Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-29T09:01:10.718Z Has data issue: false hasContentIssue false
  • English
  • Français

Change in Cognitive Performance From Midlife Into Old Age: Findings from the Midlife in the United States (MIDUS) Study

Published online by Cambridge University Press:  18 July 2018

Matthew L. Hughes ,
Stefan Agrigoroaei ,
Minjeong Jeon ,
Molly Bruzzese  and
Margie E. Lachman
Matthew L. Hughes
Affiliation:
Department of Psychology, Brandeis University, Waltham, Massachusetts
Stefan Agrigoroaei
Affiliation:
Psychological Sciences Research Institute, Université catholique de Louvain, Belgium
Minjeong Jeon
Affiliation:
Graduate School of Education & Information Studies, University of California, Los Angeles, Los Angeles, California
Molly Bruzzese
Affiliation:
Department of Psychology, Brandeis University, Waltham, Massachusetts
Margie E. Lachman*
Affiliation:
Department of Psychology, Brandeis University, Waltham, Massachusetts
*
Correspondence and reprint requests to: Margie E. Lachman, Department of Psychology, MS 062, Brandeis University, Waltham, MA 02453. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Objectives: A substantial body of research has documented age-related declines in cognitive abilities among adults over 60, yet there is much less known about changes in cognitive abilities during midlife. The goal was to examine longitudinal changes in multiple cognitive domains from early midlife through old age in a large national sample, the Midlife in the United States (MIDUS) study. Methods: The Brief Test of Adult Cognition by Telephone (BTACT) was administered on two occasions (MIDUS 2, MIDUS 3), an average of 9 years apart. At MIDUS 3, those with the cognitive assessment (N=2518) ranged in age from 42 to 92 years (M=64.30; SD=11.20) and had a mean education of 14.68 years (SD=2.63). The BTACT includes assessment of key aging-sensitive cognitive domains: immediate and delayed free recall, number series, category fluency, backward digit span, processing speed, and reaction time for attention switching and inhibitory control, which comprise two factors: episodic memory and executive functioning. Results: As predicted, all cognitive subtests and factors showed very small but significant declines over 9 years, with differences in the timing and extent of change. Processing speed showed the earliest and steepest decrements. Those with higher educational attainment scored better on all tests except reaction time. Men had better executive functioning and women performed better on episodic memory. Conclusions: Examining cognitive changes in midlife provides opportunities for early detection of cognitive impairments and possibilities for preventative interventions. (JINS, 2018, 24, 805–820)

Keywords

Middle agedCognitive agingSex differencesEducational statusLongitudinal studiesCognitive function
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 24 , Issue 8 , September 2018 , pp. 805 - 820
Copyright
Copyright © The International Neuropsychological Society 2018 

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

Agrigoroaei, S., & Lachman, M.E. (2011). Cognitive functioning in midlife and old age: Combined effects of psychosocial and behavioral factors. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 66B, i130–i140. doi:10.1093/geronb/gbr017 Google Scholar
Alley, D., Suthers, K., & Crimmins, E. (2007). Education and cognitive decline in older Americans results from the AHEAD sample. Research on Aging, 29, 73–94. doi:10.1177/0164027506294245 Google Scholar
Alosco, M.L., Kasimis, A.B., Stamm, J.M., Chua, A.S., Baugh, C.M., Daneshvar, D.H., & Au, R. (2018). Age of first exposure to American football and long-term neuropsychiatric and cognitive outcomes. Translational Psychiatry, 7, e1236. doi:1-.1038/tp.2017.197 Google Scholar
Anstey, K.J., Sargent-Cox, K., Garde, E., Cherbuin, N., & Butterworth, P. (2014). Cognitive development over 8 years in midlife and its association with cardiovascular risk factors. Neuropsychology, 28, 653–655. doi:10.1037/neu0000044 Google Scholar
Baltes, P.B., Lindenberger, U., & Staudinger, U.M. (2006). Life span theory in developmental psychology. In W. Damon & R.M. Lerner (Eds.), Handbook of child psychology, Vol. I, Theoretical models of human development (6th ed., pp. 569–664). New York: Wiley.Google Scholar
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48. doi:10.18637/jss.v067.i01 Google Scholar
Bielak, A.A.M., Hughes, T.F., Small, B.J., & Dixon, R.A. (2007). It’s never too late to engage in lifestyle activities: Significant concurrent but not change relationships between lifestyle activities and cognitive speed. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 62B, P331–P339. doi:10.1093/geronb/62.6.P331 Google Scholar
Brim, O.G., Ryff, C.D., & Kessler, R.C. (2004). The MIDUS National Survey: An overview. In O.G. Brim, C.D. Ryff & R.C. Kessler (Eds.), How healthy are we?: A national study of well-being at midlife (pp. 1–34). Chicago, IL: University of Chicago Press.Google Scholar
Bruce, M.L., Hoff, R.A., Jacobs, S.C., & Leaf, P.J. (1995). The effects of cognitive impairment on 9-year mortality in a community sample. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 50B, P289–P296. doi:10.1093/geronb/50B.6.P289 Google Scholar
Brunner, E.J., Welch, C.A., Shipley, M.J., Ahmadi-Abhari, S., Singh-Manoux, A., & Kivimäki, M. (2017). Midlife risk factors for impaired physical and cognitive functioning at older ages: A cohort study. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences, 72, 237–242. doi:10.1093/gerona/glw092 Google Scholar
Cagney, K.A., & Lauderdale, D.S. (2002). Education, wealth, and cognitive function in later life. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 57B, P163–P172. doi:10.1093/geronb/57.2.P163 Google Scholar
Caselli, R.J., Dueck, A.C., Locke, D.E., Baxter, L.C., Woodruff, B.K., & Geda, Y.E. (2015). Sex-based memory advantages and cognitive aging: A challenge to the cognitive reserve construct? Journal of the International Neuropsychological Society, 21, 95–104. doi:10.1017/S1355617715000016 Google Scholar
Cook, N.R., Albert, M.S., Berkman, L.F., Blazer, D., Taylor, J.O., & Hennekens, C.H. (1995). Interrelationships of peak expiratory flow rate with physical and cognitive function in the elderly: MacArthur Foundation studies of aging. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 50A, M317–M323. doi:10.1093/gerona/50A.6.M317 Google Scholar
Craik, F.I.M., & Salthouse, T.A. (Eds.) (2008). The handbook of aging and cognition (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Dams-O’Connor, K., Sy, K.T., Landau, A., Bodien, Y., Dikmen, S., Felix, E.R., & Whiteneck, G. (2018). The feasibility of telephone-administered cognitive testing in individuals 1 and 2 years after inpatient rehabilitation for traumatic brain injury. Journal of Neurotrauma, 35, 1138–1145.Google Scholar
Davis, D., Bendayan, R., Terrera, G.M., Hardy, R., Richards, M., & Kuh, D. (2017). Decline in search speed and verbal memory over 26 years of midlife in a British birth cohort. Neuroepidemiology, 49, 121–128. doi:10.1159/000481136 Google Scholar
Elias, M.R., Elias, P.K., Robbins, M.A., Wolf, P.A., & D’Agostino, R.B. (2000). Cardiovascular risk factors and cognitive functioning: An epidemiological perspective. In S.R. Waldstein & M.F. Elias (Eds.), Neuropsychology of cardiovascular disease. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Evans, D.A., Beckett, L.A., Albert, M.S., Herbert, L.E., Scherr, P.A., Funkenstein, H.H., & Taylor, J.O. (1993). Level of education and change in cognitive function in a community population of older persons. Annals of Epidemiology, 3, 71–77. doi:10.1016/1047-2797(93)90012-S Google Scholar
Farias, S.T., Park, L.K., Harvey, D.J., Simon, C., Reed, B.R., Carmichael, O., & Mungas, D. (2013). Everyday cognition in older adults: Associations with neuropsychological performance and structural brain imaging. Journal of the International Neuropsychological Society, 19, 430–441. doi:10.1017/S135561771200160 Google Scholar
Fastenau, P.S., Denburg, N.L., & Hufford, B.J. (1999). Adult norms for the Rey-Osterrieth Complex Figure Test and for supplemental recognition and matching trials from the Extended Complex Figure Test. The Clinical Neuropsychologist, 13, 30–47. doi:10.1076/clin.13.1.30.1976 Google Scholar
Fisher, G.G., Stachowski, A., Infurna, F.J., Faul, J.D., Grosch, J., & Tetrick, L.E. (2014). Mental work demands, retirement, and longitudinal trajectories of cognitive functioning. Journal of Occupational Health Psychology, 19, 231–242. doi:10.1037/a0035724 Google Scholar
Fitzmaurice, G.M., Laird, N.M., & Ware, J.H. (2011). Applied longitudinal analysis. Hoboken, NJ: Wiley.Google Scholar
Gallagher, C., & Burke, T. (2007). Age, gender and IQ effects on the Rey-Osterrieth Complex Figure Test. British Journal of Clinical Psychology, 46, 35–45. doi:10.1348/014466506X106047 Google Scholar
Ganguli, M., Ratcliff, G., Huff, F.J., Belle, S., Kancel, M.J., Fischer, L., & Kuller, L.H. (1991). Effects of age, gender, and education on cognitive tests in a rural elderly community sample: Norms from the Monongahela Valley Independent Elders Survey. Neuroepidemiology, 10, 42–52. doi:10.1159/000110246 Google Scholar
Ghisletta, P., Rabbitt, P., Lunn, M., & Lindenberger, U. (2012). Two thirds of the age-based changes in fluid and crystallized intelligence, perceptual speed, and memory in adulthood are shared. Intelligence, 40, 260–268. doi:10.1016/j.intell.2012.02.008 Google Scholar
Greiner, P.A., Snowdon, D.A., & Schmitt, F.A. (1996). The loss of independence in activities of daily living: The role of low normal cognitive function in elderly nuns. American Journal of Public Health, 86, 62–66. doi:10.2105/AJPH.86.1.62 Google Scholar
Gross, A.L., Benitez, A., Shih, R., Bangen, K.J., Glymour, M.M.M., Sachs, B., & Manly, J.J. (2015). Predictors of retest effects in a longitudinal study of cognitive aging in a diverse community-based sample. Journal of the International Neuropsychological Society, 21, 506–518. doi:10.1017/S1355617715000508 Google Scholar
Hatch, S.L., Feinstein, L., Link, B.G., Wadsworth, M.E.J., & Richards, M. (2007). The continuing benefits of education: Adult education and midlife cognitive ability in the British 1946 birth cohort. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 62, S404–S414. doi:10.1093/geronb/62.6.S404 Google Scholar
Hedges, L.V. (2007). Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics, 32, 341–370. doi:10.3102/1076998606298043 Google Scholar
Herzog, A.R., & Wallace, R.B. (1997). Measures of cognitive functioning in the AHEAD study. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 52B (Special Issue), 37–48. doi:10.1093/geronb/52B.Special_Issue.37 Google Scholar
Hofer, S., & Alwin, D. (Eds.) (2008). Handbook on cognitive aging: Interdisciplinary perspectives. Thousand Oaks, CA: Sage Publishers.Google Scholar
Horn, J.L., & McArdle, J.J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18, 117–144. doi:10.1080/03610739208253916 Google Scholar
Hultsch, D.F., Hertzog, C., & Dixon, R.A. (1990). Ability correlates of memory performance in adulthood and aging. Psychology and Aging, 5, 356–368. doi:10.1037/0882-7974.5.3.356 Google Scholar
Idler, E.L., & Benyamini, Y. (1997). Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior, 38, 21–37.Google Scholar
Isiordia, M., & Ferrer, E. (2016). Curve of factors model: A latent growth modeling approach for educational research. Educational and Psychological Measurement, 78, 203–231. doi:10.1177/0013164416677143 Google Scholar
Jorm, A.F., Anstey, K.J., Christensen, H., & Rodgers, B. (2004). Gender differences in cognitive abilities: The mediating role of health state and health habits. Intelligence, 32, 7–23. doi:10.1016/j.intell.2003.08.001 Google Scholar
Jurado, M.B., & Rosselli, M. (2007). The elusive nature of executive functions: A review of our current understanding. Neuropsychology Review, 17, 213–233. doi:10.1007/s11065-007-9040-z Google Scholar
Karlamangla, A.S., Lachman, M.E., Han, W.J., Huang, M.H., & Greendale, G.A. (2017). Evidence for cognitive aging in midlife women: Study of women's health across the nation. PLoS One, 12, e0169008. doi:10.1371/journal.pone.0169008 Google Scholar
Karlamangla, A.S., Miller-Martinez, D., Aneshensel, C.S., Seeman, T.E., Wight, R.G., & Chodosh, J. (2009). Trajectories of cognitive function in late life in the United States: Demographic and socioeconomic predictors. American Journal of Epidemiology, 170, 331–342. doi:10.1093/aje/kwp154 Google Scholar
Karlamangla, A.S., Singer, B.S., Williams, D.R., Schwartz, J.E., Matthews, K.A., Kiefe, C.I., & Seeman, T.E. (2005). Impact of socioeconomic status on longitudinal accumulation of cardiovascular risk in young adults: The CARDIA Study. Social Science and Medicine, 60, 999–1015. doi:10.1016/j.socscimed.2004.06.056 Google Scholar
Lachman, M.E. (2015). Mind the gap in the middle: A call to study midlife. Research in Human Development, 12, 327–334. doi:10.1080/15427609.2015.1068048 Google Scholar
Lachman, M.E., Agrigoroaei, S., Murphy, C., & Tun, P.A. (2010). Frequent cognitive activity compensates for education differences in episodic memory. American Journal of Geriatric Psychiatry, 18, 4–10. doi:10.1097/JGP.0b013e3181ab8b62 Google Scholar
Lachman, M.E., & Tun, P.A. (2008). Cognitive testing in large-scale surveys: Assessment by telephone. In S. Hofer & D. Alwin (Eds.), Handbook on cognitive aging: Interdisciplinary perspectives (pp. 506–522). Thousand Oaks, CA: Sage Publishers.Google Scholar
Lachman, M.E., Agrigoroaei, S., Tun, P.A., & Weaver, S.L. (2014). Monitoring cognitive functioning: Psychometric properties of the Brief Test of Adult Cognition by Telephone. Assessment, 21, 404–417. doi:10.1177/1073191113508807 Google Scholar
Lee, S., Kawachi, I., Berkman, L.F., & Grodstein, F. (2003). Education, other socioeconomic indicators, and cognitive function. American Journal of Epidemiology, 157, 712–720. doi:10.1093/aje/kwg042 Google Scholar
Lenehan, M.E., Summers, M.J., Saunders, N.L., Summers, J.J., & Vickers, J.C. (2015). Relationship between education and age‐related cognitive decline: A review of recent research. Psychogeriatrics, 15, 154–162. doi:10.1111/psyg.12083 Google Scholar
Letenneur, L., Launer, L.J., Andersen, K., Dewey, M.E., Ott, A., Copeland, J.R., & Hofman, A. (2000). Education and the risk for Alzheimer’s Disease: Sex makes a difference. American Journal of Epidemiology, 151, 1064–1071. doi:10.1093/oxfordjournals.aje.a010149 Google Scholar
Lindenberger, U., & Baltes, P.B. (1994). Sensory functioning and intelligence in old age: A strong connection. Psychology and Aging, 9, 339–355. doi:10.1037/0882-7974.9.3.339 Google Scholar
Lyketsos, C.G., Chen, L., & Anthony, J.C. (1999). Cognitive decline in adulthood: An 11.5 year follow-up of the Baltimore Epidemiological Catchment Area Study. American Journal of Psychiatry, 156, 58–65. doi:10.1176/ajp.156.1.58 Google Scholar
MacCallum, R.C., Kim, C., Malarkey, W.B., & Kiecolt-Glaser, J.K. (1997). Studying multivariate change using multilevel models and latent curve models. Multivariate Behavioral Research, 32, 215–253. doi:10.1207/s15327906mbr3203_1 Google Scholar
McArdle, J.J. (2011). Longitudinal dynamic analyses of cognition in the Health and Retirement Study panel. Advances in Statistical Analysis, 95, 453–480. doi:10.1007/s10182–011-0168-z Google Scholar
McCabe, D.P., Roediger, H.L. III, McDaniel, M.A., Balota, D.A., & Hambrick, D.Z. (2010). The relationship between working memory capacity and executive functioning: Evidence for a common executive attention construct. Neuropsychology, 24, 222–243. doi:10.1037/a0017619 Google Scholar
Miller, M.E., Rejeski, W.J., Reboussin, B.A., Ten Have, T.R., & Ettinger, W.H. (2000). Physical activity, functional limitations, and disability in older adults. Journal of the American Geriatrics Society, 48, 1264–1272. doi:10.1111/j.1532-5415.2000.tb02600.x Google Scholar
Moritz, D.J., Kasl, S.V., & Berkman, L.F. (1995). Cognitive functioning and the incidence of limitations in activities of daily living in an elderly community sample. American Journal of Epidemiology, 141, 41–49. doi:10.1093/oxfordjournals.aje.a117344 Google Scholar
Murden, R.A., McRae, R.D., Kaner, S., & Bucknam, M.E. (1991). Mini-Mental State Exam scores vary with education in blacks and whites. Journal of American Geriatrics Society, 39, 149–155. doi:10.1111/j.1532-5415.1991.tb01617.x Google Scholar
Muthén, L.K., & Muthén, B.O. (2008). Mplus (Version 5.1). Los Angeles, CA: Muthén & Muthén.Google Scholar
Park, D.C., Lautenschlager, G., Hedden, T., Davidson, N.S., Smith, A.D., & Smith, P.K. (2002). Models of visuospatial and verbal memory across the adult life span. Psychology and Aging, 17, 299–320. doi:10.1037//0882-7974.17.2.299 Google Scholar
Piccinin, A., & Hofer, S.M. (2008). Integrative analysis of longitudinal studies on aging: Collaborative research networks, meta-analysis, and optimizing future studies. In S. Hofer & D. Alwin (Eds.), Handbook on cognitive aging: Interdisciplinary perspectives (pp. 446–476). Thousand Oaks, CA: Sage Publishers.Google Scholar
Rabbitt, P., Donlan, C., Watson, P., McInnes, L., & Bent, N. (1995). Unique and interactive effects of depression, age, socioeconomic advantage, and gender on cognitive performance of normal healthy older people. Psychology and Aging, 10, 307–313. doi:10.1037/0882-7974.10.3.307 Google Scholar
Radler, B.T., & Ryff, C.D. (2010). Who participates? Accounting for longitudinal retention in the MIDUS national study of health and well-being. Journal of Aging and Health, 22, 307–331. doi:10.1177/0898264309358617 Google Scholar
Rentz, D.M., Weiss, B.K., Jacobs, E.G., Cherkerzian, S., Klibanski, A., Remington, A., & Goldstein, J.M. (2017). Sex differences in episodic memory in early midlife: Impact of reproductive aging. Menopause, 24, 400–408. doi:10.1097/GME.0000000000000771 Google Scholar
Rönnlund, M., & Nilsson, L.G. (2006). Adult life-span patterns in WAIS-R Block Design performance: Cross-sectional versus longitudinal age gradients and relations to demographic factors. Intelligence, 34, 63–78. doi:10.1016/j.intell.2005.06.004 Google Scholar
Royall, D.R., Lauterbach, E.C., Cummings, J.L., Reeve, A., Rummans, T.A., Kaufer, D.I., & Coffey, C.E. (2002). Executive control function: A review of its promise and challenges for clinical research. A report from the Committee on Research of the American Neuropsychiatric Association. The Journal of Neuropsychiatry and Clinical Neurosciences, 14, 377–405. doi:10.1176/jnp.14.4.377 Google Scholar
Royall, D.R., Palmer, R., Chiodo, L.K., & Polk, M.J. (2005). Normal rates of cognitive change in successful aging: The freedom house study. Journal of the International Neuropsychological Society, 11, 899–909. doi:10.1017/S135561770505109X Google Scholar
Ryan, J.J., Sattler, J.M., & Lopez, S.J. (2000). Age effects on Wechsler adult intelligence scale-III subtests. Archives of Clinical Neuropsychology, 15, 311–317. doi:10.1016/S0887-6177(99)00019-0 Google Scholar
Salthouse, T.A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403–428. doi:10.1037/0033-295X.103.3.403 Google Scholar
Salthouse, T.A. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society, 16, 754–760. doi:10.1017/S1355617710000706 Google Scholar
Salthouse, T.A., Schroeder, D.H., & Ferrer, E. (2004). Estimating retest effects in longitudinal assessments of cognitive functioning in adults between 18 and 60 years of age. Developmental Psychology, 40, 813–822. doi:10.1037/0012-1649.40.5.813 Google Scholar
Sawilowsky, S.S. (2009). New effect size rules of thumb. Journal of Modern Applied Statistical Methods, 8, 597–599.Google Scholar
Scarmeas, N., Albert, S.M., Manly, J.J., & Stern, Y. (2006). Education and rates of cognitive decline in incident Alzheimer’s disease. Journal of Neurology, Neurosurgery, & Psychiatry, 77, 308–316. doi:10.1136/jnnp.2005.072306 Google Scholar
Schaie, K.W. (1994). The course of adult intellectual development. American Psychologist, 49, 304–313. doi:10.1037/0003-066X.49.4.304 Google Scholar
Schaie, K.W. (1996). Intellectual development in adulthood: The Seattle Longitudinal Study. New York: Cambridge University Press.Google Scholar
Seeman, T.E., McEwen, B.S., Singer, B.H., Albert, M.S., & Rowe, J.W. (1997). Increase in urinary cortisol excretion and memory declines: MacArthur studies of successful aging. Journal of Clinical Endocrinology and Metabolism, 82, 2458–2465. doi:10.1210/jcem.82.8.4173 Google Scholar
Singer, T., Verhaeghen, P., Ghisletta, P., Lindenberger, U., & Baltes, P.B. (2003). The fate of cognition in very old age: Six-year longitudinal findings in the Berlin Aging Study (BASE). Psychology and Aging, 18, 318–331. doi:10.1037/0882-7974.18.2.318 Google Scholar
Singh-Manoux, A., Kivimaki, M., Glymour, M.M., Elbaz, A., Berr, C., Ebmeier, K.P., & Dugravot, A. (2012). Timing of onset of cognitive decline: Results from Whitehall II prospective cohort study. BMJ: British Medical Journal, 344, d7622. doi:10.1136/bmj.d7622 Google Scholar
Soederberg Miller, L.M., & Lachman, M.E. (2000). Cognitive performance and the role of control beliefs in midlife. Aging, Neuropsychology, and Cognition, 7, 69–85. doi:10.1076/1382-5585(200006)7:2;1-U;FT069 Google Scholar
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448–460. doi:10.1017/S1355617702813248 Google Scholar
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47, 2015–2028. doi:10.1016/j.neuropsychologia.2009.03.004 Google Scholar
Stern, Y. (2012). Cognitive reserve in ageing and Alzheimer’s disease. Lancet Neurology, 11, 1006–1012.Google Scholar
Sternberg, R.J., Grigorenko, H., & Oh, S. (2001). The development of intelligence at midlife. In M.E. Lachman (Ed.), Handbook of midlife development (pp. 217–247). New York: John Wiley & Sons.Google Scholar
Stewart, R., & Liolitsa, D. (1999). Type 2 diabetes mellitus, cognitive impairment and dementia. Diabetic Medicine, 16, 93–112. doi:10.1046/j.1464-5491.1999.00027.x Google Scholar
Swan, G.E., Carmelli, D., & LaRue, A. (1995). Performance on the digit-symbol substitution test and 5-year mortality in the Western Collaborative Group Study. American Journal of Epidemiology, 141, 32–40. doi:10.1093/oxfordjournals.aje.a117342 Google Scholar
Tucker, A.M., & Stern, Y. (2011). Cognitive reserve in aging. Current Alzheimer Research, 8, 354–360. doi:10.2174/156720511795745320 Google Scholar
Tun, P.A., & Lachman, M.E. (2006). Telephone assessment of cognitive function in adulthood: The Brief Test of Adult Cognition by Telephone (BTACT). Age and Ageing, 35, 629–632. doi:10.1093/ageing/afl095 Google Scholar
Tun, P.A., & Lachman, M.E. (2008). Age differences in reaction time in a national telephone sample of adults: Task complexity, education, and gender matter. Developmental Psychology, 44, 1421–1429. doi:10.1037/a0012845 Google Scholar
Turrell, G., Lynch, J.W., Kaplan, G.A., Everson, S.A., Helkala, E.L., Kauhanen, J., &Salonen, J.T. (2002). Socioeconomic position across the lifecourse and cognitive function in late middle age. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 57, S43–S51. doi:10.1093/geronb/57.1.S43 Google Scholar
Uhlmann, R.F., & Larson, E.B. (1991). Effect of education on the Mini-Mental State Examination as a screening test for dementia. Journal of American Geriatrics Society, 39, 876–880. doi:10.1111/j.1532-5415.1991.tb04454.x Google Scholar
Vandenberg, R.J., & Lance, C.E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 2, 4–69. doi:10.1177/109442810031002 Google Scholar
Verbeke, G., & Molenberghs, G. (2000). Linear mixed models for longitudinal data. New York: Springer.Google Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale-III (WAIS-III) manual. New York, NY: The Psychological Corporation.Google Scholar
Wiederholt, W.C., Chan, D., Butters, N.M., Salmon, D.P., Kritz-Silverstein, D., & Barrett-Connor, E. (1993). Effects of age, gender, and education on selected neuropsychological tests in an elderly community cohort. Journal of the American Geriatrics Society, 41, 639–647. doi:10.1111/j.1532-5415.1993.tb06738.x Google Scholar
Willis, S.L. (1996). Assessing everyday competence in the cognitively challenged elderly. In M.A. Smyer, K.W. Schaie & M.B. Kapp (Eds.), Older adults' decision making and the law (pp. 87–127). New York: Springer.Google Scholar
Willis, S.L., & Boron, J.B. (2008). Midlife cognition: The association with personality and cognition and risk of cognitive impairment. In S. Hofer & D. Alwin (Eds.), Handbook of aging and cognition (pp. 647–660). Thousand Oaks, CA: Sage.Google Scholar
Willis, S.L., & Schaie, K.W. (1999). Intellectual functioning in midlife. In S.L. Willis & J.D. Reid (Eds.), Life in the middle (pp. 233–247). San Diego, CA: Academic Press.Google Scholar
Willis, S.L., & Schaie, K.W. (2006). Cognitive functioning in the baby boomers: Longitudinal and cohort effects. In S.K. Whitbourne & S.L. Willis (Eds.), The baby boomers grow up (pp. 205–234). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Wilson, R.S., Hebert, L.E., Scherr, P.A., Barnes, L.L., De Leon, C.M., & Evans, D.A. (2009). Educational attainment and cognitive decline in old age. Neurology, 72, 460–465. doi:10.1212/01.wnl.0000341782.71418.6c Google Scholar
Wingfield, A., Tun, P.A., & McCoy, S.L. (2005). Hearing loss in adulthood: What it is and how it interacts with cognitive performance. Current Directions in Psychological Science, 14, 144–148. doi:10.1111/j.0963-7214.2005.00356.x Google Scholar
Wu, W., Brickman, A.M., Luchsinger, J., Ferrazzano, P., Pichiule, P., Yoshita, M., & Small, S.A. (2008). The brain in the age of old: The hippocampal formation is targeted differentially by diseases of late life. Annals of Neurology, 64, 698–706. doi:10.1002/ana.21557 Google Scholar
Yeung, S.E., Fischer, A.L., & Dixon, R.A. (2009). Exploring effects of type 2 diabetes on cognitive functioning in older adults. Neuropsychology, 23, 1–9. doi:10.1037/a0013849 Google Scholar
Zahodne, L.B., Glymour, M.M., Sparks, C., Bontempo, D., Dixon, R.A., MacDonald, S.W.,& Manly, J.J. (2011). Education does not slow cognitive decline with aging: 12-year evidence from the Victoria Longitudinal Study. Journal of the International Neuropsychological Society, 17, 1039–1046. doi:10.1017/S1355617711001044 Google Scholar
Zimprich, D., & Mascherek, A. (2010). Five views of a secret: Does cognition change during middle adulthood? European Journal of Ageing, 7, 135–146. doi:10.1007/s10433-010-0161-5 Google Scholar
Supplementary material: File

Hughes et al. supplementary material

Tables S1-S2 and Figures S1-S2

Download Hughes et al. supplementary material(File)
File 448.4 KB