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Mediterranean diet lowers risk of new-onset diabetes: a nationwide cohort study in China

Nutrition Journal volume 23, Article number: 131 (2024) Cite this article

Abstract

Background

The Mediterranean diet (MD) has shown promising results in preventing type 2 diabetes, particularly in Mediterranean and European populations. However, the applicability of these benefits to non-Mediterranean populations is unclear, with contradictory findings in the literature.

Methods

In this study, we included 12,575 participants without diabetes at baseline from the China Health and Nutrition Survey (CHNS). Dietary intake was measured by three consecutive 24-h dietary recalls. The Mediterranean diet adherence (MDA) was measured by a score scale that included nine components of vegetables, legumes, fruits, nuts, cereals, fish, red meat, dairy products, and alcohol. New-onset diabetes was defined as self-reported physician-diagnosed diabetes during the follow-up.

Results

During a median follow-up of 9.0 years, 445 (3.5%) subjects developed diabetes. Overall, there was an inverse association between the MDA score and new-onset diabetes (per score increment, HR 0.83, 95% CI 0.76–0.90). Moreover, age, sex, BMI, and energy intake significantly modified the association between the MDA score and the risk of new-onset diabetes (all P interactions < 0.05). Greater fruit, fish, and nut intake was significantly associated with a lower risk of new-onset diabetes.

Conclusion

There was an inverse association between Mediterranean diet adherence and new-onset diabetes in the Chinese population.

Peer Review reports

Introduction

The global prevalence of type 2 diabetes underscores the critical importance of effective dietary strategies for its prevention and management [1]. Among various dietary patterns, the Mediterranean diet (MD) has emerged as particularly beneficial [2,3,4]. Characterized by a high intake of olive oil, nuts, cereals, fruits, and vegetables; moderate consumption of fish, poultry, and wine; and minimal reliance on red and processed meats, dairy products, and sweets [5, 6], the MD has demonstrated significant preventive effects against diabetes, particularly in Mediterranean and European populations, as evidenced by the PREDIMED study and several prospective cohorts [7,8,9,10,11].

Despite these promising findings, the applicability of the benefits of MD across non-Mediterranean populations remains an open question. In fact, there are contradictions in the current evidence regarding the diabetes benefits of the MD among non-Mediterranean populations. Although certain studies indicate the potential of MD to mitigate diabetes risk [12], a recent cross-sectional analysis revealed no association between MDA and T2D in a non-Mediterranean population [13]. Several studies have indicated that there are racial/ethnic disparities in the association between a Mediterranean diet and incident diabetes [14, 15]. This ambiguity underscores the need to investigate the impact of MD on diverse population groups, including those outside the Mediterranean region. Therefore, we plan to explore the effects of the Mediterranean diet on diabetes in the Chinese population.

Diabetes is one of the most serious chronic diseases in China, with approximately 140.9 million adults having diabetes in 2021 [16, 17]. Accompanied by rapid economic changes, the dietary pattern in China is changing from a high intake of cereals and vegetables and a low intake of animal food to a Western pattern with a high intake of animal foods and other high-energy–density foods [18, 19]. Meanwhile, diabetes prevalence in Chinese adults aged 20–79 years was projected to increase from 8.2% to 9.7% during 2020–2030 [20, 21]. Few studies have assessed the health benefits of the Mediterranean diet in China [22,23,24], and the relationship between MD and the development of diabetes in the general Chinese population is unclear.

In this study, we aimed to investigate (1) the association between MDA and new-onset diabetes, (2) the association between different populations and the risk of developing diabetes, and (3) the association of food components of the Mediterranean diet with diabetes risk in the China Health and Nutrition Survey (CHNS).

Methods

Study design and participants

Details of the study design and some major results of the CHNS have been described elsewhere [25,26,27,28]. Briefly, the CHNS is an ongoing, national, multipurpose, longitudinal, open cohort study initiated in 1989 and has been followed up every 2–4 years. By 2011, the provinces included in the CHNS constituted 47% of China’s population [26]. The present study was based on 6 rounds of CHNS data from 1997 to 2011 (1997, 2000, 2004, 2006, 2009, and 2011), including a total of 82,343 person-waves. We first excluded participants who were pregnant or < 18 years old. Among the remaining participants (including 65,611 person-waves), those with missing diabetes diagnoses (including 3895 person-waves) or with only one survey wave (including 8841 person-waves) were further excluded. Therefore, a cohort based on 13,500 participants (including 52,875 person-waves) with two or more survey waves was identified, and the first survey round was considered as the baseline. Of the 13,500 participants, 213 participants with self-report diabetes at baseline and 712 with extreme dietary energy data (males: > 4200 or < 800 kcal/day; females: > 3600 or < 600 kcal/day) [29] were further excluded. Ultimately, a total of 12,575 participants were included in the final analysis (Fig. 1).

Fig. 1
figure 1

Flow chart of the study participants

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The characteristics of the included (n = 12,575) and excluded (n = 8061) populations are shown in Table S1. The institutional review boards of the University of North Carolina at Chapel Hill, the National Institute of Nutrition and Food Safety, and the Chinese Center for Disease Control and Prevention approved the study. Each participant provided written informed consent. The data and study materials that support the findings of this study can be found on the official CHNS website.

Assessment of the Mediterranean Diet

The dietary intake of each participant was assessed using 24-h recalls for three consecutive days (2 weekdays and 1 weekend day). Researchers at the CHNS recorded the types and amounts of food consumed at each meal during the previous day. Detailed information on the data collection has been reported previously [30, 31]. In the analyses, 3-day average intakes of dietary intake in each round were calculated. Repeated 3-day dietary recalls may reduce the day-to-day variation in dietary intake, and collect more complete food information. Moreover, all values of each nutrient in the analyses, if not specified, were presented as the cumulative averages, using all results from baseline to the last visit or the date of new-onset diabetes, to represent long-term dietary intake status and minimize within-person variation.

We used the MDA score scale proposed by Trichopoulou [24, 32]. This scale includes nine components: vegetables, legumes, fruits, nuts, cereals, fish, meat, dairy products, and alcohol. Values of 0 or 1 were assigned to each of the components, using the sex-specific median values for the participants as cutoffs for all components except for alcohol and dairy. For the six components presumed to be beneficial (vegetables, legumes, fruits, nuts, cereals, and fish), participants whose intake was at or above the sex-specific medians were assigned a value of 1, while those whose intake was below these medians were assigned a value of 0. For meat, a value of 0 was assigned to participants whose intake was above the median, while those whose intake was below the sex-specific median were assigned a value of 1. For alcohol intake, a value of 1 was assigned to men who consumed 10–50 g/day and women who consumed 5–25 g/day. For dairy products, a value of 1 was assigned to those whose daily intake was between 5 and 25 g. The scores of the nine categories were summed. The total range of the MDA score was from 0 to 9. The MDA score was calculated for all individuals upon recruitment. MDA was categorized into three levels, below the median (score 0–3), median (score 4), or above the median (score 5–9) [33], using the low level as the reference level.

Assessment of other covariates

Information on age, sex, body mass index (BMI), urban or rural residence, region, education level, occupation, income, physical activity, smoking status and cumulative average total energy intake was obtained from the questionnaires at each follow-up survey. Height and weight were measured following a standard procedure with calibrated equipment. BMI was calculated as weight (kg) by height squared (m2). The level of physical activity was the product of the self-reported time spent in each activity multiplied by specific metabolic equivalent (MET) values [34]. For all the nondietary covariates, we used the baseline year measurements. The cumulative average total energy intake was calculated using 3-day average intakes of dietary intake in each round.

Study outcome

Diabetes status was identified by a questionnaire-based interview at each follow-up. In the physical examination questionnaire, two questions were used to collect diabetes diagnosis data: (a) Has the doctor ever told you that you suffer from diabetes? If yes, (b) did you use any of the following treatment methods? (1) special diet, (2) weight control, (3) oral medicine, (4) injection of insulin, (5) Chinese traditional medicine, (6) home remedies, and (7) Qi Gong (Spiritual). The participants who answered yes to the question “a” were classified as diabetes cases in the primary analysis. In CHNS, data of blood glucose and HbA1c were only available in the wave of 2009. To test the reliability of self-reported diagnosis, we used two more criteria defining diabetes cases in sensitivity analysis, which were (1) self-reported cases based on the question “a” and cases identified based on blood glucose and HbA1c (fasting blood glucose ≥ 7.0 mmol/L or HbA1c ≥ 6.5%) in the wave of 2009, and 2) cases using oral hypoglycemic medicine or insulin injection based on question “b” [35].

Statistical analysis

The population characteristics are presented as the means ± standard deviations (SDs) or medians (IQRs) for continuous variables and proportions for categorical variables. Differences in population characteristics by MDA scores were compared using one-way ANOVA tests, Kruskal–Wallis test, or chi-square tests, accordingly.

The year of each participant’s first entry into the survey was considered as a baseline. The follow-up person-time for each participant was calculated from baseline until the first new-onset diabetes diagnosis, the last survey round before the participant departed from the survey, or the end of the latest survey (2011), whichever came first. Participants were censored on the date of the last survey round before the participant departed from the survey or the end of the latest survey. The incidence rates of new-onset diabetes, expressed as person-years, were calculated as the sum of follow-up years for participants.

Variables that are known to be traditional or suspected risk factors for diabetes or variables that showed significant differences among different MDA score levels were chosen as the covariates in the adjusted models. The relationships between the MDA score and new-onset diabetes were estimated using Cox proportional hazards models. Model 1 included adjustments for age and sex. Model 2 included the adjustments in Model 1 plus BMI, occupation, education level, region, smoking status, urban or rural residence, income, physical activity (low, moderate, high) at baseline, and cumulative average total energy intake. We also used restricted cubic splines (RCS) with 3 knots to explore the potentially non-linear relationship of MDA score with new-onset diabetes with adjustments in Model 2. Moreover, possible modifications of the association between MDA score and new-onset diabetes were evaluated by stratified analyses and interaction testing. Those with missing values of covariates were excluded from the main analysis. A series of sensitivity analyses were conducted to test the robustness of our findings, such as (1) both self-reported cases and cases diagnosed by blood glucose and HbA1c in the wave of 2009 were defined as diabetes cases, (2) only cases taking oral hypoglycemic medicines or insulin injection were defined as diabetes cases, (3) multiple imputations were also used to handle missing covariates.

A two-sided P value < 0.05 was considered to indicate statistical significance in all analyses. All the statistical analyses were conducted using Stata 17 and R version 3.6.3.

Results

Characteristics of the study population

As demonstrated in Table S1, the final analysis cohort included a total of 12,575 participants. The mean age of the participants was 42.5 (15.2) years, and 51.4% were females. The mean MDA score of the participants was 2.9 (1.3), and they were categorized into below-median (MDA scores 0–3), median (MDA scores 4), and above-median (MDA scores 5–9) groups based on their MDA scores. Table 1 suggests that participants within the above median MD (scores 5–9) were more likely to be younger, to be farmers, less likely to live in urban and southern regions, and had a higher BMI, physical activity levels, and energy intake, as well as lower educational levels.

Table 1 Baseline population characteristics in different Mediterranean diet score groups
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Relationships between the MDA score and new-onset diabetes

Among the 12,575 participants included, during a median follow-up duration of 9.0 years (interquartile range: 5 to 14 years), 445 participants (3.5%) developed new-onset diabetes. Overall, there was an inverse association between the MDA score and new-onset diabetes (per score increment, Model 2 HR 0.83, 95% CI 0.76–0.90) (Fig. 2, Table 2). Accordingly, when the MDA score was assessed by quartile, compared with those in the first quartile (< 3), a significantly lower risk of new-onset diabetes was found in participants in quartiles 2–4 (Q2: Model 2 HR 0.69, 95% CI 0.54–0.89; Q3: Model 2 HR 0.65, 95% CI 0.50–0.86; Q4: Model 2 HR 0.48, 95% CI 0.34–0.69; P for trend < 0.001) (Table 2). In addition, Cox regression analysis revealed that a higher MDA score (median and above median) was significantly associated with a risk of new-onset diabetes (Table 2). High MDA was still associated with a reduced risk of new-onset diabetes after the exclusion of early new-onset diabetes that occurred within the first 2 years after enrollment (Table S2). Sensitivity analyses using different criteria for diabetes case identification and multiple imputations to handle missing covariates showed consistent findings, underscoring the reliability of our findings (Table S3).

Table 2 The association between MDA and new-onset diabetes
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Fig. 2
figure 2

The association between the MDA score and new-onset diabetes. Adjusted for age, sex, BMI, occupation, education level, region, smoking status, urban or rural residence status, income, physical activity (low, moderate, high) at baseline, and cumulative average total energy intake. Overall P = 0.0002; Nonlinearity P = 0.9096

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Subgroup analysis

We included interaction terms for the MDA score and age, sex, BMI, and energy intake in our models (Table S4). The results indicated that age, sex, BMI, and energy intake significantly modified the association between the MDA score and the risk of new-onset diabetes (all P interactions < 0.05). Therefore, we conducted a stratified analysis to explore the association between median MDA score and new-onset diabetes in different subgroups. The results revealed that the association between median MDA score and new-onset diabetes remained statistically significant only among people with BMI < 24 kg/m2 (Model 2 HR 0.63, 95% CI,0.41–0.98) and energy intake < 2220 kcal/day (Model 2 HR 0.60, 95% CI 0.41–0.87), while the association between above median MDA score and new-onset diabetes was not statistically significant among women (Model 2 HR 0.62, 95% CI 0.38–1.01) and energy intake ≥ 2220 kcal/day (Model 2 HR 0.68, 95% CI 0.42–1.08). Furthermore, we also used restricted cubic splines (RCS) with 3 knots to explore the potentially non-linear relationship of MDA score with new-onset diabetes in different subgroups. Overall, there was no non-linear relationship between MDA score with new-onset diabetes in all subgroups (All non-linearity P > 0.05). Notably, an inverse association between the MDA score and new-onset diabetes was observed in all subgroups (Fig. 3).

Fig. 3
figure 3

The association between the MDA score and new-onset diabetes in different subgroups. Adjusted for age, sex, BMI, occupation, education level, region, smoking status, urban or rural residence status, income, physical activity (low, moderate, high) at baseline, and cumulative average total energy intake. a Male: overall P = 0.0076; nonlinearity P = 0.3544; b female: overall P = 0.0170; nonlinearity P = 0.3528; c age < 60: overall P = 0.0107; nonlinearity P = 0.8596; d age ≥ 60: overall P = 0.0115; nonlinearity P = 0.7829; d BMI < 24 kg/m2: overall P = 0.0047; nonlinearity P = 0.3841; d BMI ≥ 24 kg/m.2: overall P = 0.0160; nonlinearity P = 0.1940; g energy intake < 2220 kcal/d: overall P = 0.0183; nonlinearity P = 0.3235; d energy ≥ 2220 kcal/d: overall P = 0.0023; nonlinearity P = 0.2545

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Associations of individual food components of the Mediterranean diet with new-onset diabetes

To examine in depth the association between Mediterranean diet components and new-onset diabetes, Cox regression analysis was utilized. Among the components of the MED diet, greater fruit, fish, and nut intake was significantly associated with a lower risk of new-onset diabetes after adjustment for age, sex, BMI, occupation, education level, region, smoking status, urban or rural residence, income, physical activity (low, moderate, high) at baseline, and cumulative average total energy intake. (Fig. 4).

Fig. 4
figure 4

Forest plot of Cox regression analysis of Mediterranean diet components and new-onset diabetes

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Discussion

Our findings suggested an inverse association between the Mediterranean diet score and the risk of new-onset diabetes in the general Chinese population. Additionally, our results indicated that age, sex, BMI, and energy intake significantly modify the association between the MDA score and the risk of new-onset diabetes. An inverse association between the MDA score and new-onset diabetes was observed in all subgroups, but the association between above-median MDA score and new-onset diabetes was not statistically significant among women. Among the components of the MDA diet, greater fruit, fish, and nut intake was significantly associated with a lower risk of new-onset diabetes.

Our study utilized the CHNS database, a large-scale national cohort covering multiple provinces and cities in China, to confirm and explore the relationship between MDA and diabetes risk in the Chinese population. The Mediterranean diet, a healthy eating pattern, has been proven to be associated with a reduced risk of diabetes [10]. However, most studies assessing the health benefits of the Mediterranean diet have been conducted in Mediterranean countries [7, 8], with few focusing on the Chinese population. Research in the Singaporean Chinese population suggests that the Mediterranean diet can lower diabetes risk [12], but due to dietary variations resulting from geographical and social environmental differences [36], it is debatable whether these findings can be generalized to the mainland Chinese population. The metabolic benefits of the Mediterranean diet in mainland China are also controversial. An RCT showed that an energy-restricted Mediterranean diet could reduce weight and improve glycemic control in adults with prediabetes [22]. There are also studies indicating that greater MDA in Chinese adults is associated with protective correlations with bone mineral density (BMD) [23] and hypertension [24]. However, a multiethnic case‒control study revealed no association between the first acute myocardial infarction (FAMI) Mediterranean diet score and the incidence of ST-elevation myocardial infarction (STEMI) in the Chinese population [37]. In a cross-sectional study targeting the suburban population of Shanghai, no significant correlation was detected between MD and metabolic syndrome (MetS) [38]. Therefore, our study, using a large Chinese prospective cohort, confirmed that the Mediterranean diet could reduce the risk of diabetes in the Chinese population and has greater significance for the prevention of diabetes.

We found that although an inverse relationship between MDA scores and the incidence of new-onset diabetes was observed in both men and women, in women, MDA scores above the median did not show a significant association with new-onset diabetes. This suggests potential sex-specific responses to the Mediterranean diet intervention in the Chinese population. Similar phenomena have also been observed in studies from other countries. Research indicates that, compared to a Mediterranean diet, a Mediterranean diet has more favorable effects on men’s weight [39], waist circumference [39, 40], glucose-insulin balance [41, 42], TAG levels, and high-density lipoprotein cholesterol [39, 40]. Moreover, adherence to the Mediterranean diet leads to a significant decrease in adiponectin concentration [43] and a more favorable redistribution of LDL subclasses from smaller to larger LDL in men only [44]. Our findings, highlighting the interplay between diet and sex-specific responses, may help personalize dietary interventions and contribute to overall health and well-being.

Our study revealed that greater fruit, fish, and nut intake was significantly associated with a lower risk of new-onset diabetes. Fruits are rich in fiber and antioxidants and may prevent type 2 diabetes by reducing the risk of weight gain and improving insulin sensitivity [45,46,47,48]. Nuts and seeds, which are recommended daily snacks in the Mediterranean diet, reduce oxidative stress and improve vascular endothelial function [45, 49], thereby improving the lipid profile and reducing insulin resistance [50]. The ability of unsaturated fatty acids such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) to prevent diabetes in fish may be due to improvements in insulin function [51, 52]. Considering the relative lack of intake of these foods in the Chinese population, our findings could help to promote the use of such foods, thereby reducing the risk of diabetes.

Our study involved a relatively large-scale, nationally prospective cohort of the Chinese general population. Repeated measurements of 3 days of 24-h recall data were used to represent long-term dietary intake status and minimize within-person variation, and adjustments were made for a comprehensive range of covariates and multiple sensitivity analyses and subgroup analyses to ensure the robustness of the study findings. However, some limitations need to be mentioned. First, diabetes cases were self-reported in the CHNS, which may underestimate diabetes incidence. Although two sensitivity analyses using different diagnostic criteria for diabetes showed consistent findings, the bias caused by self-reported diabetes cannot be ignored. Second, compared with excluded individuals, those included in the current study (Table S1) seemed to have greater physical activity and energy intake, lower education levels, greater likelihood of being current smokers, and lived in urban areas. Although we fully adjusted for these potential covariates and did not find any significant modification effects, unmeasured and residual confounding factors remain possible. Third, information about the family history of diabetes was unavailable in the CHNS; therefore, we could not examine whether the history of diabetes may have affected our findings. Overall, further studies are still needed to confirm these results.

Conclusion

In summary, this study demonstrates that there is an inverse association between adherence to the Mediterranean diet and new-onset diabetes in general Chinese adults. If further confirmed, these findings are beneficial for promoting the prevalence of the Mediterranean diet in the Chinese population and have the potential to identify populations better suited to the Mediterranean diet, enabling personalized nutritional support and contributing to the primary prevention of diabetes mellitus.

Data availability

No datasets were generated or analysed during the current study.

References

  1. Ley SH, et al. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. Lancet. 2014;383(9933):1999–2007.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Galbete C, et al. Evaluating Mediterranean diet and risk of chronic disease in cohort studies: an umbrella review of meta-analyses. Eur J Epidemiol. 2018;33(10):909–31.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Salas-Salvadó J, et al. Protective Effects of the Mediterranean Diet on Type 2 Diabetes and Metabolic Syndrome. J Nutr. 2015;146(4):920s–7s.

    Article  PubMed  Google Scholar 

  4. Grosso G, et al. A comprehensive meta-analysis on evidence of Mediterranean diet and cardiovascular disease: Are individual components equal? Crit Rev Food Sci Nutr. 2017;57(15):3218–32.

    Article  PubMed  Google Scholar 

  5. Gadgil MD, et al. The effects of carbohydrate, unsaturated fat, and protein intake on measures of insulin sensitivity: results from the OmniHeart trial. Diabetes Care. 2013;36(5):1132–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Imamura F, et al. Effects of Saturated Fat, Polyunsaturated Fat, Monounsaturated Fat, and Carbohydrate on Glucose-Insulin Homeostasis: A Systematic Review and Meta-analysis of Randomised Controlled Feeding Trials. PLoS Med. 2016;13(7):e1002087.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Salas-Salvadó J, et al. Reduction in the incidence of type 2 diabetes with the Mediterranean diet: results of the PREDIMED-Reus nutrition intervention randomized trial. Diabet Care. 2011;34(1):14–9.

    Article  Google Scholar 

  8. Salas-Salvadó J, et al. Prevention of diabetes with Mediterranean diets: a subgroup analysis of a randomized trial. Ann Intern Med. 2014;160(1):1–10.

    Article  PubMed  Google Scholar 

  9. Martínez-González MA, et al. Benefits of the Mediterranean Diet: Insights From the PREDIMED Study. Prog Cardiovasc Dis. 2015;58(1):50–60.

    Article  PubMed  Google Scholar 

  10. Koloverou E, et al. The effect of Mediterranean diet on the development of type 2 diabetes mellitus: a meta-analysis of 10 prospective studies and 136,846 participants. Metab. 2014;63(7):903–11.

    Article  CAS  Google Scholar 

  11. Esposito K, et al. Which diet for prevention of type 2 diabetes? A meta-analysis of prospective studies.  Endocrine. 2014;47(1):107–16.

    Article  CAS  PubMed  Google Scholar 

  12. Chen GC, et al. Diet Quality Indices and Risk of Type 2 Diabetes Mellitus: The Singapore Chinese Health Study. Am J Epidemiol. 2018;187(12):2651–61.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bossel A, et al. Association between Mediterranean Diet and Type 2 Diabetes: Multiple Cross-Sectional Analyses. Nutr. 2023;15(13):3025.

  14. Qiao Y, et al. Racial/ethnic disparities in association between dietary quality and incident diabetes in postmenopausal women in the United States: the Women’s Health Initiative 1993–2005. Ethn Health. 2014;19(3):328–47.

    Article  PubMed  Google Scholar 

  15. Sotos-Prieto M, Mattei J. Mediterranean Diet and Cardiometabolic Diseases in Racial/Ethnic Minority Populations in the United States. Nutr. 2018;10(3):352.

  16. Li Y, et al. Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study. BMJ. 2020;369: m997.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sun H, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.

    Article  PubMed  Google Scholar 

  18. Zhai F, et al. Prospective study on nutrition transition in China. Nutr Rev. 2009;67(Suppl 1):S56-61.

    Article  PubMed  Google Scholar 

  19. Xu X, et al. Evaluation of older Chinese people’s macronutrient intake status: results from the China Health and Nutrition Survey. Br J Nutr. 2015;113(1):159–71.

    Article  CAS  PubMed  Google Scholar 

  20. [Clinical guidelines for prevention and treatment of type 2 diabetes mellitus in the elderly in China (2022 edition)]. Zhonghua Nei Ke Za Zhi, 2022. 61(1): p. 12–50.

  21. Liu J, et al. Projected rapid growth in diabetes disease burden and economic burden in China: a spatio-temporal study from 2020 to 2030. Lancet Reg Health West Pac. 2023;33:100700.

    PubMed  PubMed Central  Google Scholar 

  22. Luo Y, et al. Isocaloric-restricted Mediterranean Diet and Chinese Diets High or Low in Plants in Adults With Prediabetes. J Clin Endocrinol Metab. 2022;107(8):2216–27.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Chen GD, et al. Adherence to the Mediterranean diet is associated with a higher BMD in middle-aged and elderly Chinese. Sci Rep. 2016;6:25662.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gao M, et al. Trajectories of Mediterranean Diet Adherence and Risk of Hypertension in China: Results from the CHNS Study, 1997-2011. Nutr. 2018;10(12):2014.

  25. Popkin BM, et al. Cohort Profile: The China Health and Nutrition Survey–monitoring and understanding socio-economic and health change in China, 1989–2011. Int J Epidemiol. 2010;39(6):1435–40.

    Article  PubMed  Google Scholar 

  26. Zhang B, et al. The China Health and Nutrition Survey. Obes Rev. 2014;15 Suppl 1(01):2–7.

    Article  CAS  PubMed  Google Scholar 

  27. Liu M, et al. Inverse Association Between Riboflavin Intake and New-Onset Hypertension: A Nationwide Cohort Study in China. Hypertension. 2020;76(6):1709–16.

    Article  CAS  PubMed  Google Scholar 

  28. Yuan S, et al. Egg, cholesterol and protein intake and incident type 2 diabetes mellitus: Results of repeated measurements from a prospective cohort study. Clin Nutr. 2021;40(6):4180–6.

    Article  CAS  PubMed  Google Scholar 

  29. Seidelmann SB, et al. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet Public Health. 2018;3(9):e419–28.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Xu X, et al. Dietary Pattern Is Associated with Obesity in Older People in China: Data from China Health and Nutrition Survey (CHNS). Nutrients. 2015;7(9):8170–88.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Wang Z, et al. Sociodemographic disparity in the diet quality transition among Chinese adults from 1991 to 2011. Eur J Clin Nutr. 2017;71(4):486–93.

    Article  CAS  PubMed  Google Scholar 

  32. Trichopoulou A, et al. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003;348(26):2599–608.

    Article  PubMed  Google Scholar 

  33. Fan H, et al. Mediterranean diet lowers all-cause and cardiovascular mortality for patients with metabolic syndrome. Diabetol Metab Syndr. 2023;15(1):107.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Ainsworth BE, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9 Suppl):S498-504.

    Article  CAS  PubMed  Google Scholar 

  35. Li J, et al. Prenatal exposure to famine and the development of diabetes later in life: an age-period-cohort analysis of the China health and nutrition survey (CHNS) from 1997 to 2015. Eur J Nutr. 2023;62(2):941–50.

    PubMed  Google Scholar 

  36. Woo J, et al. The Mediterranean score of dietary habits in Chinese populations in four different geographical areas. Eur J Clin Nutr. 2001;55(3):215–20.

    Article  CAS  PubMed  Google Scholar 

  37. Scarano P, et al. Effect of adherence to Mediterranean diet on first ST-elevation myocardial infarction: Insights from multiethnic case-control study. Nutrition. 2019;65:185–90.

    Article  PubMed  Google Scholar 

  38. Wei L, et al. The Effect of Dietary Pattern on Metabolic Syndrome in a Suburban Population in Shanghai, China. Nutr. 2023;15(9):2185.

  39. Soldevila-Domenech N, et al. Sex differences in endocannabinoids during 3 years of Mediterranean diet intervention: Association with insulin resistance and weight loss in a population with metabolic syndrome. Front Nutr. 2022;9:1076677.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Leblanc V, et al. Gender differences in the long-term effects of a nutritional intervention program promoting the Mediterranean diet: changes in dietary intakes, eating behaviors, anthropometric and metabolic variables. Nutr J. 2014;13:107.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Bédard A, et al. Sex-related differences in the effects of the mediterranean diet on glucose and insulin homeostasis. J Nutr Metab. 2014;2014:424130.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Bédard A, et al. Sex differences in the impact of the Mediterranean diet on cardiovascular risk profile. Br J Nutr. 2012;108(8):1428–34.

    Article  PubMed  Google Scholar 

  43. Bédard A, et al. Effects of the traditional Mediterranean diet on adiponectin and leptin concentrations in men and premenopausal women: do sex differences exist? Eur J Clin Nutr. 2014;68(5):561–6.

    Article  PubMed  Google Scholar 

  44. Bédard A, et al. Sex Differences in the Impact of the Mediterranean Diet on LDL Particle Size Distribution and Oxidation. Nutrients. 2015;7(5):3705–23.

    Article  PubMed  PubMed Central  Google Scholar 

  45. D'Alessandro A, Lampignano L, De Pergola G. Mediterranean Diet Pyramid: A Proposal for Italian People. A Systematic Review of Prospective Studies to Derive Serving Sizes. Nutr. 2019;11(6):1296.

  46. Li M, et al. Fruit and vegetable intake and risk of type 2 diabetes mellitus: meta-analysis of prospective cohort studies. BMJ Open. 2014;4(11):e005497.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Wu Y, et al. Fruit and vegetable consumption and risk of type 2 diabetes mellitus: a dose-response meta-analysis of prospective cohort studies. Nutr Metab Cardiovasc Dis. 2015;25(2):140–7.

    Article  CAS  PubMed  Google Scholar 

  48. Li S, et al. Fruit intake decreases risk of incident type 2 diabetes: an updated meta-analysis. Endocrine. 2015;48(2):454–60.

    Article  PubMed  Google Scholar 

  49. Violi F, et al. Extra virgin olive oil use is associated with improved post-prandial blood glucose and LDL cholesterol in healthy subjects. Nutr Diabetes. 2015;5(7):e172.

  50. de Souza RGM, et al. Nuts and Human Health Outcomes: A Systematic Review. Nutrients, 2017;9(12).

  51. Zheng JS, et al. Effects of n-3 fatty acid supplements on glycemic traits in Chinese type 2 diabetic patients: A double-blind randomized controlled trial. Mol Nutr Food Res. 2016;60(10):2176–84.

    Article  CAS  PubMed  Google Scholar 

  52. Sinha S, et al. The Effect of Omega-3 Fatty Acids on Insulin Resistance. Life (Basel). 2023;13(6):1322.

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Funding

This research was supported by grants from the Shanghai Qingpu District Health Commission (No. QWJ2022-01) and the Qingpu Branch of Zhongshan Hospital (QY2023-10).

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Author notes

  1. Zhen Ying and Minjie Fu contributed equally to this work.

Authors and Affiliations

  1. Zhongshan Hospital, Fudan University, Shanghai, 200032, China

    Zhen Ying

  2. Huashan Hospital, Fudan University, Shanghai, 200032, China

    Zhen Ying & Minjie Fu

  3. People’s Hospital of Putuo, Zhoushan, 316000, China

    Zezhou Fang

  4. Department of Endocrinology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, 201700, China

    Xiaomei Ye, Ping Wang & Jiaping Lu

Authors
  1. Zhen Ying
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  2. Minjie Fu
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  3. Zezhou Fang
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  4. Xiaomei Ye
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  5. Ping Wang
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  6. Jiaping Lu
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Contributions

ZY, MF and JL designed the research. FZ, PW, and YX provided data analysis support. ZY and MF wrote the manuscript and revised the paper. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Zhen Ying, Ping Wang or Jiaping Lu.

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The institutional review boards of the University of North Carolina at Chapel Hill, the National Institute of Nutrition and Food Safety, and the Chinese Center for Disease Control and Prevention approved the study. Each participant provided written informed consent.

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The authors declare no competing interests.

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Ying, Z., Fu, M., Fang, Z. et al. Mediterranean diet lowers risk of new-onset diabetes: a nationwide cohort study in China. Nutr J 23, 131 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12937-024-01036-x

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12937-024-01036-x

Keywords

Nutrition Journal

ISSN: 1475-2891

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