can be found in NHANES.
Acknowledgments: None.
Conflicts of Interest: The authors declare no conflict of interest.