Association Between Adherence to the MIND Diet and Cognitive Performance is Affected by Income The ELSA-Brasil Study

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art_V_Association_Between_Adherence_to_the_MIND_Diet_and_2022.PDF (215.08 KB)
Citações na Scopus
6
Tipo de produção
article
Data de publicação
2022
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Editora
LIPPINCOTT WILLIAMS & WILKINS
Autores
MARCHIONI, Dirce M. L.
BARRETO, Sandhi M.
VIANA, Maria C.
CARAMELLI, Paulo
Citação
ALZHEIMER DISEASE & ASSOCIATED DISORDERS, v.36, n.2, p.133-139, 2022
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Background: The relationship between the Mediterranean-DASH Diet Intervention for Neurodegenerative Delay (MIND) diet and cognition has not been widely investigated in low- to middle-income countries. We investigated the relationship between MIND diet and cognition in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline data. Methods: We included 11,788 participants. MIND diet adherence was based on the intake of 15 components according to a food frequency questionnaire. We analyzed the association between MIND diet adherence and global cognition, memory, and executive function using adjusted linear regression. We examined the interaction between income and MIND diet adherence on cognition and presented income stratified analyses. Results: MIND diet adherence was not associated with cognition in the whole sample. Income was an effect modifier of MIND adherence on global cognition (P= 0.03) and executive function (P< 0.001). For participants with high income, greater adherence was associated with better executive function [ss= 0.015, 95% confidence interval (CI)= 0.002; 0.028, P= 0.025]; while for participants with low income, greater adherence was associated with lower global cognition (ss=-0.020, 95% CI= -0.036; -0.005, P= 0.010) and executive function (ss= -0.023, 95% CI=-0.039; -0.007, P= 0.004). Adherence to the MIND diet was higher among participants with high income (P< 0.001). Conclusion: For high-income participants, greater adherence was associated with better cognitive performance; for low-income participants, greater adherence was associated with lower cognitive performance.
Palavras-chave
cognition, MIND diet, income, LMIC, ELSA-Brasil
URI
https://observatorio.fm.usp.br/handle/OPI/53804
Referências
  1. [Anonymous], 2020, ALZHEIMERS DEMENT, V16, P391, DOI 10.1002/alz.12068
  2. Aquino EML, 2012, AM J EPIDEMIOL, V175, P315, DOI 10.1093/aje/kwr294
  3. Barnard ND, 2014, NEUROBIOL AGING, V35, pS65, DOI 10.1016/j.neurobiolaging.2014.02.030
  4. Beck L, 2019, TRANSL BEHAV MED, V9, P942, DOI 10.1093/tbm/ibz113
  5. Berendsen AM, 2018, J NUTR HEALTH AGING, V22, P222, DOI 10.1007/s12603-017-0909-0
  6. Berr C, 2009, DEMENT GERIATR COGN, V28, P357, DOI 10.1159/000253483
  7. Molina MDB, 2013, REV NUTR, V26, P167, DOI 10.1590/S1415-52732013000200005
  8. Brasil, 2017, FUNDO NACL DESENVOLV
  9. Calil SRB, 2018, CLIN NUTR ESPEN, V28, P201, DOI 10.1016/j.clnesp.2018.08.001
  10. Carrera I, 2019, CURR TOP MED CHEM, V19, P2999, DOI 10.2174/1568026619666191202155738
  11. Passos VMD, 2014, SAO PAULO MED J, V132, P170, DOI 10.1590/1516-3180.2014.1323646
  12. Drehmer M, 2016, J NUTR, V146, P81, DOI 10.3945/jn.115.220699
  13. Evans D A, 1993, Ann Epidemiol, V3, P71
  14. Faleiro Jéssica Costa, 2017, Cad. Saúde Pública, V33, pe00017916, DOI 10.1590/0102-311x00017916
  15. Pitanga FJG, 2018, ARQ BRAS CARDIOL, V110, P36, DOI 10.5935/abc.20170178
  16. Hackman DA, 2010, NAT REV NEUROSCI, V11, P651, DOI 10.1038/nrn2897
  17. Hiza HAB, 2013, J ACAD NUTR DIET, V113, P297, DOI 10.1016/j.jand.2012.08.011
  18. Hosking DE, 2019, ALZHEIMERS DEMENT, V15, P581, DOI 10.1016/j.jalz.2018.12.011
  19. Kheirouri S, 2022, CRIT REV FOOD SCI, V62, P8059, DOI 10.1080/10408398.2021.1925220
  20. Livingston G, 2020, LANCET, V396, P413, DOI 10.1016/S0140-6736(20)30367-6
  21. Lloyd-Jones DM, 2010, CIRCULATION, V121, P586, DOI 10.1161/CIRCULATIONAHA.109.192703
  22. Lo YT, 2009, ASIA PAC J CLIN NUTR, V18, P598
  23. Maccoby EE., 1987, PSYCHOL SEX DIFFEREN
  24. Machado LBM, 2018, INT J CARDIOL, V254, P333, DOI 10.1016/j.ijcard.2017.12.037
  25. Manly JJ, 1998, NEUROLOGY, V50, P1238, DOI 10.1212/WNL.50.5.1238
  26. McEvoy CT, 2017, J AM GERIATR SOC, V65, P1857, DOI 10.1111/jgs.14922
  27. Molina Maria del Carmen Bisi, 2013, Cad. Saúde Pública, V29, P379, DOI [10.1590/S0102-311X2013000600024, 10.1590/S0102-311X2013000200024]
  28. Morris MC, 2015, ALZHEIMERS DEMENT, V11, P1015, DOI 10.1016/j.jalz.2015.04.011
  29. Naqvi AZ, 2011, J AM GERIATR SOC, V59, P837, DOI 10.1111/j.1532-5415.2011.03402.x
  30. Parrott MD, 2013, J NUTR, V143, P1767, DOI 10.3945/jn.113.181115
  31. Pribis P, 2014, AM J CLIN NUTR, V100, p347S, DOI 10.3945/ajcn.113.071506
  32. Prince M., 2015, WORLD ALZHEIMER REPO
  33. Salthouse TA, 2018, MECH AGE COGNITION R
  34. Samieri C, 2013, EPIDEMIOLOGY, V24, P490, DOI 10.1097/EDE.0b013e318294a065
  35. Shakersain B, 2018, NUTRIENTS, V10, DOI 10.3390/nu10020229
  36. Suemoto CK, 2019, J GERONTOL A-BIOL, V74, P358, DOI 10.1093/gerona/gly061
  37. van den Brink AC, 2019, ADV NUTR, V10, P1040, DOI 10.1093/advances/nmz054
  38. van der Lee SJ, 2018, LANCET NEUROL, V17, P434, DOI [10.1016/s1474-4422(18)30053-X, 10.1016/S1474-4422(18)30053-X]
  39. vanDuinkerken E, 2020, DIABETIC MED, V37, P1742, DOI 10.1111/dme.14349
  40. Woolf SH, 2011, HEALTH AFFAIR, V30, P1852, DOI 10.1377/hlthaff.2011.0685
  41. World Health Organization, 2019, RISK RED COGN DECL D

Coleções
Artigos e Materiais de Revistas Científicas - FM/MCM
Artigos e Materiais de Revistas Científicas - LIM/20
Artigos e Materiais de Revistas Científicas - LIM/22
Artigos e Materiais de Revistas Científicas - LIM/66