Abstract
INTRODUCTION
Mild cognitive impairment (MCI) represents a transitional stage between normal aging and dementia. We investigate associations among cardiovascular and metabolic disorders (hypertension, diabetes mellitus, and hyperlipidemia) and diagnosis (normal; amnestic [aMCI]; and non‐amnestic [naMCI]).
METHODS
Multinomial logistic regressions of participant data (N = 8737; age = 70.9 ± 7.5 years) from the National Alzheimer's Coordinating Center Uniform Dataset Version 3 protocol cohort were used.
RESULTS
Controlling for demographic/health variables, individuals with aMCI, though not naMCI, showed a higher likelihood of hypertension, diabetes, and hyperlipidemia compared to cognitively normal counterparts, though no differences between aMCI/naMCI. Black Americans, regardless of cognitive status, were more likely to fall into hypertension and diabetes groups compared to White Americans.
DISCUSSION
These findings underscore the critical role of diagnosis and race in MCI diagnosis and care, emphasizing the need for tailored interventions to address inequities and reduce the risk of progression to dementia.
Highlights
The study leverages a large, racially diverse cohort from the NACC database.
Black Americans with non‐amnestic mild cognitive impairment(naMCI) show highest comorbidity burden.
No significant differences in comorbidity burden between amnestic MCI (aMCI) and naMCI subtypes.
Education is protective, but less so for Black American individuals.
Older age, male sex, body mass index (BMI), and low education associate with increased risk for comorbidities.
Keywords: amnestic MCI, black American, comorbidities, diabetes mellitus, hyperlipidemia, hypertension, mild cognitive impairment, non‐amnestic MCI, white American
1. BACKGROUND
Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD) affect 55 million people globally, making AD/ADRD the leading causes of disability and mortality among older adults, with aging as the strongest risk factor. 1 Mild cognitive impairment (MCI), a transitional phase between normal cognition and AD/ADRD, affects 10%‐15% of older adults and is projected to reach 13.85 million cases by 2060. 2 MCI, involving declines in cognitive areas such as memory, attention, and executive functions without markedly impairing daily function, can be categorized into amnestic MCI (aMCI) and non‐amnestic (naMCI) subtypes. aMCI, memory dependent, has been reported to increase risk of progression to AD dementia, while naMCI, non‐memory affected, frequently increases risk of progression to other dementia etiologies such as vascular, frontotemporal, or Lewy body dementia. 3
A robust body of evidence has demonstrated that chronic medical conditions—particularly hypertension (HTN), hyperlipidemia (HLD), and diabetes mellitus (DM)—are strongly associated with an elevated risk of MCI and AD/ADRD. 4 , 5 , 6 Cardiometabolic disorders, including DM and cardiovascular disease (CVD), as well as their associated risk factors such as HTN, are consistently linked to diminished cognitive performance and adverse neurophysiological alterations, particularly among older adults. 7 , 8 , 9 , 10 , 11 Epidemiological studies indicate that individuals with HTN, DM, or elevated cholesterol levels are significantly more likely to present with MCI relative to those without these conditions. 12 , 13 , 14 , 15
The cumulative burden of multiple chronic conditions further exacerbates cognitive vulnerability. Specifically, the presence of comorbidity clusters—defined as the co‐occurrence of two or more chronic diseases—has been implicated in a disproportionately increased risk of the naMCI subtype. 16 , 17 Moreover, chronic multimorbidity has been shown to significantly heighten the probability of cognitive decline over time. 17 Older adults with multiple concurrent comorbidities also report a substantially higher prevalence of subjective cognitive complaints and are more frequently diagnosed with MCI than their healthier counterparts. 18 , 19
Black Americans are projected to experience a 141.8% increase in MCI prevalence by 2060, compared to just 25.9% among White populations.2 However, data from the National Alzheimer's Coordinating Center (NACC) reveal a paradox: despite having higher rates of dementia‐related risk factors such as HTN, DM, and cognitive impairment, Black participants were 35% less likely than their White counterparts to receive an AD/ADRD diagnosis at baseline (26.8% vs. 36.1%). 20 These contrasting trends point to potential disparities in diagnostic practices and access to care. Understanding racial differences in dementia risk and diagnosis is therefore essential for advancing person‐centered approaches to prevention, early detection, and clinical management of cognitive decline—particularly within historically underserved and minoritized populations.
This study examines comorbidities and their relationship with MCI subtypes among White and Black Americans aged 55 years and older compared to participants with a diagnosis of normal cognition using the NACC data set. The NACC dataset is a critical resource for scientific advancement, offering a large, diverse, and well‐characterized cohort that enables robust examination of diagnostic patterns, comorbidities, and cognitive outcomes across racial and clinical subgroups. We hypothesize that (1) individuals with MCI (both aMCI and naMCI) would show higher rates of cardiometabolic comorbidities compared to cognitively normal (CN) individuals; (2) naMCI patients would have a higher burden of comorbidities than aMCI; and (3) Black Americans would demonstrate a higher burden of comorbidities than White Americans, regardless of cognitive diagnosis.
2. METHODS
2.1. Participants
This study used de‐identified data from the NACC, which compiles standardized data from multiple Alzheimer's Disease Research Centers (ADRCs) across the United States. A total of 8737 participants from the NACC Uniform Data Set Version 3 (UDSv3) were included in the current study if their diagnosis was MCI or CN. Participants came from National Institutes of Health‐National Institute on Aging (NIH‐NIA) funded ADRCs across the United States. The obtained NACC dataset contained 10,341 participants, but 688 were dropped from analyses after applying inclusion criteria of 55 years of age or older. This cutoff was used to best characterize the older adult population available from the NACC. Additionally, 916 participants were dropped as this analysis only considered individuals who self‐identify as Black or White Americans. Participants completed site‐specific consent forms, and all sites’ consents were approved by their individual medical ethics review committees (e.g., Institutional Review Board). All procedures followed the ethical standards outlined in the 1964 Declaration of Helsinki and its later amendments or comparable ethical guidelines.
2.2. Procedure
RESEARCH IN CONTEXT
Systematic review: Few studies stratify by both MCI subtype and race or assess multimorbidity patterns using large, well‐characterized datasets. To accomplish this, our group used data from the National Alzheimer's Disease Coordinating Center, specifically data from the Unified Data Set v3.
Interpretation: This study shows that cardiometabolic disorders are associated with both amnestic mild cognitive impairment (aMCI) and non‐amnestic MCI (naMCI,) challenging assumptions about distinct vascular versus neurodegenerative etiologies. Black participants exhibited higher comorbidity burden, particularly those with naMCI. Protective effects of education were evident but attenuated among Black individuals. The use of multinomial models enables a nuanced view of comorbidity patterns beyond binary outcomes that has not been accomplished before.
Future directions: Longitudinal studies are needed to clarify causal pathways and track progression from MCI to dementia. Future research should prioritize diverse samples, integrate social determinants, and test interventions targeting vascular‐metabolic risk to reduce racial disparities and promote cognitive health.
Participants enrolled in the NACC ADRC longitudinal observational study complete a series of assessments approximately annually. This analysis utilizes data from participants’ initial assessment with the NACC UDSv3. Interview and evaluation forms were completed with all participants. These included participant‐ and informant‐reported standardized questionnaires for demographic and historical data (e.g., age, biological sex, race, educational attainment, review of history) and medical, neurological, and neuropsychological examinations. 21 Body mass index (BMI) was calculated and standardized using the standard formula, (BMI—BMI mean (r, d)) / BMI sd (r, d), where r = race (white and black); and d = diagnosis (CN, aMCI, naMCI). Specifics about the UDSv3 have been described in greater detail elsewhere. 21 , 22 For the purposes of the current study, we include self‐reported demographic characteristics (i.e., age, biological sex, race, and educational attainment; Tables 1 and 2), clinician‐assessed height, weight, and medical conditions (i.e., HTN, DM, HLD, atrial fibrillation [AF]; Tables 3 and 4) evaluated during the clinical interview portion of the assessment and clinical diagnosis as determined by consensus conference.
TABLE 1.
Summary of various demographic characteristics for the sample overall and by diagnosis.
| Overall | Group differences | ||||||
|---|---|---|---|---|---|---|---|
| Characteristic | Whole sample | CN | aMCI | naMCI | p‐Value | Holm‐adjusted post hoc test | p‐value |
| N | 8737 | 5470 | 2620 | 647 | |||
| Age, mean (SD) | 70.9 (7.6) | 70.2 (7.3) | 72.4 (7.8) | 71.0 (7.6) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
<0.001 <0.001 0.001 |
| Sex, N male (%) | 3560 (40.8%) | 1890 (34.6%) | 1367 (52.2%) | 303 (46.8%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.01 <0.001 <0.001 |
| Years of education, mean (SD) | 16.2 (2.8) | 16.3 (2.7) | 15.9 (3.0) | 15.9 (2.9) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.4 <0.001 <0.001 |
| Missing (N) | 37 | 23 | 12 | 2 | |||
| Body mass index, mean (SD) | 27.7 (5.5) | 27.9 (5.7) | 27.2 (5.0) | 28.2 (5.6) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
<0.001 <0.001 0.01 |
| Missing (N) | 764 | 425 | 235 | 104 | |||
Note: Kruskal–Wallis test used for continuous variables. Pearson's chi‐squared test used for categorical variables; Holm corrections were used for post hoc adjustment.
Abbreviations: aMCI, amnestic mild cognitive impairment; CN, cognitively normal; naMCI, non‐amnestic mild cognitive impairment.
TABLE 2.
Summary of various demographic characteristics across diagnostic groups by race.
| CN | aMCI | naMCI | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Characteristic | White | Black | p‐Value | White | Black | p‐Value | White | Black | p‐Value |
| N | 4462 | 1008 | 2218 | 402 | 531 | 116 | |||
| Age, mean (SD) | 70.5 (7.5) | 69.1 (6.6) | <0.001 | 72.6 (7.7) | 71.2 (7.8) | <0.001 | 71.0 (7.5) | 71.1 (7.8) | >0.9 |
| Sex, N male (%) | 1,657 (37.1%) | 233 (23.1%) | <0.001 | 1,241 (56.0%) | 126 (31.3%) | <0.001 | 273 (51.4)% | 30 (25.9%) | <0.001 |
| Years of education, mean (SD) | 16.5 (2.6) | 15.5 (2.7) | <0.001 | 16.1 (3.0) | 14.8 (2.8) | <0.001 | 16.1 (3.0) | 14.9 (2.4) | <0.001 |
| Missing (N) | 20 | 3 | 9 | 3 | 2 | 0 | |||
| Body mass index, mean (SD) | 27.2 (5.2) | 30.9 (6.7) | <0.001 | 26.9 (4.8) | 29.1 (5.6) | <0.001 | 27.5 (5.2) | 31.3 (6.3) | <0.001 |
| Missing (N) | 348 | 77 | 213 | 22 | 93 | 11 | |||
Abbreviations: aMCI, amnestic mild cognitive impairment; CN, cognitively normal; naMCI, non‐amnestic mild cognitive impairment.
TABLE 3.
Summary of comorbid conditions for the sample overall and by diagnosis.
| Group differences | |||||||
|---|---|---|---|---|---|---|---|
| Characteristic | Whole sample | CN | aMCI | naMCI | p‐value | Holm‐adjusted post hoc test | p‐value |
| N | 8737 | 5470 | 2620 | 647 | |||
| Hypertension, N (%) | 4033 (46.4%) | 2,353 (43.2%) | 1,352 (51.7%) | 328 (51.1%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.8 <0.001 <0.001 |
| Missing (N) | 37 | 26 | 6 | 5 | |||
| Hyperlipidemia, N (%) | 4462 (51.7%) | 2,656 (49.3%) | 1,455 (56.0%) | 351 (55.0%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.8 <0.001 <0.001 |
| Missing (N) | 109 | 80 | 20 | 9 | |||
| Diabetes, N (%) | 1158 (13.4%) | 649 (12.0%) | 410 (15.7%) | 99 (15.4%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.8 <0.001 0.02 |
| Missing (N) | 61 | 49 | 8 | 4 | |||
| Atrial fibrillation, N (%) | 481 (5.6%) | 257 (4.8%) | 180 (6.9%) | 44 (6.9%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐CN” |
>0.9 <0.001 0.039 |
| Missing (N) | 72 | 58 | 8 | 6 | |||
| Hypertension and hyperlipidemia, N (%) | 2679 (30.9%) | 1,1516 (28%) | 946 (36.3%) | 217 (34.0%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.3 <0.001 0.003 |
| Hypertension and diabetes, N (%) | 862 (9.9%) | 476 (8.8%) | 311 (11.9%) | 75 (11.7%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.8 <0.001 0.027 |
| Hyperlipidemia and diabetes, N (%) | 898 (10.4%) | 508 (9.4%) | 309 (12.0%) | 81 (12.7%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.5 0.002 0.015 |
| Hypertension, hyperlipidemia, and diabetes, N (%) | 707 (8.2%) | 392 (7.2%) | 253 (9.7%) | 62 (9.7%) | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
>0.9 0.002 0.049 |
| Number medical comorbidities | <0.001 |
“aMCI ‐ naMCI” “aMCI ‐ CN” “naMCI ‐ CN” |
0.8 <0.001 <0.001 |
||||
| No comorbidities | 2751 (32%) | 1873 (34.9%) | 706 (27.2%) | 172 (27.1%) | |||
| One comorbidity | 2843 (33.1%) | 1793 (33.4%) | 836 (32.2%) | 214 (33.8%) | |||
| Two comorbidities | 2291 (26.7%) | 1307 (24.4%) | 798 (30.8%) | 186 (29.3%) | |||
| Three comorbidities | 707 (8.2%) | 392 (7.3%) | 253 (9.8%) | 62 (9.8%) | |||
Note: Kruskal–Wallis test used for continuous variables. Pearson's chi‐squared test used for categorical variables; Holm corrections were used for post hoc adjustment.
Abbreviations: aMCI, amnestic mild cognitive impairment; CN, cognitively normal; naMCI, non‐amnestic mild cognitive impairment.
TABLE 4.
Summary of comorbid conditions across diagnostic groups by race.
| CN | aMCI | naMCI | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Characteristic | White | Black | p‐value | White | Black | p‐value | White | Black | p‐value |
| N | 4462 | 1008 | 2218 | 402 | 531 | 116 | |||
| Hypertension, N (%) | 1,680 (37.8%) | 673 (67.2%) | <0.001 | 1,071 (48.4%) | 281 (69.9%) | <0.001 | 235 (44.7%) | 93 (80.2%) | <0.001 |
| Missing (N) | 19 | 7 | 6 | 0 | 5 | 0 | |||
| Hyperlipidemia, N (%) | 2148 (48.8%) | 508 (51.4%) | <0.001 | 1231 (55.9%) | 224 (56.1%) | >0.9 | 284 (54.3 %) | 67 (58.3%) | <0.001 |
| Missing (N) | 60 | 20 | 17 | 3 | 8 | 1 | |||
| Diabetes, N (%) | 419 (9.5%) | 230 (23.1%) | <0.001 | 288 (13.0%) | 122 (30.3%) | <0.001 | 63 (11.9%) | 36 (31.9%) | <0.001 |
| Missing (N) | 35 | 14 | 8 | 0 | 1 | 3 | |||
| Atrial fibrillation, N (%) | 231 (5.2%) | 26 (2.6%) | <0.001 | 161 (7.3%) | 19 (4.7%) | <0.001* | 39 (7.4%) | 5 (4.3%) | 0.2* |
| Missing (N) | 49 | 9 | 7 | 1 | 6 | 0 | |||
| Hypertension and hyperlipidemia, N (%) | 1106 (25.0%) | 410 (41.0%) | <0.001 | 763 (34.5%) | 183 (45.6%) | <0.001 | 158 (30.2%) | 59 (50.9%) | <0.001 |
| Hypertension and diabetes, N (%) | 272 (6.13%) | 204 (20.4%) | <0.001 | 214 (9.7%) | 97 (24.1%) | <0.001 | 41 (7.8%) | 34 (29.6%) | <0.001 |
| Hyperlipidemia and diabetes, N (%) | 327 (7.4%) | 181 (18.3%) | <0.001 | 219 (9.9%) | 90 (22.4%) | <0.001 | 53 (10.1%) | 28 (24.8%) | <0.001 |
| Hypertension, hyperlipidemia, and diabetes, N (%) | 228 (5.2%) | 164 (16.4%) | <0.001 | 174 (7.9%) | 79 (19.7%) | <0.001 | 36 (6.9%) | 26 (22.6%) | <0.001 |
| Number comorbidities | <0.001 | <0.001 | <0.001 | ||||||
| No comorbidity | 1654 (37.7%) | 219 (22.4%) | 641 (29.2%) | 65 (16.3%) | 158 (30.3%) | 14 (12.5%) | |||
| One comorbidity | 1496 (34.1%) | 297 (30.3%) | 712 (32.5%) | 124 (31.1%) | 184 (35.3%) | 30 (26.8%) | |||
| Two comorbidities | 1007 (23%) | 300 (30.6%) | 667 (30.4%) | 79 (19.8%) | 144 (27.6%) | 42 (37.5%) | |||
| Three comorbidities | 228 (5.2%) | 164 (16.7%) | 174 (7.9%) | 131 (32.8%) | 36 (6.9%) | 26 (23.2%) | |||
Note: Pearson's chi‐squared test used for categorical variables except for * Fisher's exact test.
Abbreviations: aMCI, amnestic mild cognitive impairment; CN, cognitively normal; naMCI, non‐amnestic mild cognitive impairment.
2.3. Statistical analyses
All analyses were conducted in R version 4.4.2. R Core. 23 , 24 Chi‐square tests were used to assess statistically significant group differences for categorical variables (i.e., sex, presence of medical condition) and Kruskal–Wallis tests were used for continuous variables (i.e., age, education, BMI). Holm corrections were applied to the post hoc comparisons of chi‐squared tests. Dunn's tests with Holm corrections were used for post hoc comparisons for continuous variables. Given the strong correlation between BMI and race, and BMI and diagnosis, BMI was standardized by race and diagnosis. Of note, AF was originally considered and descriptive statistics for this condition are presented in Tables 3 and 4. However, the low base rate of individuals with this condition precluded us from including AF in the final analysis. To better understand the landscape of comorbid medical conditions, all combinations of HTN, DM, and HLD are also compared across diagnostic and racial categories (Table 3).
The primary research questions regarding likelihood of exhibiting a particular medical comorbidity were determined by a series of binary logistic regressions. Independent predictors included diagnosis and the diagnosis by race multiplicative interaction (i.e., assess for potentially different effects of diagnosis for Black vs. White Americans). Covariates included age, sex, education, and BMI. Finally, to assess the effect of independent predictors on the number of comorbid medical conditions present, multinomial logistic regression was used.
3. RESULTS
Demographic characteristics are presented in Tables for the overall sample (Table 1) as well as by race within diagnostic categories (Table 2).
There were significant Kruskal–Wallis differences in mean age, years of education, and BMI for the sample overall (p < 0.001) as well as between White and Black Americans within the CN and aMCI diagnostic groups (both ps < 0.001). No significant differences in mean age were found between White and Black Americans in the naMCI group but were discovered between White and Black Americans with naMCI in mean years of education and BMI. Additionally, a series of chi‐square tests revealed significant differences in the percentage of individuals in each diagnostic group from the total number of participants (p < 0.001) and between White and Black Americans in each of the three diagnostic categories of CN, aMCI, and naMCI (all ps < 0.001). There was a significantly greater percentage of females than males in each diagnostic group (p < 0.001; Table 1). Within each diagnostic group (CN, aMCI, naMCI), there was a significantly greater percentage of White males compared to Black males (all ps < 0.001; Table 4).
To understand the prevalence of medical comorbidities within the whole sample and then potential differences in the proportion of those with or without certain comorbidities across diagnostic groups, a series of Chi‐square tests were conducted (Tables 3 and 4). Significant differences between diagnostic groups were found in the percentage of individuals with HTN, HLD, DM, as well as the following combinations: (1) HTN and DM, (2) HLD and HTN, (3) HLD and DM, and (4) HTN, HLD, and DM (2a) (all ps < 0.001). There were also significant group differences between diagnoses in the percentage of those with AF (p < 0.001).
Additionally, significant differences emerged between White and Black participants within each of the three diagnostic categories (all ps < 0.001; Table 4) except when assessing the difference in those with and without HLD among aMCI. Fisher's exact test revealed differences between White and Black Americans in both the CN and aMCI groups (ps < 0.001). No significant differences in AF were found between White and Black Americans with naMCI.
Results from the three separate logistic regressions are presented in Table 5. For all comorbid conditions, older individuals were significantly more likely to have HTN (adjusted odds ratio [aOR] = 1.07, confidence interval [CI] = 1.06–1.07, p < 0.001), HLD (aOR = 1.04, CI 1.03–1.04, p < 0.001), or DM (aOR = 1.02, CI = 1.01–1.03, p < 0.001). Males are at significantly higher risk than females for having HTN (aOR = 1.45, CI = 1.31–1.61, p < 0.001), HLD (aOR = 1.29, CI = 1.17–1.42, p < 0.001), or DM (aOR = 1.36, CI = 1.18–1.57, p < 0.001). Higher education was significantly predictive of lower likelihood of HTN (aOR = 0.96, CI = 0.94–0.98, p < 0.001) and DM (aOR = 0.92, CI = 0.90–0.94, p < 0.001), but not HLD (aOR = 0.98, CI = 0.97–1.00, p = 0.04). Higher BMI was related to increased likelihood for HTN (aOR = 1.80, CI = 0.870–1.89, p < 0.001), HLD (aOR = 1.36, CI = 1.30–1.43, p < 0.001), and DM (aOR = 1.71, CI = 1.61–1.83, p < 0.001). Compared to persons with aMCI, CN individuals were significantly less likely to have HTN (aOR = 0.73, CI = 0.65–0.82, p < 0.001), HLD (aOR = 0.84, CI = 0.75–0.94, p < 0.001), or DM (aOR = 0.76, CI = 0.64–0.91, p = 0.002), although no such difference was found between those with aMCI and naMCI. Individuals with naMCI were just as likely to have HTN, HLD, or DM as persons with aMCI.
TABLE 5.
Binary logistic regression models: To find the association between comorbidities, race, and diagnosis controlling for demographic characteristics.
| Hypertension | Hyperlipidemia | Diabetes | ||||
|---|---|---|---|---|---|---|
| Characteristic | aOR (95% CI) | p‐value | aOR (95% CI) | p‐value | aOR (95% CI) | p‐value |
| Age | 1.07 (1.06–1.07) | <0.001 | 1.04 (1.03–1.04) | <0.001 | 1.02 (1.01–1.03) | <0.001 |
| Sex | ||||||
| Female | 1.00 | 1.00 | 1.00 | |||
| Male | 1.45 (1.31–1.61) | <0.001 | 1.29 (1.17–1.42) | <0.001 | 1.36 (1.18–1.57) | <0.001 |
| Years of education | 0.96 (0.94–0.98) | <0.001 | 0.98 (0.97–1.00) | 0.04 | 0.92 (0.90–0.94) | <0.001 |
| Body mass index (standardized) | 1.80 (0.70–1.89) | <0.001 | 1.36 (1.30–1.43) | <0.001 | 1.71 (1.61–1.83) | <0.001 |
| Diagnosis | ||||||
| Amnestic MCI | 1.00 | 1.00 | 1.00 | |||
| Cognitively normal | 0.73 (0.65–0.82) | <0.001 | 0.84 (0.75, 0.94) | 0.002 | 0.76 (0.64–0.91) | 0.002 |
| Non‐amnestic MCI | 0.92 (0.74–1.15) | 0.4 | 1.01 (0.81, 1.24) | >0.9 | 0.98 (0.70–1.34) | 0.9 |
| Diagnosis * Race | ||||||
| Cognitively Normal * White | 1.00 | 1.00 | 1.00 | |||
| Cognitively Normal * Black | 4.29 (3.65–5.05) | <0.001 | 1.18 (1.02–1.37) | 0.030 | 3.17 (2.61–3.85) | <0.001 |
| Amnestic MCI * White | 1.00 | 1.00 | 1.00 | |||
| Amnestic MCI * Black | 3.01 (2.35–3.88) | <0.001 | 1.06 (0.84–1.33) | 0.6 | 2.94 (2.24–3.85) | <0.001 |
| Non‐amnestic MCI * White | 1.00 | 1.00 | 1.00 | |||
| Non‐amnestic MCI * Black | 5.76 (3.45–9.94) | <0.001 | 1.13 (0.73–1.76) | 0.6 | 3.05 (1.78–5.16) | <0.001 |
Note: The reference group for diagnosis comparison is aMCI. The reference group for the interaction between diagnosis and race is White Americans.
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; MCI, mild cognitive impairment.
We examined the effect of race on diagnosis in predicting each comorbid condition. Black CN Americans were at significantly higher risk of having HTN (aOR = 4.29, CI = 3.65–5.05, p < 0.001), HLD (aOR = 1.18, CI = 1.02–1.37, p < 0.001), and DM (aOR = 3.17, CI = 2.61–3.85, p < 0.001) compared to White CN Americans. Black Americans with aMCI were significantly more likely to have HTN (aOR = 3.01, CI = 2.35–3.88, p < 0.001), and DM (aOR = 2.94, CI = 2.24–3.85, p < 0.001) compared to White Americans with aMCI, but no significant difference was found in the likelihood of having HLD (aOR = 1.06, CI = 0.84–1.33, p > 0.05). Finally, Black Americans with naMCI were significantly more likely than White Americans with naMCI to have HTN (aOR = 5.76, CI = 3.45–9.94, p < 0.001) or DM (aOR = 3.05, CI = 1.78–5.16, p < 0.001) but not HLD (aOR = 1.13, CI = 0.73–1.76, p > 0.05). The forest plot (Figure 1) shows the odds ratios and 95% confidence intervals for predicting comorbidities across predictors: diagnosis, race, BMI, and demographic characteristics from the regression analysis (Table 5).
FIGURE 1.
Forest plot illustrating the odds ratios for predicting comorbidities across predictors: diagnosis, race, body mass index, and demographic characteristics. Each point reflects the odds ratio, with the horizontal lines indicating 95% confidence interval.
Finally, we conducted a multinomial logistic regression to understand predictors of those with multiple comorbidities as compared to just a single condition or no condition and results are presented in Table 6. Older age (aOR = 1.04, CI = 1.03–1.05, p < 0.001), males (aOR = 1.26, CI = 1.12–1.42, p < 0.001), and individuals with higher BMI (aOR = 1.48, CI = 1.39–1.58, p < 0.001) were all predictive of having at least one medical condition compared to not having any conditions. Although neither education nor diagnosis predicted increased likelihood of having just one comorbid condition, Black Americans were significantly more likely than White Americans to have at least one medical condition among CN individuals (aOR = 1.66, CI = 1.36–2.03, p < 0.001), participants with aMCI (aOR = 1.88, CI = 1.35–203, p < 0.001), and persons with naMCI (aOR = 2.15, CI = 1.06–4.36, p = 0.033).
TABLE 6.
Multinomial logistic regression model (reference group = 0 comorbid conditions): To find the association between the number of comorbidities, diagnosis, and race.
| Characteristic | aOR (95% CI) | p‐value |
|---|---|---|
| One comorbidity | ||
| Age | 1.04 (1.03–1.05) | <0.001 |
| Sex | ||
| Female | 1.00 | |
| Male | 1.26 (1.12–1.42) | <0.001 |
| Education | 0.98 (0.96–1.01) | 0.1 |
| Body mass index (standardized) | 1.48 (1.39–1.58) | <0.001 |
| Diagnosis | ||
| Amnestic MCI | 1.00 | |
| Cognitively Normal | 0.88 (0.77–1.02) | 0.1 |
| Non‐amnestic MCI | 1.03 (0.79–1.34) | 0.8 |
| Diagnosis * Race | ||
| Amnestic MCI * White | 1.00 | |
| Amnestic MCI * Black | 1.88 (1.35–2.63) | <0.001 |
| Cognitively Normal * White | 1.00 | |
| Cognitively Normal * Black | 1.66 (1.36–2.03) | <0.001 |
| Non‐amnestic MCI * White | 1.00 | |
| Non‐amnestic MCI * Black | 2.15 (1.06–4.36) | 0.033 |
| Two comorbidities | ||
| Age | 1.08 (1.07–1.09) | <0.001 |
| Sex | ||
| Female | 1.00 | |
| Male | 1.65 (1.45–1.88) | <0.001 |
| Education | 0.96 (0.94–0.98) | <0.001 |
| Body mass index (standardized) | 1.98 (1.85–2.12) | <0.001 |
| Diagnosis | ||
| Amnestic MCI | 1.00 | |
| Cognitively normal | 0.68 (0.58–0.79) | <0.001 |
| Non‐amnestic MCI | 0.96 (0.72–1.28) | 0.8 |
| Diagnosis * Race | ||
| Amnestic MCI * White | 1.00 | |
| Amnestic MCI * Black | 2.31 (1.65–3.25) | <0.001 |
| Cognitively Normal * White | 1.00 | |
| Cognitively Normal * Black | 2.91 (2.36–3.59) | <0.001 |
| Non‐amnestic MCI * White | 1.00 | |
| Non‐amnestic MCI * Black | 4.10 (2.05–8.20) | <0.001 |
| Three comorbidities | ||
| Age | 1.09 (1.07–1.10) | <0.001 |
| Sex | ||
| Female | 1.00 | |
| Male | 1.81 (1.49–2.23) | <0.001 |
| Education | 0.90 (0.87–0.93) | <0.001 |
| Body mass index (Standardized) | 2.75 (2.51–3.02) | <0.001 |
| Diagnosis | ||
| Amnestic MCI | 1.00 | |
| Cognitively normal | 0.60 (0.47–0.76) | <0.001 |
| Non‐amnestic MCI | 0.94 (0.61–1.47) | 0.8 |
| Diagnosis * Race | ||
| Amnestic MCI * White | 1.00 | |
| Amnestic MCI * Black | 5.42 (3.61–8.14) | <0.001 |
| Cognitively Normal * White | 1.00 | |
| Cognitively Normal * Black | 7.29 (5.53–9.61) | <0.001 |
| Non‐amnestic MCI * White | 1.00 | |
| Non‐amnestic MCI * Black | 8.17 (3.55–18.8) | <0.001 |
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; MCI, mild cognitive impairment
A similar pattern was found when examining risk factors for likelihood of having two comorbid conditions compared to not having any conditions. Older age (aOR = 1.08, CI = 1.07–1.09, p < 0.001), male (aOR = 1.65, CI = 1.45–1.88, p < 0.001), fewer years of education (aOR = 0.96, CI = 0.94–0.98, p < 0.001), and higher BMI (aOR = 1.98, CI = 1.85–2.12, p < 0.001) all predicted increased likelihood of having two comorbid conditions compared to not having any condition. Whereas CN individuals were no more or less likely to have one medical condition compared to those without any conditions, they were found less likely to have two conditions (aOR = 0.68, CI = 0.58–0.79, p < 0.001). No significant difference was found in likelihood of having two conditions between individuals with aMCI and individuals with naMCI (aOR = 0.96, CI = 0.72–1.28, p > 0.05). Black participants were more likely to have two or more comorbidities compared to White participants among each CN (aOR = 2.91, CI = 2.36–3.59, p < 0.001), aMCI (aOR = 2.31, CI = 1.65–3.25, p < 0.001), and naMCI (aOR = 4.10, CI = 2.05–8.20, p < 0.001) diagnosis.
The same pattern of results for assessing the likelihood of having two comorbid conditions compared to not having any medical conditions emerged when examining predictors of having all three comorbid conditions. Older age (aOR = 1.09, CI = 1.07–1.10, p < 0.001), male (aOR = 1.81, CI = 1.49–2.23, p < 0.001), fewer years of education (aOR = 0.90, CI = 0.87–0.93, p < 0.001), and higher BMI (aOR = 2.75, CI = 2.51–3.02, p < 0.001) all predicted increased likelihood of having all three comorbid conditions used in these analyses compared to not having any condition. CN status served as a protective factor, reducing the likelihood of having all three medical conditions (aOR = 0.60, CI = 0.47–0.76, p < 0.001). As when examining the likelihood of having two conditions, there was no significant difference between individuals with aMCI compared to those with naMCI (aOR = 0.94, CI = 0.61–1.47, p > 0.05). Black Americans were found to be at a higher risk for having all three conditions compared to their White American peers in each diagnosis category: CN (aOR = 7.29, CI = 5.53–9.61, p < 0.001), aMCI (aOR = 5.42, CI = 3.61–8.14, p < 0.001), and naMCI (aOR = 8.17, CI = 3.55–18.80, p < 0.001).
4. DISCUSSION
This study utilized data from the NACC centralized repository to examine the association between HTN, DM, and HLD among CN, aMCI, and naMCI participants. These findings highlight how comorbid conditions and race are associated with MCI subtypes in community‐based cohorts, underscoring the need for more inclusive, socially aware models of risk assessment and care planning. These findings support Hypothesis 1 indicating that individuals with MCI, regardless of subtype, are significantly more likely to have HTN, DM, and HLD compared to CN participants.
The lack of significant differences in comorbidities between aMCI and naMCI was unexpected given our Hypothesis 2. This suggests that both subtypes may be similarly associated with cardiovascular and metabolic conditions, as discussed, below.
Our data supported Hypothesis 3, demonstrating that Black Americans exhibited higher rates of all comorbidities —except HLD— across all diagnostic groups compared to White Americans. This aligns with national data showing a disproportionate burden of HTN and DM in Black populations, 24 , 25 and with literature reporting higher rates of cardiovascular and metabolic disease, earlier onset of chronic conditions, and greater cognitive decline in Black Americans. 2 , 26 Multinomial logistic regression further revealed that Black Americans had a greater likelihood of multimorbidity—defined as two or more chronic conditions—across both MCI subtypes, regardless of the condition combination. Multimorbidity is a well‐established risk factor for cognitive impairment. 27 Higher rates of HTN, DM, and other metabolic disorders among African Americans contribute to a disproportionately greater burden of cognitive decline and dementia. 28 Finally, regression models adjusting for covariates showed that older age, male sex, lower education, and higher BMI were all associated with increased incidence of each comorbidity.
4.1. Hypertension
Higher rates of HTN among MCI participants compared to CN individuals are consistent with prior research linking chronic vascular and metabolic disorders to cognitive impairment through mechanisms such as chronic inflammation, cerebrovascular dysfunction, and insulin resistance. These findings support the idea that aggressive management of cardiovascular and metabolic risk factors may reduce cognitive decline across MCI and various dementia subtypes. 29 , 30 Our results also align with studies connecting HTN to cerebral white matter changes, hippocampal atrophy, and reduced cognitive resilience—hallmarks of early‐stage MCI. 31 , 32 Interestingly, no significant differences in HTN prevalence were found between aMCI and naMCI. This was initially unexpected, as vascular contributions are often assumed to be more pronounced in naMCI‐related conditions 33 , 34 and aMCI is thought to be less associated with cerebrovascular disease and more closely linked to the pathophysiology of AD. 35 However, research on this topic remains mixed. While some studies report higher HTN risk for naMCI but not aMCI, 34 others, consistent with our findings, suggest HTN is broadly associated with cognitive impairment, regardless of MCI subtype. 36 Camarda et al. similarly found that HTN increases the risk for both aMCI and naMCI by damaging small brain vessels, leading to hypoperfusion and white matter injury. 37 Our results suggest that common vascular/metabolic mechanisms may underlie both MCI subtypes and that clinical subtype may not map cleanly onto etiology in diverse community‐based samples. 38
4.2. Diabetes mellitus
Our results indicate that individuals with both aMCI and naMCI have significantly higher rates of DM compared to CN participants. While DM is widely recognized as a risk factor for cognitive impairment through both vascular and neurodegenerative Alzheimer's pathways, 39 it remains unclear whether its prevalence differs between aMCI and naMCI. 34 Similarly, Xue et al. found no significant difference between aMCI and naMCI in relation to DM (pooled effect sizes of 1.50 and 1.34, respectively). 40 In contrast, Luchcinger 14 found that DM was associated with a significantly increased risk of aMCI after adjusting for covariates. DM‐related microvascular and macrovascular damage may impair cerebral perfusion, leading to subcortical white matter lesions, small vessel disease, and slower information processing—mechanisms potentially relevant to both aMCI and naMCI. 41 , 42
4.3. Hyperlipidemia
Characterized by elevated cholesterol and triglyceride levels, HLD is a well‐known risk factor for CVD, but its association with cognitive decline and MCI remains inconsistent. Our results show that individuals with MCI have significantly higher rates of HLD compared to CN participants. These findings align with prior studies linking dyslipidemia to increased risk of MCI and dementia. 43 , 44 Elevated cholesterol levels have been implicated in promoting amyloid‐beta (Aβ) aggregation, a hallmark of AD. 45
4.4. Multimorbidity
A well‐established link exists between multimorbidity and increased risk for MCI. 17 Our findings show that Black individuals with MCI had consistently higher odds of having one, two, or three comorbidities, indicating a cumulative disadvantage that may amplify health disparities over time. The disproportionately higher prevalence of multimorbidity among Black Americans with MCI suggests that chronic disease burden contributes to earlier cognitive decline in this population. 46 Prior research similarly shows that Black Americans with MCI exhibit higher rates of conditions such as DM and HTN, both of which are known to accelerate cognitive deterioration. 14 , 47
4.5. Differences associated with race
One of the most notable findings in our study is the significantly higher prevalence of HTN and DM among Black Americans compared to White Americans across all diagnostic groups. These disparities have important implications for MCI risk and dementia prevention. Black individuals tend to develop HTN earlier and experience greater blood pressure variability, both associated with increased dementia risk. 48 Genetic, environmental, and socioeconomic factors likely contribute to differences in vascular reactivity, endothelial function, and blood pressure control. 49 , 50 , 51 Similarly, higher DM prevalence has been linked to a combination of epigenetic influences, environmental stressors, and limited access to care. 52 Reducing disparities in HTN and DM management—and improving healthcare access—is essential to addressing racial inequities in MCI and dementia.
4.6. Demographic factors
The finding that age is associated with higher odds of HTN, HLD, and DM aligns with prior research linking aging to increased cardiovascular and metabolic burden. 53 , 54 , 55 The progressive rise in multimorbidity risk with age is also consistent with models of age‐related disease accumulation. 55 Binary logistic regression further showed that males had significantly higher odds of these comorbidities compared to females, consistent with studies attributing sex differences to hormonal and lifestyle factors. 56 Estrogen's proposed neuroprotective and vasoprotective effects may help explain the later onset of HTN‐related cognitive decline in postmenopausal women. 57 , 58 Higher educational attainment also appeared protective. Borrel et al. found an inverse association between education and DM prevalence among Whites and Hispanics, but not Blacks, suggesting that education may influence health differently across racial/ethnic groups. 59 This supports the education–health gradient, wherein greater education enhances health literacy and socioeconomic opportunity, potentially reducing chronic disease risk via cognitive reserve. 60 Our findings underscore the importance of lifelong learning and health education in mitigating the risk of chronic disease and cognitive decline.
4.7. Limitations and future directions
Several limitations of this study must be acknowledged. Although being Black was a significant predictor of HTN, other unmeasured factors—such as socioeconomic status, healthcare access, and neighborhood deprivation—may also contribute to its higher prevalence but were unavailable for inclusion in our analyses. Additionally, the study's observational design limits causal interpretations between comorbidities and MCI progression.
Despite a large overall sample (N = 8737), racial distribution was uneven (82.5% White, 17.5% Black), which limited our ability to explore race‐by‐diagnosis interactions and reduced the robustness of complex models. Although this imbalance was addressed using generalized logistic regression, generalizability remains a concern, particularly for racial comparisons. The NACC dataset is based on volunteer participants, often recruited from clinics or advertisements. This raises concerns about representativeness, though it increases the likelihood of including individuals with diagnosed conditions.
Treatment adherence was not assessed, which could affect comorbidity management and cognitive outcomes. BMI was not categorized into subgroups (e.g., normal, overweight, obese), as doing so would have significantly reduced statistical power. Despite these limitations, the large sample size and rigorous analytical approach strengthen the validity of our findings. Future longitudinal studies should include more diverse populations and assess additional variables such as diet, physical activity, medication adherence, and socioeconomic stressors to inform precision medicine strategies for cognitive health.
4.8. Conclusion
This study indicates that individuals diagnosed with MCI, regardless of subtype, have a significantly higher prevalence of cardiovascular and metabolic comorbidities compared to CN participants. Additionally, the study underscores racial disparities in multimorbidity, showing that Black Americans are disproportionately affected by HTN, DM, and multimorbidity, which may contribute to their increased risk of MCI cognitive decline. The lack of significant differences in comorbidities between aMCI and naMCI suggests that both MCI subtypes may share similar vascular and metabolic risk factors, supporting the view that cardiovascular health plays a critical role in cognitive aging. Furthermore, the study emphasizes education as a protective factor, with higher educational attainment being associated with a lower prevalence of HTN, DM, and HLD. However, this protective effect may vary across racial groups.
By integrating diagnostic subtypes (aMCI vs. naMCI), racial stratification, and multimorbidity profiles within a large, nationally representative ADRC‐based cohort (NACC UDSv3), our study offers a meaningful, incremental advancement of prior research and contributes novel insights into the complex interplay between cognitive impairment and cardiometabolic burden across racial groups. Expanding studies to incorporate a more diverse population, assessing additional risk factors, and integrating precision medicine approaches will be crucial for developing targeted prevention and intervention strategies. Ultimately, addressing racial health disparities, promoting cardiovascular health, and improving education and health care access are vital steps toward reducing the burden of cognitive impairment and dementia in aging populations.
AUTHOR CONTRIBUTIONS
Dr. Giordani had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Mr. Turaani and Dr. Kavcic contributed equally as co‐first authors. Concept and design: Giordani, Kavcic, Turaani, Reader. Acquisition, analysis, or interpretation of data: Turaani, Reader, Pal, Giordani. Drafting of the manuscript: Turaani, Kavcic, Pal, Reader, Giordani. Critical review of the manuscript for important intellectual content: Giordani, Kavcic, Turaani, Pal, Reader. Statistical analysis: Pal, Reader. Obtained funding: Giordani, Kavcic. Administrative, technical, or material support: Reader. Supervision: Kavcic, Giordani, Reader.
CONFLICT OF INTEREST STATEMENT
None reported. Author disclosures are available in the supporting information.
Supporting information
Supporting Information
ACKNOWLEDGMENTS
This work was supported in part by the National Institutes of Health/National Institute on Aging funding (P30AG053760 and 1R01AG054484), as well as National Institutes of Health/National Institute on Aging National Alzheimer's Disease Coordinating Center funding (U24 AG072122) and National Institutes of Health/National Institute on Aging‐funded ADRC P30s (AG062429, AG066468, AG062421, AG066509, AG066514, AG066530, AG066507, AG066444, AG066518, AG066512, AG066462, AG072979, AG072972, AG072976, AG072975, AG072978, AG072977, AG066519, AG062677, AG079280, AG062422, AG066511, AG062715, AG072973, AG066506, AG066508, AG066515, AG072947, AG072931, AG066546, AG086401, AG086404, AG072958, AG072959). NIH/NIA provided support for research and Wayne State University and University of Michigan provided salary support. Funding sources was not involved in preparation of the article, study design, data collection, analysis and interpretation, writing of the report, and in the decision to submit the article for publication. The authors thank the participants who volunteered their time and effort to the national network of Alzheimer's Disease Research Centers.
Kavcic V, Turaani M, Pal S, Reader JM, Giordani B. Cardiometabolic disorders and mild cognitive impairment in White and Black Americans. Alzheimer's Dement. 2025;21:e70642. 10.1002/alz.70642
DATA AVAILABILITY STATEMENT
Data are available upon request from the National Alzheimer's Coordinating Center (NACC).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information
Data Availability Statement
Data are available upon request from the National Alzheimer's Coordinating Center (NACC).