Cardiovascular disease risk communication and prevention: a meta-analysis

Abstract Background and Aims Knowledge of quantifiable cardiovascular disease (CVD) risk may improve health outcomes and trigger behavioural change in patients or clinicians. This review aimed to investigate the impact of CVD risk communication on patient-perceived CVD risk and changes in CVD risk factors. Methods PubMed, Embase, and PsycINFO databases were searched from inception to 6 June 2023, supplemented by citation analysis. Randomized trials that compared any CVD risk communication strategy versus usual care were included. Paired reviewers independently screened the identified records and extracted the data; disagreements were resolved by a third author. The primary outcome was the accuracy of risk perception. Secondary outcomes were clinician-reported changes in CVD risk, psychological responses, intention to modify lifestyle, and self-reported changes in risk factors and clinician prescribing of preventive medicines. Results Sixty-two trials were included. Accuracy of risk perception was higher among intervention participants (odds ratio = 2.31, 95% confidence interval = 1.63 to 3.27). A statistically significant improvement in overall CVD risk scores was found at 6–12 months (mean difference = −0.27, 95% confidence interval = −0.45 to −0.09). For primary prevention, risk communication significantly increased self-reported dietary modification (odds ratio = 1.50, 95% confidence interval = 1.21 to 1.86) with no increase in intention or actual changes in smoking cessation or physical activity. A significant impact on patients’ intention to start preventive medication was found for primary and secondary prevention, with changes at follow-up for the primary prevention group. Conclusions In this systematic review and meta-analysis, communicating CVD risk information, regardless of the method, reduced the overall risk factors and enhanced patients’ self-perceived risk. Communication of CVD risk to patients should be considered in routine consultations.


Methods
PubMed, Embase, and PsycINFO databases were searched from inception to 6 June 2023, supplemented by citation analysis.Randomized trials that compared any CVD risk communication strategy versus usual care were included.Paired reviewers independently screened the identified records and extracted the data; disagreements were resolved by a third author.The primary outcome was the accuracy of risk perception.Secondary outcomes were clinician-reported changes in CVD risk, psychological responses, intention to modify lifestyle, and self-reported changes in risk factors and clinician prescribing of preventive medicines.

Results
Sixty-two trials were included.Accuracy of risk perception was higher among intervention participants (odds ratio = 2.31, 95% confidence interval = 1.63 to 3.27).A statistically significant improvement in overall CVD risk scores was found at 6-12 months (mean difference = −0.27,95% confidence interval = −0.45 to −0.09).For primary prevention, risk communication significantly increased self-reported dietary modification (odds ratio = 1.50, 95% confidence interval = 1.21 to 1.86) with no increase in intention or actual changes in smoking cessation or physical activity.A significant impact on patients' intention to start preventive medication was found for primary and secondary prevention, with changes at follow-up for the primary prevention group.

Conclusions
In this systematic review and meta-analysis, communicating CVD risk information, regardless of the method, reduced the overall risk factors and enhanced patients' self-perceived risk.Communication of CVD risk to patients should be considered in routine consultations.

Introduction
The increasing prevalence of cardiovascular disease (CVD) and associated morbidity is now considered a global emergency.Cardiovascular disease mortality is estimated to account for a third of all deaths worldwide (17.9 million per year according to the World Health Organization). 1 The corresponding Australian estimate is 25%, 2 with heart attacks and strokes responsible for 85% of the yearly deaths. 2 Sedentary lifestyles, smoking, unhealthy diet, and poor screening behaviour are largely responsible for the escalation of this problem. 24][5] Cardiovascular disease risk calculators to estimate individualized risk have also played a role in either preventing or modifying risk factors. 6Different international guidelines usually recommend to communicate individual CVD risk, which is calculated by combining risk factors in an empirical equation, as a first step to establish behaviour modification to decrease CVD risk even for asymptomatic people.Risk communication is challenging as multiple factors appear to affect risk perception, for example, how best to visually present this information and which numerical format to use.Timeframe (lifetime, 10 year) of the risk can also influence the perception of risk severity and intention to initiate treatment even in educated populations. 6,7arious medical specialties have examined the gap between communicating risk information and inducing behaviour change.However, the effectiveness of different strategies to reduce this gap has shown mixed results. 8,9everal systematic reviews have investigated the effect of risk information on clinical outcomes either by looking at the effect of personalized risk information as general descriptors 10 or providing CVD risk scores (irrespective of the model used e.g.Framingham) or comparing the effect of the different calculators on accuracy of risk perception. 11,12The systematic reviews reported mixed results and the impact of risk communication interventions on changes in the accuracy of risk perception, patient intentions and actual behaviour change, and clinician's medications prescribing (in response to the knowledge of their patients' CVD risk) remains unclear.Hence, an updated synthesis with the inclusion of results from newly published articles was warranted to enhance understanding of the total effects of risk communication on patients and doctors for primary and secondary prevention.
This review investigated the following research questions: (i) What is the impact of CVD risk communication on patient-perceived CVD risk, actual change in CVD risk factors, psychological responses, and selfreported behaviours?(ii) What is the impact of CVD risk knowledge on clinician's prescribing behaviour?

Methods
This systematic review is reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. 13The protocol was developed prospectively and registered on the Open Science Framework (https://doi.org/10.17605/OSF.IO/SNAKV).

Participants
We included studies of adults aged 30 years and above with (secondary prevention) or without (primary prevention) established CVD.Studies of adults with genetic predisposition of CVD or with a sample size less than 40 were excluded for the validity of normal approximation of estimates. 14

Interventions and comparators
We included trials that compared any type of CVD risk communication strategy covering online, paper-based, or verbal administration of any scoring system or tool presenting global CVD risk score or the risk of any specific clinical CVD events (e.g.heart attack, stroke, or atrial fibrillation).This was then compared with usual care with or without any CVD risk communication strategy including comparisons against different risk communication formats (e.g.visual, verbal, and numeric) or communication strategies (e.g.threat and efficacy).

Setting
Eligible interventions were those implemented in any health setting and delivered by any healthcare provider (e.g.cardiologist, general practitioner, nurse, or pharmacist).

Primary outcome
• Accuracy of risk perception (patient-reported) as defined and reported eligible by study authors, which could be reported using a scale, numerical, or categorial and then assessed for its accuracy (where the numerator is the self-perception of risk and the denominator is the objectively calculated risk, or where categories of low-medium-high are assigned to % risk levels).

Secondary outcomes Participant-reported outcomes
• Psychological responses to CVD risk information (e.g.decisional conflict and depression).• Behaviour changes either intention to change (e.g.smoking cessation, exercise, and start medications) or actual reported and recorded changes (e.g.quit smoking, lost weight, and dietary changes).

Clinician-reported outcomes
• Change in predicted global CVD risk or event rates.
• Changes in blood pressure, lipids, and glucose levels.
• Prescribing of new/additional medications (e.g.lipid-lowering and/or antihypertensive medications) or lifestyle changes (e.g.smoking cessation).

Study design
We included randomized controlled trials (RCTs) of any design (e.g.parallel, cluster, and crossover) if at least one of the primary or secondary outcomes of interest was reported.Excluded were as follows: observational studies, pre-post or qualitative designs, or studies using hypothetical case scenarios of risk perception.Reviews of primary studies (e.g.systematic reviews and literature reviews) were excluded, but the reference lists of any relevant reviews were checked for any additional, relevant primary studies.

Timeframe
We included eligible outcomes reported immediately after the intervention and other follow-up timeframes ranging from 2 weeks to over 12 months.

Database search
PubMed (MEDLINE), Embase (Elsevier), and PsycINFO (OVID) were searched from inception to 6 June 2023.One of the review authors (J.C.), designed the search string in PubMed, refined and pilot tested with two other authors (M.B. and M.C.), and then translated it for use in the other databases using the Polyglot Search Translator. 15The complete search strategy for all databases is provided in Supplementary data online, Box S1.No restrictions by language or publication date were imposed, but only publications that were available in full were includable.Conference abstracts were excluded unless they had a clinical trial registry record, or other public report, with the additional information required for inclusion.We supplemented our search with forward and backward citation searches of included studies and by contacting authors of studies not yet published, which we identified in conference abstracts or randomized trial protocols.

Study selection and screening
Two pairs of review authors (M.B. and E.A. or M.C. and S.F.) independently screened the title and abstract of retrieved records against the inclusion criteria.Screening was conducted using the Screenatron feature of the Systematic Review Accelerator. 16Disputes were identified using the Disputatron feature of the Systematic Review Accelerator and were resolved by discussion or by consulting a third author (M.C. or P.G.). 15,16ee Figure 1 for the PRISMA flow diagram outlining the selection process and Supplementary data online, Table S1 for the complete list of excluded full-text articles with reasons for exclusions.

Data extraction
A data extraction form was piloted on two of the included studies and modified based on feedback from within the team as required.

Assessment of risk of bias in included studies
Paired authors (M.B. and E.A. or M.C. and S.F.) independently assessed the risk of bias for each included RCT using the Cochrane Risk of Bias 1.0 tool. 18isk of Bias Tool 1.0 was used in preference to the Risk of Bias Tool 2.0 as the former allows the assessment of biases from conflict of interest and funding (under the domain: other sources of bias), whilst the latter does not.The following domains were assessed: random sequence generation, allocation concealment, blinding (participants and personnel), blinding (outcome assessment), incomplete outcome data, selective reporting, and other sources of bias (e.g.funding and reported conflicts of interests).Each potential source of bias was graded as low, high, or unclear, and each judgement was supported by a quote from the relevant study.Any disagreements were resolved by discussion between screeners or by referring to a senior author (M.C. or P.G.).

Measurement of effect and data synthesis
Where feasible, dichotomous data were expressed as odds ratios (ORs) or risk ratios with 95% confidence intervals (CIs).Continuous data were expressed as mean differences (MDs) or standardized MDs with 95% CIs.Meta-analysis was only undertaken when meaningful (i.e. when ≥2 studies or comparisons reported the same outcome) using the individual as the unit of analysis, where possible, and due to the anticipated heterogeneity among included studies, a random effects model was used (DerSimonian and Laird random effects method).We used the I 2 statistic to measure heterogeneity among the included trials.Publication bias was intended to be assessed using a funnel plot, provided there were greater than 10 trials included in the analysis.When meta-analysis was not feasible, studies were plotted to facilitate interpretation and narrative explanation was provided. 19or psychological response data, the only meta-analysable outcome under this domain was decisional conflict, a concept encompassing ambiguity on the next steps to take on lifestyle modifications.Decisional conflict scales generally covered subcomponents of uncertainty, lack of clarity, information deficits, perception of support levels, and quality of the decision.The outcome was measured as a difference between follow-up and baseline score points.
We also intended to analyse the effects by the following a priori-defined subgroups, when feasible: type of comparator (e.g.usual care or another risk communication strategy), setting, and time to follow-up.We intended to analyse the data according to the TiDIER intervention components and to conduct a sensitivity analysis by including vs. excluding studies with three or more Cochrane risk of bias domains rated at high risk of bias; however, it was not possible due to the paucity of data.We reported the intervention components in Supplementary data online, Table S2.

Included studies
Our search identified 1782 records, of which 1093 remained after duplicates were removed.After full-text screening of 136 records, 62 studies reported in 68 articles met our inclusion criteria.  A tol of 55 studies were included in the meta-analysis (reporting at least one outcome), and seven studies did not contribute to the meta-analysis 22,31,32,41,49,69,73 (Figure 1).

Intervention descriptions
Of note, 22 interventions in this review were multi-component (Table 1 and Supplementary data online, Table S2) and elements went beyond the communication of the risk, being supplemented with other strategies such as educational materials for patients to keep, motivational counselling, attendance to physical activity sessions, knowledge re-testing, interdisciplinary referrals, prescriptions, and follow-up appointments to check on progress.,85

Risk of bias
The studies generally had low risk of selection bias with appropriate random sampling, low attrition rates, and complete reporting of intended outcomes.Some concerns were apparent on allocation concealment in almost half of the studies.High risk of bias was found in 41 studies that did not blind participants and/or personnel, with some concerns or unclear reporting for the remaining studies.Risk of bias for blinding of outcome assessment was rated as high or unclear for 20 and 22 studies, respectively.A total of 13 articles did not report on conflicts of interest or funding sources or both (Figure 2 and Supplementary data online, Figure S1).
We were able to produce funnel plots to assess the potential for reporting bias for five outcomes, which are shown in Supplementary data online, Box S2 (accuracy of risk perception, changes in CVD risk score, actual changes in medication, blood pressure, and cholesterol changes).Visual inspection of the plots indicated the potential for publication bias related to studies reporting these outcomes.

Accuracy of risk perception Meta-analysable studies
The accuracy of risk perception assessed immediately after the risk communication in 10/55 studies was higher among intervention participants with or without established disease (10 studies, pooled estimate OR = 2.31, 95% CI = 1.63, 3.27) than among the control participants, although heterogeneity was high (I 2 = 70%).This was apparent regardless of whether the control strategy was usual care or active control (Figure 3).A test for subgroup difference showed no evidence that the effect of intervention differed across primary versus secondary prevention subgroups (P = .79).The high heterogeneity for primary prevention vs. usual care was related to settings, personnel administering the intervention, and intervention components.

Non-meta-analysable studies
Among the eight non-meta-analysable studies for this outcome (Table 2 and Supplementary data online, Table S4), only three primary prevention interventions led to significantly more accurate risk perception: two trials using decision aids with outcomes at 3-and 6-month followup, respectively 30,63 and a multi-component study where the Heart Age message achieved higher accuracy at 4 weeks than intervention without the CVD risk communication. 72

Secondary outcomes
See Table 2 and Supplementary data online, Table S4 for a summary of findings for the non-meta-analysable studies and Table 3 for the meta-analysed studies.

Change in cardiovascular disease risk score Meta-analysable studies
The overall influence of CVD risk communication on the change in actual risk score at 6-to 12-month follow-up indicates a significantly larger reduction in risk for the group using CVD risk communication tools than for those receiving usual care [17 studies, pooled estimate MD = −0.27,95% CI = −0.45,−0.09 with moderate heterogeneity (I 2 = 67%); Figure 4].A test for subgroup difference showed no evidence that the effect of intervention differed across subgroups (P = .18).

Non-meta-analysable studies
Two of the three interventional studies that could not be meta-analysed did not show a statistically significant effect on CVD risk score at either 3, 6, or 12 months. 43,49One workplace-based multi-component intervention study achieved a small but significant 12-month difference in risk score (−1.33 or 22.6%, P = .013)among people with pre-existing CVD 52 (Table 2 and Supplementary data online, Table S4).

Psychological response
Meta-analysis of nine studies showed a reduction of decisional conflict at the primary follow-up favouring CVD risk communication (MD = −4.25,95% CI = −6.58,−1.93) with high heterogeneity (I 2 = 78%; Supplementary data online, Figure S2).A test for subgroup difference showed evidence that the effect of intervention differed across subgroups (P = .03).

Smoking cessation intention and reported change
Meta-analysis was possible among the more homogeneous outcomes illustrating participant-reported short-term intention to change behaviour (e.g.smoking cessation, exercise, diet, and start medications).Although people without established disease exposed to the CVD risk communication appeared to have an increased intention to quit smoking, there was no significant difference compared with people in the usual care group in the four small studies that measured this outcome (OR = 1.65, 95% CI = 0.96, 2.85; Supplementary data online, Figure S3A).
At follow-up, no significant impact of CVD risk communication on actual smoking cessation was observed when pooling studies in primary or secondary prevention with active control groups or usual care, with no overall significant impact of CVD risk communication (OR = 1.00, 95% CI = 0.65, 1.54,I 2 = 41%; Supplementary data online, Figure S3B).

Physical activity intention and reported change
Meta-analysis results suggest that cardiovascular risk communication does not enhance patients' intention to change physical activity (pooled effect for four studies; OR = 1.02, 95% CI = 0.86, 1.21; Supplementary data online, Figure S4A).Likewise, there was no statistically significant impact of CVD risk communication on self-reported change in physical activity at follow-up for either primary or secondary prevention patients (pooled effect for nine studies; OR = 1.05, 95% CI = 0.91, 1.21; Supplementary data online, Figure S4B).

Dietary modifications intention and reported change
Four primary prevention studies reported patient's intention to change their diet after CVD risk communication and showed no difference between intervention and usual care (OR = 0.71, 95% CI = 0.38, 1.34; Supplementary data online, Figure S5A).
At follow-up, the pooled estimate of self-reported dietary changes in seven studies indicated a statistically significant impact of the CVD risk communication in this primary prevention target group when compared with usual care (OR = 1.76, 95% CI = 1.39, 2.22; Supplementary data online, Figure S5B).An overall improvement in self-reported dietary change after CVD risk communication was observed for either primary or secondary prevention patients (seven studies of low heterogeneity I 2 = 29%, OR = 1.50, 95% CI = 1.21, 1.86; Supplementary data online, Figure S5B).

Impact on medication intention and reported change
Compared with usual care, the impact of CVD risk communication on patient's intention to initiate, switch, increase, or adhere to preventive medication (such as cholesterol or blood pressure lowering tablets or aspirin) was statistically significantly better for people in the intervention groups with and without established disease (seven studies, OR = 1.21, 95% CI = 1.09, 1.34; Supplementary data online, Figure S6A).This direction of effect remained significant for actual initiation or change in medication at follow-up for the primary prevention interventions with usual care (five studies of moderate heterogeneity I 2 = 52%, OR = 1.82, 95% CI = 1.14, 2.93; Supplementary data online, Figure S6B).
Among the non-meta-analysable studies in Table 2, the intention to start any preventive medication did not significantly change within the a Only one study in the meta-analysis.Bolded values are significant.MD, mean difference; OR, odds ratio; RR, risk ratio; 95% CI, 95% confidence interval.
intervention group for people without established disease.The interventions did not modify actual medication adherence at any follow-up time between 6 and 18 months either.

Impact on cardiovascular disease risk factors Cholesterol
The overall impact of CVD risk communication on measured cholesterol levels was a small but statistically significant reduction at follow-up (20 studies with high heterogeneity I 2 = 85%, MD = −0.10mmol/L, 95% CI = −0.16,−0.03; Supplementary data online, Figure S7), with no significant subgroup differences (P = .64).

Blood glucose
By contrast, regardless of study sample size or the presence or absence of CVD, there was no difference in the follow-up blood glucose levels between those exposed to their CVD risk at baseline and those receiving usual care in the seven studies that reported it (pooled MD = −0.01mmol/L, 95% CI = −0.02,0.01; Supplementary data online, Figure S8).

Blood pressure
Cardiovascular disease risk communication delivered either face to face or remotely via the web led to a small but statistically significant reduction in mean blood pressure at follow-up (23 studies, MD = −1.67 mmHg, 95% CI = −2.70,−0.63; Supplementary data online, Figure S9).

Impact on clinician's prescribing
None of the primary or secondary prevention interventions using CVD risk communication led to significantly higher rates in clinician prescription of medication to reduce the risk factors identified than those in the control groups (seven studies, pooled OR = 1.16, 95% CI = 0.80, 1.69; Supplementary data online, Figure S10).With one exception, 64 these trials of actual prescribing reported by clinicians were not the same as those studies where patients reported medication use, so discrepancies in reporting between patients and clinicians could not be examined.

Summary of findings
This systematic review of 62 trials of generally low risk of bias found that disclosing and communicating cardiovascular risk had a mixed impact on intention to change and subsequent behaviours (Structured Graphical Abstract).Not all studies reported all outcomes of interest and not all outcomes were amenable to meta-analyses.However, to our knowledge, this is the first systematic review investigating the impact on both patients and clinicians.
Overall, and relying largely on the studies that were meta-analysable, the communication of CVD risk led to an increased accuracy of risk perception that was two-to three-fold higher than the control groups, with a greater effect on patients without established CVD (nine studies).Risk communication also led to small but significant reductions in the cardiovascular risk score at 6-to 12-month follow-up (17 studies).It is possible that most of this change was derived from the increase in initiation or adherence to preventive medications (11 studies) or the reported changes in dietary behaviours (7 studies).
Further objective benefits of CVD risk communication were reductions in mean blood pressure at follow-up (23 studies) and blood cholesterol (20 studies).
From the behavioural perspective, intentions to stop smoking or modify physical activity after exposure to risk communication were not different to those of people in the control group; and self-reported smoking cessation or actual changes in physical activity at follow-up did not differ between active and control groups for patients with or without ).Yet, it significantly improved dietary changes in primary prevention interventions when compared with usual care (four studies) and overall, despite not having an impact on secondary prevention (two studies) or primary prevention against active control (two studies).Knowing CVD risk increased patients' intention to initiate or adhere to medication for primary and secondary prevention patients (five studies) and actual medication adherence at follow-up (11 studies).This suggests that people prefer to rely on pharmacotherapy to reduce cardiovascular risk than engage in proactive goal setting, self-regulation, and self-monitoring efforts 87 to modify harder-to-achieve lifestyle behaviours such as physical activity and smoking cessation.The impact of the unreliable nature of self-reported outcomes cannot be discounted as a reason for the lack of success in these interventions.Yet, it did not change clinician's preventive prescribing behaviour (seven studies).While this is a disappointing finding, clinical decision-making may have incorporated patient preference or other risks such as side effects or concurrent comorbidities, as recommended in the guidelines. 88indings from the non-meta-analysable studies were also mixed, with the most impact on positive psychological response (five studies), accuracy of risk perception (three studies), and self-reported smoking cessation for people without established disease (four studies), and somewhat on physical activity and diet (two studies each).

Results in context with other literature
Non-RCT study designs have reported high levels of inaccuracy of risk perception.A before-after study of adult (47 ± 15 years) community dwellers in the USA reported 66% baseline inaccuracy in relation to their objective Framingham risk calculation.The discrepancy was mostly underestimation of 5-year CVD risk (low, moderate, and high) among non-Africans aged >45 years who used alcohol. 89arge prospective initiatives continue to promote the use of risk assessment tools for periodic monitoring to inform personalized therapeutic decisions among adults at risk. 90Further, while closing the gap between known cardiovascular risk and lifestyle behaviour change remains a challenge, [91][92][93] the importance of identifying and communicating prognostic cardiovascular risk cannot be underestimated.Not only it is known to predict disability and mortality, 94 but also associations between cardiovascular risk factors and cognitive impairment have been reported from large cohort studies. 95,96There is some evidence that small efforts to minimize several risk factors may prove as beneficial or more effective than substantial reduction in a single risk factor. 97ays to sustain the change over time include multi-disciplinary team engagement, and consideration of the social determinants of health, 97 to determine level of support required.
The impact of CVD risk communication is also known to vary according to the type of risk format used, although our analysis did not focus on this.Of note, the diversity of ways in which risk was communicated in these studies is part of real-life practice where approaches vary depending on provider preference, patient literacy, available evidence, or local health service policy.
Following the completion of our review, a 2022 systematic review of nine tools of diverse formats reported the biggest impact on both intention and actual behaviour derived from tools that used CVD imaging. 98A recent review of quantitative and qualitative studies investigated the impact of the Heart Age CVD risk tool on psychological, behavioural, and clinical outcomes when compared with absolute risk calculation.The authors reported enhanced psychological responses and increased risk perception with Heart Age but no impact on intention to pursue lifestyle modifications. 99By contrast, the Fitness Age tool, was associated with reduced intentions to change lifestyle when compared with Heart Age.A simulation study of 25 risk calculators generating risk categories low, moderate, or high based on seven risk factors found the risk estimates to be non-reproducible for different timeframes (5-or 10-year risk) and patient types (e.g.diabetes vs. not).The authors warned about using risk calculators to inform clinical practice guidelines. 100espite this, CVD risk calculation and communication are currently recommended by the Australian Heart, Stroke, Diabetes, and Kidney foundations not only to make patients aware of their modifiable lifestyle factors but also for clinicians to decide on monitoring frequency and to guide medication adjustment. 101For doctors, best practice CVD risk communication should include assessment of modifiable and not modifiable risk factors and consideration of family and personal history of comorbidities.However, management decisions to reduce risk will need to adapt a patient-centred approach 102 with balanced discussion on risk and benefits of pharmacotherapy, impact on quality of life, physical and financial burden of treatment, monitoring demands, and personal preferences.

Limitations of this review
Our intention to document multiple outcomes was driven by the need to investigate impacts on both patients and clinicians' behaviour to capture the overall effects.However, many of the outcomes were selfreported and, hence, selected results need to be viewed with caution.][107] Some potentially eligible studies may have been excluded if the full text did not clearly state that the measured CVD risk was communicated to participants.For the primary outcome, the accuracy of risk perception was assessed differently among the included studies, which could have contributed to the high heterogeneity reported in the analysis.There were multiple eligible studies not amenable to inclusion in the meta-analysis due to heterogeneity of samples, interventions, and outcome measurements.Their results, presented in the supplement, need to be viewed with caution.
Many of the interventions in this review were multi-component, and hence, it is acknowledged that this resource-intensive investment for wider implementation in routine care may not be feasible.

Implications for practice and research
As CVD risk communication increases risk perception and leads to quantifiable overall risk reduction, it is recommended for clinicians to continue communicating CVD risk with or without decision support tools, particularly for people without an established disease where the impact appears more widespread across risk factor modification.Caution is recommended in the potential for overestimation of risk from tools calibrated for populations from other countries and the variation in patient's willingness to start pharmacotherapy to reduce cardiovascular events after becoming aware of their risk. 108Another important consideration is the need to further investigate whether reasons for the apparent lack of response from clinicians in increasing prescribing of preventative medications to reduce CVD risk were consumer or provider driven.

Conclusions
This systematic review revealed that CVD risk communication has a mixed impact on intentions and behavioural change for different risk factors.Disclosing and communicating cardiovascular risk levels to atrisk patients has a favourable effect on enhancing accuracy and awareness of self-perceived risk and lowers overall risk score after 6-12 months of follow-up, as well as blood pressure and cholesterol levels.This effect was greater for adults without established CVD.Motivation intentions and actual change in smoking or physical activity were not significantly impacted by CVD risk communications among people with or without established disease.However, actual change in diet was significant at follow-up for the primary prevention participants.Patient-reported intention to medication commencement or ongoing adherence was significantly improved by CVD risk communication in both primary and secondary prevention interventions with actual changes reported in the primary prevention group, but clinicians' change in preventive prescribing behaviour did not align with this finding, possibly due to genuine patient factors.We conclude that it is worth making patients aware of their risk levels to achieve some gain in overall risk reduction regardless of the individual risk factor impacted.
disease risk communication on primary and secondary prevention measures: a systematic review and meta-analysis

Figure 2 '
Figure 2 'Risk of bias graph' illustrates authors' judgements about each risk of bias item presented as percentages across all included studies

Figure 4
Figure 4 Change in cardiovascular disease risk score at 6-12 months of follow-up (n = 17 studies).CI, confidence interval; SE, standard error