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As with many health constructs, cognition is difficult to measure accurately; it is assessed by multiple psychometric tests. Two approaches are commonly adopted to address this multivariate aspect in longitudinal analyses: the composite score approach summarizes the tests into a single outcome and subsequently analyzes its change; the multivariate approach relates the tests to the underlying cognitive level and simultaneously analyzes its change. We compared the quality of inference of these approaches in a simulation study based on three combinations of tests inspired by two population-based cohorts. In the absence of missing data and with relatively Gaussian psychometric tests, the composite score approach provided similar type-I error rates and statistical power as the multivariate latent process approach. In the more plausible scenario with departures from normality, transformations of each constituent test or of the composite score were required to avoid excess type-I error rates. When missing tests were more likely in cognitively impaired subjects, inference with the composite was not correct. In conclusion, composite scores can be used to assess risk factors for cognitive change provided they are correctly normalized, constituent tests are reliable and the amount of uninformative missing tests remains small. Otherwise, latent variable models are recommended.

Background: To use neuropsychological assessments for studying the underlying disease processes contributing to dementia, it is crucial that they correspond to magnetic resonance imaging (MRI)-based measures of dementia, regardless of educational level., Methods: French 3-City Dijon MRI study cohort members (n=1782) with assessments of white matter lesion volume (WMLV), hippocampal volume (HCV), and cerebrospinal fluid volume (CSFV), and 6 waves of neuropsychological assessments over 11 years, including Mini-Mental State Examination (MMSE), plus 5 other tests combined using a Z-score or item-response theory (IRT-cognition) comprised the study cohort. We evaluated, testing interactions, whether education modified associations of MRI markers with intercept or rate of change of MMSE, Z-score composite, or IRT-cognition., Results: In linear models, education modified the associations of WMLV and CSFV with MMSE and CSFV and Z-score composite. In mixed models, education modified the associations of WMLV and CSFV with level of MMSE and the association of HCV with slope of MMSE. Education also modified the association with CSFV and slope of Z-score composite decline. There was no evidence that education modified associations between MRI measures and level or slope of IRT-cognition., Conclusions: Longitudinal analysis of correctly scaled neuropsychological assessments may provide unbiased proxies for MRI-based measures of dementia risk.

To test the hypothesis that age at retirement is associated with dementia risk among self-employed workers in France, we linked health and pension databases of self-employed workers and we extracted data of those who were still alive and retired as of December 31st 2010. Dementia cases were detected in the database either through the declaration of a long-term chronic disease coded as Alzheimer's disease and other dementia (International Classification of Disease codes G30, F00, F01, F03) or through the claim for reimbursement of one of the anti-dementia drugs. Data were analyzed using Cox proportional hazard model adjusting for potential confounders. Among the 429,803 retired self-employed workers alive on December 31st 2010, prevalence of dementia was 2.65 %. Multivariable analyses showed that the hazard ratio of dementia was 0.968 [95 % confidence interval = (0.962-0.973)] per each extra year of age at retirement. After excluding workers who had dementia diagnosed within the 5 years following retirement, the results remained unchanged and highly significant (p < 0.0001). We show strong evidence of a significant decrease in the risk of developing dementia associated with older age at retirement, in line with the "use it or lose it" hypothesis. Further evidence is necessary to evaluate whether this association is causal, but our results indicate the potential importance of maintaining high levels of cognitive and social stimulation throughout work and retiree life.

Objectives: Biomechanical and psychosocial occupational exposures are seldom considered simultaneously and over extended follow-up in occupational epidemiologic studies, although there is some evidence that combined exposures have interactive effects on workers' health during working life. Given high prevalence of functional disability among retirees, research on earlier-life determinants of subsequent functional outcomes can help shape workplace policies and practices. This study investigates whether health effects of combined occupational exposures during working life are observed after individuals retire and are no longer exposed., Methods: Analyses were conducted among retirees in the French GAZEL occupational cohort (n=9168). Cumulative exposure during working life to eight biomechanical strains and to one or more reports of psychosocial job strain (high-demand, low-control work) were assessed as predictors of three outcomes: difficulty with physical functioning, role limitations due to physical difficulties, and bodily pain. Individuals were classified by joint exposure to both biomechanical and psychosocial constraints. We modeled risk ratios (RR) between exposure to biomechanical and psychosocial factors at work (separately and in combination) and disability after retirement, and we calculated the relative excess risk due to interaction (RERI) to test whether combined effects departed from additivity., Results: Both psychosocial and biomechanical exposures during working life were independent predictors of the three functional health outcomes. Compared with individuals who had neither biomechanical nor psychosocial exposures, in fully adjusted log-binomial models of the combined effects of biomechanical and psychosocial exposure, among those with low biomechanical exposures, the RR for physical functioning difficulties associated with psychosocial exposures was 1.18 (95% CI 1.01, 1.37). Among those with the highest levels of biomechanical exposures, RR was 1.42 (95% CI 1.21, 1.65) among those with low psychosocial exposures and 1.91 (95% CI 1.61, 2.26) among those with high psychosocial exposures. The two exposure types were modestly super-additive, with an RERI of 0.32 (95% CI 0.00, 0.62) between those with the highest and lowest levels of biomechanical exposures; if the effects were strictly additive, we would have expected an RERI of 0. For the other two outcomes results were similar, although there was no significant departure from additivity. Some effects varied in magnitude by gender., Conclusion: Across the sample, combined biomechanical and psychosocial occupational exposures during working life appear to have additive or perhaps interactive effects on functional health in retirement. However, the relationship is less straightforward among women. Improving overall working conditions may lessen future disability among retirees., (Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: Longitudinal studies of dementia rely on the assumption that individuals who drop out are comparable to those who remain in the study, adjusting for measured covariates. Existing methods to handle dropouts account for differences based on past health and cognitive measures. We assess whether such adjustments fully account for differences in future dementia risk., Methods: Among Three-City Study participants in Dijon, France, with 1 (n = 1,633) or 2 (n = 1,168) brain MRI scans, we tested whether white matter lesion volume (WMLV), hippocampal volume, or brain CSF volume predicted dropout ("unable to contact" or "refused interview") in repeated-measures logistic regression with up to 4 follow-ups (average 3.5 waves). Using linear regression, we also estimated differences in MRI volumes and MRI changes by subsequent dropout status and estimated plausible ranges for selective attrition bias based on these associations. Models were adjusted for demographic, health, and cognitive score covariates., Results: Baseline greater WMLV predicted increased odds of dropping out (adjusted odds ratio = 1.71; 95% confidence interval [CI] 1.20-2.43). Among participants with 2 MRI scans, individuals who subsequently dropped out had significantly worse declines in hippocampal volume (-0.30 SD difference; 95% CI -0.43 to -0.17) between the first and second MRI scans., Conclusions: Higher future dementia risk, indicated by worse past brain MRI findings, predicted future study dropout. Adjustment for selective attrition, based on MRI markers when available, may help reduce bias in estimates of dementia incidence and improve research on dementia risk factors. MRI findings may also help prospectively identify cohort members at elevated risk of attrition.

Objective: Chronic occupational solvent exposure is associated with long-term cognitive deficits. Cognitive reserve may protect solvent-exposed workers from cognitive impairment. We tested whether the association between chronic solvent exposure and cognition varied by educational attainment, a proxy for cognitive reserve., Methods: Data were drawn from a prospective cohort of French national gas and electricity (GAZEL) employees (n = 4,134). Lifetime exposure to 4 solvent types (chlorinated solvents, petroleum solvents, benzene, and nonbenzene aromatic solvents) was assessed using a validated job-exposure matrix. Education was dichotomized at less than secondary school or below. Cognitive impairment was defined as scoring below the 25th percentile on the Digit Symbol Substitution Test at mean age 59 (SD 2.8; 88% of participants were retired at testing). Log-binomial regression was used to model risk ratios (RRs) for poor cognition as predicted by solvent exposure, stratified by education and adjusted for sociodemographic and behavioral factors., Results: Solvent exposure rates were higher among less-educated patients. Within this group, there was a dose-response relationship between lifetime exposure to each solvent type and RR for poor cognition (e.g., for high exposure to benzene, RR = 1.24, 95% confidence interval 1.09-1.41), with significant linear trends (p < 0.05) in 3 out of 4 solvent types. Recency of solvent exposure also predicted worse cognition among less-educated patients. Among those with secondary education or higher, there was no significant or near-significant relationship between any quantification of solvent exposure and cognition., Conclusions: Solvent exposure is associated with poor cognition only among less-educated individuals. Higher cognitive reserve in the more-educated group may explain this finding.