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Title: Global rural health disparities in Alzheimer's disease and related dementias: State of the science
AbstractINTRODUCTION
Individuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place‐based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators.
METHODS
An interdisciplinary, international group of ADRD researchers convened to address the overarching question of: “What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?” In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings.
RESULTS
A range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions.
DISCUSSION
A location dynamics model and ADRD‐focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities.
HIGHLIGHTS
Rural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities.
Defining the unique rural barriers and facilitators to cognitive health yields insight.
The strengths and resilience of rural residents can mitigate ADRD‐related challenges.
A novel “location dynamics” model guides assessment of rural‐specific ADRD issues.
Alzheimer's disease (AD) and AD‐related dementias (ADRD) are leading causes of death among older adults in the United States. Efforts to understand risk factors for prevention are needed.
METHODS
Participants (n = 146,166) enrolled in the Women's Health Initiative without AD at baseline were included. Diabetes status was ascertained from self‐reported questionnaires and deaths attributed to AD/ADRD from hospital, autopsy, and death records. Competing risk regression models were used to estimate the cause‐specific hazard ratios (HRs) and 95% confidence intervals (CIs) for the prospective association of type 2 diabetes mellitus (T2DM) with AD/ADRD and non‐AD/ADRD mortality.
RESULTS
There were 29,393 treated T2DM cases and 8628 AD/ADRD deaths during 21.6 (14.0–23.5) median (IQR) years of follow‐up. Fully adjusted HRs (95% CIs) of the association with T2DM were 2.94 (2.76–3.12) for AD/ADRD and 2.65 (2.60–2.71) for the competing risk of non‐AD/ADRD mortality.
DISCUSSION
T2DM is associated with AD/ADRD and non‐AD/ADRD mortality.
Highlights
Type 2 diabetes mellitus is more strongly associated with Alzheimer's disease (AD)/AD and related dementias (ADRD) mortality compared to the competing risk of non‐AD/ADRD mortality among postmenopausal women.
This relationship was consistent for AD and ADRD, respectively.
This association is strongest among participants without obesity or hypertension and with younger age at baseline, higher diet quality, higher physical activity, higher alcohol consumption, and older age at the time of diagnosis of type 2 diabetes mellitus.
Derby, Carol A.; Hutchins, Franya; Greendale, Gail A.; Matthews, Karen A.; Sternfeld, Barbara; Everson‐Rose, Susan A.; Kazlauskaite, Rasa; Whitmer, Rachel A.; Brooks, Maria M.(
, Alzheimer's & Dementia)
AbstractIntroduction
Cardiovascular risk factors in midlife have been linked to late life risk for Alzheimer's disease and related dementias (ADRD). The relation of vascular risk factors on cognitive decline within midlife has been less studied.
Methods
Using data from the Study of Women's Health Across the Nation, we examined associations of midlife hypertension, elevated lipid levels, diabetes, fasting glucose, central adiposity, and Framingham heart age with rates of cognitive decline in women who completed multiple cognitive assessments of processing speed, and working and verbal memory during midlife.
Results
Diabetes, elevated fasting glucose, central obesity, and heart age greater than chronological age were associated with rate of decline in processing speed during midlife. Vascular risk factors were not related to rate of decline in working or verbal memory.
Discussion
Midlife may be a critical period for intervening on cardiovascular risk factors to prevent or delay later life cognitive impairment and ADRD.
Trott, Daniel W.; Fadel, Paul J.(
, Experimental Physiology)
New Findings
What is the topic of this review?
This review summarizes and synthesizes what is known about the contribution of inflammation to age‐related arterial dysfunction.
What advances does it highlight?
This review details observational evidence for the relationship of age‐related inflammation and arterial dysfunction, insight from autoimmune inflammatory diseases and their effects on arterial function, interventional evidence linking inflammation and age‐related arterial dysfunction, insight into age‐related arterial inflammation from preclinical models and interventions to ameliorate age‐related inflammation and arterial dysfunction.
Abstract
Advanced age is a primary risk factor for cardiovascular disease, the leading cause of death in the industrialized world. Two major components of arterial ageing are stiffening of the large arteries and impaired endothelium‐dependent dilatation in multiple vascular beds. These two alterations are major contributors to the development of overt cardiovascular disease. Increasing inflammation with advanced age is likely to play a role in this arterial dysfunction. The purpose of this review is to synthesize what is known about inflammation and its relationship to age‐related arterial dysfunction. This review discusses both the initial observational evidence for the relationship of age‐related inflammation and arterial dysfunction and the evidence that inflammatory autoimmune diseases are associated with a premature arterial ageing phenotype. We next discuss interventional and mechanistic evidence linking inflammation and age‐related arterial dysfunction in older adults. We also attempt to summarize the relevant evidence from preclinical models. Lastly, we discuss interventions in both humans and animals that have been shown to ameliorate age‐related arterial inflammation and dysfunction. The available evidence provides a strong basis for the role of inflammation in both large artery stiffening and impairment of endothelium‐dependent dilatation; however, the specific inflammatory mediators, the initiating factors and the relative importance of the endothelium, smooth muscle cells, perivascular adipose tissue and immune cells in arterial inflammation are not well understood. With the expansion of the ageing population, ameliorating age‐related arterial inflammation represents an important potential strategy for preserving vascular health in the elderly.
Identifying mild cognitive impairment (MCI) patients at risk for dementia could facilitate early interventions. Using electronic health records (EHRs), we developed a model to predict MCI to all‐cause dementia (ACD) conversion at 5 years.
METHODS
Cox proportional hazards model was used to identify predictors of ACD conversion from EHR data in veterans with MCI. Model performance (area under the receiver operating characteristic curve [AUC] and Brier score) was evaluated on a held‐out data subset.
RESULTS
Of 59,782 MCI patients, 15,420 (25.8%) converted to ACD. The model had good discriminative performance (AUC 0.73 [95% confidence interval (CI) 0.72–0.74]), and calibration (Brier score 0.18 [95% CI 0.17–0.18]). Age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors, while body mass index, alcohol abuse, and sleep apnea were protective factors.
DISCUSSION
EHR‐based prediction model had good performance in identifying 5‐year MCI to ACD conversion and has potential to assist triaging of at‐risk patients.
Highlights
Of 59,782 veterans with mild cognitive impairment (MCI), 15,420 (25.8%) converted to all‐cause dementia within 5 years.
Electronic health record prediction models demonstrated good performance (area under the receiver operating characteristic curve 0.73; Brier 0.18).
Age and vascular‐related morbidities were predictors of dementia conversion.
Synthetic data was comparable to real data in modeling MCI to dementia conversion.
Key Points
An electronic health record–based model using demographic and co‐morbidity data had good performance in identifying veterans who convert from mild cognitive impairment (MCI) to all‐cause dementia (ACD) within 5 years.
Increased age, stroke, cerebrovascular disease, myocardial infarction, hypertension, and diabetes were risk factors for 5‐year conversion from MCI to ACD.
High body mass index, alcohol abuse, and sleep apnea were protective factors for 5‐year conversion from MCI to ACD.
Models using synthetic data, analogs of real patient data that retain the distribution, density, and covariance between variables of real patient data but are not attributable to any specific patient, performed just as well as models using real patient data. This could have significant implications in facilitating widely distributed computing of health‐care data with minimized patient privacy concern that could accelerate scientific discoveries.
Thunell, Johanna; Chen, Yi; Joyce, Geoffrey; Barthold, Douglas; Shekelle, Paul G.; Brinton, Roberta Diaz; Zissimopoulos, Julie(
, Alzheimer's & Dementia)
AbstractIntroduction
Most older Americans use drug therapies for chronic conditions. Several are associated with risk of Alzheimer's disease and related dementias (ADRD).
Methods
A scoping review was used to identify drug classes associated with increasing or decreasing ADRD risk. We analyzed size, type, and findings of the evidence.
Results
We identified 29 drug classes across 11 therapeutic areas, and 404 human studies. Most common were studies on drugs for hypertension (93) or hyperlipidemia (81). Fewer than five studies were identified for several anti‐diabetic and anti‐inflammatory drugs. Evidence was observational only for beta blockers, proton pump inhibitors, benzodiazepines, and disease‐modifying anti‐rheumatic drugs. For 13 drug classes, 50% or more of the studies reported consistent direction of effect on risk of ADRD.
Discussion
Future research targeting drug classes with limited/non‐robust evidence, examining sex, racial heterogeneity, and separating classes by molecule, will facilitate understanding of associated risk, and inform clinical and policy efforts to alleviate the growing impact of ADRD.
@article{osti_10419065,
place = {Country unknown/Code not available},
title = {Global rural health disparities in Alzheimer's disease and related dementias: State of the science},
url = {https://par.nsf.gov/biblio/10419065},
DOI = {10.1002/alz.13104},
abstractNote = {Abstract INTRODUCTIONIndividuals living in rural communities are at heightened risk for Alzheimer's disease and related dementias (ADRD), which parallels other persistent place‐based health disparities. Identifying multiple potentially modifiable risk factors specific to rural areas that contribute to ADRD is an essential first step in understanding the complex interplay between various barriers and facilitators. METHODSAn interdisciplinary, international group of ADRD researchers convened to address the overarching question of: “What can be done to begin minimizing the rural health disparities that contribute uniquely to ADRD?” In this state of the science appraisal, we explore what is known about the biological, behavioral, sociocultural, and environmental influences on ADRD disparities in rural settings. RESULTSA range of individual, interpersonal, and community factors were identified, including strengths of rural residents in facilitating healthy aging lifestyle interventions. DISCUSSIONA location dynamics model and ADRD‐focused future directions are offered for guiding rural practitioners, researchers, and policymakers in mitigating rural disparities. HIGHLIGHTSRural residents face heightened Alzheimer's disease and related dementia (ADRD) risks and burdens due to health disparities.Defining the unique rural barriers and facilitators to cognitive health yields insight.The strengths and resilience of rural residents can mitigate ADRD‐related challenges.A novel “location dynamics” model guides assessment of rural‐specific ADRD issues.},
journal = {Alzheimer's & Dementia},
volume = {19},
number = {9},
publisher = {Wiley Blackwell (John Wiley & Sons)},
author = {Wiese, Lisa Ann Kirk and Gibson, Allison and Guest, Marc Aaron and Nelson, Amy R. and Weaver, Raven and Gupta, Aditi and Carmichael, Owen and Lewis, Jordan P. and Lindauer, Allison and Loi, Samantha and Peterson, Rachel and Radford, Kylie and Rhodus, Elizabeth K. and Wong, Christina G. and Zuelsdorff, Megan and Saidi, Ladan Ghazi and Valdivieso‐Mora, Esmeralda and Franzen, Sanne and Pope, Caitlin N. and Killian, Timothy S. and Shrestha, Hom L. and Heyn, Patricia C. and Ng, Ted Kheng Siang and Prusaczyk, Beth and John, Samantha and Kulshreshtha, Ambar and Sheffler, Julia L. and Besser, Lilah and Daniel, Valerie and Tolea, Magdalena I. and Miller, Justin and Musyimi, Christine and Corkey, Jon and Yank, Veronica and Williams, Christine L. and Rahemi, Zahra and Park, JuYoung and Magzamen, Sheryl and Newton, Jr., Robert L. and Harrington, Candace and Flatt, Jason D. and Arora, Sonakshi and Walter, Sarah and Griffin, Percy and Babulal, Ganesh M.},
}
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