Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-25T06:00:55.001Z Has data issue: false hasContentIssue false
  • English
  • Français

Cognitive Correlates of MRI-defined Cerebral Vascular Injury and Atrophy in Elderly American Indians: The Strong Heart Study

Published online by Cambridge University Press:  03 December 2019

Astrid Suchy-Dicey ,
Dean Shibata ,
Brenna Cholerton ,
Lonnie Nelson ,
Darren Calhoun ,
Tauqeer Ali ,
Thomas J. Montine ,
W.T. Longstreth Jr. ,
Dedra Buchwald  and
Steven P. Verney Open the ORCID record for Steven P. Verney [Opens in a new window]
Astrid Suchy-Dicey
Affiliation:
Initiative for Research and Education to Advance Community Health, Washington State University, Seattle, WA, USA Elson S Floyd College of Medicine, Washington State University, Seattle, WA, USA
Dean Shibata
Affiliation:
Department of Radiology, University of Washington, Seattle, WA, USA
Brenna Cholerton
Affiliation:
Department of Pathology, Stanford University, Palo Alto, CA, USA
Lonnie Nelson
Affiliation:
College of Nursing, Washington State University, Seattle, WA, USA
Darren Calhoun
Affiliation:
Phoenix Field Office MedStar Research Institute, Phoenix, AZ, USA
Tauqeer Ali
Affiliation:
Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
Thomas J. Montine
Affiliation:
Department of Pathology, Stanford University, Palo Alto, CA, USA
W.T. Longstreth Jr.
Affiliation:
Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, USA
Dedra Buchwald
Affiliation:
Initiative for Research and Education to Advance Community Health, Washington State University, Seattle, WA, USA Elson S Floyd College of Medicine, Washington State University, Seattle, WA, USA
Steven P. Verney*
Affiliation:
Department of Psychology and Psychology Clinical Neuroscience Center, University of New Mexico, Albuquerque, NM, USA
*
*Correspondence and reprint requests to: Steven P. Verney, Department of Psychology and Psychology Clinical Neuroscience Center, University of New Mexico, Psychology MSC03-2220, Albuquerque, NM 87131-0001, USA. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

American Indians experience substantial health disparities relative to the US population, including vascular brain aging. Poorer cognitive test performance has been associated with cranial magnetic resonance imaging findings in aging community populations, but no study has investigated these associations in elderly American Indians.

Methods:

We examined 786 American Indians aged 64 years and older from the Cerebrovascular Disease and its Consequences in American Indians study (2010–2013). Cranial magnetic resonance images were scored for cortical and subcortical infarcts, hemorrhages, severity of white matter disease, sulcal widening, ventricle enlargement, and volumetric estimates for white matter hyperintensities (WMHs), hippocampus, and brain. Participants completed demographic, medical history, and neuropsychological assessments including testing for general cognitive functioning, verbal learning and memory, processing speed, phonemic fluency, and executive function.

Results:

Processing speed was independently associated with the presence of any infarcts, white matter disease, and hippocampal and brain volumes, independent of socioeconomic, language, education, and clinical factors. Other significant associations included general cognitive functioning with hippocampal volume. Nonsignificant, marginal associations included general cognition with WMH and brain volume; verbal memory with hippocampal volume; verbal fluency and executive function with brain volume; and processing speed with ventricle enlargement.

Conclusions:

Brain-cognition associations found in this study of elderly American Indians are similar to those found in other racial/ethnic populations, with processing speed comprising an especially strong correlate of cerebrovascular disease. These findings may assist future efforts to define opportunities for disease prevention, to conduct research on diagnostic and normative standards, and to guide clinical evaluation of this underserved and overburdened population.

Keywords

Neuropsychological testsMagnetic resonance imagingVascular brain injuryCerebrovascular disordersIndiansNorth AmericanHealth status disparitiesCognitive agingCultural diversity
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 26 , Issue 3 , March 2020 , pp. 263 - 275
Copyright
Copyright © INS. Published by Cambridge University Press, 2019

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

REFERENCES

Aggarwal, N.T., Wilson, R.S., Bienias, J.L., De Jager, P.L., Bennett, D.A., Evans, D.A., & DeCarli, C. (2010). The association of magnetic response imaging measures with cognitive function in a biracial population sample. Archives of Neurology, 67, 475–482.10.1001/archneurol.2010.42CrossRefGoogle Scholar
Al-Khindi, T., Macdonald, R.L., & Schweizer, T.A. (2010). Cognitive and functional outcome after aneurysmal subarachnoid hemorrhage. Stroke, 41, e519–e536.CrossRefGoogle ScholarPubMed
Arnold, A.M., Psaty, B.M., Kuller, L.H., Burke, G.L., Manolio, T.A., Fried, L.P., Robbins, J.A., & Kronmal, R.A. (2005). Incidence of cardiovascular disease in older Americans: The cardiovascular health study. Journal of American Geriartrics Society, 53, 211–218.10.1111/j.1532-5415.2005.53105.xCrossRefGoogle ScholarPubMed
Ayala, C., Greenlund, K.J., Croft, J.B., Keenan, N.L., Donehoo, R.S., Giles, W.H., Kittner, S.J., & Marks, J.S. (2001). Racial/ethnic disparities in mortality by stroke subtype in the United States, 1995–1998. American Journal of Epidemiology, 154, 1057–1063.10.1093/aje/154.11.1057CrossRefGoogle ScholarPubMed
Benjamini, Y.H. & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society B, 57, 289–300.Google Scholar
Benton, A.L. & Hansher, K. (1976). Multilingual aphasia examination (2nd ed.). Iowa City, IO: AJA Associates.Google Scholar
Biesbroek, J.M., Weaver, N.A., Hilal, S., Kuijf, H.J., Ikram, M.K., Xu, X., Tan, B.Y., Venketasubramanian, N., Postma, A., Biessels, G.J., & Chen, C.P. (2016). Impact of strategically located white matter hyperintensities on cognition in memory clinic patients with small vessel disease. PLoS One, 11, e0166261.CrossRefGoogle ScholarPubMed
Birdsill, A.C., Koscik, R.L., Jonaitis, E.M., Johnson, S.C., Okonkwo, O.C., Herman, B.P., Larue, A., Sager, M.A., & Bendlin, B.B. (2014). Regional white matter hyperintensities, aging, AD risk, and cognitive function. Neurobiol Aging, 35, 1–18.10.1016/j.neurobiolaging.2013.10.072CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. (2004). Diabetes prevalence among American Indians and Alaska Natives and the overall population- United States, 1994–2002. Morbidity and Mortality Weekly Report, 52 (30), 702–704.Google Scholar
Charidimou, A., Shams, S., Romero, J.R., Ding, J., Veltkamp, R., Horstmann, S., Eiriksdottir, G., van Buchem, M.A., Gudnason, V., Himali, J.J., Gurol, M.E., Viswanathan, A., Imaizumi, T., Vernooij, M.W., Seshadri, S., Greenberg, S.M., Benavente, O.R., Launer, L.J., Shoamanesh, A., & International META-MICROBLEEDS Initiative (2018). Clinical significance of cerebral microbleeds on MRI: A comprehensive meta-analysis of risk of intracerebral hemorrhage, ischemic stroke, mortality, and dementia in cohort studies (v1). International Journal of Stroke, 13, 454–468.CrossRefGoogle Scholar
Cholerton, B., Baker, L.D., & Craft, S. (2011). Insulin resistance and pathological brain ageing. Diabetic Medicine: A Journal of the British Diabetic Association, 28, 1463–1475.CrossRefGoogle ScholarPubMed
Cholerton, B., Omidpanah, A., Madhyastha, T.M., Grabowski, T.J., Suchy-Dicey, A.M., Shibata, D.K., Nelson, L.A., Verney, S.P., Howard, B.V., Longstreth, W.T. Jr., Montine, T.J., & Buchwald, D. (2017). Total brain and hippocampal volumes and cognition in older American Indians: The Strong Heart Study. Alzheimer Disease and Associated Disorders, 31, 94–100.CrossRefGoogle ScholarPubMed
Cordonnier, C., Al-Shahi Salman, R., & Wardlaw, J. (2007). Spontaneous brain microbleeds: Systematic review, subgroup analyses and standards for study design and reporting. Brain, 130, 1988–2003.CrossRefGoogle ScholarPubMed
Debette, S., Beiser, A., DeCarli, C., Au, R., Himali, J.J., Kelly-Hayes, M., Romero, J.R., Kase, C.S., Wolf, P.A., & Seshadri, S. (2010). Association of MRI markers of vascular brain injury with incident stroke, mild cognitive impairment, dementia, and mortality: The Framingham Offspring Study. Stroke, 41, 600–606.CrossRefGoogle ScholarPubMed
DeCarli, C., Reed, B.R., Jagust, W.J., Martinez, O., Ortega, M., & Mungas, D. (2008). Brain behavior relationships amongst African Americans, Caucasians and Hispanics. Alzheimer Disease and Associated Disorders, 22, 382–391.CrossRefGoogle Scholar
Delis, D.C., Kramer, J.H., Kaplan, E., & Ober, B.A. (2000). California verbal learning test (CVLT-II) (2nd ed.). San Antonio, TX: The Psychological Corporation.Google Scholar
Dhamoon, M.S., Cheung, Y.K., Gutierrez, J., Moon, Y.P., Sacco, R.L., Elkind, M.S.V., & Wright, C.B. (2018). Functional trajectories, cognition, and subclinical cerebrovascular disease. Stroke, 49, 549–555.CrossRefGoogle ScholarPubMed
Drag, L.L. & Bieliauskas, L.A. (2010). Contemporary review 2009: Cognitive again. Journal of Geriatric Psychiatry and Neurology, 23, 75–93.CrossRefGoogle Scholar
Erkinjuntti, T., Inzitari, D., Pantoni, L., Wallin, A., Scheltens, P., Rockwood, K., Roman, G.C., Chui, H., & Desmond, D.W. (2000). Research criteria for subcortical vascular dementia in clinical trials. Journal of Neural Transmission Supplement, 59, 23–30.Google ScholarPubMed
Eyler, L.T., Sherzai, A., Kaup, A.R., & Jeste, D.V. (2011). A review of functional brain imaging correlates of successful cognitive aging. Biological Psychiatry, 70, 115–122.CrossRefGoogle ScholarPubMed
Fine, E.M., Kramer, J.H., Lui, L.Y., Yaffe, K., & Study of Osteoporotic Fractures Research Group. (2012). Normative data in women aged 85 and older: Verbal fluency, digit span, and the CVLT-II short form. Clinical Neuropsychologist, 26, 18–30.CrossRefGoogle ScholarPubMed
Gillum, R.F. (1995). The epidemiology of stroke in Native Americans. Stroke, 26, 514–521.10.1161/01.STR.26.3.514CrossRefGoogle ScholarPubMed
Glazer, H., Dong, C., Yoshita, M., Rundek, T., Elkind, M.S., Sacco, R.L., DeCarli, C., Stern, Y., & Wright, C.B. (2015). Subclinical cerebrovascular disease inversely associates with learning ability: The NOMAS. Neurology, 84, 2362–2367.CrossRefGoogle ScholarPubMed
Gorelick, P.B., Scuteri, A., Black, S.E., DeCarli, C., Greenberg, S.M., Iadecola, C., Launer, L.J., Laurent, S., Lopez, O.L., Nyenhuis, D., Petersen, R.C., Schneider, J.A., Tzourio, C., Arnett, D.K., Bennett, D.A., Chui, H.C., Higashida, R.T., Lindquist, R., Nilsson, P.M., Roman, G.C., Sellke, F.W., & Seshadri, S. (2011). Vascular contributions to cognitive impairment and dementia: A statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke, 42, 2672–2713.CrossRefGoogle ScholarPubMed
Gregg, N.M., Kim, A.E., Gurol, M.E., Lopez, O.L., Aizenstein, H.J., Price, J.C., Mathis, C.A., James, J.A., Snitz, B.E., Cohen, A.D., Kamboh, M.I., Minhas, D., Weissfeld, L.A., Tamburo, E.L., & Klunk, W.E. (2015). Incidental cerebral microbleeds and cerebral blood flow in elderly individuals. JAMA Neurology, 72, 1021–1028.CrossRefGoogle ScholarPubMed
Harris, R., Nelson, L.A., Muller, C., & Buchwald, D. (2015). Stroke in American Indians and Alaska Natives: A systematic review. American Journal of Public Health, 105, e16–e26.CrossRefGoogle ScholarPubMed
Harwell, T.S., Oser, C.S., Okon, N.J., Fogle, C.C., Helgerson, S.D., & Gohdes, D. (2005). Defining disparities in cardiovascular disease for American Indians: Trends in heart disease and stroke mortality among American Indians and whites in Montana, 1991 to 2000. Circulation, 112, 2263–2267.CrossRefGoogle ScholarPubMed
Hill, C.V., Perez-Stable, E.J., Anderson, N.A., & Bernard, M.A. (2015). The National Institute on Aging Health Disparities Research Framework. Ethnicity & Disease, 25, 245–254.CrossRefGoogle ScholarPubMed
Hutchinson, R.N. & Shin, S. (2014). Systematic review of health disparities for cardiovascular diseases and associated factors among American Indian and Alaska Native populations. PLoS One, 9, e80973.CrossRefGoogle ScholarPubMed
Jokinen, H., Kalska, H., Ylikoski, R., Madureira, S., Verdelho, A., Gouw, A., Scheltens, P., Barkhof, F., Visser, M.C., Fazekas, F., Schmidt, R., O’Brien, J., Hennerici, M., Baezner, H., Waldemar, G., Wallin, A., Chabriat, H., Pantoni, L., Inzitari, D., Erkinjuntti, T., & LADIS group (2009). MRI-defined subcortical ischemic vascular disease: Baseline clinical and Neuropsychological findings. Cerebrovascular Disease, 27, 336–344.10.1159/000202010CrossRefGoogle ScholarPubMed
Jones, R.N. & Gallo, J.J. (2002). Education and sex differences in the mini-mental state examination: Effects of differential item functioning. Journals of Gerontology Series B, 57, P548–P558.CrossRefGoogle ScholarPubMed
Knopman, D.S., Griswold, M.E., Lirette, S.T., Gottesman, R.F., Kantarci, K., Sharrett, A.R., Jack, C.R., Graff-Radford, J., Schneider, A.L.C., Windham, B.G., Coker, L.H., Albert, M.S., Mosley, T.H., & the ARIC Neurocognitive Investigators. (2015). Vascular imaging abnormalities and cognition: Mediation by cortical volume in nondemented individuals: Atherosclerosis risk in communities-neurocognitive study. Stroke, 46, 433–440.CrossRefGoogle ScholarPubMed
Lee, E.T., Welty, T.K., Fabsitz, R., Cowan, L.D., Le, N.A., Oopik, A.J., Cucchiara, A.J., Savage, P.J., & Howard, B.V. (1990). The Strong Heart Study. A study of cardiovascular disease in American Indians: Design and methods. American Journal of Epidemiology, 132, 1141–1155.CrossRefGoogle ScholarPubMed
Longstreth, W.T. Jr., Arnold, A.M., Beauchamp, N.J. Jr., Manolio, T.A., Lefkowitz, D., Jungreis, C., Hirsch, C.H., O'Leary, D.H., & Furberg, C.D. (2005). Incidence, manifestations, and predictors of worsening white matter on serial cranial magnetic resonance imaging in the elderly: The Cardiovascular Health Study. Stroke, 36, 56–61.CrossRefGoogle ScholarPubMed
Longstreth, W.T. Jr., Dulberg, C., Manolio, T.A., Lewis, M.R., Beauchamp, N.J. Jr., O’Leary, D., Carr, J., & Furberg, C.D. (2002). Incidence, manifestations, and predictors of brain infarcts defined by serial cranial magnetic resonance imaging in the elderly: The Cardiovascular Health Study. Stroke, 33, 2376–2382.CrossRefGoogle ScholarPubMed
Luchsinger, J.A. (2010). Diabetes, related conditions, and dementia. Journal of the Neurological Sciences, 299, 35–38.CrossRefGoogle ScholarPubMed
Miralbell, J., Lopez-Cancio, E., Lopez-Oloriz, J., Arenillas, J.F., Barrios, M., Soriano-Raya, J.J., Galán, A., Cáceres, C., Alzamora, M., Pera, G., Toran, P., Dávalos, A., & Mataro, M. (2013). Cognitive patterns in relation to biomarkers of cerebrovascular disease and vascular risk factors. Cerebrovascular Disease, 36, 98–105.CrossRefGoogle ScholarPubMed
Morris, Z., Whiteley, W.N., Longstreth, W.T. Jr, Weber, F., Lee, Y.-C., Tsushima, Y., Alphs, H., Ladd, S.C., Warlow, C., Wardlaw, J.M., & Salman, R.A.-S. (2009). Incidental findings on brain magnetic resonance imaging: Systematic review and meta-analysis. BMJ, 339, 1–7.CrossRefGoogle ScholarPubMed
Moseley, J.V. & Linden, W. (2006). Predicting blood pressure and heart rate change with cardiovascular reactivity and recovery: Results from 3-year and 10-year follow up. Psychosomatic Medicine, 68, 833–843.10.1097/01.psy.0000238453.11324.d5CrossRefGoogle ScholarPubMed
Mosley, T.H. Jr., Knopman, D.S., Catellier, D.J., Bryan, N., Hutchinson, R.G., Grothues, C.A., Folsom, A.R., Cooper, L.S., Burke, G.L., Liao, D., & Szklo, M. (2005). Cerebral MRI findings and cognitive functioning: The Atherosclerosis Risk in Communities study. Neurology, 64, 2056–2062.10.1212/01.WNL.0000165985.97397.88CrossRefGoogle ScholarPubMed
Office of Management and Budget (1997). Revisions to the standards for the classification of federal data on race and ethnicity. In Office of Information and Regulatory Affairs (Ed.). Washington, DC: Federal Register Notice.Google Scholar
Pantoni, L., Fierini, F., Poggesi, A., & LADIS Study Group (2015). Impact of cerebral white matter changes on functionality in older adults: An overview of the LADIS Study results and future directions. Geriatrics & Gerontology International, 15 Suppl 1, 10–16.CrossRefGoogle ScholarPubMed
Papp, K.V., Kaplan, R.F., Springate, B., Moscufo, N., Wakefield, D.B., Guttman, C.R.G., & Wolfson, L. (2014). Processing speed in normal aging: Effects of white matter hyperintensities and hippocampal volume loss. Neuropsychology, development, and cognition. Section B, Aging, Neuropsychology and Cognition, 21, 197–213.CrossRefGoogle ScholarPubMed
Prins, N.D., van Dijk, E.J., den Heijer, T., Vermeer, S.E., Jolles, J., Koudstaal, P.J., Hofman, A., & Breteler, M.M.B. (2005). Cerebral small-vessel disease and decline in information processing speed, executive function and memory. Brain, 128, 2034–2041.CrossRefGoogle ScholarPubMed
Rosamond, W.D., Folsom, A.R., Chambless, L.E., Wang, C.H., McGovern, P.G., Howard, G., Copper, L.S., & Shahar, E. (1999). Stroke incidence and survival among middle-aged adults: 9 year follow-up of the Atherosclerosis Risk in Communities (ARIC) cohort. Stroke; a Journal of Cerebral Circulation, 30, 736–743.CrossRefGoogle ScholarPubMed
Saczynski, J.S., Sigurdsson, S., Jonsdottir, M.K., Eiriksdottir, G., Jonsson, P.V., Garcia, M.E., Kjartansson, O., Lopez, O., van Buchem, M.A., Gudnason, V., & Launer, L.J. (2009). Cerebral infarcts and cognitive performance: Importance of location and number of infarcts. Stroke, 40, 677–682.10.1161/STROKEAHA.108.530212CrossRefGoogle ScholarPubMed
Sadanand, S., Balachandar, R., & Bharath, S. (2015). Memory and executive functions in persons with type 2 diabetes: A meta-analysis. Diabetes & Metabolic Syndrome, 32, 132–142.Google ScholarPubMed
Schnieder, J.A., Wilson, R.S., Cochran, E.J., Bienias, J.L., Arnold, S.E., Evans, D.A., & Bennett, D.A. (2003). Relation of cerebral infarctions to dementia and cognitive function in older persons. Neurology, 60, 1082–1088.10.1212/01.WNL.0000055863.87435.B2CrossRefGoogle Scholar
Shahjouei, S., Tsivgoulis, G., Singh, M., McCormack, M., Noorbakhsh-Sabet, N., Goyal, N., Alexandrov, A.W., Alexandrov, A.V., & Zand, R. (2017). Racial Difference in Cerebral Microbleed Burden among Ischemic Stroke Patients. Journal of Stroke and Cerebrovascular Diseases: The Official Journal of National Stroke Association, 26, 2680–2685.CrossRefGoogle ScholarPubMed
Shiels, M.S., Chernyavskiy, P., Anderson, W.F., Best, A.F., Haozous, E.A., Hartge, P., Rosenberg, P.S., Thomas, D., Freedman, N.D., & Berrington de Gonzalez, A. (2017). Trends in premature mortality in the USA by sex, race, and ethnicity from 1999 to 2014: An analysis of death certificate data. Lancet, 389, 1043–1054.CrossRefGoogle ScholarPubMed
Smith, E.E., Salat, D.H., Jengs, J., McCreary, C.R., Fischi, B., Schmahmann, J.D., Dickerson, B.C., Viswanathan, A., Albert, M.S., Blacker, D., & Greenberg, S.M. (2011). Correlations between MRI white matter lesion location and executive function and episodic memory. Neurology, 76, 1492–1499.CrossRefGoogle ScholarPubMed
StataCorp. (2014). Stata Statistical Software: Release 14. College Station, TX: StataCorp LP.Google Scholar
Stijntjes, M., de Craen, A.J., van der Grond, J., Meskers, C.G., Slagboom, P.E., & Maier, A.B. (2016). Cerebral Microbleeds and Lacunar Infarcts Are Associated with Walking Speed Independent of Cognitive Performance in Middle-Aged to Older Adults. Gerontology, 62, 500–507.CrossRefGoogle ScholarPubMed
Strachan, M.W. (2003). Insulin and cognitive function. Lancet, 362, 1253.CrossRefGoogle ScholarPubMed
Suchy-Dicey, A.M., Muller, C.J., Madhyastha, T.M., Shibata, D., Cole, S.A., Zhao, J., Longstreth, W.T. Jr., & Buchwald, D. (2018). Telomere Length and magnetic resonance imaging findings of vascular brain injury and central brain atrophy: The Strong Heart Study. American Journal of Epidemiology, 187, 1231–1239.CrossRefGoogle ScholarPubMed
Suchy-Dicey, A.M., Shibata, D., Best, L.G., Verney, S.P., Longstreth, W.T. Jr., Lee, E.T.,., Okin, P.M., Devereux, R., O'Leary, M., Ali, T., Jensen, P.N., Muller, C., Nelson, L.A., Rhoades, E., Madhyastha, T., Grabowski, T.J., Beauchamp, N., Umans, J.G., & Buchwald, D. (2016). Cranial magnetic resonance imaging in elderly American Indians: Design, methods, and implementation of the cerebrovascular disease and its consequences in American Indians Study. Neuroepidemiology, 47, 67–75.CrossRefGoogle ScholarPubMed
Suchy-Dicey, A.M., Shibata, D.K., Madhyastha, T.M., Grabowski, T.J., Longstreth, W.T. Jr., Okin, P.M., Devereux, R., O’Leary, M., Ali, T., Jensen, P.N., Muller, C., Nelson, L.A., Rhoades, E., Madhyastha, T., Grabowski, T.J., Beauchamp, N., Umans, J.G., & Buchwald, D.S. (2017). Findings of vascular brain injury and structural loss from cranial magnetic resonance imaging in elderly American Indians: The strong heart study. Neuroepidemiology, 48, 39–47.CrossRefGoogle ScholarPubMed
Suzuki, L.A., Naqvi, S., & Hill, J.S. (2013). Assessing intelligence in a cultural context. In Leong, F.T.L. (Ed.), APA handbook of multicultural psychology: theory and research, Vol. 1 (pp. 247–266). Washington, DC: American Psychological Association.Google Scholar
R Core Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Teng, E.L. & Chang Chui, H. (1987). The Modified Mini-Mental (3MS) examination. Journal Clinical Psychiatry, 48, 314–318.Google ScholarPubMed
Teng, E.L. & Chui, H.C. (1987). The Modified Mini-Mental State (3MS) examination. Journal Clinical Psychiatry, 48, 314–318.Google ScholarPubMed
Tombaugh, T.N., Kozak, J., & Rees, L. (1999). Normative data stratified by age and education for two measures of verbal fluency: FAS and animal naming. Archives of Clinical Neuropsychology, 14, 167–177.Google ScholarPubMed
Tournoy, J., Lee, D.M., Pendleton, N., O’Neill, T.W., O’Connor, D.B., Bartfai, G., Casanueva, F.F., Finn, J.D., Forti, G., Giwercman, A., Han, T.S., Huhtaniemi, I.T., Kula, K., Lean, M.E., Moseley, C.M., Punab, M., Silman, A.J., Vanderschueren, D., Wu, F.C., Boonen, S., EMAS study group. (2010). Association of cognitive performance with the metabolic syndrome and with glycaemia in middle-aged and older European men: The European Male Ageing Study. Diabetes-Metabolism Research and Reviews, 26, 668–676.CrossRefGoogle ScholarPubMed
U.S. Department of Health and Human Services (2014). Healthy people 2020: Foundation health measures archive on disparities. In Office of Disease Prevention and Health Promotion (ODPHP) (Ed.). Washington, DC.Google Scholar
Valenti, R., Del Bene, A., Poggesi, A., Ginestroni, A., Salvadori, E., Pracucci, G., Ciolli, L., Marini, S., Nannucci, S., Pasi, M., Pescini, F., Diciotti, S., Orlandi, G., Cosottini, M., Chiti, A., Mascalchi, M., Bonuccelli, U., Inzitari, D., Pantoni, L. & VMCI-Tuscany Study Group (2016). Cerebral microbleeds in patients with mild cognitive impairment and small vessel disease: The Vascular Mild Cognitive Impairment (VMCI)-Tuscany study. Journal of The Neurological Sciences, 368, 195–202.CrossRefGoogle ScholarPubMed
van den Berg, E., Kessels, R.P., Kappelle, L.J., de Haan, E.H., Biessels, G.J., & Utrecht Diabetic Encephalopathy Study Group (2006). Type 2 diabetes, cognitive function and dementia: Vascular and metabolic determinants. Drugs of today (Barcelona, Spain: 1998), 42, 741–754.CrossRefGoogle ScholarPubMed
Vermeer, S.E., Prins, N.D., den Heijer, T., Hofman, A., Koudstaal, P.J., & Breteler, M.M.B. (2003). Silent brain infarcts and the risk of dementia and cognitive decline. New England Journal of Medicine, 348 (13), 1215–1222.CrossRefGoogle ScholarPubMed
Verney, S.P., Bennett, J., & Hamilton, J.M. (2015). Cultural considerations in the neuropsychological assessment of American Indians/Alaska Natives, In Ferraro, F.R. (Ed.), Minority and cross-cultural aspects of neuropsychological assessment (2nd ed.). Lisse, Netherlands: Taylor & Francis.Google Scholar
Verney, S.P., Suchy-Dicey, A., Cholerton, B., Calhoun, D., Nelson, L., Montine, T., Ali, T., Longstreth, W.J., & Buchwald, D. (in press). The associations among sociocultural factors and neuropsychological functioning in older American Indians: The Strong Heart Study. Neuropsychology, 2019 Jul 25 [Epub ahead of print] PMID: 31343235.CrossRefGoogle Scholar
Warren, M.W., Weiner, M.F., Rossetti, H.C., McColl, R., Peshock, R., & King, K.S. (2015). Cognitive impact of lacunar infarcts and white matter hyperintensity volume. Dementia and Geriatric Cognitive Disorders Extra, 5, 170–175.CrossRefGoogle ScholarPubMed
Wechsler, D. (2008). Wechsler adult intelligence scale (4th ed.). San Antonio, TX: Pearson.Google Scholar
Wisdom, N.M., Mignogna, J., & Collins, R.L. (2012). Variability in Wechsler Adult Intelligence Scale-IV subtest performance across age. Archives of Clinical Neuropsychology, 27, 389–397.CrossRefGoogle ScholarPubMed
Xu, X., Chan, Q.L., Hilal, S., Goh, W.K., Ikram, M.K., Wong, T.Y., Cheng, C.Y., Chen, C.L., & Venketasubramanian, N. (2017). Cerebral microbleeds and neuropsychiatric symptoms in an elderly Asian cohort. J Neurol Neurosurg Psychiatry, 88, 7–11.CrossRefGoogle Scholar
Yamashiro, K., Tanaka, R., Okuma, Y., Shimura, H., Ueno, Y., Miyamoto, N., Urabe, T., & Hattori, N. (2014). Cerebral microbleeds are associated with worse cognitive function in the nondemented elderly with small vessel disease. Cerebrovascular Diseases Extra, 4, 212–220.CrossRefGoogle ScholarPubMed
Yamawaki, M., Wada-Isoe, K., Yamamoto, M., Nakashita, S., Uemura, Y., Takahashi, Y., Nakayama, T., & Nakashima, K. (2015). Association of cerebral white matter lesions with cognitive function and mood in Japanese elderly people: A population-based study. Brain Behav, 5, e00315.CrossRefGoogle ScholarPubMed
Zahodne, L., Manly, J.J., Narkhede, A., Griffith, E.Y., DeCarli, C., Schupf, N.S., Mayeux, R., & Brickman, A.M. (2015). Structural MRI predictors of late-life cognition differ across African Americans, Hispanics, and Whites. Current Alzheimer Research, 12, 632–639.CrossRefGoogle ScholarPubMed
Zhang, Y., Galloway, J.M., Welty, T.K., Wiebers, D.O., Whisnant, J.P., Devereaux, R.B., Kizer, J.R., Howard, B.V., Cowan, L.D., Yeh, J., Howard, W.J., Wang, W., Best, L., & Lee, E.T. (2008). Incidence and Risk Factors for Stroke in American Indians: The Strong Heart Study. Circulation, 118, 1577–1584.CrossRefGoogle ScholarPubMed
Zhao, Q., Roberts, R.O., Ding, D., Cha, R., Guo, Q., Meng, H., Luo, J., Machulda, M.M., Shane Pankratz, V., Wang, B., Christianson, T.J., Aakre, J.A., Knopman, D.S., Boeve, B.F., Hong, Z., Petersen, R.C., Shanghai Aging Study (SAS), & Mayo Clinic Study of Aging (MCSA) (2015). Diabetes is associated with worse executive function in Both Eastern and Western populations: Shanghai Aging Study and Mayo Clinic Study of Aging. Journal of Alzheimer's Disease, 47, 167–176.CrossRefGoogle ScholarPubMed
Supplementary material: File

Suchy-Dicey et al. supplementary material

Suchy-Dicey et al. supplementary material 1

Download Suchy-Dicey et al. supplementary material(File)
File 3.7 MB