Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Plant-based dietary patterns in relation to mortality among older adults in China

Nature Aging volume 2, pages 224–230 (2022)Cite this article

Subjects

Abstract

A plant-based dietary pattern has been recommended for its potential health and environmental benefits, but its relation to mortality warrants further exploration1. We examined this association among 13,154 adults aged 65 years and older (57.4% female) in the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The overall plant-based diet index (PDI), healthful plant-based diet index (hPDI) and unhealthful plant-based diet index (uPDI) were calculated using dietary data collected by a simplified food frequency questionnaire (FFQ). Compared with the lowest quintile, participants in the highest quintile of PDI and hPDI had a decreased risk of all-cause mortality (hazard ratio (HR) = 0.92; 95% confidence interval (CI) 0.86, 0.98 for PDI; HR = 0.81, 95% CI, 0.76, 0.87 for hPDI), whereas participants with the highest uPDI scores had a 17% (95% CI, 9%, 26%) increased risk. Among plant foods, fresh fruits, fresh vegetables, legumes, garlic, nuts and tea were the main protective contributors, whereas preserved vegetables and sugar were associated with a higher risk of mortality. These findings support the beneficial roles of overall and healthful plant-based dietary patterns. The quality, and not only quantity, of plant foods should be emphasized in relevant public health recommendations.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: HRs and 95% CIs for all-cause mortality, according to continuous plant-based diet indices (n = 13,154).
Fig. 2: HRs and 95% CI for all-cause mortality per 10-unit increment in adherence to plant-based diet indices, stratified by selected characteristics (n = 13,154).

Similar content being viewed by others

Data availability

Data described in this paper are stored in the Peking University Open Research Data Platform, a public data repository (https://opendata.pku.edu.cn/dataset.xhtml?persistentId=doi:10.18170/DVN/WBO7LK).

Code availability

The code scripts used in this analysis are available from the corresponding authors upon reasonable request.

References

  1. Soultoukis, G. A. & Partridge, L. Dietary protein, metabolism, and aging. Annu. Rev. Biochem. 85, 5–34 (2016).

    Article  CAS  PubMed  Google Scholar 

  2. GBD 2019 Risk Factors Collaborators Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1223–1249 (2020).

    Article  Google Scholar 

  3. English, L. K. et al. Evaluation of dietary patterns and all-cause mortality: a systematic review. JAMA Netw. Open 4, e2122277 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Schulze, M. B., Martínez-González, M. A., Fung, T. T., Lichtenstein, A. H. & Forouhi, N. G. Food based dietary patterns and chronic disease prevention. BMJ 361, k2396 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sofi, F., Cesari, F., Abbate, R., Gensini, G. F. & Casini, A. Adherence to Mediterranean diet and health status: meta-analysis. BMJ 337, a1344 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Kheirouri, S. & Alizadeh, M. MIND diet and cognitive performance in older adults: a systematic review. Crit. Rev. Food Sci. Nutr. 14, 1–19 (2021).

    Google Scholar 

  7. Sacks, F. M. et al. Effects on blood pressure of reduced dietary sodium and the dietary approaches to stop hypertension (DASH) diet. DASH-Sodium Collaborative Research Group. N. Engl. J. Med. 344, 3–10 (2001).

    Article  CAS  PubMed  Google Scholar 

  8. Hemler, E. C. & Hu, F. B. Plant-based diets for personal, population, and planetary health. Adv. Nutr. 10, S275–S283 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hall, K. D. et al. Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake. Nat. Med. 27, 344–353 (2021).

    Article  CAS  PubMed  Google Scholar 

  10. Baden, M. Y. et al. Changes in plant-based diet quality and total and cause-specific mortality. Circulation 140, 979–991 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Satija, A. et al. Changes in intake of plant-based diets and weight change: results from 3 prospective cohort studies. Am. J. Clin. Nutr. 110, 574–582 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Satija, A. et al. Plant-based dietary patterns and incidence of type 2 diabetes in US men and women: results from three prospective cohort studies. PLoS Med. 13, e1002039 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Satija, A. et al. Healthful and unhealthful plant-based diets and the risk of coronary heart disease in U.S. adults. J. Am. Coll. Cardiol. 70, 411–422 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Kim, H. et al. Operational differences in plant-based diet indices affect the ability to detect associations with incident hypertension in middle-aged US adults. J. Nutr. 150, 842–850 (2020).

    Article  PubMed  Google Scholar 

  15. Keaver, L. et al. Plant- and animal-based diet quality and mortality among US adults: a cohort study. Br. J. Nutr. 125, 1405–1415 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Kim, H. et al. Plant-based diets are associated with a lower risk of incident cardiovascular disease, cardiovascular disease mortality, and all-cause mortality in a general population of middle-aged adults. J. Am. Heart Assoc. 8, e012865 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kim, H., Caulfield, L. E. & Rebholz, C. M. Healthy plant-based diets are associated with lower risk of all-cause mortality in US adults. J. Nutr. 148, 624–631 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Martínez-González, M. A. et al. A provegetarian food pattern and reduction in total mortality in the Prevención con Dieta Mediterránea (PREDIMED) study. Am. J. Clin. Nutr. 100, 320s–328s (2014).

    Article  PubMed  Google Scholar 

  19. Kim, J., Kim, H. & Giovannucci, E. L. Plant-based diet quality and the risk of total and disease-specific mortality: a population-based prospective study. Clin Nutr 40, 5718–5725 (2021).

    Article  CAS  PubMed  Google Scholar 

  20. Schwingshackl, L. et al. Food groups and risk of all-cause mortality: a systematic review and meta-analysis of prospective studies. Am. J. Clin. Nutr. 105, 1462–1473 (2017).

    CAS  PubMed  Google Scholar 

  21. Aune, D. et al. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. Int. J. Epidemiol. 46, 1029–1056 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Luo, C. et al. Nut consumption and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a systematic review and meta-analysis. Am. J. Clin. Nutr. 100, 256–269 (2014).

    Article  CAS  PubMed  Google Scholar 

  23. Zhang, C. et al. Tea consumption and risk of cardiovascular outcomes and total mortality: a systematic review and meta-analysis of prospective observational studies. Eur J Epidemiol 30, 103–113 (2015).

    Article  CAS  PubMed  Google Scholar 

  24. Ramne, S. et al. Association between added sugar intake and mortality is nonlinear and dependent on sugar source in 2 Swedish population-based prospective cohorts. Am. J. Clin. Nutr. 109, 411–423 (2019).

    Article  PubMed  Google Scholar 

  25. Wang, X. et al. Red and processed meat consumption and mortality: dose-response meta-analysis of prospective cohort studies. Public Health Nutr. 19, 893–905 (2016).

    Article  PubMed  Google Scholar 

  26. Theuma, P. & Fonseca, V. A. Inflammation and emerging risk factors in diabetes mellitus and atherosclerosis. Curr. Diab. Rep. 3, 248–254 (2003).

    Article  PubMed  Google Scholar 

  27. Ma, Y. et al. Association between dietary fiber and markers of systemic inflammation in the Women’s Health Initiative Observational Study. Nutrition 24, 941–949 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cassidy, A. et al. Higher dietary anthocyanin and flavonol intakes are associated with anti-inflammatory effects in a population of US adults. Am. J. Clin. Nutr. 102, 172–181 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Tran, E., Dale, H. F., Jensen, C. & Lied, G. A. Effects of plant-based diets on weight status: a systematic review. Diabetes Metab. Syndr. Obes. 13, 3433–3448 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Najjar, R. S. & Feresin, R. G. Plant-based diets in the reduction of body fat: physiological effects and biochemical insights. Nutrients 11, 2712 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  31. Pearson, T. A. et al. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 107, 499–511 (2003).

    Article  PubMed  Google Scholar 

  32. Soltani, S., Jayedi, A., Shab-Bidar, S., Becerra-Tomás, N. & Salas-Salvadó, J. Adherence to the Mediterranean diet in relation to all-cause mortality: a systematic review and dose-response meta-analysis of prospective cohort studies. Adv. Nutr. 10, 1029–1039 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Akbaraly, T. N. et al. Alternative Healthy Eating Index and mortality over 18 y of follow-up: results from the Whitehall II cohort. Am. J. Clin. Nutr. 94, 247–253 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Mokhtari, Z. et al. Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet and risk of total and cause-specific mortality: results from the Golestan Cohort Study. Int. J. Epidemiol. 48, 1824–1838 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  35. He, Y. et al. The dietary transition and its association with cardiometabolic mortality among Chinese adults, 1982-2012: a cross-sectional population-based study. Lancet Diabetes Endocrinol. 7, 540–548 (2019).

    Article  PubMed  Google Scholar 

  36. Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Pimentel, D. & Pimentel, M. Sustainability of meat-based and plant-based diets and the environment. Am. J. Clin. Nutr. 78, 660s–663s (2003).

    Article  CAS  PubMed  Google Scholar 

  38. Tjonneland, A. et al. Influence of individually estimated portion size data on the validity of a semiquantitative food frequency questionnaire. Int. J. Epidemiol. 21, 770–777 (1992).

    Article  CAS  PubMed  Google Scholar 

  39. Yuan, C., Lee, H. J., Shin, H. J., Stampfer, M. J. & Cho, E. Fruit and vegetable consumption and hypertriglyceridemia: Korean National Health and Nutrition Examination Surveys (KNHANES) 2007-2009. Eur. J. Clin. Nutr. 69, 1193–1199 (2015).

    Article  CAS  PubMed  Google Scholar 

  40. Zeng, Y. in Healthy Longevity in China: Demographic, Aocioeconomic, and Psychological Dimensions. Vol. 20 (eds Y. Zeng, L. P. Dudley, A. V. Denese & G. Danan) 23–38 (Springer, 2008).

  41. Zhao, W., Hasegawa, K. & Chen, J. The use of food-frequency questionnaires for various purposes in China. Public Health Nutr. 5, 829–833 (2002).

    Article  PubMed  Google Scholar 

  42. Jin, X. et al. Association of APOE ε4 genotype and lifestyle with cognitive function among Chinese adults aged 80 years and older: a cross-sectional study. PLoS Med. 18, e1003597 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Zhang, Y. et al. Interaction between APOE ε4 and dietary protein intake on cognitive decline: a longitudinal cohort study. Clin. Nutr. 40, 2716–2725 (2021).

    Article  CAS  PubMed  Google Scholar 

  44. Wang, Z. et al. Association of healthy lifestyle with cognitive function among Chinese older adults. Eur. J. Clin. Nutr. 75, 325–334 (2021).

    Article  PubMed  Google Scholar 

  45. Liu, D. et al. Association of dietary diversity changes and mortality among older people: a prospective cohort study. Clin. Nutr. 40, 2620–2629 (2021).

    Article  PubMed  Google Scholar 

  46. Stockwell, T. et al. Do “moderate” drinkers have reduced mortality risk? A systematic review and meta-analysis of alcohol consumption and all-cause mortality. J. Stud. Alcohol Drugs 77, 185–198 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  47. David, S. Partial residuals for the proportional hazards regression model. Biometrika 69, 239–241 (1982).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by Fundamental Research Funds from the Central Universities of Zhejiang University (X.W. and C. Y.). The collection of the CLHLS datasets analyzed in this paper was jointly supported by the National Key R&D Program of China (2018YFC2000400), the National Natural Sciences Foundation of China (72061137004), the National Institute on Aging of the National Institutes of Health (P01AG031719) and Duke/Duke-NUS (grant RECA(Pilot)/2019/0051 to Y. Z.). The funders had no role in study design, data collection, analysis, decision to publish or manuscript preparation. We are grateful to all cooperating organizations and their staff during the CLHLS, whose hard work made this study possible. We thank the interviewees and their families for their voluntary participation in the CLHLS.

Author information

Author notes

  1. These authors contributed equally: Hui Chen, Jie Shen.

Authors and Affiliations

  1. School of Public Health, Zhejiang University School of Medicine, Hangzhou, China

    Hui Chen, Jie Shen & Changzheng Yuan

  2. China Academy for Rural Development, Department of Agricultural Economics and Management, Zhejiang University, Hangzhou, China

    Jiaqi Xuan & Xiaoxi Wang

  3. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany

    Anna Zhu

  4. Medical Faculty, Heidelberg University, Heidelberg, Germany

    Anna Zhu

  5. Vanke School of Public Health, Tsinghua University, Beijing, China

    John S. Ji

  6. Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, IL, USA

    Xiaoran Liu

  7. CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China

    Yaying Cao & Geng Zong

  8. Center for Healthy Aging and Development Studies, Raissun Institute for Advanced Studies, National School of Development, Peking University, Beijing, China

    Yi Zeng

  9. Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, NC, USA

    Yi Zeng

  10. Potsdam Institute for Climate Impact Research, Potsdam, Germany

    Xiaoxi Wang

  11. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Changzheng Yuan

Authors
  1. Hui Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jie Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiaqi Xuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anna Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. John S. Ji
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiaoran Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yaying Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Geng Zong
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Yi Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Xiaoxi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Changzheng Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

C.Y., J.S.J., X.W., and H.C. designed the analysis; H.C. and A.Z. performed the statistical analyses; J.S., J.X., X.W., and X.L. interpreted the data; J.S. and H.C. drafted the manuscript; X.L., Y.C., X.W. and G.Z. critically reviewed and revised the manuscript; Y.Z. designed and administered the original CLHLS; C.Y. and X.W. supervised the data analysis and interpretation; and C.Y. had primary responsibility for the final content. All authors approved the final draft.

Corresponding authors

Correspondence to Xiaoxi Wang or Changzheng Yuan.

Ethics declarations

Competing interests

The authors have no competing interests.

Peer review

Peer review information

Nature Aging thanks Zhangling Chen, Shankar Viswanathan and Paul Jacques for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 The pairwise Spearman correlation coefficient between different food groups.

Pairwise Spearman correlation coefficients were presented.

Source data

Extended Data Fig. 2 Flow chart of participant inclusion.

Of a total of 16954 participants, 13154 eligible participants were included in the final analysis.

Supplementary information

Source data

Source Data Fig. 1

Source data for Fig. 1.

Source Data Fig. 2

Source data for Fig. 2.

Extended Data Fig. 1

Source data for Extended Data Fig. 1.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, H., Shen, J., Xuan, J. et al. Plant-based dietary patterns in relation to mortality among older adults in China. Nat Aging 2, 224–230 (2022). https://doi.org/10.1038/s43587-022-00180-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43587-022-00180-5

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing