Geographic disparities in mortality from Alzheimer's disease and related dementias

Evaluating disparity of subjective cognitive decline between male veterans and non-veterans in the United States using propensity score matching estimation: A behavioral risk factor surveillance system survey cross-sectional study

Subjective cognitive decline (SCD) is one of the most important early onset symptoms of Alzheimer's Disease. Previous studies consistently reported that SCD is associated with quality of life, socio-economic factors, and related health comorbidities. However, the impact of veteran status on SCD has been little investigated. This study conducted a cross-sectional study to address disproportionate effects in subjective cognitive decline between veterans and non-veterans in the United States. Propensity score matching (PSM) was applied in this observational study to achieve covariate balancing and reduce selection bias, providing a more accurate estimate of the isolated effect of veteran status on SCD. Our study utilized 32,431 forty-five years or older non-institutionalized White, Black or African-American, and Hispanic or Latin-American male population from the 2019 Behavioral Risk Factor Surveillance System data. We first identified 10,685 paired PSM samples for the binary veteran status using the preselected covariates. Next, we performed a logistic regression for modeling the relationship between the veteran status and the SCD status using the PSM samples along with the covariates selected by a BIC-based stepwise selection. Our analyses revealed a statistically significant causal association between veteran status and SCD after PSM (odds ratio (OR): 1.16 and 95% confidence interval (CI): 1.06-1.27). We obtained a similar result before PSM with an OR of 1.20 and 95% CI of 1.10-1.31. When we focused on a minority group (Black or African-American males), we found a significantly increased veterans' risk of SCD, especially after propensity score matching (OR: 1.69, 95% CI: 1.16-2.45). We also found several factors such as employment status, difficulty dressing/walking/running errands, general health status, physical health status, unaffordability of medical costs, mental health status, and comorbid conditions including stroke, blindness, high cholesterol, and arthritis as statistically significantly associated with SCD (P-value < 0.05). Similar to post-traumatic stress disorder and traumatic brain injury, our study demonstrated a causal association between SCD and military-related activities in the United States, which has a disproportionate impact on the minority population. This study sets the groundwork to further research in this domain to diagnose neurological diseases early among veterans.

Alzheimer`s disease mortality in the United States: Cross-sectional analysis of county-level socio-environmental factors

BACKGROUND

Geographical disparities in mortality among Alzheimer`s disease (AD) patients have been reported and complex sociodemographic and environmental determinants of health (SEDH) may be contributing to this variation. Therefore, we aimed to explore high-risk SEDH factors possibly associated with all-cause mortality in AD across US counties using machine learning (ML) methods.

METHODS

We performed a cross-sectional analysis of individuals ≥65 years with any underlying cause of death but with AD in the multiple causes of death certificate (ICD-10,G30) between 2016 and 2020. Outcomes were defined as age-adjusted all-cause mortality rates (per 100,000 people). We analyzed 50 county-level SEDH and Classification and Regression Trees (CART) was used to identify specific county-level clusters. Random Forest, another ML technique, evaluated variable importance. CART`s performance was validated using a "hold-out" set of counties.

RESULTS

Overall, 714,568 individuals with AD died due to any cause across 2,409 counties during 2016-2020. CART identified 9 county clusters associated with an 80.1% relative increase of mortality across the spectrum. Furthermore, 7 SEDH variables were identified by CART to drive the categorization of clusters, including High School Completion (%), annual Particulate Matter 2.5 Level in Air, live births with Low Birthweight (%), Population under 18 years (%), annual Median Household Income in US dollars ($), population with Food Insecurity (%), and houses with Severe Housing Cost Burden (%).

CONCLUSION

ML can aid in the assimilation of intricate SEDH exposures associated with mortality among older population with AD, providing opportunities for optimized interventions and resource allocation to reduce mortality among this population.

Decomposition of disparities in life expectancy with applications to administrative health claims and registry data

Research shows that geographic disparities in life expectancy between leading and lagging states are increasing over time while racial disparities between Black and White Americans have been going down. In the 65+ age strata morbidity is the most common cause of death, making differences in morbidity and associated adverse health-related outcomes between advantaged and disadvantaged groups an important aspect of disparities in life expectancy at age 65 (LE65). In this study, we used Pollard's decomposition to evaluate the disease-related contributions to disparities in LE65 for two types of data with distinctly differing structures: population/registry and administrative claims. To do so, we analyzed Pollard's integral, which is exact by construction, and developed exact analytic solutions for both types of data without the need for numerical integration. The solutions are broadly applicable and easily implemented. Applying these solutions, we found that the largest relative contributions to geographic disparities in LE65 were chronic lower respiratory diseases, circulatory diseases, and lung cancer; and, to racial disparities: arterial hypertension, diabetes mellitus, and cerebrovascular diseases. Overall, the increase in LE65 observed over 1998-2005 and 2010-2017 was primarily due to a reduction in the contributions of acute and chronic ischemic diseases; this was partially offset by increased contributions of diseases of the nervous system including dementia and Alzheimer's disease.

Geographic Patterns of Dementia in the United States: Variation by Place of Residence, Place of Birth, and Subpopulation

OBJECTIVES

The prevalence of dementia varies geographically in the United States. However, the extent to which this variation reflects contemporary place-based experiences versus embodied exposures from earlier in the life course remains unclear, and little is known regarding the intersection of place and subpopulation. This study, therefore, evaluates whether and how risk for assessed dementia varies by place of residence and birth, overall and by race/ethnicity and education.

METHODS

We pool data from the 2000 to 2016 waves of the Health and Retirement Study, a nationally representative panel survey of older U.S. adults (n = 96,848 observations). We estimate the standardized prevalence of dementia by Census division of residence and birth. We then fit logistic regression models of dementia on region of residence and birth, adjusting for sociodemographic characteristics, and examine interactions between region and subpopulation.

RESULTS

The standardized prevalence of dementia ranges from 7.1% to 13.6% by division of residence and from 6.6% to 14.7% by division of birth, with rates highest throughout the South and lowest in the Northeast and Midwest. In models accounting for region of residence, region of birth, and sociodemographic covariates, Southern birth remains significantly associated with dementia. Adverse relationships between Southern residence or birth and dementia are generally largest for Black and less-educated older adults. As a result, sociodemographic disparities in predicted probabilities of dementia are largest for those residing or born in the South.

DISCUSSION

The sociospatial patterning of dementia suggests its development is a lifelong process involving cumulated and heterogeneous lived experiences embedded in place.

Expanding the scope of health disparities research in Alzheimer's disease and related dementias: Recommendations from the "Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias" Workshop Series

Topics discussed at the "Leveraging Existing Data and Analytic Methods for Health Disparities Research Related to Aging and Alzheimer's Disease and Related Dementias" workshop, held by Duke University and the Alzheimer's Association with support from the National Institute on Aging, are summarized.  Ways in which existing data resources paired with innovative applications of both novel and well-known methodologies can be used to identify the effects of multi-level societal, community, and individual determinants of race/ethnicity, sex, and geography-related health disparities in Alzheimer's disease and related dementia are proposed.  Current literature on the population analyses of these health disparities is summarized with a focus on identifying existing gaps in knowledge, and ways to mitigate these gaps using data/method combinations are discussed at the workshop.  Substantive and methodological directions of future research capable of advancing health disparities research related to aging are formulated.

Spatial disparity and factors associated with dementia mortality: A cross-sectional study in Zhejiang Province, China

Objective

Evidence of spatial disparity in dementia mortality in China has been found to have higher dementia mortality in eastern and rural China. Regional factors of physical and social features may be influencing this spatial disparity. However, the extent of spatial difference in dementia mortality across small regional localities is unclear. This study aims to investigate the geographic variations in mortality and risk of all dementia subtypes and identify the effect of the associated environmental risk factors.

Methods

We used surveillance data on death reports from Alzheimer's disease and other forms of dementia in Zhejiang province from 2015 to 2019. We estimated the relative risk of dementia mortality using a Bayesian spatial model. We mapped predicted relative risk to visualize the risk of death from different types of dementia and to identify risk factors associated with dementia.

Results

Thirty thousand three hundred and ninety-eight deaths attributable to dementia as the underlying or related cause (multiple causes) were reported during 2015-2019. Counties and districts in the southeast and west of Zhejiang province had significantly higher standardized mortality ratios than others. Counties and districts with a smaller proportion of residents aged 60 years or older, poorer economic status, insufficient health resources, and worse pollution had a higher risk of deaths due to dementia.

Conclusion

Higher risks of dementia mortality were found in counties and districts with poorer economic status, insufficient health resources, and worse pollution in Zhejiang. Our study adds new evidence on the association between socioeconomic and environmental factors and the mortality risk due to dementia.

The role of geographic information system and global positioning system in dementia care and research: a scoping review

Background

Geographic Information System (GIS) and Global Positioning System (GPS), vital tools for supporting public health research, provide a framework to collect, analyze and visualize the interaction between different levels of the health care system. The extent to which GIS and GPS applications have been used in dementia care and research is not yet investigated. This scoping review aims to elaborate on the role and types of GIS and GPS applications in dementia care and research.

Methods

A scoping review was conducted based on Arksey and O’Malley’s framework. All published articles in peer-reviewed journals were searched in PubMed, Scopus, and Web of Science, subject to involving at least one GIS/GPS approach focused on dementia. Eligible studies were reviewed, grouped, and synthesized to identify GIS and GPS applications. The PRISMA standard was used to report the study.

Results

Ninety-two studies met our inclusion criteria, and their data were extracted. Six types of GIS/GPS applications had been reported in dementia literature including mapping and surveillance (n = 59), data preparation (n = 26), dementia care provision (n = 18), basic research (n = 18), contextual and risk factor analysis (n = 4), and planning (n = 1). Thematic mapping and GPS were most frequently used techniques in the dementia field.

Conclusions

Even though the applications of GIS/GPS methodologies in dementia care and research are growing, there is limited research on GIS/GPS utilization in dementia care, risk factor analysis, and dementia policy planning. GIS and GPS are space-based systems, so they have a strong capacity for developing innovative research based on spatial analysis in the area of dementia. The existing research has been summarized in this review which could help researchers to know the GIS/GPS capabilities in dementia research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12942-022-00308-1.

The rising burden of Alzheimer's disease mortality in rural America

Since the 1990s, there has been a striking urban-rural divergence in life expectancy within the United States, with metropolitan areas achieving strong life expectancy increases and nonmetropolitan areas experiencing stagnation or actual declines in life expectancy. While Alzheimer's disease and related dementias (ADRD) are likely to pose a particular challenge in nonmetropolitan areas, we know relatively little about the level of ADRD mortality in nonmetropolitan areas, how it has changed over time, and whether it is contributing to metropolitan/nonmetropolitan life expectancy gaps. This study finds that ADRD mortality has risen more rapidly in nonmetropolitan areas than in all other metro areas (large central metros, suburbs, and medium/small cities) between 1999 and 2019. While death rates from ADRD were nearly identical in large central metros and nonmetros in 1999, a clear metro/nonmetro gradient has emerged and widened substantially over the past two decades. Today, nonmetros now experience the highest levels of ADRD mortality, while large central metros have the lowest levels. These metro/nonmetro gaps in ADRD differ substantially by region, with the largest gaps observed in the Middle Atlantic and South Atlantic. The contribution of ADRD to metro/nonmetro differences life expectancy at age 65 is now considerable in many regions, reaching up to 30% for women and 13% for men. In several regions, ADRD's contribution to female life expectancy gaps is on par with or exceeds the contributions of other leading causes of death such as heart disease, cancer, and chronic lower respiratory diseases. The rising burden of Alzheimer's disease mortality is likely to pose a substantial challenge in rural areas of the United States which are aging rapidly, experiencing adverse mortality trends, and increasingly disadvantaged in terms of socioeconomic resources and health care infrastructure.