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Metabolic Syndrome and Physical Performance: The Moderating Role of Cognition among Middle-to-Older-Aged Adults

Published online by Cambridge University Press:  10 August 2020

Elisa F. Ogawa*
Affiliation:
New England Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA, USA
Elizabeth Leritz
Affiliation:
New England Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA, USA Neuroimaging Research for Veterans Center, Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System, Boston, MA, USA Harvard Medical School, Boston, MA, USA
Regina McGlinchey
Affiliation:
New England Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA, USA Neuroimaging Research for Veterans Center, Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System, Boston, MA, USA Harvard Medical School, Boston, MA, USA
William Milberg
Affiliation:
New England Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA, USA Neuroimaging Research for Veterans Center, Translational Research Center for TBI and Stress Disorders, VA Boston Healthcare System, Boston, MA, USA Harvard Medical School, Boston, MA, USA
Jonathan F. Bean
Affiliation:
New England Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA, USA Harvard Medical School, Boston, MA, USA Spaulding Rehabilitation Hospital, Boston, MA, USA
*
*Correspondence and reprint requests to: Elisa F. Ogawa, PhD, New England Geriatric Research, Education and Clinical Center, VA Boston Healthcare System, Boston, MA 02130, USA. Tel: +1 857-364-4011. E-mail: [email protected]

Abstract

Objective:

Mobility limitation and cognitive decline are related. Metabolic syndrome (MetS), the clustering of three or more cardiovascular risk factors, is associated with decline in both mobility and cognition. However, the interrelationship among MetS, mobility, and cognition is unknown. This study investigated a proposed pathway where cognition moderates the relationship between MetS and Mobility.

Method:

Adults ages 45–90 years were recruited. MetS risk factors and mobility performance (Short Physical Performance Battery (SPPB) and gait speed) were evaluated. Cognition was assessed using a comprehensive neuropsychological battery. A factor analysis of neuropsychological test scores yielded three factors: executive function, explicit memory, and semantic/contextual memory. Multivariable linear regression models were used to examine the relationship among MetS, mobility, and cognition.

Results:

Of the 74 participants (average age 61 ± 9 years; 41% female; 69% White), 27 (36%) participants manifested MetS. Mean SPPB score was 10.9 ± 1.2 out of 12 and gait speed was 1.0 ± 0.2 m/s. There were no statistically significant differences in mobility by MetS status. However, increase in any one of the MetS risk factors was associated with decreased mobility performance after adjusting for age and gender (SPPB score: β (SE) -.17 (0.08), p < .05; gait speed: -.03 (.01), p < .01). Further adjusting for cognitive factors (SPPB score: explicit memory .31 (.14), p = .03; executive function 0.45 (0.13), p < .01; gait speed: explicit memory 0.04 (0.02), p = .03; executive function 0.06 (0.02), p < .01) moderated the relationships between number of metabolic risk factors and mobility.

Conclusion:

The relationship between metabolic risk factors and mobility may be moderated by cognitive performance, specifically through executive function and explicit memory.

Type
Regular Research
Copyright
Copyright © INS. Published by Cambridge University Press, 2020

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References

REFERENCES

Aguilar, M., Bhuket, T., Torres, S., Benny, L., & Wong, R.J. (2015). Prevalence of the metabolic syndrome in the United States, 2003–2012. The Journal of the American Medical Association, 313(19), 19731974. doi: 10.1001/jama.2015.4260CrossRefGoogle ScholarPubMed
Alberti, K.G., Eckel, R.H., Grundy, S.M., Zimmet, P.Z., Cleeman, J.I., Donato, K.A., … International Association for the Study of Obesity. (2009). Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation, 120(16), 16401645. doi: 10.1161/CIRCULATIONAHA.109.192644CrossRefGoogle Scholar
Alcorn, T., Hart, E., Smith, A.E., Feuerriegel, D., Stephan, B.C.M., Siervo, M., & Keage, H.A.D. (2019). Cross-sectional associations between metabolic syndrome and performance across cognitive domains: a systematic review. Applied Neuropsychology: Adult, 26(2), 186199. doi: 10.1080/23279095.2017.1363039CrossRefGoogle ScholarPubMed
Ambrose, A.F., Noone, M.L., Pradeep, V.G., Johnson, B., Salam, K.A., & Verghese, J. (2010). Gait and cognition in older adults: insights from the Bronx and Kerala. Annals of Indian Academy of Neurology, 13(Suppl 2), S99S103. doi: 10.4103/0972-2327.74253CrossRefGoogle ScholarPubMed
Beavers, K.M., Hsu, F.C., Houston, D.K., Beavers, D.P., Harris, T.B., Hue, T.F., … Health, A.B.C.S. (2013). The role of metabolic syndrome, adiposity, and inflammation in physical performance in the Health ABC Study. The Journals of Gerontology. Series A, Biological Sciences and Medical sciences, 68(5), 617623. doi: 10.1093/gerona/gls213CrossRefGoogle ScholarPubMed
Benedict, R.H.B., Schretlen, D., Groniner, L., Dobraski, M., & Shpritz, B. (1996). Revision of the brief visuospatial memory test: studies of normal performance, reliability, and validity. Psychological Assessment, 8(2), 145153.CrossRefGoogle Scholar
Blazer, D.G., Hybels, C.F., & Fillenbaum, G.G. (2006). Metabolic syndrome predicts mobility decline in a community-based sample of older adults. Journal of the American Geriatrics Society, 54(3), 502506. doi: 10.1111/j.1532-5415.2005.00607.xCrossRefGoogle Scholar
Bokura, H., Yamaguchi, S., Iijima, K., Nagai, A., & Oguro, H. (2008). Metabolic syndrome is associated with silent ischemic brain lesions. Stroke, 39(5), 16071609. doi: 10.1161/STROKEAHA.107.508630CrossRefGoogle ScholarPubMed
Bondi, M.W., & Kaszniak, A.W. (1991). Implicit and explicit memory in Alzheimer’s disease and Parkinson’s disease. Journal of Clinical and Experimental Neuropsychology, 13(2), 339358. doi: 10.1080/01688639108401048CrossRefGoogle ScholarPubMed
Brooks, B.L., Weaver, L.E., & Scialfa, C.T. (2006). Does impaired executive functioning differentially impact verbal memory measures in older adults with suspected dementia? Clinical Neuropsychology, 20(2), 230242. doi: 10.1080/13854040590947461CrossRefGoogle ScholarPubMed
Cohen, J. (1989). Statistical Power Analysis For The Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates Inc.Google Scholar
DeCoster, J. (1998). Overview of Factor Analysis. Retrieved from http://www.stat-help.com/notes.htmlGoogle Scholar
Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive Function System: Technical Manual. San Antonio, TX: Psychological Corporation.Google Scholar
Delis, D.C., Kramer, J.H., Kaplan, E., & Ober, B.A. (1987). California Verbal Learning Test: Adult version. Manual. San Antonio, TX: Psychological Corporation.Google Scholar
Doi, T., Makizako, H., Shimada, H., Park, H., Tsutsumimoto, K., Uemura, K., & Suzuki, T. (2013). Brain activation during dual-task walking and executive function among older adults with mild cognitive impairment: a fNIRS study. Aging Clinical and Experimental Research, 25(5), 539544. doi: 10.1007/s40520-013-0119-5CrossRefGoogle ScholarPubMed
Doi, T., Shimada, H., Makizako, H., Tsutsumimoto, K., Uemura, K., Anan, Y., & Suzuki, T. (2014). Cognitive function and gait speed under normal and dual-task walking among older adults with mild cognitive impairment. BMC Neurology, 14, 67. doi: 10.1186/1471-2377-14-67CrossRefGoogle ScholarPubMed
Everson-Rose, S.A., Paudel, M., Taylor, B.C., Dam, T., Cawthon, P.M., Leblanc, E., … Osteoporotic Fractures in Men Research Group. (2011). Metabolic syndrome and physical performance in elderly men: the osteoporotic fractures in men study. Journal of the American Geriatrics Society, 59(8), 13761384. doi: 10.1111/j.1532-5415.2011.03518.xCrossRefGoogle ScholarPubMed
Falkowski, J., Atchison, T., Debutte-Smith, M., Weiner, M.F., & O’Bryant, S. (2014). Executive functioning and the metabolic syndrome: a project FRONTIER study. Archives of Clinical Neuropsychology, 29(1), 4753. doi: 10.1093/arclin/act078CrossRefGoogle ScholarPubMed
Ford, E.S., Giles, W.H., & Dietz, W.H. (2002). Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. The Journal of the American Medical Association, 287(3), 356359.CrossRefGoogle ScholarPubMed
Guerra-Carrillo, B., Katovich, K., & Bunge, S.A. (2017). Does higher education hone cognitive functioning and learning efficacy? Findings from a large and diverse sample. PLoS One, 12(8), e0182276. doi: 10.1371/journal.pone.0182276CrossRefGoogle ScholarPubMed
Guralnik, J.M., Simonsick, E.M., Ferrucci, L., Glynn, R.J., Berkman, L.F., Blazer, D.G., … Wallace, R.B. (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), M8594. doi: 10.1093/geronj/49.2.m85CrossRefGoogle Scholar
Hair, J., Anderson, R., Tatham, R., & Black, W. (1998). Multivariate Data Analysis (5th ed.). Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
Hoaglin, D. C., & Welsch, R. E. (1978). The Hat Matrix in Regression and ANOVA. The American Statistician, 32(1), 1722.Google Scholar
Holtzer, R., Mahoney, J.R., Izzetoglu, M., Izzetoglu, K., Onaral, B., & Verghese, J. (2011). FNIRS study of walking and walking while talking in young and old individuals. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 66(8), 879887. doi: 10.1093/gerona/glr068CrossRefGoogle Scholar
Holtzer, R., Wang, C., & Verghese, J. (2012). The relationship between attention and gait in aging: facts and fallacies. Motor Control, 16(1), 6480. doi: 10.1123/mcj.16.1.64CrossRefGoogle ScholarPubMed
Iadecola, C. (2013). The pathobiology of vascular dementia. Neuron, 80(4), 844866. doi: 10.1016/j.neuron.2013.10.008CrossRefGoogle ScholarPubMed
Javanshiri, K., Waldo, M.L., Friberg, N., Sjovall, F., Wickerstrom, K., Haglund, M., & Englund, E. (2018). Atherosclerosis, hypertension, and diabetes in Alzheimer’s disease, vascular dementia, and mixed dementia: prevalence and presentation. Journal of Alzheimer’s Disease, 66(4), 1753. doi: 10.3233/JAD-189011CrossRefGoogle ScholarPubMed
Kaplan, E., Goodglass, H., & Weintraub, S. (1983). Boston Naming Test. Philadelphia, PA: Lea & Febiger.Google Scholar
Kazlauskaite, R., Janssen, I., Wilson, R., Appelhans, B., Evans, D., Arvanitakis, Z., … Kravitz, H. (2020). Is midlife metabolic syndrome associated with cognitive function change? The study of women’s health across the nation. The Journal of Clinical Endocrinology & Metabolism, 105(4), e1093e1105. doi:10.1210/clinem/dgaa067CrossRefGoogle Scholar
Leritz, E.C., McGlinchey, R.E., Kellison, I., Rudolph, J.L., & Milberg, W.P. (2011). Cardiovascular disease risk factors and cognition in the elderly. Current Cardiovascular Risk Reports, 5(5), 407412. doi: 10.1007/s12170-011-0189-xCrossRefGoogle ScholarPubMed
Lezak, M.D., Howieson, D.B., Loring, D.W., Hannay, H.J., & Fischer, J.S. (2004). Neuropsychological Assessment (4th ed.). New York, NY: Oxford University Press.Google Scholar
McGuinness, B., Barrett, S.L., Craig, D., Lawson, J., & Passmore, A.P. (2010). Executive functioning in Alzheimer’s disease and vascular dementia. International Journal of Geriatric Psychiatry, 25(6), 562568. doi: 10.1002/gps.2375Google ScholarPubMed
Mielke, M.M., Roberts, R.O., Savica, R., Cha, R., Drubach, D.I., Christianson, T., … Petersen, R. C. (2013). Assessing the temporal relationship between cognition and gait: slow gait predicts cognitive decline in the Mayo Clinic Study of Aging. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 68(8), 929937. doi: 10.1093/gerona/gls256CrossRefGoogle ScholarPubMed
Mirelman, A., Shema, S., Maidan, I., & Hausdorff, J.M. (2018). Gait. Handbook of Clinical Neurology, 159, 119134. doi: 10.1016/B978-0-444-63916-5.00007-0CrossRefGoogle ScholarPubMed
Montero-Odasso, M., Verghese, J., Beauchet, O., & Hausdorff, J.M. (2012). Gait and cognition: a complementary approach to understanding brain function and the risk of falling. Journal of the American Geriatrics Society, 60(11), 21272136. doi: 10.1111/j.1532-5415.2012.04209.xCrossRefGoogle ScholarPubMed
Okoro, C.A., Zhong, Y., Ford, E.S., Balluz, L.S., Strine, T.W., & Mokdad, A.H. (2006). Association between the metabolic syndrome and its components and gait speed among U.S. adults aged 50 years and older: a cross-sectional analysis. BMC Public Health, 6, 282. doi: 10.1186/1471-2458-6-282CrossRefGoogle ScholarPubMed
Pahor, M., Blair, S.N., Espeland, M., Fielding, R., Gill, T.M., Guralnik, J.M., … Studenski, S. (2006). Effects of a physical activity intervention on measures of physical performance: results of the lifestyle interventions and independence for Elders Pilot (LIFE-P) study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 61(11), 11571165. doi: 10.1093/gerona/61.11.1157Google ScholarPubMed
Parihar, R., Mahoney, J.R., & Verghese, J. (2013). Relationship of gait and cognition in the elderly. Current Translational Geriatrics and Experimental Gerontology Report, 2(3). doi: 10.1007/s13670-013-0052-7Google ScholarPubMed
Pedersen, M.M., Holt, N.E., Grande, L., Kurlinski, L.A., Beauchamp, M.K., Kiely, D.K., … Bean, J.F. (2014). Mild cognitive impairment status and mobility performance: an analysis from the Boston RISE study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 69(12), 15111518. doi: 10.1093/gerona/glu063CrossRefGoogle ScholarPubMed
Penninx, B.W., Nicklas, B.J., Newman, A.B., Harris, T.B., Goodpaster, B.H., Satterfield, S., … Health, A.B.C.S. (2009). Metabolic syndrome and physical decline in older persons: results from the Health, Aging And Body Composition Study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 64(1), 96102. doi: 10.1093/gerona/gln005CrossRefGoogle ScholarPubMed
Perera, S., Mody, S.H., Woodman, R.C., & Studenski, S.A. (2006). Meaningful change and responsiveness in common physical performance measures in older adults. Journal of the American Geriatrics Society, 54(5), 743749. doi: 10.1111/j.1532-5415.2006.00701.xCrossRefGoogle ScholarPubMed
Perl, D.P. (2010). Neuropathology of Alzheimer’s disease. Mount Sinai Journal of Medicine, 77(1), 3242. doi: 10.1002/msj.20157CrossRefGoogle ScholarPubMed
Poole, V.N., Wooten, T., Iloputaife, I., Milberg, W., Esterman, M., & Lipsitz, L.A. (2018). Compromised prefrontal structure and function are associated with slower walking in older adults. NeuroImage: Clinical, 20, 620626. doi: 10.1016/j.nicl.2018.08.017CrossRefGoogle ScholarPubMed
Portet, F., Brickman, A.M., Stern, Y., Scarmeas, N., Muraskin, J., Provenzano, F.A., … Akbaraly, T.N. (2012). Metabolic syndrome and localization of white matter hyperintensities in the elderly population. Alzheimer’s & Dementia, 8(5 Suppl), S8895 e81. doi: 10.1016/j.jalz.2011.11.007CrossRefGoogle ScholarPubMed
Prins, N.D., van Dijk, E.J., den Heijer, T., Vermeer, S.E., Jolles, J., Koudstaal, P.J., … Breteler, M.M. (2005). Cerebral small-vessel disease and decline in information processing speed, executive function and memory. Brain, 128(Pt 9), 20342041. doi: 10.1093/brain/awh553CrossRefGoogle ScholarPubMed
Rodriguez-Molinero, A., Herrero-Larrea, A., Minarro, A., Narvaiza, L., Galvez-Barron, C., Gonzalo Leon, N., … Sabater, J.B. (2019). The spatial parameters of gait and their association with falls, functional decline and death in older adults: a prospective study. Scientific Reports, 9(1), 8813. doi: 10.1038/s41598-019-45113-2CrossRefGoogle ScholarPubMed
Rouch, I., Trombert, B., Kossowsky, M.P., Laurent, B., Celle, S., Ntougou Assoumou, G., … Barthelemy, J.C. (2014). Metabolic syndrome is associated with poor memory and executive performance in elderly community residents: the PROOF study. The American Journal of Geriatric Psychiatry, 22(11), 10961104. doi: 10.1016/j.jagp.2014.01.005CrossRefGoogle ScholarPubMed
Schroeder, R.W., Twumasi-Ankrah, P., Baade, L.E., & Marshall, P.S. (2012). Reliable Digit Span: a systematic review and cross-validation study. Assessment, 19(1), 2130. doi: 10.1177/1073191111428764CrossRefGoogle ScholarPubMed
Schwartz, E.S., Erdodi, L., Rodriguez, N., Ghosh, J.J., Curtain, J.R., Flashman, L.A., & Roth, R.M. (2016). CVLT-II forced choice recognition trial as an embedded validity indicator: a systematic review of the evidence. Journal of the International Neuropsychological Society, 22(8), 851858. doi: 10.1017/S1355617716000746CrossRefGoogle Scholar
Schwarz, N.F., Nordstrom, L.K., Pagen, L.H.G., Palombo, D.J., Salat, D.H., Milberg, W.P., … Leritz, E.C. (2018). Differential associations of metabolic risk factors on cortical thickness in metabolic syndrome. NeuroImage: Clinical, 17, 98108. doi: 10.1016/j.nicl.2017.09.022CrossRefGoogle ScholarPubMed
Song, J., Lee, W.T., Park, K.A., & Lee, J.E. (2014). Association between risk factors for vascular dementia and adiponectin. BioMed Research International, 2014, 261672. doi: 10.1155/2014/261672CrossRefGoogle ScholarPubMed
Stuss, D.T., & Levine, B. (2002). Adult clinical neuropsychology: lessons from studies of the frontal lobes. Annual Review of Psychology, 53, 401433. doi: 10.1146/annurev.psych.53.100901.135220CrossRefGoogle ScholarPubMed
Tiehuis, A.M., van der Graaf, Y., Mali, W.P., Vincken, K., Muller, M., Geerlings, M.I., & Group, S.S. (2014). Metabolic syndrome, prediabetes, and brain abnormalities on mri in patients with manifest arterial disease: the SMART-MR study. Diabetes Care, 37(9), 25152521. doi: 10.2337/dc14-0154CrossRefGoogle ScholarPubMed
Toots, A.T.M., Taylor, M.E., Lord, S.R., & Close, J.C.T. (2019). Associations between gait speed and cognitive domains in older people with cognitive impairment. Journal of Alzheimer’s Disease, 71(s1), S15S21. doi: 10.3233/JAD-181173CrossRefGoogle ScholarPubMed
Vanderploeg, R.D., Schinka, J.A., & Retzlaff, P. (1994). Relationships between measures of auditory verbal learning and executive functioning. Journal of Clinical and Experimental Neuropsychology, 16(2), 243252. doi: 10.1080/01688639408402635CrossRefGoogle ScholarPubMed
Viscogliosi, G., Donfrancesco, C., Palmieri, L., & Giampaoli, S. (2017). The metabolic syndrome and 10-year cognitive and functional decline in very old men. A population-based study. Archives of Gerontology and Geriatrics, 70, 6266. doi: 10.1016/j.archger.2016.12.008CrossRefGoogle ScholarPubMed
Watson, N.L., Rosano, C., Boudreau, R.M., Simonsick, E.M., Ferrucci, L., Sutton-Tyrrell, K., … Health, A.B.C.S. (2010). Executive function, memory, and gait speed decline in well-functioning older adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 65(10), 10931100. doi: 10.1093/gerona/glq111CrossRefGoogle ScholarPubMed
Wechsler, D. (1945). Wechsler Memory Scale. San Antonio, TX: Psychological Corporation.Google Scholar
Wooten, T., Ferland, T., Poole, V., Milberg, W., McGlinchey, R., DeGutis, J., … Leritz, E. (2019). Metabolic risk in older adults is associated with impaired sustained attention. Neuropsychology, 33(7), 947955. doi: 10.1037/neu0000554CrossRefGoogle ScholarPubMed