Ambient air pollution and neurotoxicity on brain structure: Evidence from women's health initiative memory study.

OBJECTIVE: The aim of this study was to examine the putative adverse effects of ambient fine particulate matter (PM2.5 : PM with aerodynamic diameters <2.5µm) on brain volumes in older women. METHODS: We conducted a prospective study of 1,403 community-dwelling older women without dementia enrolled in the Women's Health Initiative Memory Study, 1996-1998. Structural brain magnetic resonance imaging scans were performed at the age of 71-89 years in 2005-2006 to obtain volumetric measures of gray matter (GM) and normal-appearing white matter (WM). Given residential histories and air monitoring data, we used a spatiotemporal model to estimate cumulative PM2.5 exposure in 1999-2006. Multiple linear regression was employed to evaluate the associations between PM2.5 and brain volumes, adjusting for intracranial volumes and potential confounders. RESULTS: Older women with greater PM2.5 exposures had significantly smaller WM, but not GM, volumes, independent of geographical region, demographics, socioeconomic status, lifestyles, and clinical characteristics, including cardiovascular risk factors. For each interquartile increment (3.49µg/m(3) ) of cumulative PM2.5 exposure, the average WM volume (WMV; 95% confidence interval) was 6.23cm(3) (3.72-8.74) smaller in the total brain and 4.47cm(3) (2.27-6.67) lower in the association areas, equivalent to 1 to 2 years of brain aging. The adverse PM2.5 effects on smaller WMVs were present in frontal and temporal lobes and corpus callosum (all p values <0.01). Hippocampal volumes did not differ by PM2.5 exposure. INTERPRETATION: PM2.5 exposure may contribute to WM loss in older women. Future studies are needed to determine whether exposures result in myelination disturbance, disruption of axonal integrity, damages to oligodendrocytes, or other WM neuropathologies.

Nutrition self-efficacy is unidirectionally related to outcome expectations in children.

OBJECTIVE: To clarify the underlying relationship between nutrition self-efficacy and outcome expectations because the direction of the relationship (unidirectional vs bidirectional) is debated in the literature. METHODS: Secondary data analysis of a 10-week, 10-lesson school-based nutrition education intervention among 3rd grade students (N = 952). Nutrition self-efficacy (7 items) and nutrition outcome expectations (9 items) were measured through student self-report at intervention pre- (time 1) and post- (time 2) assessments. A series of two time point, multi-group cross-lagged bivariate change score models were used to determine the direction of the relationship. RESULTS: A cross lag from nutrition self-efficacy at time 1 predicting changes in nutrition outcome expectations at time 2 significantly improved the fit of the model (Model 3), whereas a cross lag from nutrition outcome expectations at time 1 to changes in nutrition self-efficacy at time 2 only slightly improved the fit of the model (Model 2). Furthermore, adding both cross lags (Model 4) did not improve model fit compared to the model with only the self-efficacy cross lag (Model 3). Lastly, the nutrition outcome expectations cross lag did not significantly predict changes in nutrition self-efficacy in any of the models. CONCLUSIONS: Data suggest that there is a unidirectional relationship between nutrition self-efficacy and outcome expectations, in which self-efficacy predicts outcome expectations. Therefore, theory-based nutrition interventions may consider focusing more resources on changing self-efficacy because it may also lead to changes in outcome expectations as well.

On the Mathematical Relationship Between Latent Change Score and Autoregressive Cross-Lagged Factor Approaches: Cautions for Inferring Causal Relationship Between Variables.

The present paper focuses on the relationship between latent change score (LCS) and autoregressive cross-lagged (ARCL) factor models in longitudinal designs. These models originated from different theoretical traditions for different analytic purposes, yet they share similar mathematical forms. In this paper, we elucidate the mathematical relationship between these models and show that the LCS model is reduced to the ARCL model when fixed effects are assumed in the slope factor scores. Additionally, we provide an applied example using height and weight data from a gerontological study. Throughout the example, we emphasize caution in choosing which model (ARCL or LCS) to apply due to the risk of obtaining misleading results concerning the presence and direction of causal precedence between two variables. We suggest approaching model specification not only by comparing estimates and fit indices between the LCS and ARCL models (as well as other models) but also by giving appropriate weight to substantive and theoretical considerations, such as assessing the justifiability of the assumption of random effects in the slope factor scores.

Loehlin's original models and model contributions.

This is a short story about John C. Loehlin who is now at the University of Texas at Austin, dealing with his original simulation models and developments, which led to his current latent variable models. This talk was initially presented at a special meeting for John before the BGA in Rhode Island, and I was very pleased to contribute. It probably goes without saying, but John helped create this important society, has been a key contributor to this journal for several decades, and he deserves a lot for this leadership.

Fighting for Intelligence: A Brief Overview of the Academic Work of John L. Horn.

John L. Horn (1928-2006) was a pioneer in multivariate thinking and the application of multivariate methods to research on intelligence and personality. His key works on individual differences in the methodological areas of factor analysis and the substantive areas of cognition are reviewed here. John was also our mentor, teacher, colleague, and friend. We overview John Horn's main contributions to the field of intelligence by highlighting 3 issues about his methods of factor analysis and 3 of his substantive debates about intelligence. We first focus on Horn's methodological demonstrations describing (a) the many uses of simulated random variables in exploratory factor analysis; (b) the exploratory uses of confirmatory factor analysis; and (c) the key differences between states, traits, and trait-changes. On a substantive basis, John believed that there were important individual differences among people in terms of cognition and personality. These sentiments led to his intellectual battles about (d) Spearman's g theory of a unitary intelligence, (e) Guilford's multifaceted model of intelligence, and (f) the Schaie and Baltes approach to defining the lack of decline of intelligence earlier in the life span. We conclude with a summary of John Horn's unique approaches to dealing with common issues.

The Project TALENT Twin and Sibling Study.

Project TALENT is a US national longitudinal study of about 377,000 individuals born in 1942-1946, first assessed in 1960. Students in about 1,200 schools participated in a 2-day battery covering aptitudes, abilities, interests, and individual and family characteristics (Flanagan, 1962; www.projectTALENT.org). Follow-up assessments 1, 5, and 11 years later assessed educational and occupational outcomes. The sample includes approximately 92,000 siblings from 40,000 families, including 2,500 twin pairs and 1,200 other siblings of twins. Until recently, almost no behavior genetic research has been conducted with the sample. In the original data collection information was not collected with the intent to link family members. Recently, we developed algorithms using names, addresses, birthdates, and information about family structure to link siblings and identify twins. We are testing several methods to determine zygosity, including use of yearbook photographs. In this paper, we summarize the design and measures in Project TALENT, describe the Twin and Sibling sample, and present our twin-sib-classmate model. In most twin and family designs, the 'shared environment' includes factors specific to the family combined with between-family differences associated with macro-level variables such as socioeconomic status. The school-based sampling design used in Project TALENT provides a unique opportunity to partition the shared environment into variation shared by siblings, specific to twins, and associated with school- and community-level factors. The availability of many measured characteristics on the family, schools, and neighborhoods enhances the ability to study the impact of specific factors on behavioral variation.

Factor structure and predictive validity of somatic and nonsomatic symptoms from the patient health questionnaire-9: a longitudinal study after spinal cord injury.

OBJECTIVE: To investigate the factor structure and predictive validity of somatic and nonsomatic depressive symptoms over the first 2.5 years after spinal cord injury (SCI) using the Patient Health Questionnaire-9 (PHQ-9). DESIGN: Somatic and nonsomatic symptoms were assessed at baseline during inpatient hospitalization (average of 50 days after onset) and during 2 follow-ups (average of 498 and 874 days after onset). SETTING: Data were collected at a specialty hospital in the Southeastern United States and analyzed at a medical university. We performed time-lag regression between inpatient baseline and follow-up somatic and nonsomatic latent factors of the PHQ-9. PARTICIPANTS: Adults with traumatic SCI (N=584) entered the study during inpatient rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: PHQ-9, a 9-item measure of depressive symptoms. RESULTS: The inpatient baseline nonsomatic latent factor was significantly predictive of the nonsomatic (r=.40; P=.000) and somatic latent factors at the second follow-up (r=.29; P=.006), whereas the somatic factor at inpatient baseline did not significantly predict either factor. In contrast, when regressing latent factors between the 2 follow-ups, the nonsomatic factor predicted only the nonsomatic factor (r=.66; P=.002), and the somatic factor predicted only future somatic symptoms (r=.66; P=.000). In addition, the factor structure was not stable over time. Item analysis verified the instability of somatic items between inpatient baseline and follow-up and also indicated that self-harm at inpatient baseline was highly predictive of future self-harm. CONCLUSIONS: Nonsomatic symptoms are better predictors of future depressive symptoms when first assessed during inpatient rehabilitation, whereas somatic symptoms become stable predictors only after inpatient rehabilitation. Self-harm (suicidal ideation) is the most stable symptom over time. Clinicians should routinely assess for suicidal ideation and use nonsomatic symptoms when performing assessments during inpatient rehabilitation.

A structural analysis of health outcomes after spinal cord injury.

OBJECTIVE: To develop and validate a latent model of health outcomes among persons with spinal cord injury. METHODS: Survey data were collected at a large specialty hospital in the southeastern USA from 1,388 adult participants with traumatic spinal cord injury of at least 1 year's duration. Multiple indicators of health outcomes were used, including general health ratings, days adversely affected by poor health and poor mental health, treatments and hospitalizations, depressive symptoms, symptoms of illness or infection (eg, sweats, chills, fever), and multiple individual conditions (eg, pressure ulcers, subsequent injuries, fractures, contractures). RESULTS: We performed exploratory factor analysis on half of the sample and confirmatory factor analysis on the other. A 6-factor solution was the best overall solution, because there was an excellent fit with the exploratory factor analysis (root mean square error of approximation = 0.042) and acceptable fit with the confirmatory factor analysis (root mean square error of approximation = 0.065). Four of the factors were types of secondary conditions, including symptoms of illness or infection, orthopedic conditions, pressure ulcers, and subsequent injuries. The 2 remaining factors reflected global health and treatment. Gender, race-ethnicity, age, injury severity, and years of education were all significantly related to at least 1 factor dimension, indicating variations in health outcomes related to these characteristics. CONCLUSION: Identification of the 6 factors represents an improvement over the utilization of multiple individual indicators, because composite scores generated from multiple individual indicators provide more informative and stable outcome scores than utilization of single indicators.

A biometric latent curve analysis of memory decline in older men of the NAS-NRC twin registry.

Previous research has shown cognitive abilities to have different biometric patterns of age-changes. We examined the variation in episodic memory (word recall task) for over 6,000 twin pairs who were initially aged 59-75, and were subsequently re-assessed up to three more times over 12 years. In cross-sectional analyses, variation in the number of words recalled independent of age was explained largely by non-shared influences (65-72%), with clear additive genetic influences (12-32%), and marginal shared family influences (1-18%). The longitudinal phenotypic analysis of the word recall task showed systematic linear declines over age, but several nonlinear models with more dramatic changes at later ages, improved the overall fit. A two-part spline model for the longitudinal twin data with an optimal turning point at age 74 led to: (a) a separation of non-shared environmental influences and transient measurement error (~50%); (b) strong additive genetic components of this latent curve (~44% at age 60) with increases (over 50%) up to age 74, but with no additional genetic variation after age 74; (c) the smaller influences of shared family environment (~15% at age 74) were constant over all ages; (d) non-shared effects play an important role over most of the life-span but diminish after age 74.

Parental education and late-life dementia in the United States.

We investigated the relation between parental education and dementia in the United States. Participants in the Aging, Demographics, and Memory Study were included, with information regarding parental education obtained from the Health and Retirement Study. The odds of dementia in elderly Americans whose mothers had less then 8 years of schooling were twice (95% CI, 1.1-3.8) that of individuals with higher maternal education, when adjusted for paternal education. Of elderly Americans with less educated mothers, 45.4% (95% CI, 37.4-53.4%) were diagnosed with dementia or ;;cognitive impairment, no dementia'' compared to 31.2% (95% CI, 25.0-37.4%) of elderly Americans whose mothers had at least an 8th grade education. The population attributable risk of dementia due to low maternal education was 18.8% (95% CI, 9.4-28.2%). The education of girls in a population may be protective of dementia in the next generation.

Depression as a risk factor or prodromal feature for dementia? Findings in a population-based sample of Swedish twins.

This study tested whether history of depression is associated with an increased likelihood of dementia, and whether a first depressive episode earlier in life is associated with increased dementia risk, or whether only depressive episodes close in time to dementia onset are related to dementia. Depression information came from national hospital discharge registries, medical history, and medical records. Dementia was diagnosed clinically. In case-control results, individuals with recent registry-identified depression were 3.9 times more likely than those with no registry-identified depression history to have dementia, whereas registry-identified depression earlier in life was not associated with dementia risk. Each 1-year increase in time between depression onset and dementia onset or equivalent age decreased the likelihood of dementia by 8.4%. In co-twin control analyses, twins with prior depression were 3.0 times more likely to have dementia than their nondepressed twin partners, with a similar age of depression gradient. These findings suggest that after partially controlling for genetic influences, late-life depression for many individuals may be a prodrome rather than a risk factor for dementia.

Genetic variance in processing speed drives variation in aging of spatial and memory abilities.

Previous analyses have identified a genetic contribution to the correlation between declines with age in processing speed and higher cognitive abilities. The goal of the current analysis was to apply the biometric dual change score model to consider the possibility of temporal dynamics underlying the genetic covariance between aging trajectories for processing speed and cognitive abilities. Longitudinal twin data from the Swedish Adoption/Twin Study of Aging, including up to 5 measurement occasions covering a 16-year period, were available from 806 participants ranging in age from 50 to 88 years at the 1st measurement wave. Factors were generated to tap 4 cognitive domains: verbal ability, spatial ability, memory, and processing speed. Model-fitting indicated that genetic variance for processing speed was a leading indicator of variation in age changes for spatial and memory ability, providing additional support for processing speed theories of cognitive aging.

Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement.

The authors use multiple-sample longitudinal data from different test batteries to examine propositions about changes in constructs over the life span. The data come from 3 classic studies on intellectual abilities in which, in combination, 441 persons were repeatedly measured as many as 16 times over 70 years. They measured cognitive constructs of vocabulary and memory using 8 age-appropriate intelligence test batteries and explore possible linkage of these scales using item response theory (IRT). They simultaneously estimated the parameters of both IRT and latent curve models based on a joint model likelihood approach (i.e., NLMIXED and WINBUGS). They included group differences in the model to examine potential interindividual differences in levels and change. The resulting longitudinal invariant Rasch test analyses lead to a few new methodological suggestions for dealing with repeated constructs based on changing measurements in developmental studies.

Prevalence of cognitive impairment without dementia in the United States.

BACKGROUND: Cognitive impairment without dementia is associated with increased risk for disability, increased health care costs, and progression to dementia. There are no population-based prevalence estimates of this condition in the United States. OBJECTIVE: To estimate the prevalence of cognitive impairment without dementia in the United States and determine longitudinal cognitive and mortality outcomes. DESIGN: Longitudinal study from July 2001 to March 2005. SETTING: In-home assessment for cognitive impairment. PARTICIPANTS: Participants in ADAMS (Aging, Demographics, and Memory Study) who were age 71 years or older drawn from the nationally representative HRS (Health and Retirement Study). Of 1770 selected individuals, 856 completed initial assessment, and of 241 selected individuals, 180 completed 16- to 18-month follow-up assessment. MEASUREMENTS: Assessments, including neuropsychological testing, neurologic examination, and clinical and medical history, were used to assign a diagnosis of normal cognition, cognitive impairment without dementia, or dementia. National prevalence rates were estimated by using a population-weighted sample. RESULTS: In 2002, an estimated 5.4 million people (22.2%) in the United States age 71 years or older had cognitive impairment without dementia. Prominent subtypes included prodromal Alzheimer disease (8.2%) and cerebrovascular disease (5.7%). Among participants who completed follow-up assessments, 11.7% with cognitive impairment without dementia progressed to dementia annually, whereas those with subtypes of prodromal Alzheimer disease and stroke progressed at annual rates of 17% to 20%. The annual death rate was 8% among those with cognitive impairment without dementia and almost 15% among those with cognitive impairment due to medical conditions. LIMITATIONS: Only 56% of the nondeceased target sample completed the initial assessment. Population sampling weights were derived to adjust for at least some of the potential bias due to nonresponse and attrition. CONCLUSION: Cognitive impairment without dementia is more prevalent in the United States than dementia, and its subtypes vary in prevalence and outcomes.

A latent variable structural path model of health behaviors after spinal cord injury.

BACKGROUND/OBJECTIVE: To develop a latent behavioral model by identifying and confirming the factor structure of health behaviors of people with spinal cord injury (SCI) and their relationships with biographic, injury, and educational characteristics. RESEARCH DESIGN: Survey data were collected from 1388 adults with traumatic SCI of at least 1 year duration. MAIN OUTCOME MEASURES: Selection of health behaviors was based on a bidimensional behavioral risk model. Behaviors were measured by core item sets from the Behavioral Risk Factor Surveillance System and supplemented by an alcohol screening measure, select fitness proxies, and the SCI Health Survey. RESULTS: Latent variable structural equation modeling was used to identify underlying factors and their relationship with participant characteristics. Seven specific factors were identified by exploratory factor analysis and were cross-validated using confirmatory factor analysis. They included: (a) healthy nutrition, (b) unhealthy nutrition, (c) fitness, (d) smoking, (e) alcohol use, (f) psychotropic prescription medications, and (g) SCI healthy activities. Two higher-order dimensions were also identified, including a risk dimension (b, d, e) and a protective dimension (a, c, g). Participant characteristics were associated with the domains. For instance, participants with the most severe injuries scored lower on smoking and alcohol but higher on psychotropic medications; age was positively correlated with healthy nutrition and negatively correlated with alcohol and tobacco use but also negatively correlated with fitness. CONCLUSION: Behaviors can be meaningfully combined into underlying dimensions to more efficiently use them as predictors of secondary conditions.

Investigating Ceiling Effects in Longitudinal Data Analysis.

Score limitation at the top of a scale is commonly termed "ceiling effect." Ceiling effects can lead to serious artifactual parameter estimates in most data analysis. This study examines the consequences of ceiling effects in longitudinal data analysis and investigates several methods of dealing with ceiling effects through Monte Carlo simulations and empirical data analyses. Data were simulated based on a latent growth curve model with T = 5 occasions. The proportion of the ceiling data [10%-40%] was manipulated by using different thresholds, and estimated parameters were examined for R = 500 replications. The results showed that ceiling effects led to incorrect model selection and biased parameter estimation (shape of the curve and magnitude of the changes) when regular growth curve models were applied. The Tobit growth curve model, instead, performed very well in dealing with ceiling effects in longitudinal data analysis. The Tobit growth curve model was then applied in an empirical cognitive aging study and the results were discussed.

A latent change score analysis of a randomized clinical trial in reasoning training.

The authors analyzed longitudinal data from a cognitive training experiment--Advanced Cognitive Training for Independent and Vital Elderly--using several alternative contemporary statistical models to test dynamic hypotheses based on latent change scores. The analyses focused on pretest and posttest data for only the group who received Reasoning training compared with the No-Contact (control) group. The initial structural equation modeling (SEM) path model isolated several training effects and an important source of transfer of training, Near-->Far, but this transfer was not increased due to training. The subsequent models, which accounted for pretest differences and latent changes, implied that only the Near measurements were influenced by training, and the change transfer was small. Introduction of common factors for both Near and Far measurements showed the factor patterns were unaffected by training or time and suggested training was a broader effect than in any single variable. The bivariate analysis of common factors did not appear to alter the previous results. Addition of demographic covariates and latent mixture analysis of the trained group led to further results. The uses of contemporary SEMs with experimental data are discussed.

Neuropsychological measures in normal individuals that predict subsequent cognitive decline.

OBJECTIVE: To examine neuropsychological measures among normal individuals that predict time to subsequent cognitive decline. DESIGN: Cognitive performance, as measured by 6 neuropsychological tests, was examined at baseline. Participants were followed up for approximately 5 years. Cox proportional hazards models were used to evaluate the neuropsychological measures at baseline that predicted time to progression from normal cognition to mild impairment. Comparable data also examined time to progression from mild impairment to a diagnosis of Alzheimer disease. SETTING: Community volunteer-based sample examined at a medical institution. PARTICIPANTS: One hundred and seven individuals who were cognitively normal and 235 individuals with mild cognitive impairment at baseline. MAIN OUTCOME MEASURES: Time to progression from normal cognition to mild impairment and time to progression from mild impairment to a diagnosis of Alzheimer disease. RESULTS: The risk of progressing from normal to mild impairment was considerably greater among those with lower scores on tests of episodic memory (eg, hazard ratio for a 1-SD decrease in the California Verbal Learning Test, 0.55; P<.001). Normal individuals who carried at least 1 copy of the apolipoprotein E epsilon2 allele were less likely to develop cognitive impairments over time than individuals with no epsilon2 allele (hazard ratio for presence of allele, 0.13; P = .006). Measures of both episodic memory and executive function were significant predictors of time to progression from mild impairment to a clinical diagnosis of Alzheimer disease (eg, hazard ratio for a 1-SD decrease in California Verbal Learning Test score, 0.67; P = .005; hazard ratio for a 1-SD increase in the time to complete part B of the Trail Making test, 1.40; P = .007). Among individuals with mild impairments, the apolipoprotein E epsilon4 allele increased risk for Alzheimer disease in a dose-dependent manner; however, this effect was not significant within the context of multivariable models. CONCLUSIONS: Episodic memory performance among normal individuals predicts time to progression to mild impairment while apolipoprotein E epsilon2 status is associated with lower risk of cognitive decline among normal individuals. Tests of both episodic memory and executive function are predictors of time to progression from mild impairment to a clinical diagnosis of Alzheimer disease.

Longitudinal change in cognitive performance among individuals with mild cognitive impairment.

The authors used mixed-effects growth models to examine longitudinal change in neuropsychological performance over a 4-year period among 197 individuals who were either normal or had mild cognitive impairment (MCI) at baseline. At follow-up, the participants were divided into 4 groups: (a) controls: participants who were normal at both baseline and follow-up (n = 33), (b) stables: participants with MCI whose Clinical Dementia Rating-Sum of Boxes (CDR-SB) score did not differ between the first and last evaluations (n = 22), (c) decliners: participants with MCI whose CDR-SB score declined between the first and last evaluations (n = 95), and (d) converters: participants who received a clinical diagnosis of Alzheimer's disease during the follow-up period (n = 47). Only the Episodic Memory factor showed a significantly greater rate of decline over the follow-up period among the converters. Two other factors were significantly lower in converters at baseline in comparison with other groups (the executive function factor and the general knowledge factor), but the rate of decline over time did not differ. Individuals with an APOE epsilon4 allele scored lower on the episodic memory and executive function factors at baseline.

John L. Horn (1928-2006).

John Leonard Horn was born in St. Joseph, Missouri, on September 7, 1928, and he died in Los Angeles, California, on August 18, 2006. John Horn was a world-renowned scholar of immense intellect, and he was highly respected in his time. I believe his major contributions to psychology, as well as his influence on psychologists, will continue to grow. His challenging factor-analytic methods of the 1960s, the important methodological debates of the 1970s and 1980s, and his continuing resistance to faddish trends in psychological research all represent fundamental contributions. Through his research and teaching he forced people to question popular assumptions and to evaluate all the data available. He challenged us to think longer, harder, and better. His work will continue to inspire important research in the fields of multivariate analysis and human cognitive abilities for many decades to come.