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The Journals of Gerontology Series B: Psychological Sciences and Social Sciences logoLink to The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
. 2024 Feb 20;79(4):gbae009. doi: 10.1093/geronb/gbae009

Depression, Vascular Burden, and Dementia Prevalence in Late Middle-Aged and Older Black Adults

Shellie-Anne Levy 1,2,✉, Maria B Misiura 3, Jeremy G Grant 4, Tamare V Adrien 5, Zinat Taiwo 6,7, Rebecca Armstrong 8, Vonetta M Dotson 9,10
Editor: Vanessa Taler11
PMCID: PMC10926943  PMID: 38374692

Abstract

Objectives

Late-life depression and white matter hyperintensities (WMH) have been linked to increased dementia risk. However, there is a dearth of literature examining these relationships in Black adults. We investigated whether depression or WMH volume are associated with a higher likelihood of dementia diagnosis in a sample of late middle-aged to older Black adults, and whether dementia prevalence is highest in individuals with both depression and higher WMH volume.

Methods

Secondary data analysis involved 443 Black participants aged 55+ with brain imaging within 1 year of baseline visit in the National Alzheimer’s Coordinating Center Uniform Data Set. Chi-square analyses and logistic regression models controlling for demographic variables examined whether active depression in the past 2 years, WMH volume, or their combination were associated with higher odds of all-cause dementia.

Results

Depression and higher WMH volume were associated with a higher prevalence of dementia. These associations remained after controlling for demographic factors, as well as vascular disease burden. Dementia risk was highest in the depression/high WMH volume group compared to the depression-only group, high WMH volume-only group, and the no depression/low WMH volume group. Post hoc analyses comparing the Black sample to a demographically matched non-Hispanic White sample showed associations of depression and the combination of depression and higher WMH burden with dementia were greater in Black compared to non-Hispanic White individuals.

Discussion

Results suggest late-life depression and WMH have independent and joint relationships with dementia and that Black individuals may be particularly at risk due to these factors.

Keywords: African Americans, Cerebrovascular disease, Cognitive impairment, Depressive symptoms

Late-life depression (LLD) is a leading cause of disability, morbidity, and mortality among older adults (Haigh et al., 2018). There is a wealth of evidence indicating LLD increases dementia risk (Gallagher et al., 2018), and that recurrent depressive episodes are particularly detrimental to cognitive status (Dotson et al., 2010). White matter hyperintensities (WMH), a neuroimaging proxy for white matter disease or cerebral small vessel disease, are also associated with increased risk for cognitive impairment and dementia, including all-cause dementia, Alzheimer’s dementia, and vascular dementia (Hu et al., 2021) Despite this evidence, these associations have not been well-studied in Black older adults as this research has largely relied on predominantly non-Hispanic White (NHW) samples. This gap in the literature is particularly stark given that Black older adults are at higher risk for undiagnosed depression (Gallo et al., 2005), may have higher white matter lesion burden (Brickman et al., 2008; Zahodne et al., 2015), and are twice as likely to develop dementia than NHWs (“2021 Alzheimer’s disease facts and figures,” 2021).

There is a small but growing body of evidence suggesting increased vulnerability to depression-related cognitive decline in Black older adults (Zahodne et al., 2014), albeit with mixed findings (Wagner et al., 2022). This vulnerability may be influenced by systemic societal inequities (e.g., differential access to healthcare) or more internalized stigma in seeking treatment for depression relative to NHWs (Conner et al., 2010). Two relatively recent studies found (1) depressive symptoms were more strongly related to poorer memory and executive function in Black Americans relative to NHWs, independent of health status, income, and reading level (Zahodne et al., 2014), and (2) depressive symptoms (particularly depressed mood and anhedonia) were related to a faster rate of cognitive decline in Black older adults relative to NHWs (Turner et al., 2015). Notably, they did not investigate associations between depression and dementia risk or incidence, specifically.

The association between WMH and increased risk for cognitive impairment and dementia may occur through hypoperfusion, neuroinflammation, and protein accumulation (e.g., amyloid) among other pathophysiological processes (Graff-Radford et al., 2019; Hase et al., 2018), although these mechanistic pathways remain under investigation. In context of a dearth of research, there have been inconsistent findings regarding whether WMH confers increased risk for cognitive decline in Black older adults (Gavett et al., 2018; Meier et al., 2012). Meier and colleagues (2012) found increased WMH volume in the frontal lobes were associated with poor memory performance in Black older adults. In contrast, in a recent longitudinal study with a diverse sample of older adults, Gavett and colleagues (2018) found that baseline WMH volume was not a strong predictor of cognitive decline in Black Americans.

Both the severity and volume of WMH have been found to predict worsening of incident depression and depressive symptoms (Godin et al., 2008; Teodorczuk et al., 2010). Although there is an abundance of evidence supporting the association between WMH and LLD, the mechanisms behind this relationship remain unclear. WMH are a hallmark of vascular depression, a particularly treatment-resistant subtype of depression (Bogoian & Dotson, 2021) and individuals with vascular depression may be at greater risk for developing cognitive impairment, including vascular dementia (Diniz et al., 2013). The vascular depression hypothesis, which proposes that depressive symptoms are promoted by way of cerebrovascular ischemic damage (Butters et al., 2008), is considered to be one of the more dominant models for understanding the relationship between WMH and LLD. Notably, Black older adults are poorly represented in vascular depression research, but at least one study found that vascular depression is overrepresented among Black older adults (Reinlieb et al., 2014), ostensibly increasing their risk for cognitive decline. This increased burden of vascular depression may be due, in part, to the disproportionately high rates of cardiovascular disease seen in Black Americans that may reflect racial inequities including structural/institutional, perceived, or internalized racism (Carnethon et al., 2017).

There have been prior studies supporting the association between depression and dementia outcomes using the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS; Babulal et al., 2022; Gallagher et al., 2018; Kim et al., 2021). Gallagher and colleagues (2018) found adults with active depression and mild cognitive impairment (MCI) have a faster rate of progression to Alzheimer’s dementia than those with MCI and a history of remote depression. Similarly, Kim and colleagues (2021) found cognitively normal adults with active depression were twice as likely to progress to Alzheimer’s dementia than those without active depression. Babulal and colleagues (2022) found that depression predicted incident cognitive impairment and this did not differ by ethnoracial group. Regarding the association between WMH and depression, findings from studies using the NACC UDS were consistent with prior literature and revealed greater baseline volume of WMH was associated with increased depressive symptoms over time (Anor et al., 2021; Puzo et al., 2019). Regarding the association between WMH and cognitive impairment, one study using the NACC UDS found increased volume of WMH over time was associated with the development of MCI in men but not women (Burke et al., 2019). To our knowledge, there have been few to no studies examining the associations between depression, WMH, and dementia together within the NACC cohort or elsewhere and none examining these relationships in a predominantly Black cohort.

Both LLD and WMH are modifiable targets for intervention that can greatly influence cognitive trajectories in Black older adults, an especially vulnerable minoritized population. As such, the present study seeks to better understand the association between depression, WMH volume, and dementia, specifically in a homogeneous sample of Black adults aged 55 and older. Leveraging the NACC UDS, we hypothesized depressive symptoms and WMH volume would be independent predictors of dementia prevalence, and that odds of dementia diagnosis would be highest in individuals with higher depressive symptoms alongside a higher burden of WMH. We also performed post hoc analyses comparing the Black sample to a demographically matched NHW sample to determine whether associations of depression and the combination of depression and higher WMH burden with dementia differed by race.

Method

Participants

The current study used data from the NACC UDS, a publicly available longitudinal repository that includes data collected during standardized annual evaluations at Alzheimer’s Disease Research Centers (ADRCs) across the country. The recruitment, consent, and data collection protocol were described in detail by Morris and colleagues (2006). At each annual NACC-UDS visit, participants completed a standardized visit packet including basic sociodemographic information, personal and family medical history, and self-report and collateral questionnaires. They also received psychiatric and neurological examinations, and neuropsychological measures. A subset of participants also received brain imaging. The NACC databases are approved by the University of Washington Institutional Review Board, and informed consent from participants was obtained at the individual ADRCs under local institutional review board oversight. The study was conducted in accordance with the Declaration of Helsinki.

The current analyses were based on data from the first available visit between September 2005 to June 2019 for adults aged 55 and older who self-identified as Black or African American and who had a brain imaging visit and depression or depressive symptom data within 1 year of a UDS visit (N = 443). This subsample did not differ in demographics or depressive symptom severity from the Black/African American baseline sample aged 55 and older in the larger NACC data set at the time of our analysis (N = 5,093). Characteristics of the total sample are summarized in Table 1. The sample size varied for each analysis based on the available data. The results tables summarize demographic and clinical characteristics of the subsample for each analysis.

Table 1.

Characteristics of the Total Sample (N = 443)

Variable Mean or % SD Range
Age (years) 72.80 8.83 55–95
Education (years) 14.10 3.25 0–22
Sex (% female) 70.65% — —
Depression in past 2 years 21.03% — —
Depression > 2 years ago 14.22% — —
GDS-15 1.97 2.62 0–13
WMH volume 12.54 13.55 0.07–67.05
Dementia 19.41% — —
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Notes: GDS-15 = 15-item Geriatric Depression Scale; SD = standard deviation; WMH = white matter hyperintensities. Depression in the past 2 years, GDS-15, and WMH volumes were available for subsets of 391, 430, and 180 participants, respectively. Characteristics of the subsample used for each analysis are provided in the results tables.

Dementia Diagnosis

NACC participants receive annual or semiannual follow-up visits and receive a clinical diagnosis of normal cognition, cognitively impaired but not MCI, MCI, or dementia aided by review of the Clinical Dementia Rating Dementia Staging Instrument and participant performance on a comprehensive neuropsychological test battery. Dementia diagnosis is based on National Institute on Aging–Alzheimer’s Association or National Institutes of Neurologic and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association criteria and is made by either an examining physician or by a consensus conference within ADRCs who contribute data to the data set.

Depression

During each NACC-UDS visit, trained clinicians collected participant health history using standardized forms. This includes psychiatric conditions diagnosed or treated by a physician. The current analyses used the dichotomous yes/no variable of active depression in the last 2 years.

Depressive Symptom Severity

The Geriatric Depression Scale-15 item (GDS-15) was used to assess self-reported severity of depressive symptoms in the previous week. Developed from the original 30-item GDS to reduce the interference of fatigue and concentration difficulties on questionnaire completion in older adults (Yesavage & Sheikh, 1986), the GDS-15 has excellent reliability, validity, and clinical utility, similar to the original GDS (Balsamo et al., 2018). Participants completed the GDS-15 either independently or with assistance from ADRC staff.

White Matter Hyperintensities

For the NACC data set, total WMH volumes (in cm3) were quantified based on the WMH estimation protocol from the Alzheimer’s Disease Neuroimaging Initiative-II, described in detail in Alosco et al. (2018). In brief, the fluid attenuated inversion recovery (FLAIR) scan is transformed to the T1 image using linear image registration [FMRIB’s linear imaging registration tool (FLIRT) from the FMRIB software library (FSL) toolbox]. Inhomogeneity correction of the coregistered FLAIR and T1 is performed using a histogram normalization method. The T1 scan is aligned to a common template atlas and WMH are estimated using a Bayesian probability structure with semiautomatic detection of WMH followed by manual editing. Likelihood estimates of the native image are calculated and all segmentation is performed in standard space to generate probability likelihood values of WMH at each white matter voxel. A threshold of 3.5 SDs above the mean is applied to the probabilities to result in a binary WMH mask. The segmented WMH are transformed to native space and summary volume of WMH (in cm3) is calculated. The present analyses used a ratio of total WMH volume to total brain volume.

Statistical Analyses

To address the question of whether depression is associated with a higher dementia prevalence, chi-square analyses were performed to compare dementia rates across depression groups (yes/no variable). Follow-up logistic regression analyses were performed to determine the associations of depression in the past 2 years and GDS-15 scores, a measure of current depressive symptom severity, with dementia when controlling for demographic variables (age, sex, and education) and when controlling for cumulative vascular burden. In keeping with previous studies examining associations of vascular burden with mood or cognitive outcomes (Pettigrew et al., 2020; Romankiewicz et al., 2023), the latter was based on summing the number of conditions present out of the following vascular risk factors and vascular diseases (for a range of scores of 0–11): history of tobacco use, current tobacco use, heart attack, atrial fibrillation, congestive heart failure, obesity, diabetes, hypertension, high cholesterol, stroke, and transient ischemic attack.

Logistic regression analyses were also used to determine whether increased WMH volume increases likelihood of dementia diagnosis in Black adults. In this model, a total WMH/total brain volume variable predicted dementia status, controlling for age, sex, and education.

We then tested whether depression and WMH volume have an interactive effect on dementia status by performing chi-square analyses followed by logistic regression analyses that controlled for age, sex, and education. The predictor in these models was a depression by WMH volume variable. This variable comprised four groups based on the presence or absence of depression and WMH volume above or below the median split for the sample: (1) no depression/low WMH volume, (2) no depression/high WMH volume, (3) depression/low WMH, and (4) depression/high WMH volume.

To address the question of disparities in dementia, that is, increased vulnerability in Black individuals, significant effects in the main analysis were followed by post hoc analyses that included an age-, sex-, and education-matched sample of NHW participants from the NACC data set. We created matched samples using the R “match.it” package (Ho et al., 2011). Using the Black sample as our reference group, we matched the NHW sample with the exact distribution of sex and nearest Euclidean distance for age at first magentic resonance imaging (MRI) and years of education. Matching was verified by conducting a chi-square for race by sex and two-sample t tests for age and years of education, none of which yielded dependence or significant group differences. Race differences were determined by Cochran–Mantel–Haenszel (CMH) tests for chi-square analyses and by race interactions in the logistic regressions.

Results

Depression, Depressive Symptoms, and Dementia Risk

Rates of dementia were higher in participants with depression in the past 2 years (Figure 1A). Specifically, 40.24% of participants with depression in the past 2 years versus 14.56% of those without depression in the past 2 years had a diagnosis of dementia, X2(1, N = 391) = 26.76, p < .0001. This association remained when controlling for demographic factors, odds ratio (OR) = 4.90 [95% confidence interval (CI): 2.75–8.73], X2 = 29.04, df = 1, p < .0001 (Table 2). Analysis of the GDS-15 showed that greater severity of current depressive symptoms was associated with a higher likelihood of having a dementia diagnosis, OR = 1.14 [95% CI: 1.04–1.24], X2 = 8.05, df = 1, p = .005. The effect for depression in the past 2 years remained significant when current depressive symptoms on the GDS-15 were included as a covariate, OR = 4.41 [95% CI: 2.26–8.62], X2 = 18.90, df = 1, p < .0001. Including vascular burden as a covariate did not change any of the results, OR = 5.71 [95% CI: 3.06–10.65], X2 = 29.91, df = 1, p < .0001; GDS-15 OR = 1.13 [95% CI: 1.03–1.25], X2 = 6.21, df = 1, p = .013.

Figure 1.

Figure 1.

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Frequency of dementia diagnosis by depression in the past 2 years (A) and white matter hyperintensities (WMH) volume by depression group (B). The dark portion of each bar represents the percentage of dementia cases for each group.

Table 2.

Subsample Characteristics and Results of Logistic Regression Analyses: Depression Predicting Dementia and WMH Predicting Dementia

Variable Mean ± SD or % OR 95% CI Wald p
Depression predicting dementia
Age 72.61 ± 8.78 1.03 1.00–1.06 4.02 .045
Sex (female) 70.51% 0.81 0.46–1.43 0.55 .459
Education 14.04 ± 3.32 0.88 0.81–0.96 9.04 .003
Depression 21.03% 4.90 2.75–8.73 29.04 <.0001
WMH predicting dementia
Age 76.14 ± 7.80 0.98 0.91–1.06 0.17 .678
Sex (female) 66.11% 0.65 0.23–1.85 0.65 .421
Education 13.72 ± 3.29 0.82 0.70–0.96 6.23 .013
WMH volume 12.54 ± 13.55 >999.99 200.32–>999.99 5.36 .021
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Notes: CI = confidence interval; OR = odds ratio; SD = standard deviation; WMH = white matter hyperintensities. Sex was coded as 1 = male, 2 = female. Depression was coded as 0 = absent, 1 = present. Mean raw WMH volumes are reported in the first column, but the statistical analyses used a ratio of WMH volume to total brain volume.

WMH Volume and Dementia Risk

A higher volume of WMH was associated with a higher likelihood of having a dementia diagnosis in logistic regression analyses controlling for age, sex, and education, OR > 999.99 [95% CI: 200.32–>999.99], X2 = 5.36, df = 1, p = .021 (Table 2).

Depression, WMH Volume, and Dementia Risk

Dementia risk significantly differed by depression–WMH group (Figure 1B), X2(3, N = 175) = 20.67, p = .0001. Participants with no depression/high WMH volume (9.46%) or depression/low WMH (7.69%) were more likely to have a dementia diagnosis compared to the no depression/low WMH volume group (5.33%), but the likelihood was five to nearly nine times higher in the depression/high WMH volume group (46.15%) relative to the other groups. The effect remained significant when controlling for demographic variables, X2 = 15.64, df = 3, p = .001 (Table 3).

Table 3.

Subsample Characteristics and Results of Logistic Regression Analyses: Depression–WMH Group Predicting Dementia

Variable Mean ± SD or % OR 95% CI Wald p
Age 76.22 ± 7.54 0.99 0.92–1.08 0.01 .930
Sex (female) 66.86% 0.59 0.19–1.80 0.86 .354
Education 13.68 ± 3.31 0.79 0.66–0.94 6.88 .009
WMH/depression group — — — 14.76 .002
 Low WMH, no depression 42.86% — — — —
 Low WMH, depression 7.43% 2.34 0.21–25.99 0.48 .489
 High WMH, no depression 42.29% 2.18 0.56–8.42 1.27 .259
 High WMH, depression 7.43% 22.59 4.45–114.75 14.13 .0002
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Notes: CI = confidence interval; OR = odds ratio; SD = standard deviation; WMH = white matter hyperintensities. Low WMH, no depression was the reference group. Sex was coded as 1 = male, 2 = female. Depression was coded as 0 = absent, 1 = present. Low and high WMH designation was based on a median split of the WMH volume to total brain volume ratio (0.008).

Race Differences

Rates of dementia by depression and by depression–WMH group differed across racial groups (depression CMH = 33.58, df = 1, p < .0001; depression–WMH CMH = 18.02, df = 4, p = .0004). As shown in Figure 2, the increased likelihood of dementia related to depression in the past 2 years and in the depression/high WMH volume group was greater in Black compared to NHW participants. Race did not affect the associations of GDS-15 scores, X2 = 0.52, df = 1, p = .469, or WMH volume, X2 = 0.00, df = 1, p = .991, with dementia diagnosis.

Figure 2.

Figure 2.

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Frequency of dementia diagnosis in white matter hyperintensities (WMH) volume by depression groups for Black and White participants. Groups were based on the presence or absence of depression combined with a median split of WMH volume (high/low WMH).

Discussion

Consistent with our hypotheses, study findings revealed depression and high WMH volume were independent predictors of dementia rates in late middle-aged to older Black adults. Higher severity of depressive symptoms was also associated with higher dementia prevalence. The rate of dementia was highest in those with high WMH volume and a history of depression in the past 2 years. While depression and higher WMH were related to 50%–75% higher dementia rates, the rate of dementia was nine times higher in individuals with a combination of higher WMH and depression compared to individuals with neither risk factor. Moreover, associations of depression and the combination of depression and higher WMH burden with dementia were greater in Black compared to NHW individuals. To our knowledge, these are novel findings that provide insight into the interrelationships of LLD, white matter burden, and dementia in Black older adults, while also raising important questions for future research.

Our findings support the association between LLD and dementia that has been documented in predominantly NHW samples (Barnes & Yaffe, 2012; Gallagher et al., 2018; McClintock et al., 2021) We not only extend previous findings to underrepresented Black adults, but also show that both current depressive symptoms (as measured by the GDS-15) and more remote depression (i.e., within the past 2 years) are implicated in dementia for this population. The cross-sectional design of the study does not allow for a determination of how depression and dementia are temporally related, but it is possible that depressive symptoms concurrent with dementia may be an early sign of dementia or reaction to cognitive impairment, while more remote episodes may represent a causal risk factor for dementia (Wiels et al., 2020). For example, vascular, neurodegenerative, and inflammatory processes implicated in LLD also contribute to cognitive impairment and dementia (Dotson et al., 2021). Because these underlying neurobiological changes often persist even in remitted LLD (Liao et al., 2017), individuals who experienced an episode of depression within the past 2 years may have experienced chronic neurobiological changes that increased the risk for developing dementia.

Relative to their NHW counterparts, Black Americans are disproportionately burdened by cardiovascular disease and associated risk factors (e.g., hypertension, diabetes mellitus, obesity; Carnethon et al., 2017), which are implicated in cognitive impairment and dementia outcomes (Gorelick et al., 2011). We found that higher severity of WMH, an indicator of vascular burden, was associated with dementia independent of depression history, consistent with previous literature in Black older adults and in other ethnoracial groups (Hu et al., 2021). Still, the finding that depression was associated with dementia diagnosis even after controlling for cumulative vascular burden suggests that the putative mechanism underlying the association between LLD and dementia for some Black older adults might be independent of ongoing of vascular risk factors, and may reflect sequelae of distinct or multifactorial etiologies. For example, while there is within-group heterogeneity in the socioeconomic status of older Black adults, chronic depression may be influenced by structural societal disadvantages (e.g., segregated neighborhoods and lack of healthcare access), which may lead to a cascade of physiological stress responses (e.g., hypothalamic-pituitary-adrenal axis dysregulation and increased glucocorticoid production) implicated in cognitive decline and Alzheimer’s disease (Zahodne, 2021).

Our finding of much higher odds of dementia diagnosis in individuals with both a history of depression in the past 2 years and higher WMH volumes suggests a potential synergistic effect of depression and WMH on dementia prevalence in Black adults. It is possible that the presence of both LLD and WMH reflects more severe global cerebrovascular disease, or that mechanisms related to each risk factor interact in a multiplicative way to increase dementia risk (Hybels et al., 2016; Van Agtmaal et al., 2017). The interrelationships between depression, WMH, and dementia are complex and definitive mechanisms are yet to be established. In light of this, the temporal and causal associations between WMH, LLD, and dementia in Black older adults have yet to be determined. Our findings in this cross-sectional study indirectly suggest that WMH and LLD may be independent and additive pathways for dementia, but a variety of temporal and causal pathways are possible. For example, it is possible that WMH initiate a cascade of neurocognitive vulnerability that results in depression, which further reduces brain integrity, thereby increasing dementia risk, or perhaps vice versa. It is also possible that WMH lead to dementia, and depression occurs in response to cognitive and functional decline in dementia. Longitudinal studies are necessary to provide clarity about these complex associations. Exploring these relationships is important given the persistence and severity of LLD and WMH in Black older adults, as well as growing evidence of both depression and vascular disease as modifiable risk factors for dementia. Our demonstration that the combination of depression and higher WMH disproportionately affected odds of dementia diagnosis in Black compared to NHW participants underscores the need for additional studies examining depression, vascular disease, and dementia in Black older adults.

There are several limitations to the current study. First, the NACC was not designed to be a study of depression; thus, participants did not undergo a diagnostic interview to support a formal clinical diagnosis of past or present major depressive disorder (MDD), in line with diagnostic criteria from the Diagnostic and Statistical Manual of Mental Health Disorders, and the overall depressive symptom severity is low. However, while not a substitute for a diagnostic interview, the NACC UDS utilizes the GDS-15 at every clinic visit, which is high in sensitivity and specificity relative to MDD diagnostic criteria at cutoff scores of 4, 5, or 6 (Pocklington et al., 2016). Moreover, significant findings in a sample with low levels of depressive symptoms highlight the important contributions of even subclinical levels of depressive symptoms to cognitive outcomes in late life. Second, we cannot determine a temporal timeline of emergence of depressive symptoms, WMH, and dementia with cross-sectional data. Future analyses with longitudinal data could potentially elucidate the time course during which depressive symptoms and WMH burden confer an increased dementia risk, clarifying causality. In following, future analyses may include the associations of depressive symptoms and WMH burden with MCI status and progression to dementia. This will help us to better understand when to introduce intervention strategies or when to begin monitoring these factors in Black older adults. Future research should also examine mechanistic explanations of the relationships between depressive symptoms, WMH burden, and dementia risk, including biological as well as social factors that may contribute to differential dementia risk in Black older adults. Finally, a recent comparison of NACC participant characteristics relative to the nationally representative sample of older adults in the Health and Retirement Study (HRS) found that NACC participants were on average older, had higher levels of education, and reported fewer depressive symptoms than HRS participants (Arce Rentería et al., 2023). These differences were observed across racial and ethnic groups but were magnified between racial and ethnic groups. By using the Black NACC sample as a reference group to identify a demographically matched NHW group, the current study minimized some of the confounding issues between racial and ethnic groups. Nonetheless, the characteristics of the NACC sample limit generalizability of the current findings.

Despite these limitations, the current results have implications for both research and clinical practice. Though we did not formally examine vascular depression, the depression/higher WMH group corresponds with operational definitions of vascular depression used in many research studies. The finding of the highest odds of dementia diagnosis in this group highlights the critical need for research examining vascular depression in Black older adults, who are poorly represented in the existing vascular depression literature. Clinically, our results suggest healthcare providers should monitor depression, vascular disease, and especially their co-occurrence in Black older adults. Referrals for neuropsychological testing, mental health treatment, and lifestyle interventions targeting vascular health (e.g., exercise, nutrition) should be emphasized. Considering racial disparities in dementia risk, it is incumbent upon practitioners to address modifiable risk factors for dementia, such as depression and vascular disease, to promote better brain health for vulnerable groups.

Acknowledgments

The corresponding author acknowledges the UF Center for Cognitive Aging and Memory and the UF McKnight Brain Institute for their support. Results from this study were presented at the Society for Black Neuropsychology Symposium, July 15, 2022.

Contributor Information

Shellie-Anne Levy, Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA; The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA.

Maria B Misiura, Department of Psychology, Georgia State University, Atlanta, Georgia, USA.

Jeremy G Grant, Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA.

Tamare V Adrien, Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA.

Zinat Taiwo, Department of Rehabilitation Psychology and Neuropsychology, TIRR Memorial Hermann, Houston, Texas, USA; H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, Texas, USA.

Rebecca Armstrong, Department of Clinical and Health Psychology, The Center for Cognitive Aging and Memory, University of Florida, Gainesville, Florida, USA.

Vonetta M Dotson, Department of Psychology, Georgia State University, Atlanta, Georgia, USA; Gerontology Institute, Georgia State University, Atlanta, Georgia, USA.

Vanessa Taler, (Psychological Sciences Section).

Funding

The National Alzheimer’s Coordinating Center (NACC) database is supported by National Institute on Aging (NIA)/National Institutes of Health Grant U24 AG072122. NACC data are contributed by the NIA-funded Alzheimer’s Disease Research Centers: P30 AG062429 [Principal Investigator (PI) James Brewer, MD, PhD], P30 AG066468 (PI Oscar Lopez, MD), P30 AG062421 (PI Bradley Hyman, MD, PhD), P30 AG066509 (PI Thomas Grabowski, MD), P30 AG066514 (PI Mary Sano, PhD), P30 AG066530 (PI Helena Chui, MD), P30 AG066507 (PI Marilyn Albert, PhD), P30 AG066444 (PI John Morris, MD), P30 AG066518 (PI Jeffrey Kaye, MD), P30 AG066512 (PI Thomas Wisniewski, MD), P30 AG066462 (PI Scott Small, MD), P30 AG072979 (PI David Wolk, MD), P30 AG072972 (PI Charles DeCarli, MD), P30 AG072976 (PI Andrew Saykin, PsyD), P30 AG072975 (PI David Bennett, MD), P30 AG072978 (PI Neil Kowall, MD), P30 AG072977 (PI Robert Vassar, PhD), P30 AG066519 (PI Frank LaFerla, PhD), P30 AG062677 (PI Ronald Petersen, MD, PhD), P30 AG079280 (PI Eric Reiman, MD), P30 AG062422 (PI Gil Rabinovici, MD), P30 AG066511 (PI Allan Levey, MD, PhD), P30 AG072946 (PI Linda Van Eldik, PhD), P30 AG062715 (PI Sanjay Asthana, MD, FRCP), P30 AG072973 (PI Russell Swerdlow, MD), P30 AG066506 (PI Glenn Smith, PhD), P30 AG066508 (PI Stephen Strittmatter, MD, PhD), P30 AG066515 (PI Victor Henderson, MD, MS), P30 AG072947 (PI Suzanne Craft, PhD), P30 AG072931 (PI Henry Paulson, MD, PhD), P30 AG066546 (PI Sudha Seshadri, MD), P20 AG068024 (PI Erik Roberson, MD, PhD), P20 AG068053 (PI Justin Miller, PhD), P20 AG068077 (PI Gary Rosenberg, MD), P20 AG068082 (PI Angela Jefferson, PhD), P30 AG072958 (PI Heather Whitson, MD), P30 AG072959 (PI James Leverenz, MD). This work is also supported by the National Science Foundation (2112455 to V. M. Dotson) and the Florida Department of Health, Public Health Research (22A11 to J. G. Grant).

Conflict of Interest

None.

Data Availability

This is not a preregistered study. As the authors used publicly available data (National Alzheimer’s Coordinating Center Database), specific analytic methods will be made available to other researchers upon request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

This is not a preregistered study. As the authors used publicly available data (National Alzheimer’s Coordinating Center Database), specific analytic methods will be made available to other researchers upon request.

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