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Dietary patterns and intrinsic capacity among community-dwelling older adults: a 3-year prospective cohort study

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Abstract

Purpose

The WHO has proposed a novel model of healthy aging called intrinsic capacity (IC). However, the association between dietary patterns and IC is unclear. We aimed to investigate the prospective associations between dietary patterns and IC trajectories over a 3-year period in community-dwelling Japanese adults aged ≥ 60 years.

Methods

A prospective cohort study which contained nutritional status, mental status, and physical function was used. A validated 34-item food frequency questionnaire was used to determine dietary intake and to derive five dietary patterns (“fruits and vegetables”, “sugar and fat”, “salt and pickles”, “noodle and alcohol”, and “protein-rich”) using principal component analysis. The composite IC score was calculated as the mean of the locomotion Z-score, cognition Z-score, psychological Z-score, vitality Z-score, and sensory regression score. A generalized estimating equation was applied for longitudinal analysis.

Results

A total of 666 enrollees were included in the analysis. The mean baseline IC was 0.07 ± 0.47. The “fruits and vegetables” dietary pattern was positively associated with composite IC score changes after adjusting for confounders (Q4 vs. Q1: mean difference [0.069], P = 0.019). Similarly, a positive correlation was observed for the “protein-rich” dietary pattern with the composite IC score changes (Q4 vs. Q1: mean difference [0.092], Q3 vs. Q1: mean difference [0.101], Q2 vs. Q1: mean difference [0.083]; all P < 0.01). However, adherence to the “sugar and fat” dietary pattern was negatively associated with composite IC score changes (Q4 vs. Q1: mean difference [− 0.072], P = 0.026). Furthermore, the percentage of animal protein to total protein intake showed a significant incremental trend in the “protein-rich” dietary pattern (P for trend < 0.001).

Conclusion

The “fruits and vegetables” and “protein-rich” (animal-based protein in particular) dietary patterns were positively associated with IC changes, whereas the “sugar and fat” dietary pattern was negatively associated with IC changes. Identification and promotion of healthy dietary patterns in older adults may inform future health policies and research.

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Availability of data and material

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. World report on ageing and health (2015). World Health Organization

  2. De Carvalho I, Martin FC, Cesari M, Summi Y, Thiyagarajan JA, Beard J (2017) Operationalising the concept of intrinsic capacity in clinical settings. Background paper for the WHO Working Group on Metrics and Research Standards for Healthy Ageing, March

  3. Cesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, Cooper C, Martin FC, Reginster JY, Vellas B, Beard JR (2018) Evidence for the domains supporting the construct of intrinsic capacity. J Gerontol A Biol Sci Med Sci 73(12):1653–1660. https://doi.org/10.1093/gerona/gly011

    Article  PubMed  Google Scholar 

  4. Beard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I (2019) The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open 9(11):e026119. https://doi.org/10.1136/bmjopen-2018-026119

    Article  PubMed  PubMed Central  Google Scholar 

  5. Giudici KV, de Souto BP, Guerville F, Beard J, Araujo de Carvalho I, Andrieu S, Rolland Y, Vellas B, group MD (2019) Associations of C-reactive protein and homocysteine concentrations with the impairment of intrinsic capacity domains over a 5-year follow-up among community-dwelling older adults at risk of cognitive decline (MAPT Study). Exp Gerontol 127:110716. https://doi.org/10.1016/j.exger.2019.110716

    Article  CAS  PubMed  Google Scholar 

  6. Charles A, Buckinx F, Locquet M, Reginster JY, Petermans J, Gruslin B, Bruyere O (2019) Prediction of adverse outcomes in nursing home residents according to intrinsic capacity proposed by the World Health Organization. J Gerontol A Biol Sci Med Sci. https://doi.org/10.1093/gerona/glz218

    Article  Google Scholar 

  7. Bonaccio M, Di Castelnuovo A, Costanzo S, Gialluisi A, Persichillo M, Cerletti C, Donati MB, de Gaetano G, Iacoviello L (2018) Mediterranean diet and mortality in the elderly: a prospective cohort study and a meta-analysis. Br J Nutr 120(8):841–854. https://doi.org/10.1017/s0007114518002179

    Article  CAS  PubMed  Google Scholar 

  8. Martinez-Lacoba R, Pardo-Garcia I, Amo-Saus E, Escribano-Sotos F (2018) Mediterranean diet and health outcomes: a systematic meta-review. Eur J Pub Health 28(5):955–961. https://doi.org/10.1093/eurpub/cky113

    Article  Google Scholar 

  9. Schwingshackl L, Schwedhelm C, Galbete C, Hoffmann G (2017) Adherence to mediterranean diet and risk of cancer: an updated systematic review and meta-analysis. Nutrients. https://doi.org/10.3390/nu9101063

    Article  PubMed  PubMed Central  Google Scholar 

  10. Lassale C, Batty GD, Baghdadli A, Jacka F, Sánchez-Villegas A, Kivimäki M, Akbaraly T (2019) Healthy dietary indices and risk of depressive outcomes: a systematic review and meta-analysis of observational studies. Mol Psychiatry 24(7):965–986. https://doi.org/10.1038/s41380-018-0237-8

    Article  PubMed  Google Scholar 

  11. Silva R, Pizato N, da Mata F, Figueiredo A, Ito M, Pereira MG (2018) Mediterranean diet and musculoskeletal-functional outcomes in community-dwelling older people: a systematic review and meta-analysis. J Nutr Health Aging 22(6):655–663. https://doi.org/10.1007/s12603-017-0993-1

    Article  CAS  PubMed  Google Scholar 

  12. Loughrey DG, Lavecchia S, Brennan S, Lawlor BA, Kelly ME (2017) The impact of the mediterranean diet on the cognitive functioning of healthy older adults: a systematic review and meta-analysis. Adv Nutr (Bethesda, Md) 8(4):571–586. https://doi.org/10.3945/an.117.015495

    Article  Google Scholar 

  13. Coelho-Junior HJ, Milano-Teixeira L, Rodrigues B, Bacurau R, Marzetti E, Uchida M (2018) Relative protein intake and physical function in older adults: a systematic review and meta-analysis of observational studies. Nutrients. https://doi.org/10.3390/nu10091330

    Article  PubMed  PubMed Central  Google Scholar 

  14. Coelho-Júnior HJ, Rodrigues B, Uchida M, Marzetti E (2018) Low protein intake is associated with frailty in older adults: a systematic review and meta-analysis of observational studies. Nutrients. https://doi.org/10.3390/nu10091334

    Article  PubMed  PubMed Central  Google Scholar 

  15. Darling AL, Manders RJF, Sahni S, Zhu K, Hewitt CE, Prince RL, Millward DJ, Lanham-New SA (2019) Dietary protein and bone health across the life-course: an updated systematic review and meta-analysis over 40 years. Osteoporos Int 30(4):741–761. https://doi.org/10.1007/s00198-019-04933-8

    Article  CAS  PubMed  Google Scholar 

  16. Shams-White MM, Chung M, Du M, Fu Z, Insogna KL, Karlsen MC, LeBoff MS, Shapses SA, Sackey J, Wallace TC, Weaver CM (2017) Dietary protein and bone health: a systematic review and meta-analysis from the National Osteoporosis Foundation. Am J Clin Nutr 105(6):1528–1543. https://doi.org/10.3945/ajcn.116.145110

    Article  CAS  PubMed  Google Scholar 

  17. Schwingshackl L, Schwedhelm C, Hoffmann G, Lampousi AM, Knüppel S, Iqbal K, Bechthold A, Schlesinger S, Boeing H (2017) Food groups and risk of all-cause mortality: a systematic review and meta-analysis of prospective studies. Am J Clin Nutr 105(6):1462–1473. https://doi.org/10.3945/ajcn.117.153148

    Article  CAS  PubMed  Google Scholar 

  18. Rashidi Pour Fard N, Amirabdollahian F, Haghighatdoost F (2019) Dietary patterns and frailty: a systematic review and meta-analysis. Nutr Rev 77(7):498–513. https://doi.org/10.1093/nutrit/nuz007

    Article  PubMed  Google Scholar 

  19. Huang CH, Martins BA, Okada K, Matsushita E, Uno C, Satake S, Kuzuya M (2020) A 3-year prospective cohort study of dietary patterns and frailty risk among community-dwelling older adults. Clin Nutr. https://doi.org/10.1016/j.clnu.2020.05.013

    Article  PubMed  PubMed Central  Google Scholar 

  20. Arakawa Martins B, Visvanathan R, Barrie H, Huang CH, Matsushita E, Okada K, Satake S, Uno C, Kuzuya M (2019) Frailty prevalence using Frailty Index, associated factors and level of agreement among frailty tools in a cohort of Japanese older adults. Arch Gerontol Geriatr 84:103908. https://doi.org/10.1016/j.archger.2019.103908

    Article  PubMed  Google Scholar 

  21. Matsushita E, Okada K, Ito Y, Satake S, Shiraishi N, Hirose T, Kuzuya M (2017) Characteristics of physical prefrailty among Japanese healthy older adults. Geriatr Gerontol Int 17(10):1568–1574. https://doi.org/10.1111/ggi.12935

    Article  PubMed  Google Scholar 

  22. Martins BA, Visvanathan R, Barrie HR, Huang CH, Matsushita E, Okada K, Satake S, Edwards S, Uno C, Kuzuya M (2020) Built environment and frailty: neighborhood perceptions and associations with frailty, experience from the nagoya longitudinal study. J Appl Gerontol. https://doi.org/10.1177/0733464820912663

    Article  PubMed  Google Scholar 

  23. Baecke JA, Burema J, Frijters JE (1982) A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr 36(5):936–942. https://doi.org/10.1093/ajcn/36.5.936

    Article  CAS  PubMed  Google Scholar 

  24. Ono R, Hirata S, Yamada M, Nishiyama T, Kurosaka M, Tamura Y (2007) Reliability and validity of the Baecke physical activity questionnaire in adult women with hip disorders. BMC Musculoskelet Disord 8:61. https://doi.org/10.1186/1471-2474-8-61

    Article  PubMed  PubMed Central  Google Scholar 

  25. Benedetti A, Wu Y, Levis B, Wilchesky M, Boruff J, Ioannidis JPA, Patten SB, Cuijpers P, Shrier I, Gilbody S, Ismail Z, McMillan D, Mitchell N, Ziegelstein RC, Thombs BD (2018) Diagnostic accuracy of the Geriatric Depression Scale-30, Geriatric Depression Scale-15, Geriatric Depression Scale-5 and Geriatric Depression Scale-4 for detecting major depression: protocol for a systematic review and individual participant data meta-analysis. BMJ Open 8(12):e026598. https://doi.org/10.1136/bmjopen-2018-026598

    Article  PubMed  PubMed Central  Google Scholar 

  26. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40(5):373–383

    Article  CAS  PubMed  Google Scholar 

  27. Vellas B, Villars H, Abellan G, Soto ME, Rolland Y, Guigoz Y, Morley JE, Chumlea W, Salva A, Rubenstein LZ, Garry P (2006) Overview of the MNA–its history and challenges. J Nutr Health Aging 10(6):456–463 ((discussion 463–455))

    CAS  PubMed  Google Scholar 

  28. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 49(2):M85–M94. https://doi.org/10.1093/geronj/49.2.M85

    Article  CAS  PubMed  Google Scholar 

  29. Sugiyama M, Ijuin M, Sakuma N (2015) Reliability and validity of the Five Cognitive Test in the context of detecting older people with mild cognitive impairment living in the community. Jpn J Geriatr Psychiatry 26(2):183–195

    Google Scholar 

  30. Schreiner AS, Hayakawa H, Morimoto T, Kakuma T (2003) Screening for late life depression: cut-off scores for the Geriatric Depression Scale and the Cornell Scale for Depression in Dementia among Japanese subjects. Int J Geriatr Psychiatry 18(6):498–505. https://doi.org/10.1002/gps.880

    Article  PubMed  Google Scholar 

  31. Neugarten BL, Havighurst RJ, Tobin SS (1961) The measurement of life satisfaction. J Gerontol 16:134–143

    Article  CAS  PubMed  Google Scholar 

  32. Takahashi K (2003) Food frequency questionnaire based on food groups for estimating individual nutrient intake. Jpn J Nutr Diet 61(3):161–169. https://doi.org/10.5264/eiyogakuzashi.61.161

    Article  Google Scholar 

  33. Zeger SL, Liang KY, Albert PS (1988) Models for longitudinal data: a generalized estimating equation approach. Biometrics 44(4):1049–1060

    Article  CAS  PubMed  Google Scholar 

  34. Huque MH, Carlin JB, Simpson JA, Lee KJ (2018) A comparison of multiple imputation methods for missing data in longitudinal studies. BMC Med Res Methodol 18(1):168. https://doi.org/10.1186/s12874-018-0615-6

    Article  PubMed  PubMed Central  Google Scholar 

  35. White IR, Royston P, Wood AM (2011) Multiple imputation using chained equations: issues and guidance for practice. Stat Med 30(4):377–399. https://doi.org/10.1002/sim.4067

    Article  PubMed  Google Scholar 

  36. Rubin DB (2004) Multiple imputation for nonresponse in surveys, vol 81. John Wiley & Sons

  37. Tosti V, Bertozzi B, Fontana L (2018) Health benefits of the mediterranean diet: metabolic and molecular mechanisms. J Gerontol A Biol Sci Med Sci 73(3):318–326. https://doi.org/10.1093/gerona/glx227

    Article  CAS  PubMed  Google Scholar 

  38. Sofi F, Macchi C, Abbate R, Gensini GF, Casini A (2014) Mediterranean diet and health status: an updated meta-analysis and a proposal for a literature-based adherence score. Public Health Nutr 17(12):2769–2782. https://doi.org/10.1017/s1368980013003169

    Article  PubMed  Google Scholar 

  39. Phillips SM, Martinson W (2019) Nutrient-rich, high-quality, protein-containing dairy foods in combination with exercise in aging persons to mitigate sarcopenia. Nutr Rev 77(4):216–229. https://doi.org/10.1093/nutrit/nuy062

    Article  PubMed  Google Scholar 

  40. Lorenzo-López L, Maseda A, de Labra C, Regueiro-Folgueira L, Rodríguez-Villamil JL, Millán-Calenti JC (2017) Nutritional determinants of frailty in older adults: a systematic review. BMC Geriatr 17(1):108. https://doi.org/10.1186/s12877-017-0496-2

    Article  PubMed  PubMed Central  Google Scholar 

  41. Otsuka R, Kato Y, Tange C, Nishita Y, Tomida M, Imai T, Ando F, Shimokata H, Arai H (2020) Protein intake per day and at each daily meal and skeletal muscle mass declines among older community dwellers in Japan. Public Health Nutr 23(6):1090–1097. https://doi.org/10.1017/s1368980019002921

    Article  PubMed  Google Scholar 

  42. Cuesta-Triana F, Verdejo-Bravo C, Fernández-Pérez C, Martín-Sánchez FJ (2019) Effect of Milk and Other Dairy Products on the Risk of Frailty, Sarcopenia, and Cognitive Performance Decline in the Elderly: A Systematic Review. Advances in nutrition (Bethesda, Md) 10 (suppl_2):S105-s119. https://doi.org/10.1093/advances/nmy105

  43. Li SS, Blanco Mejia S, Lytvyn L, Stewart SE, Viguiliouk E, Ha V, de Souza RJ, Leiter LA, Kendall CWC, Jenkins DJA, Sievenpiper JL (2017) Effect of plant protein on blood lipids: a systematic review and meta-analysis of randomized controlled trials. J Am Heart Assoc. https://doi.org/10.1161/jaha.117.006659

    Article  PubMed  PubMed Central  Google Scholar 

  44. Chalvon-Demersay T, Azzout-Marniche D, Arfsten J, Egli L, Gaudichon C, Karagounis LG, Tomé D (2017) A systematic review of the effects of plant compared with animal protein sources on features of metabolic syndrome. J Nutr 147(3):281–292. https://doi.org/10.3945/jn.116.239574

    Article  CAS  PubMed  Google Scholar 

  45. Messina M, Lynch H, Dickinson JM, Reed KE (2018) No Difference between the effects of supplementing with soy protein versus animal protein on gains in muscle mass and strength in response to resistance exercise. Int J Sport Nutr Exerc Metab 28(6):674–685. https://doi.org/10.1123/ijsnem.2018-0071

    Article  CAS  PubMed  Google Scholar 

  46. Khan TA, Tayyiba M, Agarwal A, Mejia SB, de Souza RJ, Wolever TMS, Leiter LA, Kendall CWC, Jenkins DJA, Sievenpiper JL (2019) Relation of total sugars, sucrose, fructose, and added sugars with the risk of cardiovascular disease: a systematic review and dose-response meta-analysis of prospective cohort studies. Mayo Clin Proc 94(12):2399–2414. https://doi.org/10.1016/j.mayocp.2019.05.034

    Article  CAS  PubMed  Google Scholar 

  47. Narain A, Kwok CS, Mamas MA (2016) Soft drinks and sweetened beverages and the risk of cardiovascular disease and mortality: a systematic review and meta-analysis. Int J Clin Pract 70(10):791–805. https://doi.org/10.1111/ijcp.12841

    Article  CAS  PubMed  Google Scholar 

  48. Clifton PM, Keogh JB (2017) A systematic review of the effect of dietary saturated and polyunsaturated fat on heart disease. Nutr Metab Cardiovasc Dis 27(12):1060–1080. https://doi.org/10.1016/j.numecd.2017.10.010

    Article  CAS  PubMed  Google Scholar 

  49. Erickson J, Sadeghirad B, Lytvyn L, Slavin J, Johnston BC (2017) The scientific basis of guideline recommendations on sugar intake: a systematic review. Ann Intern Med 166(4):257–267. https://doi.org/10.7326/m16-2020

    Article  PubMed  Google Scholar 

  50. Wanders AJ, Zock PL, Brouwer IA (2017) Trans fat intake and its dietary sources in general populations worldwide: a systematic review. Nutrients. https://doi.org/10.3390/nu9080840

    Article  PubMed  PubMed Central  Google Scholar 

  51. Yokoyama Y, Sasaki M, Sato K (2019) Nutrition intake among the Japanese elderly: an intergenerational comparison based on national health and nutrition survey scores. Ann Hum Biol 46(4):311–322. https://doi.org/10.1080/03014460.2019.1662943

    Article  PubMed  Google Scholar 

  52. Rhee CM, Ahmadi SF, Kovesdy CP, Kalantar-Zadeh K (2018) Low-protein diet for conservative management of chronic kidney disease: a systematic review and meta-analysis of controlled trials. J Cachexia Sarcopenia Muscle 9(2):235–245. https://doi.org/10.1002/jcsm.12264

    Article  PubMed  Google Scholar 

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Funding

This work was supported by the Mitsui Sumitomo Insurance Welfare Foundation Research Grant, Chukyo Longevity Medical and Promotion Foundation, JSPS KAKENHI (Grant Number JP 15 K01733, 16K16611), and Research Fund for Longevity Science from the National Center for Geriatrics and Gerontology, Japan (Grant Number 35-11). No financial disclosures were reported by all the authors. The funding bodies had no roles in the study design, data collection, data analysis and interpretation, or report writing.

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Authors and Affiliations

  1. Department of Community Health and Geriatrics, Nagoya University Graduate School of Medicine, 65 Tsuruma-cho, Showa-ku, Nagoya, Aichi Prefecture, 466-8550, Japan

    Chi Hsien Huang, Beatriz Arakawa Martins & Masafumi Kuzuya

  2. Department of Family Medicine, E-Da Hospital, No. 1, Yida Road, Jiaosu Village, Yanchao District, Kaohsiung City, Taiwan, ROC

    Chi Hsien Huang

  3. School of Medicine for International Students, College of Medicine, I-Shou University, No. 8, Yida Rd., Jiaosu Village, Yanchao District, Kaohsiung City, 82445, Taiwan, ROC

    Chi Hsien Huang

  4. Graduate School of Nutritional Sciences, Nagoya University of Arts and Sciences, Takenoyama-57, Iwasakicho, Nisshin, Aichi Prefecture, Japan

    Kiwako Okada, Eiji Matsushita & Chiharu Uno

  5. Section of Frailty Prevention, Department of Frailty Research, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, Aichi Prefecture, Japan

    Shosuke Satake

  6. Department of Geriatric Medicine, National Center for Geriatrics and Gerontology, Hospital, 7-430 Morioka-cho, Obu, Aichi Prefecture, Japan

    Shosuke Satake

  7. Adelaide Medical School, University of Adelaide, Adelaide Geriatrics Training and Research With Aged Care (G-TRAC Centre), Discipline of Medicine, 61 Silkes Rd, Paradise, SA, 5075, Australia

    Beatriz Arakawa Martins

  8. University of Adelaide, National Health and Medical Research Council Centre of Research Excellence in Frailty and Healthy Ageing, Adelaide, SA, 5005, Australia

    Beatriz Arakawa Martins

  9. Nagoya University, Institute of Innovation for Future Society, NIC, Chikusa Ward, Furocho, Nagoya, Aichi Prefecture, Japan

    Chi Hsien Huang, Chiharu Uno & Masafumi Kuzuya

Authors
  1. Chi Hsien Huang
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  2. Kiwako Okada
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  3. Eiji Matsushita
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  4. Chiharu Uno
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  5. Shosuke Satake
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  6. Beatriz Arakawa Martins
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  7. Masafumi Kuzuya
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Contributions

The authors’ responsibilities were as follows: KO, EM, CU, SS, and MK designed the research; CHH, KO, EM, CU, SS, BAM, and MK conducted the research, including the recruitment of study volunteers and the collection of samples and data; CHH and BAM performed the statistical analysis and data interpretation; CHH drafted the paper; KO, CU, and MK contributed to subsequent versions; and all authors read and approved the final manuscript.

Corresponding author

Correspondence to Masafumi Kuzuya.

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Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics approval

In accordance with the guidelines of the Declaration of Helsinki, this study was approved by the Ethics Committee of the Nagoya University Graduate School of Medicine (2013-0055-2) and the Ethics Committee of the Nagoya University of Arts and Sciences (83, approved on September 10, 2013).

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Informed consent was obtained from all the participants included in the study.

Consent for publication

Informed consent was obtained from all the participants included in the study.

Code availability

We analyzed the data using SPSS for Windows version 25.0. (IBM Corp., Armonk, NY).

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Huang, C.H., Okada, K., Matsushita, E. et al. Dietary patterns and intrinsic capacity among community-dwelling older adults: a 3-year prospective cohort study. Eur J Nutr 60, 3303–3313 (2021). https://doi.org/10.1007/s00394-021-02505-3

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