Comparisons of disease cluster patterns, prevalence and health factors in the USA, Canada, England and Ireland.

BACKGROUND: Identification of those who are most at risk of developing specific patterns of disease across different populations is required for directing public health policy. Here, we contrast prevalence and patterns of cross-national disease incidence, co-occurrence and related risk factors across population samples from the U.S., Canada, England and Ireland. METHODS: Participants (n = 62,111) were drawn from the US Health and Retirement Study (n = 10,858); the Canadian Longitudinal Study on Ageing (n = 36,647); the English Longitudinal Study of Ageing (n = 7938) and The Irish Longitudinal Study on Ageing (n = 6668). Self-reported lifetime prevalence of 10 medical conditions, predominant clusters of multimorbidity and their specific risk factors were compared across countries using latent class analysis. RESULTS: The U.S. had significantly higher prevalence of multimorbid disease patterns and nearly all diseases when compared to the three other countries, even after adjusting for age, sex, BMI, income, employment status, education, alcohol consumption and smoking history. For the U.S. the most at-risk group were younger on average compared to Canada, England and Ireland. Socioeconomic gradients for specific disease combinations were more pronounced for the U.S., Canada and England than they were for Ireland. The rates of obesity trends over the last 50 years align with the prevalence of eight of the 10 diseases examined. While patterns of disease clusters and the risk factors related to each of the disease clusters were similar, the probabilities of the diseases within each cluster differed across countries. CONCLUSIONS: This information can be used to better understand the complex nature of multimorbidity and identify appropriate prevention and management strategies for treating multimorbidity across countries.

A novel approach to model cumulative stress: Area under the s-factor curve.

OBJECTIVE: Using a large longitudinal sample of adults from the Midlife in the United States (MIDUS) study, the present study extended a recently developed hierarchical model to determine how best to model the accumulation of stressors, and to determine whether the rate of change in stressors or traditional composite scores of stressors are stronger predictors of health outcomes. METHOD: We used factor analysis to estimate a stress-factor score and then, to operationalize the accumulation of stressors we examined five approaches to aggregating information about repeated exposures to multiple stressors. The predictive validity of these approaches was then assessed in relation to different health outcomes. RESULTS: The prediction of chronic conditions, body mass index, difficulty with activities of daily living, executive function, and episodic memory later in life was strongest when the accumulation of stressors was modeled using total area under the curve (AUC) of estimated factor scores, compared to composite scores that have traditionally been used in studies of cumulative stress, as well as linear rates of change. CONCLUSIONS: Like endogenous, biological markers of stress reactivity, AUC for individual trajectories of self-reported stressors shows promise as a data reduction technique to model the accumulation of stressors in longitudinal studies. Overall, our results indicate that considering different quantitative models is critical to understanding the sequelae and predictive power of psychosocial stressors from midlife to late adulthood.

Cohort Changes and Sex Differences After Age 50 in Cognitive Variables in the English Longitudinal Study of Ageing.

OBJECTIVES: This paper models cognitive aging, across mid and late life, and estimates birth cohort and sex differences in both initial levels and aging trajectories over time in a sample with multiple cohorts and a wide span of ages. METHODS: The data used in this study came from the first 9 waves of the English Longitudinal Study of Ageing, spanning 2002-2019. There were n = 76,014 observations (proportion male 45%). Dependent measures were verbal fluency, immediate recall, delayed recall, and orientation. Data were modeled using a Bayesian logistic growth curve model. RESULTS: Cognitive aging was substantial in 3 of the 4 variables examined. For verbal fluency and immediate recall, males and females could expect to lose about 30% of their initial ability between the ages of 52 and 89. Delayed recall showed a steeper decline, with males losing 40% and females losing 50% of their delayed recall ability between ages 52 and 89 (although females had a higher initial level of delayed recall). Orientation alone was not particularly affected by aging, with less than a 10% change for either males or females. Furthermore, we found cohort effects for initial ability level, with particularly steep increases for cohorts born between approximately 1930 and 1950. DISCUSSION: These cohort effects generally favored later-born cohorts. Implications and future directions are discussed.

It Runs in the Family: Testing for Longitudinal Family Flynn Effects.

The Flynn effect refers to increases over time in measured (particularly fluid) intelligence of approximately 3 IQ points per decade. We define the Flynn effect at the family level, using longitudinal data and two new family-level cohort definitions. Multilevel growth curve analyses of the National Longitudinal Survey of Youth 1979 data showed that children in families with later-born mothers had higher average PIAT math scores, and lower average reading comprehension scores and growth, in young and middle childhood. Children in families where the first child was born later had higher average PIAT math, reading recognition, and reading comprehension scores, as well as larger developmental growth. The latter family-level Flynn effects were of higher magnitudes than the usual individual-level Flynn effect found in previous studies. Our results, showing family level-intercept and slope Flynn effects for both maternal birthyear and first child birthyear, have implications for research aiming to explain the Flynn effect.

An integrative approach for the analysis of risk and health across the life course: challenges, innovations, and opportunities for life course research.

Life course epidemiology seeks to understand the intricate relationships between risk factors and health outcomes across different stages of life to inform prevention and intervention strategies to optimize health throughout the lifespan. However, extant evidence has predominantly been based on separate analyses of data from individual birth cohorts or panel studies, which may not be sufficient to unravel the complex interplay of risk and health across different contexts. We highlight the importance of a multi-study perspective that enables researchers to: (a) Compare and contrast findings from different contexts and populations, which can help identify generalizable patterns and context-specific factors; (b) Examine the robustness of associations and the potential for effect modification by factors such as age, sex, and socioeconomic status; and (c) Improve statistical power and precision by pooling data from multiple studies, thereby allowing for the investigation of rare exposures and outcomes. This integrative framework combines the advantages of multi-study data with a life course perspective to guide research in understanding life course risk and resilience on adult health outcomes by: (a) Encouraging the use of harmonized measures across studies to facilitate comparisons and synthesis of findings; (b) Promoting the adoption of advanced analytical techniques that can accommodate the complexities of multi-study, longitudinal data; and (c) Fostering collaboration between researchers, data repositories, and funding agencies to support the integration of longitudinal data from diverse sources. An integrative approach can help inform the development of individualized risk scores and personalized interventions to promote health and well-being at various life stages.

Getting a Grip on Secular Changes: Age-Period-Cohort Modeling of Grip Strength in the English Longitudinal Study of Ageing.

BACKGROUND: Grip strength is a popular and valuable measure in studies of physical functional capabilities in old age. The influence of historical trends and differential period-specific exposures can complicate the interpretation of biomarkers of aging and health and requires careful analysis and interpretation of aging, birth cohort, and period effects. This study evaluates the effects of aging, period, and cohort on grip strength in a population of adults and older adults. METHODS: We use more than 27 000 observations for individuals at least 50 years of age, born in approximately 1910-1960, from the English Longitudinal Study of Ageing to examine a variety of multilevel and cross-classified modeling approaches to evaluate age, period, and cohort effects. Our results extended Hierarchical Age-Period-Cohort modeling and compared our results with a set of 9 submodels with explicit assumptions to determine the most reliable modeling approach. RESULTS: Findings suggest grip strength is primarily related to age, with minimal evidence of either period and/or cohort effects. Each year's increase in a person's age was associated with a 0.40-kg decrease in grip strength, though this decline differs by gender. CONCLUSIONS: We conclude that as the population ages, grip strength declines at a systematic and predictable rate equal to -0.40 kg per year (approximately -0.50 kg for men and -0.30 kg for women) in residents of England aged 50 and older. Age effects were predominant and most consistent across methodologies. While there was some evidence for cohort effects, such effects were minimal and therefore indicative that grip strength is a consistent physiological biomarker of aging.

Methodological considerations when establishing reliable and valid normative data: Canadian Longitudinal Study on Aging (CLSA) neuropsychological battery.

Objective: Creation of normative data with regression corrections for demographic covariates reduces risk of small cell sizes compared with traditional normative approaches. We explored whether methods of correcting for demographic covariates (e.g., full regression models versus hybrid models with stratification and regression) and choice of covariates (i.e., correcting for age with or without sex and/or education correction) impacted reliability and validity of normative data. Method: Measurement invariance for sex and education was explored in a brief telephone-administered cognitive battery from the Canadian Longitudinal Study on Aging (CLSA; after excluding persons with neurological conditions N = 12,350 responded in English and N = 1,760 in French). Results: Measurement invariance was supported in hybrid normative models where different age-based regression models were created for groups based on sex and education level. Measurement invariance was not supported in full regression models where age, sex, and education were simultaneous predictors. Evidence for reliability was demonstrated by precision defined as the 95% inter-percentile range of the 5th percentile. Precision was higher for full regression models than for hybrid models but with negligible differences in precision for the larger English sample. Conclusions: We present normative data for a remotely administered brief neuropsychological battery that best mitigates measurement bias and are precise. In the smaller French speaking sample, only one model reduced measurement bias, but its estimates were less precise, underscoring the need for large sample sizes when creating normative data. The resulting normative data are appended in a syntax file.

The Canadian longitudinal study on aging as a platform for exploring cognition in an aging population.

Objective: We present descriptive information on the cognitive measures used in the Canadian Longitudinal Study on Aging (CLSA) Comprehensive Cohort, relate this to information on these measures in the extant literature, and identify key considerations for their use in research and clinical practice.Method: The CLSA Comprehensive Cohort is composed of 30,097 participants aged 45-85 years at baseline who provided a broad range of sociodemographic, physical, social, and psychological health information via questionnaire and took part in detailed physical and cognitive assessments. Cognitive measures included: the Rey Auditory Verbal Learning Test - immediate and 5-min delayed recall, Animal Fluency, Mental Alternation Test (MAT), Controlled Oral Word Association Test (COWAT), Stroop Test - Victoria Version, Miami Prospective Memory Test (MPMT), and a Choice Reaction Time (CRT) task.Results: CLSA Comprehensive Cohort sample sizes were far larger than previous studies, and performances on the cognitive measures were similar to comparable groups. Within the CLSA Comprehensive Cohort, main effects of age were observed for all cognitive measures, and main effects of language were observed for all measures except the CRT. Interaction effects (language × age) were observed for the MAT, MPMT Event-based score, all time scores on the Stroop Test, and most COWAT scores. Main effects of education were observed for all measures except for the MPMT Time score in the French sample, and interaction effects (age × education) were observed for the RAVLT (immediate and delayed) for the English sample and the Stroop Dot time for the French sample.Conclusion: This examination of the cognitive measures used in the CLSA Comprehensive Cohort lends support to their use in large studies of health and aging. We propose further exploration of the cognitive measures within the CLSA to make this information relevant to and available for clinical practice.

Miami Prospective Memory Test in the Canadian Longitudinal Study on Aging.

OBJECTIVE: The aim of this study was to verify the effect of age, education and sex on Miami Prospective Memory Test (MPMT) performance obtained at baseline of the Canadian Longitudinal Study on Aging (CLSA) by neurologically healthy French- and English-speaking subsamples of participants (N = 18,511). METHOD: The CLSA is a nation-wide large epidemiological study with participants aged 45-85 years old at baseline. The MPMT is an event- and time-based measure of prospective memory, with scores of intention, accuracy and need for reminders, administered as part of the Comprehensive data collection. Participants who did not self-report any conditions that could impact cognition were selected, which resulted in 15,103 English- and 3408 French-speaking participants. The samples are stratified according to four levels of education and four age groups (45-54; 55-64; 65-74; 75+). RESULTS: There is a significant age effect for English- and French-speaking participants on the Event-based, Time-based, and Event- + Time-based scores of the MPMT. The effect of the education level was also demonstrated on the three MPMT scores in the English-speaking group. The score 'Intention to perform' was the most sensitive to the effect of age in both the English and French samples. Sex had no impact on performance on the MPMT. CONCLUSIONS: This study confirms the impact of age and level of education on this new prospective memory task. It informs future research with this measure including the development of normative data in French- and English-speaking Canadians on the Event-based and Time-based MPMT.

Normative comparison standards for measures of cognition in the Canadian Longitudinal Study on Aging (CLSA): Does applying sample weights make a difference?

Large-scale studies present the opportunity to create normative comparison standards relevant to populations. Sampling weights applied to the sample data facilitate extrapolation to the population of origin, but normative scores are often developed without the use of these sampling weights because the values derived from large samples are presumed to be precise estimates of the population parameter. The present article examines whether applying sample weights in the context of deriving normative comparison standards for measures of cognition would affect the distributions of regression-based normative data when using data from a large population-based study. To address these questions, we examined 3 cognitive measures from the Canadian Longitudinal Study on Aging tracking cohort (N = 14,110, Age 45-84 years at recruitment): Rey Auditory Verbal Learning Test - Immediate Recall, Animal Fluency, and the Mental Alternation Test. The use of sampling weights resulted in similar model parameter estimates to unweighted regression analyses and similar cumulative frequency distributions to the unweighted analyses. We randomly sampled progressively smaller subsets from the full database to test the hypothesis that sampling weights would help maintain the estimates from the full sample, but discovered that the weighted and unweighted estimates were similar and were less precise with smaller samples. These findings suggest that although use of sampling weights can help mitigate biases in data from sampling procedures, the application of weights to adjust for sampling biases do not appreciably impact the normative data, which lends support to the current practice in creation of normative data. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

An evidence-based approach to the creation of normative data: base rates of impaired scores within a brief neuropsychological battery argue for age corrections, but against corrections for medical conditions.

OBJECTIVE: We detail a new approach to the creation of normative data for neuropsychological tests. The traditional approach to normative data creation is to make demographic adjustments based on observations of correlations between single neuropsychological tests and selected demographic variables. We argue, however, that this does not describe the implications for clinical practice, such as increased likelihood of misclassification of cognitive impairment, nor does it elucidate the impact on decision-making with a neuropsychological battery. METHOD: We propose base rate analyses; specifically, differential base rates of impaired scores between theoretical and actual base rates as the basis for decisions to create demographic adjustments within normative data. Differential base rates empirically describe the potential clinical implications of failing to create an appropriate normative group. We demonstrate this approach with data from a short telephone-administered neuropsychological battery given to a large, neurologically healthy sample aged 45-85 years old. We explored whether adjustments for age and medical conditions were warranted based on differential base rates of spuriously impaired scores. CONCLUSIONS: Theoretical base rates underestimated the frequency of impaired scores in older adults and overestimated the frequency of impaired scores in younger adults, providing an evidence base for the creation of age-corrected normative data. In contrast, the number of medical conditions (numerous cardiovascular, hormonal, and metabolic conditions) was not related to differential base rates of impaired scores. Despite a small correlation between number of medical conditions and each neuropsychological variable, normative adjustments for number of medical conditions does not appear warranted. Implications for creation of normative data are discussed.