Next Article in Journal
Anti-Colorectal Cancer Effects of Inonotus hispidus (Bull.: Fr.) P. Karst. Spore Powder through Regulation of Gut Microbiota-Mediated JAK/STAT Signaling
Next Article in Special Issue
Higher Intake of Fat, Vitamin E-(β+γ), Magnesium, Sodium, and Copper Increases the Susceptibility to Prostatitis-like Symptoms: Evidence from a Chinese Adult Cohort
Previous Article in Journal
Effect of Fructooligosaccharides Supplementation on the Gut Microbiota in Human: A Systematic Review and Meta-Analysis
Previous Article in Special Issue
Development and Validation of Nutrition Literacy Assessment Instrument for Chinese Pregnant Women
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

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

1
The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
2
National Health Commission Key Laboratory of Reproductive Health, Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(16), 3297; https://doi.org/10.3390/nu14163297
Submission received: 20 June 2022 / Revised: 29 July 2022 / Accepted: 8 August 2022 / Published: 12 August 2022
(This article belongs to the Special Issue China National Nutrition Survey)

Abstract

:
Specific nutrients or dietary patterns influence an individual’s psychological stress. As a major aspect of a healthy diet, the influence of dietary diversity on psychological stress remains uncertain. Within these contexts, we aimed to examine the association between the dietary diversity score and psychological stress, using prospective data from the China Health and Nutrition Survey (CHNS). We included 7434 adult participants, with complete dietary information, in the 2011 wave, and followed-up with perceived stress scale (PSS-14) in the 2015 wave. The dietary intake of foods was coded into 29 food groups, using the DQQ for China, and the dietary diversity scores were obtained, using DQQ, by calculating the number of food groups consumed during one 24-h dietary recall. The univariate analysis, and logistic regression model were used to examine the relationship between psychological stress and diet diversity. Approximately half of the participants (4204, 56.55%) perceived a higher level of stress (PSS-14 total score > 25). Dietary diversity was lower in the higher-stress group (p for trend <0.0001). Unconditional multivariate logistic regression demonstrated that participants with higher daily dietary diversity were less likely to experience higher-level psychological stress, compared with participants with lower daily dietary diversity (ORs range: 0.480–0.809). Dietary diversity was found to be inversely associated with psychological stress, in this prospective analysis of a national population. Further studies are required to figure out the mechanism and effectiveness of dietary diversity on psychological stress.

1. Introduction

The burden of mental disorders is becoming a worldwide problem [1]. Psychological stress, defined as the sustained, excessive secretion of mental and/or emotional strain from work, family and other daily responsibilities [2], is a specific negative psychological experience that may elicit a host of mental disorders [3]. People living in modern society are faced with multiple stressors, including job stress, financial strain, relationship problems, and adverse life-events. It was estimated that 70% of visits to primary care providers can be attributed to psychological stress [4]. The effects of psychological stress on health require attention.
Several investigations have revealed that healthy dietary patterns, as modifiable lifestyle factors, can help manage stress and prevent stress-related diseases [5,6]. Nutritional psychiatry is an emerging field [7], and experimental evidence on the interplay of nutrition, stress, and mental disorders is increasing [3]. Studies indicate that specific nutrients or foods can influence an individual’s physiological and psychological response to stress [8]. For example, omega-3 polyunsaturated fatty acids and dietary vegetables have been considered to exert stress-buffering effects [9]. High-dose sustained-release ascorbic acid helps to palliate subjective responses to psychological stress [8]. Multivitamin supplementation has a beneficial effect on reducing stress and mood symptoms [10]. Soy lecithin phosphatidic acid and phosphatidylserine complex (PAS) has potential in the treatment of stress-related disorders [11]. A Mediterranean diet supplemented with dairy foods or nuts could exert a beneficial effect on cognitive function and psychological well-being [12,13]. A previous study also demonstrated the significant clinical effect of Mg, B vitamins, rhodiola, and green tea (L-theanine) on relieving stress, after only 14 days of treatment [14]. These studies have focused, more specifically, on the relationship between individual nutrients and psychological stress or stress-related diseases [15]. Despite the role of individual nutrients, a diverse diet is a cornerstone of a sufficient and balanced supply of nutrients [16].
Dietary diversity is a major aspect of a healthy diet [17]. It is defined as the number of foods or food groups consumed individually over a certain period [18]. Although the dietary diversity score cannot perform a comprehensive assessment of nutrient intake, it provides a good assessment of the nutritional adequacy of the diet [19]. The dietary diversity score is a convenient and cost-benefit-integrated indicator of diet quality [20]. In most dietary guidelines, globally, a diverse diet is suggested [21,22], and thought to be one of the best population-engaged approaches to improving public nutrition [23]. According to the results of previous studies, the dietary diversity score is negatively correlated with anxiety [17] and depression [24]. A diverse diet may mitigate cognitive decline and reduce the risk of cognitive impairment in older adults [25]. Moreover, psychological resilience, defined as the ability to cope, adapt, and respond positively to stress, was reported to be positively associated with dietary diversity [26]. However, studies specifically examining the relationship between dietary diversity and psychological stress prospectively among adults are very scarce [27].
Moreover, previous studies calculated dietary diversity using eight food groups [27] or five main food groups [28], which usually depended on quantitative dietary measurement, such as the 24-h dietary recall survey. Recently, the Diet Quality Questionnaire (DQQ) was developed using 29 food groups, to enable the collection of population-level dietary data, based on the framework of global diet quality [29]. The DQQ is a low-burden and standardized method, which has been adapted for the Chinese population, and is used to measure the dietary diversity score [30]. In the present study, we aimed to examine the association between the dietary diversity score, calculated from DQQ for China, and psychological stress, using prospective data from the China Health and Nutrition Survey (CHNS).

2. Materials and Methods

2.1. Data Resource and Study Participants

In the present study, the data was obtained from the China Health and Nutrition Survey (CHNS), an ongoing, national, household-based cohort study, developed and administered 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 CHNS research team employed a multistage, stratified sampling design and included participants from nine provinces to ensure the study’s representativeness. This project was reviewed and approved by the corresponding institutional review committees (2015017). Informed consent was obtained from all participants. Detailed information regarding the project’s description, design, methods and quality control procedures, and the research teams of the CHNS, can be obtained from the cohort profile [31] and the official website (http://www.cpc.unc.edu/projects/china, accessed on 27 May 2022).
Our analysis included the two rounds of survey data collected in 2011 and 2015. There were 15,725 participants in the 2011 wave of the CHNS, and 8737 adult participants were followed up in the 2015 wave. In the 2015 wave, the Perceived Stress Scale (PSS) (Chinese version), was administered in the project for the first time [32], and we included 7434 participants, with information on: basic demographic characteristics (i.e., age, gender, weight (kg), height (m), marital status, province, and urbanization index); complete PSS-14 score; and dietary information (Figure 1).

2.2. Study Outcome and Definitions

The perceived psychological stress was measured in 2015 using PSS-14, which was developed by Cohen et al. [33]. It is the most widely-used instrument for measuring psychological stress [32]. The Chinese version of this scale was validated [34]. The PSS-14 comprises 14 items, rated 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 (4–7, 9, 10 and 13). Possible scores range from 0 to 56 by summing the scores across all 14 items, with higher scores indicating higher perceived stress. A previous study by Leng et al. (2021) [35] suggested that a total stress score of >25 points can be considered harmful and has a certain degree of negative impact on a person’s physical and mental health. The PSS-14 demonstrated high reliability in our sample (Cronbach α = 0.83).

2.3. Dietary Data Collection and Assessment

The quantitative dietary data was collected using three consecutive 24-h recalls, by trained investigators [36]. A previous study had validated the reliability of the 24-h dietary recall [37]. Further details on the dietary interview have been described elsewhere [38].
DQQ is a rapid dietary-assessment tool that captures food-group level data and reflects dietary patterns through sentinel foods (defined as the foods in each food group that were consumed by more than 95% of people) [30,39]. In addition, a previous study had already adapted DQQ for China and verified its reliability in capturing food group consumption in the Chinese population [30]. DQQ, the instrument we used, was designed to obtain and evaluate food-group intake data from only one 24-h recall [30]. Thus, in this study, the dietary intake of foods during the first day only, was coded into 29 food groups using the DQQ for China as follows: (1) staple foods made from grains; (2) whole grains; (3) white roots/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 and seafood; (21) nuts and 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. Dietary diversity scores were obtained using DQQ by calculating the number of food groups consumed during the 24-h dietary recall. More information about DQQ for China was previously described [30].

2.4. Measurements and Calculation of Covariates

Information on sociodemographic factors (e.g., age, gender, weight and height, marital status, and urbanization index) was assessed. Body weight and height were measured according to standard procedures. Body mass index (BMI, kg/m2) was calculated by the formula: weight (kg)/[height (m)]2. Underweight was defined as BMI < 18 kg/m2, normal weight was defined as BMI ≥ 18.5 kg/m2 and <24 kg/m2, overweight was defined as BMI ≥ 24 kg/m2 and <28 kg/m2, and obese was defined as BMI ≥ 28 kg/m2.
The CHNS research team reminded the potential users of the data that the sampling weights are unavailable, and recommended that the users employ control measures, such as the community-level measures of the newly created urbanization index, to control for multilevel, multistage sampling and various multilevel modeling issues [31,40]. Thus, in our study, the urbanization index was controlled as a covariate in multivariate logistic regression, to explore the association between perceived stress and dietary diversity.

2.5. Statistical Analysis

Descriptive analyses were used to analyze sample characteristics. The normality of the data distribution was assessed using the Shapiro–Wilk test. Data was summarized in terms of numbers (percentages) for categorical parameters, and medians ± interquartile ranges for continuous parameters that fit a non-normal distribution.
First, univariate analysis was used to analyze the difference, in several variables, between the psychological stress levels. A Wilcoxon rank test was applied for non-Gaussian assumption, to compare differences in continuous parameters between groups (PSS-14 ≤ 25 vs. PSS-14 > 25). For categorical variables, statistical significance between various groups was assessed using Chi-square test. The Cochran–Armitage test was used to examine the trends in dietary diversity across perceived stress-level groups.
Second, we used logistic regression models to explore the association between perceived stress and dietary diversity. Odds ratios (OR) [95% confidence interval] were presented using maximum likelihood methods. Variables adjusted in the model included: age; marital status (never married, married, and divorced/separated/widowed); BMI group (underweight, normal weight, overweight, and obese); gender (female or male); and urbanization index in 2015.
Figures of stratified analyses by gender (female vs. male) were created. The 2-sided p-value <0.05 was considered as statistically significant. All analyses were performed using SAS statistical software version 9.4 (SAS Institute Inc., Cary, NC, USA).

3. Results

3.1. Participant Characteristics

In the analysis, 7434 participants were included. Descriptive statistics of the participants is displayed in Table 1. A total of 4204 (56.55%) people perceived a higher level of stress (PSS-14 total score > 25) and 3230 (43.45%) had a lower level of stress (PSS-14 total score ≤25). Gender, marital status, urbanization index, and BMI showed statistically significant differences between the PSS-14 groups (p < 0.05) (Table 1).

3.2. The Distribution of Dietary Diversity and Perceived Stress Level

The proportions of different DQQ food groups in the two stress groups are presented in Table 2. Due to the small sample size of participants eating more than 10 species of food in one day, they were aggregated into one group (number of DQQ food groups ≥ 10) in the analysis. According to the result of the Cochran-Armitage test, when compared with the higher-stress group, dietary diversity was higher in the lower-stress group (Z = 7.1100, p for trend < 0.0001). In general, the level of psychological stress decreased as the daily dietary diversity increased, for both female and male (Figure 2).

3.3. The Relationship between Dietary Diversity and Perceived Stress Level

Unconditional multivariate logistic regression demonstrated that participants with higher dietary diversity in their daily diet were less likely to experience a higher level of psychological stress, compared with participants with lower daily dietary diversity (ORs range: 0.480–0.809) (Table 3).

4. Discussion

In this national prospective study using the data from the CHNS, we observed an inverse association between dietary diversity and perceived psychological stress, which remained significant after adjustment for covariates. This finding implies that the more food groups one eats, the less psychological stress one may have.
Diet, as a modifiable environmental factor, plays an important role in modulating psychological stress and preventing stress-related disease [41]. In general support of this idea, there have been recent human and animal studies reporting stress-reducing effects of specific nutrients, or dietary patterns [42]. In animal experiments, calorie restriction, Mediterranean diet, and diets containing prebiotics and/or glycoprotein lactoferrin were proven to reduce psychological stress or enhance stress resilience [43,44,45]. Regarding human research, dietary supplementation with specific nutrients, such as macular carotenoids [42], omega-3 [46], omega-6 [46], Eicosatetraenoic-Acid-enriched phospholipids [47], bioactive components [48], probiotics [49] and B group vitamins [50], was found to reduce psychological distress and mental-disease symptoms, through mechanisms possibly related to neuroinflammation and apoptosis [47]. Moreover, diet pattern was reported to influence psychological distress and stress-induced disorders. For example, Helms, E.R., et al., indicated that high-protein low-fat diet may be effective in mitigating stress and fatigue [51] through alterations in gut microbiota and expression of inflammatory genes [52]. Dietary approaches to stop hypertension, (DASH) dietary patterns, were associated with better mental health in Iranian university students [53]. Additionally, a highly palatable diet, offering a choice of food items, is associated with a reduction in the response to chronic variable stress (CVS) [54]. In addition, a meta-analysis concluded that adhering to a healthy diet and avoiding a pro-inflammatory diet appears to confer some protection against depression [55]. However, no significant associations were observed between a vegetarian dietary pattern and mental-health outcomes in another meta-analysis [56]. Different foods and food groups are good sources of various macro-, and micronutrients [57], so a diversified diet best ensures nutrient adequacy and may play an important role in influencing psychological stress.
In our study, we found that higher dietary diversity was associated with lower psychological stress in Chinese adults, and there was a dose-response relationship. We calculated the dietary diversity score using the data from only one recall. One concern is that it may not represent an individual’s habitual eating patterns as effectively as a calculation using data from more recalls. However, this fact didn’t seem to impact the final result: our study found an association similar to that found by another study, which, using the CHNS 3-day dietary recall of elderly people, found that higher dietary diversity was associated with less psychological stress (ORs range: 0.59–0.63) [27], and even the strengths of association in the two studies were quite similar. Therefore, the number of recalls included in the study might not have fundamentally impacted the finding. This result is also supported by other previous studies investigating the beneficial effect of higher dietary diversity on psychological stress. For instance, dietary diversity was reported to be associated with psychological resilience, which is defined as the ability to cope, adapt, and respond positively to stress [26]. In the longitudinal analysis of Jiang et al., it was demonstrated that the dietary diversity level was negatively associated with the future depression level [58]. Women with higher dietary diversity were reported to obtain lower anxiety scores [17]. In preschoolers, a higher dietary diversity was reported to be associated with a lower likelihood of having mental-health symptoms, such as hyperactivity/inattention, peer relationship problems, and prosocial behavior problems [59]. These all indicate that an enriched diet may have a protective effect against stress or stress-related health issues.
Although the potential mechanism underlying these associations is not clear, there are several possible explanations for how a varied diet protects against psychological stress. First, dietary diversity is a useful proxy of nutritional adequacy and diet quality [18], so higher dietary diversity may be beneficial for mental health. For example, the intake of adequate micronutrients, such as zinc, magnesium, and selenium, is related to the promotion of mental health [60]. Second, previous studies have indicated that an enriched diet is associated with an increased intake of healthy food groups, such as fruits, vegetables, and dairy products [24]. Contrarily, a randomized clinical trial suggested that restricting meat-, fish-, and poultry intake was positively correlated with both dietary diversity and mood state [61]. Therefore, it could be said that with an increase of dietary diversity, the dietary pattern could become more similar to the Mediterranean diet, which is characterized by a high intake of fruits, vegetables, whole grains, legumes, nuts, and seeds and low consumption of red meat [62]. Third, the protective effect of a diverse diet on psychological stress may be attributed to the higher antioxidant intake [63], which has a positive impact on oxidative stress, and immune response [59], protecting the mitochondria and lipids in neuronal circuits [64]. Fourth, higher dietary diversity may also contribute to mental health through a healthier microbiota [27]. Recent findings indicated that decreased dietary diversity corresponded with reduced microbiome diversity [65], which was suggested to be strongly associated with stress-related disorders [66].

5. Strengths and Limitations

In this study, we examined the relationship between dietary diversity and psychological stress, prospectively. First, the 29 food group dietary diversity score—according to the China-adapted DQQ—was calculated for the first time for Chinese populations and we observed a higher likelihood of lower psychological stress with higher dietary diversity. This result implies that improving dietary diversity might be an important strategy in reducing psychological stress and improving mental health [59]. Second, this study used the 2011 and 2015 waves of the CHNS data obtained from a national representative sample. This helped to ensure that all relevant types of people were included in the sample, limiting the effect of confounders.
However, several limitations of this study should be noted. First, although covariates, such as age, sex, urbanization index, marital status, and BMI were considered in analyses, other potential confounders were not controlled, such as family history of mental health, physical activity, and income. Second, the cross-sectional nature of the study means that the evidence cannot imply causation. Further animal studies and randomized controlled trials are needed, to validate the interventional effect and causal relationship between dietary diversity and psychological stress. Third, the dietary information was gathered in 2011, and stress was assessed in 2015. While a person’s dietary habits can remain stable over their lifetime, they may also vary with changing circumstances. Therefore, it is a limitation that the diet was not analyzed at both time points. Fourth, while a minimum of three dietary recalls are needed to represent habitual diet, only one of the 24-h diet recalls in 2011 was used to calculate dietary diversity in our study.

6. Conclusions

In conclusion, dietary diversity calculated using China-adapted DQQ was inversely associated with psychological stress in this prospective analysis of a national population. Further studies are needed to ascertain the mechanism underlying the association and effectiveness of dietary diversity in reducing psychological stress.

Author Contributions

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

Funding

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

Institutional Review Board Statement

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.

Informed Consent Statement

Informed consent was obtained from all subjects.

Data Availability Statement

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).

Acknowledgments

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.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study, data collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

References

  1. GBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry 2022, 9, 137–150. [Google Scholar] [CrossRef]
  2. Vidal, E.J.; Alvarez, D.; Martinez-Velarde, D.; Vidal-Damas, L.; Yuncar-Rojas, K.A.; Julca-Malca, A.; Bernabe-Ortiz, A. Perceived stress and high fat intake: A study in a sample of undergraduate students. PLoS ONE 2018, 13, e0192827. [Google Scholar] [CrossRef] [PubMed]
  3. Bremner, J.D.; Moazzami, K.; Wittbrodt, M.T.; Nye, J.A.; Lima, B.B.; Gillespie, C.F.; Rapaport, M.H.; Pearce, B.D.; Shah, A.J.; Vaccarino, V. Diet, Stress and Mental Health. Nutrients 2020, 12, 2428. [Google Scholar] [CrossRef] [PubMed]
  4. McCabe, D.; Lisy, K.; Lockwood, C.; Colbeck, M. The impact of essential fatty acid, B vitamins, vitamin C, magnesium and zinc supplementation on stress levels in women: A systematic review. JBI Database Syst. Rev. Implement. Rep. 2017, 15, 402–453. [Google Scholar] [CrossRef]
  5. Li, Y.; Lv, M.R.; Wei, Y.J.; Sun, L.; Zhang, J.X.; Zhang, H.G.; Li, B. Dietary patterns and depression risk: A meta-analysis. Psychiatry Res. 2017, 253, 373–382. [Google Scholar] [CrossRef]
  6. Li, R.; Zong, Z.Y.; Gu, X.X.; Wang, D.N.; Dong, C.; Sun, C.; Zhao, R.; Gu, Z.F.; Gao, J.L. Higher dietary diversity as a protective factor against depression among older adults in China: A cross-sectional study. Ann. Palliat. Med. 2021, 11, 1278–1289. [Google Scholar] [CrossRef]
  7. Jesus, M.; Silva, T.; Cagigal, C.; Martins, V.; Silva, C. Dietary Patterns: A New Therapeutic Approach for Depression? Curr. Pharm. Biotechnol. 2019, 20, 123–129. [Google Scholar] [CrossRef]
  8. Brody, S.; Preut, R.; Schommer, K.; Schürmeyer, T.H. A randomized controlled trial of high dose ascorbic acid for reduction of blood pressure, cortisol, and subjective responses to psychological stress. Psychopharmacology 2002, 159, 319–324. [Google Scholar] [CrossRef]
  9. Soltani, H.; Keim, N.L.; Laugero, K.D. Diet Quality for Sodium and Vegetables Mediate Effects of Whole Food Diets on 8-Week Changes in Stress Load. Nutrients 2018, 10, 1606. [Google Scholar] [CrossRef]
  10. Long, S.J.; Benton, D. Effects of vitamin and mineral supplementation on stress, mild psychiatric symptoms, and mood in nonclinical samples: A meta-analysis. Psychosom. Med. 2013, 75, 144–153. [Google Scholar] [CrossRef]
  11. Hellhammer, J.; Fries, E.; Buss, C.; Engert, V.; Tuch, A.; Rutenberg, D.; Hellhammer, D. Effects of soy lecithin phosphatidic acid and phosphatidylserine complex (PAS) on the endocrine and psychological responses to mental stress. Stress 2004, 7, 119–126. [Google Scholar] [CrossRef]
  12. Wade, A.T.; Davis, C.R.; Dyer, K.A.; Hodgson, J.M.; Woodman, R.J.; Keage, H.A.D.; Murphy, K.J. 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, 646–658. [Google Scholar] [CrossRef]
  13. Sánchez-Villegas, A.; Martínez-González, M.A.; Estruch, R.; Salas-Salvadó, J.; Corella, D.; Covas, M.I.; Arós, F.; Romaguera, D.; Gómez-Gracia, E.; Lapetra, J.; et al. Mediterranean dietary pattern and depression: The PREDIMED randomized trial. BMC Med. 2013, 11, 208. [Google Scholar] [CrossRef]
  14. Noah, L.; Morel, V.; Bertin, C.; Pouteau, E.; Macian, N.; Duale, C.; Pereira, B.; Pickering, G. 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, 1863. [Google Scholar] [CrossRef]
  15. Rashidkhani, B.; Gargari, B.P.; Ranjbar, F.; Zareiy, S.; Kargarnovin, Z. Dietary patterns and anthropometric indices among Iranian women with major depressive disorder. Psychiatry Res. 2013, 210, 115–120. [Google Scholar] [CrossRef]
  16. Merali, Z.; Graitson, S.; Mackay, J.C.; Kent, P. Stress and eating: A dual role for bombesin-like peptides. Front. Neurosci. 2013, 7, 193. [Google Scholar] [CrossRef]
  17. Poorrezaeian, M.; Siassi, F.; Qorbani, M.; Karimi, J.; Koohdani, F.; Asayesh, H.; Sotoudeh, G. Association of dietary diversity score with anxiety in women. Psychiatry Res. 2015, 230, 622–627. [Google Scholar] [CrossRef]
  18. Oldewage-Theron, W.H.; Kruger, R. Food variety and dietary diversity as indicators of the dietary adequacy and health status of an elderly population in Sharpeville, South Africa. J. Nutr. Elder. 2008, 27, 101–133. [Google Scholar] [CrossRef]
  19. De Oliveira Otto, M.C.; Anderson, C.A.M.; Dearborn, J.L.; Ferranti, E.P.; Mozaffarian, D.; Rao, G.; Wylie-Rosett, J.; Lichtenstein, A.H.L. American Heart Association Behavioral Change for Improving Health Factors Committee of the Council on, H. Cardiometabolic, et al. Dietary Diversity: Implications for Obesity Prevention in Adult Populations: A Science Advisory from the American Heart Association. Circulation 2018, 138, e160–e168. [Google Scholar]
  20. Azadbakht, L.; Esmaillzadeh, A. Dietary diversity score is related to obesity and abdominal adiposity among Iranian female youth. Public Health Nutr. 2010, 14, 62–69. [Google Scholar] [CrossRef]
  21. World Health Organization WHO. Healthy Diet. Available online: https://www.who.int/news-room/fact-sheets/detail/healthy-diet (accessed on 22 April 2021).
  22. Chinese Nutrition Society. The Chinese Dietary Guidelines, 4th ed.; People’s Health Publishing House: Beijing, China, 2016; pp. 1–298. ISBN 978-711-722-214-3. [Google Scholar]
  23. Otsuka, R.; Kato, Y.; Nishita, Y.; Tange, C.; Nakamoto, M.; Tomida, M.; Imai, T.; Ando, F.; Shimokata, H.; Suzuki, T. Dietary diversity and 14-year decline in higher-level functional capacity among middle-aged and elderly Japanese. Nutrition 2016, 32, 784–789. [Google Scholar] [CrossRef]
  24. Poorrezaeian, M.; Siassi, F.; Milajerdi, A.; Qorbani, M.; Karimi, J.; Sohrabi-Kabi, R.; Pak, N.; Sotoudeh, G. Depression is related to dietary diversity score in women: A cross-sectional study from a developing country. Ann. Gen. Psychiatry 2017, 16, 39. [Google Scholar] [CrossRef]
  25. Zheng, J.; Zhou, R.; Li, F.; Chen, L.; Wu, K.; Huang, J.; Liu, H.; Huang, Z.; Xu, L.; Yuan, Z.; et al. Association between dietary diversity and cognitive impairment among the oldest-old: Findings from a nationwide cohort study. Clin. Nutr. 2021, 40, 1452–1462. [Google Scholar] [CrossRef]
  26. Yin, Z.; Brasher, M.S.; Kraus, V.B.; Lv, Y.; Shi, X.; Zeng, Y. Dietary Diversity Was Positively Associated with Psychological Resilience among Elders: A Population-Based Study. Nutrients 2019, 11, 650. [Google Scholar] [CrossRef]
  27. Zhang, J.; Zhao, A. Dietary Diversity and Healthy Aging: A Prospective Study. Nutrients 2021, 13, 1787. [Google Scholar] [CrossRef]
  28. Salehi-Abargouei, A.; Akbari, F.; Bellissimo, N.; Azadbakht, L. Dietary diversity score and obesity: A systematic review and meta-analysis of observational studies. Eur. J. Clin. Nutr. 2015, 70, 1–9. [Google Scholar] [CrossRef]
  29. Herforth, A.; Steele, E.M.; Calixto, G.; Sattamini, I.; Olarte, D.; Ballard, T.; Monteiro, C. Development of a Diet Quality Questionnaire for Improved Measurement of Dietary Diversity and Other Diet Quality Indicators (P13-018-19). Curr. Dev. Nutr. 2019, 3, nzz036-P13. [Google Scholar] [CrossRef]
  30. Ma, S.; Herforth, A.W.; Vogliano, C.; Zou, Z. Most Commonly-Consumed Food Items by Food Group, and by Province, in China: Implications for Diet Quality Monitoring. Nutrients 2022, 14, 1754. [Google Scholar] [CrossRef]
  31. Zhang, B.; Zhai, F.Y.; Du, S.F.; Popkin, B.M. The China Health and Nutrition Survey, 1989–2011. Obes. Rev. 2014, 15 (Suppl. S1), 2–7. [Google Scholar] [CrossRef]
  32. Cao, B.; Zhao, Y.; Ren, Z.; McIntyre, R.S.; Teopiz, K.M.; Gao, X.; Ding, L. Are Physical Activities Associated With Perceived Stress? The Evidence From the China Health and Nutrition Survey. Front. Public Health 2021, 9, 697484. [Google Scholar] [CrossRef]
  33. Cohen, S.; Kamarck, T.; Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 1983, 24, 385–396. [Google Scholar] [CrossRef] [PubMed]
  34. Huang, F.; Wang, H.; Wang, Z.; Zhang, J.; Du, W.; Su, C.; Jia, X.; Ouyang, Y.; Wang, Y.; Li, L.; et al. Psychometric properties of the perceived stress scale in a community sample of Chinese. BMC Psychiatry 2020, 20, 130. [Google Scholar]
  35. Leng, M.; Wei, L.; Shi, X.; Cao, G.; Wei, Y.; Xu, H.; Zhang, X.; Zhang, W.; Xing, S.; Wei, H. Mental distress and influencing factors in nurses caring for patients with COVID-19. Nurs. Crit. Care 2020, 26, 94–101. [Google Scholar] [CrossRef] [PubMed]
  36. Zhai, F.Y.; Du, S.F.; Wang, Z.H.; Zhang, J.G.; Du, W.W.; Popkin, B.M. Dynamics of the Chinese diet and the role of urbanicity, 1991–2011. Obes. Rev. 2014, 15 (Suppl. S1), 16–26. [Google Scholar] [CrossRef]
  37. Zhai, F.; Guo, X.; Popkin, B.M.; Ma, L.; Wang, Q.; Shuigao, W.Y.; Ge, J.A.K. Evaluation of the 24-Hour Individual Recall Method in China. Food Nutr. Bull. 1996, 17, 1–7. [Google Scholar] [CrossRef]
  38. Yan, S.; Li, J.; Li, S.; Zhang, B.; Du, S.; Gordon-Larsen, P.; Adair, L.; Popkin, B. The expanding burden of cardiometabolic risk in China: The China Health and Nutrition Survey. Obes. Rev. 2012, 13, 810–821. [Google Scholar] [CrossRef]
  39. Herforth, A.W.; Wiesmann, D.; Martínez-Steele, E.; Andrade, G.; Monteiro, C.A. Introducing a Suite of Low-Burden Diet Quality Indicators That Reflect Healthy Diet Patterns at Population Level. Curr. Dev. Nutr. 2020, 4, nzaa168. [Google Scholar] [CrossRef]
  40. Popkin, B.M. Weights for the China Health and Nutrition Study. Available online: https://bbs.pinggu.org/a-2362260.html (accessed on 27 May 2022).
  41. Gonzalez, M.J.; Miranda-Massari, J.R. Diet and stress. Psychiatr. Clin. N. Am. 2014, 37, 579–589. [Google Scholar] [CrossRef]
  42. Stringham, N.T.; Holmes, P.V.; Stringham, J.M. Supplementation with macular carotenoids reduces psychological stress, serum cortisol, and sub-optimal symptoms of physical and emotional health in young adults. Nutr. Neurosci. 2017, 21, 286–296. [Google Scholar] [CrossRef]
  43. Willette, A.A.; Coe, C.L.; Colman, R.J.; Bendlin, B.B.; Kastman, E.K.; Field, A.S.; Alexander, A.L.; Allison, D.B.; Weindruch, R.H.; Johnson, S.C. Calorie restriction reduces psychological stress reactivity and its association with brain volume and microstructure in aged rhesus monkeys. Psychoneuroendocrinology 2012, 37, 903–916. [Google Scholar] [CrossRef]
  44. Shively, C.A.; Appt, S.E.; Chen, H.; Day, S.M.; Frye, B.M.; Shaltout, H.A.; Silverstein-Metzler, M.G.; Snyder-Mackler, N.; Uberseder, B.; Vitolins, M.Z.; et al. Mediterranean diet, stress resilience, and aging in nonhuman primates. Neurobiol. Stress 2020, 13, 100254. [Google Scholar] [CrossRef]
  45. Mika, A.; Day, H.E.; Martinez, A.; Rumian, N.L.; Greenwood, B.N.; Chichlowski, M.; Berg, B.M.; Fleshner, M. Early life diets with prebiotics and bioactive milk fractions attenuate the impact of stress on learned helplessness behaviours and alter gene expression within neural circuits important for stress resistance. Eur. J. Neurosci. 2016, 45, 342–357. [Google Scholar] [CrossRef]
  46. Ramsden, C.E.; Zamora, D.; Makriyannis, A.; Wood, J.T.; Mann, J.D.; Faurot, K.R.; MacIntosh, B.A.; Majchrzak-Hong, S.F.; Gross, J.R.; Courville, A.B.; et al. Diet-induced changes in n-3- and n-6-derived endocannabinoids and reductions in headache pain and psychological distress. J. Pain 2015, 16, 707–716. [Google Scholar] [CrossRef]
  47. Wang, C.C.; Du, L.; Shi, H.H.; Ding, L.; Yanagita, T.; Xue, C.H.; Wang, Y.M.; Zhang, T.T. Dietary EPA-Enriched Phospholipids Alleviate Chronic Stress and LPS-Induced Depression and Anxiety-Like Behavior by Regulating Immunity and Neuroinflammation. Mol. Nutr. Food Res. 2021, 65, e2100009. [Google Scholar] [CrossRef]
  48. Jaatinen, N.; Korpela, R.; Poussa, T.; Turpeinen, A.; Mustonen, S.; Merilahti, J.; Peuhkuri, K. Effects of daily intake of yoghurt enriched with bioactive components on chronic stress responses: A double-blinded randomized controlled trial. Int. J. Food Sci. Nutr. 2014, 65, 507–514. [Google Scholar] [CrossRef]
  49. Marquez-Morales, L.; El-Kassis, E.G.; Cavazos-Arroyo, J.; Rocha-Rocha, V.; Martinez-Gutierrez, F.; Perez-Armendariz, B. Effect of the Intake of a Traditional Mexican Beverage Fermented with Lactic Acid Bacteria on Academic Stress in Medical Students. Nutrients 2021, 13, 1551. [Google Scholar] [CrossRef]
  50. Stough, C.; Simpson, T.; Lomas, J.; McPhee, G.; Billings, C.; Myers, S.; Oliver, C.; Downey, L.A. Reducing occupational stress with a B-vitamin focussed intervention: A randomized clinical trial: Study protocol. Nutr. J. 2014, 13, 122. [Google Scholar] [CrossRef]
  51. Helms, E.R.; Zinn, C.; Rowlands, D.S.; Naidoo, R.; Cronin, J. High-protein, low-fat, short-term diet results in less stress and fatigue than moderate-protein moderate-fat diet during weight loss in male weightlifters: A pilot study. Int. J. Sport Nutr. Exerc. Metab. 2015, 25, 163–170. [Google Scholar] [CrossRef]
  52. Yanguas-Casas, N.; Torres, C.; Crespo-Castrillo, A.; Diaz-Pacheco, S.; Healy, K.; Stanton, C.; Chowen, J.A.; Garcia-Segura, L.M.; Arevalo, M.A.; Cryan, J.F.; et al. High-fat diet alters stress behavior, inflammatory parameters and gut microbiota in Tg APP mice in a sex-specific manner. Neurobiol. Dis. 2021, 159, 105495. [Google Scholar] [CrossRef]
  53. Faghih, S.; Babajafari, S.; Mirzaei, A.; Akhlaghi, M. Adherence to the dietary approaches to stop hypertension (DASH) dietary pattern and mental health in Iranian university students. Eur. J. Nutr. 2020, 59, 1001–1011. [Google Scholar] [CrossRef]
  54. Zeeni, N.; Daher, C.; Fromentin, G.; Tome, D.; Darcel, N.; Chaumontet, C. A cafeteria diet modifies the response to chronic variable stress in rats. Stress 2012, 16, 211–219. [Google Scholar] [CrossRef] [PubMed]
  55. Lassale, C.; Batty, G.D.; Baghdadli, A.; Jacka, F.; Sánchez-Villegas, A.; Kivimäki, M.; Akbaraly, T. Healthy dietary indices and risk of depressive outcomes: A systematic review and meta-analysis of observational studies. Mol. Psychiatry 2019, 24, 965–986. [Google Scholar] [CrossRef] [PubMed]
  56. Askari, M.; Daneshzad, E.; Mofrad, M.D.; Bellissimo, N.; Suitor, K.; Azadbakht, L. Vegetarian diet and the risk of depression, anxiety, and stress symptoms: A systematic review and meta-analysis of observational studies. Crit. Rev. Food Sci. Nutr. 2022, 62, 261–271. [Google Scholar] [CrossRef] [PubMed]
  57. Molla, W.; Adem, D.A.; Tilahun, R.; Shumye, S.; Kabthymer, R.H.; Kebede, D.; Mengistu, N.; Ayele, G.M.; Assefa, D.G. Dietary diversity and associated factors among children (6–23 months) in Gedeo zone, Ethiopia: Cross-sectional study. Ital. J. Pediatr. 2021, 47, 233. [Google Scholar] [CrossRef]
  58. Jiang, W.; Mo, M.; Li, M.; Wang, S.; Muyiduli, X.; Shao, B.; Jiang, S.; Yu, Y. The relationship of dietary diversity score with depression and anxiety among prenatal and post-partum women. J. Obstet. Gynaecol. Res. 2018, 44, 1929–1936. [Google Scholar] [CrossRef]
  59. Li, S.; Chen, K.; Liu, C.; Bi, J.; He, Z.; Luo, R.; Yu, Y.; Wang, Z. Dietary diversity and mental health in preschoolers in rural China. Public Health Nutr. 2020, 24, 1869–1876. [Google Scholar] [CrossRef]
  60. Wang, J.; Um, P.; Dickerman, B.A.; Liu, J. Zinc, Magnesium, Selenium and Depression: A Review of the Evidence, Potential Mechanisms and Implications. Nutrients 2018, 10, 584. [Google Scholar] [CrossRef]
  61. Beezhold, B.L.; Johnston, C.S. Restriction of meat, fish, and poultry in omnivores improves mood: A pilot randomized controlled trial. Nutr. J. 2012, 11, 9. [Google Scholar] [CrossRef]
  62. Muñoz, M.A.; Fíto, M.; Marrugat, J.; Covas, M.I.; Schröder, H. Adherence to the Mediterranean diet is associated with better mental and physical health. Br. J. Nutr. 2009, 101, 1821–1827. [Google Scholar] [CrossRef]
  63. Abshirini, M.; Siassi, F.; Koohdani, F.; Qorbani, M.; Mozaffari, H.; Aslani, Z.; Soleymani, M.; Entezarian, M.; Sotoudeh, G. Dietary total antioxidant capacity is inversely associated with depression, anxiety and some oxidative stress biomarkers in postmenopausal women: A cross-sectional study. Ann. Gen. Psychiatry 2019, 18, 3. [Google Scholar] [CrossRef]
  64. Chen, Y.; Feng, X.; Hu, X.; Sha, J.; Li, B.; Zhang, H.; Fan, H. Dexmedetomidine Ameliorates Acute Stress-Induced Kidney Injury by Attenuating Oxidative Stress and Apoptosis through Inhibition of the ROS/JNK Signaling Pathway. Oxid. Med. Cell. Longev. 2018, 2018, 4035310. [Google Scholar] [CrossRef]
  65. Johnson, A.J.; Howell, B.R. Dietary diversity contributes to microbiome associations in autism. Cell Metab. 2021, 33, 2311–2313. [Google Scholar] [CrossRef]
  66. Winter, G.; Hart, R.A.; Charlesworth, R.P.G.; Sharpley, C.F. Gut microbiome and depression: What we know and what we need to know. Rev. Neurosci. 2018, 29, 629–643. [Google Scholar] [CrossRef]
Figure 1. Participant flow diagram.
Figure 1. Participant flow diagram.
Nutrients 14 03297 g001
Figure 2. Trends in the relationship between psychological stress and dietary diversity. (a) The relationship for all participants; (b) The relationship for female participants; (c) The relationship for male participants.
Figure 2. Trends in the relationship between psychological stress and dietary diversity. (a) The relationship for all participants; (b) The relationship for female participants; (c) The relationship for male participants.
Nutrients 14 03297 g002
Table 1. Descriptive statistics of participants.
Table 1. Descriptive statistics of participants.
Variables
n (%) or Median (Quartile)
Total Participants
(n = 7434)
Lower Psychological Stress Group (n = 4204)Higher Psychological Stress Group (n = 3230)Z/ϰ2p
Age in 201151.00 (41.00–60.00)51.00 (41.00–60.00)52.00 (41.00–61.00)1.13030.2584
Age in 201555.00 (45.00–65.00)55.00 (45.00–64.00)56.00 (45.00–65.00)1.14440.2525
Gender 9.60490.0019
Male3464 (46.60)2025 (48.17)1439 (44.55)
Female3970 (53.40)2179 (51.83)1791 (55.45)
Marital status in 2011 9.52940.0230
Never married286 (3.86)171 (4.07)115 (3.56)
Married6530 (88.14)3712 (88.30)2818 (87.24)
Divorced/Separated/Widowed593 (8.00)304 (7.23)289 (8.95)
Marital status in 2015 11.62030.0088
Never married184 (2.48)110 (2.62)74 (2.29)
Married6596 (88.97)3764 (89.53)2832 (87.68)
Divorced/Separated/Widowed634 (8.55)321 (7.64)313 (9.69)
BMI in 201123.70 (21.45–26.15)23.80 (21.49–26.26)23.61 (21.36–26.03)−2.65820.0079
BMI categories in 2011 13.77770.0032
Normal weight3555 (49.01)2013 (48.84)1542 (49.23)
Obesity922 (12.71)545 (13.22)377 (12.04)
Overweight2457 (33.87)1412 (34.26)1045 (33.37)
Underweight320 (4.41)152 (3.69)168 (5.36)
BMI in 201524.09 (21.82–26.52)24.13 (21.89–26.52)24.07 (21.75–26.52)−1.35820.1744
BMI categories in 2015 4.88680.1803
Normal weight2986 (44.68)1709 (44.91)1277 (44.37)
Obesity968 (14.48)571 (15.01)397 (13.79)
Overweight2454 (36.72)1382 (36.32)1072 (37.25)
Underweight275 (4.11)143 (3.76)132 (4.59)
Residence 53.6550<0.0001
Rural4563 (61.38)2428 (57.75)2135 (66.10)
Urban2871 (38.62)1776 (42.25)1095 (33.90)
Province 229.9176<0.0001
Beijing702 (9.44)413 (9.82)289 (8.95)
Chongqing548 (7.37)240 (5.71)308 (9.54)
Guangxi606 (8.15)293 (6.97)313 (9.69)
Guizhou613 (8.25)296 (7.04)317 (9.81)
Heilongjiang518 (6.97)294 (6.99)224 (6.93)
Henan602 (8.1)316 (7.52)286 (8.85)
Hubei610 (8.21)314 (7.47)296 (9.16)
Hunan561 (7.55)304 (7.23)257 (7.96)
Jiangsu759 (10.21)493 (11.73)266 (8.24)
Liaoning608 (8.18)460 (10.94)148 (4.58)
Shandong569 (7.65)292 (6.95)277 (8.58)
Shanghai738 (9.93)489 (11.63)249 (7.71)
Urbanization index in 201173.84 (54.55–88.93)77.18 (56.16–89.77)68.92 (53.08–87.88)−8.0879<0.0001
Weight in 2011, kg61.40 (54.50–70.00)62.25 (55.00–70.20)60.40 (53.50–68.60)−6.4470<0.0001
Height in 2011, cm161.00 (155.50–167.80)162.00 (156.00–168.00)160.00 (154.90–166.60)−7.0626<0.0001
WC in 2011, cm84.00 (77.00–91.10)84.50 (77.00–91.70)83.20 (76.50–90.60)−3.16370.0016
Urbanization index in 201577.08 (60.12–87.60)79.74 (61.02–88.55)73.57 (57.97–86.98)−7.9719<0.0001
Weight in 2015, kg62.30 (55.00–70.40)62.90 (55.70–71.00)61.60 (54.20–69.80)−4.8665<0.0001
Height in 2015, cm160.70 (155.00–167.10)161.50 (155.80–168.00)160.00 (154.00–166.00)−6.5127<0.0001
WC in 2015, cm85.00 (78.00–92.50)85.60 (78.50–93.00)85.00 (77.35–92.00)−2.76710.0057
Cumulative average dietary intake
Energy, kcal/day1835.11 (1407.41–2359.90)1841.62 (1407.83–2385.35)1820.19 (1407.40–2329.92)−1.00280.3159
Protein, g/day63.04 (46.23–84.70)63.99 (46.85–86.02)61.62 (45.56–82.87)−3.70500.0002
Carbohydrate, g/day255.30 (184.39–342.15)255.12 (181.50–340.87)255.91 (186.87–344.86)1.28330.1994
Fat, g/day58.90 (35.97–87.89)59.85 (37.24–89.23)58.05 (34.05–86.01)−2.96580.0030
Calcium, mg/day363.27 (241.08–539.65)376.55 (248.32–561.32)345.63 (232.72–512.31)−5.4703<0.0001
Sodium, mg/day3761.39 (2655.46–5272.83)3781.94 (2662.10–5307.16)3740.80 (2648.67–5230.20)−0.60630.5443
Note: BMI, body mass index; WC, waist circumference. Continuous variables are expressed as median (quartile). Categorical variables are expressed as numbers (percentages).
Table 2. Dietary diversity and psychological stress level n (%).
Table 2. Dietary diversity and psychological stress level n (%).
VariablesLower Psychological Stress GroupHigher Psychological Stress GroupZp
Dietary diversity
(Number of DQQ food groups)
7.1100<0.0001
251 (1.21)68 (2.11)
3268 (6.37)290 (8.98)
4580 (13.80)534 (16.53)
5822 (19.55)650 (20.12)
6924 (21.98)658 (20.37)
7722 (17.17)516 (15.98)
8430 (10.23)286 (8.85)
9242 (5.76)130 (4.02)
≥10165 (3.92)98 (3.03)
1086 (2.05)63 (1.95)
1151 (1.21)23 (0.71)
1220 (0.48)10 (0.31)
137 (0.17)2 (0.06)
141 (0.02)0 (0.00)
Table 3. Associations of dietary diversity with psychological stress.
Table 3. Associations of dietary diversity with psychological stress.
ParameterdfEstimateStandard ErrorWald ϰ2pOR95%CI
Intercept10.93430.295010.02870.0015
BMI categories in 2015
Normal weightRef
Obesity1−0.06790.07570.80350.37010.9340.806, 1.084
Overweight10.05860.05551.11280.29151.0600.951, 1.182
Underweight10.17690.12741.92800.16501.1940.930, 1.532
Gender
FemaleRef
Male1−0.15790.05079.69830.00180.8540.773, 0.943
Marital status in 2015
Never marriedRef
Married1−0.13360.17840.56040.45410.8750.617, 1.241
Divorced/Separated/Widowed10.0004630.20440.00000.99821.0000.670, 1.493
Age10.0007270.002010.13140.71701.0010.997, 1.005
Urbanization index1−0.008360.0016027.3869<0.00010.9920.989, 0.995
Dietary diversity
(Number of DQQ food groups)
≤2Ref
31−0.21180.22510.88500.34680.8090.521, 1.258
41−0.39430.21553.34690.06730.6740.442, 1.029
51−0.45870.21434.58140.03230.6320.415, 0.962
61−0.53500.21496.19440.01280.5860.384, 0.893
71−0.50360.21705.38900.02030.6040.395, 0.925
81−0.48990.22414.77680.02880.6130.395, 0.951
91−0.73310.24049.30100.00230.4800.300, 0.770
≥101−0.68580.25137.44840.00630.5040.308, 0.824
Note: 761 observations were deleted due to missing values for the explanatory variables.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

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, 3297. https://doi.org/10.3390/nu14163297

AMA Style

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(16):3297. https://doi.org/10.3390/nu14163297

Chicago/Turabian Style

Zhou, Jia, Huan Wang, and Zhiyong Zou. 2022. "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 14, no. 16: 3297. https://doi.org/10.3390/nu14163297

APA Style

Zhou, J., Wang, H., & Zou, Z. (2022). 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, 14(16), 3297. https://doi.org/10.3390/nu14163297

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop