Sustained Benefit of Alternate Behavioral Interventions to Improve Hypertension Control: A Randomized Clinical Trial

Effect of m-Health-Based Interventions on Blood Pressure: An Updated Systematic Review with Meta-Analysis

Background: In recent years, the integration of mobile health (m-Health) interventions has garnered increasing attention as a potential means to improve blood pressure (BP) management in adults. This updated systematic review with meta-analysis aimed to identify the effect of m-Health-based interventions on BP in adults and to evaluate the effect of m-Health on BP according to the characteristics of subjects, interventions, and countries. Methods: The search was carried out in PubMed, Embase, ResearchGate, and Cochrane databases in January 2022. Study selection and data extraction were performed by two independent reviewers. For analysis, random effects models were used with a confidence interval (CI) of 95% and p < 0.05. Results: Fifty studies were included in this review and in the meta-analysis. Interventions with m-Health reduced systolic BP in 3.5 mmHg (95% CI -4.3; -2.7; p < 0.001; I2 = 85.8%) and diastolic BP in 1.8 mmHg (95% CI -2.3; -1.4; p < 0.001; I2 = 78.9%) compared to usual care. The effects of m-Health interventions on BP were more evident in men and in older adults, in interventions lasting 6-8 weeks, with medication reminders, with the possibility of insertion of BP values (p < 0.05). Conclusion: The results of this study support the effectiveness of m-Health in reducing BP when compared to standard care. However, these effects are dependent on the characteristics of the subjects and interventions. Given the substantial heterogeneity among the results of this systematic review with meta-analysis, its interpretation should be cautious. Future research on this topic is warranted.

Effectiveness of digital health interventions on adherence and control of hypertension: a systematic review and meta-analysis

BACKGROUND

Hypertension, a risk factor for developing cardiovascular disease, is becoming increasingly prevalent worldwide. Digital health is now widely utilized for hypertension management, and numerous studies have assessed its effectiveness.

OBJECTIVE

The review aims to analyse the effectiveness of digital health (i.e., mobile health (mHealth), telehealth, and the combination of mHealth & telehealth) on hypertensive patients, concerning three key areas: clinical outcomes, medication adherence, and adherence to lifestyle changes, as compared to standard care.

METHODS

The review followed the PRISMA framework. Eight electronic databases were scanned for randomized control trials focusing on the effects of mHealth or telehealth on hypertensive patients, published between 2010 and 2023. All processes were conducted by the first two authors independently. A meta-analysis was conducted for quantitative data, while a narrative synthesis was conducted for qualitative data.

RESULTS

In total, 74 studies involving 92 686 participants were identified. The meta-analysis favoured the interventions, revealing a significant decrease in systolic blood pressure and diastolic blood pressure for mHealth, telehealth and mHealth & telehealth groups. Nevertheless, medication adherence showed improvement only in the mHealth group, while blood pressure control showed improvement in both mHealth and mHealth & telehealth groups, and BMI showed improvement only in the mHealth group. Evidence for adherence to physical activity and DASH diet/salt intake remained inconclusive.

CONCLUSION

In general, mHealth and telehealth have demonstrated their merits in improving the clinical outcomes of hypertensive patients.

Role of Health Care Professionals in the Success of Blood Pressure Control Interventions in Patients With Hypertension: A Meta-Analysis

BACKGROUND

Globally, only 13.8% of patients with hypertension have their blood pressure (BP) controlled. Trials testing interventions to overcome barriers to BP control have produced mixed results. Type of health care professional delivering the intervention may play an important role in intervention success. The goal of this meta-analysis is to determine which health care professionals are most effective at delivering BP reduction interventions.

METHODS

We searched Medline and Embase (until December 2023) for randomized controlled trials of interventions targeting barriers to hypertension control reporting who led intervention delivery. One hundred articles worldwide with 116 comparisons and 90 474 participants with hypertension were included. Trials were grouped by health care professional, and the effects of the intervention on systolic and diastolic BP were combined using random effects models and generalized estimating equations.

RESULTS

Pharmacist-led interventions , community health worker-led interventions, and health educator-led interventions resulted in the greatest systolic BP reductions of -7.3 (95% CI, -9.1 to -5.6), -7.1 (95% CI, -10.8 to -3.4), and -5.2 (95% CI, -7.8 to -2.6) mm Hg, respectively. Interventions led by multiple health care professionals, nurses, and physicians also resulted in significant systolic BP reductions of -4.2 (95% CI, -6.1 to -2.4), -3.0 (95% CI, -4.2 to -1.9), and -2.4 (95% CI, -3.4 to -1.5) mm Hg, respectively. Similarly, the greatest diastolic BP reductions were -3.9 (95% CI, -5.2 to -2.5) mm Hg for pharmacist-led and -3.7 (95% CI, -6.6 to -0.8) mm Hg for community health worker-led interventions. In pairwise comparisons, pharmacist were significantly more effective than multiple health care professionals, nurses, and physicians at delivering interventions.

CONCLUSIONS

Pharmacists and community health workers are most effective at leading BP intervention implementation and should be prioritized in future hypertension control efforts.

Association of the built environment and neighborhood resources with obesity-related health behaviors in older veterans with hypertension

OBJECTIVE

To evaluate the association of the built environment and neighborhood resources with exercise, diet, and body mass index (BMI).

METHOD

Person-level data were collected from 533 veterans with uncontrolled hypertension. Neighborhood measures were: (a) census-tract level walkability; and (b) healthy food proximity (HFP). Robust or logistic regression (adjusting for age, race, education, comorbidity, and clustered by provider) was used to evaluate associations between neighborhood and exercise duration (hours/week), exercise adherence (% adherent), saturated fat index (0-10), Healthy Eating Index (HEI; 0-100), HEI adherence (≥ 74 score), stage of change (SOC) for exercise and diet (% in action/maintenance), BMI (kg/m²), and obesity (BMI ≥ 30 kg/m²).

RESULTS

The adjusted difference in HEI score (standard error [SE]) between the highest and lowest walkability tertiles was 3.67 (1.35), p = .006; the corresponding comparison for the saturated fat index was 1.03 (.50), p = .041 and BMI was -1.12 (.45), p = .013. The adjusted odds ratio (OR; 95% confidence intervals [CI]) between the highest and lowest walkability tertiles for HEI adherence was 2.16 [1.22, 3.82], p = .009 and for action/maintenance for exercise SOC was 1.78 [1.15, 2.76], p = .011. The adjusted difference (SE) between the highest and lowest HFP tertiles for exercise duration was .65 (.31), p = .03. The adjusted OR [95% CI] between the highest and lowest HFP tertiles for exercise adherence was 1.74 [1.08, 2.79], p = .023 and for action/maintenance for exercise SOC was 1.75 [1.10, 2.79], p = .034.

CONCLUSIONS

Geographical location is associated with exercise and diet. Environment-tailored health recommendations could promote healthier lifestyles and decrease obesity-related cardiovascular disease. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Electronic health strategies to improve medication adherence in patients with cardiometabolic disease: current status and future directions

PURPOSE OF REVIEW

Enabled by widespread technological advancements, electronic health (eHealth) strategies have expanded rapidly over the last decade, presenting opportunities to support self-management including medication adherence for cardiometabolic disease control. eHealth can minimize access barriers to medications, enable timely assessment and shared decision-making, and provide medication reminders and health data feedback. This review summarizes current evidence for effectiveness of eHealth strategies for improving medication adherence in patients with hypertension, type 2 diabetes, and/or hyperlipidemia, and identifies priorities for future research.

RECENT FINDINGS

Current research supports the effectiveness of eHealth strategies to improve medication adherence and clinical outcomes for cardiometabolic disease. Although patient acceptability of eHealth strategies is generally high, engagement may decline over time. In addition, differences in effectiveness across intervention characteristics and sociodemographic groups are understudied, limiting generalizability and tailoring of interventions to local health system resources, culture, and patient needs or preferences.

SUMMARY

eHealth is a promising tool for addressing low medication adherence. Further work incorporating rigorous evaluation, assessment of patient engagement over time and effectiveness of intervention characteristics and components, and a health equity lens addressing eHealth use in vulnerable groups will increase understanding of the full potential of eHealth for improving medication adherence in diverse patients with cardiometabolic disease.

Effectiveness of a Transtheoretical Model-Based Intervention to Improve Blood Pressure Control of Hypertensive Patients in China: A Clustered Randomized Controlled Trial

Background

Hypertension can result in great cardiovascular risk, while medication adherence and blood pressure control of patients were suboptimal. Therefore, we conducted a 12-month clustered randomized controlled trial to evaluate the effectiveness of transtheoretical model (TTM)-based health intervention mode on blood pressure of Chinese newly-diagnosed hypertensive patients.

Methods

This trial was conducted in six primary healthcare centers, Shunyi District, Beijing, China from September 2016 to September 2017. A total of 400 patients were included and randomized, 194 patients in the control group and 206 patients in the intervention group. Patients in the intervention group received TTM-based health intervention and those in the control group received usual care. Multilevel modeling was used to adjust for clustering effect and repeated measurements.

Results

Systolic blood pressure of patient was reduced by 4.534 mm Hg at 3-month follow-up [95% CI (−3.054, −1.403), p = 0.005], 3.982 mm Hg at 6-month follow-up [95% CI (−7.387, −0.577), p = 0.022], and 5.803 mm Hg at 12-month follow-up [95% (−9.716, −1.891), p = 0.004]. Diastolic blood pressure of patient was reduced by 3.383 mm Hg at 3-month follow-up [95% CI (−5.724, −1.042), p = 0.005], 0.330 mm Hg at 6-month follow-up [95% CI (−2.870, 2.210), p = 0.799], and 3.129 mm Hg at 12-month follow-up [95% CI (−6.048, −0.21), p = 0.036]. Medication adherence of patients was improved at all the three time points. For stages of change for taking medication, patients in the intervention group were 8.401-fold more likely to be in a higher stage at 3-month follow-up [95% CI (4.186, 16.862), p < 0.001]. The odds ratio of being in a higher stage was 8.454 at 6-month follow-up [95% CI (3.943, 18.123), p < 0.001] and 19.263 at 12-month follow-up [95% CI (7.979, 46.505), p < 0.001].

Conclusion

Transtheoretical model-based health intervention might be a promising strategy to improve medication adherence of newly-diagnosed hypertensive patients in community.