Impact of the mindfulness-based blood pressure reduction (MB-BP) program on cardiovascular health: A randomized clinical trial

Abstract

Background

Mindfulness-based interventions may improve cardiovascular health (CVH) by supporting behavioral change across multiple risk factors. This study evaluated the impact of Mindfulness-Based Blood Pressure Reduction (MB-BP), a mindfulness program targeting hypertension-related behaviors, on CVH using the American Heart Association’s Life’s Essential 8 framework.

Methods

This secondary analysis of parallel-group, phase 2 randomized clinical trial evaluated the effects of MB-BP on CVH in 201 participants with elevated office BP (≥120/80 mmHg). The MB-BP group (n=101) received an 8-week program focused on mindfulness training and education targeting diet, physical activity, medication adherence, alcohol use, and stress, whereas the control group (n=100) received enhanced usual care. CVH was assessed using available Life’s Essential 8 components: systolic blood pressure, body mass index (BMI), diet (DASH adherence), physical activity, smoking, and sleep duration. Generalized estimating equations evaluated intervention effects through six months.

Results

At six months follow-up, MB-BP participants significantly improved composite CVH scores compared to controls (standardized mean difference: 0.144; 95% CI: 0.023, 0.266). MB-BP influenced most CVH components in healthier directions at trend levels, with the strongest responses for physical activity (47.9 MET min/week; 95% CI: -16.5, 112.3), sleep (0.34 hours/night; 95% CI: -0.10, 0.78), systolic blood pressure (-4.95 mmHg; 95% CI: -10.34, 0.44) and DASH diet score (0.27, 95% CI: -0.15, 0.69).

Conclusions

MB-BP led to modest but clinically relevant improvements in CVH, driven by multiple Life’s Essential 8 components. These findings suggest that MB-BP may be an effective behavioral intervention to support CVH and reduce risk for cardiovascular disease.

ClinicalTrials.gov Preregistration Identifiers: NCT03256890, NCT03859076

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, responsible for an estimated 19.4 million deaths in 2021 [1]. In response, public health initiatives have expanded focus from treating CVD to promoting overall cardiovascular health (CVH), aiming to enhance quality of life and reduce long-term disease risk [2]. The American Heart Association defines CVH through eight core metrics: physical activity, diet, body mass index (BMI), smoking status, sleep, blood lipids, blood glucose, and blood pressure. They are collectively known as Life’s Essential 8 [3]. Of the top 20 risk factors contributing to years of life lost in the United States, 11 are directly related to components of CVH. In 2021, the four leading contributors were hypertension, smoking, hyperglycemia, and elevated BMI [4].

In recognition of the multifaceted drivers of CVH, the American Heart Association’s Presidential Advisory on Life’s Essential 8 emphasized the importance of psychological well-being and social determinants of health, identifying mindfulness as a promising influence on CVH [5]. Transdiagnostic interventions—those that address multiple coexisting conditions—offer a potentially efficient means of improving population-level CVH while reducing CVD risk [6,7]. One class of transdiagnostic interventions showing promise is mindfulness-based programs. Mindfulness has been described as comprising three key elements: (1) present-moment awareness of thoughts, emotions, and physical sensations; (2) the quality of that awareness, which includes non-judgment, curiosity, compassion, and discernment; and (3) remembering, such as remembering to bring one’s wisdom to the present moment and apply it skillfully [[8], [9], [10]].

From a public health perspective, mindfulness has the potential to enhance intrinsic motivation, improve engagement, and make health interventions more meaningful, which are factors shown to improve adherence and long-term outcomes [11,12]. Moreover, mindfulness may reduce stress and emotional reactivity that often accompany behavior change efforts, thereby lowering psychological barriers to sustained engagement [12]. These qualities make mindfulness a compelling tool not only for clinical outcomes but also for supporting long-term behavior change.

To conceptualize how mindfulness training might influence CVH, a theoretical framework was developed that emphasizes the cultivation of mindfulness skills and their application to behaviors and risk factors relevant to CVD prevention [12]. This framework is summarized in Fig. 1.

Fig. 1.

Theoretical framework for Mindfulness-Based Blood Pressure Reduction (MB-BP). MB-BP is theorized to enhance self-regulation processes (emotion regulation, attention control, and self-awareness), which influence key cardiovascular health components, including physical activity, diet, sleep, BMI, smoking, blood glucose, blood lipids, and blood pressure, ultimately improving overall cardiovascular health.

Emerging evidence suggests that mindfulness training may positively impact individual components of CVH, including dietary behavior, physical activity, blood pressure, weight management, and sleep quality [[13], [14], [15], [16]]. However, there is a paucity of research examining mindfulness interventions that target multiple CVH components simultaneously. To address this gap, the Mindfulness-Based Blood Pressure Reduction (MB-BP) program was developed to apply mindfulness skills to the behavioral and psychosocial drivers of hypertension, including Life’s Essential 8 components such as diet, physical activity, and weight regulation [17].

While an observational study involving 382 participants demonstrated a cross-sectional association between dispositional mindfulness and CVH [18], there remains limited randomized trial evidence evaluating the impact of mindfulness training on CVH outcomes. Therefore, the objective of this study was to evaluate the effects of MB-BP on overall CVH at 6-month follow-up using a randomized controlled trial design.

1. Methods

1.1. Study sample and design

The present study is a secondary analysis of the MB-BP Study, which was a parallel-group phase 2 randomized controlled trial conducted in the Providence, Rhode Island area. Participant recruitment and assessments took place from June 2017 to November 2020, using community advertisements and referrals from healthcare and public health providers [14]. The study was preregistered on ClinicalTrials.gov at the onset of participant recruitment (applied in July 2017, approved in August 2017) and prior to outcome assessment in participants. The primary pre-registered outcomes (systolic blood pressure, DASH diet adherence, interoceptive awareness) are reported elsewhere [13,14]. Data were not examined prior to registration. This study followed CONSORT guidelines for RCT reporting [19]. The MB-BP Study is described in detail elsewhere [13,14].

Participants included adults aged 18 years or older who had elevated blood pressure (SBP ≥120 mmHg or DBP ≥80 mmHg) [13]. The study excluded those who meditated more than once a week, did not speak English, had severe medical conditions that precluded regular class attendance, had substance use or eating disorder, had suicidal ideation, history of bipolar disorder, psychotic disorder, or self-injurious behavior. The Brown University institutional review board approved this study protocol on June 12, 2017 (protocol number 1,412,001,171). All participants provided written informed consent.

1.2. Blinding and randomization

Those participants who passed the screening and assessment performed at baseline were randomized in a 1:1 ratio either to participate in the MB-BP group or control group. Randomization was stratified by 2 potential determinants of blood pressure at follow-up: sex and BP status (i.e., SBP≥140 mmHg or DBP ≥90 mmHg vs other). Randomization took place one week before the start of the MB-BP program initiation, and participants were notified of group assignments within 24 hours of randomization [14]. One of the researchers blinded to the participant identity performed the randomization using Research Randomizer Version 4.0 software. The senior project manager communicated the group assignments to participants. Staff conducting follow-up activities were blinded to group allocation, with the exception of the events relatedness inquiries which were completed by a separate staff member.

1.3. Intervention descriptions and theoretical framework

MB-BP is based on, and time-matched to, the standardized Mindfulness-Based Stress Reduction (MBSR) program [17]. Both consist of a group orientation session, eight 2.5-hour weekly group sessions, and a 7.5-hour one-day group session (total of 10 sessions). Recommended home mindfulness practice was ≥45 min/day, 6 days/week. Adaptations to MBSR that were specific to MB-BP are described in supplementary material Table S1 and elsewhere [14,17]. Briefly, MB-BP builds a foundation of mindfulness skills (e.g., meditation, yoga, self-awareness, attention control, emotion regulation) through the MBSR curriculum, and then directs those skills towards participants’ adhering to behaviors that can lower BP, many that are components of Life’s Essential 8 (e.g., diet, PA, weight loss) alongside other blood pressure drivers such as stress reactivity, alcohol consumption, and antihypertensive medication adherence (Fig. 1) [14,17]. MB-BP was led by qualified MBSR instructors with prior expertise in CVD etiology, treatment, and prevention. They were further trained and certified to teach MB-BP. Classes were provided in-person for the first ten cohorts (n=173), while the final two cohorts (n=28) began in-person and shifted to online via Zoom because of the COVID pandemic. Classes were held in Providence RI, USA at Brown University or a health center in a low income, urban neighborhood. MB-BP participants also received a home BP device (Omron, Model PB786N), training in home BP monitoring [20], and if office BP was ≥140/90 mmHg, notification of primary care physicians about their BP results; those without a primary care physician were offered assistance finding a primary care physician within the constraints of their health insurance.

Participants assigned to the enhanced usual care control group received the same home BP device, training in home BP monitoring, physician notification if office BP was ≥140/90 mmHg, and option for referral to primary care as participants in the intervention group. They also received an American Heart Association brochure about high BP and how to treat it (product code 50–1731). Control group participants did not receive mindfulness training as part of the study.

1.4. Outcomes

The primary outcome was CVH assessed at baseline, three months, and six months using six components of the American Heart Association’s Life’s Essential 8: blood pressure, BMI, smoking status, sleep duration, physical activity, and dietary pattern. CVH was evaluated as a continuous composite score using standardized (z-scored) means for each component to take advantage of the continuous nature of the outcome variables, in order to enhance sensitivity and statistical power. Specifically, for each participant i, the z-score was computed as: Z_i = (X_i − X̄) / SD where X_i represents the observed value for participant i, X̄ denotes the sample mean of the variable, and SD denotes the sample standard deviation. This transformation centers the variable at a mean of 0 and scales it to a standard deviation of 1, thereby facilitating comparability across measures and interpretation of effect sizes in standard deviation units. Secondary analyses used another CVH scoring method developed by Lloyd-Jones et al [5] which assign 0–100 points per component based on categorical thresholds (e.g., BMI<25=100; 25.0–29.9=70; 30.0–34.9=30; 35.0–39.9=15; ≥40=0). Details on the points assigned for each component are described elsewhere [5], with BMI shown as an example of the points assigned for the BMI categories. Using this method, the overall CVH score is calculated as the mean of available components, yielding a score from 0 to 100, with higher scores indicating better CVH. This categorical scoring system uses broad categories that may not detect meaningful within-category changes (e.g., a 31-lb range within BMI 25.0–29.9 for someone who is 5′8″ tall), hence the analyses prioritized reporting CVH using standardized means. As the MB-BP study did not collect blood samples, glucose and lipid levels were not included; results should be interpreted with this limitation in mind. Methods for assessing each CVH component are detailed below.

Blood pressure assessment occurred in a dedicated room at the Brown University School of Public Health using a calibrated Omron HEM-705CPN automated blood pressure monitor. The mean of the second and third blood pressure readings at each assessment was used for analyses, following best practices [21].

BMI was determined based on weight and height measured with participants in light clothing without shoes, using a calibrated stadiometer (SECA, Hamburg, Germany) and weighing scale (SECA, Model 22,089, Hamburg, Germany).

Current cigarette smoking was assessed via self-report of number of cigarettes smoked per day.

Sleep duration (average hours of sleep per night during the past month) was assessed using the Pittsburgh Sleep Quality Index [22,23].

Physical activity during the prior week was measured using the International Physical Activity Questionnaire as total MET (metabolic equivalent of task)-minutes per week of physical activity [24].

Dietary Approaches to Stop Hypertension (DASH)-consistent diet was assessed using the Harvard 163-item 2007 Grid Food Frequency Questionnaire [25], and coding of DASH diet adherence using methods developed by Folsom et al [26].

Adverse Events systematic monitoring was undertaken with a particular view on clinically significant changes in anxiety and depression symptoms. Monthly online safety checks monitored serious adverse events and physical injuries. Any serious adverse events were recorded by the data safety monitoring plan, with reporting to the principal investigator and the chair of the data safety monitoring board.

1.5. Statistical analysis

We analyzed the effect of the MB-BP program compared with the control condition at both 3- and 6-months using generalized estimating equations (GEE) with an identity link and autoregressive covariance structure [27]. Unadjusted analyses were performed to avoid possible bias and imprecision associated with covariate adjustment, particularly when adjusting for baseline measures of the primary outcome [[28], [29], [30]]. Analyses adjusted for the strata used to randomize participants (i.e., sex and BP status) can increase statistical power [31]. Marginal means were reported as the estimate for each model. We present analyses adjusting for the randomization strata variables, while also providing unadjusted analyses. The general analytic plan was specified in the original study protocol (see Supplemental Study Protocol) [13].

All analyses were undertaken on an intention-to-treat basis. All available data for each subject were included regardless of whether the subject completed the MB-BP program or control condition, detailed elsewhere [14]. To account for missing data, multiple imputation was implemented using predicted mean matching of 14 baseline variables (e.g., mean SBP, mean DBP, 10-item Perceived Stress Scale score, Five-Facet Mindfulness Questionnaire score, International Physical Activity Questionnaire score, DASH diet score, body mass index, age, race and ethnicity, and sex), imputing missing variables separately for each group, described elsewhere [14,32]. Fifty imputations were generated, and GEE analysis was performed in each one.

All statistical analyses were conducted in SAS, version 9.4, except for multiple imputation that was carried out in R, version 4.2.2 using mice package [33].

2. Results

The study included 201 participants divided into a control group (n=100) and an MB-BP group (n=101). There were no substantial differences between MB-BP vs. control group in all baseline variables, detailed in Table 1. Participants included 58.8% female, 81.1% non-Hispanic White, with mean age 59.5 years, and mean CVH score of 68.8 according to the Lloyd-Jones et al method [5], which represents moderate levels of CVH.

Table 1.

Baseline characteristics of study sample by treatment group.

	Control Group (n=100)	MB-BP Group (n=101)
Age, years (mean, SD)	60.0 (12.3)	61.0 (12.2)
Sex (n, %)
Male	42 (42.0%)	41 (40.6%)
Female	58 (58.0%)	60 (59.4%)
Race/ethnicity (n, %)
Asian	2 (2.0%)	3 (3.0%)
Black/African American	2 (2.0%)	7 (6.9%)
Hispanic	5 (5.0%)	3 (3.0%)
Native American	0 (0.0%)	3 (3.0%)
White	83 (83.0%)	80 (79.2%)
All other races/ethnicities	5 (5.0%)	5 (5.0%)
Don't know/refused	3 (3.0%)	0 (0.0%)
Education (n, %)
High School	12 (12.2%)	10 (10.2%)
Associate degree	5 (5.1%)	3 (3.1%)
College (4 year)	28 (28.6%)	34 (33.7%)
Graduate School	43 (43.9%)	41 (41.8%)
Other, n (%)	10 (10.2%)	10 (10.2%)
Cardiovascular Health Components
Cardiovascular Health Score, mean (SD)	64.0 (10.2)	65.6 (10.2)
Physical Activity, MET minutes/week, median (IQR)	3321 (1603–6600)	3397 (1855–6637)
DASH Diet Score, mean (SD)	5.1 (1.5)	5.3 (1.3)
Body Mass Index, kg/m2, mean (SD)	29.5 (6.4)	29.9 (6.6)
Sleep, hours per night, median (IQR)	7.0 (6.0–8.0)	6.5 (6.0–7.0)
Systolic Blood Pressure, mmHg, mean (SD)	138.4 (13.7)	138.6 (12.7)
Diastolic Blood Pressure, mmHg, mean (SD)	82.6 (9.9)	81.9 (8.4)
Cigarette Smoking, (n, %)
No	39 (92.9%)	33 (94.3%)
Yes	3 (7.14%)	0 (0%)
Don't know/refused	0 (0%)	2 (5.7%)
Other Relevant Variables
Sedentary Activity, sitting minutes/week, median (IQR)	2220 (1560–3060)	1980 (1440–3000)
Daily Alcohol Use, drinks/day, median (IQR)	0.3 (0.1–1.0)	0.4 (0.1–1.0)
Antihypertensive Medication Use (n, %)	70 (70.1%)	64 (64.0%)
Mindfulness (FFMQ) score	133.4 (20.8)	132.9 (19.2)
Perceived Stress Scale (PSS-14) score	22.3 (8.6)	23.6 (9.0)

Of the 201 participants enrolled, 18 in the control group and 16 in the MB-BP group had no data collection at 6 months follow-up, resulting in an 82.6% follow-up rate. With the COVID pandemic affecting the 6-month follow-up in-person data collection for the last three cohorts, and CVH components not prioritized for data collection as they were not the preregistered primary outcomes (other than systolic blood pressure and diet), at least one CVH outcome variable was available at both baseline and the 6 month follow-up for 165 participants (82.1%; 81 MB-BP and 84 control); at least two CVH outcome variables were available at both baseline and the 6-month follow-up for 156 participants (77.6%; 78 MB-BP and 78 control). Four or more outcome variables were available for 131 participants (65.2%; 67 MB-BP and 64 control), and all six outcome variables were available for 109 participants (54.2%; 54 MB-BP and 55 control). Please see the CONSORT diagram in Fig. 2 for further details. Due to missing variables, findings prioritize reporting the multiple imputation results. Complete case analyses showed similar findings and are available in Supplemental Table S2.

Fig. 2.

CONSORT diagram. Note that multiple imputation analyses were prioritized which resulted in all participants (n=201) included in primary analyses.

Ninety-nine of the 101 participants assigned to MB-BP received the intervention, whereas all 100 assigned to the control group were provided the enhanced usual care components. Eighty-four of the 101 MB-BP participants (83.2%) attended at least 7 of the 10 MB-BP class sessions; the median number of classes attended was 9. The most common reason provided for discontinuing the intervention was because of health problems unrelated to the course (n=5); details are in Fig. 2. Loss-to-follow-up rates across the 2 groups were similar, with 17.8% (n=18) of MB-BP participants discontinuing the study versus 17.0% (n=17) of control group participants.

2.1. Primary outcome findings for CVH

Adjusted analyses demonstrated that participants randomized to MB-BP had 0.144 greater standardized mean (95% CI: 0.023, 0.266; Cohen’s d=0.164) CVH scores by 6 months follow-up compared to control (Fig. 3). Exploratory analyses utilizing the categorical version of the CVH score showed similar directions of effect, while also demonstrating an expected lower sensitivity of the CVH variables to the intervention due to the variables being categorical rather than continuous (Supplemental Table S3).

Fig. 3.

Impacts of MB-BP vs. control on cardiovascular health score. Error bars represent standard error of the mean.

2.2. Secondary outcome findings for CVH components

Analyses of individual CVH components are exploratory to inform what contributed to the findings on the primary outcome (CVH), and hence not adjusted for multiplicity. MB-BP influenced all CVH components in healthier directions at trend levels, with the exception of smoking which was close to null (0.05 cigarettes per day (95% CI: -0.05, 0.15) increase in MB-BP vs. control). Effects of MB-BP vs. control on CVH components were greatest for physical activity (47.9 MET min/week; 95% CI: -16.5, 112.3), sleep (0.34 hours/night; 95% CI: -0.10, 0.78), systolic blood pressure (-4.95 mmHg; 95% CI: -10.34, 0.44) and DASH diet score (0.27, 95% CI: -0.15, 0.69), as shown in Table 2. Unadjusted analyses showed similar findings (Table 2), as did complete case analyses (Supplemental Table S2). Effects of MB-BP vs. control on standardized means of all individual CVH variables are shown in Supplementary Table S4.

Table 2.

Regression analyses on effects of MB-BP vs. control on components of CVH.

Outcome Variable	Timepoint
	3 Months		6 Months
	Estimate (95% CI)	P	Estimate (95% CI)	P
Unadjusted
Physical Activity, MET min/wk	25.1 (-33.6, 83.9)	0.40	52.4 (-16.6, 121.3)	0.14
Cigarette Smoking, cigs/day	0.05 (-0.05, 0.14)	0.33	0.05 (-0.05, 0.15)	0.34
Sleep Duration, hr/night	0.14 (-0.15, 0.62)	0.23	0.33 (-0.04, 0.70)	0.080
Body Mass Index, kg/m2	0.09 (-0.80, 0.98)	0.84	-0.28 (-1.29, 0.73)	0.59
Systolic Blood Pressure, mmHg	-2.6 (-7.6, 2.4)	0.31	-4.83 (-10.17, 0.51)	0.077
DASH Diet, score	0.16 (-0.28, 0.60)	0.47	0.28 (-0.10, 0.66)	0.15
Adjusted
Physical Activity, MET min/wk	31.6 (-33.1, 96.4)	0.34	47.9 (-16.5, 112.3)	0.15
Cigarette Smoking, cigs/day	0.04 (-0.04, 0.13)	0.33	0.05 (-0.05, 0.15)	0.34
Sleep Duration, hr/night	0.25 (-0.08, 0.57)	0.13	0.34 (-0.10, 0.78)	0.13
Body Mass Index, kg/m2	0.09 (-0.80, 0.99)	0.84	-0.28 (-1.32, 0.75)	0.59
Systolic Blood Pressure, mmHg	-2.7 (-7.7, 2.2)	0.28	-4.95 (-10.34, 0.44)	0.072
DASH Diet, score	0.17 (-0.25, 0.59)	0.44	0.27 (-0.15, 0.69)	0.20

Outcome point estimates are continuous variables. Analyses were performed using multiple imputation. Adjusted analyses were controlled for baseline randomization strata (gender, baseline hypertension status).

2.3. Adverse events

Reliable Change Index analyses demonstrated, by 6-month follow-up, reliable deterioration in anxiety symptoms and depression symptoms in 3.7% and 6.2% of MB-BP group participants, respectively, and reliable improvements in 12.4% and 14.8% of MB-BP group participants, respectively (Supplemental Figure S1). There was evidence of lesser improvement and greater deterioration for anxiety and depression in the control group by 6-month follow-up (Supplemental Figure S1)

Eight serious adverse events were observed during the 6-month follow-up period, with four occurring in the control group and four in the MB-BP group (e.g., hospitalizations due to altitude sickness, sepsis, stroke, and gastrointestinal bleeding). Adverse events related to physical injuries (e.g., concussions, lacerations, broken bones) were equally distributed between the study groups (n=8 per group). No serious adverse events or physical injuries were determined to be related to study participation.

3. Discussion

This randomized controlled trial evaluated the impact of MB-BP on CVH and found significant improvements at 6 months follow-up among participants randomized to MB-BP compared to the control group. All CVH components showed positive trends, except smoking, which may be attributed to the small number of smokers (n=3) in the sample of 201 participants. These findings suggest that MB-BP is a promising intervention for CVH promotion.

3.1. Comparison to existing literature

While self-reported mindfulness levels were found to be associated with CVH in a cross-sectional observational study [34], to our knowledge, no other mindfulness interventions targeting CVH as a comprehensive measure of both health behaviors and health factors (e.g., BMI, blood pressure) have been published in the peer-reviewed literature. However, several studies have examined mindfulness effects on individual CVH components, as discussed below.

3.1.1. Blood pressure

This study demonstrated a 5 mmHg reduced systolic blood pressure, consistent with previous findings [13,35]. The effect was particularly evident in complete case analyses that did not adjust for baseline blood pressure stratification, likely in part because statistical adjustments for outcomes can reduce model precision and introduce bias when baseline levels are balanced between groups [[28], [29], [30]]. Prior research supports mindfulness and meditation training as a means to lower blood pressure [36]. The American Heart Association/American College of Cardiology's 2025 guidelines for managing hypertension in adults now recommend meditation and breath control as the most effective evidence-informed stress-reduction strategies for lowering blood pressure [37]. However, further long-term follow-up studies with ambulatory blood pressure monitoring and diverse populations are needed.

3.1.2. Physical activity

The modest trend-level improvement in physical activity (48 MET minutes per week; 95% CI: -17, 112) aligns with systematic reviews indicating that both dispositional mindfulness and mindfulness training support increased physical activity [38,39]. MB-BP has also demonstrated significant effects on lowering sedentary behavior, reported elsewhere [14,17]. Mindfulness may also enhance the affective experience of exercise, making physical activity more enjoyable [40]. Interventions appear to be most effective when specifically designed for physical activity and when they target psychological factors influencing exercise behavior [38].

3.1.3. Smoking

No significant effect on smoking cessation was observed, at least in part due to the small number of smokers (n=3) in the sample. Previous studies highlight mindfulness as a potential tool for smoking cessation, although findings remain mixed in systematic reviews [41,42].

3.1.4. Sleep duration

This study showed some trend-level evidence of improved sleep (20 min per night average improvement for MB-BP vs. control), although findings were not statistically significant (p = 0.13). Participants were not recruited based on low sleep duration, and baseline sleep levels (6.5–7.0 hours per night) were close to the recommended 7–9 hours per night for adults. Mindfulness-based interventions have shown effects in populations with inadequate sleep, such as those with insomnia [43]. Mindfulness training may also help regulate sleep quality and duration, promoting wakefulness for those who oversleep (e.g., due to depression) and relaxation for those with insufficient sleep, in part by redirecting attention away from repetitive negative wakeful thoughts [44].

3.1.5. Dietary patterns

This study found modest non-significant evidence of improved diet quality, including greater DASH diet adherence. Effects were larger (and statistically significant) in participants of this study that had poor baseline diet quality, as reported elsewhere [13,17]. While observational studies suggest that mindfulness is associated with healthier dietary patterns [45,46], few clinical trials have assessed its impact on dietary patterns. Systematic reviews about the effects of mindfulness training on dietary patterns report mixed results [39,47]. MB-BP may be particularly effective in supporting DASH diet adherence, as detailed in previous research [13,17].

3.1.6. Adiposity

Minimal effects were observed on BMI (0.28 kg/m² lowering by 6 months follow-up in MB-BP vs control; 95% CI: -1.32, 0.75), which aligns with research indicating small-to-moderate effects from MBIs on weight-related outcomes [48]. Since overweight/obesity or desire for weight loss were not an inclusion criterion, not all participants were seeking to lower adiposity. Additionally, among participants with overweight/obesity, not all prioritized weight loss, which may have limited intervention effects.

However, while BMI reductions in those who went through MB-BP have shown significant short-term effects, these effects have not persisted over the long term [13,17]. Given that BMI has a substantial impact on blood pressure and that over 70% of Americans are overweight/obese, contemporary iterations of MB-BP have incorporated additional mindfulness-based practices focused on weight management. These include exploring participants’ relationships with evidence-informed weight loss strategies, such as caloric restriction and GLP-1 inhibitor prescriptions.

3.2. Clinical implications

Clinical implications are described below, recognizing that while CVH as a whole had statistically significant findings (i.e., p<0.05 and 95% CI not encompassing the null), most individual CVH components were demonstrated at a trend level with the 95% Cis within the null. With the study being a secondary data analyses and not statistically powered to address all these CVH components, and participants not recruited with high levels of these components other than elevated blood pressure, we felt clinical interpretations of effect sizes were of service, recognizing that future adequately powered replication studies are needed for greater clarity on the significance of the individual CVH component findings. We are influenced by a 2019 article in the journal Nature, where over 800 scientists called for an end to the concept of “statistical significance.”[49] For example, they stated: Let’s be clear about what must stop: we should never conclude there is ‘no difference’ or ‘no association’ just because a P value is larger than a threshold such as 0.05, or equivalently, because a confidence interval includes zero. Neither should we conclude that two studies conflict because one had a statistically significant result and the other did not. These errors waste research efforts and misinform policy decisions [49]. We provide interpretation of the effect sizes through this lens, recognizing they are exploratory findings in need of adequately powered replication.

Findings from the MB-BP program demonstrated varying levels of clinical relevance across CVH outcomes. For systolic blood pressure, the observed reduction of 5 mmHg vs. control suggests a clinically meaningful effect. A systematic review and meta-analysis of 344,716 participants with elevated blood pressure in randomized controlled trials found that a 5 mmHg reduction in systolic blood pressure achieved through antihypertensive medication was associated with a 10% reduction in major cardiovascular events, such as myocardial infarction and stroke [50].

Similarly, the observed improvement in the DASH score of 0.27 units should be interpreted in the context that participants were not recruited based on CVH parameters other than blood pressure. Consequently, many participants had healthy diets, BMI, and physical activity levels at baseline. In a separate analysis of these data, restricting the sample to participants with initially unhealthy DASH diet scores revealed significant improvements, equivalent to increasing daily consumption by approximately one serving of fruits or vegetables [13].

Physical activity improved at trend level by 48 MET-minutes per week, roughly translating to an additional 24 min of moderate pace walking per week (moderate pace walking has an MET score of about 3 METs compared to a person at rest that has 1 MET). A systematic review and meta-analysis found that an increase of 675 MET-minutes per week was associated with a 23% reduction in CVD mortality, suggesting that the more modest increase of 48 MET-minutes/week observed here may translate to approximately a 1.6% reduction in CVD mortality risk [51].

The reduction in BMI of 0.28 kg/m² corresponds to an estimated 2-pound weight loss for an individual who is 5 feet 9 inches tall. A meta-analysis of over 900,000 participants found that among those with overweight or obesity, each 1 kg/m² increase in BMI was associated with a 6% increase in all-cause mortality and an 8% increase in vascular mortality. Thus, a 0.28 kg/m² reduction may represent approximately a 1–2% decrease in all-cause mortality risk and a 2–3% reduction in vascular mortality risk [52].

The increase in sleep duration of 0.34 hours corresponds to about 20 additional minutes of sleep per night. Given that the average baseline sleep duration in the study was 6.5 to 7.0 hours, which slightly below the recommended 7 to 9 hours to minimize CVD risk, this improvement is potentially meaningful [5,53].

Taken together, these modest improvements across multiple drivers of CVH and CVD risk suggest a potential cumulative impact on reducing CVD risk and enhancing overall well-being. Additional analyses from this dataset reported elsewhere have demonstrated significant improvements in other markers of cardiovascular and whole-person health, including reductions in sedentary behavior and depression symptoms [14,54].

4. Study limitations

This study includes several limitations. Firstly, the measure of CVH did not include glucose regulation or lipids, due to the study not collecting blood samples. Including these components in future studies would provide a more comprehensive understanding of how mindfulness training affects CVH [5]. Secondly, the limited diversity of the sample, with a predominantly non-Hispanic White and well-educated population, restricts generalizability, highlighting the need to include more diverse populations in future research using evidence-based strategies [[55], [56], [57]]. The program shows promise as a culturally adaptable approach to delivering blood pressure–specific health education, potentially more targeted than standard MBSR [14,57,58]. Current work by our team focuses on adapting and evaluating the program in more diverse populations, cultures, and languages – including Native American populations and those living with HIV/AIDS [59]. Thirdly, the 6-month follow-up period is too short to assess the long-term sustainability of the program’s effects, necessitating longer-term studies to evaluate whether improvements in CVH persist over time. However, in a prior clinical trial of MB-BP, effects on systolic blood pressure were shown to hold through at least 2 years follow-up [35]. Fourthly, the COVID pandemic influenced the MB-BP delivery and data collection for 28 participants. In underpowered sensitivity analyses evaluating data obtained in participants who either (1) received in-person MB-BP before the COVID-19 pandemic (n=173) or (2) received hybrid in-person/online MB-BP during the COVID-19 pandemic (n=28), findings demonstrated effect sizes of CVH components that could be assessed during the pandemic such as physical activity and DASH diet score, that were in the same directions for both subsamples at 6-month follow-up, reported elsewhere [14]. Current delivery systems for MB-BP utilizes online delivery approaches, and research is underway assessing that delivery approach. Fifth, using the current study design, it was not possible to determine which components of MB-BP were most important for improving CVH. Future studies with dismantling or optimization designs can answer these questions.

5. Conclusions

This trial suggests that a structured mindfulness-based intervention may modestly improve multiple dimensions of cardiovascular health. These findings support further evaluation in larger, longer-term trials with event-based outcomes.

Central Illustration.

Funding sources

This work was supported by the National Institutes of Health [grant numbers UH2AT009145, UH3AT009145]. The funding source had no involvement in the study design, collection, analysis, or interpretation of data, the writing of the report, or the decision to submit the article for publication.

Disclosures

Dr. Loucks is the founder and owner of Sapivita LLC, which provides mindfulness training to improve cardiovascular health and human performance. Conditions were put in place to limit the potential bias of Dr. Loucks on study data interpretation. For example, the primary outcomes were preregistered on ClinicalTrials.gov. Dr. Loucks did not have access to the master data file. He also did not perform the statistical analyses which were led by an independent data analyst (M.S.).

Data Statement

To minimize the possibility of unintentionally sharing information that can be used to re‐identify private information, a subset of the data generated for this study is available at the Open Science Framework and can be accessed at doi.org/10.17605/OSF.IO/86UCD. If further data are desired, interested parties can contact the senior author (Loucks) to request those data. Requests will be considered in alignment with Brown University's IRB guidelines for protection of human subjects.

CRediT authorship contribution statement

Fan Wu: Formal analysis, Visualization, Writing – original draft, Writing – review & editing. LaPrincess C. Brewer: Methodology, Writing – review & editing. Vinicius V. Neves: Writing – review & editing, Project administration, Visualization. Matthew M. Scarpaci: Formal analysis, Data curation, Methodology, Supervision, Visualization, Writing – original draft, Writing – review & editing. Frances B. Saadeh: Project administration, Methodology, Writing – review & editing. Jeffrey A. Proulx: Writing – review & editing. Eric B. Loucks: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Eric Loucks reports a relationship with Sapivita LLC that includes: employment. Dr. Loucks is the founder and owner of Sapivita LLC, which provides mindfulness training to improve cardiovascular health and human performance. Conditions were put in place to limit the potential bias of Dr. Loucks on study data interpretation. For example, the primary outcomes for this study were preregistered on ClinicalTrials.gov. Dr. Loucks did not have access to the master data file. He also did not perform the statistical analyses which were led by an independent data analyst (M.S.). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.