scholarly journals Trajectories of Aging Among U.S. Older Adults: Mixed Evidence for a Hispanic Paradox

2018 ◽  
Vol 75 (3) ◽  
pp. 601-612 ◽  
Author(s):  
Wassim Tarraf ◽  
Gail A Jensen ◽  
Heather E Dillaway ◽  
Priscilla M Vásquez ◽  
Hector M González
Keyword(s):  
Latent Class ◽  
Population Heterogeneity ◽  
High Morbidity ◽  
Hispanic Paradox ◽  
Logit Models ◽  
Foreign Born ◽  
Multinomial Logit Models ◽  
Curve Modeling ◽  
Risk Ratios ◽  
Retirement Study

Abstract Objectives A well-documented paradox is that Hispanics tend to live longer than non-Hispanic Whites (NHW), despite structural disadvantages. We evaluate whether the “Hispanic paradox” extends to more comprehensive longitudinal aging classifications and examine how lifecourse factors relate to these groupings. Methods We used biennial data (1998–2014) on adults aged 65 years and older at baseline from the Health and Retirement Study. We use joint latent class discrete time and growth curve modeling to identify trajectories of aging, and multinomial logit models to determine whether U.S.-born (USB-H) and Foreign-born (FB-H) Hispanics experience healthier styles of aging than non-Hispanic Whites (NHW), and test how lifecycle factors influence this relationship. Results We identify four trajectory classes including, “cognitive unhealthy,” “high morbidity,” “nonaccelerated”, and “healthy.” Compared to NHWs, both USB-H and FB-H have higher relative risk ratios (RRR) of “cognitive unhealthy” and “high morbidity” classifications, relative to “nonaccelerated.” These patterns persist upon controlling for lifecourse factors. Both Hispanic groups, however, also have higher RRRs for “healthy” classification (vs “nonaccelerated”) upon adjusting for adult achievements and health behaviors. Discussion Controlling for lifefcourse factors USB-H and FB-H have equal or higher likelihood for “high morbidity” and “cognitive unhealthy” classifications, respectively, relative to NHWs. Yet, both groups are equally likely of being in the “healthy” group compared to NHWs. These segregations into healthy and unhealthy groups require more research and could contribute to explaining the paradoxical patterns produced when population heterogeneity is not taken into account.

scholarly journals Do Life Course Physical Activity Profiles Reduce the Effects of Childhood Exposures on Cognition?

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 29-29
Author(s):  
Monica Williams-Farrelly ◽  
Jacqui Smith
Keyword(s):  
Physical Activity ◽  
Life Course ◽  
Healthy Aging ◽  
Latent Class ◽  
Mail Survey ◽  
Learning Problems ◽  
Average Reference ◽  
Curve Modeling ◽  
The Relationship ◽  
Retirement Study

Abstract Although physical activity throughout life is one of the most reliable predictors of healthy aging, can less consistent or favorable trajectories also improve cognition trajectories among older adults? Drawing from accumulation theories, we use longitudinal data from the Health and Retirement Study and Life History Mail Survey (N=9,309) to examine the early antecedents of cognitive decline and the extent to which different life course physical activity profiles can slow such a decline. Results from latent class analysis reveal seven distinct profiles: consistently low, consistently high, consistently average (reference), improvers, decliners, midlife motivators, and previously athletic “couch potatoes.” Growth curve modeling analyses show that membership in the consistently high class and midlife motivators were associated with better cognition initially and over time, with no difference between the two classes. Additionally, though poor health and learning problems in childhood were associated with worse initial cognition, physical activity does not mediate the relationship.

scholarly journals Association Between Baseline Glycemic Markers (HbA1c) and 8-Year Trajectories of Functional Disability

2019 ◽  
Vol 74 (11) ◽  
pp. 1828-1834 ◽  
Author(s):  
Miriam Mutambudzi ◽  
Carlos Díaz-Venegas ◽  
Sonia Menon
Keyword(s):  
Glycemic Control ◽  
Latent Class ◽  
Functional Disability ◽  
Multinomial Logistic Regression ◽  
Clinical Care ◽  
Multinomial Logistic Regression Analysis ◽  
Glycemic Markers ◽  
Risk Ratios ◽  
Retirement Study ◽  
Hba1c Levels

Abstract Background This study assessed whether baseline (i) HbA1c (low [<5.7%], intermediate [5.7%–6.4%], and high [≥6.5%]) and (ii) glycemic control (7% HbA1c cutoff) in participants with self-reported diabetes were associated with differential 8-year functional disability trajectories. Methods We used data from the 2006–2014 waves of the Health and Retirement Study for adults aged 50 years and older. Latent class mixture modeling was used to identify distinct functional disability trajectory classes. Multinomial logistic regression analysis examined the association between the newly constructed trajectories and baseline HbA1c levels, and glycemic control, respectively. Results All participants (N = 5,966) were classified into four functional disability trajectory classes (no disability, low disability, low-increasing, and high-increasing). Participants with elevated HbA1c were at greater risk of being classified into the high-increasing (relative risk ratios = 1.63, 95% confidence interval [CI] = 1.25–2.11) trajectory class. Results showed significant effect modification by age and race. Three functional disability trajectories (no disability, low-increasing, and high-increasing) were identified for participants with self-reported diabetes (n = 1,119). There was no significant association between glycemic control in adults with self-reported diabetes and functional disability trajectory classes. Conclusions Participants with intermediate HbA1c and elevated HbA1c were more likely to be classified into the trajectories with progressing disability over the study period. More research is needed to better understand the association between glycemic markers and functional disability trajectories. Such research may provide insights into improvements for clinical care, self-management, and public health interventions for both conditions.

scholarly journals Profiles of Family and Friend Caregivers of Community-Dwelling People With Dementia: A Latent Class Analysis

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 59-59
Author(s):  
Eric Jutkowitz ◽  
Lauren Mitchell ◽  
Joseph Gaugler
Keyword(s):  
Latent Class Analysis ◽  
Latent Class ◽  
Disease Onset ◽  
Community Dwelling ◽  
Health And Retirement Study ◽  
Class Analysis ◽  
People With Dementia ◽  
The Hours ◽  
Retirement Study ◽  
Post Onset

Abstract People living with Alzheimer’s disease and related dementias (ADRD) receive most of their care from family/friends, but little is known about the organization of this care. We used data from the Health and Retirement Study and latent class analysis to determine variation in the hours of care received by community-dwelling people with ADRD from disease onset up to 6-years post onset. At incidence (n=1,158), the latent class analysis identified two groups of caregiving patterns. In the first group, 10% (n=109) of people with ADRD received 481 hours (SD=177) of care. Most care was provided by a spouse (411 hours) with less from children (28 hours), other family/friends (17 hours), and paid individuals (25 hours). In the second latent class, the remaining 90% (n=1,049) of people with ADRD received 114 hours (SD=202) of care which was distributed between spouses (12 hours), children (51 hours), other relatives/friends (22 hours), and paid individuals (29 hours). By 6-years post incidence, 7% (n=76) of the original ADRD cohort remained in the community, and we identified two latent classes independent of those identified at incidence. Almost 15% (n=11) of people with ADRD received a majority of care from a spouse (376 hours) with care supplemented by children (10 hours) and paid individuals (54 hours). The remaining 85% (n=65) of people with ADRD received 294 (SD=314) hours of care from spouses (13 hours), children (104 hours), other family/friends (83 hours), and paid individuals (67 hours). Policies/interventions supporting caregivers must account for the heterogeneity in the organization caregivers.

Delirium superimposed on dementia: defining disease states and course from longitudinal measurements of a multivariate index using latent class analysis and hidden Markov chains

2011 ◽  
Vol 23 (10) ◽  
pp. 1659-1670 ◽  
Author(s):  
Antonio Ciampi ◽  
Alina Dyachenko ◽  
Martin Cole ◽  
Jane McCusker
Keyword(s):  
Mental Disorders ◽  
Markov Chains ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Hidden Markov ◽  
The Elderly ◽  
Population Heterogeneity ◽  
Class Analysis ◽  
Hidden Markov Chains ◽  
Time Point

ABSTRACTBackground: The study of mental disorders in the elderly presents substantial challenges due to population heterogeneity, coexistence of different mental disorders, and diagnostic uncertainty. While reliable tools have been developed to collect relevant data, new approaches to study design and analysis are needed. We focus on a new analytic approach.Methods: Our framework is based on latent class analysis and hidden Markov chains. From repeated measurements of a multivariate disease index, we extract the notion of underlying state of a patient at a time point. The course of the disorder is then a sequence of transitions among states. States and transitions are not observable; however, the probability of being in a state at a time point, and the transition probabilities from one state to another over time can be estimated.Results: Data from 444 patients with and without diagnosis of delirium and dementia were available from a previous study. The Delirium Index was measured at diagnosis, and at 2 and 6 months from diagnosis. Four latent classes were identified: fairly healthy, moderately ill, clearly sick, and very sick. Dementia and delirium could not be separated on the basis of these data alone. Indeed, as the probability of delirium increased, so did the probability of decline of mental functions. Eight most probable courses were identified, including good and poor stable courses, and courses exhibiting various patterns of improvement.Conclusion: Latent class analysis and hidden Markov chains offer a promising tool for studying mental disorders in the elderly. Its use may show its full potential as new data become available.

scholarly journals Towards the elimination of paediatric tuberculosis in high-income, immigrant-receiving countries: a 25-year conventional and molecular epidemiological case study

2018 ◽  
Vol 4 (2) ◽  
pp. 00131-2017 ◽  
Author(s):  
Vivek Dhawan ◽  
Jennifer Bown ◽  
Angela Lau ◽  
Deanne Langlois-Klassen ◽  
Dennis Kunimoto ◽  
...  
Keyword(s):  
Epidemiologic Study ◽  
High Income ◽  
Contact Tracing ◽  
Molecular Profile ◽  
High Morbidity ◽  
Foreign Born ◽  
Targeted Screening ◽  
Source Case ◽  
Latent Tb Infection ◽  
Culture Positive

The epidemiology of tuberculosis (TB) in high-income countries is increasingly dictated by immigration. The influence of this trend on paediatric TB and TB elimination are not well defined.We undertook a 25-year conventional and molecular epidemiologic study of paediatric TB in Alberta, one of four major immigrant-receiving provinces in Canada. All isolates ofMycobacterium tuberculosiswere DNA fingerprinted using standard methodology.Between 1990 and 2014, 176 children aged 0–14 years were diagnosed with TB. Foreign-born children or Canadian-born children of foreign-born parents accounted for an increasingly large proportion of total cases during the study period (from 32.1% to 89.5%). Of the 78 culture-positive cases, 35 (44.9%) had a putative source case identified by conventional epidemiology, with 34 (97.1%) having a concordant molecular profile. Of the remaining 43 culture-positive cases, molecular profiling identified spatially and temporally related sources in six cases (14.0%). These six children, along with four other children whose source cases were discovered through reverse-contact tracing, had a high morbidity and mortality.The increasing burden of paediatric TB in both foreign-born children and Canadian-born children of foreign-born parents calls for more timely diagnosis of source cases and more targeted screening for latent TB infection.

scholarly journals Monoclonal Antibodies in Multiple Sclerosis: Present and Future

Biomedicines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 20 ◽  
Author(s):  
Natalia Voge ◽  
Enrique Alvarez
Keyword(s):  
Multiple Sclerosis ◽  
Monoclonal Antibodies ◽  
Morbidity Rate ◽  
High Morbidity ◽  
Disease Modifying Therapies ◽  
High Morbidity Rate ◽  
New Treatments ◽  
Near Future ◽  
Risk Ratios

The global incidence of multiple sclerosis (MS) appears to be increasing. Although it may not be associated with a high mortality rate, this disease has a high morbidity rate which affects the quality of life of patients and reduces their ability to do their activities of daily living. Thankfully, the development of novel disease modifying therapies continues to increase. Monoclonal antibodies (MABs) have become a mainstay of MS treatment and they are likely to continue to be developed for the treatment of this disease. Specifically, MABs have proven to be some of the most efficacious treatments at reducing relapses and the inflammation in MS patients, including the first treatment for primary progressive MS and are being explored as reparative/remyelinating agents as well. These relatively new treatments will be reviewed here to help evaluate their efficacy, adverse events, immunogenicity, and benefit-risk ratios in the treatment of the diverse spectrum of MS. The focus will be on MABs that are currently approved or may be approved in the near future.

scholarly journals A MULTIDIMENSIONAL MODEL FOR POLYPHARMACY MEASUREMENT IN OLDER ADULTS: EVIDENCE FROM THE HEALTH RETIREMENT STUDY

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S707-S707
Author(s):  
Rebecca Bendayan ◽  
Ewan Carr ◽  
Alex D Federman ◽  
Richard J Dobson
Keyword(s):  
Older Adults ◽  
Latent Class ◽  
Optimal Number ◽  
Model Fit ◽  
Latent Classes ◽  
Chi Square ◽  
Chronic Health ◽  
Adverse Health Outcomes ◽  
Traditional Research ◽  
Retirement Study

Abstract Polypharmacy is associated with increased health care costs and adverse health outcomes. Traditional research on polypharmacy uses dichotomous measures which overlook its multidimensional nature. We propose a new approach to grouping older adults based on the number and type of medications taken as well as other indicators of polypharmacy. Data was extracted from 1328 respondents of the 2007 Prescription Drug Survey (a sub-study of the Health Retirement Study) who were between 50 and 70 years old and taking ≥1 medication each month. Latent class analysis was carried out with the optimal number of classes assessed based on relative model fit (AIC, adjusted BIC) and interpretability. Latent classes were formed based on the number of medications, drug types, duration of medication intake, side effects, and presence of chronic health conditions. A four-class model was selected based on model fit and interpretability of the solutions. Although there was some overlap when we compared our model with standard cut-offs for polypharmacy (i.e., ‘high polypharmacy’ classes were more likely to take 5+ and 9+ medications), chi-square tests showed significant differences between our latent classes and cut-offs based on 5+ [X2 = 894; p&lt;0.001] and 9+ medications [X2 = 398; p&lt;0.001]. Among individuals taking &lt;5 medications, our model differentiated two distinct types of ‘low polypharmacy’ based on the types of drugs reported. Our proposal to incorporate a multidimensional assessment of polypharmacy considers the wider context of medication use and chronic health in older age, moving beyond crude medication counts.

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