Direct Measurements of Abdominal Visceral Fat and Cognitive Impairment in Late Life: Findings From an Autopsy Study

Carregando...
Imagem de Miniatura
Citações na Scopus
5
Tipo de produção
article
Data de publicação
2019
Título da Revista
ISSN da Revista
Título do Volume
Editora
FRONTIERS MEDIA SA
Autores
NISHIZAWA, Aline
CUELHO, Anderson
FERRETTI-REBUSTINI, Renata E. L.
GRINBERG, Lea T.
Citação
FRONTIERS IN AGING NEUROSCIENCE, v.11, article ID 109, 8p, 2019
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Background: The relationship between cognitive impairment and abdominal visceral is controversial. Moreover, all studies so far used imaging studies to evaluate visceral fat and this association has not been described yet using autopsy material, which allows the direct quantification of abdominal fat. We aimed to investigate the association between direct measurements of abdominal visceral fat and cognitive impairment in an autopsy study. Methods: In this cross-sectional study, we collected information on sociodemographics, cardiovascular risk factors, and cognitive status from subjects aged 50 or older at time of death in a general autopsy service in Brazil. Abdominal visceral fat was obtained in natura by the dissection of perirenal, mesenteric, omental, and mesocolon fat. The associations of total abdominal visceral fat with cognitive impairment [clinical dementia rating (CDR) score >= 0.5] and CDR-sum of boxes (CDR-SB) were evaluated using logistic regression and negative binomial regression models, respectively. All analyses were adjusted for height, age, sex, education, hypertension, diabetes mellitus, stroke, smoking, alcohol use, and physical inactivity. In addition, we compared the discrimination of visceral fat, body mass index (BMI), and waist circumference (WC) measurements in predicting cognitive impairment. Results: We evaluated 234 participants (mean age = 71.2 +/- 12.9 years old, 59% male). Abdominal visceral fat was inversely associated with cognitive impairment (OR = 0.46, CI = 0.30; 0.70, p < 0.0001) and with CDR-SB scores (beta = 0.85, 95% CI = 1.28; 0.43, p < 0.0001). When we compared the area under the ROC curve (AUC), visceral fat (AUC = 0.754), BMI (AUC = 0.729), and WC (AUC = 0.720) showed similar discrimination in predicting cognitive impairment (p = 0.38). Conclusion: In an autopsy study, larger amount of directly measured abdominal visceral fat was associated with lower odds of cognitive impairment in older adults.
Palavras-chave
aging, autopsy, obesity, dementia, abdominal fat
Referências
  1. Alzheimer's Disease International, 2010, WORLD ALZHEIMER REPO
  2. Atti AR, 2008, J AM GERIATR SOC, V56, P111, DOI 10.1111/j.1532-5415.2007.01458.x
  3. Aziz NA, 2008, J NEUROL, V255, P1872, DOI 10.1007/s00415-009-0062-8
  4. Bastien M, 2014, PROG CARDIOVASC DIS, V56, P369, DOI 10.1016/j.pcad.2013.10.016
  5. Buchman AS, 2006, NEUROLOGY, V67, P1949, DOI 10.1212/01.wnl.0000247046.90574.0f
  6. Buchman AS, 2005, NEUROLOGY, V65, P892, DOI 10.1212/01.wnl.0000176061.33817.90
  7. Burns JM, 2010, ARCH NEUROL-CHICAGO, V67, P428, DOI 10.1001/archneurol.2010.38
  8. Cereda E, 2007, AGE AGEING, V36, P488, DOI 10.1093/ageing/afm096
  9. COHEN J, 1992, PSYCHOL BULL, V112, P155, DOI 10.1037/0033-2909.112.1.155
  10. Cronk BB, 2010, ALZ DIS ASSOC DIS, V24, P126, DOI 10.1097/WAD.0b013e3181a6bf3f
  11. Crossley R. P., 1974, POLICE CHIEF, V41, p[65, 85]
  12. Dahl AK, 2008, J AM GERIATR SOC, V56, P2261, DOI 10.1111/j.1532-5415.2008.01958.x
  13. DELONG ER, 1988, BIOMETRICS, V44, P837, DOI 10.2307/2531595
  14. Droogsma E, 2015, Z GERONTOL GERIATR, V48, P318, DOI 10.1007/s00391-015-0891-2
  15. Ebbert JO, 2014, CURR ATHEROSCLER REP, V16, DOI 10.1007/s11883-014-0445-x
  16. Farr SA, 2006, PEPTIDES, V27, P1420, DOI 10.1016/j.peptides.2005.10.006
  17. Ferretti Renata Eloah de Lucena, 2010, Dement. neuropsychol., V4, P138, DOI 10.1590/S1980-57642010DN40200011
  18. Fewlass DC, 2004, FASEB J, V18, P1870, DOI 10.1096/fj.04-2572com
  19. Grinberg Lea Tenenholz, 2007, Cell and Tissue Banking, V8, P151, DOI 10.1007/s10561-006-9022-z
  20. Gustafson D, 2003, ARCH INTERN MED, V163, P1524, DOI 10.1001/archinte.163.13.1524
  21. Hassing LB, 2009, INT J OBESITY, V33, P893, DOI 10.1038/ijo.2009.104
  22. Holden KF, 2009, NEUROBIOL AGING, V30, P1483, DOI 10.1016/j.neurobiolaging.2007.11.024
  23. HUGHES CP, 1982, BRIT J PSYCHIAT, V140, P566, DOI 10.1192/bjp.140.6.566
  24. Isaac V, 2011, FRONT AGING NEUROSCI, V3, DOI 10.3389/fnagi.2011.00012
  25. Jagust W, 2005, ARCH NEUROL-CHICAGO, V62, P1545, DOI 10.1001/archneur.62.10.1545
  26. Kamogawa K, 2010, DEMENT GERIATR COGN, V30, P432, DOI 10.1159/000321985
  27. Kanaya AM, 2009, ARCH NEUROL-CHICAGO, V66, P329, DOI 10.1001/archneurol.2008.570
  28. Knopman DS, 2007, NEUROLOGY, V69, P739, DOI 10.1212/01.wnl.0000267661.65586.33
  29. Luchsinger JA, 2007, ARCH NEUROL-CHICAGO, V64, P392, DOI 10.1001/archneur.64.3.392
  30. Mandviwala T, 2016, CURR ATHEROSCLER REP, V18, DOI 10.1007/s11883-016-0575-4
  31. Morris JC, 1997, NEUROLOGY, V48, P1508, DOI 10.1212/WNL.48.6.1508
  32. Nishizawa A, 2016, OPEN HEART, V3, DOI 10.1136/openhrt-2016-000433
  33. Noel M, 2005, PRIMARY CARE, V32, P659, DOI 10.1016/j.pop.2005.06.007
  34. Nourhashemi F, 2003, NEUROLOGY, V60, P117, DOI 10.1212/01.WNL.0000038910.46217.AA
  35. O'Bryant SE, 2008, ARCH NEUROL-CHICAGO, V65, P1091, DOI 10.1001/archneur.65.8.1091
  36. Papachristou E, 2015, BMC GERIATR, V15, DOI 10.1186/s12877-015-0169-y
  37. Pedditizi E, 2016, AGE AGEING, V45, P14, DOI 10.1093/ageing/afv151
  38. Power BD, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0017902
  39. Spauwen PJJ, 2017, AGE AGEING, V46, P250, DOI 10.1093/ageing/afw219
  40. Suemoto CK, 2015, INT J OBESITY, V39, P1383, DOI 10.1038/ijo.2015.83
  41. Suemoto CK, 2017, PLOS MED, V14, DOI 10.1371/journal.pmed.1002267
  42. VANDERKOOY K, 1993, INT J OBESITY, V17, P187
  43. West NA, 2009, J GERONTOL A-BIOL, V64, P103, DOI 10.1093/gerona/gln006
  44. Whitmer RA, 2008, NEUROLOGY, V71, P1057, DOI 10.1212/01.wnl.0000306313.89165.ef
  45. Whitmer RA, 2005, BRIT MED J, V330, P1360, DOI 10.1136/bmj.38446.466238.E0
  46. WHO, 2017, DEM FACT SHEET
  47. World Health Organization, 2018, OB OV FACT SHEET
  48. Yoon DH, 2012, AGE AGEING, V41, P456, DOI 10.1093/ageing/afs018
  49. Zamboni M, 1997, AM J CLIN NUTR, V66, P111