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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.

We aimed to examine whether long-term use of benzodiazepines is associated with an accelerated decline of cognitive performances by using a statistical model specifically adapted to multivariate longitudinal bounded quantitative outcomes. The data came from the "Three-city" study, a French population based study. All the subjects were 65 years old or older at inclusion and had been followed-up for 7 years. The use of benzodiazepines and cognitive functioning were assessed at each examination phase (baseline, 2, 4 and 7 years). Cognitive decline was analyzed using a nonlinear multivariate mixed model with a latent process. This model makes it possible to assess change over time of the latent cognitive process underlying several neuropsychological tests: Mini Mental Status Examination, Isaacs Set test, Benton Visual Retention Test, and Trail Making Test (A and B), and to describe and account for their metrological properties. Analyses were adjusted for age, center, gender, education, socio-professional status, depression, insomnia, high blood pressure, hypercholesterolemia, alcohol, tobacco consumption and physical activity. Nine hundred and sixty nine subjects who reported taking benzodiazepines for 2, 4 or 7 consecutive years were compared to 4226 subjects who were non-benzodiazepine users. Chronic use of benzodiazepine was significantly associated with a lower latent cognitive level (β=-1.79 SE=0.25 p=<0.001), but no association was found between chronic use and an acceleration of cognitive decline, neither on the latent cognitive process (β × time=0.010 SE=0.04 p=0.81), nor on specific neuropsychological tests. Our results suggest that chronic benzodiazepine use is associated with poorer cognitive performance but not with accelerated cognitive decline with age., (Copyright © 2012 Elsevier B.V. and ECNP. All rights reserved.)

Long-chain omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) may slow cognitive decline. The ε4 allele of the ApolipoproteinE (ApoE), the main genetic risk factor for Alzheimer's disease, and depressive symptoms, which are frequently associated with cognitive impairment in older persons, may modify this relationship. We estimated the associations between EPA and DHA plasma levels and subsequent cognitive decline over 7 years, taking into account ApoE-ε4 status and depressive symptoms, in a prospective population-based cohort. Participants (≥ 65 years, n = 1,228 nondemented at baseline) were evaluated at least once over three follow-up visits using four cognitive tests. Plasma EPA was associated with slower decline on Benton Visual Retention Test (BVRT) performances in ApoE-ε4 carriers, or in subjects with high depressive symptoms at baseline. Plasma DHA was associated with slower decline on BVRT performances in ApoE-ε4 carriers only. EPA and DHA may contribute to delaying decline in visual working memory in ApoE-ε4 carriers. In older depressed subjects, EPA, but not DHA, may slow cognitive decline., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The linear mixed model (LMM), which is routinely used to describe change in outcomes over time and its association with risk factors, assumes that a unit change in any predictor is associated with a constant change in the outcome. When it is used on psychometric tests, this assumption may not hold. Indeed, psychometric tests usually suffer from ceiling and/or floor effects and curvilinearity (i.e., varying sensitivity to change). The authors aimed to determine the consequences of such misspecification when evaluating predictors of cognitive decline. As an alternative to the LMM, they considered 2 mixed models based on latent processes that handle discrete and bounded outcomes. Model differences are illustrated here using data on 4 psychometric tests from the Personnes Agées QUID (PAQUID) Study (1989-2004). The type I error of the Wald test for risk-factor regression parameters was formally assessed in a simulation study. It demonstrated that type I errors in the LMM could be dramatically inflated for some tests, such that spurious associations with risk factors were found. In particular, confusion between effects on mean level and effects on change over time was highlighted. The authors recommend use of the alternative mixed models when studying psychometric tests and more generally quantitative scales (quality of life, activities of daily living).

Ordinal and quantitative discrete data are frequent in biomedical and neuropsychological studies. We propose a semi-parametric model for the analysis of the change over time of such data in longitudinal studies. A threshold model is defined where the outcome value depends on the current value of an underlying Gaussian latent process. The latent process model is a Gaussian linear mixed model with a non-parametric function of time, f(t), to model the expected change over time. This model includes random-effects and a stochastic error process to flexibly handle correlation between repeated measures. The function f(t) and all the model parameters are estimated by penalized likelihood using a cubic-spline approximation for f(t). The smoothing parameter is estimated by an approximate cross-validation criterion. Confidence bands may be computed for the estimated curves for the latent process and, using a Monte Carlo approach, for the outcome in its natural scale. The method is applied to the Paquid cohort data to compare the time-course over 14 years of two cognitive scores in a sample of 350 future Alzheimer patients and in a matched sample of healthy subjects., (Copyright © 2010 John Wiley & Sons, Ltd.)

In cognitive aging research, the study of a general cognitive factor has been shown to have a substantial explanatory power over the study of isolated tests. The authors aimed at differentiating the impact of gender and education on global cognitive change with age from their differential impact on 4 psychometric tests using a new latent process approach, which intermediates between a single-factor longitudinal model for sum scores and an item-response theory approach for longitudinal data. The analysis was conducted on a sample of 2,228 subjects from PAQUID, a population-based cohort of older adults followed for 13 years with repeated measures of cognition. Adjusted for vascular factors, the analysis confirmed that women performed better in tests involving verbal components, while men performed better in tests involving visuospatial skills. In addition, the model suggested that women had a slightly steeper global cognitive decline with oldest age than men, even after excluding incident dementia or death. Subjects with higher education exhibited a better mean score for the 4 tests, but this difference tended to attenuate with age for tests involving a speed component., ((c) 2008 APA, all rights reserved)

Choosing the measure of cognition in an epidemiologic study investigating cognitive changes over time is a challenging question. A powerful measure must be able to detect small cognitive changes in all the range of cognition observed in the target population. This work aims at comparing the sensitivity to detect cognitive changes in the observed range of cognition of four widely used psychometric tests in an aging-population-based study through a nonlinear latent process model, assuming that the psychometric tests are nonlinear noisy transformations of their common factor. With data from the French prospective cohort study PAQUID (1989-2001), the authors found that the Mini-Mental State Examination and the Benton Visual Retention Test exhibited a better sensitivity to cognitive changes in low levels of cognition, while the Digit Symbol Substitution Test was more sensitive to changes in high levels of cognition. In contrast, the Isaacs Set Test shortened at 15 seconds appeared to be sensitive to small changes in all the range of cognition and, thus, represents an appropriate measure of cognition in population-based studies including both highly normal and severely impaired subjects.

The association between sex/gender and aging-related cognitive decline remains poorly understood because of inconsistencies in findings. Such heterogeneity could be attributable to the cognitive functions studied and study population characteristics, but also to differential selection by dropout and death between men and women. We aimed to evaluate the impact of selection by dropout and death on the association between sex/gender and cognitive decline. We first compared the statistical methods most frequently used for longitudinal data, targeting either population estimands (marginal models fitted by generalized estimating equations) or subject-specific estimands (mixed/joint models fitted by likelihood maximization) in 8 studies of aging: 6 population-based studies (the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) Study (1996–2009), Personnes Âgées QUID (PAQUID; 1988–2014), the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study (2003–2016), the Three-City Study (Bordeaux only; 1999–2016), the Washington Heights-Inwood Community Aging Project (WHICAP; 1992–2017), and the Whitehall II Study (2007–2016)) and 2 clinic-based studies (the Alzheimer's Disease Neuroimaging Initiative (ADNI; 2004–2017) and a nationwide French cohort study, MEMENTO (2011–2016)). We illustrate differences in the estimands of the association between sex/gender and cognitive decline in selected examples and highlight the critical role of differential selection by dropout and death. Using the same estimand, we then contrast the sex/gender–cognitive decline associations across cohorts and cognitive measures suggesting a residual differential sex/gender association depending on the targeted cognitive measure (memory or animal fluency) and the initial cohort selection. We recommend focusing on subject-specific estimands in the living population for assessing sex/gender differences while handling differential selection over time. [ABSTRACT FROM AUTHOR]

Objectives: The co-occurrence of multiple medical or psychosocial conditions (geriatric syndromes (GS) and age-related diseases) is a growing concern in older people. Given the diversity of these conditions and their complex interactions, our aim was to determine whether they could be structured into synthetic dimensions in order to facilitate the management of multimorbidity. Design: The underlying structure of 10 GSs and 8 age-related diseases was identified using a multiple correspondence analysis (MCA), and confronted to subjective and objective health outcomes. Setting: Community residents from Bordeaux City (France) older than 75 years in 2010 Participants: 630 adults aged 75+ years who lived in Bordeaux and participated in the 10-year follow-up of the Three-City study. Measurements: GSs included physical frailty, cognitive impairment and dementia, dependency, depressive symptoms, polymedication, thinness, falls, sensory deficit, social isolation, incontinence. Age-related diseases were cancer, cardiac diseases, peripheral vascular diseases, diabetes, hypertension, pulmonary diseases, osteoporosis, other chronic diseases. Association of the MCA-derived independent dimensions was assessed with 10-year visit subjective health and well-being, and with incident death and entry into institution during the remaining cohort follow-up. Results: Most of the participants (82%) had at least two age-related syndromes or diseases. The MCA structured the 18 conditions into three major dimensions: Degradation (D) driven by GS, Vascular (V), and Psychosocial (P) representing 68.7%, 7.4%, and 5.7% of the total variance, respectively. Dimension D was a strong predictor of future death and institutionalization. Dimensions D and P were strongly associated with current well-being. Conclusions: This work confirmed that multimorbidity is very common among older adults, and demonstrated the essential role of GS as manifestations of aging, even more than age-related diseases. [ABSTRACT FROM AUTHOR]

Background: Long-term behavioral and health risk factors constitute a primary focus of research on the etiology of chronic diseases. Yet, identifying critical time-windows during which risk factors have the strongest impact on disease risk is challenging. To assess the trajectory of association of an exposure history with an outcome, the weighted cumulative exposure index (WCIE) has been proposed, with weights reflecting the relative importance of exposures at different times. However, WCIE is restricted to a complete observed error-free exposure whereas exposures are often measured with intermittent missingness and error. Moreover, it rarely explores exposure history that is very distant from the outcome as usually sought in life-course epidemiology.Methods: We extend the WCIE methodology to (i) exposures that are intermittently measured with error, and (ii) contexts where the exposure time-window precedes the outcome time-window using a landmark approach. First, the individual exposure history up to the landmark time is estimated using a mixed model that handles missing data and error in exposure measurement, and the predicted complete error-free exposure history is derived. Then the WCIE methodology is applied to assess the trajectory of association between the predicted exposure history and the health outcome collected after the landmark time. In our context, the health outcome is a longitudinal marker analyzed using a mixed model.Results: A simulation study first demonstrates the correct inference obtained with this approach. Then, applied to the Nurses' Health Study (19,415 women) to investigate the association between body mass index history (collected from midlife) and subsequent cognitive decline (evaluated after age 70), the method identified two major critical windows of association: long before the first cognitive evaluation (roughly 24 to 12 years), higher levels of BMI were associated with poorer cognition. In contrast, adjusted for the whole history, higher levels of BMI became associated with better cognition in the last years prior to the first cognitive interview, thus reflecting reverse causation (changes in exposure due to underlying disease).Conclusions: This approach, easy to implement, provides a flexible tool for studying complex dynamic relationships and identifying critical time windows while accounting for exposure measurement errors. [ABSTRACT FROM AUTHOR]

Background: Thoroughly understanding the temporal associations between cognitive and functional dimensions along the dementia process is fundamental to define preventive measures likely to delay the disease's onset. This work aimed to finely describe the trajectories of cognitive and functional declines, and assess their dynamic bidirectional relationships among subjects at different stages of the dementia process. Methods: We leveraged extensive repeated data of cognition and functional dependency from the French prospective COGICARE study, designed to better characterize the natural history of cognitive and functional declines around dementia diagnosis. Cognition was measured by the Mini-Mental State Examination, the Isaacs Set Test for verbal fluency, the Benton Visual Retention Test for visuo-spatial memory, and Trail Making Test Part B for executive functioning. Functional dependency was measured by basic and instrumental activities of daily living. The study included 102 cognitively normal, 123 mildly cognitively impaired, and 72 dementia cases with a median of 5 repeated visits over up to 57 months. We used a dynamic causal model which addresses the two essential issues in temporal associations assessment: focusing on intra-individual change and accounting for time. Results: Better cognitive abilities were associated with lower subsequent decline of the functional level among the three clinical stages with an intensification over time but no reciprocity of the association whatever the clinical status. Conclusion: This work confirms that the progressive functional dependency could be induced by cognitive impairment. Subjects identified as early as possible with clinically significant cognitive impairments could benefit from preventive measures before the deterioration of activities of daily living and the appearance of dementia clinical signs. [ABSTRACT FROM AUTHOR]

Healthy lifestyles are promising targets for prevention of cognitive aging, yet the optimal time windows for interventions remain unclear. We selected a case-control sample nested within the Nurses' Health Study (starting year 1976, mean age = 51 years), including 14,956 women aged ≥70 years who were free of both stroke and cognitive impairment at enrollment in a cognitive substudy (1995–2001). Cases (n  = 1,496) were women with the 10% worst slopes of cognitive decline, and controls (n  = 7,478) were those with slopes better than the median. We compared the trajectories of body mass index (weight (kg)/height (m)2), alternate Mediterranean diet (A-MeDi) score, and physical activity between groups, from midlife through 1 year preceding the cognitive substudy. In midlife, cases had higher body mass index than controls (mean difference (MD) = 0.59 units, 95% confidence interval (CI): 0.39, 0.80), lower physical activity (MD = –1.41 metabolic equivalent of task–hours/week, 95% CI: –2.07, –0.71), and worse A-MeDi scores (MD = –0.16 points, 95% CI: –0.26, –0.06). From midlife through later life, compared with controls, cases had consistently lower A-MeDi scores but a deceleration of weight gain and a faster decrease in physical activity. In conclusion, maintaining a healthy lifestyle since midlife may help reduce cognitive decline in aging. At older ages, both deceleration of weight gain and a decrease in physical activity may reflect early signs of cognitive impairment. [ABSTRACT FROM AUTHOR]

In line with declining trends in dementia incidence, we compared the cognitive and functional evolution of 2 "generations" of elderly individuals aged 78–88 years, who were included 10 years apart in the French Personnes Agées Quid cohort (n = 612 in 1991–1992 and n = 628 in 2001–2002) and followed-up for 12 years with assessments of cognition and disability. The impact of specific risk factors on this evolution was evaluated. Differences between the generations in baseline levels and decline over time were estimated using a joint model to account for differential attrition. Compared with the first generation, the second generation had higher performances at baseline on 4 cognitive tests (from P < 0.005). Differences in global cognition, verbal fluency, and processing speed, but not in working memory, were mostly explained by improvement in educational level. The second generation also exhibited less cognitive decline in verbal fluency and working memory. Progression of disability was less over the follow-up period for the second generation than for the first. The cognitive state of this elderly population improved, partially due to improvements in educational level. [ABSTRACT FROM AUTHOR]

Importance: Evidence is limited regarding the relation between cardiovascular health level and dementia risk.Objective: To investigate the association between cardiovascular health level, defined using the 7-item tool from the American Heart Association (AHA), and risk of dementia and cognitive decline in older persons.Design, Setting, and Participants: Population-based cohort study of persons aged 65 years or older from Bordeaux, Dijon, and Montpellier, France, without history of cardiovascular diseases or dementia at baseline who underwent repeated in-person neuropsychological testing (January 1999-July 2016) and systematic detection of incident dementia (date of final follow-up, July 26, 2016).Exposures: The number of the AHA's Life's Simple 7 metrics at recommended optimal level (nonsmoking, body mass index <25, regular physical activity, eating fish twice a week or more and fruits and vegetables at least 3 times a day, cholesterol <200 mg/dL [untreated], fasting glucose <100 mg/dL [untreated], and blood pressure <120/80 mm Hg [untreated]; score range, 0-7) and a global cardiovascular health score (range, 0-14; poor, intermediate, and optimal levels of each metric assigned a value of 0, 1, and 2, respectively).Main Outcomes and Measures: Incident dementia validated by an expert committee and change in a composite score of global cognition (in standard units, with values indicating distance from population means, 0 equal to the mean, and +1 and -1 equal to 1 SD above and below the mean).Results: Among 6626 participants (mean age, 73.7 years; 4200 women [63.4%]), 2412 (36.5%), 3781 (57.1%), and 433 (6.5%) had 0 to 2, 3 to 4, and 5 to 7 health metrics at optimal levels, respectively, at baseline. Over a mean follow-up duration of 8.5 (range, 0.6-16.6) years, 745 participants had incident adjudicated dementia. Compared with the incidence rate of dementia of 1.76 (95% CI, 1.38-2.15) per 100 person-years among those with 0 or 1 health metrics at optimal levels, the absolute differences in incident dementia rates for 2, 3, 4, 5, and 6 to 7 metrics were, respectively, -0.26 (95% CI, -0.48 to -0.04), -0.59 (95% CI, -0.80 to -0.38), -0.43 (95% CI, -0.65 to -0.21), -0.93 (95% CI, -1.18 to -0.68), and -0.96 (95% CI, -1.37 to -0.56) per 100 person-years. In multivariable models, the hazard ratios for dementia were 0.90 (95% CI, 0.84-0.97) per additional optimal metric and 0.92 (95% CI, 0.89-0.96) per additional point on the global score. Furthermore, the gain in global cognition associated with each additional optimal metric at baseline was 0.031 (95% CI, 0.009-0.053) standard units at inclusion, 0.068 (95% CI, 0.045-0.092) units at year 6, and 0.072 (95% CI, 0.042-0.102) units at year 12.Conclusions and Relevance: In this cohort of older adults, increased numbers of optimal cardiovascular health metrics and a higher cardiovascular health score were associated with a lower risk of dementia and lower rates of cognitive decline. These findings may support the promotion of cardiovascular health to prevent risk factors associated with cognitive decline and dementia. [ABSTRACT FROM AUTHOR]

Joint models are used in ageing studies to investigate the association between longitudinal markers and a time-to-event, and have been extended to multiple markers and/or competing risks. The competing risk of death must be considered in the elderly because death and dementia have common risk factors. Moreover, in cohort studies, time-to-dementia is interval-censored since dementia is assessed intermittently. So subjects can develop dementia and die between two visits without being diagnosed. To study predementia cognitive decline, we propose a joint latent class model combining a (possibly multivariate) mixed model and an illness-death model handling both interval censoring (by accounting for a possible unobserved transition to dementia) and semi-competing risks. Parameters are estimated by maximum-likelihood handling interval censoring. The correlation between the marker and the times-to-events is captured by latent classes, homogeneous sub-groups with specific risks of death, dementia, and profiles of cognitive decline. We propose Markovian and semi-Markovian versions. Both approaches are compared to a joint latent-class model for competing risks through a simulation study, and applied in a prospective cohort study of cerebral and functional ageing to distinguish different profiles of cognitive decline associated with risks of dementia and death. The comparison highlights that among subjects with dementia, mortality depends more on age than on duration of dementia. This model distinguishes the so-called terminal predeath decline (among healthy subjects) from the predementia decline. [ABSTRACT FROM AUTHOR]

Abstract: Long-chain omega-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) may slow cognitive decline. The ε4 allele of the ApolipoproteinE (ApoE), the main genetic risk factor for Alzheimer''s disease, and depressive symptoms, which are frequently associated with cognitive impairment in older persons, may modify this relationship. We estimated the associations between EPA and DHA plasma levels and subsequent cognitive decline over 7 years, taking into account ApoE-ε4 status and depressive symptoms, in a prospective population-based cohort. Participants (≥ 65 years, n = 1,228 nondemented at baseline) were evaluated at least once over three follow-up visits using four cognitive tests. Plasma EPA was associated with slower decline on Benton Visual Retention Test (BVRT) performances in ApoE-ε4 carriers, or in subjects with high depressive symptoms at baseline. Plasma DHA was associated with slower decline on BVRT performances in ApoE-ε4 carriers only. EPA and DHA may contribute to delaying decline in visual working memory in ApoE-ε4 carriers. In older depressed subjects, EPA, but not DHA, may slow cognitive decline. [Copyright &y& Elsevier]