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Education and adolescent cognitive ability as predictors of dementia in a cohort of Danish men

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  • Else Foverskov
  • M Maria Glymour
  • Erik Lykke Mortensen
  • Merete Osler
  • Gunhild Tidemann Okholm
  • Rikke Lund

Abstract

Background: An association between education and dementia is well-established but it is unclear whether education is associated with dementia after accounting for early life cognitive ability and whether there is a joint effect, such that the risk associated with one of the exposures depends on the value of the other. We examined separate and joint associations of adolescent cognitive ability and educational attainment with risk of dementia among Danish men born between 1939 and 1959. Methods: Men (N = 477,421) from the Danish Conscription Database were followed for dementia from the age 60 for up to 17 years via patient and prescription registry linkages. Exposure measures included cognitive ability assessed at the conscript board examination around age 18 and highest educational level (low: 0–10 year, medium: 10–13 years, high: ≥13 years) at age 30 from registry records. Associations with dementia diagnosis were estimated in Cox proportional hazards models adjusted for birth year and age at conscript board examination. Interaction was assessed on the multiplicative scale by including a product term between the two exposure measures and on the additive scale by calculating relative excess risk due to interaction (RERI) between different levels of the exposure measures. Results: Compared to men in the high education group hazard ratio [HR] for men in the medium and low group were 1.21 (95% confidence interval [CI]: 1.13, 1.30) and 1.34 (95% CI: 1.24, 1.45), respectively when not adjusting for cognitive ability. Additional adjustment for cognitive ability attenuated the magnitude of the associations, but they remained significant (education medium: HR = 1.10, 95% CI: 1.02, 1.19 and education low: HR = 1.12, 95% CI: 1.02, 1.22). A 10% higher cognitive ability score was associated with a 3.8% lower hazard of dementia (HR = 0.962; 95% CI: 0.957, 0.967), and the magnitude of the association only changed marginally after adjustment for education. Men in the low education group with relatively low cognitive ability were identified as a high-risk subgroup for dementia. The increased risk associated with exposure to both risk factors did, however, not significantly depart from the sum of risk experienced by men only exposed to one of the risk factors (estimates of RERI were not significantly different from 0) and no significant evidence of either additive or multiplicative interactions was found. Conclusions: In conclusion, the results suggest that education and cognitive ability protect against the risk of dementia independently of one another and that increases in educational attainment may at least partially offset dementia risk due to low cognitive ability.

Suggested Citation

  • Else Foverskov & M Maria Glymour & Erik Lykke Mortensen & Merete Osler & Gunhild Tidemann Okholm & Rikke Lund, 2020. "Education and adolescent cognitive ability as predictors of dementia in a cohort of Danish men," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-13, August.
    • Handle: RePEc:plo:pone00:0235781
    DOI: 10.1371/journal.pone.0235781
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    References listed on IDEAS

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    1. Li, Jinhu & Powdthavee, Nattavudh, 2015. "Does more education lead to better health habits? Evidence from the school reforms in Australia," Social Science & Medicine, Elsevier, vol. 127(C), pages 83-91.
    2. Patrick Royston & Douglas G. Altman, 1994. "Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(3), pages 429-453, September.
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