Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-26T16:23:28.823Z Has data issue: false hasContentIssue false
  • English
  • Français

Modeling Metabolic Syndrome and Its Association with Cognition: The Northern Manhattan Study

Published online by Cambridge University Press:  10 November 2014

Bonnie E. Levin ,
Maria M. Llabre ,
Chuanhui Dong ,
Mitchell S.V. Elkind ,
Yaakov Stern ,
Tatjana Rundek ,
Ralph L. Sacco  and
Clinton B. Wright
Bonnie E. Levin*
Affiliation:
Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami Leonard M. Miller School of Medicine, Miami, Florida Deparment of Psychology, University of Miami, Miami, Florida
Maria M. Llabre
Affiliation:
Deparment of Psychology, University of Miami, Miami, Florida
Chuanhui Dong
Affiliation:
Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami Leonard M. Miller School of Medicine, Miami, Florida
Mitchell S.V. Elkind
Affiliation:
Department of Neurology, Columbia University, New York, New York
Yaakov Stern
Affiliation:
Cognitve Neuroscience Division, Department of Neurology, Columbia University, New York, New York
Tatjana Rundek
Affiliation:
Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami Leonard M. Miller School of Medicine, Miami, Florida Department of Public Health Sciences, University of Miami Leonard M. Miller School of Medicine, Miami, Florida
Ralph L. Sacco
Affiliation:
Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami Leonard M. Miller School of Medicine, Miami, Florida Department of Public Health Sciences, University of Miami Leonard M. Miller School of Medicine, Miami, Florida Hussman Institute for Human Genomics, University of Miami Leonard M. Miller School of Medicine, Miami, Florida
Clinton B. Wright
Affiliation:
Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami Leonard M. Miller School of Medicine, Miami, Florida Hussman Institute for Human Genomics, University of Miami Leonard M. Miller School of Medicine, Miami, Florida
*
Correspondence and reprint requests to: Bonnie E. Levin, Division of Neuropsychology, 1120 NW 14th Street, Ste 1337, Miami, Fl 33136. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Metabolic syndrome (MetS) is a clustering of vascular risk factors and is associated with increased risk of cardiovascular disease. Less is known about the relationship between MetS and cognition. We examined component vascular risk factors of MetS as correlates of different cognitive domains. The Northern Manhattan Study (NOMAS) includes 1290 stroke-free participants from a largely Hispanic multi-ethnic urban community. We used structural equation modeling (SEM) to model latent variables of MetS, assessed at baseline and an average of 10 years later, at which time participants also underwent a full cognitive battery. The two four-factor models, of the metabolic syndrome (blood pressure, lipid levels, obesity, and fasting glucose) and of cognition (language, executive function, psychomotor, and memory), were each well supported (CFI=0.97 and CFI=0.95, respectively). When the two models were combined, the correlation between metabolic syndrome and cognition was −.31. Among the metabolic syndrome components, only blood pressure uniquely predicted all four cognitive domains. After adjusting for age, gender, race/ethnicity, education, smoking, alcohol, and risk factor treatment variables, blood pressure remained a significant correlate of all domains except memory. In this stroke-free race/ethnically diverse community-based cohort, MetS was associated with cognitive function suggesting that MetS and its components may be important predictors of cognitive outcomes. After adjusting for sociodemographic and vascular risk factors, blood pressure was the strongest correlate of cognitive performance. Findings suggest MetS, and in particular blood pressure, may represent markers of vascular or neurodegenerative damage in aging populations. (JINS, 2014, 20, 1–10)

Keywords

CognitionDementiaHypertensionAgingMetabolic syndromeCardiovascularVascular markers
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 20 , Issue 10 , November 2014 , pp. 951 - 960
Copyright
Copyright © The International Neuropsychological Society 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Birdsill, A.C., Carlsson, C.M., Willette, A.A., Okonkwo, O.C., Johnson, S.C., Xu, G., … Bendlin, B. B. (2013). Low cerebral blood flow is associated with lower memory function in metabolic syndrome. Obesity, 21(7), 1313–1320.CrossRefGoogle ScholarPubMed
Dahl, A.K., Hassing, L.B., Fransson, E.I., Gatz, M., Reynolds, C.A., & Pedersen, N. L. (2013). Body mass index across midlife and cognitive change in late life. International Journal of Obesity, 37(2), 296–302.CrossRefGoogle ScholarPubMed
Del Ser, T., Gonzalez-Montalvo, J.-I., Martinez-Espinosa, S., Delgado-Villapalos, C., & Bermejo, F. (1997). Estimation of premorbid intelligence in Spanish people with the Word Accentuation Test and its application to the diagnosis of dementia. Brain and Cognition, 33, 343–356.CrossRefGoogle Scholar
Dik, M.G., Jonker, C., Comijs, H.C., Deeg, D.J., Kok, A., Yaffe, K., & Penninx, B.W. (2007). Contribution of metabolic syndrome components to cognition in older individuals. Diabetes Care, 30(10), 2655–2660.CrossRefGoogle ScholarPubMed
Farr, S.A., Yamada, K.A., Butterfield, D.A., Abdul, H.M., Xu, L., Miller, N.E., … Morley, J. E. (2008). Obesity and hypertriglyceridemia produce cognitive Impairment. Endocrinology, 149(5), 2628–2636.CrossRefGoogle ScholarPubMed
Fedor, A., & Gunstad, J. (2013). Higher BMI is associated with reduced cognitive performance in division I athletes. Obesity Facts, 6(2), 185–192.CrossRefGoogle ScholarPubMed
Ford, E.S., Giles, W.H., & Mokdad, A.H. (2004). Increasing prevalence of the metabolic syndrome among US adults. Diabetes Care, 27(10), 2444–2449.CrossRefGoogle Scholar
Galassi, A., Reynolds, K., & He, J. (2006). Metabolic syndrome and risk of cardiovascular disease: A meta-analysis. The American Journal of Medicine, 119(10), 812–819.CrossRefGoogle ScholarPubMed
Gifford, K.A., Badaracco, M., Liu, D., Tripodis, Y., Gentile, A., Lu, Z., … Jefferson, A.L. (2013). Blood pressure and cognition among older adults: A meta-analysis. Archives of Clinical Neuropsychology, 28(7), 649–664.CrossRefGoogle ScholarPubMed
Gunstad, J., Paul, R.H., Cohen, R.A., Tate, D.F., Spitznagel, M.B., & Gordon, E. (2007). Elevated body mass index is associated with executive dysfunction in otherwise healthy adults. Comprehensive Psychiatry, 48(1), 57–61.CrossRefGoogle ScholarPubMed
Kilander, L., Nyman, H., Boberg, M., Hansson, L., & Lithell, H. (1998). Hypertension is related to cognitive impairment a 20-year follow-up of 999 men. Hypertension, 31(3), 780–786.CrossRefGoogle ScholarPubMed
Komulainen, P., Lakka, T.A., Kivipelto, M., Hassinen, M., Helkala, E.L., Haapala, I., … Rauramaa, R. (2006). Metabolic syndrome and cognitive function: A population-based follow-up study in elderly women. Dementia and Geriatric Cognitive Disorders, 23(1), 29–34.CrossRefGoogle ScholarPubMed
Launer, L.J., Ross, G.W., Petrovitch, H., Masaki, K., Foley, D., White, L.R., & Havlik, R.J. (2000). Midlife blood pressure and dementia: The Honolulu-Asia aging study. Neurobiology of Aging, 21(1), 49–55.CrossRefGoogle ScholarPubMed
Luchsinger, J.A., Reitz, C., Patel, B., Tang, M.X., Manly, J.J., & Mayeux, R. (2007). Relation of diabetes to mild cognitive impairment. Archives of Neurology, 64(4), 570.CrossRefGoogle ScholarPubMed
Marcus, J., Gardener, H., Rundek, T., Elkind, M.S., Sacco, R.L., DeCarli, C., & Wright, C.B. (2011). Baseline and longitudinal increases in diastolic blood pressure are associated with greater white matter hyperintensity volume The Northern Manhattan Study. Stroke, 42(9), 2639–2641.CrossRefGoogle ScholarPubMed
McCrimmon, R.J., Ryan, C.M., & Frier, B.M. (2012). Diabetes and cognitive dysfunction. The Lancet, 379(9833), 2291–2299.CrossRefGoogle ScholarPubMed
Mokdad, A.H., Serdula, M.K., Dietz, W.H., Bowman, B.A., Marks, J.S., & Koplan, J.P. (2000). The continuing epidemic of obesity in the United States. The Journal of the American Medical Association, 284(13), 1650–1651.CrossRefGoogle ScholarPubMed
Muldoon, M.F., Barger, S.D., Ryan, C.M., Flory, J.D., Lehoczky, J.P., Matthews, K.A., & Manuck, S.B. (2000). Effects of lovastatin on cognitive function and psychological well-being. The American Journal of Medicine, 108(7), 538–546.CrossRefGoogle ScholarPubMed
Muller, M., Tang, M.X., Schupf, N., Manly, J.J., Mayeux, R., & Luchsinger, J.A. (2007). Metabolic syndrome and dementia risk in a multiethnic elderly cohort. Dementia and Geriatric Cognitive Disorders, 24(3), 185–192.CrossRefGoogle Scholar
Nagai, M., Hoshide, S., Ishikawa, J., Shimada, K., & Kario, K. (2008). Ambulatory blood pressure as an independent determinant of brain atrophy and cognitive function in elderly hypertension. Journal of Hypertension, 26(8), 1636–1641.CrossRefGoogle ScholarPubMed
Narayan, S.K., Firbank, M.J., Saxby, B.K., Stansby, G., Hansrani, M., O’Brien, J.T., & Ford, G.A. (2011). Elevated plasma homocysteine is associated with increased brain atrophy rates in older subjects with mild hypertension. Dementia and Geriatric Cognitive Disorders, 31(5), 341–348.CrossRefGoogle ScholarPubMed
Novak, V., & Hajjar, I. (2010). The relationship between blood pressure and cognitive function. Nature Reviews . Cardiology, 7(12), 686–698.Google Scholar
Palaniappan, L., Carnethon, M.R., Wang, Y., Hanley, A.J., Fortmann, S.P., Haffner, S.M., & Wagenknecht, L. (2004). Predictors of the Incident Metabolic Syndrome in Adults: The Insulin Resistance Atherosclerosis Study. Diabetes Care, 27(3), 788–793.CrossRefGoogle ScholarPubMed
Petrova, M., Prokopenko, S., Pronina, E., & Mozheyko, E. (2010). Diabetes type 2, hypertension and cognitive dysfunction in middle age women. Journal of the Neurological Sciences, 299(1), 39–41.CrossRefGoogle ScholarPubMed
Pladevall, M., Singal, B., Williams, L.K., Brotons, C., Guyer, H., Sadurni, J., … Haffner, S. (2006). A single factor underlies the metabolic syndrome A confirmatory factor analysis. Diabetes Care, 29(1), 113–122.CrossRefGoogle ScholarPubMed
Pfützner, A., Musholt, P.B., Schipper, C., Niemeyer, M., Qvist, M., Schorsch, A., & Forst, T. (2012). Self-assessment and objective determination of dexterity in patients with type 1 or type 2 diabetes mellitus. Current Medical Research & Opinion, 28(1), 15–21.CrossRefGoogle ScholarPubMed
Raffaitin, C., Gin, H., Empana, J.P., Helmer, C., Berr, C., Tzourio, C., … Barberger-Gateau, P. (2009). Metabolic syndrome and risk for incident Alzheimer’s disease or vascular dementia: The Three-City Study. Diabetes Care, 32(1), 169–174.CrossRefGoogle ScholarPubMed
Royston, P., Altman, D.G., & Sauerbrei, W. (2006). Dichotomizing continuous predictors in multiple regression: A bad idea. Statistics in Medicine, 25(1), 127–141.CrossRefGoogle ScholarPubMed
Sabayan, B., Wijsman, L.W., Foster-Dingley, J.C., Stott, D.J., Ford, I., Buckley, B.M., … Mooijaart, S.P. (2013). Association of visit-to-visit variability in blood pressure with cognitive function in old age: Prospective cohort study. British Medical Journal Open, 347, f4600.CrossRefGoogle ScholarPubMed
Sacco, R.L., Benson, R.T., Kargman, D.E., Boden-Albala, B., Tuck, C., Lin, I.F., & Berglund, L. (2001). High-density lipoprotein cholesterol and ischemic stroke in the elderly. The Journal of the American Medical Association, 285(21), 2729–2735.CrossRefGoogle ScholarPubMed
Shen, B.J., Todaro, J.F., Niaura, R., McCaffery, J.M., Zhang, J., Spiro, A. III, & Ward, K.D. (2003). Are metabolic risk factors one unified syndrome? Modeling the structure of the metabolic syndrome X. American Journal of Epidemiology, 157(8), 701–711.CrossRefGoogle ScholarPubMed
Shen, B.J., Goldberg, R.B., Llabre, M.M., & Schneiderman, N. (2006). Is the factor structure of the metabolic syndrome comparable between men and women and across three ethnic groups: The Miami Community Health Study. Annals of Epidemiology, 16(2), 131–137.CrossRefGoogle ScholarPubMed
Siedlecki, K.L., Stern, Y., Reuben, A., Sacco, R.L., Elkind, M.S., & Wright, C.B. (2009). Construct validity of cognitive reserve in a multiethnic cohort: The Northern Manhattan Study. Journal of the International Neuropsychological Society, 15(4), 558.CrossRefGoogle Scholar
Stevenson, J.E., Wright, B.R., & Boydstun, A.S. (2012). The metabolic syndrome and coronary artery disease: A structural equation modeling approach suggestive of a common underlying pathophysiology. Metabolism, 61(11), 1582–1588.CrossRefGoogle ScholarPubMed
Strassburger, T.L., Lee, H.C., Daly, E.M., Szczepanik, J., Krasuski, J.S., Mentis, M.J., … Alexander, G.E. (1997). Interactive effects of age and hypertension on volumes of brain structures. Stroke, 28(7), 1410–1417.CrossRefGoogle ScholarPubMed
Takahashi, Y., Iseki, C., Wada, M., Momma, T., Ueki, M., Kawanami, T., … Kato, T. (2011). Impaired glucose metabolism slows executive function independent of cerebral ischemic lesions in Japanese elderly: The Takahata study. Internal Medicine, 50(16), 1671–1678.CrossRefGoogle ScholarPubMed
Taylor, C., Tillin, T., Chaturvedi, N., Dewey, M., Ferri, C.P., Hughes, A., … Stewart, R. (2013). Midlife hypertensive status and cognitive function 20 years later: The Southall and Brent Revisited Study. Journal of the American Geriatrics Society, 61(9), 1489–1498.CrossRefGoogle ScholarPubMed
Vieira, J.R., Elkind, M.S., Moon, Y.P., Rundek, T., Boden-Albala, B., Paik, M.C., … Wright, C.B. (2011). The metabolic syndrome and cognitive performance: The Northern Manhattan Study. Neuroepidemiology, 37(3-4), 153–159.CrossRefGoogle ScholarPubMed
Viscogliosi, G., Andreozzi, P., Chiriac, I.M., Cipriani, E., Servello, A., Ettorre, E., … Marigliano, V. (2012). Screening cognition in the elderly with metabolic syndrome. Metabolic Syndrome and Related Disorders, 10(5), 358–362.CrossRefGoogle ScholarPubMed
Waldstein, S.R., & Katzel, L.I. (2001). Hypertension and cognitive function. I.W.ldstein, S.R., & Elias, M.F. (Eds.), Neuropsychology of cardiovascular disease (pp. 5–36). Mahwah, NJ: Lawrence Erlbaum Associates.CrossRefGoogle Scholar
Wilkinson, G.S. (1993). Wide Range Achievement Test 3 – Administration Manual. Wilimington, DE: Jastak Associates.Google Scholar
Wright, C.B., Festa, J.R., Paik, M.C., Schmiedigen, A., Brown, T.R., Yoshita, M., … Stern, Y. (2008). White matter hyperintensities and subclinical infarction associations with psychomotor speed and cognitive flexibility. Stroke, 39(3), 800–805.CrossRefGoogle ScholarPubMed
Yaffe, K., Kanaya, A., Lindquist, K., Simonsick, E.M., Harris, T., Shorr, R.I., … Newman, A.B. (2004). The metabolic syndrome, inflammation, and risk of cognitive decline. The Journal of the American Medical Association, 292(18), 2237.CrossRefGoogle ScholarPubMed
Yaffe, K., Haan, M., Blackwell, T., Cherkasova, E., Whitmer, R.A., & West, N. (2007). Metabolic syndrome and cognitive decline in elderly Latinos: Findings from the Sacramento Area Latino Study of Aging study. Journal of the American Geriatrics Society, 55(5), 758–762.CrossRefGoogle ScholarPubMed
Yaffe, K., Vittinghoff, E., Pletcher, M.J., Hoang, T., Launer, L., Whitmer, R., … Sidney, S. (2014). Early adult to mid-life cardiovascular risk factors and cognitive function. Circulation, 129, 1560–1567.CrossRefGoogle ScholarPubMed