Short Sleep Duration and Hypertension: A Double Hit for the Brain
Journal of the American Heart Association
Abstract
Background
Short sleep duration has been associated with an increased risk of cognitive impairment and dementia. Short sleep is associated with elevated blood pressure, yet the combined insult of short sleep and hypertension on brain health remains unclear. We assessed whether the association of sleep duration with cognition and vascular brain injury was moderated by hypertensive status.
Methods and Results
A total of 682 dementia‐free participants (mean age, 62±9 years; 53% women) from the Framingham Heart Study completed assessments of cognition, office blood pressure, and self‐reported habitual and polysomnography‐derived sleep duration; 637 underwent brain magnetic resonance imaging. Linear regressions were performed to assess effect modification by hypertensive status on total sleep time (coded in hours) and cognitive and magnetic resonance imaging outcomes. There was a significant interaction between sleep duration and hypertensive status when predicting executive function/processing speed (Trail Making B‐A) and white matter hyperintensities. When results were stratified by hypertensive status, longer sleep duration was associated with better executive functioning/processing speed scores in the hypertensive group (meaning that shorter sleep duration was associated with poorer executive function/processing speed scores) (self‐report sleep: β=0.041 [95% CI, 0.012–0.069], P=0.005; polysomnography sleep: β=0.045 [95% CI, 0.002–0.087], P=0.038), but no association was observed for the normotensive group. Similarly, shorter subjective sleep duration was associated with higher white matter hyperintensity burden in the hypertensive group (β=−0.115 [95% CI, −0.227 to −0.004], P=0.042), but not in the normotensive group.
Conclusions
In individuals with hypertension, shorter sleep duration was associated with worse cognitive performance and greater brain injury.
Nonstandard Abbreviations and Acronyms
- APOEε4
- apolipoprotein E epsilon 4
- FHS
- Framingham Heart Study
- N1
- stage 1 nonrapid eye movement
- N2
- stage 2 nonrapid eye movement
- N3
- stage 3 nonrapid eye movement
- STRIVE
- Standards for Reporting Vascular Changes on Neuroimaging
- WMH
- white matter hyperintensity
Clinical Perspective
What Is New?
•
Inadequate sleep has been linked to hypertension and dementia, and though the underlying mechanisms remain unclear, it is possible that short sleep and hypertension interact to increase the risk of cognitive impairment and vascular brain injury.
•
We used data from 682 Framingham Heart Study participants to determine whether the combined effect of hypertension and short sleep duration had a negative impact on brain health.
•
We show that in people with hypertension, shorter sleep duration was associated with poorer executive functioning, increased white matter hyperintensities, and gray matter atrophy on brain magnetic resonance imaging; these same associations were not observed in people with normotension.
What Are the Clinical implications?
•
Individuals with both hypertension and short sleep duration may represent a high‐risk group for cognitive impairment and vascular brain injury.
•
Screening individuals with hypertension for insufficient sleep may allow tailored therapies to improve brain aging and reduce brain injury.
•
These individuals could be targeted for new randomized controlled trials to determine the efficacy of sleep treatments and blood pressure–lowering therapies in preventing or delaying cognitive impairment.
Insufficient sleep is emerging as a major health problem, with up to half of US adults getting less than the recommended 7 hours of sleep per night.1 These sleep deficits may have a detrimental impact on the brain, as sleep that is too short or too long in duration is associated with cognitive decline2 and increased risk of incident dementia.3, 4 As sleep improvement represents a potential intervention target to reduce dementia risk, understanding the underlying mechanisms early in the pathological disease process remains a high priority.
Sleep dysfunction is thought to impair glymphatic clearance of neurotoxic proteins involved in the pathogenesis of Alzheimer disease.2, 5, 6 Although, poor sleep may directly impair Aβ clearance, insufficient sleep may also contribute to dementia via other shared risk factors. One plausible candidate is hypertension, with a large body of evidence showing its association with short sleep duration.7
Hypertension in midlife is an established risk factor for late‐life cognitive impairment and dementia.8, 9, 10 Attention and executive function appear to be particularly sensitive to decline in the presence of hypertension. This may be because hypertension is associated with diffuse cerebral small vessel disease, including white matter hyperintensities (WMHs), cerebral infarction, and demylination or microinfarction in the cerebral white matter.11 Furthermore, cerebrovascular burden to subcortical regions is thought to interrupt fronto‐subcortical circuits involved in executive function.12 Cohort studies consistently show that short sleep duration is associated with an increased risk of hypertension7, 13 and cardiovascular disease,14 including stroke.15 This is unsurprising, as sleep exerts a powerful influence over blood pressure (BP) and its control. Upon sleep onset, BP reduces by ≈10% compared with wake and insufficient sleep can abolish or reverse this normal “blood pressure dipping” profile, leading to nocturnal (masked) hypertension. When comorbid with hypertension, short sleep is a strong predictor of cardiovascular events.16 Yet, this double hit (hypertension+poor sleep) has not been fully explored in regard to cognition and neural injury.
In this study, we assessed the moderating effects of hypertension on the association between: (1) sleep duration and cognition and (2) sleep duration and magnetic resonance imaging (MRI) markers of accelerated brain aging and injury, using both subjective and objective measures of sleep in a community‐based sample from the FHS (Framingham Heart Study).
We hypothesized that shorter sleep durations would be associated with poorer executive functioning and evidence of white matter injury and that this association would be strongest in people with hypertension.
METHODS
Data Availability
FHS makes phenotypic and genetic data available through the online repositories BioLINCC and dbGap, respectively. Sleep data are available via the National Sleep Research Resource.
Sample Selection in FHS
FHS is a large multigenerational cohort study. The Original cohort was established in 1948. In 1971, a second‐generation (Offspring) cohort of 5124 men and women were enrolled, consisting of the offspring of the Original cohort and spouses of those offspring. The Offspring cohort continue to be followed with regular examination cycles, approximately every 4 years. In 1994, the FHS Omni 1 cohort enrolled 507 men and women of Black, Hispanic, Asian, Indian, Pacific Islander, and Native American origins. The Omni 1 cohort was examined alongside the Offspring cohort. Between 1995 and 1998 (proximal to examination cycle 6), a subset of the FHS Offspring and Omni 1 cohorts underwent sleep questionnaires and home‐based polysomnography as part of the Sleep Heart Health Study.17 Following sleep assessment, participants underwent cognitive testing and brain MRI between 1999 and 2002 (proximal to examination cycle 7).
There were 760 participants who underwent both sleep and cognitive assessments. We excluded people younger than 40 years (n=10), those with prevalent neurological diseases including dementia or stroke (n=37), those with unreliable polysomnography sleep data for scoring (n=29), and those without BP data (n=2). Prevalent neurological disease at baseline was captured by rigorous and uninterrupted surveillance as previously described.18 Following exclusion, 682 participants were included in the analysis sample, with cognition as the outcome. Of these participants, 635 had brain MRI. Written informed consent was provided by all participants before the commencement of the study. The study was approved by the institutional review board at Boston University Medical Center and Monash University's human research ethics committee. One author (J.H.) attests to having full access to the data and takes full responsibility for its integrity and the data analysis.
Sleep Assessment
Sleep duration was assessed subjectively, where participants were asked “On average, how long do you sleep for?” For objective measures of sleep, detailed methods have been previously described.17 Briefly, home‐based polysomnography was performed using the Compumedics P Series System with electroencephalogram (C3A2 and C4A1), electrooculogram, chin electromyogram, thoracic and abdominal displacement (inductive plethysmography bands), airflow (nasal‐oral thermocouples), finger pulse oximeter, a single bipolar ECG, body position by an Hg gauge sensor, and ambient light level were all recorded. Overnight polysomnography studies were analyzed by trained sleep technicians and overseen by a centralized Sleep Reading Center, with a high level of quality control for sleep scoring.3, 19 Sleep was scored in 30‐second epochs using Rechtshaffen and Kales and the American Academy of Sleep Medicine arousal criteria. The primary variables of interest were measures of subjective and objective sleep duration. Moreover, we also investigated stage 1 nonrapid eye movement (N1) duration (minutes, %), stage 2 nonrapid eye movement (N2) duration (minutes, %), stage 3 nonrapid eye movement (N3) duration (minutes, %), rapid eye movement (REM) duration (minutes, %), and the obstructive apnea hypopnea index (defined as number of obstructive apneas and hypopneas with >30% flow reduction and ≥4% oxygen desaturation per hour of sleep) as a measure of obstructive sleep apnea.
BP Measurement
At the time of sleep assessment, all participants completed standard sphygmomanometry. Three seated arm‐cuff measures were recorded with a 5‐minute rest period before the first measurement, and with a 30‐second rest between each measure. Antihypertensive medication usage was recorded at the time of BP measurement. Participants were categorized as having hypertension if their systolic BP was ≥140 mm Hg or diastolic BP was ≥90 mm Hg or they were prescribed hypertensive medication.
Cognitive Tests
Participants completed a neuropsychological test battery administered by trained research assistants and neuropsychologists as previously described.20 Cognitive testing was performed an average of 3.3 years following the polysomnography and subjective sleep assessment. The neuropsychological tasks included the Trail Making Test A and B (measuring processing speed and executive functions), Logical Memory (measuring immediate and delayed recall [verbal memory]), Visual Reproductions (measuring immediate and delayed recall [visual memory]), and similarities (measuring executive functions). Individual cognitive test scores were used as outcomes. For Trail Making Tests A and B, we used time to complete B minus A as the outcome, and scores were transformed such that higher scores indicated better performance. In this fashion, higher scores on all tasks indicated better performance. In addition to analyzing each cognitive test separately, we assessed global cognition by creating a global cognitive score created with principal component analysis forcing a single component solution.21 The global cognitive score was the weighted sum of standardized scores, where higher scores represent better performance.
MRI Assessments
MRI assessments were performed an average of 3.3 years following the polysomnography and subjective sleep assessment. Brain MRI outcomes included total brain volume, subcortical gray matter volume, hippocampal volume, WMH volume, and silent infarcts. The MRI protocols have been previously published.22 In brief, we used a Siemens 1‐Tesla or 1.5‐Tesla field strength machine with a T2‐weighted double spin‐echo coronal imaging sequence in contiguous slices of 4 mm. Brain volumes and WMHs are expressed as a percentage of intracranial volume to account for differences in head size. Using automated or semiautomated algorithms, total brain volume, subcortical gray matter volume, and hippocampal brain volume, which are both susceptible to early neurodegeneration in Alzheimer dementia,23 were assessed. WMHs were analyzed via in‐house software with quantitative or semiquantitative scales. Data for WHMs were skewed and therefore log transformed. Silent brain infarcts, also indicative of cerebral small vessel disease, were assessed using STRIVE (Standards for Reporting Vascular Changes on Neuroimaging) criteria.24 Infarcts were defined categorically, based on their presence or absence.
Statistical Analysis
Statistical analyses were conducted using SAS software version 9.4 (SAS Institute Inc). Continuous variables are presented as mean±SD for normally distributed data and median (quartile 1, quartile 3) for nonparametric data. Categorical variables are expressed as percentages.
The associations between sleep duration (continuous), cognitive outcomes, and each MRI marker were assessed using a series of linear or logistic (for categorical outcomes) regressions. To test for interactions and address potential confounding and bias, 3 models were created. Model 1 adjusted for the following confounders: age (years), age squared (years squared) to account for the known nonlinear association between age and cognition, sex (male versus female), race (Black, White, Hispanic, other), time interval between polysomnography and cognitive testing/MRI (years), and education in models with a cognitive outcome (any college education versus no college education). Model 2 adjusted for the same confounders as model 1 with the addition of apolipoprotein E epsilon (APOE e4) allele status (noncarrier versus carrier), use of sleeping pills at least once per week (yes versus no), body mass index (kg/m2), and diabetic status (yes versus no). Model 3 adjusted for the same confounders as models 1 and 2 with the addition of obstructive sleep apnea measured with the apnea hypopnea index (events per hour). Model 1 was used to assess effect modification by hypertension status (normotensive versus hypertensive) for each outcome, and, in the presence of a significant interaction, stratified results for hypertensive status were investigated as per the 3 models. The β estimate of the regression models indicate the degree of change in the dependent variable (eg, cognitive performance) per 1‐hour change in the independent variable (eg, sleep duration). A positive β estimate indicates that longer sleep duration is associated with better cognitive performance, while shorter sleep duration is associated with poorer cognitive performance. To normalize its distribution, Trails B‐A scores were natural log transformed. Results were considered significant if the P value was <0.05, except for interactions that were considered significant at P<0.1, since they are generally less powerful than main effects.25
Exploratory Analysis
It is possible that sleep duration and hypertension impact cognitive and MRI measures via changes in the composition of sleep architecture.26, 27 Accordingly, for those models yielding significant sleep duration×hypertension interactions, we performed an exploratory analysis, where the primary analyses were repeated for polysomnography‐derived sleep stages N1%, N2%, N3%, and REM% in place of sleep duration.
RESULTS
Demographics and Sample Characteristics
The characteristics of participants included in the analysis of cognitive outcomes are presented in Table 1 (characteristics of the subset with MRI are shown in Table S1). Of the 682 participants included, the mean age was 62 years (SD, 9 years) and 53% were women. The majority of the cohort was White (72%), 9% were Black, 9% were Hispanic, and 10% were of other races. More than half recorded any college education (66%), while one‐third (34%) reported no college education. Just over one‐third (35%) of the sample were classified as having hypertension, 9% had prevalent diabetes, and 7% had prevalent cardiovascular disease. Compared with the normotensive group, the hypertensive group were on average ≈5 years older, with less education (≈10% less college education), and had 13% higher prevalence of self‐reported diabetes.
Sample with cognitive outcomes | |||
---|---|---|---|
Normotensive | Hypertensive | Overall | |
No. (%) | 445 (65.2) | 237 (34.8) | 682 |
Age, y | 59.57±8.55 | 65.39±8.25 | 61.59±8.88 |
Women, n (%) | 246 (55.3) | 117 (49.4) | 363 (53.2) |
Self‐reported race, n (%) | |||
White | 318 (71.5) | 173 (73.0) | 491 (72.0) |
Black | 43 (9.7) | 21 (8.9) | 64 (9.4) |
Hispanic | 50 (11.2) | 11 (4.6) | 61 (8.9) |
Other | 34 (7.6) | 32 (13.5) | 66 (9.7) |
Education, n (%) | |||
College education (>12 y) | 309 (69.4) | 143 (60.3) | 452 (66.3) |
No college education (<12 y) | 136 (30.6) | 94 (39.7) | 230 (33.7) |
Time interval between polysomnography and assessment, y | −3.33 (1.21) | −3.12 (1.08) | −3.26 (1.17) |
Systolic BP, mm Hg | 117±11 | 139±17 | 125±17 |
Diastolic BP, mm Hg | 72±8 | 79±11 | 75±9 |
Treatment for hypertension, n (%) | NA | 156 (65.8) | 156 (22.9) |
Prevalent diabetes, n (%) | 20 (4.5) | 41 (17.6) | 61 (9.0) |
History of CVD, n (%) | 14 (3.1) | 33 (13.9) | 47 (6.9) |
Current smoking, n (%) | 66 (14.8) | 25 (10.5) | 91 (13.3) |
Body mass index, kg/m2 | 26.8 [24.0–30.2] | 28.3 [25.4–32.2] | 27.3 [24.7–30.7] |
Regular use of sleeping pills, n (%) | 71 (16.2) | 49 (21.1) | 120 (17.9) |
Depression, n (%)* | 38 (11.3) | 28 (14.4) | 66 (12.5) |
Positivity for an APOE ε4 allele, n (%) | 89 (20.6) | 56 (23.9) | 145 (21.8) |
Cognitive outcomes | |||
Global cognition (weighted score units) | −0.09±1.03 | −0.40±0.96 | −0.20±1.01 |
Trail Making B‐A (completion time, min) | 0.72, [0.50–1.08] | 0.77, [0.53–1.25] | 0.73, [0.50–1.10] |
Similarities (total correct score), | 16.06±4.03 | 15.72±3.87 | 15.94±3.97 |
Visual Reproductions delayed recall (total correct score) | 8.25±3.34 | 7.11±3.35 | 7.85±3.38 |
Logical Memory delayed recall (total correct score) | 10.15±3.38 | 9.73±3.53 | 10.00±3.43 |
Values are mean±SD, median [quartile 1, quartile 3] for nonnormally distributed variables, or number (percentage). APOE ε4 indicates apolipoprotein E epsilon 4; BP, blood pressure; and CVD, cardiovascular disease.
*
Depression was defined as a Center for Epidemiologic Study Depression score ≥16.
Sleep Measures
Sleep characteristics of the sample are presented in Table 2. The mean self‐reported sleep duration was 6.95±1.15 hours per night, with 32% reporting a short sleep duration of ≤6 hours per night. For polysomnography‐derived objective measures, mean sleep duration was 6.25±0.95 hours per night and about one‐third (38%) experienced a short sleep duration ≤6 hours per night. Moderate–severe obstructive sleep apnea (apnea hypopnea index ≥15) was identified in 16% of individuals, and almost one‐quarter of the overall sample reported using sleeping pills regularly.
Sleep exposure | Cognitive cohort | MRI cohort |
---|---|---|
N1% | 4.90±3.33 | 4.88±3.32 |
N2% | 55.80±10.82 | 55.81±10.85 |
N3% | 18.47±10.57 | 18.44±10.60 |
NREM% | 79.17±5.78 | 79.13±5.78 |
REM% | 20.83±5.78 | 20.87±5.78 |
Sleep maintenance efficiency, % | 85.03±9.48 | 85.11±9.43 |
Wake after sleep onset, min | 53.55±40.61 | 53.27±40.49 |
AHI, events per h | 8.15±11.88 | 8.20±12.13 |
AHI categories mild to severe: AHI ≥5 per h but <15 per h; moderate to severe: AHI ≥15 per h, n (%): | 278 (43.7) 103 (16.2) | 260 (43.9) 96 (16.2) |
No. of wakenings | 3.73±1.58 | 3.73±1.60 |
Arousal index | 18.02±9.55 | 18.13±9.78 |
Objective total sleep time, h | 6.25±0.95 | 6.25±0.95 |
Objective total sleep time, n (%), h | ||
≤6 | 193 (37.6) | 180 (37.6) |
>6 | 321 (62.5) | 299 (62.4) |
Subjective total sleep time, h | 6.95±1.15 | 6.93±1.12 |
Subjective total sleep time, n (%), h | ||
≤6 | 213 (32.0) | 202 (32.7) |
7–8 | 413 (62.1) | 384 (62.1) |
≥9 | 39 (5.9) | 32 (5.2) |
Values are mean±SD or number (percentage). AHI indicates apnea hypopnea index; MRI, magnetic resonance imaging; N1, stage 1 nonrapid eye movement; N2, stage 2 nonrapid eye movement; N3, stage 3 nonrapid eye movement; NREM, nonrapid eye movement; and REM, rapid eye movement. Wake after sleep onset was defined as the number of minutes spent awake between sleep onset and offset; sleep maintenance efficiency was expressed as the ratio of total sleep time to the sleep period (defined as the time between sleep onset and offset).
Sleep and Cognition: Main Effects and Interactions
There were no direct main effects between sleep duration, measured subjectively or objectively, and cognitive outcome (main effects presented in Table S2). The association between the sleep measures and cognition, stratified by hypertensive status, are presented in Figure 1. The association between subjective or objective sleep duration and executive function (Trails B‐A) was moderated by hypertensive status (Figure 1A and 1B). When results were stratified by hypertensive status, longer subjective and objective sleep durations were associated with better executive functioning in people with hypertension only (meaning that shorter sleep duration was associated with poorer executive functioning in this group) (self‐report sleep: β=0.041 [95% CI, 0.012–0.069], P=0.005; polysomnography sleep: β=0.045 [95% CI, 0.002–0.087], P=0.038), whereas there was no association observed in people without hypertension (Figure 1A and 1B) (self‐report sleep: β=−0.004 [95% CI, –0.020 to 0.011], P=0.600; polysomnography sleep: β=0.001 [95% CI, –0.021 to 0.022], P=0.948). These results remained significant following adjustments in models 2 and 3 (Table S3). No other statistically significant interactions were observed between sleep duration and hypertensive status for other cognitive outcomes.

Figure 1. The β estimates (95% CIs) for model 1 examining the association between subjective (top panel A) and objective (bottom panel B) sleep duration and cognitive outcomes stratified by hypertensive status (normotensive [blue] vs hypertensive [red] group).
Note that to normalize its distribution, Trails B‐A scores were log transformed, and, for ease of interpretation, raw Trails B‐A scores were reversed, such that higher scores were indicative of better performance. For Trails B‐A scores, β estimates (95% CIs) were multiplied by a factor of 10 for improved data visualization and for ease of interpretation. Model 1 was adjusted for age, age squared, sex, education, race, and time between polysomnography and magnetic resonance imaging assessments. Positive β estimates reflect the increase in cognitive test score per 1‐hour increase in sleep duration.
Sleep and Brain MRI Outcomes: Main Effects and Interactions
Few main effects were observed between sleep duration and MRI outcomes, except that shorter sleep duration was associated with higher total cortical gray matter volume% (main effects presented in Table S4). The association between sleep measures and MRI outcomes, with data stratified by hypertensive status, are presented in Figure 2. The associations between subjective sleep duration and WMH (Figure 2A) and objective sleep duration and subcortical gray matter volume (Figure 2B) were each moderated by hypertensive status. When data were stratified by hypertensive status, people with hypertension with longer subjective sleep duration had lower WMH (indicating that shorter sleep duration associated with higher WMH) (β=−0.115 [95% CI, −0.227 to −0.004], P=0.042), whereas no association was observed in people without hypertension (β=0.006 [95% CI, –0.078 to 0.089], P=0.894). In fully adjusted models (models 2 and 3; data presented in Table S5), people with hypertension with longer objective sleep duration had larger subcortical gray matter volume (indicating that shorter objective sleep duration associated with smaller subcortical gray matter volume in this group) (model 2: β=0.081 [95% CI, 0.018–0.143], P=0.012; model 3: β=0.084 [95% CI, 0.019–0.149], P=0.012). In contrast, the opposite (longer sleep duration associated with smaller gray matter volume) was found in people with normotension (model 1: β=−0.043 [95% CI, –0.077 to −0.009], P=0.013; model 2: β=−0.045 [95% CI, –0.080 to −0.010], P=0.012); however, this association was no longer significant following adjustment for apnea hypopnea index (model 3; Table S5). No other interactions were observed between sleep duration and hypertensive status for other MRI outcomes.

Figure 2. The β estimates (95% CIs) for model 1 examining the association subjective (top panel A) and objective (bottom panel B) sleep duration and magnetic resonance imaging (MRI) outcomes stratified by hypertensive status (normotensive [blue] vs hypertensive [red] group]).
A natural log transformation was applied to white matter hyperintensity volume. MRI metrics are expressed as a percentage of intracranial volume. Model 1 was adjusted for age, age squared, sex, race, and time between polysomnography and MRI assessments. Positive β estimates reflect the increase in MRI outcome per 1‐hour increase in sleep duration.
Exploratory Analysis
Based on the above findings, sleep stage × hypertension interactions were explored for the outcomes of executive functioning, WMH%, and subcortical gray matter volume% (interactions presented in Table S6). The association between N1% and executive functioning was moderated by hypertensive status (interaction term, P=0.043), with higher N1% associated with lower executive functioning in people with hypertension (β=−0.012 [95% CI, –0.021 to −0.002], P=0.014), but not in those without hypertension (β=−0.001 [95% CI, −0.007 to 0.004], P=0.634). In addition, the association between REM% and executive functioning was moderated by hypertensive status (interaction term, P=0.034), with higher REM% associated with better executive functioning in people with hypertension (β=0.016 [95% CI, 0.0003–0.012], P=0.040), but not in those without hypertension (β=0.0005 [95% CI, –0.004 to 0.003], P=0.761). There were no significant interactions for any of the other sleep stages and hypertension status on executive functioning, WMH%, or subcortical gray matter volume% (Table S6).
DISCUSSION
Overall, we showed that shorter sleep duration was associated with lower executive functioning and subcortical gray matter volume and higher WMHs, with these relationships only observed in people with hypertension. These effect sizes were similar following adjustment for APOE e4 status, cardiovascular disease risk factors, and obstructive sleep apnea. We also found that higher N1% was associated with poorer cognition in people with hypertension. These data suggest that the potential adverse consequences of short sleep duration are more strongly related to poorer brain health outcomes when accompanied by hypertension. Although causality remains unclear, the combination of short sleep and high BP may cause subclinical cerebrovascular injury that could lead to cognitive impairment.
Sleep, Hypertension, and Cognition
To date, associations between sleep and cognition have been mixed, with some studies showing associations with short28, 29, 30 or long31, 32, 33 sleep duration or no34, 35 association with poorer cognition. We show that hypertensive status moderates the relationship between sleep duration and cognition, which may partly explain previous inconsistent findings. Areas of the brain that are responsible for executive functioning, including frontal and subcortical regions, can be particularly susceptible to hypertensive injury.36 Insufficient sleep has also been associated with performance in executive function, with UK Biobank data of 479 420 adults aged 38 to 73 years showing that self‐reported sleep duration was associated with poorer executive functioning, following adjustment of hypertension and other comorbid vascular risk factors.37 Although cause and effect are unclear from this study, executive functioning may be particularly vulnerable to short sleep in people with hypertension. We showed that shorter sleep duration was associated with lower Trails B‐A scores in people with hypertension. Trails B‐A largely reflects the executive attention element of executive functioning (set shifting and cognitive flexibility, as well as visual search, attention, and processing speed). Of note, there was no interaction observed when predicting performance on the test of similarities. Although the similarities test does measure elements of executive functioning, it has much stronger verbal abstract reasoning and verbal comprehension components, showing that these processes were not associated with the effects of short sleep duration in those with hypertension.
Interestingly, we show that higher amounts of N1% and lower amounts of REM% in people with hypertension were associated with poorer executive functioning. Although glymphatic clearance is optimized in N3,5 we found no associations between cognition and this sleep stage. Interestingly, lower REM% has been associated with poorer executive functioning38 and increased dementia risk.39 Of note, REM sleep is important for memory consolidation, and reduced REM sleep is observed in those with short sleep duration.40 Higher levels of N1% generally reflects “lighter” sleep and poor sleep continuity and may be a driver of shorter sleep durations. Of note, higher N1% in people with hypertension in the FHS cohort has previously been associated with enlarged perivascular spaces, possibly suggesting a relationship between lighter sleep and impaired glymphatic clearance or cerebral small vascular disease.41 Taken together, individuals with both insufficient sleep and hypertension appear to represent a group with poorer cognition who may be at risk for accelerated cognitive decline.
Sleep, Hypertension, and Brain Structure
We complemented assessments of cognition with markers of accelerated brain aging and vascular injury on MRI. In people with hypertension, self‐reported short sleep duration was associated with higher levels of white matter injury, whereas objective short sleep duration was associated with lower volumes of subcortical gray matter. Previous data from other cohorts show that sleep duration <6 hours per night versus >6 to 8 hours is associated with smaller gray matter volumes and greater WMHs.37 Furthermore, in FHS, midlife hypertension is associated with the accelerated progression of WMH and worsening executive functioning.42 Accordingly, changes in executive function in those with short sleep duration and hypertension may be the result of vascular brain injury, as evidenced by white matter lesions or gray matter atrophy. Interestingly, WMH burden is associated with further gray matter atrophy,43 and white matter lesions strengthen the relationship between gray matter atrophy and executive dysfunction in populations with atherosclerotic disease.44 The associations identified in our study also seem to be attributable to overall sleep loss per se rather than changes in the composition of sleep architecture as, unlike our findings in cognitive outcomes, sleep stage associations were not modified by hypertensive status.
What Makes People With Short Sleep and Hypertension Vulnerable?
It is well established that hypertension can have a significant impact on cerebral vasculature.45 Owing to exposure of high pressure flow, hypertension increases the risk of small vessel disease, including WMHs, cerebral infarcts, cerebral microbleeds, and enlarged perivascular spaces.45 Hypertension has also been linked with blood–brain barrier dysfunction and accumulation of amyloid‐β.45 Taken together, these factors lead to gray matter atrophy and are known to be associated with cognitive decline and dementia.46, 47
Both short sleep and hypertension may contribute to poorer executive functioning and neuronal injury via independent (as discussed above) or interdependent contributions. That is, sleep restriction can abolish or reverse the normal sleep‐related BP dipping profile48 and over one‐third of people with hypertension exhibit a nondipping profile.49 In addition to vascular effects, elevated nocturnal BP is also thought to decrease glymphatic clearance via enlarged perivascular spaces50 and reduced efficiency of perivascular pumping.51, 52 Hypertension is largely detected via daytime measurement of office BP and, often, there is a lack of attention to diurnal BP variation. The composite of short sleep and hypertension may capture those individuals with undiagnosed nocturnal hypertension. Importantly, current antihypertensive treatment regimens are not tailored to counteract these nocturnal elevations in BP.53 Therefore, those with short sleep duration and hypertension may represent a group exposed to high pressure flow throughout the 24‐hour period, putting individuals at particularly high risk for white matter injury, gray matter atrophy, and poorer executive functioning.
Limitations
This study is not without limitations. Although we utilized objective sleep measures, the home‐based polysomnography was performed over a single night and may not be representative of chronic sleep durations. However, this study also found associations with self‐reported durations, which possibly capture longer‐term sleep patterns. BP assessment was also limited to office BP, which consists of 3 daytime measures of oscillometric BP. Future studies should consider the use of 24‐hour ambulatory BP monitoring to provide important insight into the effects of sleep duration on nocturnal BP and how this moderates the relationship with cognition and brain aging. As FHS is an observational study, we cannot determine whether the associations identified were causal in origin. Intervention trials investigating the effects of sleep extension protocols in those with hypertension on brain health outcomes may be able to address this issue. The FHS Offspring and Omni 1 cohorts included participants who were mostly of White and Black races; therefore, the generalizability of our findings is limited and should be replicated in more ethnically diverse populations. Finally, we acknowledge that we made multiple statistical comparisons and that our results could be subject to type I error. Accordingly, these findings will require replication in other samples.
CONCLUSIONS
Insufficient sleep represents a potential modifiable target for prevention of dementia, but who to target and why remains elusive. Screening individuals for insufficient sleep and hypertension may allow tailored therapies to improve brain aging and reduce brain injury. Accordingly, screening for nocturnal hypertension by use of 24‐hour BP assessment may prove to be helpful in this context. Both insufficient sleep and high BP are treatable with safe and affordable interventions. These high‐risk individuals represent a group that could be targeted for new randomized controlled trials to determine the efficacy of sleep treatments or BP‐lowering therapies in preventing or delaying cognitive impairment. The hypertensive group in this study included participants who were already being treated with antihypertensive therapy. This is not to say that hypertensive therapy would be ineffective in improving brain health. On the contrary, it may suggest that individuals with hypertension and short sleep duration could benefit from more tailored pharmacological intervention to normalize BP throughout the full 24 hours. Over half of individuals taking antihypertensives still experience nocturnal hypertension or a nondipping BP profile,54 even though their daytime BP remains within normal limits. Through more individualized and optimized treatment regimens, such as chronotherapy (scheduling treatment according to body rhythms), 24‐hour BP levels and profiles can be better controlled. Administrating antihypertensive medication in the evening versus the morning may have a greater therapeutic effect on normalization of the circadian BP profile toward a more dipping pattern.55 Future studies are needed to confirm whether this is the case, however. Furthermore, studies are also needed to determine whether the association between sleep duration and dementia incidence is moderated by hypertension. Importantly, findings from this study suggest that the combined management of sleep and hypertension may be beneficial in at‐risk individuals to improve cognitive health and brain aging.
Sources of Funding
This study and Dr Yiallourou are funded by the American Alzheimer's Association (AARG‐NTF‐22‐971 405). FHS and Dr Seshadri are funded by contracts from the National Institutes of Health (N01‐HC‐25195, HHSN268201500001I, 75N92019D00031) and grants from the National Institute on Aging (AG054076, AG049607, AG033090, NS017950). Dr Baril is funded by the Banting Fellowship Program (#454104). Dr DeCarli is supported by a grant from the National Institute of Aging (P30 AG010129). Dr Pase is funded by the National Health and Medical Research Council (GTN1158384, GTN2009264) and the Alzheimer's Association (AARG‐18‐591358). Drs Pase and Himali are also supported by a grant from the National Institute on Aging (AG062531). Drs Seshadri and Himali are partially supported by the South Texas Alzheimer's Disease Center (1P30AG066546‐01A1) and The Bill and Rebecca Reed Endowment for Precision Therapies and Palliative Care. Dr Himali is also supported by an endowment from the William Castella family as William Castella Distinguished University Chair for Alzheimer's Disease Research and Dr Seshadri by an endowment from the Barker Foundation as the Robert R Barker Distinguished University Professor of Neurology, Psychiatry and Cellular and Integrative Physiology. Drs Cavuoto and Pase are supported by a Dementia Australia Research Foundation award (Lucas' Papaw Remedies Project Grant). All granting agencies funding this work were either governmental or foundations.
Disclosures
None.
Acknowledgements
We thank the Framingham Heart Study participants for their commitment and dedication to the study.
Footnotes
This article was sent to Michelle H. Leppert, MD, MBA, Associate Editor, for review by expert referees, editorial decision, and final disposition.
Supplemental Material is available at Supplemental Material
For Sources of Funding and Disclosures, see page 10.
Supplemental Material
Tables S1–S6
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© 2024 The Author(s). Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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Received: 19 April 2024
Accepted: 12 September 2024
Published online: 25 October 2024
Published in print: 5 November 2024
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Funding Information
American Alzheimer’s Association: AARG‐NTF‐22‐971 405
National Institutes of Health: N01‐HC‐25195, HHSN268201500001I, 75N92019D00031
National Institute on Aging: AG054076, AG049607, AG033090, NS017950, P30 AG010129, AG062531
Banting Fellowship Program: 454104
National Health and Medical Research Council: GTN1158384, GTN2009264
Alzheimer’s Association: AARG‐18‐591358
South Texas Alzheimer’s Disease Center: 1P30AG066546‐01A1
The Bill and Rebecca Reed Endowment for Precision Therapies and Palliative Care
William Castella Distinguished University Chair for Alzheimer’s Disease Research
Barker Foundation
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