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Effects of early-life environment and adulthood SES on cognitive change in a multiethnic cohort

Published online by Cambridge University Press:  07 March 2023

Oanh L. Meyer*
Affiliation:
Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, USA
Amal Harrati
Affiliation:
Mathematica, Oakland, CA, USA
Brandon E. Gavett
Affiliation:
School of Psychological Science, University of Western Australia, Crawley, WA, Australia
Sarah T. Farias
Affiliation:
Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, USA
Rachel A. Whitmer
Affiliation:
Department of Public Health Sciences, University of California, Davis, CA, USA
Keith Widaman
Affiliation:
School of Education, University of California, Riverside, CA, USA
Victoria Hoang
Affiliation:
Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, USA
Michele Tobias
Affiliation:
UC Davis DataLab, University of California, Davis, CA, USA
Dan Mungas
Affiliation:
Department of Neurology, University of California, Davis School of Medicine, Sacramento, CA, USA
*
Corresponding author: Oanh L. Meyer, email: olmeyer@ucdavis.edu

Abstract

Objectives:

Early-life socioeconomic status (SES) and adversity are associated with late-life cognition and risk of dementia. We examined the association between early-life SES and adversity and late-life cross-sectional cognitive outcomes as well as global cognitive decline, hypothesizing that adulthood SES would mediate these associations.

Methods:

Our sample (N = 837) was a racially and ethnically diverse cohort of non-Hispanic/Latino White (48%), Black (27%), and Hispanic/Latino (19%) participants from Northern California. Participant addresses were geocoded to the level of the census tract, and US Census Tract 2010 variables (e.g., percent with high school diploma) were extracted and combined to create a neighborhood SES composite. We used multilevel latent variable models to estimate early-life (e.g., parental education, whether participant ever went hungry) and adult (participant’s education, main occupation) SES factors and their associations with cross-sectional and longitudinal cognitive outcomes of episodic memory, semantic memory, executive function, and spatial ability.

Results:

Child and adult factors were strongly related to domain-specific cognitive intercepts (0.20–0.48 SD per SD of SES factor); in contrast, SES factors were not related to global cognitive change (0.001–0.01 SD per year per SD of SES factor). Adulthood SES mediated a large percentage (68–75%) of the total early-life effect on cognition.

Conclusions:

Early-life sociocontextual factors are more strongly associated with cross-sectional late-life cognitive performance compared to cognitive change; this effect is largely mediated through associations with adulthood SES.

Type
Research Article
Copyright
Copyright © INS. Published by Cambridge University Press, 2023

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References

Aartsen, M. J., Cheval, B., Sieber, S., Van der Linden, B. W., Gabriel, R., Courvoisier, D. S., Guessous, I., Burton-Jeangros, C., Blane, D., Ihle, A., Kliegel, M., & Cullati, S. (2019). Advantaged socioeconomic conditions in childhood are associated with higher cognitive functioning but stronger cognitive decline in older age. Proceedings of the National Academy of Sciences, 116, 5478. https://doi.org/10.1073/pnas.1807679116 CrossRefGoogle ScholarPubMed
Asparouhov, T., & Muthén, B. (2010). Bayesian analysis of latent variable models using Mplus (Technical report). Muthén & Muthén.Google Scholar
Barnes, L. L., Wilson, R. S., Everson-Rose, S. A., Hayward, M. D., Evans, D. A., & Mendes de Leon, C. F. (2012). Effects of early-life adversity on cognitive decline in older African Americans and whites. Neurology, 79, 2321. https://doi.org/10.1212/WNL.0b013e318278b607 CrossRefGoogle ScholarPubMed
Beck, A., Franz, C. E., Xian, H., Vuoksimaa, E., Tu, X., Reynolds, C. A., Panizzon, M.S., McKenzie, R.M., Lyons, M.J., Toomey, R., Jacobson, K.C., Hauger, R.L., Hatton, S.N., & Kremen, W. S. (2018). Mediators of the effect of childhood socioeconomic status on late midlife cognitive abilities: A four decade longitudinal study. Innovation in Aging, 2, igy003. https://doi.org/10.1093/geroni/igy003 CrossRefGoogle ScholarPubMed
Blom, G. (1958). Statistical estimates and transformed beta-variables. Wiley.Google Scholar
Brewster, P. W. H., Melrose, R. J., Marquine, M. J., Johnson, J. K., Napoles, A., MacKay-Brandt, A., Farias, S., Reed, B., & Mungas, D. (2014). Life experience and demographic influences on cognitive function in older adults. Neuropsychology, 28, 846858. https://doi.org/10.1037/neu0000098 CrossRefGoogle ScholarPubMed
Clarke, P. J., Ailshire, J. A., House, J. S., Morenoff, J. D., King, K., Melendez, R., & Langa, K. M. (2012). Cognitive function in the community setting: The neighbourhood as a source of “cognitive reserve”? Journal of Epidemiology and Community Health, 66, 730736. https://doi.org/10.1136/jech.2010.128116 CrossRefGoogle ScholarPubMed
Comijs, H. C., Beekman, A. T., Smit, F., Bremmer, M., van Tilburg, T. T., & Deeg, D. J. (2007). Childhood adversity, recent life events and depression in late life. Journal of Affective Disorders, 103, 243246.10.1016/j.jad.2007.01.012CrossRefGoogle ScholarPubMed
Crane, P. K., Narasimhalu, K., Gibbons, L. E., Pedraza, O., Mehta, K. M., Tang, Y., Manly, J.J., Reed, B.R., & Mungas, D. M. (2008). Composite scores for executive function items: Demographic heterogeneity and relationships with quantitative magnetic resonance imaging. Journal of the International Neuropsychological Society, 14, 746759. https://doi.org/10.1017/S1355617708081162 CrossRefGoogle ScholarPubMed
Early, D. R., Widaman, K. F., Harvey, D., Beckett, L., Park, L. Q., Farias, S. T., Reed, B.R., DeCarli, C., & Mungas, D. (2013). Demographic predictors of cognitive change in ethnically diverse older persons. Psychology and Aging, 28, 633645.CrossRefGoogle ScholarPubMed
Ertel, K. A., Glymour, M. M., & Berkman, L. F. (2008). Effects of social integration on preserving memory function in a nationally representative US elderly population. American Journal of Public Health, 98, 12151220. https://doi.org/10.2105/AJPH.2007.113654 CrossRefGoogle Scholar
Everson-Rose, S. A., Mendes de Leon, C. F., Bienias, J. L., Wilson, R. S., & Evans, D. A. (2003). Early life conditions and cognitive functioning in later life. American Journal of Epidemiology, 158, 10831089. https://doi.org/10.1093/aje/kwg263 CrossRefGoogle ScholarPubMed
Fletcher, E., Gavett, B., Harvey, D., Farias, S. T., Olichney, J., Beckett, L., DeCarli, C., & Mungas, D. (2018). Brain volume change and cognitive trajectories in aging. Neuropsychology, 32, 436449.10.1037/neu0000447CrossRefGoogle ScholarPubMed
Fors, S., Lennartsson, C., & Lundberg, O. (2009). Childhood living conditions, socioeconomic position in adulthood, and cognition in later life: Exploring the associations. The Journals of Gerontology: Series B, 64B, 750757. https://doi.org/10.1093/geronb/gbp029 CrossRefGoogle Scholar
Gavett, B. E., Fletcher, E., Harvey, D., Farias, S. T., Olichney, J., Beckett, L., DeCarli, C., & Mungas, D. (2018). Ethnoracial differences in brain structure change and cognitive change. Neuropsychology, 32, 529540.10.1037/neu0000452CrossRefGoogle ScholarPubMed
George, K. M., Peterson, R. L., Gilsanz, P., Barnes, L. L., Mayeda, E. R., Glymour, M. M., Mungas, D.M., DeCarli, C.S., & Whitmer, R. A. (2021). Stroke belt birth state and late-life cognition in the study of healthy aging in African Americans (STAR). Annals of Epidemiology, 64, 2632.10.1016/j.annepidem.2021.09.001CrossRefGoogle Scholar
Gill, T. M., Richardson, E. D., & Tinetti, M. E. (1995). Evaluating the risk of dependence in activities of daily living among community-living older adults with mild to moderate cognitive impairment. The Journals of Gerontology: Series A, 50A, M235M241. https://doi.org/10.1093/gerona/50A.5.M235 CrossRefGoogle Scholar
Gilsanz, P., Mayeda, E. R., Glymour, M. M., Quesenberry, C. P., & Whitmer, R. A. (2017). Association between birth in a high stroke mortality state, race, and risk of dementia. JAMA Neurology, 74, 10561062.10.1001/jamaneurol.2017.1553CrossRefGoogle Scholar
Glass, T. A., Rasmussen, M. D., & Schwartz, B. S. (2006). Neighborhoods and obesity in older adults: The Baltimore memory study. American Journal of Preventive Medicine, 31, 455463. https://doi.org/10.1016/j.amepre.2006.07.028 CrossRefGoogle ScholarPubMed
Glymour, M. M., Tzourio, C., & Dufouil, C. (2012). Is cognitive aging predicted by one’s own or one’s parents’ educational level? Results from the three-city study. American Journal of Epidemiology, 175, 750759. https://doi.org/10.1093/aje/kwr509 CrossRefGoogle ScholarPubMed
Greenfield, E. A., & Moorman, S. M. (2019). Childhood socioeconomic status and later life cognition: Evidence from the Wisconsin longitudinal study. Journal of Aging and Health, 31, 15891615. https://doi.org/10.1177/0898264318783489 CrossRefGoogle ScholarPubMed
Grove, B. J., Lim, S. J., Gale, C. R., & Shenkin, S. D. (2017). Birth weight and cognitive ability in adulthood: A systematic review and meta-analysis. Intelligence, 61, 146158.10.1016/j.intell.2017.02.001CrossRefGoogle Scholar
Hinton, L., Carter, K., Reed, B. R., Beckett, L., Lara, E., DeCarli, C., & Mungas, D. (2010). Recruitment of a community-based cohort for research on diversity and risk of dementia. Alzheimer Disease and Associated Disorders, 24, 234241. https://doi.org/10.1097/WAD.0b013e3181c1ee01 CrossRefGoogle ScholarPubMed
Horvat, P., Richards, M., Malyutina, S., Pajak, A., Kubinova, R., Tamosiunas, A., Pikhart, H., Peasey, A., Marmot, M.G., & Bobak, M. (2014). Life course socioeconomic position and mid-late life cognitive function in Eastern Europe. The Journals of Gerontology Series B, Psychological Sciences and Social Sciences, 69, 470481. https://doi.org/10.1093/geronb/gbu014 CrossRefGoogle ScholarPubMed
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 155. https://doi.org/10.1080/10705519909540118 CrossRefGoogle Scholar
Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D., Butchart, A., Mikton, C., Jones, L., & Dunne, M. P. (2017). The effect of multiple adverse childhood experiences on health: A systematic review and meta-analysis. The Lancet Public Health, 2, e356e366.10.1016/S2468-2667(17)30118-4CrossRefGoogle Scholar
Korten, N. C. M., Penninx, B. W. J. H., Pot, A. M., Deeg, D. J. H., & Comijs, H. C. (2014). Adverse childhood and recent negative life events: Contrasting associations with cognitive decline in older persons. Journal of Geriatric Psychiatry and Neurology, 27, 128138. https://doi.org/10.1177/0891988714522696 CrossRefGoogle ScholarPubMed
Krieger, N, Chen, JT, Waterman, PD, Soobader, M.-J., , S. V., & Carson, R. (2003). Choosing area based socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning: The Public Health Disparities Geocoding Project (US). Journal of Epidemiology & Community Health, 57, 186199.10.1136/jech.57.3.186CrossRefGoogle ScholarPubMed
Luo, Y., & Waite, L. J. (2005). The impact of childhood and adult SES on physical, mental, and cognitive well-being in later life. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 60, S93S101. https://doi.org/10.1093/geronb/60.2.s93 CrossRefGoogle ScholarPubMed
Melrose, R. J., Brewster, P., Marquine, M. J., MacKay-Brandt, A., Reed, B., Farias, S. T., & Mungas, D. (2015). Early life development in a multiethnic sample and the relation to late life cognition. Journals of Gerontology, Psychological and Social Sciences, 70, 519531.10.1093/geronb/gbt126CrossRefGoogle Scholar
Meyer, O. L., Mungas, D., King, J., Hinton, L., Farias, S., Reed, B., DeCarli, C., Geraghty, E., & Beckett, L. (2018). Neighborhood socioeconomic status and cognitive trajectories in a diverse longitudinal cohort. Clinical Gerontologist, 41, 8293.10.1080/07317115.2017.1282911CrossRefGoogle Scholar
Meyer, O. L., Sisco, S. M., Harvey, D., Zahodne, L. B., Glymour, M. M., Manly, J. J., & Marsiske, M. (2017). Neighborhood predictors of cognitive training outcomes and trajectories in ACTIVE. Research on Aging, 39, 443467. https://doi.org/10.1177/0164027515618242 CrossRefGoogle ScholarPubMed
Minn, M. (2021). MMQGIS, version 2020.01.16. https://michaelminn.com/linux/mmqgis/ Google Scholar
Morris, J. C. (1993). The clinical dementia rating (CDR). Neurology, 43, 2412. https://doi.org/10.1212/WNL.43.11.2412-a CrossRefGoogle ScholarPubMed
Mungas, D., Reed, B. R., Crane, P. K., Haan, M. N., & González, H. (2004). Spanish and English neuropsychological assessment scales (SENAS): Further development and psychometric characteristics. Psychological Assessment, 16, 347.10.1037/1040-3590.16.4.347CrossRefGoogle ScholarPubMed
Mungas, D., Reed, B. R., Haan, M. N., & González, H. (2005). Spanish and English neuropsychological assessment scales: Relationship to demographics, language, cognition, and independent function. Neuropsychology, 19, 466.CrossRefGoogle ScholarPubMed
Mungas, D., Reed, B. R., Marshall, S. C., & González, H. M. (2000). Development of psychometrically matched English and Spanish language neuropsychological tests for older persons. Neuropsychology, 14, 209.CrossRefGoogle ScholarPubMed
Mungas, D., Reed, B. R., Tomaszewski Farias, S., & DeCarli, C. (2005). Criterion-referenced validity of a neuropsychological test battery: Equivalent performance in elderly Hispanics and non-Hispanic Whites. Journal of the International Neuropsychological Society, 11, 620630. https://doi.org/10.1017/S1355617705050745 CrossRefGoogle ScholarPubMed
Muthén, L., & Muthén, B. (1998–2017). Mplus user’s guide (8th ed.). Muthén & Muthén.Google Scholar
Noble, K. G., Engelhardt, L. E., Brito, N. H., Mack, L. J., Nail, E. J., Angal, J., Barr, R., Fifer, W.P., Elliott, A.J., & PASS Network. (2015). Socioeconomic disparities in neurocognitive development in the first two years of life. Developmental Psychobiology, 57, 535551.10.1002/dev.21303CrossRefGoogle ScholarPubMed
Oveisgharan, S., Wilson, R. S., Yu, L., Schneider, J. A., & Bennett, D. A. (2020). Association of early-life cognitive enrichment with Alzheimer disease pathological changes and cognitive decline. JAMA Neurology, 77, 12171224. https://doi.org/10.1001/jamaneurol.2020.1941 CrossRefGoogle ScholarPubMed
Peterson, R. L., George, K. M., Gilsanz, P., Mayeda, E. R., Glymour, M. M., Meyer, O. L., Mungas, D.M., DeCarli, C., & Whitmer, R. A. (2021). Lifecourse socioeconomic changes and late-life cognition in a cohort of U.S.-born and U.S. immigrants: Findings from the KHANDLE study. BMC Public Health, 21, 920.10.1186/s12889-021-10976-6CrossRefGoogle Scholar
Peyre, H., Bernard, J. Y., Hoertel, N., Forhan, A., Charles, M.-A., De Agostini, M., Heude, B., Ramus, F., & EDEN Mother-Child Cohort Study Group. (2016). Differential effects of factors influencing cognitive development at the age of 5-to-6 years. Cognitive Development, 40, 152162.CrossRefGoogle Scholar
QGIS Development Team. (2020). QGIS geographic information system, version 3.16.14. QGIS Association.Google Scholar
Reed, B. R., Dowling, M., Tomaszewski Farias, S., Sonnen, J., Strauss, M., Schneider, J. A., Bennett, D.A., & Mungas, D. (2011). Cognitive activities during adulthood are more important than education in building reserve. Journal of the International Neuropsychological Society, 17, 615624. https://doi.org/10.1017/s1355617711000014 CrossRefGoogle ScholarPubMed
Roos, P.A., & Treiman, D.J.. (1980). DOT scales for the 1970 Census classification, In Miller, A.R., D.J. Treiman, P.S. Cain, P.A. Roos (Eds.), Work, jobs, and occupations: A critical review of the dictionary of occupational titles (pp. Appendix F 336–389). N.R.C. Committee on Occupational Classification and Analysis. Washington, DC: National Academy Press.Google Scholar
Rosso, A. L., Flatt, J. D., Carlson, M. C., Lovasi, G. S., Rosano, C., Brown, A. F., Matthews, K.A., & Gianaros, P. J. (2016). Neighborhood socioeconomic status and cognitive function in late life. American Journal of Epidemiology, 183, 10881097. https://doi.org/10.1093/aje/kwv337 CrossRefGoogle ScholarPubMed
Saenz, J. L., Downer, B., Garcia, M. A., & Wong, R. (2018). Cognition and context: Rural-urban differences in cognitive aging among older Mexican adults. Journal of Aging and Health, 30, 965986.CrossRefGoogle ScholarPubMed
Sheffield, K. M., & Peek, M. K. (2009). Neighborhood context and cognitive decline in older Mexican Americans: Results from the Hispanic established populations for epidemiologic studies of the elderly. American Journal of Epidemiology, 169, 10921101. https://doi.org/10.1093/aje/kwp005 CrossRefGoogle ScholarPubMed
Shih, R. A., Ghosh-Dastidar, B., Margolis, K. L., Slaughter, M. E., Jewell, A., Bird, C. E., Eibner, C., Denburg, N.L., Ockene, J., Messina, C.R., & Espeland, M. A. (2011). Neighborhood socioeconomic status and cognitive function in women. American Journal of Public Health, 101, 17211728. https://doi.org/10.2105/AJPH.2011.300169 CrossRefGoogle ScholarPubMed
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47, 20152028. https://doi.org/10.1016/j.neuropsychologia.2009.03.004 CrossRefGoogle ScholarPubMed
Tucker-Drob, E. M., Brandmaier, A. M., & Lindenberger, U. (2019). Coupled cognitive changes in adulthood: A meta-analysis. Psychological Bulletin, 145, 273301. https://doi.org/10.1037/bul0000179 CrossRefGoogle ScholarPubMed
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, S43S51. https://doi.org/10.1093/geronb/57.1.s43 CrossRefGoogle ScholarPubMed
Wight, R. G., Aneshensel, C. S., Miller-Martinez, D., Botticello, A. L., Cummings, J. R., Karlamangla, A. S., & Seeman, T. E. (2006). Urban neighborhood context, educational attainment, and cognitive function among older adults. American Journal of Epidemiology, 163, 10711078. https://doi.org/10.1093/aje/kwj176 CrossRefGoogle ScholarPubMed
Wilson, R. S., Scherr, P. A., Hoganson, G., Bienias, J. L., Evans, D. A., & Bennett, D. A. (2005). Early life socioeconomic status and late life risk of Alzheimer’s disease. Neuroepidemiology, 25(1), 814. doi: 10.1159/000085307.CrossRefGoogle ScholarPubMed
Yang, L., & Wang, Z. (2020). Early-life conditions and cognitive function in middle-and old-aged Chinese adults: A longitudinal study. International Journal of Environmental Research and Public Health, 17, 3451. https://doi.org/10.3390/ijerph17103451 CrossRefGoogle ScholarPubMed
Zeki Al Hazzouri, A., Haan, M. N., Kalbfleisch, J. D., Galea, S., Lisabeth, L. D., & Aiello, A. E. (2011). Life-course socioeconomic position and incidence of dementia and cognitive impairment without dementia in older Mexican Americans: Results from the Sacramento area Hispanic study on aging. American Journal of Epidemiology, 173, 11481158. https://doi.org/10.1093/aje/kwq483 CrossRefGoogle Scholar
Zhang, Z., Gu, D., & Hayward, M. D. (2008). Early life influences on cognitive impairment among oldest old Chinese. The Journals of Gerontology: Series B, 63, S25S33. https://doi.org/10.1093/geronb/63.1.S25 CrossRefGoogle ScholarPubMed