Impact of lifestyle-based interventions on absolute cardiovascular disease risk: a systematic review and meta-analysis

Abstract

Objective: The objective of the review was to synthesize the evidence of the effectiveness of lifestyle-based interventions for mitigating absolute cardiovascular disease (CVD) risk.

Introduction: Evidence-based guidelines recommend employing an absolute CVD risk score to inform the selection and intensity of preventive interventions. However, studies employing this strategy have reported mixed results, hence the need for a systematic review of the current evidence.

Inclusion criteria: Studies published in English that included a lifestyle-based intervention to mitigate CVD risk were considered. Studies were eligible if they enrolled individuals aged ≥18 years, with no history of CVD at baseline. The primary outcome was change in absolute CVD risk score post-intervention.

Methods: PubMed, Embase, and CINAHL searches were conducted from database inception to February 2022. The trial registers searched included Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov. Searches for unpublished studies/gray literature were conducted in ProQuest Dissertations and Theses Global, GreyLit Report, and OCLC First Search Proceedings. Two independent reviewers selected the studies and critically appraised them for methodological quality using JBI tools. Data extraction was performed for main outcome variables. Data were presented using separate pooled statistical meta-analysis for quasi-experimental and randomized clinical trials. Random effects models were employed in the analyses. Effect sizes (Cohen's d) were expressed as standardized mean difference at 95% CI. Heterogeneity was assessed via Cochran's Q statistic, and the inconsistency index ( I2 ) was used to describe variability in effect estimates due to heterogeneity rather than sampling error.

Results: Twenty-nine studies with a total sample of 5490 adults with no CVD at baseline were included. Fifteen were randomized controlled trials (RCTs; n=3605) and 14 were quasi-experimental studies (n=1885). The studies were conducted in Europe (n=18), the United States (n = 5), Asia (n=3), Mexico (n=1), Canada (n = 1), and Australia (n=1) and included the following lifestyle interventions: diet, physical activity, motivational interviewing, problem-solving, psychological counseling, cardiovascular risk assessment and feedback, health self-management education, and peer support. Six validated absolute CVD risk assessment tools were used to measure the study outcomes, including Framingham, SCORE, Heart Health Risk Assessment Score, Dundee, ASSIGN, and The UK Prospective Diabetes Study risk score. Overall, the methodological rigor of the RCTs and quasi-experimental studies was high. Of the 15 RCTs included in the meta-analysis, lifestyle intervention was favored over control in reducing absolute CVD risk score (Cohen's d = -0.39; P =0.032; Z= -2.14; I2 = 96). Similarly, in the 14 quasi-experimental studies, the absolute CVD risk score after lifestyle intervention was significantly lower compared to baseline (Cohen's d = -0.39; P <0.001; Z= -3.54; I2= 88). RCTs that combined diet and physical activity reported no significant impact on absolute CVD risk score, but those that used either intervention independently reported significant improvement in the absolute CVD risk score.

Conclusions: There is evidence supporting the positive impact of lifestyle modification on absolute CVD risk score in adult populations without CVD. Our analysis further suggests that diet and physical activity had significant impact on absolute CVD risk, and a variety of validated screening tools can be used to monitor, evaluate, and communicate changes in absolute risk score after lifestyle modification.

Supplemental digital content: A Spanish-language version of the abstract of this review is available [ http://links.lww.com/SRX/A29 ].

Figure 1:

Search results and and study selection process CVD, cardiovascular disease

Figure 2:

Forest plot of the comparative meta-analysis including studies that employed RCT design

Figure 3:

Forest plot of the meta-analysis of quasi-experimental design studies

Figure 4:

Forest plot of the comparative meta-analysis including RCT studies that employed a combination of diet and physical activity in their intervention

Figure 5:

Forest plot of the meta-analysis including quasi-experimental studies that employed a combination of diet and physical activity in their intervention

Figure 6:

Forest plot of the comparative meta-analysis including RCT studies that employed dietary interventions

Figure 7:

Forest plot of the meta-analysis including quasi-experimental studies that employed dietary interventions

Figure 8:

Forest plot of the comparative meta-analysis including RCT studies that employed physical activity interventions

Figure 9:

Forest plot of the meta-analysis including quasi-experimental studies that employed physical activity interventions

Figure 10:

Forest plot of the meta-analysis including quasi-experimental studies that employed diet, physical activity, and psychological counseling interventions

Figure 11:

Forest plot of the comparative meta-analysis including RCT studies that employed health risk assessment and lifestyle counseling interventions

Figure 12:

Forest plot of the meta-analysis including quasi-experimental studies that employed health risk assessment and lifestyle counseling interventions

Figure 13:

Forest plot of the comparative meta-analysis including all studies that used the Framingham algorithm and RCT design

Figure 14:

Forest plot of the meta-analysis including all studies that used the Framingham algorithm and quasi-experimental design