Skip to main content

Interventions in hypertension: systematic review and meta-analysis of natural and quasi-experiments

Abstract

Background

Hypertension is an urgent public health problem. Consistent summary from natural and quasi-experiments employed to evaluate interventions that aim at preventing or controlling hypertension is lacking in the current literature. This study aims to summarize the evidence from natural and quasi-experiments that evaluated interventions used to prevent or control hypertension.

Methods

We searched PubMed, Embase and Web of Science for natural and quasi-experiments evaluating interventions used to prevent hypertension, improve blood pressure control or reduce blood pressure levels from January 2008 to November 2018. Descriptions of studies and interventions were systematically summarized, and a meta-analysis was conducted.

Results

Thirty studies were identified, and all used quasi-experimental designs including a difference-in-difference, a pre-post with a control group or a propensity score matching design. Education and counseling on lifestyle modifications such as promoting physical activity (PA), promoting a healthy diet and smoking cessation consultations could help prevent hypertension in healthy people. The use of computerized clinical practice guidelines by general practitioners, education and management of hypertension, the screening for cardiovascular disease (CVD) goals and referral could help improve hypertension control in patients with hypertension. The educating and counseling on PA and diet, the monitoring of patients’ metabolic factors and chronic diseases, the combination of education on lifestyles with management of hypertension, the screening for economic risk factors, medical needs, and CVD risk factors and referral all could help reduce blood pressure. In the meta-analysis, the largest reduction in blood pressure was seen for interventions which combined education, counseling and management strategies: weighted mean difference in systolic blood pressure was − 5.34 mmHg (95% confidence interval [CI], − 7.35 to − 3.33) and in diastolic blood pressure was − 3.23 mmHg (95% CI, − 5.51 to − 0.96).

Conclusions

Interventions that used education and counseling strategies; those that used management strategies; those that used combined education, counseling and management strategies and those that used screening and referral strategies were beneficial in preventing, controlling hypertension and reducing blood pressure levels. The combination of education, counseling and management strategies appeared to be the most beneficial intervention to reduce blood pressure levels.

Background

Cardiovascular diseases (CVD) represent the leading cause of death, accounting for one in three deaths in the United States (US) and worldwide [1,2,3]. One of their most potent risk factors, hypertension (also known as high blood pressure), is a common risk factor for CVD [3, 4]. Approximately 40% of adults aged 25 and over had elevated blood pressure in 2008 [3]. What is more, hypertension is responsible for at least 45% of deaths due to heart diseases and 51% of deaths due to stroke worldwide [3, 4]. In the US alone, the direct medical and indirect expenses from CVDs were estimated at approximately $329 billion in 2013 to 2014 [5]. Effective large-scale interventions to prevent or treat hypertension are therefore urgently needed to reverse this trend. Yet, as new and promising interventions are surfacing every day, the need for rigorous evaluation of these interventions to inform evidence-based policies and clinical practice is ever growing.

To this effect, several randomized clinical trials (RCT) have been conducted to evaluate interventions used to prevent hypertension or improve its control [6,7,8]. However, although RCTs represent the gold standard for evaluating the efficacy (i.e., impact under ideal conditions) of most health interventions because of their high internal validity [9, 10], they are not always feasible, appropriate or ethical for the evaluation of certain types of interventions. Furthermore, results from RCTs are not always generalizable to populations or settings of interest due to the highly selected sample and because the intervention is generally conducted under more stringent conditions (low external validity) [11]. To evaluate the effectiveness of an intervention (i.e., impact under real conditions) and to increase the uptake and implementation of evidence-based health interventions in the communities of interests, other types of experimental designs have been proposed. One such example is natural and quasi-experiments. The terms “natural experiments” and “quasi-experiments” are sometimes used interchangeably. In this study, and as described by others [12], we will distinguish these two concepts. Natural and quasi-experiments are similar in that, in both cases, there is no randomization of treatments or exposures (i.e., no random assignment). They differ, however, in that, natural experiments are those that involve naturally occurring or unplanned events (e.g., a national policy, new law), while quasi-experiments involve intentional or planned interventions implemented (typically for the purpose of research/evaluation) to change a specific outcome of interest (e.g., a community intervention program). Furthermore, in natural experiments, the investigator does not have control over the treatment assignment whereas in quasi-experiments, the investigator has control over the treatment assignment [12]. These experiments include difference-in-difference (DID) designs, synthetic controls and regression discontinuity designs to name a few [13,14,15].

As utilization of natural and quasi-experiments is increasing in public health and in the biomedical field [13,14,15], more natural and quasi-experiments are being conducted to evaluate interventions targeted to prevent or control hypertension [16,17,18,19]. This could be due to recent development or the reframing of classical approaches for determining causality in natural and quasi- experiments [13,14,15, 20]. However, unlike RCTs of interventions aiming to prevent hypertension or improve its control [6,7,8], consistent summary and synthesis of evidence from natural and quasi- experiments is lacking in the current literature. The primary aim of the current systematic review is to summarize the evidence from natural and quasi-experiments that have evaluated interventions used to prevent, control hypertension or reduce blood pressure levels. A secondary aim of this study is to conduct a meta-analysis to summarize intervention effectiveness.

Methods

Data sources and strategy

We searched PubMed, Embase and Web of Science from January 2008 to November 2018. This time frame was selected to encompass studies that would have likely benefited from recent development and improvement in natural and quasi- experiments [13, 20]. Briefly, the search strategy consisted in intersecting keywords related to the study methods (e.g., natural experiments, quasi-experiments, DID, synthetic control, interrupted time series, etc.) with the environment or settings (e.g., community, nation, organization, etc.) and the outcome (e.g., hypertension, elevated blood pressure, etc.). The full search strategy is described in Table S1. This systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement [21] (Fig. 1).

Fig. 1
figure 1

Study search and selection flow

Study selection

Two trained members (TX, FZ) screened abstracts and full-text articles. Disagreements were decided by a third member (RN). We included studies that used natural and quasi-experiments to evaluate interventions aimed at preventing hypertension, controlling hypertension or reducing blood pressure levels. The outcome measures were prevalence of hypertension and changes in mean blood pressure. Studies were excluded if they were not in English, were not a natural experiment or a quasi-experimental design, did not include a control group (as it has higher risk to internal validity due to the absence of comparison to adjust for time trends and confounding) [22], did not include blood pressure or hypertension as their outcome or included participants that were 13 years old or younger. In addition, we excluded studies that were not original research articles (e.g., study protocol, books, commentary, dissertations, conference proceedings, comments, systematic reviews, modeling and simulation studies), or had no full text available.

Data extraction and quality assessment

The following information was extracted: study design, sample size, study duration, data source, geographic location, participants’ socio-demographic characteristics, intervention types, intervention levels (e.g., individuals, community, school, clinic and national levels as suggested by the socio-ecological model [23]), behavior targeted and outcome measures (prevalence of hypertension or mean blood pressure change) (Table 1, Table S2).

Table 1 Description of the study characteristics and findings among the 30 studies

The interventions were classified by strategies into four types:

  1. (1)

    Education and counseling: This subcategory includes strategies that aim at educating and providing knowledge and counseling to participants on lifestyle modifications (e.g., increasing physical activity (PA), eating better, avoiding or stopping smoking, etc.).

  2. (2)

    Management: This subcategory includes strategies that aim at monitoring patients’ metabolic factors and chronic diseases (e.g., blood pressure, cholesterol level, etc.) as well as patients’ adherence to medication. These strategies are generally done or facilitated by physicians, general practitioners (e.g., by assessing computerized clinical guidelines in the electronic health record management system), nurses, other staffs, or patients themselves.

  3. (3)

    Education, counseling and management: This subcategory combines education and counseling strategies with management strategies as described above.

  4. (4)

    Screening and referral for management: This subcategory includes strategies that aim at screening for (i.e., checking for the presence of) economic risk factors, medical needs, and CVD risk factors, followed by the referral of participants who screened positive to professionals who specialize in the management of those needs.

We also classified the interventions by settings into (1) community level; (2) health center level (i.e., primary care center or general practices), (3) organization level and (4) nationwide. In addition, we have classified the intervention by duration of the study into short-term (i.e., participants were followed for less than 12 months) and long-term (i.e., participants were followed for longer than or equal to 12 months).

We implemented the Cochrane Risk of Bias Tool for risk of bias and used the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to assess the quality of the evidence for mean blood pressure change outcome [50], since the meta-analysis focused on this outcome. The risk of bias for studies included in this review could be found in Table S3 and the quality of studies has also been summarized in Table S4.

Meta-analysis

To summarize the effectiveness of interventions on mean blood pressure changes, we also conducted a meta-analysis. Due to the high heterogeneity in the studies and interventions, we undertook a random-effects model and only summarized the effectiveness of intervention strategies by subgroup defined by intervention types, settings and duration. We estimated the weighted mean difference (WMD) of blood pressure and 95% confidence intervals (CIs). The studies included in the meta-analysis were only those whose outcomes were mean differences (MDs) in blood pressure (n = 27) [16, 19, 25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49] as these studies provided the data needed for performing the meta-analysis. Three studies [38, 39, 43] were excluded as they did not provide enough information to compute the standard errors (SEs). To estimate the average effect of the intervention when not directly provided, we subtracted the before-and-after change in the intervention group from that in the control group or subtracted the intervention-to-control difference at follow-up to that at baseline (pre-post design with a control group). Methods to calculate intervention impact and SEs were outlined in the appendix (Figs. S1, S2, Table S5).

We presented the meta-analysis results using forest plots (Table 2, Fig. 2, Figs. S3, S4). We assessed the heterogeneity by using the I2 (Table 2, Fig. 2, Figs. S3, S4). We did not perform meta-regression as it is not recommended when the number of studies is small (< 10 studies per covariate) [51]. We assessed publication bias by using funnel plots of SEs (Figs. S5, S6, S7). To test the robustness of our results, we performed sensitivity analyses by removing one study at a time from the pool of studies to assess its impact on the findings (Tables S, S7, S8, Figs. S8, S9, S10). Data were analyzed with Stata 15.1 (StataCorp LLC, College Station, TX, USA).

Table 2 Summary estimates of the subgroup meta-analysis
Fig. 2
figure 2

Forest plot stratified by intervention types for blood pressure. A Forest plot stratified by intervention types for systolic blood pressure (SBP). B Forest plot stratified by intervention types for diastolic blood pressure (DBP)

Results

Overall, 788 titles of potentially relevant studies were identified and screened. In total, 545 were excluded and 243 full papers were retrieved, then 30 studies were included in the final sample (Fig. 1).

Study characteristics

Of the 30 studies included in this review [16,17,18,19, 24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49], three studies reported changes in hypertension prevalence, among which one study reported preventing hypertension in the general population [24] and two studies reported blood pressure control in patients with hypertension [17, 18]; 25 studies reported mean blood pressure changes [16, 19, 27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49]; two studies reported both outcome measures (changes in hypertension prevalence and mean blood pressure changes) [25, 26]. Thirteen studies used education and counseling intervention strategies [24, 25, 27,28,29,30,31,32,33,34,35,36,37]; four studies used management intervention strategies [18, 19, 38, 39]; seven studies combined education, counseling and management intervention strategies [26, 40,41,42,43,44,45]; and six studies used screening and referral for management intervention strategies [16, 17, 46,47,48,49]. Fourteen studies followed participants for less than 12 months (i.e., short-term interventions) [17, 26, 27, 29, 30, 32,33,34, 36, 40,41,42,43, 45]. Twelve studies were conducted in the US [16, 17, 19, 24, 27, 28, 32, 33, 39, 41, 43, 46] and most studies included both genders [16,17,18,19, 24,25,26, 28,29,30,31, 33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49] and all racial/ethnic groups [16,17,18,19, 24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40, 42,43,44,45,46,47,48,49]. We found no natural experiments according to the definition used in this study (Table 1, Table S2).

Quality ratings

According to the Cochrane Risk of Bias Tool, most studies included in this review were found to have a high risk of bias (Table S3). This was so because the Cochrane Risk of Bias Tool was mostly designed for RCTs. Studies included in this review only used quasi-experiment designs and as such did not use randomization, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment. Using the GRADE approach, the quality of evidence was deemed of low quality for the mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) change outcome (Table S4).

Studies that reported prevalence of hypertension in the general population or changes in the prevalence of controlled blood pressure in hypertension patients after intervention

Outcome of interest: prevention of hypertension in healthy people

Education and counseling intervention strategies

Two studies evaluated the education and counseling intervention strategies, and both found that those strategies could help prevent hypertension in healthy people [24, 25]. One study in the US found that nutritional education and giving access to fruits and vegetables through community gardens helped reduce hypertension prevalence (61.0% vs. 45.0%; P < 0.01), whereas the prevalence of hypertension in the control group did not change (46.7% vs. 49.8%; P = 0.39) [24]. The other study in Africa showed that an education strategy which promoted PA and healthy diet and combined with free smoking cessation consultations could help reduce the prevalence of hypertension (22.8% vs. 16.2%; P = 0.01), compared to that in control group (14.0% vs. 15.1%; P = 0.52) [25].

Outcome of interest: improvement of hypertension control in patients with hypertension

Management intervention strategies

A study in the US showed that patients whose general practitioners accessed the computerized clinical practice guideline at least twice a day improved their hypertension control compared to the patients whose general practitioners never accessed the computerized clinical practice guideline (P < 0.001) [18].

Education, counseling and management intervention strategies

A study in the US found that patients who received education about hypertension and did home blood pressure monitoring had a better control of their hypertension compared to the control group (P = 0.03) [26].

Screening and referral for management intervention strategies

A study in the US showed that for White patients, interventions which involved a coordinator who identified and reached out to patients not meeting CVD goals and linked them to management programs could improve the odds of blood pressure control (odds ratio, 1.13; 95% CI, 1.05 to 1.22) compared to no intervention [17].

Studies that reported mean blood pressure changes after intervention

Outcome of interest: reduction in mean blood pressure

Education and counseling intervention strategies

Seven [25, 27,28,29,30, 34, 35] of twelve [25, 27,28,29,30,31,32,33,34,35,36,37] (58.3%) studies showed that the education and counseling intervention strategies could help reduce mean blood pressure compared to the control group. Education and counseling interventions targeting lifestyle modifications (e.g., diet and PA) have been found effective in reducing blood pressure in the workplace. A study in US female nursing assistants found that combining education and continuing motivation (e.g., counseling on questions of interventions and receiving feedback) on diet and PA led to more reduction in DBP compared to the control group who only received the education (MD, − 6.70 mmHg; 95% CI, − 13.35 to − 0.05) [27]. Two other studies also found that multi-component lifestyle interventions in the workplace including sharing health information by messages, putting up posters, using pedometers, and giving education on PA could help healthy employees or employees with hypertension lower blood pressure [28, 29]. Besides the workplace, interventions implemented in a community setting also appeared to work in reducing blood pressure. A study that included participants age 55 years or more in Asia found that people who attended 60-min Tai Chi three times per week for 12 weeks had a larger reduction in SBP (MD, − 14.30 mmHg; 95% CI, − 19.20 to − 9.40) and in DBP (MD, − 7.02 mmHg; 95% CI, − 10.62 to − 3.42) compared to people maintaining usual daily activities [30]. Another study among patients with hypertension in Asia found that education about the nutritional behavior and guidelines from dietary approaches to stop hypertension (DASH) approach could help reduce blood pressure more in the intervention group compared to the control group who only received the instruction booklets used in intervention group (SBP: MD, − 13.50 mmHg; 95% CI, − 16.15 to − 10.85; DBP: MD, − 6.60 mmHg; 95% CI, − 8.17 to − 5.03) [34]. One study in Africa also showed that education on promoting PA and healthy diet, combined with free smoking cessation consultations could help reduce SBP in the intervention group [25].

Management intervention strategies

Two [19, 39] of three [19, 38, 39] (66.7%) studies showed that the management intervention strategies could help reduce mean blood pressure compared to the control group. A study in the US showed that supporting diabetes patients’ self-management of hypertension by team-based chronic models (e.g., proactive patient outreach, depression screening, and health coaching) could decrease more DBP over a 6-month period compared to the usual care (MD, − 1.13 mmHg; 95% CI, − 2.23 to − 0.04) [19]. A study among hypertension patients in Asia showed that improving the social health insurance system by increasing outpatient expenditure reimbursement ratio could help reduce more SBP (MD, − 2.9 mmHg; P = 0.01) compared to outpatient expense not covered [38]. The other study among diabetes patients in the US also showed that team-based treatment with trained staff on medical management and self-management helped lower SBP (MD, − 0.88 mmHg; P = 0.01), but it did not compare the MD between treatment and control group [39].

Education, counseling and management intervention strategies

Six [26, 40, 42,43,44,45] of seven [26, 40,41,42,43,44,45] (85.7%) studies showed that the combination of education, counseling and management intervention strategies led to more blood pressure reduction compared to the control group. One study among hypertension patients in Europe found that management of stress by biofeedback-assisted relaxation and lifestyle counseling on diet and PA reduced more SBP (MD, − 2.62 mmHg; 95% CI, − 3.96 to − 1.29) and DBP (MD, − 1.00 mmHg; 95% CI, − 1.90 to − 0.93) compared to the control group [40]. One study among hypertension patients in the US also found that education about hypertension and home blood pressure monitoring could help reduce more SBP (MD, − 4.70 mmHg; 95% CI, − 7.14 to − 2.26) and DBP (MD, − 2.20 mmHg; 95% CI, − 3.80 to − 0.60) compared to controls [26]. A study among 65-year-and-older hypertension patients in Asia found that the intervention group who received education on hypertension management, community-based eHealth monitoring, and monthly telephone counseling had more reduction in SBP (MD, − 10.80 mmHg; 95% CI, − 14.99 to − 6.61) compared to the control group who only received a poster about hypertension management [42]. A study among hypertension patients in the US also showed that interventions on lifestyle modifications, and nutritional, pharmacological therapies as well as medication adherence lowered SBP and DBP compared to the control group [43]. A study among hypertension patients in Asia found that integration of preventive-curative services delivery and cooperation among village-town-county physicians for education on lifestyle modifications, taking blood pressure drugs regularly and monitoring the blood pressure could help reduce blood pressure more in the intervention group [44]. The other study in Asia also found that integrated program with health education on home blood pressure monitoring and hypertension measurement skills could help reduce blood pressure more in the intervention group [45].

Screening and referral for management intervention strategies

Four [16, 46,47,48] of five [16, 46,47,48,49] (80.0%) studies showed that the screening and referral for management intervention strategies could help reduce more blood pressure compared to the control group. Screening for medical or economic needs followed by offering treatment and resources has been found helpful. One study in the US found that screening for unmet needs in primary care and offering those who screened positive some resources could reduce SBP (MD, − 2.6 mmHg; 95% CI, − 3.5 to − 1.7]) and DBP (MD, − 1.4 mmHg; 95% CI, − 1.9 to − 0.9) in patients [16]. The other study among patients with serious mental illness in the US also found that using registry for general medical needs and outcomes, screening and referral for general medical illness prevention and treatment could help reduce more DBP compared to controls (MD, − 3.00 mmHg; 95% CI, − 4.96 to − 1.04) [46]. Assessing and screening CVD risk followed by a management program has also been found beneficial to reduce blood pressure. A study in Europe showed that participating in CVD risk assessment and management program, including screening and tailored strategies for lifestyle advice on CVD risk factors could reduce more SBP (MD, − 2.51 mmHg; 95% CI, − 2.77 to − 2.25) and DBP (MD, − 1.46 mmHg; 95% CI, − 1.62 to − 1.29) compared to controls [47]. A study among hypertension patients in Asia also found that a standardized CVD-risk assessment, a hypertension complication screening and adherence to medications could help reduce more blood pressure compared to the usual care [48].

Meta-analysis of the effectiveness of interventions on mean blood pressure change

Intervention type sub-group analysis

The largest blood pressure reduction (SBP: WMD, − 5.34 mmHg; 95% CI, − 7.35 to − 3.33; DBP: WMD, − 3.23 mmHg; 95% CI, − 5.51 to − 0.96) was seen for interventions that combined education, counseling and management intervention strategies (Table 2, Fig. 2).

Intervention setting sub-group analysis

Participants who experienced interventions implemented in community settings (WMD, − 3.77 mmHg; 95% CI, − 6.17 to − 1.37) and in health center settings (WMD, − 3.77 mmHg; 95% CI, − 5.78 to − 1.76) had large SBP reduction. Participants experienced interventions implemented in organization settings had large DBP reduction (WMD, − 3.92 mmHg; 95% CI, − 5.80 to − 2.04) (Table 2, Fig. S3).

Intervention duration sub-group analysis

Participants who were followed for less than 12 months (i.e., short-term interventions) had a large reduction in blood pressure (SBP: WMD, − 6.25 mmHg; 95% CI, − 9.28 to − 3.21; DBP: WMD, − 3.54 mmHg; 95% CI, − 5.21 to − 1.87) and participants who were followed for longer than or equal to 12 months (i.e., long-term interventions) had a moderate reduction in blood pressure (SBP: WMD, − 1.89 mmHg; 95% CI, − 2.80 to − 0.97; DBP: WMD, − 1.33 mmHg; 95% CI, − 2.11 to − 0.55) (Table 2, Fig. S4).

Discussion

We summarized the evidence from quasi-experiments that have evaluated interventions used to (1) prevent hypertension in the general population, (2) improve hypertension control in patients with hypertension or (3) reduce blood pressure levels in both the general population and patients.

In this systematic review, we found that the intervention strategies such as (1) education and counseling, (2) management, (3) education, counseling and management and (4) screening and referral for management were beneficial in preventing, controlling hypertension or reducing blood pressure levels. In particular, we found that education and counseling on lifestyle modifications (i.e., promoting PA, healthy diet, smoking cessation consultations) could help prevent hypertension in healthy people. The use of computerized clinical practice guidelines by general practitioners, education and management of hypertension, screening for CVD goals and referral to management could help improve hypertension control in patients with hypertension. The education and counseling on lifestyle modifications, the monitoring of patients’ metabolic factors and chronic diseases (e.g., blood pressure, cholesterol level, etc.) as well as patients’ adherence to medication, the combined education and management of hypertension, the screening for economic risk factors, medical needs, and CVD risk factors, followed by the referral to management all could help reduce blood pressure levels. Our study is one of the few systematic reviews that have summarized the evidence from quasi-experiments on hypertension prevention and control. A previous systematic review [52] which summarized evidence from cluster-randomized trials and quasi-experimental studies had been conducted and found that education, counseling and management strategies were also beneficial in controlling hypertension and reducing blood pressure. It showed that educating healthcare providers and patients, facilitating relay of clinical data to providers, promoting patients’ accesses to resources were associated with improved hypertension control and decreased blood pressure [52]. Another systematic review which summarized evidence from RCTs found that several interventions including blood pressure self-monitoring, educational strategies, improving the delivery of care, and appointment reminder systems could help control hypertension and reduce blood pressure [6]. Another study also found that community-based health workers interventions including health education and counseling, navigating the health care system, managing care, as well as giving social services and support had a significant effect on improving hypertension control and decreasing blood pressure [53]. A review from observational studies and RCT evidence from the US Preventive Services Task Force found that office measurement of blood pressure could effectively screen adults for hypertension [7].

Our review did not find natural experiments studies according to the definition used in this study. Quasi-experimental designs included DID, propensity score matching and pre-post designs with a control group (PPCG). While PPCG designs generally involve two groups (intervention and control) and two different time points (before and after the intervention), DID designs generally involve two or more intervention and control groups and multiple time points [13]. In this review, we did not include pre-post without a control group design because of its higher risk to internal validity due to the absence of comparison to adjust for time trends and confounding [22]. The findings in this review, highlight that, quasi-experiments are increasingly used to evaluate the effectiveness of health interventions for hypertension management when RCTs are not feasible or appropriate. For instance, several studies included in our systematic review often indicated that RCTs would have been difficult to be implemented given that the intervention was conducted in a particular setting such as a pragmatic clinical setting [16, 43, 45, 48], a community setting [24, 35, 36, 42], or a real-world organizational setting [33] because of ethical concerns and human resources issues. Another reason why quasi-experiments were chosen had to do with the need for translation and generalizability of the evidence in a specific community setting [32]. In fact, RCTs are not always generalizable to the communities or settings of interests [11]. The growing interest in and hence the increase in the use of natural and quasi-experiments in public health may be due to the recognition and realization of its usefulness in evaluating health interventions [14, 54].

Given that there was high heterogeneity in the studies included in this systematic review, we have performed a random effects model and have only presented the subgroup analysis by intervention types, settings and duration of the study. Overall, our study suggested that interventions that combined education, counseling and management strategies appeared to show a relatively large beneficial effect for reducing blood pressure. However, our finding should be interpreted with caution due to the high-risk of bias and lower quality of evidence given the quasi-experimental nature of the designs (as opposed to evidence from randomized experiments). Nevertheless, the findings here can give us some insights on the benefit of interventions such as education, counseling and management, especially given that our findings are in line with previous studies [6, 8, 52, 55]. Given that RCTs are not always feasible or appropriate, scientists should develop more rigorous methods to increase the internal validity of non-randomized studies. Compared to previous studies, one systematic review with meta-analysis including cluster-randomized trials and quasi-experiment studies showed that multi-component interventions which incorporated education of health care providers and patients, facilitating relay of clinical data to providers, and promoting patients’ accesses to resources could reduce more blood pressure compared to controls [52]. A recent systematic review with meta-analysis of RCTs also reported that interventions which included blood pressure self-monitoring, appointment reminder systems, educational strategies, and improving the delivery of care showed beneficial effects on lowering blood pressure [6]. Another systematic review and meta-analysis of RCTs also showed that self-measured blood pressure monitoring lowered SBP by 3.9 mmHg and DBP by 2.4 mmHg at 6 months compared to the usual care group [8]. One systematic review and meta-analysis of RCTs found that diet improvement, aerobic exercise, alcohol and sodium restriction, and fish oil supplements reduced blood pressure as well [55].

Limitations

This review has some limitations. First, the definition of natural and quasi-experiments is not consistent across fields. Second, the main limitation in most if not all the quasi-experimental study designs noted in this review was the potential for unobserved and uncontrolled confounding, which is a threat to internal validity and could lead to biased findings. Third, our findings may not be generalizable to all countries and settings as we only included studies published in the English language in this review. Fourth, as is the case in most other reviews, we could have missed relevant studies despite our best attempt to conduct a thorough search of the literature. Fifth, we found that most studies included in this study had a high risk of bias. It might be because we used the Cochrane Risk of Bias Tool to assess bias which was designed for examining RCTs. Studies in this review only used quasi-experiment designs and did not have randomization, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment. Sixth, studies generally reported the measure of intervention impact differently across studies, making it difficult to combine the findings. In addition, studies were highly heterogeneous in terms of the types of individuals included in the study (e.g., healthy individuals and patients). We conducted the subgroup meta-analysis to reduce the heterogeneity, but the high heterogeneity still existed. Therefore, the results from meta-analysis need to be interpreted with caution. The individual impact reported for each individual study and the results from systematic review should be given more consideration.

Conclusions

In this systematic review, interventions that used education and counseling strategies; those that used management strategies; those that combined education, counseling and management strategies and those that used screening and referral for management strategies were beneficial in preventing, controlling hypertension and reducing blood pressure levels. The combination of education, counseling and management strategies appeared to be the most beneficial intervention to reduce blood pressure levels. The findings in this review, highlight that, a number of interventions that aim at preventing, controlling hypertension or reducing blood pressure levels are being evaluated through the use of quasi-experimental studies. Given that RCTs are not always feasible or appropriate, scientists should develop more rigorous methods to increase the internal validity of such quasi-experimental studies.

Availability of data and materials

The data supporting the conclusions of this article is included within the article and the additional file.

Abbreviations

CI:

Confidence interval

CVD:

Cardiovascular disease

DASH:

Dietary approaches to stop hypertension

DBP:

Diastolic blood pressure

DID:

Difference-in-difference

GRADE:

Grading of Recommendations, Assessment, Development, and Evaluation

MD:

Mean difference

PA:

Physical activity

PPCG:

Pre-post designs with a control group

RCT:

Randomized clinical trial

SBP:

Systolic blood pressure

SE:

Standard error

US:

United States

WMD:

Weighted mean difference

References

  1. National Center for Health Statistics & Heron, M. Deaths: Leading Causes for 2018. Atlanta: CDC; 2021.

  2. Lewington S, Lacey B, Clarke R, Guo Y, Kong XL, Yang L, et al. The burden of hypertension and associated risk for cardiovascular mortality in China. JAMA Intern Med. 2016;176:524–32.

    Article  PubMed  Google Scholar 

  3. World Health Organization (WHO). A global brief on hypertension: silent killer, global public health crisis: World Health Day 2013. Geneva: WHO; 2013.

  4. Sun D, Liu J, Xiao L, Liu Y, Wang Z, Li C, et al. Recent development of risk-prediction models for incident hypertension: an updated systematic review. PLoS One. 2017;12:e0187240.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, et al. Heart disease and stroke statistics-2018 update: a report from the American Heart Association. Circulation. 2018;137:e67–492.

    Article  PubMed  Google Scholar 

  6. Glynn LG, Murphy AW, Smith SM, Schroeder K, Fahey T. Interventions used to improve control of blood pressure in patients with hypertension. Cochrane Database Syst Rev. 2010;3:CD005182.

    Google Scholar 

  7. Sheridan S, Pignone M, Donahue K. Screening for high blood pressure: a review of the evidence for the U.S. preventive services task force. Am J Prev Med. 2003;25:151–8.

    Article  PubMed  Google Scholar 

  8. Uhlig K, Patel K, Ip S, Kitsios GD, Balk EM. Self-measured blood pressure monitoring in the management of hypertension: a systematic review and meta-analysis. Ann Intern Med. 2013;159:185–94.

    Article  PubMed  Google Scholar 

  9. de Simone G, Izzo R, Verdecchia P. Are observational studies more informative than randomized controlled trials in hypertension? Pro side of the argument. Hypertension. 2013;62:463–9.

    Article  PubMed  Google Scholar 

  10. Li DZ, Zhou Y, Yang YN, Ma YT, Li XM, Yu J, et al. Acupuncture for essential hypertension: a meta-analysis of randomized sham-controlled clinical trials. Evid Based Complement Alternat Med. 2014;2014:279478.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Murthy VH, Krumholz HM, Gross CP. Participation in cancer clinical trials: race-, sex-, and age-based disparities. JAMA. 2004;291:2720–6.

    Article  CAS  PubMed  Google Scholar 

  12. Remler DK, Van Ryzin GG. Research methods in practice: strategies for description and causation. 2nd ed. SAGE: Los Angeles; 2014.

    Google Scholar 

  13. Handley MA, Lyles CR, McCulloch C, Cattamanchi A. Selecting and improving quasi-experimental designs in effectiveness and implementation research. Annu Rev Public Health. 2018;39:5–25.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Basu S, Meghani A, Siddiqi A. Evaluating the health impact of large-scale public policy changes: classical and novel approaches. Annu Rev Public Health. 2017;38:351–70.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Craig P, Katikireddi SV, Leyland A, Popham F. Natural experiments: an overview of methods, approaches, and contributions to public health intervention research. Annu Rev Public Health. 2017;38:39–56.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Berkowitz SA, Hulberg AC, Standish S, Reznor G, Atlas SJ. Addressing unmet basic resource needs as part of chronic cardiometabolic disease management. JAMA Intern Med. 2017;177:244–52.

    Article  PubMed  PubMed Central  Google Scholar 

  17. James A, Berkowitz SA, Ashburner JM, Chang Y, Horn DM, O’Keefe SM, et al. Impact of a population health management intervention on disparities in cardiovascular disease control. J Gen Intern Med. 2018;33:463–70.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Comin E, Catalan-Ramos A, Iglesias-Rodal M, Grau M, Del Val JL, Consola A, et al. Impact of implementing electronic clinical practice guidelines for the diagnosis, control and treatment of cardiovascular risk factors: a pre-post controlled study. Aten Primaria. 2017;49:389–98.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Panattoni L, Hurlimann L, Wilson C, Durbin M, Tai-Seale M. Workflow standardization of a novel team care model to improve chronic care: a quasi-experimental study. BMC Health Serv Res. 2017;17:286.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Bor J. Capitalizing on natural experiments to improve our understanding of population health. Am J Public Health. 2016;106:1388–9.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Moher D, Liberati A, Tetzlaff J, Altman DG. PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6:e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Ho AM, Phelan R, Mizubuti GB, Murdoch JAC, Wickett S, Ho AK, et al. Bias in before-after studies: narrative overview for anesthesiologists. Anesth Analg. 2018;126:1755–62.

    Article  PubMed  Google Scholar 

  23. Bronfenbrenner U. The ecology of human development: experiments by nature and design. Cambridge: Harvard University Press; 1979.

    Google Scholar 

  24. Barnidge EK, Baker EA, Schootman M, Motton F, Sawicki M, Rose F. The effect of education plus access on perceived fruit and vegetable consumption in a rural African American community intervention. Health Educ Res. 2015;30:773–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Sahli J, Maatoug J, Harrabi I, Ben Fredj S, Dendana E, Ghannem H. Effectiveness of a community-based intervention program to reduce hypertension prevalence among adults: results of a quasiexperimental study with control group in the region of Sousse. Tunisia Glob Heart. 2016;11:131–7.

    Article  PubMed  Google Scholar 

  26. Fikri-Benbrahim N, Faus MJ, Martínez-Martínez F, Alsina DG, Sabater-Hernandez D. Effect of a pharmacist intervention in Spanish community pharmacies on blood pressure control in hypertensive patients. Am J Health Syst Pharm. 2012;69:1311–8.

    Article  PubMed  Google Scholar 

  27. Flannery K, Resnick B, Galik E, Lipscomb J, McPhaul K, Shaughnessy M. The worksite heart health improvement project (WHHIP): feasibility and efficacy. Public Health Nurs. 2012;29:455–66.

    Article  PubMed  Google Scholar 

  28. Gemson DH, Commisso R, Fuente J, Newman J, Benson S. Promoting weight loss and blood pressure control at work: impact of an education and intervention program. J Occup Environ Med. 2008;50:272–81.

    Article  PubMed  Google Scholar 

  29. Lin YP, Lin CC, Chen MM, Lee KC. Short-term efficacy of a “sit less, walk more” workplace intervention on improving cardiometabolic health and work productivity in office workers. J Occup Environ Med. 2017;59:327–34.

    Article  PubMed  Google Scholar 

  30. Chang MY, Yeh SC, Chu MC, Wu TM, Huang TH. Associations between Tai chi Chung program, anxiety, and cardiovascular risk factors. Am J Health Promot. 2013;28:16–22.

    Article  PubMed  Google Scholar 

  31. Verberne LD, Hendriks MR, Rutten GM, Spronk I, Savelberg HH, Veenhof C, et al. Evaluation of a combined lifestyle intervention for overweight and obese patients in primary health care: a quasi-experimental design. Fam Pract. 2016;33:671–7.

    Article  PubMed  Google Scholar 

  32. Xu F, Letendre J, Bekke J, Beebe N, Mahler L, Lofgren IE, et al. Impact of a program of Tai chi plus behaviorally based dietary weight loss on physical functioning and coronary heart disease risk factors: a community-based study in obese older women. J Nutr Gerontol Geriatr. 2015;34:50–65.

    Article  PubMed  Google Scholar 

  33. Zhu W, Gutierrez M, Toledo MJ, Mullane S, Stella AP, Diemar R, et al. Long-term effects of sit-stand workstations on workplace sitting: a natural experiment. J Sci Med Sport. 2018;21:811–6.

    Article  PubMed  Google Scholar 

  34. Kamran A, Sharifirad G, Heydari H, Sharifian E. The effect of theory based nutritional education on fat intake, weight and blood lipids. Electron Physician. 2016;8:3333–42.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Ibrahim N, Ming Moy F, Awalludin IA, Mohd Ali Z, Ismail IS. Effects of a community-based healthy lifestyle intervention program (co-HELP) among adults with prediabetes in a developing country: a quasi-experimental study. PLoS One. 2016;11:e0167123.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kassim MSA, Manaf MRA, Nor NSM, Ambak R. Effects of lifestyle intervention towards obesity and blood pressure among housewives in Klang Valley: a quasi-experimental study. Malays J Med Sci. 2017;24:83–91.

    PubMed  PubMed Central  Google Scholar 

  37. Fazliana M, Liyana AZ, Omar A, Ambak R, Mohamad Nor NS, Shamsudin UK, et al. Effects of weight loss intervention on body composition and blood pressure among overweight and obese women: findings from the MyBFF@home study. BMC Womens Health. 2018;18(Suppl 1):93.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Miao Y, Gu J, Zhang L, He R, Sandeep S, Wu J. Improving the performance of social health insurance system through increasing outpatient expenditure reimbursement ratio: a quasi-experimental evaluation study from rural China. Int J Equity Health. 2018;17:89.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Scanlon DP, Hollenbeak CS, Beich J, Dyer AM, Gabbay RA, Milstein A. Financial and clinical impact of team-based treatment for medicaid enrollees with diabetes in a federally qualified health center. Diabetes Care. 2008;31:2160–5.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Darviri C, Artemiadis AK, Protogerou A, Soldatos P, Kranioutou C, Vasdekis S, et al. A HEALth promotion and STRESS management program (HEAL-STRESS study) for prehypertensive and hypertensive patients: a quasi-experimental study in Greece. J Hum Hypertens. 2016;30:397–403.

    Article  CAS  PubMed  Google Scholar 

  41. Fernandez S, Scales KL, Pineiro JM, Schoenthaler AM, Ogedegbe G. A senior center-based pilot trial of the effect of lifestyle intervention on blood pressure in minority elderly people with hypertension. J Am Geriatr Soc. 2008;56:1860–6.

    Article  PubMed  Google Scholar 

  42. Jung H, Lee JE. The impact of community-based eHealth self-management intervention among elderly living alone with hypertension. J Telemed Telecare. 2017;23:167–73.

    Article  PubMed  Google Scholar 

  43. Hussain T, Franz W, Brown E, Kan A, Okoye M, Dietz K, et al. The role of care management as a population health intervention to address disparities and control hypertension: a quasi-experimental observational study. Ethn Dis. 2016;26:285–94.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Miao Y, Zhang L, Sparring V, Sandeep S, Tang W, Sun X, et al. Improving health related quality of life among rural hypertensive patients through the integrative strategy of health services delivery: a quasi-experimental trial from Chongqing. China Int J Equity Health. 2016;15:132.

    Article  PubMed  Google Scholar 

  45. Visanuyothin S, Plianbangchang S, Somrongthong R. An integrated program with home blood-pressure monitoring and village health volunteers for treating poorly controlled hypertension at the primary care level in an urban community of Thailand. Integr Blood Press Control. 2018;11:25–35.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Scharf DM, Schmidt Hackbarth N, Eberhart NK, Horvitz-Lennon M, Beckman R, Han B, et al. General medical outcomes from the primary and behavioral health care integration grant program. Psychiatr Serv. 2016;67:1226–32.

    Article  PubMed  Google Scholar 

  47. Chang KC, Lee JT, Vamos EP, Soljak M, Johnston D, Khunti K, et al. Impact of the National Health Service Health Check on cardiovascular disease risk: a difference-in-differences matching analysis. CMAJ. 2016;188:E228–38.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Yu EY, Wan EY, Wong CK, Chan AK, Chan KH, Ho SY, et al. Effects of risk assessment and management programme for hypertension on clinical outcomes and cardiovascular disease risks after 12 months: a population-based matched cohort study. J Hypertens. 2017;35:627–36.

    Article  CAS  PubMed  Google Scholar 

  49. van de Vijver S, Oti SO, Gomez GB, Agyemang C, Egondi T, Moll van Charante E, et al. Impact evaluation of a community-based intervention for prevention of cardiovascular diseases in the slums of Nairobi. the SCALE-UP study Glob Health Action. 2016;9:30922.

    Article  PubMed  Google Scholar 

  50. Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions. 2nd ed. Wiley-Blackwell: Hoboken; 2020.

    Google Scholar 

  51. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Introduction to meta-analysis. Chichester: John Wiley & Sons; 2009.

    Book  Google Scholar 

  52. Walsh JM, McDonald KM, Shojania KG, Sundaram V, Nayak S, Lewis R, et al. Quality improvement strategies for hypertension management: a systematic review. Med Care. 2006;44:646–57.

    Article  PubMed  Google Scholar 

  53. Kim K, Choi JS, Choi E, Nieman CL, Joo JH, Lin FR, et al. Effects of community-based health worker interventions to improve chronic disease management and care among vulnerable populations: a systematic review. Am J Public Health. 2016;106:e3–28.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Rehkopf DH, Basu S. A new tool for case studies in epidemiology-the synthetic control method. Epidemiology. 2018;29:503–5.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Dickinson HO, Mason JM, Nicolson DJ, Campbell F, Beyer FR, Cook JV, et al. Lifestyle interventions to reduce raised blood pressure: a systematic review of randomized controlled trials. J Hypertens. 2006;24:215–33.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

Not applicable.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

Authors

Contributions

TX participated in the study conception, design and analysis and wrote the initial first draft of the article. FZ participated in the study conception, design and reviewed the first draft of the article. RN conceived and supervised the design and analysis, finalized the first draft and critically reviewed and revised the manuscript. All authors provided critical input and insights into the development and writing of the article and approved the final manuscript as submitted.

Corresponding author

Correspondence to Roch A. Nianogo.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Table S1.

Search words. Table S2. Summary of the characteristics of the studies included in this review (n = 30). Table S3. Risk of Bias Tool Assessments Across Studies (n = 30). Table S4. GRADE Evidence Profiles Across Studies in Meta-analysis (n = 24). Table S5. Estimates and parameters in studies that reported on the mean difference in blood pressure (n = 27). Table S6. Sensitivity analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP) in meta-analysis stratified by intervention type. Table S7. Sensitivity analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP) in meta-analysis stratified by intervention setting. Table S8. Sensitivity analysis for systolic blood pressure (SBP) and diastolic blood pressure (DBP) in meta-analysis stratified by intervention duration. Fig. S1. Methods to calculate mean differences (MD). Fig. S2. Methods to calculate standard errors (SE). Fig. S3. Forest plot stratified by intervention settings for blood pressure. (A) Forest plot stratified by intervention settings for systolic blood pressure (SBP). (B) Forest plot stratified by intervention settings for diastolic blood pressure (DBP). Fig. S4. Forest plot stratified by intervention duration for blood pressure. (A) Forest plot stratified by intervention duration for systolic blood pressure (SBP). (B) Forest plot stratified by intervention duration for diastolic blood pressure (DBP). Fig. S5. Funnel plot of systolic blood pressure (SBP), diastolic blood pressure (DBP) stratified by intervention types. Fig. S6. Funnel plot of systolic blood pressure (SBP), diastolic blood pressure (DBP) stratified by intervention settings. Fig. S7. Funnel plot of systolic blood pressure (SBP), diastolic blood pressure (DBP) stratified by intervention duration. Fig. S8. Sensitivity analysis of systolic blood pressure (SBP), diastolic blood pressure (DBP) stratified by intervention types. Fig. S9. Sensitivity analysis of systolic blood pressure (SBP), diastolic blood pressure (DBP) stratified by intervention settings. Fig. S10. Sensitivity analysis of systolic blood pressure (SBP), diastolic blood pressure (DBP) stratified by intervention duration

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xia, T., Zhao, F. & Nianogo, R.A. Interventions in hypertension: systematic review and meta-analysis of natural and quasi-experiments. Clin Hypertens 28, 13 (2022). https://doi.org/10.1186/s40885-022-00198-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40885-022-00198-2

Keywords