Article

Fasting insulin levels and cognitive decline in older women without diabetes.

Department of Epidemiology/Biostatistics and Neurology, Erasmus Medical Center, Rotterdam, The Netherlands.
Neuroepidemiology (Impact Factor: 2.48). 02/2008; 30(3):174-9. DOI: 10.1159/000126909
Source: PubMed

ABSTRACT Type 2 diabetes has been associated with an increased risk of dementia. To assess possible independent effects of insulin, we investigated the relation of insulin levels to cognitive decline in nondiabetic women.
Fasting plasma insulin levels were measured in mid-life in 1,416 nondiabetic Nurses' Health Study participants, who also completed cognitive testing that began 10 years later (current age: 70-75 years). Over 4 years, 3 assessments of general cognition, verbal memory, category fluency and attention were administered. Primary outcomes were the Telephone Interview for Cognitive Status (TICS) performance, the global score (average of all tests) and verbal memory (average of verbal recall tests). Linear mixed-effects models were used to calculate the association between insulin and cognitive decline.
Higher insulin levels were associated with a faster decline on the TICS and verbal memory. For analysis, batch-specific quartiles of insulin levels were constructed. Compared to the lowest quartile, adjusted differences in the annual rates of decline (with 95% CI values in parentheses) for the second, third and fourth quartiles were: TICS, -0.06 (-0.16, 0.03), -0.14 (-0.24, -0.04), and -0.09 (-0.19, 0.01) points (p trend = 0.04); verbal memory, -0.01 (-0.04, 0.02), -0.05 (-0.08, -0.02), and -0.02 (-0.05, 0.01) units (p trend = 0.02). These associations remained after multivariable adjustment.
Our study provides evidence for a potential role of higher fasting insulin levels in cognitive decline, possibly independent of diabetes.

0 Bookmarks
 · 
88 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: This manuscript provides a comprehensive review of the epidemiologic evidence linking the continuum of elevated adiposity, hyperinsulinemia, and type 2 diabetes (T2D) with late-onset Alzheimer’s disease (LOAD). The mechanisms relating this continuum to LOAD may be vascular and non-vascular. Elevated adiposity in middle age is related to a higher risk of LOAD but the data on this association in old age are conflicting. Several studies have shown that hyperinsulinemia, a consequence of higher adiposity and insulin resistance, is also related to a higher risk of LOAD. Studies have consistently shown a relationship between T2D and higher LOAD risk. A large proportion of the world population may be at increased risk of LOAD, given the trends for increasing prevalence of overweight, obesity, hyperinsulinemia, and T2D. However, these associations may present a unique opportunity for prevention and treatment of LOAD. Several studies in the prevention and treatment of T2D are currently conducting or have planned cognition ancillary studies. In addition, clinical trials using insulin sensitizers in the treatment or prevention of LOAD are under way.
    03/2010: pages 89-107;
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper describes an activity by the Electric Power Research Institute (EPRI) to provide a handbook for guidance on design, verification and validation of digital upgrades to instrumentation and control systems. The handbook follows a layered design, with a hgh level handbook useful for managers, and supporting detail providing guidance for engineers. A classification approach is central for providing focused guidance for particular classes of applications. I. INTRODUCTION Nuclear utilities have embarked upon extensive programs to replace and upgrade their analog instrumentation and control (I&C) systems with digital technology. These new digital systems cover a wide range of applications, from safetycritical protection systems to non-safety control systems, and their implementations range from customized, turnkey computer systems to utility-integrated configurations of programmable logic controllers. In each case, the utility must address Micult issues of digital system and software quality. To support these utility activities, EPRI is developing a Handbook for Verification and Validation (V&V) of digital I&C systems. V&V is a systematic program of review and testing activities performed throughout the software life cycle. According to IEEE Standard 610.12-1990,
    Journal of Nutritional Biochemistry - J NUTR BIOCHEM. 01/1993;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Given the biological complexity of the ageing process, there is no single, simple and reliable measure of how healthily someone is ageing. Intervention studies need a panel of measures which capture key features of healthy ageing. To help guide our research in this area, we have adopted the concept of the "Healthy Ageing Phenotype" (HAP) and this study aimed to (i) identify the most important features of the HAP and (ii) identify/develop tools for measurement of those features. After a comprehensive assessment of the literature we selected the following domains: physiological and metabolic health, physical capability, cognitive function, social wellbeing, and psychological wellbeing which we hoped would provide a reasonably holistic characterisation of the HAP. We reviewed the literature and identified systematic reviews and/or meta-analysis of cohort studies, and clinical guidelines on outcome measures of these domains relevant to the HAP. Selection criteria for these measures included: frequent use in longitudinal studies of ageing; expected to change with age; evidence for strong association with/prediction of ageing-related phenotypes such as morbidity, mortality and lifespan; whenever possible, focus on studies measuring these outcomes in populations rather than on individuals selected on the basis of a particular disease; (bio)markers that respond to (lifestyle-based) intervention. Proposed markers were exposed to critique in a Workshop held in Newcastle, UK in October 2012. We have selected a tentative panel of (bio)markers of physiological and metabolic health, physical capability, cognitive function, social wellbeing, and psychological wellbeing which we propose may be useful in characterising the HAP and which may have utility as outcome measures in intervention studies. In addition, we have identified a number of tools which could be applied in community-based intervention studies designed to enhance healthy ageing. We have proposed, tentatively, a panel of outcome measures which could be deployed in community-based, lifestyle intervention studies. The evidence base for selection of measurement domains is less well developed in some areas e.g. social wellbeing (where the definition of the concept itself remains elusive) and this has implications for the identification of appropriate tools. Although we have developed this panel as potential outcomes for intervention studies, we recognise that broader agreement on the concept of the HAP and on tools for its measurement could have wider utility and e.g. could facilitate comparisons of healthy ageing across diverse study designs and populations.
    Maturitas 08/2013; · 2.84 Impact Factor

Full-text (2 Sources)

Download
36 Downloads
Available from
May 20, 2014