Characterizing the Effects of Sex, <i>APOE</i> ɛ4, and Literacy on Mid-life Cognitive Trajectories: Application of Information-Theoretic Model Averaging and Multi-model Inference Techniques to the Wisconsin Registry for Alzheimer’s Prevention Study

Koscik, Rebecca L.; Norton, Derek; Allison, Samantha L.; Jonaitis, Erin M.; Clark, Lindsay R.; Mueller, Kimberly D.; Hermann, Bruce P.; Engelman, Corinne D.; Gleason, Carey E.; Sager, Mark A.; Chappell, Richard J.; Johnson, Sterling C.

doi:10.1017/s1355617718000954

Cited by 7 publications

(9 citation statements)

References 55 publications

(88 reference statements)

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“…In particular, confrontation naming, assessed in WRAP using the Boston Naming Test [42], was not considered. Previous analyses in this cohort have suggested there is not yet enough variability in this measure for it to be a meaningful differentiator [43]. Instead, we focused on measures that were components of one of several composites of interest to us, so that we could more easily make relevant comparisons.…”

Section: Discussionmentioning

confidence: 99%

Measuring longitudinal cognition: Individual tests versus composites

Jonaitis

Koscik

Clark

et al. 2018

Alz & Dem Diag Ass & Dis Mo

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109

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Introduction Longitudinal cohort studies of cognitive aging must confront several sources of within‐person variability in scores. In this article, we compare several neuropsychological measures in terms of longitudinal error variance and relationships with biomarker‐assessed brain amyloidosis (Aβ). Methods Analyses used data from the Wisconsin Registry for Alzheimer's Prevention. We quantified within‐person longitudinal variability and age‐related trajectories for several global and domain‐specific composites and their constituent scores. For a subset with cerebrospinal fluid or amyloid positron emission tomography measures, we examined how Aβ modified cognitive trajectories. Results Global and theoretically derived composites exhibited lower intraindividual variability and stronger age × Aβ interactions than did empirically derived composites or raw scores from single tests. For example, the theoretical executive function outperformed other executive function scores on both metrics. Discussion These results reinforce the need for careful selection of cognitive outcomes in study design, and support the emerging consensus favoring composites over single‐test measures.

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Section: Discussionmentioning

confidence: 99%

Measuring longitudinal cognition: Individual tests versus composites

Jonaitis

Koscik

Clark

et al. 2018

Alz & Dem Diag Ass & Dis Mo

Self Cite

109

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“…Given our goal of characterizing the combined influences of multiple health behavior predictors and related interactions, we opted to use an information theoretic (IT) modeling technique detailed by our group in previous work. [26] In brief, the IT framework evaluates a set of plausible scientific hypotheses, and uses the relative strengths of information considered across all models to obtain model-averaged parameter estimates, instead of selecting a single model based on traditional model selection techniques. In so doing, after fitting all of the models of interest to each outcome (with differing combinations of health behavior predictors and interactions), results are combined across models in proportion to the relative strength of information each model contributes [26].…”

Section: Discussionmentioning

confidence: 99%

“…[26] In brief, the IT framework evaluates a set of plausible scientific hypotheses, and uses the relative strengths of information considered across all models to obtain model-averaged parameter estimates, instead of selecting a single model based on traditional model selection techniques. In so doing, after fitting all of the models of interest to each outcome (with differing combinations of health behavior predictors and interactions), results are combined across models in proportion to the relative strength of information each model contributes [26]. The IT framework also offers advantages over a traditional model selection approach (e.g., forward or backward selection), in that it allows comparison of fits across all models and reduces over-estimation of effect sizes compared to standard models.…”

Section: Discussionmentioning

confidence: 99%

Self-reported health behaviors and longitudinal cognitive performance in late middle age: Results from the Wisconsin Registry for Alzheimer’s Prevention

et al. 2020

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Background Studies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimer's Prevention (WRAP), an Alzheimer's disease risk-enriched cohort who were non-demented and in late midlife at baseline. Method We analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multidomain cognitive composite, and secondary outcomes were immediate/delayed memory and executive function composites. Predictors of interest were self-reported measures of physical activity, cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) model averaging (MA) approach on a set of models including covariates and combinations of these 2-and 3-way interactions. The IT approach was

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“…Health behavior predictors were converted to z-scores (mean=0, sd=1) for analyses. Further details about model fitting and diagnostics are detailed in our previous work 26 .…”

Section: Methodsmentioning

confidence: 99%

Self-reported health behaviors and longitudinal cognitive performance: Results from the Wisconsin Registry for Alzheimer’s Prevention

Mueller

Koscik

Norton

et al. 2019

Preprint

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Background3 Studies have suggested associations between self-reported engagement in health behaviors and 4 reduced risk of cognitive decline. Most studies explore these relationships using one health 5 behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored 6 whether several individual self-reported health behaviors were associated with cognitive decline 7 when considered simultaneously, using data from the Wisconsin Registry for Alzheimer's 8 Prevention (WRAP), an Alzheimer's disease risk-enriched cohort who were non-demented and 9 in late midlife at baseline. 10 11 Method 12 We analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at 13 baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years 14 (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multi-domain 15 cognitive composite, and secondary outcomes were immediate/delayed memory and executive 16 function composites. Predictors of interest were self-reported measures of physical activity, 17 cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each 18 other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) 19 model averaging (MA) approach on a set of models including covariates and combinations of 20 these 2-and 3-way interactions. The IT approach was selected due to the large number of 21 interactions of interest and to avoid pitfalls of traditional model selection approaches. 22 23 Results 2 2425 Model-averaged results identified no significant modifiable behavior*age interactions in 26 relationship to the primary composite outcome. In secondary outcomes, higher MIND diet scores 27 associated with slower decline in executive function. Men showed faster decline than women on 28 delayed memory, independent of health behaviors. There were no other significant interactions 29 among any other health behaviors and cognitive trajectories. 31 Conclusions32 When multiple covariates and health behaviors were considered simultaneously, there were 33 limited weak associations with cognitive decline in this age range. These results may be 34 explained alone or in combination by three alternative explanations: 1) the range of cognitive 35 decline is in middle age is too small to observe relationships with health behaviors, 2) the 36 putative associations of these health behaviors on cognition may not be robust in this age range, 37 or 3) the self-reported measures of the health behaviors may not be optimal for predicting 38 cognitive decline. More study may be needed that incorporates sensitive measures of health 39 behaviors, AD biomarker profiles, and/or other disease comorbidities. 40 3 41 Introduction 42 The estimated prevalence of dementia in America in 2019 was 5.8 million, and it is projected to 43 rise to 13.9 million by 2050 if prevention or cures are not identified. Delaying the onset of 44 dementia by five years would result in a financial savings of up ...

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Characterizing the Effects of Sex, APOE ɛ4, and Literacy on Mid-life Cognitive Trajectories: Application of Information-Theoretic Model Averaging and Multi-model Inference Techniques to the Wisconsin Registry for Alzheimer’s Prevention Study

Cited by 7 publications

References 55 publications

Measuring longitudinal cognition: Individual tests versus composites

Measuring longitudinal cognition: Individual tests versus composites

Self-reported health behaviors and longitudinal cognitive performance in late middle age: Results from the Wisconsin Registry for Alzheimer’s Prevention

Self-reported health behaviors and longitudinal cognitive performance: Results from the Wisconsin Registry for Alzheimer’s Prevention

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