Dataset Information

Predictors of Olfactory Decline in Aging: A Longitudinal Population-Based Study.

ABSTRACT: BACKGROUND:Olfactory dysfunction is common in aging and associated with dementia and mortality. However, longitudinal studies tracking change in olfactory ability are scarce. We sought to identify predictors of interindividual differences in rate of olfactory identification change in aging. METHOD:Participants were 1780 individuals, without dementia at baseline and with at least 2 olfactory assessments over 12 years of follow-up (mean age = 70.5 years; 61.9% female), from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Odor identification was assessed with the Sniffin' Sticks. We estimated the impact of demographic, health, and genetic factors on rate of olfactory change with linear mixed effect models. RESULTS:Advancing age, manufacturing profession, history of cerebrovascular disease, higher cardiovascular disease burden, diabetes, slower walking speed, higher number of medications, and the APOE ?4 allele were associated with accelerated odor identification decline (ps < .014). Multi-adjusted analyses showed unique associations of age, diabetes, and ?4 to olfactory decline (ps < .017). In 1531 participants who remained free of dementia (DSM IV criteria) during follow-up, age, cardiovascular disease burden, and diabetes were associated with accelerated decline (ps < .011). Of these, age and diabetes remained statistically significant in the multi-adjusted model (ps < .001). CONCLUSION:Demographic, vascular, and genetic factors are linked to rate of decline in odor identification in aging. Although some olfactory loss may be an inevitable part of aging, our results highlight the importance of vascular factors for the integrity of the olfactory system, even in the absence of dementia.

SUBMITTER: Ekstrom I

PROVIDER: S-EPMC7662159 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Predictors of Olfactory Decline in Aging: A Longitudinal Population-Based Study.

Ekström Ingrid I Larsson Maria M Rizzuto Debora D Fastbom Johan J Bäckman Lars L Laukka Erika J EJ

The journals of gerontology. Series A, Biological sciences and medical sciences 20201101 12

<h4>Background</h4>Olfactory dysfunction is common in aging and associated with dementia and mortality. However, longitudinal studies tracking change in olfactory ability are scarce. We sought to identify predictors of interindividual differences in rate of olfactory identification change in aging.<h4>Method</h4>Participants were 1780 individuals, without dementia at baseline and with at least 2 olfactory assessments over 12 years of follow-up (mean age = 70.5 years; 61.9% female), from the Swed ...[more]

PMID: 32886741

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Project description:Background/objectivesTo investigate potential mechanisms underlying the well-established relationship of diabetes and obesity with cognitive decline, among older adults participating in a population-based study.Design/settingTen-year population-based cohort study.ParticipantsA total of 478 individuals aged 65 years and older.MeasurementsWe assayed fasting blood for markers of glycemia (glucose and hemoglobin A1c [HbA1c]), insulin resistance (IR) (insulin and homeostatic model assessment of IR), obesity (resistin, adiponectin, and glucagon-like peptide-1), and inflammation (C-reactive protein). We modeled these indices as predictors of the slope of decline in global cognition, adjusting for age, sex, education, APOE*4 genotype, depressive symptoms, waist-hip ratio (WHR), and systolic blood pressure, in multivariable regression analyses of the entire sample and stratified by sex-specific median WHR. We then conducted WHR-stratified machine-learning (Classification and Regression Tree [CART]) analyses of the same variables.ResultsIn multivariable regression analyses, in the entire sample, HbA1c was significantly associated with cognitive decline. After stratifying by median WHR, HbA1c remained associated with cognitive decline in those with higher WHR. No metabolic indices were associated with cognitive decline in those with lower WHR. Cross-validated WHR-stratified CART analyses selected no predictors in participants older than 87 to 88 years. Faster cognitive decline was associated, in lower WHR participants younger than 87 years, with adiponectin of 11 or greater; and in higher WHR participants younger than 88 years, with HbA1c of 6.2% or greater.ConclusionsOur population-based data suggest that, in individuals younger than 88 years with central obesity, even modest degrees of hyperglycemia might independently predispose to faster cognitive decline. In contrast, among those younger than 87 years without central obesity, adiponectin may be a novel independent risk factor for cognitive decline. J Am Geriatr Soc 68:991-998, 2020.

Project description:Describing the trajectories of age-related change for different brain structures has been of interest in many recent studies. However, our knowledge regarding these trajectories and their associations is still limited due to small sample sizes and low numbers of repeated measures. For the present study, we used a large longitudinal dataset (four measurements over 4 years) comprising anatomical data from a sample of healthy older adults (N = 231 at baseline). This dataset enables us to gain new insights about volumetric cortical and subcortical changes and their associations in the context of healthy aging. Brain structure volumes were derived from T1-weighted MRI scans using FreeSurfer segmentation tools. Brain structure trajectories were fitted using mixed models and latent growth curve models to gain information about the mean extent and variability of decline trajectories for different brain structures as well as the associations between individual trajectories. On the group level, our analyses indicate similar linear changes for frontal and parietal brain regions, while medial temporal regions showed an accelerated decline with advancing age. Regarding subcortical regions, some structures showed strong declines (e.g., hippocampus), others showed little decline (e.g., pallidum). Our data provide little evidence for sex differences regarding the aforementioned trajectories. Between-person variability of the person-specific slopes (random slopes) was largest in subcortical and medial temporal brain structures. When looking at the associations between the random slopes from each brain structure, we found that the decline is largely homogenous across the majority of cortical brain structures. In subcortical and medial temporal brain structures, however, more heterogeneity of the decline was observed, meaning that the extent of the decline in one structure is less predictive of the decline in another structure. Taken together, our study contributes to enhancing our understanding of structural brain aging by demonstrating (1) that average volumetric change differs across the brain and (2) that there are regional differences with respect to between-person variability in the slopes. Moreover, our data suggest (3) that random slopes are highly correlated across large parts of the cerebral cortex but (4) that some brain regions (i.e., medial temporal regions) deviate from this homogeneity.

Project description:BackgroundSex differences in post-stroke cognitive decline have not been systematically evaluated in a nationally representative cohort. We use a quasi-experimental design to investigate sex differences in rate of post-stroke cognitive decline.MethodsUtilizing the event study design, we use the Health and Retirement Study (HRS) data (1996-2016) to evaluate the differences (percentage points [95% Confidence interval]) in the rate of change in cognitive function, measured using the modified version of the Telephone Interview for Cognitive Status (TICS-m) score, before and after incident stroke, and among patients with and without incident stroke. We estimated this event study model for the overall study population and separately fit the same model for male and female participants.ResultsOf 25,872 HRS participants included in our study, 14,459 (55.9%) were females with an overall mean age (SD) of 61.2 (9.3) years. Overall, 2,911 (11.3%) participants reported experiencing incident stroke. Participants with incident stroke (vs. no stroke) had lower baseline TICS-m score (15.6 vs. 16.1). Among participants with incident stroke, the mean pre-stroke TICS-m score was higher than the mean post-stroke TICS-m score (14.9 vs. 12.7). Event study revealed a significant short-term acceleration of cognitive decline for the overall population (4.2 [1.7-6.6] percentage points, p value = 0.001) and among female participants (5.0 [1.7-8.3] percentage points, p value = 0.003). We, however, found no evidence of long-term acceleration of cognitive decline after stroke. Moreover, among males, incident stroke was not associated with significant changes in rate of post-stroke cognitive decline.ConclusionFemales, in contrast to males, experience post-stroke cognitive deficits, particularly during early post-stroke period. Identifying the sex-specific stroke characteristics contributing to differences in post stroke cognitive decline may inform future strategies for reducing the burden of post-stroke cognitive impairment and dementia.

Dataset Information

Predictors of Olfactory Decline in Aging: A Longitudinal Population-Based Study.

Publications

Predictors of Olfactory Decline in Aging: A Longitudinal Population-Based Study.

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