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Association between 29 food groups of diet quality questionnaire and perceived stress in Chinese adults: a prospective study from China health and nutrition survey

Abstract

Purpose

Diet plays a fundamental role in promoting resilience against stress-related disorders. We aimed to examine the overall and sex-specific association between food groups and perceived stress in adults.

Methods

We analyzed the prospective data of 7,434 adults who completed both the 2011 and 2015 surveys of the China Health and Nutrition Survey (CHNS). The Diet Quality Questionnaire (DQQ) was used to code all the food items of 2011 dietary intake into 29 food groups, and perceived stress in 2015 was measured using a 14-item perceived stress scale (PSS-14). Univariate analysis and logistic regression models were used to examine the relationship between food groups and perceived stress.

Results

People who perceived a higher level of stress (PSS-14 total score > 25) made up 41.5% and 45.1% of the male and female groups, respectively (χ2 = 9.605, p = 0.002). Individuals with increased intake of food groups such as legumes, other vegetables, other fruits, yogurt, poultry, fish & seafood, fluid milk, and fruit juice were less likely to experience a higher level of psychological stress (OR range: 0.544–0.892, p < 0.05). Additionally, we found sex-specific associations between food groups and perceived stress. The difference in the proportion of food groups, such as fluid milk and fish & seafood, between the two stress groups in men was statistically significant (p < 0.025). In the female group, the distribution of eight food groups, like legumes and nuts & seeds, between the two stress groups was statistically significant (p < 0.025).

Conclusion

This study indicated that food groups were differentially associated with perceived stress.

Peer Review reports

Introduction

Stress-related disorder is a global problem, and it is estimated that 322 million people live with depression worldwide [1]. Perceived stress, which takes into account the perceived controllability, manageability, and personal impact of situations, has a strong and consistent association with concurrent and subsequent depression and potentially other mental health problems [2]. A previous study by Leng et al. suggested that a higher level of stress can be considered harmful and has a certain degree of negative impact on a person’s health [3]. It impairs emotional, physical, cognitive, and social functioning [4] and puts people at increased risk of stress-related health problems, especially depression [5]. Bremner et al., reviewed the associations between diet, stress, and stress-related disorders. They found that diet can affect mood through direct effects, and stress could lead to stress-related mental disorders, such as depression and posttraumatic stress disorder (PTSD) [6]. In today’s society, we thrive on performance, competition, and perfection, which leads to an insidious increase in stress. Meanwhile, rapidly growing urbanization and the globalization of the food industry have prompted profound shifts away from traditional dietary patterns. Although stress-related disorders (e.g., depression) seems to be heterogeneous disorders with no established mechanism [7], emerging and compelling evidence suggests that diet has a fundamental role in promoting resilience against these disorders [8,9,10]. A study conducted in China indicated that dietary diversity was found to be inversely associated with psychological stress [11]. Another study conducted in China also indicated that the dietary affected the degree of stress significantly [12]. Wu et al. reported that following a traditional Chinese dietary pattern was associated with a lower risk of depressive symptoms [13].

In terms of the potential mechanism, the structure and function of the brain is dependent upon energy, amino acids, fats, vitamins, minerals, and trace elements provided by food. The immune system [14], inflammatory system [15], antioxidant defense system [16], gut microbiota [17] and neurotrophic factors [18], which moderate the risk for stress-related disorders, operate with the support of nutrient cofactors and phytochemicals. Furthermore, there are two main types of neurotransmitters that affect mood: serotonin, which mainly affects mood, and epinephrine, which affects motivation [19]. Some nutrients in food are the precursors of these neurotransmitters [20], when the body ingests these nutrients, through body processing, the corresponding neurotransmitters can be formed, a certain amount of nutrients can produce a certain amount of neurotransmitters, thereby affecting their concentration levels in the body, and ultimately affecting our mood [21]. For example, the study of Radavelli-Bagatini et al. indicated that fruit and vegetable intake is inversely associated with perceived stress across the adult lifespan [22]. So, although the reality is quite complicated, in theory the emotions or stress can be regulated by adjusting the recipe.

Different food groups may lead to different stress levels. Various studies have illustrated the association between different nutritional factors and psychological health [23], including single nutrients such as magnesium [24], vitamin C [25], B vitamins [26], and omega-3 fatty acids [27], as well as dietary patterns [28] such as ketogenic diet [29], MIND diet, DASH (Dietary Approaches to Stop Hypertension) [30] diet, and the Mediterranean diet [31, 32], and also food groups such as fruits and vegetables [33] and fish [34]. Furthermore, previous studies found that a diet enriched with curcumin promotes resilience against chronic social defeat stress [35]. The latest research reported that psychobiotic dietary intervention has a promising role in reducing perceived stress [36]. People with lower adherence to the Mediterranean diet demonstrated higher perceived stress [37]. These previous findings have shown that diet has a fundamental influence on the perceived stress. Even though relationship between diet and stress can be bidirectional, as a systematic review indicated that stress can lead to disruption to normal eating behaviors [38]. Diet hold promise as potential approaches to address stress-related disorders through future dietary guidelines. Furthermore, although research has shown that females are more vulnerable to the development of depression and other stress related mental disorder [39], studies examining sex-specific association between diet and perceived stress are very limited.

A potential source of variation in the diet-pressure association may be biological sex. For example, sex-based differences was found in the association between dietary fiber intake and the prevalence of very severe stress in men and women [40]. Sex differences were also reported in the relationship between dietary pattern adherence and cognitive function [41]. Lee and Allen found the sex differences in the effect of fruit consumption on depression [42]. A greater understanding of sex-based differences in the association between dietary intake and psychological status would be useful in optimizing existing nutritional interventions and facilitating the execution of new comprehensive interventions intended to enhance the nutritional status and health profile of populations [43].

The Diet Quality Questionnaire (DQQ) was developed by Anna W. Herforth with a global framework of 29 food groups, which aimed to make food groups comparable globally [44]. The DQQ for China with the same 29 food groups was previously developed and evaluated by our research group [45], and we have also previously shown that dietary diversity was inversely associated with stress [11]. However, limited studies have comprehensively investigated the relationship between food groups and perceived stress in a general population in China. Thus, the aim of the current study is to examine the overall and sex-specific associations between 29 food groups from the DQQ for China and perceived stress, using prospective data from the China Health and Nutrition Survey (CHNS). We hypothesized that different food groups lead to different stress levels and that this relationship varies by gender.

Materials and methods

Data resource and study participants

The CHNS was an ongoing open-cohort study jointly conducted by the Carolina Population Center at the University of North Carolina and the National Institute of Nutrition at the Chinese Center for Disease Control and Prevention. The project began in 1989 and comprised a total of 10 waves (in 1989, 1991, 1993, 1997, 2000, 2004, 2006, 2009, 2011, and 2015). It used a multistage random-cluster sampling process, including nine provinces (Liaoning, Heilongjiang, Jiangsu, Shandong, Henan, Guangxi, and Guizhou) and three municipalities (Beijing, Shanghai, and Chongqing) that differ in economic development, geography, health indicators, and public resources. CHNS was reviewed and approved by the corresponding institutional review committees (2015,017). Details about the study design are available elsewhere [46].

The present analysis selected Chinese adults who participated in the two rounds of surveys in 2011 and 2015 as longitudinal tracking subjects. In the 2015 wave, the 14-item perceived stress scale (PSS-14) was incorporated into the project for the first time [47]. A total of 15,725 people participated in the 2011 wave. Those excluded from analysis included 2,628 participants aged ≤ 17 in 2015, 4,360 participants lost to follow-up, and 1,303 participants with no/incomplete PSS-14 information. Ultimately, 7,434 participants with information comprised of basic demographic characteristics (i.e., age, sex, weight (kg), height (m), location, province, marital status, and urbanicity index), complete PSS-14 score, and diet information were included in this analysis. The determination process of participants was consistent with our previous article [11].

Study outcome and other definitions

The PSS-14 is a validated questionnaire developed by Cohen et al. [48], and its Chinese version has been validated [49]. It aims to measure the degree to which situations in one’s life are appraised as stressful, and the items are designed to measure the extent to which one’s life is perceived as unpredictable, uncontrollable, and overloading [48]. The questions were examined on a 5-point Likert-type scale, ranging from 0 = “never” to 4 = “very often”. Scores are obtained by reverse scoring the positively stated items (4, 5, 6, 7, 9, 10, and 13). The total score (range 0–56) was calculated by summing the scores of all 14 items. A higher PSS-14 score indicates a higher degree of perceived stress. There is a lack of studies proposing a standard cut-off score to diagnose or grade stress for PSS-14 (Wang et al. [50]. Previous studies have often used medians or quartiles to define cut-off score. In this study, the participants were characterized into two groups based on the median of PSS-14. High reliability was demonstrated in our sample (Cronbach α = 0.83).

Dietary assessment and food group collection

The dietary information in 2011 was collected by trained nutritionists. They interviewed the participants in their households using 24-hour dietary recall, which is a validated method [51]. Further information on the dietary interview has been described elsewhere [52]. The Diet Quality Questionnaire (DQQ) is a valid and low-burden tool to collect data about the most common food groups consumed by the general population, using sentinel foods (defined as the foods in each food group that were consumed by more than 95% of people) to capture food group level data and reflect healthy dietary patterns [53]. The Chinese version of the DQQ has been adapted and verified [45]. The DQQ can be used to code diet into 29 food groups and it has been adapted to represent foods in the Chinese context [45]. The 29 food groups are included as follows: (1) staple foods made from grains; (2) whole grains; (3) white root/tubers; (4) legumes; (5) vitamin -rich orange vegetables; (6) dark green leafy vegetables; (7) other vegetables; (8) vitamin A-rich fruits; (9) citrus; (10) other fruits; (11) grain-based sweets; (12) other sweets; (13) eggs; (14) cheese; (15) yogurt; (16) processed meats; (17) unprocessed red meat (ruminant); (18) unprocessed red meat (nonruminant); (19) poultry; (20) fish & seafood; (21) nuts & seeds; (22) packaged ultra-processed salty snacks; (23) instant noodles; (24) deep fried foods; (25) fluid milk; (26) sweetened tea/coffee/milk drinks; (27) fruit juice; (28) sugar-sweetened beverages (SSBs) (sodas); and (29) fast food. All foods were grouped into the 29 globally unified food groups with reference to the International Dietary Quality Framework [45, 54]. If the intake of each group of food is greater than 15 g/day, it is judged that the food intake of this group is yes, and vice versa is no.

Measurements and calculation of covariates

Sociodemographic factors were assessed such as age, sex, weight and height, marital status, and urbanization index. Body mass index (BMI, kg/m2) calculated with weight (kg)/[height (m)]2 was categorized into four groups: underweight (BMI < 18.5 kg/m2), normal (BMI ≥ 18.5 and < 24.0 kg/m2), overweight (BMI ≥ 24 kg/m2 and < 28 kg/m2), and obese (BMI ≥ 28.0 kg/m2).

Statistical analysis

Sociodemographic information is summarized as the mean (standard deviation) for continuous variables and number (percentages) for categorical variables. To determine significant differences between two perceived stress levels (PSS-14 ≤ 25 vs. PSS-14 > 25), χ2 tests and Wilcoxon rank tests were used for categorical variables and continuous variables, respectively.

First, univariate analysis was used to analyze the difference in food group consumption between the perceived stress levels. Statistical significance between the two stress groups was assessed using the χ2 test or Fisher. Bonferroni approach is taken in the subgroup analysis. Second, to further explore the association between food group consumption and perceived stress level, a logistic regression model and stepwise method were applied while controlling for basic characteristics, such as sex, age, and residence.

Stratified analyses were conducted by sex (female vs. male). Tests were 2-sided at the 0.05 significance level. All analyses were performed using SAS statistical software version 9.4 (SAS Institute Inc., Cary, NC, USA).

Results

Basic information

Of the 7,434 participants, 3,464 (46.6%) were males and 3970 (53.4%) were females. Most (51.1%) of the study participants were middle-aged people (aged 45–64 years). In addition, 23.7% were young adulthood (aged 19–44 years), and 25.1% were older adulthood (aged 65 years and older) [55]. The median of the PSS-14 total score was 25. People who perceived a higher level of stress (PSS-14 total score > median) made up 41.5% and 45.1% of the male and female groups, respectively (χ2 = 9.605, p = 0.002). Detailed information on the characteristics is shown in Table 1.

Table 1 Descriptive statistics of participants n (%) or median (IQR)

The distribution of dietary foods in male and female

The intake of food groups of male and female were presented in Table 2. Compared with male, female consumed higher proportions of vitamin A-rich fruits, citrus, other fruits (fruits not classified as citrus fruits or vitamin A-rich fruits), baked sweets, yogurt, nuts & seeds, and fluid milk (p < 0.05). Meanwhile, the level of unprocessed red meat (ruminant or nonruminant), poultry, sodas/sugar-sweetened beverages SSBs (sodas) consumption was higher in male (p < 0.05).

Table 2 Percentages of individuals (n (%)) in male and female who reported intake from food groups in 2011

The distribution of dietary foods in different stress groups

The percentage of individuals reporting consumption of the 29 food groups in the two stress groups are presented in Table 3. Compared with the higher-stress group, the lower-stress group had higher proportions of legumes, other vegetables (vegetables not classified as white roots/tubers, legumes, vitamin A-rich orange vegetables, or dark green leafy vegetables), other fruits, baked sweets, eggs, yogurt, unprocessed red meat (nonruminant), poultry, fish & seafood, nuts & seeds, fluid milk, and fruit juice (p < 0.05). Meanwhile, the level of Vitamin A-rich orange vegetables consumption was higher in the higher-stress group (p = 0.032) compared to the lower-stress group.

Table 3 Percentages of individuals (n (%)) in lower and higher stress groups who reported intake from food groups in 2011

The relationship between food groups and perceived stress level

Unconditional multivariate logistic regression demonstrated that increased intake of food groups such as legumes, other vegetables, other fruits, yogurt, poultry, fish & seafood, fluid milk, and fruit juice correlates with less perceived stress (OR range: 0.544–0.892). Detailed information is shown in Table 4.

Table 4 Associations of food groups in 2011 with perceived stress level in 2015

Stratified analysis by sex

In the stratified analyses for females and males (Fig. 1), there was a statistically significant difference in the proportion of other vegetables, other fruits, fish and seafood, fluid milk, and fruit juice between the two stress groups in men (p < 0.025). In the female group, the distribution of legumes, other fruits, baked sweets, yogurt, nuts and seeds and fluid milk between the two stress groups was statistically significant (p < 0.025).

Fig. 1
figure 1

Sex-specific food groups in the higher stress group and lower stress group. Note Food group 1: staple foods made from grains; 2: whole grains; 3: white root/tubers; 4: legumes; 5: vitamin A-rich orange vegetables; 6: dark green leafy vegetables; 7: other vegetables; 8: vitamin A-rich fruits; 9: citrus; 10: other fruits; 11: grain-based sweets; 12: other sweets; 13: eggs; 14: cheese; 15: yogurt; 16: processed meats; 17: unprocessed red meat (ruminant); 18: unprocessed red meat (nonruminant); 19: poultry; 20: fish & seafood; 21: nuts & seeds; 22: packaged ultra-processed salty snacks; 23: instant noodles; 24: deep fried foods; 25: fluid milk; 26: sweetened tea/coffee/milk drinks; 27: fruit juice; 28: sugar-sweetened beverages (SSBs) (sodas); 29: fast food

Discussion

In this national prospective study, we assessed relatively comprehensive food groups in adults using the DQQ and found significant associations between lower perceived stress and certain food groups, including legumes, other vegetables (vegetables not classified as white roots/tubers, legumes, vitamin A-rich orange vegetables, or dark green leafy vegetables), other fruits(fruits not classified as citrus fruits or vitamin A-rich fruits), yogurt, poultry, fish & seafood, fluid milk, and fruit juice. We also conducted stratified analysis by sex, which is a significant factor for perceived stress. In particular, vegetables, fruits, fish & seafood, and fruit juice were negatively associated with higher stress in men. Legumes, baked sweets, yogurt, and nuts & seeds were negatively associated with higher stress in women.

Increased intake of fresh fruits and vegetables may have psychological benefits [56]; for example, people with higher fruit and vegetable consumption in daily life are less depressed [57] and happier [58]. Moreover, Ghadeer S. Aljuraiban conducted a cross-sectional study in Saudi Arabia, which included 401 female college students aged 19–35 years. This study reported that healthy plant-based diets were associated with lower stress in young Saudi women [59]. The mechanisms were speculated to be that various antioxidants and anti-inflammatory components, such as fiber [60], polyphenols [61], magnesium [62], zinc, selenium, vitamin C, B vitamins [63], and carbohydrates in fruits and vegetables, were associated with increased dopaminergic synthesis and serotonin release [64]; this would lead promotion of positive emotion and incentive motivation [65]. Regarding dairy products, a wide range of dietary yogurts and milk currently contain probiotic bacteria [66], which have been suggested to favorably alter the gut microbiota and gut function [67] and improve psychological health [68]. Indeed, evidence suggests that dysfunction of the microbiome-gut-brain axis might be implicated in stress related disorders such as depression through regulation of tryptophan metabolism [57].

We found the consumption of poultry, rather than other types of meat, was negatively associated with higher perceived stress. A systematic review showed that those who avoided meat consumption had a significantly higher risk of depression [69]. A recent meta-analysis of observational studies also indicated that adherence to the vegetarian diet may increase the risk of depression [70]. However, some studies have suggested the opposite conclusion, meat consumption may be associated with a higher risk of depression and stress [71, 72]. A potential source of variation in the meat-stress association may be meat types [73]. “Red meat,” especially high fat meat, was proven to impact the response to stress and promote depressive- and anxiety-like behaviors [74], by suppressing hypothalamic protein kinase A (PKA) signaling [75]. Poultry, classified as “white meat,” contains moderate energy, highly digestible proteins of good nutritional quality, unsaturated lipids, B-group vitamins, and minerals (such as iron, zinc, and copper) [76]. An investigation in an Iranian population found that white meat intake was inversely associated with psychological distress symptoms [73]. A study conducted in Finland also showed that subjects with a lower risk for stress-related disorders consumed white meat more often [77].

Fish and seafood are universally known food groups that are good for physical and psychological health [78]. Numerous studies have revealed that fish, as the primary dietary sources of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), is associated with a reduced risk of depression [79, 80]. A meta-analysis involving 26 studies indicated that high fish consumption can reduce the risk of depression [81]. The postulated mechanisms of EPA and DHA’s anti-depressive effects were demonstrated, such as reducing the occurrence of inflammation, decreasing the production of arachidonic acid [82], and enhancing the production of neuroprotective metabolites [80]. A nationwide longitudinal study conducted in Japan indicated that women with higher fish and/or n-3 PUFA intake showed a reduced risk of postpartum depression [34]. The present study adds important information to the field in the Chinese population. Regarding interventional studies, a randomized, placebo-controlled trial in abstinent alcoholics demonstrated that fish oil supplementation reduces cortisol basal levels and perceived stress [83].

Our result was consistent with the current evidence that sex-specific associations were observed between food groups and perceived stress. For example, a prospective study found that the intake of yogurt is related to a lower risk of depression among women but not men [84]. Western dietary patterns and high levels of triglycerides have been found to be associated with cognitive impairment in men but not in women [41]. Western pattern is usually rich in calories, saturated/trans-unsaturated fatty acids, sugar, and alcohol, which are associated with cognitive decline [85]. Moreover, the potential mechanistic links between Western diet consumption and cognition is that the Western diet includes heat-processed foods that contain high levels of advanced glycation end products (AGEs). Elevated levels of AGEs were associated with increased aggregation and cytotoxicity of amyloid-β (Aβ) [86]. Animal studies demonstrated that increased levels of circulating plasma Aβ could cause blood-brain barrier degradation and hippocampal dysfunction, and these condition are associated with cognitive impairment [87]. Eating fruit was found to be associated with increased positive affect among men but not women [65]. In addition, special attention should be given to the fact that intake of vitamin A-rich orange vegetables was higher in higher stress group of women. This finding was in line with recent reviews, which reported that elevated retinoid levels form a significant risk factor for depressive symptoms [88]. These sex-specific associations can be explained by sex-specific differences in dietary intake [89]. Moreover, sex-based differences in biophysiological sensitivity, such as sex hormones and inflammation, to dietary intake may further explain the observed association between various food groups and psychological health [60]. In addition, their brain morphology and connectivity are different, and the dimorphic state of the brain may also influence nutritional needs, behavioral traits as well as susceptibility to pressure [90].

In summary, these results were consistent with previous findings; for example, a traditional whole-food diet, consisting of higher intake of foods such as vegetables, fruits, seafood, whole grains, poultry meat, nuts, and legumes, with avoidance of processed foods, was more likely to provide the nutrients that contribute to the prevention of this stress-related disorder [91]. Similarly, the Mediterranean diet, which is high in fruits, vegetables, wholegrains, legumes, seafood, nuts, seeds, and olive oil, was indicated to be of significant benefit for psychological health [31]. Better overall diet quality is proven to be associated with a lower risk for stress and stress-associated disorders [92]. On the other hand, intake of nutritional supplementation could also affect stress and psychological status. For example, the meta-analyses by Mikola [93] and Dominika [94]concluded that vitamin D supplementation ≥ 2,000 IU/day may effectively alleviate the symptoms of depression in children and adults. As neurosteroid and immunological actions of vitamin D may regulate depression-linked physiology. The meta-analyses by Lauren provided evidence for the benefit of B vitamin supplementation in healthy and at-risk populations for stress [95]. The results from a cross‑sectional analysis and a randomized controlled trial indicated that Vitamin C supplementation promotes mental vitality in healthy young adults, and Vitamin C may has modulating effects on neurotransmitters and hormones in the brain [96]. The post-hoc analysis of a randomized controlled trial found that magnesium and vitamin B6 supplementation could provide a meaningful clinical benefit in daily life for individuals with stress [97].

Strengths and limitations

In this study, we examined the relationship between 29 food groups measured using the China-adapted DQQ and perceived stress, prospectively. First, legumes, vegetables, fruits, yogurt, poultry, fish& seafood, fluid milk, and fruit juice were associated with lower perceived stress in general adults. This finding provides new information by contributing to the growing body of literature examining the association between food groups and perceived stress. Second, the current study conducted sex-based analyses in this area of research with the assumption that the benefits of a particular food group may unequally contribute to the perceived stress of men and women. The analysis supports the need for sex-based analyses to better understand the association between dietary intake and stress. Third, the CHNS data used in this study was obtained from a national representative sample, which provides a basis for monitoring the reliability of its findings.

There were, however, also some limitations. First, this study is essentially descriptive research, and its ability to make valid causal inferences was limited. Future replication and investigation are needed, such as animal studies and randomized controlled trials. Second, a four-year gap existed between dietary information and stress assessment. During this period, a person’s dietary habits can remain stable or vary with changing circumstances. Although our result can explain the order of occurrence of diet and PSS, the diet in weeks before PSS evaluation in 2015 was not analyzed, this would be a limitation. While our design was in line with previous studies [11, 98, 99]. For example, Zhang, J., & Zhao, A. explored the effects of dietary diversity score (DDS) on healthy aging using the data of CHNS. In their study, DDSs were calculated using the dietary data collected in the years 2009 and 2011, and the healthy aging score (HAS) was calculated based on the data collected in the year 2015 [99]. Moreover, previous studies indicated that eating habits of participant may not change significantly during 2011 and 2015. According to the study of Song et al., [100], the mean total energy intake of participants in CHNS was 2091.51(716.06) kcal/day and 2009.22 (717.43) kcal/day, respectively. Another Results from the CHNS also indicated that the percentage of energy from protein, fat, carbohydrate were 32.6%, 54.4%, and 12.7% in 2011, 35.6%, 51.6%, and 12.6% in 2015, respectively [101]. To some extent, these evidences suggested that the participants’ dietary habits and lifestyle choices were relatively stable. Third, dietary data and stress levels were assessed through self-report, which is subjective and may be subject to recall bias.

Conclusions

In conclusion, food groups measured using the DQQ for China were differentially associated with perceived stress in this prospective analysis of a national population. Higher intake of certain food groups such as other vegetables, other fruits, dairy products, seafood, poultry meat, and legumes was associated with lower perceived stress.

Data availability

The dataset in the present study was open-accessed and freely obtained from the CHNS website with registration at https://www.cpc.unc.edu/projects/china/data/datasets/ (accessed on 22 March 2021).

References

  1. Friedrich MJ. Depression is the leading cause of disability around the World. JAMA. 2017;317:1517. https://doi.org/10.1001/jama.2017.3826.

    Article  PubMed  Google Scholar 

  2. Schiavone S, Colaianna M, Curtis L. Impact of early life stress on the pathogenesis of mental disorders: relation to brain oxidative stress. Curr Pharm Des. 2015;21:1404–12. https://doi.org/10.2174/1381612821666150105143358.

    Article  CAS  PubMed  Google Scholar 

  3. Leng M, Wei L, Shi X, et al. Mental distress and influencing factors in nurses caring for patients with COVID-19. Nurs Crit Care. 2021;26:94–101. https://doi.org/10.1111/nicc.12528.

    Article  PubMed  Google Scholar 

  4. McCabe D, Bednarz J, Lockwood C, et al. Specific nutrient Intake Via Diet and/or supplementation in relation to female stress: a cross-sectional study. Womens Health Rep (New Rochelle). 2020;1:241–51. https://doi.org/10.1089/whr.2020.0035.

    Article  PubMed  Google Scholar 

  5. Steinmann A, Ruf A, Ahrens KF, et al. Bacon, Brownie, or Broccoli? Beliefs about stress-relieving Foods and their relationship to Orthorexia Nervosa. Nutrients. 2022;14. https://doi.org/10.3390/nu14183673.

  6. Bremner JD, Moazzami K, Wittbrodt MT, et al. Diet, stress and Mental Health. Nutrients. 2020;12. https://doi.org/10.3390/nu12082428.

  7. Belmaker RH, Agam G. Major depressive disorder. N Engl J Med. 2008;358:55–68. https://doi.org/10.1056/NEJMra073096.

    Article  CAS  PubMed  Google Scholar 

  8. Lages YV, Maisonnette SS, Rosseti FP, et al. High-sugar/high-fat diet modulates the effects of chronic stress in cariocas high- and low-conditioned freezing rats. Physiol Behav. 2022;248:113742. https://doi.org/10.1016/j.physbeh.2022.113742.

    Article  CAS  PubMed  Google Scholar 

  9. Parletta N, Zarnowiecki D, Cho J, et al. A Mediterranean-style dietary intervention supplemented with fish oil improves diet quality and mental health in people with depression: a randomized controlled trial (HELFIMED). Nutr Neurosci. 2019;22:474–87. https://doi.org/10.1080/1028415X.2017.1411320.

    Article  CAS  PubMed  Google Scholar 

  10. Wade AT, Davis CR, Dyer KA, et al. A Mediterranean diet supplemented with dairy foods improves mood and processing speed in an Australian sample: results from the MedDairy randomized controlled trial. Nutr Neurosci. 2020;23:646–58. https://doi.org/10.1080/1028415X.2018.1543148.

    Article  CAS  PubMed  Google Scholar 

  11. Zhou J, Wang H, Zou Z. Inverse Association between Dietary Diversity score calculated from the Diet Quality Questionnaire and psychological stress in Chinese adults: a prospective study from China Health and Nutrition Survey. Nutrients. 2022;14. https://doi.org/10.3390/nu14163297.

  12. Li X, Tian D, Qin P, et al. Dietary, physical exercises and mental stress in a Chinese population: a cross-sectional study. BMC Public Health. 2021;21:1138. https://doi.org/10.1186/s12889-021-11189-7.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Wu H, Gu Y, Meng G, et al. Relationship between dietary pattern and depressive symptoms: an international multicohort study. Int J Behav Nutr Phys Act. 2023;20:74. https://doi.org/10.1186/s12966-023-01461-x.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Marx W, Lane M, Hockey M, et al. Diet and depression: exploring the biological mechanisms of action. Mol Psychiatry. 2021;26:134–50. https://doi.org/10.1038/s41380-020-00925-x.

    Article  PubMed  Google Scholar 

  15. Bizzozero-Peroni B, Ortola R, Martinez-Vizcaino V, et al. Proinflammatory dietary pattern and depression risk in older adults: prospective analyses from the Seniors-ENRICA studies. Clin Nutr. 2022;41:2614–20. https://doi.org/10.1016/j.clnu.2022.10.007.

    Article  PubMed  Google Scholar 

  16. Logan AC, Jacka FN. Nutritional psychiatry research: an emerging discipline and its intersection with global urbanization, environmental challenges and the evolutionary mismatch. J Physiol Anthropol. 2014;33:22. https://doi.org/10.1186/1880-6805-33-22.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Bear TLK, Dalziel JE, Coad J, et al. The role of the gut microbiota in dietary interventions for depression and anxiety. Adv Nutr. 2020;11:890–907. https://doi.org/10.1093/advances/nmaa016.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Molendijk ML, Bus BA, Spinhoven P, et al. Serum levels of brain-derived neurotrophic factor in major depressive disorder: state-trait issues, clinical features and pharmacological treatment. Mol Psychiatry. 2011;16:1088–95. https://doi.org/10.1038/mp.2010.98.

    Article  CAS  PubMed  Google Scholar 

  19. Shelton RC. Serotonin and norepinephrine reuptake inhibitors. Handb Exp Pharmacol. 2019;250:145–80. https://doi.org/10.1007/164_2018_164.

    Article  CAS  PubMed  Google Scholar 

  20. Gasmi A, Nasreen A, Menzel A, et al. Neurotransmitters regulation and food intake: the role of Dietary sources in neurotransmission. Molecules. 2022;28. https://doi.org/10.3390/molecules28010210.

  21. Chen Y, Xu J, Chen Y. Regulation of neurotransmitters by the Gut Microbiota and effects on Cognition in Neurological disorders. Nutrients. 2021;13. https://doi.org/10.3390/nu13062099.

  22. Radavelli-Bagatini S, Blekkenhorst LC, Sim M, et al. Fruit and vegetable intake is inversely associated with perceived stress across the adult lifespan. Clin Nutr. 2021;40:2860–7. https://doi.org/10.1016/j.clnu.2021.03.043.

    Article  PubMed  Google Scholar 

  23. Xu Y, Zeng L, Zou K, et al. Role of dietary factors in the prevention and treatment for depression: an umbrella review of meta-analyses of prospective studies. Transl Psychiatry. 2021;11:478. https://doi.org/10.1038/s41398-021-01590-6.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Noah L, Morel V, Bertin C, et al. Effect of a combination of Magnesium, B vitamins, Rhodiola, and Green Tea (L-Theanine) on chronically stressed healthy Individuals-A Randomized, Placebo-controlled study. Nutrients. 2022;14. https://doi.org/10.3390/nu14091863.

  25. Fletcher BD, Flett JAM, Wickham SR, et al. Initial evidence of variation by ethnicity in the relationship between Vitamin C Status and Mental States in Young adults. Nutrients. 2021;13. https://doi.org/10.3390/nu13030792.

  26. Wu Y, Zhang L, Li S, et al. Associations of dietary vitamin B1, vitamin B2, vitamin B6, and vitamin B12 with the risk of depression: a systematic review and meta-analysis. Nutr Rev. 2022;80:351–66. https://doi.org/10.1093/nutrit/nuab014.

    Article  PubMed  Google Scholar 

  27. Yam KY, Schipper L, Reemst K, et al. Increasing availability of omega-3 fatty acid in the early-life diet prevents the early-life stress-induced cognitive impairments without affecting metabolic alterations. FASEB J. 2019;33:5729–40. https://doi.org/10.1096/fj.201802297R.

    Article  CAS  PubMed  Google Scholar 

  28. Gianfredi V, Dinu M, Nucci D, et al. Association between dietary patterns and depression: an umbrella review of meta-analyses of observational studies and intervention trials. Nutr Rev. 2022. https://doi.org/10.1093/nutrit/nuac058.

    Article  Google Scholar 

  29. Guan YF, Huang GB, Xu MD, et al. Anti-depression effects of ketogenic diet are mediated via the restoration of microglial activation and neuronal excitability in the lateral habenula. Brain Behav Immun. 2020;88:748–62. https://doi.org/10.1016/j.bbi.2020.05.032.

    Article  CAS  PubMed  Google Scholar 

  30. Cherian L, Wang Y, Holland T, et al. DASH and Mediterranean-dash intervention for neurodegenerative Delay (MIND) diets are Associated with fewer depressive symptoms over Time. J Gerontol Biol Sci Med Sci. 2021;76:151–6. https://doi.org/10.1093/gerona/glaa044.

    Article  Google Scholar 

  31. Bayes J, Schloss J, Sibbritt D. The effect of a Mediterranean diet on the symptoms of depression in young males (the AMMEND: a Mediterranean Diet in MEN with Depression study): a randomized controlled trial. Am J Clin Nutr. 2022;116:572–80. https://doi.org/10.1093/ajcn/nqac106.

    Article  CAS  PubMed  Google Scholar 

  32. Zupo R, Griseta C, Battista P, et al. Role of plant-based diet in late-life cognitive decline: results from the Salus in Apulia Study. Nutr Neurosci. 2022;25:1300–9. https://doi.org/10.1080/1028415X.2020.1853416.

    Article  CAS  PubMed  Google Scholar 

  33. Dharmayani PNA, Mishra GD, Mihrshahi S. Fruit and vegetable consumption and depression symptoms in young women: results from 1973 to 1978 cohort of the Australian longitudinal study on women’s Health. Eur J Nutr. 2022;61:4167–78. https://doi.org/10.1007/s00394-022-02926-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Hamazaki K, Matsumura K, Tsuchida A, et al. Dietary intake of fish and n-3 polyunsaturated fatty acids and risk of postpartum depression: a nationwide longitudinal study - the Japan Environment and Children’s study (JECS). Psychol Med. 2020;50:2416–24. https://doi.org/10.1017/S0033291719002587.

    Article  PubMed  Google Scholar 

  35. Aubry AV, Khandaker H, Ravenelle R, et al. A diet enriched with curcumin promotes resilience to chronic social defeat stress. Neuropsychopharmacology. 2019;44:733–42. https://doi.org/10.1038/s41386-018-0295-2.

    Article  CAS  PubMed  Google Scholar 

  36. Berding K, Bastiaanssen TFS, Moloney GM, et al. Feed your microbes to deal with stress: a psychobiotic diet impacts microbial stability and perceived stress in a healthy adult population. Mol Psychiatry. 2022. https://doi.org/10.1038/s41380-022-01817-y.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Raparelli V, Romiti GF, Spugnardi V, et al. Gender-related determinants of adherence to the Mediterranean Diet in adults with ischemic heart disease. Nutrients. 2020;12. https://doi.org/10.3390/nu12030759.

  38. Hill D, Conner M, Clancy F, et al. Stress and eating behaviours in healthy adults: a systematic review and meta-analysis. Health Psychol Rev. 2022;16:280–304. https://doi.org/10.1080/17437199.2021.1923406.

    Article  PubMed  Google Scholar 

  39. Bangasser DA, Cuarenta A. Sex differences in anxiety and depression: circuits and mechanisms. Nat Rev Neurosci. 2021;22:674–84. https://doi.org/10.1038/s41583-021-00513-0.

    Article  CAS  PubMed  Google Scholar 

  40. Alharbi MH, Alarifi SN. Gender-based differences in the Consumption of Food Rich in Fibre and its relationship with Perceived Mood Status: a cross-sectional study. Healthc (Basel). 2022;10. https://doi.org/10.3390/healthcare10040730.

  41. D’Amico D, Parrott MD, Greenwood CE, et al. Sex differences in the relationship between dietary pattern adherence and cognitive function among older adults: findings from the NuAge study. Nutr J. 2020;19:58. https://doi.org/10.1186/s12937-020-00575-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Lee J, Allen J. Gender Differences in Healthy and Unhealthy Food Consumption and its relationship with Depression in Young Adulthood. Community Ment Health J. 2021;57:898–909. https://doi.org/10.1007/s10597-020-00672-x.

    Article  PubMed  Google Scholar 

  43. Bennett E, Peters SAE, Woodward M. Sex differences in macronutrient intake and adherence to dietary recommendations: findings from the UK Biobank. BMJ Open. 2018;8:e020017. https://doi.org/10.1136/bmjopen-2017-020017.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Herforth A, Martínez-Steele E, Calixto G, et al. Development of a Diet Quality Questionnaire for Improved Measurement of Dietary Diversity and other Diet Quality indicators (P13-018-19). Curr Developments Nutr. 2019a;3. https://doi.org/10.1093/cdn/nzz036.P13-018-19.

  45. Ma S, Herforth AW, Vogliano C, et al. Most commonly-consumed food items by Food Group, and by Province, in China: implications for Diet Quality Monitoring. Nutrients. 2022;14. https://doi.org/10.3390/nu14091754.

  46. Zhang B, Zhai FY, Du SF, et al. The China Health and Nutrition Survey, 1989–2011. Obes Rev. 2014;15(Suppl 1):2–7. https://doi.org/10.1111/obr.12119.

    Article  PubMed  Google Scholar 

  47. Cao B, Zhao Y, Ren Z, et al. Are physical activities Associated with perceived stress? The evidence from the China Health and Nutrition Survey. Front Public Health. 2021;9:697484. https://doi.org/10.3389/fpubh.2021.697484.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24:385–96.

    Article  CAS  PubMed  Google Scholar 

  49. Huang F, Wang H, Wang Z, et al. Psychometric properties of the perceived stress scale in a community sample of Chinese. BMC Psychiatry. 2020;20:130. https://doi.org/10.1186/s12888-020-02520-4.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Wang H, Huang D, Huang H, et al. The psychological impact of COVID-19 pandemic on medical staff in Guangdong, China: a cross-sectional study. Psychol Med. 2022;52:884–92. https://doi.org/10.1017/S0033291720002561.

    Article  PubMed  Google Scholar 

  51. Zhai F, Guo X, Popkin BM, et al. Evaluation of the 24-Hour Individual Recall Method in China. FoodNutr Bull. 1996;17:1–7. https://doi.org/10.1177/156482659601700209.

    Article  Google Scholar 

  52. Zhai FY, Du SF, Wang ZH, et al. Dynamics of the Chinese diet and the role of urbanicity, 1991–2011. Obes Rev. 2014;15(Suppl 1):16–26. https://doi.org/10.1111/obr.12124.

    Article  PubMed  Google Scholar 

  53. Herforth A, Martinez Steele E, Calixto G, et al. Development of a Diet Quality Questionnaire for Improved Measurement of Dietary Diversity and other Diet Quality indicators (P13-018-19). Curr Developments Nutr. 2019b;3. https://doi.org/10.1093/cdn/nzz036.P13-018-19.

  54. Uyar BTM, Talsma EF, Herforth AW, et al. The DQQ is a Valid Tool to Collect Population-Level Food Group Consumption Data: a study among women in Ethiopia, Vietnam, and Solomon Islands. J Nutr. 2023;153:340–51. https://doi.org/10.1016/j.tjnut.2022.12.014.

    Article  PubMed  Google Scholar 

  55. Maung HH. What’s my age again? Age categories as interactive kinds. Hist Philos Life Sci. 2021;43:36. https://doi.org/10.1007/s40656-021-00388-5.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Fann LY, Huang SH, Huang YC, et al. The Synergetic Impact of Physical Activity and Fruit and Vegetable Consumption on the risk of depression in Taiwanese adults. Int J Environ Res Public Health. 2022;19. https://doi.org/10.3390/ijerph19127300.

  57. Szabo de Edelenyi F, Philippe C, Druesne-Pecollo N, et al. Depressive symptoms, fruit and vegetables consumption and urinary 3-indoxylsulfate concentration: a nested case-control study in the French Nutrinet-Sante cohort. Eur J Nutr. 2021;60:1059–69. https://doi.org/10.1007/s00394-020-02306-0.

    Article  CAS  PubMed  Google Scholar 

  58. Rooney C, McKinley MC, Woodside JV. The potential role of fruit and vegetables in aspects of psychological well-being: a review of the literature and future directions. Proc Nutr Soc. 2013;72:420–32. https://doi.org/10.1017/s0029665113003388.

    Article  PubMed  Google Scholar 

  59. Aljuraiban GS. Plant-based dietary indices and stress in female college students: a cross-sectional study. Br J Nutr. 2022;127:123–32. https://doi.org/10.1017/S0007114521001689.

    Article  CAS  PubMed  Google Scholar 

  60. Swann OG, Kilpatrick M, Breslin M, et al. Dietary fiber and its associations with depression and inflammation. Nutr Rev. 2020;78:394–411. https://doi.org/10.1093/nutrit/nuz072.

    Article  PubMed  Google Scholar 

  61. Bayes J, Schloss J, Sibbritt D. Effects of polyphenols in a Mediterranean Diet on symptoms of Depression: a systematic literature review. Adv Nutr. 2020;11:602–15. https://doi.org/10.1093/advances/nmz117.

    Article  PubMed  Google Scholar 

  62. Li B, Lv J, Wang W, et al. Dietary magnesium and calcium intake and risk of depression in the general population: a meta-analysis. Aust N Z J Psychiatry. 2017;51:219–29. https://doi.org/10.1177/0004867416676895.

    Article  PubMed  Google Scholar 

  63. Wang A, Luo J, Zhang T, et al. Dietary vitamin C and vitamin C derived from vegetables are inversely Associated with the risk of depressive symptoms among the General Population. Antioxid (Basel). 2021;10. https://doi.org/10.3390/antiox10121984.

  64. Cheng HY, Shi YX, Yu FN, et al. Association between vegetables and fruits consumption and depressive symptoms in a middle-aged Chinese population: an observational study. Med (Baltim). 2019;98:e15374. https://doi.org/10.1097/MD.0000000000015374.

    Article  Google Scholar 

  65. Conner TS, Brookie KL, Richardson AC, et al. On carrots and curiosity: eating fruit and vegetables is associated with greater flourishing in daily life. Br J Health Psychol. 2015;20:413–27. https://doi.org/10.1111/bjhp.12113.

    Article  PubMed  Google Scholar 

  66. Pei R, Martin DA, DiMarco DM, et al. Evidence for the effects of yogurt on gut health and obesity. Crit Rev Food Sci Nutr. 2017;57:1569–83. https://doi.org/10.1080/10408398.2014.883356.

    Article  PubMed  Google Scholar 

  67. Daniel N, Nachbar RT, Tran TTT, et al. Gut microbiota and fermentation-derived branched chain hydroxy acids mediate health benefits of yogurt consumption in obese mice. Nat Commun. 2022;13:1343. https://doi.org/10.1038/s41467-022-29005-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Huang R, Wang K, Hu J. Effect of Probiotics on Depression: a systematic review and Meta-analysis of Randomized controlled trials. Nutrients. 2016;8. https://doi.org/10.3390/nu8080483.

  69. Dobersek U, Teel K, Altmeyer S, et al. Meat and mental health: a meta-analysis of meat consumption, depression, and anxiety. Crit Rev Food Sci Nutr. 2021;1–18. https://doi.org/10.1080/10408398.2021.1974336.

  70. Fazelian S, Sadeghi E, Firouzi S, et al. Adherence to the vegetarian diet may increase the risk of depression: a systematic review and meta-analysis of observational studies. Nutr Rev. 2022;80:242–54. https://doi.org/10.1093/nutrit/nuab013.

    Article  PubMed  Google Scholar 

  71. Lampignano L, Sardone R, D’Urso F, et al. Processed meat consumption and the risk of incident late-onset depression: a 12-year follow-up of the Salus in Apulia Study. Age Ageing. 2022;51. https://doi.org/10.1093/ageing/afab257.

  72. Zhang Y, Yang Y, Xie MS, et al. Is meat consumption associated with depression? A meta-analysis of observational studies. BMC Psychiatry. 2017;17:409. https://doi.org/10.1186/s12888-017-1540-7.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Kazemi S, Keshteli AH, Saneei P, et al. Red and White Meat Intake in Relation to Mental disorders in Iranian adults. Front Nutr. 2021;8:710555. https://doi.org/10.3389/fnut.2021.710555.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Aslani S, Vieira N, Marques F, et al. The effect of high-fat diet on rat’s mood, feeding behavior and response to stress. Transl Psychiatry. 2015;5:e684. https://doi.org/10.1038/tp.2015.178.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Vagena E, Ryu JK, Baeza-Raja B, et al. A high-fat diet promotes depression-like behavior in mice by suppressing hypothalamic PKA signaling. Transl Psychiatry. 2019;9:141. https://doi.org/10.1038/s41398-019-0470-1.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Marangoni F, Corsello G, Cricelli C, et al. Role of poultry meat in a balanced diet aimed at maintaining health and wellbeing: an Italian consensus document. Food Nutr Res. 2015;59:27606. https://doi.org/10.3402/fnr.v59.27606.

    Article  PubMed  Google Scholar 

  77. Penttinen MA, Virtanen J, Laaksonen M, et al. The Association between Healthy Diet and Burnout symptoms among Finnish municipal employees. Nutrients. 2021;13. https://doi.org/10.3390/nu13072393.

  78. Chataigner M, Mortessagne P, Lucas C, et al. Dietary fish hydrolysate supplementation containing n-3 LC-PUFAs and peptides prevents short-term memory and stress response deficits in aged mice. Brain Behav Immun. 2021;91:716–30. https://doi.org/10.1016/j.bbi.2020.09.022.

    Article  CAS  PubMed  Google Scholar 

  79. Appleton KM, Voyias PD, Sallis HM, et al. Omega-3 fatty acids for depression in adults. Cochrane Database Syst Rev. 2021;11:CD004692. https://doi.org/10.1002/14651858.CD004692.pub5.

    Article  PubMed  Google Scholar 

  80. Peng Y, Shi Z, Kumaran Satyanarayanan S, et al. Fish oil alleviates LPS-induced inflammation and depressive-like behavior in mice via restoration of metabolic impairments. Brain Behav Immun. 2020;90:393–402. https://doi.org/10.1016/j.bbi.2020.09.005.

    Article  CAS  PubMed  Google Scholar 

  81. Li F, Liu X, Zhang D. Fish consumption and risk of depression: a meta-analysis. J Epidemiol Community Health. 2016;70:299–304. https://doi.org/10.1136/jech-2015-206278.

    Article  PubMed  Google Scholar 

  82. Liao Y, Xie B, Zhang H, et al. Efficacy of omega-3 PUFAs in depression: a meta-analysis. Transl Psychiatry. 2019;9:190. https://doi.org/10.1038/s41398-019-0515-5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Barbadoro P, Annino I, Ponzio E, et al. Fish oil supplementation reduces cortisol basal levels and perceived stress: a randomized, placebo-controlled trial in abstinent alcoholics. Mol Nutr Food Res. 2013;57:1110–4. https://doi.org/10.1002/mnfr.201200676.

    Article  CAS  PubMed  Google Scholar 

  84. Perez-Cornago A, Sanchez-Villegas A, Bes-Rastrollo M, et al. Intake of High-Fat Yogurt, but not of Low-Fat Yogurt or Prebiotics, is related to Lower Risk of Depression in Women of the SUN Cohort Study. J Nutr. 2016;146:1731–9. https://doi.org/10.3945/jn.116.233858.

    Article  CAS  PubMed  Google Scholar 

  85. Shakersain B, Santoni G, Larsson SC, et al. Prudent diet may attenuate the adverse effects of Western diet on cognitive decline. Alzheimers Dement. 2016;12:100–9. https://doi.org/10.1016/j.jalz.2015.08.002.

    Article  PubMed  Google Scholar 

  86. West RK, Moshier E, Lubitz I, et al. Dietary advanced glycation end products are associated with decline in memory in young elderly. Mech Ageing Dev. 2014;140:10–2. https://doi.org/10.1016/j.mad.2014.07.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Hsu TM, Kanoski SE. Blood-brain barrier disruption: mechanistic links between Western diet consumption and dementia. Front Aging Neurosci. 2014;6:88. https://doi.org/10.3389/fnagi.2014.00088.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Hu P, van Dam AM, Wang Y, et al. Retinoic acid and depressive disorders: evidence and possible neurobiological mechanisms. Neurosci Biobehav Rev. 2020;112:376–91. https://doi.org/10.1016/j.neubiorev.2020.02.013.

    Article  CAS  PubMed  Google Scholar 

  89. Dan H, Kim J, Kim O. Effects of gender and age on Dietary Intake and Body Mass Index in Hypertensive patients: analysis of the Korea National Health and Nutrition Examination. Int J Environ Res Public Health. 2020;17. https://doi.org/10.3390/ijerph17124482.

  90. Ritchie SJ, Cox SR, Shen X, et al. Sex differences in the Adult Human Brain: evidence from 5216 UK Biobank participants. Cereb Cortex. 2018;28:2959–75. https://doi.org/10.1093/cercor/bhy109.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Sarris J, Logan AC, Akbaraly TN, et al. Nutritional medicine as mainstream in psychiatry. Lancet Psychiatry. 2015;2:271–4. https://doi.org/10.1016/S2215-0366(14)00051-0.

    Article  PubMed  Google Scholar 

  92. Ait-Hadad W, Benard M, Shankland R, et al. Optimism is associated with diet quality, food group consumption and snacking behavior in a general population. Nutr J. 2020;19:6. https://doi.org/10.1186/s12937-020-0522-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Mikola T, Marx W, Lane MM, et al. The effect of vitamin D supplementation on depressive symptoms in adults: a systematic review and meta-analysis of randomized controlled trials. Crit Rev Food Sci Nutr. 2023;63:11784–801. https://doi.org/10.1080/10408398.2022.2096560.

    Article  CAS  PubMed  Google Scholar 

  94. Głąbska D, Kołota A, Lachowicz K, et al. The Influence of Vitamin D Intake and status on Mental Health in children: a systematic review. Nutrients. 2021;13. https://doi.org/10.3390/nu13030952.

  95. Young LM, Pipingas A, White DJ et al. (2019). A Systematic Review and Meta-Analysis of B Vitamin Supplementation on Depressive Symptoms, Anxiety, and Stress: Effects on Healthy and ‘At-Risk’ Individuals. Nutrients 11. https://doi.org/10.3390/nu11092232.

  96. Sim M, Hong S, Jung S, et al. Vitamin C supplementation promotes mental vitality in healthy young adults: results from a cross-sectional analysis and a randomized, double-blind, placebo-controlled trial. Eur J Nutr. 2021;61:447–59. https://doi.org/10.1007/s00394-021-02656-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Noah L, Dye L, De Fer B, B., et al. Effect of magnesium and vitamin B6 supplementation on mental health and quality of life in stressed healthy adults: post-hoc analysis of a randomised controlled trial. Stress Health. 2021;37:1000–9. https://doi.org/10.1002/smi.3051.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Yan M, Liu Y, Wu L, et al. The Association between Dietary Purine Intake and Mortality: evidence from the CHNS Cohort Study. Nutrients. 2022;14. https://doi.org/10.3390/nu14091718.

  99. Zhang J, Zhao A. Dietary diversity and healthy aging: a prospective study. Nutrients. 2021;13. https://doi.org/10.3390/nu13061787.

  100. Song X, Wang H, Su C, et al. Secular trends in Time-of-Day of Energy Intake in a Chinese cohort. Nutrients. 2022;14. https://doi.org/10.3390/nu14102019.

  101. Zhao J, Su C, Wang H, et al. Secular trends in Energy and Macronutrient intakes and distribution among adult females (1991–2015): results from the China Health and Nutrition Survey. Nutrients. 2018;10. https://doi.org/10.3390/nu10020115.

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Acknowledgements

This study used data from the China Health and Nutrition Survey (CHNS). We gratefully acknowledge the National Institute of Nutrition, China Centre for Disease Control and Prevention; the Carolina Population Centre, University of North Carolina at Chapel Hill; the National Institutes of Health (NIH; R01-HD30880, DK056350, and R01-HD38700); and the Fogarty International Centre, NIH, for their financial contribution towards the CHNS data collection and analysis files since 1989. We also thank all the participants and the staff of CHNS involved in this study.

Funding

The study was funded by Beijing Hospitals Authority Youth Programme (No. QML20231903 to J.Z.). The Capital’s Funds for Health Improvement and Research (No. 2020-2-1171 to J.Z.). The Beijing Municipal Administration of Hospitals Incubating Program (No. PX2020073 to J.Z.). National Natural Science Foundation of China (82073573 to Z.Z.).

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Conceptualization, Z.Z.; methodology, Jia Zhou, H.W.; formal analysis, J.Z.; resources and data curation, Z.Z., H.W.; writing: original draft preparation, Jia Zhou; review and editing, C.P., Z.Z., Jingjing Zhou; supervision, project administration, and funding acquisition, Jia Zhou, Z.Z, Jingjing Zhou. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Jingjing Zhou or Zhiyong Zou.

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The study was approved by the Institutional Review Committee of the University of North Carolina at Chapel Hill, and the National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention.

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Zhou, J., Wang, H., Pao, C. et al. Association between 29 food groups of diet quality questionnaire and perceived stress in Chinese adults: a prospective study from China health and nutrition survey. BMC Public Health 24, 1832 (2024). https://doi.org/10.1186/s12889-024-19308-w

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