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Depression and memory function – evidence from cross-lagged panel models with unit fixed effects in ELSA and HRS

Published online by Cambridge University Press:  11 September 2020

Christoph Jindra Open the ORCID record for Christoph Jindra [Opens in a new window] ,
Chenlu Li ,
Ruby S. M. Tsang ,
Sarah Bauermeister  and
John Gallacher
Christoph Jindra*
Affiliation:
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, United Kingdom
Chenlu Li
Affiliation:
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, United Kingdom
Ruby S. M. Tsang
Affiliation:
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, United Kingdom
Sarah Bauermeister
Affiliation:
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, United Kingdom
John Gallacher
Affiliation:
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, United Kingdom
*
Author for correspondence: Christoph Jindra, E-mail: christoph.jindra@psych.ox.ac.uk
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Abstract

Background

Individuals with depression are often found to perform worse on cognitive tests and to have an increased risk of dementia. The causes and the direction of these associations are however not well understood. We looked at two specific hypotheses, the aetiological risk factor hypothesis and the reverse causality hypothesis.

Method

We analysed observational data from two cohorts, English Longitudinal Study of Ageing (ELSA) and Health and Retirement Study (HRS), using cross-lagged panel models with unit fixed effects. Each model was run once with depression and repeated with cognition as the dependent variable and the other variable as the main explanatory variable. All models were estimated separately for contemporaneous effects and lagged effects up to 8 years in the past. We contrasted the results with models making the random effects assumption.

Results

Evidence from the fixed effects models is mixed. We find no evidence for the reverse causality hypothesis in ELSA and HRS. While there is no evidence for the aetiological risk factors hypothesis in ELSA, results from HRS indicate some effects.

Conclusion

Our findings suggest that current levels of cognitive function do not influence future levels of depression. Results in HRS provide some evidence that current levels of depressive symptoms influence future cognition.

Keywords

Cognitioncross-lagged panel modelsdepressionELSAHRSfixed effects

Information

Type
Original Article
Information
Psychological Medicine , Volume 52 , Issue 8 , June 2022 , pp. 1428 - 1436
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Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press

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References

Airaksinen, E., Larsson, M., Lundberg, I., & Forsell, Y. (2004). Cognitive functions in depressive disorders: Evidence from a population-based study. Psychological Medicine, 34(1), 83–91.CrossRefGoogle ScholarPubMed
Allison, P. D. (2009). Fixed effects regression models. Los Angeles: SAGE.CrossRefGoogle Scholar
Allison, P. D., Williams, R., & Moral-Benito, E. (2017). Maximum likelihood for cross-lagged panel models with fixed effects. Socius: Sociological Research for a Dynamic World, 3, 1–17.CrossRefGoogle Scholar
Arve, S., Tilvis, R. S., Lehtonen, A., Valvanne, J., & Sairanen, S. (1999). Coexistence of lowered mood and cognitive impairment of elderly people in five birth cohorts. Aging Clinical and Experimental Research, 11(2), 90–95.CrossRefGoogle ScholarPubMed
Bauermeister, S., Orton, C., Thompson, S., Barker, R. A., Bauermeister, J. R., BenShlomo, Y., … Gallacher, J. E. J. (2020). The dementias platform UK (DPUK) data portal. European Journal of Epidemiology, 35, 601–611.CrossRefGoogle ScholarPubMed
Bennett, S., & Thomas, A. J. (2014). Depression and dementia: Cause, consequence or coincidence? Maturitas, 79(2), 184–190.CrossRefGoogle ScholarPubMed
Brailean, A., Aartsen, M. J., Muniz-Terrera, G., Prince, M., Prina, A. M., Comijs, H. C., … Beekman, A. (2017). Longitudinal associations between late-life depression dimensions and cognitive functioning: A cross-domain latent growth curve analysis. Psychological Medicine, 47(4), 690–702.CrossRefGoogle ScholarPubMed
Bunce, D., Batterham, P. J., Christensen, H., & MacKinnon, A. J. (2014). Causal associations between depression symptoms and cognition in a community-based cohort of older adults. American Journal of Geriatric Psychiatry, 22(12), 1583–1591.CrossRefGoogle Scholar
Clark, L., Chamberlain, S. R., & Sahakian, B. J. (2009). Neurocognitive mechanisms in depression: Implications for treatment. Annual Review of Neuroscience, 32(1), 57–74.CrossRefGoogle ScholarPubMed
Dotson, V. M., Resnick, S. M., & Zonderman, A. B. (2008). Differential association of concurrent, baseline, and average depressive symptoms with cognitive decline in older adults. American Journal of Geriatric Psychiatry, 16(4), 318–330.CrossRefGoogle ScholarPubMed
Dzierzewski, J. M., Potter, G. G., Jones, R. N., Rostant, O. S., Ayotte, B., Yang, F. M., … Steffens, C, D. (2015). Cognitive functioning throughout the treatment history of clinical late-life depression. International Journal of Geriatric Psychiatry, 30(10), 1076–1084.CrossRefGoogle ScholarPubMed
Enders, C. K. (2010). Applied missing data analysis. New York and London: The Guildford Press.Google Scholar
Gale, C. R., Allerhand, M., & Deary, I. J. (2012). Is there a bidirectional relationship between depressive symptoms and cognitive ability in older people? A prospective study using the English Longitudinal Study of Ageing. Psychological Medicine, 42(10), 2057–2069.CrossRefGoogle Scholar
Gallagher, D., Kiss, A., Lanctot, K., & Herrmann, N. (2016). Depressive symptoms and cognitive decline: A longitudinal analysis of potentially modifiable risk factors in community dwelling older adults. Journal of Affective Disorders, 190, 235–240.CrossRefGoogle ScholarPubMed
González, H. M., Bowen, M. E., & Fisher, G. G. (2008). Memory decline and depressive symptoms in a nationally representative sample of older adults: The Health and Retirement Study (1998–2004). Dementia and Geriatric Cognitive Disorders, 25(3), 266–271.CrossRefGoogle Scholar
Gunasekara, F. I., Richardson, K., Carter, K., & Blakely, T. (2014). Fixed effects analysis of repeated measures data. International Journal of Epidemiology, 43(1), 264–269.CrossRefGoogle ScholarPubMed
Halaby, C. N. (2004). Panel models in sociological research: Theory into practice. Annual Review of Sociology, 30(1), 507–544.CrossRefGoogle Scholar
Imai, K., & Kim, I. S. (2019). When should we use linear fixed effects regression models for causal inference with panel data? American Journal of Political Science, 63(2), 467–490.CrossRefGoogle Scholar
Jajodia, A., & Borders, A. (2011). Memory predicts changes in depressive symptoms in older adults: A bidirectional longitudinal analysis. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 66 B(5), 571–581.CrossRefGoogle Scholar
John, A., James, S.-N., Patel, U., Rusted, J., Richards, M., & Gaysina, D. (2019). Longitudinal associations of affective symptoms with mid-life cognitive function: Evidence from a British birth cohort. The British Journal of Psychiatry, 215(5), 675–682.CrossRefGoogle ScholarPubMed
Karim, J., Weisz, R., Bibi, Z., & ur Rehman, S. (2015). Validation of the eight-item Center for Epidemiologic Studies Depression Scale (CES-D) among older adults. Current Psychology, 34(4), 681–692.CrossRefGoogle Scholar
Koenig, A. M., Bhalla, R. K., & Butters, M. A. (2014). Cognitive functioning and late-life depression. Journal of the International Neuropsychological Society, 20(5), 461–467.CrossRefGoogle ScholarPubMed
Kommer, V. D., Comijs, T. N., Aartsen, H. C., Huisman, M. J., Deeg, M., and Beekman, D. J., & T, A. (2013). Depression and cognition: How do they interrelate in old age? American Journal of Geriatric Psychiatry, 21(4), 398–410.CrossRefGoogle ScholarPubMed
Langa, K. M., Llewellyn, D. J., Lang, I. A., Weir, D. R., Wallace, R. B., Kabeto, M. U., & Huppert, F. A. (2009). Cognitive health among older adults in the United States and in England. BMC Geriatrics, 9(1), 1–11.CrossRefGoogle ScholarPubMed
Leszczensky, L., & Wolbring, T. (2019). How to deal with reverse causality using panel data? Recommendations for researchers based on a simulation study. Sociological Methods and Research (Online First), 1–29. https://doi.org/10.1177/0049124119882473.Google Scholar
Lupien, S. J., McEwen, B. S., Gunnar, M. R., & Heim, C. (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature Reviews Neuroscience, 10(6), 434–445.CrossRefGoogle ScholarPubMed
Marmot, M., Oldfield, Z., Clemens, S., Blake, M., Phelps, A., Nazroo, J., … Oskala, A. (2017). English Longitudinal Study of Ageing: Waves 0–7, 1998–2015. [data collection]. SN: 5050, UK Data Service, 27 edition.Google Scholar
McArdle, J. J., Fisher, G. G., & Kadlec, K. M. (2007). Latent variable analyses of age trends of cognition in the Health and Retirement Study, 1992–2004. Psychology and Aging, 22(3), 525–545.CrossRefGoogle ScholarPubMed
Moral-Benito, E. (2013). Likelihood-based estimation of dynamic panels with predetermined regressors. Journal of Business and Economic Statistics, 31(4), 451–472.CrossRefGoogle Scholar
Nyberg, A., Peristera, P., Westerlund, H., Johansson, G., & Hanson, L. L. (2017). Does job promotion affect men's and women's health differently? Dynamic panel models with fixed effects. International Journal of Epidemiology, 46(4), 1137–1146.Google ScholarPubMed
Ofstedal, M. B., Fisher, G. G., & Herzog, R. A. (2005). Documentation of cognitive functioning measures in the Health and Retirement Study. Ann Arbor, Michigan: Institute for Social Research, University of Michigan.CrossRefGoogle Scholar
Panza, F., D'Introno, A., Colacicco, A. M., Capurso, C., Del Parigi, A., Caselli, R. J., … Solfrizzi, V. (2009). Temporal relationship between depressive symptoms and cognitive impairment: The Italian Longitudinal Study on Aging. Journal of Alzheimer's Disease, 17(4), 899–911.CrossRefGoogle ScholarPubMed
Perrino, T., Mason, C. A., Brown, S. C., Spokane, A., & Szapocznik, J. (2008). Functioning and depressive symptoms among hispanic older adults. Journal of Gerontology: Psychological Sciences, 63B(5), 309–317.CrossRefGoogle Scholar
Rodgers, W. L., & Ofstedal, M. B. (2011). Trends in scores on tests of cognitive ability in the elderly U.S. Population, 1993. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 58(6), S348–S349.CrossRefGoogle Scholar
Saczynski, J. S., Beiser, A., Seshadri, S., Auerbach, S., Wolf, P. A., & Au, R. (2010). Depressive symptoms and risk of dementia. Neurology, 75(1), 35 LP–35 41.CrossRefGoogle ScholarPubMed
Sheline, Y. I., Barch, D. M., Garcia, K., Gersing, K., Pieper, C., Welsh-Bohmer, K., … Doraiswamy, P. M. (2006). Cognitive function in late life depression: Relationships to depression severity, cerebrovascular risk factors and processing speed. Biological Psychiatry, 60(1), 58–65.CrossRefGoogle ScholarPubMed
Sonnega, A., Faul, J. D., Ofstedal, M. B., Langa, K. M., Phillips, J. W. R., & Weir, D. R. (2014). Cohort profile: The Health and Retirement Study (HRS). International Journal of Epidemiology, 43(2), 576–585.CrossRefGoogle Scholar
StataCorp. (2017). Stata statistical software: Release 15. College Station, TX: StataCorp LLC.Google Scholar
Steel, N., Huppert, F. A., McWilliams, B., & Melzer, D. (2003). Physical and cognitive function. In Marmot, M. G., Blundell, M., & Nazroo, L. C. (eds), Health, wealth and lifestyles of the older population in England: The 2002 English Longitudinal Study of Ageing, chapter 7. London: Institute for Fiscal Studies, pp. 249–271.Google Scholar
Steffick, D. E. (2000). Documentation of affective functioning measures in the Health and Retirement Study. Ann Arbor, Michigan: Institute for Social Research, University of Michigan. https://hrs.isr.umich.edu/sites/default/files/biblio/dr-005.pdf.CrossRefGoogle Scholar
Steptoe, A., Breeze, E., Banks, J., & Nazroo, J. (2013). Cohort profile: The English longitudinal study of ageing. International Journal of Epidemiology, 42, 1640–1648.CrossRefGoogle ScholarPubMed
Vaisey, S., & Miles, A. (2017). What you can - and can't - do with three-wave panel data. Sociological Methods and Research, 46(1), 44–67.CrossRefGoogle Scholar
Vinkers, D. J., Gussekloo, J., Stek, M. L., Westendorp, R. G., & Van Der Mast, R. C. (2004). Temporal relation between depression and cognitive impairment in old age: Prospective population based study. British Medical Journal, 329(7471), 881–883.CrossRefGoogle ScholarPubMed
Weir, D., Faul, J., & Langa, K. (2011). Proxy interviews and bias in cognition measures due to non-response in longitudinal studies: A comparison of HRS and ELSA. Longitudinal and Life Course Studies, 2(2), 170–184.Google Scholar
Williams, R., Allison, P. D., & Moral-Benito, E. (2018). Linear dynamic panel-data estimation using maximum likelihood and structural equation modeling. The Stata Journal, 18(2), 293–326.CrossRefGoogle Scholar
Zahodne, L. B., Stern, Y., & Manly, J. J. (2014). Depressive symptoms precede memory decline, but not vice versa, in non-demented older adults. Journal of the American Geriatrics Society, 62(1), 130–134.CrossRefGoogle Scholar
Zaninotto, P., Batty, G. D., Allerhand, M., & Deary, I. J. (2018). Cognitive function trajectories and their determinants in older people: 8 years of follow-up in the English Longitudinal Study of Ageing. Journal of Epidemiology and Community Health, 72(8), 685–694.CrossRefGoogle ScholarPubMed
Zivin, K., Llewellyn, D. J., Lang, I. A., Vijan, S., Kabeto, M. U., Miller, E. M., & Langa, K. M. (2010). Depression among older adults in the United States and England. American Journal of Geriatric Psychiatry, 18(11), 1036–1044.CrossRefGoogle ScholarPubMed
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