nach oben

Erschienen in:

17.02.2021 | Original Contribution

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

verfasst von: Chi Hsien Huang, Kiwako Okada, Eiji Matsushita, Chiharu Uno, Shosuke Satake, Beatriz Arakawa Martins, Masafumi Kuzuya

Erschienen in: European Journal of Nutrition | Ausgabe 6/2021

Einloggen, um Zugang zu erhalten

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.

Nur mit Berechtigung zugänglich

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

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

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/gly011CrossRefPubMed

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-2018-026119CrossRefPubMedPubMedCentral

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.2019.110716CrossRefPubMed

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/glz218CrossRef

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/s0007114518002179CrossRefPubMed

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/cky113CrossRef

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/nu9101063CrossRefPubMedPubMedCentral

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/s41380-018-0237-8CrossRefPubMed

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/s12603-017-0993-1CrossRefPubMed

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.117.015495CrossRef

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/nu10091330CrossRefPubMedPubMedCentral

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/nu10091334CrossRefPubMedPubMedCentral

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/s00198-019-04933-8CrossRefPubMed

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.116.145110CrossRefPubMed

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.117.153148CrossRefPubMed

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/nuz007CrossRefPubMed

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.2020.05.013CrossRefPubMedPubMedCentral

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.2019.103908CrossRefPubMed

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.12935CrossRefPubMed

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/10.1177/0733464820912663CrossRefPubMed

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/36.5.936CrossRefPubMed

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/10.1186/1471-2474-8-61CrossRefPubMedPubMedCentral

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-2018-026598CrossRefPubMedPubMedCentral

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):373–383CrossRefPubMed

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))PubMed

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.M85CrossRefPubMed

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

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.880CrossRefPubMed

31.

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

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.61.161CrossRef

33.

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

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/s12874-018-0615-6CrossRefPubMedPubMedCentral

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.4067CrossRefPubMed

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/glx227CrossRefPubMed

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/s1368980013003169CrossRefPubMed

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/nuy062CrossRefPubMed

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/s12877-017-0496-2CrossRefPubMedPubMedCentral

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/s1368980019002921CrossRefPubMed

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.117.006659CrossRefPubMedPubMedCentral

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.116.239574CrossRefPubMed

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.2018-0071CrossRefPubMed

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.2019.05.034CrossRefPubMed

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.12841CrossRefPubMed

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.2017.10.010CrossRefPubMed

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/m16-2020CrossRefPubMed

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/nu9080840CrossRefPubMedPubMedCentral

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/10.1080/03014460.2019.1662943CrossRefPubMed

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.12264CrossRefPubMed

Titel: Dietary patterns and intrinsic capacity among community-dwelling older adults: a 3-year prospective cohort study
verfasst von: Chi Hsien Huang
Kiwako Okada
Eiji Matsushita
Chiharu Uno
Shosuke Satake
Beatriz Arakawa Martins
Masafumi Kuzuya
Publikationsdatum: 17.02.2021
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Nutrition / Ausgabe 6/2021
Print ISSN: 1436-6207
Elektronische ISSN: 1436-6215
DOI: https://doi.org/10.1007/s00394-021-02505-3

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Live-Webinar "Urologie und Sexualmedizin in der Praxis"

Springer Medizin

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