Differing Effects of Education on Cognitive Decline in Diverse Elders with Low Versus High Educational Attainment

OBJECTIVE: In light of growing debate over whether and how early life educational experiences alter late-life cognitive trajectories, this study sought to more thoroughly investigate the relationship between educational attainment and rates of late-life cognitive decline in a racially, ethnically, and educationally diverse population. METHOD: Older adults (N = 3,435) in the community-based Washington Heights-Inwood Columbia Aging Project were administered neuropsychological tests of memory, language, visuospatial function, and processing speed at approximate 24-month intervals for up to 18 years. Second-order latent growth curves estimated direct and indirect (through income) effects of educational attainment on rates of global cognitive decline separately in individuals with low (0-8 years) and high (9-20 years) educational attainment. RESULTS: More years of education were associated with higher cognitive level and slower cognitive decline in individuals with low or high educational attainment. The association between having more than 9 years of education and exhibiting slower cognitive decline was fully mediated by income. Although having additional years of education up to 8 years was also associated with higher income, this did not explain associations between education and cognitive change in the low-education group. CONCLUSIONS: Early education (i.e., up to 8 years) may promote aspects of development during a sensitive period of childhood that protect against late-life cognitive decline independent of income. In contrast, later education (i.e., 9 years and beyond) is associated with higher income, which may influence late-life cognitive health through multiple, nonmutually exclusive pathways

Continuous time resource selection analysis for moving animals

1.Resource selection analysis (RSA) seeks to understand how spatial abundance covaries with environmental features. By combining RSA with movement, step selection analysis (SSA) has helped uncover the mechanisms behind animal relocations, thereby giving insight into the movement decisions underlying spatial patterns. However, SSA typically assumes that at each observed location, an animal makes a 'selection' of the next observed location. This conflates observation with behavioural mechanism and does not account for decisions occurring at any other time along the animal's path. 2.To address this, we introduce a continuous time framework for resource selection. It is based on a switching Ornstein‐Uhlenbeck (OU) model, parameterised by Bayesian Monte Carlo techniques. Such OU models have been used successfully to identify switches in movement behaviour, but hitherto not combined with resource selection. We test our inference procedure on simulated paths, representing both migratory movement (where landscape quality varies according to season) and foraging with depletion and renewal of resources (where the variation is due to past locations of the animals). We apply our framework to location data of migrating mule deer (Odocoileus hemionus) to shed light on the drivers of migratory decisions. 3.In a wide variety of simulated situations, our inference procedure returns reliable estimations of the parameter values, including the extent to which animals trade‐off resource quality and travel distance (within 95% posterior intervals for the vast majority of cases). When applied to the mule deer data, our model reveals some individual variation in parameter values. Nevertheless, the migratory decisions of most individuals are well‐described by a model that accounts for the cost of moving and the difference between instantaneous change of vegetation quality at source and target patches. 4.We have introduced a technique for inferring the resource‐driven decisions behind animal movement that accounts for the fact that these decisions may take place at any point along a path, not just when the animal's location is known. This removes an oft‐acknowledged but hitherto little‐addressed shortcoming of stepwise movement models. Our work is of key importance in understanding how environmental features drive movement decisions and, as a consequence, space use patterns

The role of place in explaining racial heterogeneity in cognitive outcomes among older adults

Racially patterned disadvantage in Southern states, especially during the formative years of primary school, may contribute to enduring disparities in adult cognitive outcomes. Drawing on a lifecourse perspective, we examine whether state of school attendance affects cognitive outcomes in older adults and partially contributes to persistent racial disparities. Using data from older African American and white participants in the national Health and Retirement Study (HRS) and the New York based Washington Heights Inwood Cognitive Aging Project (WHICAP), we estimated age-and gender-adjusted multilevel models with random effects for states predicting years of education and cognitive outcomes (e.g., memory and vocabulary). We summarized the proportion of variation in outcomes attributable to state of school attendance and compared the magnitude of racial disparities across states. Among WHICAP African Americans, state of school attendance accounted for 9% of the variance in years of schooling, 6% of memory, and 12% of language. Among HRS African Americans, state of school attendance accounted for 13% of the variance in years of schooling and also contributed to variance in cognitive function (7%), memory (2%), and vocabulary (12%). Random slope models indicated state-level African American and white disparities in every Census region, with the largest racial differences in the South. State of school attendance may contribute to racial disparities in cognitive outcomes among older Americans. Despite tremendous within-state heterogeneity, state of school attendance also accounted for some variability in cognitive outcomes. Racial disparities in older Americans may reflect historical patterns of segregation and differential access to resources such as educatio

Quantifying Cognitive Reserve in Older Adults by Decomposing Episodic Memory Variance: Replication and Extension

The theory of cognitive reserve attempts to explain why some individuals are more resilient to age-related brain pathology. Efforts to explore reserve have been hindered by measurement difficulties. Reed et al. (2010) proposed quantifying reserve as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). This residual variance represents the discrepancy between an individual's predicted and actual memory performance. The goals of the present study were to extend these methods to a larger, community-based sample and to investigate whether the residual reserve variable is explained by age, predicts longitudinal changes in language, and predicts dementia conversion independent of age. Results support this operational measure of reserve. The residual reserve variable was associated with higher reading ability, lower likelihood of meeting criteria for mild cognitive impairment, lower odds of dementia conversion in dependent of age, and less decline in language abilities over 3 years. Finally, the residual reserve variable moderated the negative impact of memory variance explained by brain pathology on language decline. This method has the potential to facilitate research on the mechanisms of cognitive reserve and the efficacy of interventions designed to impart reserve

Effects of wind energy development on nesting ecology of Greater Prairie-Chickens in fragmented grasslands

Wind energy is targeted to meet 20% of U.S. energy needs by 2030, but new sites for development of renewable energy may overlap with important habitats of declining populations of grassland birds. Greater Prairie-Chickens (Tympanuchus cupido) are an obligate grassland bird species predicted to respond negatively to energy development. We used a modified before–after control–impact design to test for impacts of a wind energy development on the reproductive ecology of prairie-chickens in a 5-year study. We located 59 and 185 nests before and after development, respectively, of a 201 MW wind energy facility in Greater Prairie-Chicken nesting habitat and assessed nest site selection and nest survival relative to proximity to wind energy infrastructure and habitat conditions. Proximity to turbines did not negatively affect nest site selection (β = 0.03, 95% CI = −1.2–1.3) or nest survival (β = −0.3, 95% CI = −0.6–0.1). Instead, nest site selection and survival were strongly related to vegetative cover and other local conditions determined by management for cattle production. Integration of our project results with previous reports of behavioral avoidance of oil and gas facilities by other species of prairie grouse suggests new avenues for research to mitigate impacts of energy development

Cognitive tests used in chronic adult human randomised controlled trial micronutrient and phytochemical intervention studies

In recent years there has been a rapid growth of interest in exploring the relationship between nutritional therapies and the maintenance of cognitive function in adulthood. Emerging evidence reveals an increasingly complex picture with respect to the benefits of various food constituents on learning, memory and psychomotor function in adults. However, to date, there has been little consensus in human studies on the range of cognitive domains to be tested or the particular tests to be employed. To illustrate the potential difficulties that this poses, we conducted a systematic review of existing human adult randomised controlled trial (RCT) studies that have investigated the effects of 24 d to 36 months of supplementation with flavonoids and micronutrients on cognitive performance. There were thirty-nine studies employing a total of 121 different cognitive tasks that met the criteria for inclusion. Results showed that less than half of these studies reported positive effects of treatment, with some important cognitive domains either under-represented or not explored at all. Although there was some evidence of sensitivity to nutritional supplementation in a number of domains (for example, executive function, spatial working memory), interpretation is currently difficult given the prevailing 'scattergun approach' for selecting cognitive tests. Specifically, the practice means that it is often difficult to distinguish between a boundary condition for a particular nutrient and a lack of task sensitivity. We argue that for significant future progress to be made, researchers need to pay much closer attention to existing human RCT and animal data, as well as to more basic issues surrounding task sensitivity, statistical power and type I error

Predicting population change from models based on habitat availability and utilization.

The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations

Buda-Lund hydro model for ellipsoidally symmetric fireballs and the elliptic flow at RHIC

The ellipsoidally symmetric extension of Buda-Lund hydrodynamic model is shown here to yield a natural description of the pseudorapidity dependence of the elliptic flow $v_2(\eta)$, as determined recently by the PHOBOS experiment for Au+Au collisions at $\sqrt{s_{NN}} = 130$ and 200 GeV. With the same set of parameters, the Buda-Lund model describes also the transverse momentum dependence of $v_2$ of identified particles at mid-rapidity. The results confirm the indication for quark deconfinement in Au+Au collisions at RHIC, obtained from a successful Buda-Lund hydro model fit to the single particle spectra and two-particle correlation data, as measured by the BRAHMS, PHOBOS, PHENIX and STAR collaborations.Comment: 16 pages, 2 figures, 1 table added, discussion extended and an important misprint in the caption of Fig. 1 is correcte

The Importance of Correlations and Fluctuations on the Initial Source Eccentricity in High-Energy Nucleus-Nucleus Collisions

In this paper, we investigate various ways of defining the initial source eccentricity using the Monte Carlo Glauber (MCG) approach. In particular, we examine the participant eccentricity, which quantifies the eccentricity of the initial source shape by the major axes of the ellipse formed by the interaction points of the participating nucleons. We show that reasonable variation of the density parameters in the Glauber calculation, as well as variations in how matter production is modeled, do not significantly modify the already established behavior of the participant eccentricity as a function of collision centrality. Focusing on event-by-event fluctuations and correlations of the distributions of participating nucleons we demonstrate that, depending on the achieved event-plane resolution, fluctuations in the elliptic flow magnitude $v_2$ lead to most measurements being sensitive to the root-mean-square, rather than the mean of the $v_2$ distribution. Neglecting correlations among participants, we derive analytical expressions for the participant eccentricity cumulants as a function of the number of participating nucleons, \Npart,keeping non-negligible contributions up to \ordof{1/\Npart^3}. We find that the derived expressions yield the same results as obtained from mixed-event MCG calculations which remove the correlations stemming from the nuclear collision process. Most importantly, we conclude from the comparison with MCG calculations that the fourth order participant eccentricity cumulant does not approach the spatial anisotropy obtained assuming a smooth nuclear matter distribution. In particular, for the Cu+Cu system, these quantities deviate from each other by almost a factor of two over a wide range in centrality.Comment: 18 pages, 10 figures, submitted to PR