Impact of long-term systolic blood pressure on cognitive disorder risk: Across different age groups and antihypertensive medication timing

Abstract

Background

Elevated blood pressure (BP) is considered a risk factor for cognitive disorders. This study examined the continuous relationship between 2-year mean systolic BP (SBP) and incident cognitive disorders in a large, real-world primary care cohort.

Objective

To evaluate the associations of 2-year mean SBP with incident cognitive impairment in a ‘real-world’ clinical observational dataset.

Methods

We conducted a longitudinal analysis of electronic health records (EHR) from primary care patients aged 50 or older. Patients were included if they had ≥2 SBP measurements and no cognitive disorder diagnosis prior to or within 3 years of their first included SBP measurement. Exposure was the average SBP in the two years following the first measurement. We estimated associations between (continuous) average SBP and incident cognitive impairment using a Cox model. Records from 160,052 patients were included in the analysis.

Results

In our study, SBP ≥ 140 mmHg is not associated with a statistically significant difference in cognitive disorder risk compared to lower SBP (<120 and 120–140 mmHg). In the ages 60–69 group, SBP 135 mmHg is the lowest SBP at which a significantly decreased risk for cognitive disorders was observed (HR, 0.84; 95% CI, 0.82–0.89; p < 0.05). Among unmedicated individuals, 136 mmHg SBP was the lowest SBP at which a statistically significant association with decreased cognitive disorder risk was observed (HR, 0.92; 95% CI, 0.87–1.00; p < 0.05).

Conclusions

The association between SBP and cognitive disorder risk varies by age and BP medication use. This highlights the need for individualized BP targets to mitigate cognitive impairment.

Keywords

Alzheimer's disease blood pressure cognition disorders dementia electronic health records

Introduction

The number of individuals living with dementia is increasing globally, with projections estimated to reach 152 million by 2050.¹ Hypertension is a key risk factor for dementia, with an estimated 2% contribution to modifiable risk; interventions targeting blood pressure could prevent or delay the onset of cognitive disorders.^1–4 Several observational studies suggest that elevated blood pressure (BP), particularly in midlife, may contribute to an increased risk of cognitive decline later in life^5–9 and a recent randomized trial found that intensive blood pressure control was associated with lower rates of incident cognitive impairment.¹⁰ High systolic blood pressure (SBP), specifically, has been implicated in the development of various types of dementia, including Alzheimer's disease (AD).^11,12 However, the optimal SBP threshold for preventing cognitive decline remains uncertain.^13,14 This question is especially important for older patients for whom tightly controlled blood pressure caries additional risks such as hypotension, syncope, electrolyte abnormalities and acute kidney injury.^10,15 The goal of this study was to examine the association between SBP and incident cognitive disorders and to identify age-specific blood pressure thresholds associated with cognitive disorder risk. By using large-scale electronic health record (EHR) data, we are able to explore interactions between blood pressure, age, treatments, and comorbidities in a heterogeneous, real-world patient population.

Methods

Data source and population

The analyses included EHR data from patients seen in the primary care clinics of the Johns Hopkins Health System. We included all patients who (1) had least one primary care visit between January 1, 2014, and May 31, 2025, at which time they were 50 or older and (2) had at least two blood pressure measurements on or after this visit, separated by at least one year. Each patients’ birth date was designated as the “baseline.”. Patients were excluded if they had a mild cognitive impairment (MCI) or dementia diagnosis (details given below) any time before or within three years of their first included SBP measurement. This exclusion criteria ensures that our exposure (blood pressure within the first two years) precedes our outcome (incident cognitive disorder). Data analyzed include demographics (age, gender, race), number of healthcare visits, diagnoses (cardiovascular comorbidities, dementia, MCI), vital signs (blood pressure measurements), and blood pressure medication orders. This study received approval from a Johns Hopkins Institutional Review Board (IRB No. IRB00269466), with a waiver of consent granted because all data were collected during routine care, no alterations to care were made, and the risk of privacy breaches was adequately minimized.

Covariates

Exposure measures. The exposure variable was SBP measurements averaged over the first 2 years following the patient's first eligible SBP measurement. SBP was treated as a continuous variable. SBP measurements with biologically implausible values (>255 mmHg and <40 mmHg) were excluded. SBP variability (SBPV) was included as an exposure in a secondary analysis and was calculated as the difference between the maximum and minimum SBP values within the specified period. Several studies have implicated BPV with cognitive decline. Some have shown that higher systolic BPV is associated with increased cognitive impairment and others that high BPV is linked with faster cognitive decline.^16,17

Cognitive disorder diagnoses. The primary outcome was a diagnosis of MCI or dementia or, which we refer to collectively as a cognitive disorder. This combination was chosen to maximize sensitivity in light of substantial underdiagnosis of dementia in primary care settings.¹⁸ Diagnoses of dementia and MCI were identified through one or more encounter diagnoses or hospital billing ICD-10 codes (Supplemental Table 2). The timing of the outcome was the time of the first such diagnosis code in the patient's record. The specific ICD-10 codes used to identify dementia included F01.XX, F02.XX, F03.XX, G30.XX, G31.0X, G31.1, G31.83, and to identify MCI the ICD-10 code G31.84 was used. We did not differentiate between dementia subtypes.

Demographics

Gender, and race were included as covariates. Age is a well-established risk factor for both hypertension and cognitive disorders, including MCI and dementia.¹⁹ Time zero was considered the birth date. Using birth date as time zero eliminates age confounding and addresses survival bias. Gender differences have been observed in both blood pressure regulation and the incidence of cognitive disorders.²⁰ Gender assigned at birth was not available for all patients, so current gender was used. Race was included as a covariate because of known racial differences in both blood pressure control and the prevalence of cognitive disorders.^21,22 Race was self-reported and categorized as American Indian, Asian, Black, Pacific Islander, White, unknown, or explicitly listed as “other” with no further information available. Hispanic and non-Hispanic ethnicity was determined from reports on clinical intake forms. Number of visits was also included as a covariate seeing as usually more healthcare visits indicate potentially worse health.

Comorbidities. We included diagnoses of several cardiovascular comorbidities, including history of hypertension, atrial fibrillation, heart failure, non-ischemic heart disease, ischemic heart disease, stroke/transient ischemic attack (TIA), diabetes, hyperlipidemia, and chronic kidney disease identified by ICD-10 diagnosis codes²³ (Supplemental Table 2). We adjusted for history of hypertension to account for hypertension during the observation period. As atrial fibrillation increases the risk of stroke and cognitive disorders, atrial fibrillation was included as a covariate to accounted for its potential confounding effect on the interactions between blood pressure and cognitive health.²⁴ Heart failure and non-ischemic heart disease are related to poor cardiovascular health and have been linked to an increased risk of cognitive disorders.^25,26 Ischemic heart disease is associated with reduced blood flow to the brain, increasing the risk of cognitive disorders. Like other cardiovascular conditions, it can also influence blood pressure, necessitating its inclusion as a covariate.^27,28 Stroke and TIA are significant predictors of cognitive disorders, as they directly impact brain function.^29,30 Since high blood pressure is a major risk factor for stroke, adjusting for stroke/TIA in the analysis helps to clarify the specific impact of systolic blood pressure on cognitive outcomes, independent of stroke-related effects. The presence of diabetes is associated with vascular complications, metabolic disruptions, and chronic inflammation, all of which are implicated in increased risks of cognitive impairment.^31–33 Hyperlipidemia has been linked to changes in cerebral blood flow, increased inflammation, and atherosclerosis, all of which contribute to cognitive impairment.³⁴ Chronic kidney disease is also an important covariate, seeing as in patients with chronic kidney disease, higher baseline SBP was associated with a higher risk of developing cognitive disorders and dementia.^35,36 If no diagnosis was recorded, the comorbidity was considered absent. All comorbidities were treated as fixed covariates. A patient was classified as having a diagnosis if any relevant ICD-10 codes appeared during follow-up.

Blood pressure medications. Blood pressure medication use was treated as a categorical covariate during the two-year follow-up period, classified based on prescriptions occurring before, during, or after the two-year SBP follow-up, as well as no prescription at all. Medications were categorized as diuretics, beta-blockers, calcium channel blockers, agents acting on the renin-angiotensin system (angiotensin receptor 1 blockers, angiotensin-converting enzyme inhibitors), and centrally acting antiadrenergic agents (Supplemental Table 1). If no prescriptions were recorded, it was assumed that the patient was not taking the medications of interest.

Statistical analysis

Cumulative incidence curves. Unadjusted cumulative incidence curves for cognitive disorders were generated using Kaplan-Meier estimation, with time zero set as the birth date. Three sets of curves were generated: stratified by race (non-Hispanic Black versus non-Hispanic White and overall), by average SBP over the first 2-years (“<120 mmHg” versus “120–140 mmHg” versus “≥140 mmHg” and overall), and by hypertension diagnosis (Hypertension versus No hypertension, overall, and risk difference).

Primary analysis. We employed a Cox model to examine the association between SBP and incident cognitive disorder. Because dementia risk is heavily age dependent, time to event was measured from each patient's birth date and patients were considered left-truncated until their first included blood pressure measurement. Patients were considered right censored at the last observed visit, regardless of the reason for censoring. A sensitivity analysis was conducted in which death was treated as a competing risk (see below). To examine the impact of various confounders, we present associations from three models: unadjusted (Model 1), adjusted for race, gender, blood pressure medications, number of healthcare visits, and the above comorbidities (Model 2), and adjusted for all the variable in Model 2 plus preexisting hypertension (Model 3) (Supplemental Figure 1). Preexisting hypertension is included in Model 3 to isolate blood pressure in the two years following baseline from prior periods of hypertension. That is, patients with prior hypertension may be more likely also to experience hypertension during the exposure window, resulting in confounding that overstates the isolated effect of the exposure window. Because there is also likely collinearity between preexisting hypertension and the exposure, we include Model 2 to give the range of plausible associations (akin to a partial identification range). For Models 2 and 3, history of each cardiovascular comorbidity was encoded as binary. SBP was modeled using natural centered splines (4 degrees of freedom). Model 3 was then stratified at ages 50–59, 60–69, 70–79, and 80 and older. p-values were calculated using a 2-tailed Wald test with significance set at p < 0.05. All analyses were conducted in Python using the lifelines package, version 0.28.0.

Secondary and sensitivity analyses. As part of a secondary analysis, we stratified participants into medicated and non-medicated groups by modeling antihypertensive use as a categorical covariate—defined as having a prescription before, during, or after the first two years of follow-up, or no prescription at all. In our primary analysis, for simplicity, we grouped participants as not on medication versus on medication (combining all three prescription categories).

Furthermore, as an additional secondary analysis, we employed a Cox model to examine the association between SBPV and incident cognitive disorder. In particular, we used the fully adjusted model 3 as described above but with SBPV as our exposure. Additionally, to test the sensitivity to death as a competing risk, the Aalen-Johansen estimator was employed as a sensitivity analysis for the cumulative incidence, while the Fine-Gray subdistribution hazard model was applied to the Cox proportional hazards analysis (Supplemental Figures 2 and 7).

Results

Sample characteristics and cognitive disorder cumulative incidence

A total of 353,657 patients aged 50 and older had a primary care visit during the study period. Of these, 160,052 were included in the final cohort of whom 4898 had cognitive disorder diagnosis more than 3 years after the first eligible visit (Supplemental Figure 3). The median (IQR) number of healthcare visits per patient was 7.0 (4.0–11.0). Sample characteristics are in Table 1. The median age at the first visit was 63 (IQR 56–71), 86,558 (54.1%) patients were women, and 49,724 (31.1%) were nonwhite. Significant demographic differences were observed between the blood pressure groups—“<120 mmHg”, “120–140 mmHg”, and “≥140 mmHg”—with higher SBP associated with older age and Black race (“≥140 mmHg” 28.6% versus “120–140 mmHg” 21.0% versus “<120 mmHg” 14.1%). Additionally, the incidence of cognitive disorder diagnoses was higher in the “≥140 mmHg” SBP group (5.5%) compared to the “120–140 mmHg” SBP (4.6%) and “<120 mmHg” (3.2%) groups. Cardiovascular comorbidities show a similar pattern, with higher percentages observed in the “≥140 mmHg” SBP group. The full distribution of average SBP during the follow-up period is in Supplemental Figure 4. Most patients had an average SBP between 120 and 140 mmHg with a distribution peak around 130 mmHg.

Table 1.

Participant characteristics.

Characteristics		Systolic blood pressure categories (mmHg)
Demographics	Overall	<120	120–140	≥140	p
N, (%)	160,052	38,213 (23.9)	84,241 (52.6)	37,598 (23.5)
N by Age Groups, (%)
50–60	58,014 (36.2)	17,748 (46.4)	30,196 (35.8)	10,070 (26.8)	<0.001
61–70	55,313 (34.6)	12,688 (33.2)	29,846 (35.4)	12,779 (34.0)
71–80	33,480 (20.9)	5814 (15.2)	17,730 (21.0)	9936 (26.4)
81–90	11,735 (7.3)	1746 (4.6)	5717 (6.8)	4272 (11.4)
>90	1510 (0.9)	217 (0.6)	752 (0.9)	541 (1.4)
Age, y, median (IQR)	63 (56–71)	60 (55–68)	63 (57–71)	66 (59–74)
Female, N (%)	86,558 (54.1)	22,260 (58.3)	44,037 (52.3)	20,261 (53.9)	<0.001
Race, N (%)
White	110,328 (68.9)	28,133 (73.6)	58,825 (69.8)	23,370 (62.2)	<0.001
Black
Asian and Pacific Islanders	7726 (4.8)	2313 (6.1)	3884 (4.6)	1529 (4.1)	<0.001
American Indian	443 (0.3)	96 (0.3)	261 (0.3)	86 (0.2)	0.383
Other	6369 (4.0)	1709 (4.5)	3264 (3.9)	1396 (3.7)	<0.001
Unknown	2105 (1.3)	575 (1.5)	1065 (1.3)	465 (1.2)	0.002
Hispanic ethnicity, N (%)	9570 (6.0)	199 (0.5)	4735 (5.6)	2206 (5.9)	<0.001
Comorbidities, N, (%)
Cognitive disorder	4898 (3.0)	1019 (2.7%)	2865 (3.4%)	1014 (2.7%)	<0.001
Hyperlipidemia	39,799 (24.9)	9721 (25.4)	21,630 (25.7)	8448 (22.5)	<0.001
Hypertension	34,620 (21.6)	5514 (14.4)	19,699 (23.4)	9407 (25.0)	<0.001
Diabetes	14,340 (9.0)	2719 (7.1)	7987 (9.5)	3634 (9.7)	<0.001
Ischemic heart disease	11,035 (6.9)	2507 (6.6)	5994 (7.1)	2534 (6.7)	<0.001
Chronic kidney disease	9249 (5.8)	1646 (4.3)	4947 (5.9)	2656 (7.1)	<0.001
Atrial fibrillation	6035 (3.8)	1463 (3.8)	3181 (3.8)	1391 (3.7)	0.643
Stroke/TIA	5257 (3.3)	1085 (2.8)	2759 (3.3)	1413 (3.8)	<0.001
HF/Non-IHD	5154 (3.2)	1183 (3.1)	2610 (3.1)	1361 (3.6)	<0.001
Follow-up, y, median (IQR)	8.1 (5.2–10.5)	8.2(5.3–10.6)	8.1(5.1–10.5)	7.9(5.0–10.2)	<0.001
Visits, N, median (IQR)^a	7 (4–11)	7 (4–11)	7 (5–12)	7 (4–11)	<0.001
Mortality	23,273 (14.5)	5196 (13.6)	11,653 (13.8)	6424 (17.1)	<0.001

HF: heart failure; IQR: interquartile range; N: numbers; Non-IHD: non-ischemic heart disease; TIA: transient ischemic attack; y: years.

Median number of visits per patient.

Table 2.

SBPV effects in the four age groups (50–59 years, 60–69 years, 70–79 years, 80+ years).

SBPV	50–59 age group HR (95%CI), p	60–69 age group HR (95%CI), p	70–79 age group HR (95%CI), p	80+ age group HR (95%CI), p
10 mmHg	0.76 (0.56–1.04), 0.09	0.76 (0.65–0.89), <0.05	0.96 (0.84–1.09), 0.48	0.90 (0.70–1.14), 0.38
15 mmHg	0.83 (0.61–1.14), 0.25	0.80 (0.68–0.94), <0.05	0.96 (0.86–1.06), 0.42	0.92 (0.78–1.10), 0.38
20 mmHg	0.89 (0.67–1.19), 0.44	0.84 (0.72–0.98), <0.05	0.96 (0.88–1.05), 0.41	0.95 (0.85–1.06), 0.39
25 mmHg	0.94 (0.76–1.18), 0.60	0.90 (0.80–1.01), 0.13	0.97 (0.91–1.04), 0.44	0.98 (0.92–1.04), 0.42
30 mmHg	0.99 (0.91–1.07), 0.74	0.96 (0.92–1.01), 0.18	0.99 (0.96–1.02), 0.49	0.99 (0.97–1.01), 0.54
35 mmHg	1.01 (0.95–1.07), 0.83	1.03 (0.99–1.06), 0.22	1.01 (0.98–1.04), 0.52	1.00 (0.99–1.02), 0.75
40 mmHg	1.01 (0.83–1.23), 0.91	1.10 (0.94–1.28), 0.25	1.04 (0.92–1.18), 0.55	1.00 (0.93–1.07), 0.97
45 mmHg	1.00 (0.75–1.33), 0.99	1.15 (0.90–1.47),0.29	1.07 (0.85–1.34), 0.56	0.99 (0.86–1.14), 0.90
50 mmHg	0.98 (0.72–1.32), 0.87	1.19 (0.86–1.64), 0.34	1.10 (0.79–1.52), 0.57	0.97 (0.77–1.22), 0.82
55 mmHg	0.94 (0.73–1.21), 0.63	1.18 (0.84–1.67), 0.48	1.12 (0.74–1.70), 0.58	0.95 (0.70–1.31), 0.77

Cumulative incidence curves for cognitive disorder diagnosis stratified by race (Black versus White, and overall), by average SBP in the first two years (“<120 mmHg” versus “120–140 mmHg” versus “≥140 mmHg”, and overall) as well as by hypertension history (Hypertension versus No Hypertension, overall, and risk difference) are in Figure 1. Cumulative incidence was significantly higher in Black versus non-Black patients (p < 0.001), and higher in those with an average SBP 120–140 mmHg (p = 0.68). Additionally, individuals with history of hypertension had a significantly higher cumulative incidence compared to those without history of hypertension (p < 0.001). Applying the Aalen-Johansen fitter as a sensitivity analysis did not substantively alter the cumulative incidence curves (Supplemental Figure 5).

Figure 1.

Cumulative incidence of cognitive disorder diagnosis. Kaplan-Meier estimates of cumulative incidence for cognitive disorders (dementia plus mild cognitive impairment [MCI]) stratified by average SBP during the first two years after the initial SBP measurement (<120 mmHg, 120–140 mmHg, ≥140 mmHg, and overall) (a), stratified by self-reported race (Black, non-Hispanic White, and overall) (b) and stratified by hypertension diagnosis (history of hypertension, no history of hypertension, risk difference, and overall) (c).

Association between SBP and cognitive disorder risk across age groups

In fully adjusted models stratified by age group, the association between SBP and cognitive disorders risk varied by age (Figure 2). Among individuals aged 50–59 (Figure 2(a)), elevated risk was observed at SBP <120 mmHg, although this association was not statistically significant (p > 0.05). Between 120 and 131 mmHg the risk decreases but remains nonsignificant (p > 0.05), whereas from 131–176 mmHg the risk gradually increases again without statistical significance (p > 0.05).

Figure 2.

The plots show the association of systolic blood pressure with cognitive disorders for the fully adjusted model for all covariates including hypertension (adjusted for gender, race, number of visits, blood pressure medications, atrial fibrillation, stroke, ischemic heart disease, chronic kidney disease, hypertension, hyperlipidemia, and heart failure) (model 3) at ages 50–59 years old (a), 60–69 years old (b), 70–79 years old (c), and 80 years and older (d). Shaded areas indicate 95% CIs. Hazard ratios were calculated with SBP 120 mmHg as a reference. In (b), the green shaded area represents the SBP range during which the association between SBO and decreased cognitive disorders is statistically significant (p < 0.05) and the green triangle signifies SBP 137 mmHg which is the lowest SBP at which this association becomes statistically significant (p < 0.05).

In the 60–69 age group (Figure 2(b)), SBP <115 mmHg was associated with a decreased but non-significant risk (p > 0.05). Notably, SBP 137 mmHg is the lowest SBP at which a significantly decreased risk for cognitive disorders was observed (HR, 0.89; 95% CI, 0.79–1.00; p < 0.05).

Among individuals aged 70–79 (Figure 2(c)), SBP <120 mmHg was associated with increased risk and SBP >120 mmHg with decreased risk. However, none of these associations reached statistical significance (p > 0.05).

In individuals aged 80 years and older, SBP <120 mmHg was associated with a decreased risk of cognitive disorders, although this did not reach statistical significance (p > 0.05). SBP levels between 135 and 155 mmHg were associated with a decreased risk, also not statistically significant (p > 0.05) (Figure 2(d)).

Association between SBP and cognitive disorder risk by antihypertensive medication status and initiation timing

Subgroup analysis of the fully adjusted model was conducted to examine whether associations between SBP and cognitive disorder diagnoses varied by antihypertensive prescription (Figure 3). A U-shaped pattern was observed in both groups. Among individuals not on medications, SBP of 139 mmHg was the lowest SBP at which a statistically significant association with decrease cognitive disorder risk was observed (HR, 0.92; 95% CI, 0.85–1.00; p < 0.05). For those on medications, no significant SBP threshold was identified in the overall group. However, when we further stratified the on medications subgroup into two groups of <75 and ≥75 years old, in participants aged ≥75 years, low SBP (100 mmHg) was associated with a significantly increased risk of cognitive disorder (HR, 2.66; 95% CI, 1.14–6.24; p < 0.05) (Figure 4). Furthermore, when classifying antihypertensive medication use based on timing relative to the two-year SBP follow-up period, we observed notable differences in cognitive disorder rates. Individuals on antihypertensive medication before the first eligible BP measurement, had a 79% lower cognitive disorder rate compared to those never treated (0.38% versus 1.76%, p < 0.001). Similarly, the individuals on antihypertensive medication during the 2-year SBP follow-up, had a 39% lower cognitive disorder rate (1.07% versus 1.76%, p < 0.001). On the other hand, individuals who started antihypertensives medications after the 2-year SBP follow-up had a 103% higher cognitive disorder rate (3.58% versus 1.76%, p < 0.001).

Figure 3.

Cognitive disorders risk by systolic blood pressure (SBP) and blood pressure medication use. Shaded areas indicate 95% CIs. The model was adjusted for gender, race, number of visits, blood pressure medications, history of heart failure, history of atrial fibrillation, history of ischemic heart disease, history of hypertension, history of stroke, history of diabetes, history of chronic kidney disease, and history of hyperlipidemia. SBP 120 mmHg was used as a reference.

Figure 4.

Association between systolic blood pressure (SBP) and cognitive disorder risk among individuals on blood pressure medication, stratified by age. Shaded areas indicate 95% CIs. The model was adjusted for gender, race, number of visits, blood pressure medications, history of heart failure, history of atrial fibrillation, history of ischemic heart disease, history of hypertension, history of stroke, history of diabetes, history of chronic kidney disease, and history of hyperlipidemia. SBP 120 mmHg was used as a reference.

Association between SBPV and cognitive disorder risk across age groups

As part of our secondary analysis, we stratified the fully adjusted model by age groups, using SBPV as an exposure in order to examine the association between SBPV and cognitive disorders risk varied by age (Supplemental Figure 6). Among individuals aged 50–59 years (Supplemental Figure 6(a)), no significant association between SBPV and cognitive disorder risk was observed. In the 60–69 age group (Supplemental Figure 6(b)), SBPV ≤ 23 mmHg was associated with statistically significant decreased cognitive disorder risk (p < 0.05). Risk increased progressively with higher variability, peaking at 52.2 mmHg (HR, 1.19; 95% CI, 0.85–1.68; p = 0.31). Among individuals aged 70–79 years (Supplemental Figure 6), higher SBPV showed a trend toward increased cognitive disorder risk, though confidence intervals were wide and associations did not reach statistical significance (p > 0.05). In individuals aged 80 years and older (Supplemental Figure 6(d)), no significant associations between SBPV and cognitive disorder risk were detected (p > 0.05).

In sensitivity analyses accounting for the competing risk of death, Fine-Gray competing risk models showed minimal associations (Supplemental Figure 7). To further examine the role of competing mortality, our descriptive competing risk analyses (Table 2) showed that in the age group 50–59 individuals with higher SBPV experienced death before cognitive disorders diagnosis at more than twice the rate compared with those with lower SBPV (2.18% versus 1.01%), while cognitive disorders rates were similar between those with higher and lower SBPV (0.80% versus 0.69%). Similarly, in the age group 60–69, the death rate was also higher in those with higher SBPV compared to the individuals with lower SBPV (2.98% versus 1.88%), with cognitive disorder rates being very similar (1.75% versus 1.77%). This effect was still present in the 70–79 age group (3.65% versus 2.92%) as well as in the 80+ age group (4.84% versus 3.84%).

Discussion

In analyzing EHRs of 160,052 patients, we compared cognitive disorder risk among patients with SBP measurements over a 2-year follow-up. After adjusting for demographics, number of visits, comorbidities, and antihypertensive medication use, we observed that the association between SBP and cognitive disorder risk varies by age and antihypertensive medication status. The cumulative incidence curves are higher in individuals with an average SBP 120–140 mmHg. This may occur since the higher SBP group ≥140 mmHg has the highest death rate (16.82%) before cognitive disorder developing which reduces their apparent cognitive disorder risk due to competing mortality. Furthermore, when using SBPV as our exposure a particularly strong association between SBPV and cognitive disorder risk was observed in the 60–69 age group, where lower SBPV was significantly associated with decreased cognitive disorders risk (p < 0.05), with risk increasing progressively at higher variability levels.

In the subgroup of individuals aged ≥75 years who were receiving antihypertensive medications, low SBP (100 mmHg) was associated with a significantly increased risk of cognitive disorder (HR, 2.66; 95% CI, 1.14–6.24; p < 0.05). SPRINT-MIND found that achieving a target SBP less than 120 mmHg reduced MCI risk, which aligns with our finding that SBP ≤120 mmHg was associated with decreased cognitive disorder risk.¹⁵ However, this finding also suggests that the lowest SBP stratum may represent a particular vulnerability in late life, showing the importance of avoiding overtreatment in this age group. Consistent with multiple prior studies,^37,38 our results suggest that excessively tight blood pressure control in older adults may be detrimental for cognitive outcomes. These findings further support the potential benefit of blood pressure control earlier in life. Despite statistical significance, the wide confidence interval, especially for low SBP (100 mmHg), suggests considerable uncertainty around the estimate. This likely reflects the relatively small sample size in this subgroup (n = 1048), highlighting the need for cautious interpretation and further validation in larger cohorts.

Medication timing appeared to be an important factor. Individuals who initiated antihypertensive treatment after the 2-year SBP follow-up period had a 103% higher rate of cognitive disorders compared to untreated individuals. By contrast, individuals on antihypertensive medications before the first eligible BP measurement had a 79% lower cognitive disorder rate compared to those never treated (0.38% versus 1.76%, p < 0.001), and those on treatment during the 2-year SBP follow-up had a 39% lower rate (1.07% versus 1.76%, p < 0.001). This pattern suggests protective effects of antihypertensive medications if started early but not if started late.

Our findings are consistent with prior studies demonstrating age- and medication-specific heterogeneity in the relationship between SBP and cognitive disorder risk. Findings showed that SBP ≥130 mmHg at age 50, but not at older ages (at age 60 or 70), was associated with increased dementia risk, supporting our observation that midlife SBP elevations are more predictive of cognitive decline than late-life measurements.³⁷ Similarly, another study reported a U-shaped association between SBP and Alzheimer's disease risk, particularly among older adults and those on antihypertensive therapy.³⁸

In contrast to prior studies, our results do not suggest that tight blood pressure control (SBP < 140) is associated with lower dementia risk, though, limitations of the study design prevent strong causal claims. In light of the risks associated with tight control for older patients, however, these results underscore the need for additional study to clarify age-specific treatment effects and risks of various blood pressure treatment regimens.

Several other observational and intervention studies have examined the association between blood pressure and incident cognitive disorder in older adults. The SPRINT-MIND trial found that intensive SBP lowering significantly reduced the risk of MCI across all age groups. Importantly, a secondary analysis demonstrated that these benefits extended to adults aged 80 and older highlighting the potential benefits of treatment even in the oldest age group.^15,39 The SPRINT-MIND trial provided important insights into the effects of intensive blood pressure control on cognitive outcomes. Additionally, imaging findings from the SPRINT-MIND MRI study showed that intensive SBP lowering was associated with reduced cerebral blood flow, particularly in the hippocampus, raising important considerations about potential cerebral effects of aggressive treatment.⁴⁰ Furthermore, emerging evidence suggests that BP variability, rather than average BP alone, may be a stronger predictor of cognitive decline.^16,41,42 However, using SBPV as our exposure for the older age groups especially, showed no significant association between SBPV and cognitive disorder risk. Individuals with higher SBPV experienced death before cognitive disorder diagnosis at higher rates compared to those with lower variability. This interpretation is further supported by the attenuated association observed in the Fine-Gray models, which account for death as competing risk, compared to standard Cox models (Supplemental Figure 7).

While the use of large-scale real world clinical data provides several advantages (sample size, heterogeneity, generality, etc.), it also comes with limitations. The study is observational, hence susceptible to residual confounding, and while the analysis adjusts for known confounders, unmeasured or unknown factors might affect the results. One crucial variable is confounding by indication: elevated blood pressure is associated with the prescription of antihypertensive medications. Additionally, biases may arise due to measurement errors and missing data common in EHRs. We relied on a single measure of cognitive disorder (ICD-10 codes), which may not capture the full scope of cognitive disorder or might be affected by underdiagnosis. Furthermore, we combined MCI and dementia and therefore, our findings should be interpreted as reflecting associations with overall cognitive impairment rather than specific cognitive syndromes. Future EHR-based studies with sufficient sample sizes and improved cognitive phenotyping would benefit from examining MCI and dementia as separate outcomes to better elucidate stage-specific BP effects and the optimal timing of BP interventions across the continuum of cognitive decline.

One key limitation is that the included patients do not represent an incident hypertension population, as we did not account for the timing of hypertension diagnosis or the duration of hypertension before study inclusion. Additionally, our analysis is limited by the absence of detailed adherence records to prescriptions, which prevents us from accurately capturing the cumulative duration of BP medication use. Future studies should incorporate such data to better examine the relationship between long-term medication exposure, SBP control, and cognitive outcomes. Furthermore, the variability in baseline SBP values in a primary care setting reflects heterogeneity in patient management and disease progression, and some low SBP readings may be attributed either to effective hypertension management, overtreatment, or early pathophysiological changes related to cognitive decline. Future research should further explore the optimal SBP target range in different subpopulations, considering medication use and individual risk factors.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251407126 - Supplemental material for Impact of long-term systolic blood pressure on cognitive disorder risk: Across different age groups and antihypertensive medication timing

Supplemental material, sj-docx-1-alz-10.1177_13872877251407126 for Impact of long-term systolic blood pressure on cognitive disorder risk: Across different age groups and antihypertensive medication timing by Konstantina Skolariki, Paul B. Rosenberg, Sevil Yasar, Esther S. Oh, Jeannie Leoutsakos, Constantine G. Lyketsos and Roy Adams in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

The authors have no acknowledgments to report.

ORCID iDs

Konstantina Skolariki

Paul B. Rosenberg

Sevil Yasar

Esther S. Oh

Jeannie Leoutsakos

Constantine G. Lyketsos

Roy Adams

Ethical considerations

This study received ethical approval from Johns Hopkins Institutional Review Board (approval IRB00269466) on January 07, 2021.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Author contribution(s)

Konstantina Skolariki: Conceptualization; Formal analysis; Methodology; Writing – original draft.

Paul B. Rosenberg: Conceptualization; Writing – review & editing.

Sevil Yasar: Conceptualization; Writing – review & editing.

Esther S. Oh: Conceptualization; Writing – review & editing.

Jeannie Leoutsakos: Conceptualization; Methodology; Writing – review & editing.

Roy Adams: Conceptualization; Methodology; Supervision; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Richman Family Precision Medicine Center of Excellence in Alzheimer's Disease including significant contributions from the Richman Family Foundation, the Rick Sharp Alzheimer's Foundation, the Sharp Family Foundation and others. This research was also supported by the Johns Hopkins Alzheimer's Disease Research Center (P30 AG066507) and authors KS and RA were supported by NIH grant K25AG083064.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The data are not available due to privacy or ethical restrictions.

Supplemental material

Supplemental material for this article is available online.

References

Livingston

Huntley

Liu

, et al. Dementia prevention, intervention, and care: 2024 report of the Lancet Standing Commission. Lancet 2024; 404: 572–628.

Ungvari

Toth

Tarantini

, et al. Hypertension-induced cognitive impairment: from pathophysiology to public health. Nat Rev Nephrol 2021; 17: 639–654.

Pacholko

Iadecola

. Hypertension, neurodegeneration, and cognitive decline. Hypertension 2024; 81: 991–1007.

De Anda-Duran

Woltz

Bell

, et al. Hypertension and cognitive function: a review of life-course factors and disparities. Curr Opin Cardiol 2022; 37: 326–333.

Levine

Springer

Brodtmann

. Blood pressure and vascular cognitive impairment. Stroke 2022; 53: 1104–1113.

Cheon

. Hypertension and cognitive dysfunction: a narrative review. J Yeungnam Med Sci 2023; 40: 225–232.

Jung

Yang

Kim

, et al. Associations of hypertension burden on subsequent dementia: a population-based cohort study. Sci Rep 2021; 11: 91923–91928.

Ryuno

Kamide

Gondo

, et al. Differences in the association between high blood pressure and cognitive functioning among the general Japanese population aged 70 and 80 years: the SONIC study. Hypertens Res 2016; 39: 557–563.

Canavan

O’Donnell

. Hypertension and cognitive impairment: a review of mechanisms and key concepts. Front Neurol 2022; 13: 821135.

10.

Williamson

Pajewski

Auchus

, et al. Effect of intensive vs standard blood pressure control on probable dementia. JAMA 2019; 321: 553–561.

11.

Sierra

. Hypertension and the risk of dementia. Front Cardiovasc Med 2020; 7: 5.

12.

Daugherty

. Hypertension-related risk for dementia: a summary review with future directions. Semin Cell Dev Biol 2023; 116: 82–89.

13.

Mielke

Leoutsakos

Corcoran

, et al. Effects of FDA-approved medications for Alzheimer’s disease on clinical progression. Alzheimers Dement 2012; 8: 180–187.

14.

Ghazi

Shen

Ying

, et al. Identifying patients for intensive blood pressure treatment based on cognitive benefit. JAMA Netw Open 2023; 6: e2314443.

15.

Wright

Jr Whelton

Reboussin

. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med 2016; 374: 2294.

16.

de Heus

RAA

Tzourio

Lee

EJL

, et al. Association between blood pressure variability with dementia and cognitive impairment: a systematic review and meta-analysis. Hypertension 2021; 78: 1478–1489.

17.

Zheng

Zhou

Fang

, et al. Long-term visit-to-visit blood pressure variability and cognitive decline among patients with hypertension: a pooled analysis of 3 national prospective cohorts. J Am Heart Assoc 2024; 13: e035504.

18.

Zhang

Liang

, et al. Age at diagnosis of atrial fibrillation and incident dementia. JAMA Netw Open 2023; 6: e2342744.

19.

Blanken

Nation

. Does gender influence the relationship between high blood pressure and dementia? J Alzheimers Dis 2020; 78: 23–48.

20.

Wright

DeRosa

Moon

, et al. Race/ethnic disparities in mild cognitive impairment and dementia: the Northern Manhattan Study. J Alzheimers Dis 2021; 80: 1129–1138.

21.

Oliver

Chae

Martz

. Racial differences in the relationship between blood pressure and cognitive decline. medRxiv 2024. DOI: 10.1101/2024.01.03.24300811 [Preprint]. Posted January 04, 2024.

22.

Centers for Medicare & Medicaid Services. Chronic condition data warehouse user manual, version 2.0. Des Moines, IA: CMS, 2007.

23.

Koh

Lew

LZW

Franke

, et al. Predictive role of atrial fibrillation in cognitive decline: a systematic review and meta-analysis of 2.8 million individuals. EP Europace 2022; 24: 1229–1239.

24.

van Nieuwkerk

Delewi

Wolters

, et al. Cognitive impairment in patients with cardiac disease: implications for clinical practice. Stroke 2023; 54: 2181–2191.

25.

Wolters

Segufa

Darweesh

SKL

, et al. Coronary heart disease, heart failure, and the risk of dementia: a systematic review and meta-analysis. Alzheimers Dement 2018; 14: 1493–1504.

26.

Rauseo

Salih

Raisi-Estabragh

, et al. Ischemic heart disease and vascular risk factors are associated with accelerated brain aging. JACC Cardiovasc Imaging 2023; 16: 905–915.

27.

El Husseini

Katzan

Rost

, et al. Cognitive impairment after ischemic and hemorrhagic stroke: a scientific statement from the American Heart Association/American Stroke Association. Stroke 2023; 54: e272–e291.

28.

Oestreich

Wright

O’Sullivan

. Cardiovascular risk factors are associated with cognitive trajectory in the first year after stroke. Cereb Circ Cogn Behav 2024; 7: 100230.

29.

Kuźma

Lourida

Moore

, et al. Stroke and dementia risk: a systematic review and meta-analysis. Alzheimers Dement 2018; 14: 1416–1426.

30.

Corraini

Henderson

Ording

, et al. Long-term risk of dementia among survivors of ischemic or hemorrhagic stroke. Stroke 2017; 48: 180–186.

31.

Dove

Shang

, et al. The impact of diabetes on cognitive impairment and its progression to dementia. Alzheimers Dement 2021; 17: 1769–1778.

32.

Zilliox

Chadrasekaran

Kwan

, et al. Diabetes and cognitive impairment. Curr Diab Rep 2016; 16: 87.

33.

Yang

Stanford

Jiang

. Low cholesterol level linked to reduced semantic fluency performance and reduced gray matter volume in the medial temporal lobe. Front Aging Neurosci 2020; 12: 57.

34.

Babroudi

Tighiouart

Schrauben

, et al. Blood pressure, incident cognitive impairment, and severity of CKD: findings from the Chronic Renal Insufficiency Cohort (CRIC) study. Am J Kidney Dis 2023; 82: 443–453.e1.

35.

Kelly

Rothwell

. Disentangling the relationship between chronic kidney disease and cognitive disorders. Front Neurol 2022; 13: 830064.

36.

Amjad

Roth

Sheehan

, et al. Underdiagnosis of dementia: an observational study of patterns in diagnosis and awareness in US older adults. J Gen Intern Med 2018; 33: 1131–1138.

37.

Abell

Kivimäki

Dugravot

, et al. Association between systolic blood pressure and dementia in the whitehall II cohort study: role of age, duration, and threshold used to define hypertension. Eur Heart J 2018; 39: 3119–3125.

38.

Lee

Han

, et al. Blood pressure levels and risks of dementia: a nationwide study of 4.5 million people. Hypertension 2022; 79: 218–229.

39.

Pajewski

Berlowitz

Bress

, et al. Intensive vs standard blood pressure control in adults 80 years or older: a secondary analysis of the SPRINT trial. J Am Geriatr Soc 2020; 68: 496–504.

40.

SPRINT MIND Investigators for the SPRINT Research Group; Nasrallah

Pajewski

Auchus

, et al. Association of intensive vs standard blood pressure control with cerebral white matter lesions. JAMA 2019; 322: 524–534.

41.

Oishi

Ohara

Sakata

, et al. Day-to-day blood pressure variability and risk of dementia in a general Japanese elderly population: the Hisayama Study. Circulation 2017; 136: 516–525.

42.

Blacker

Viswanathan

, et al. Visit-to-visit blood pressure variability, neuropathology, and cognitive decline. Neurology 2021; 96: e2812–e2823.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

5.24 MB