Implementing selective-prevention primary care interventions targeting cardio-metabolic diseases in five European countries: the SPIM-EU project

Background Cardio-metabolic diseases are the most common cause of death worldwide. Implementing selective prevention strategies has proven a substantial challenge, especially in primary care. Objectives As part of a collaborative European study, this paper aims to assess the implementation of primary care selective prevention interventions in the Czech Republic, Denmark, Greece, the Netherlands and Sweden. We sought to determine participants’ cardio-metabolic risk profile, as well as their evaluation of the intervention in terms of feasibility and impact in promoting a healthy lifestyle. A selective prevention intervention, including patient invitation and cardio-vascular risk assessment using country-adjusted tools, was implemented. Eligible participants were primary care patients, 40– 65 years of age, without any diagnosis of cardio-metabolic disease. Main outcomes included intervention acceptance and completion rates. Patient demographics, lifestyle-related cardiometabolic risk factors, and opinions on intervention feasibility were recorded. Findings are summarized descriptively.

prevention programs in European primary care and can be used as part of future cardio-metabolic risk reduction strategies.

Background
Cardio-metabolic disease (CMD), including cardio-vascular disease (CVD) and type-II diabetes mellitus (T2DM), represents the most common cause of death worldwide, accounting for more than 17,3 million deaths globally every year (1,2). Although statistics show a significant decline of CVD morbidity and mortality in most European countries, CMD mortality, quality of life, and health care expenditure are still considerably cumbersome (1). In light of the fact that factors such as diet, exercise, smoking, and alcohol consumption affect CMD risk (3)(4)(5), however, current evidence indicates that up to 80% of CMDs can be prevented or delayed through lifestyle changes (6).
The United States Institute of Medicine classifies preventive strategies in four categories: indicated prevention, care-related prevention, universal prevention, and selective prevention (7). Selective prevention aims to identify high-risk, asymptomatic individuals in the general population and offer them preventive strategies. Evidence from modeling studies and systematic reviews suggests that selective prevention of CMD can help reduce the burden of disease in the general population (8,9). In terms of CMD-preventive efforts, primary care and general practitioners (GPs) are on the front lines, with the European Society of Cardiology (ESC) guidelines stating that "GPs have a unique role in identifying individuals at risk of, but without established CVD, and assessing their eligibility for intervention" (6).
The present study is part of the European SPIM-EU project (http://spimeu.org/). SPIM-EU seeks to contribute to the reduction of CMD morbidity and mortality in Europe by testing the feasibility of evidence-based selective prevention strategies and providing comprehensive tools for their application in primary care (10). Within the framework of SPIM-EU an expert consensus meeting has been conducted and a set of statements representing the key characteristics of selective CMD prevention has been proposed in order to develop a universal concept of selective CMD prevention that can guide implementation within European primary care (11). The overall aim of the present study was to assess the feasibility of CMD selective prevention in five considerably different European primary care settings (Czech Republic, Denmark, Greece, Netherlands and Sweden), with special focus on patient participation and acceptance rates. We also sought to report on participants' CMD profile and CVD-risk and record their evaluation of the intervention in terms of feasibility and efficacy in promoting healthy behaviors.

Design and setting
This was a descriptive study reporting on the feasibility of a selective prevention intervention.
Outcomes were summarized using descriptive statistics.
The design and critical determinants of the selective prevention intervention were informed by a consensus meeting with an international panel of 14 experts exploring the evidence from systematic literature reviews and surveys conducted within SPIM-EU (11). The present selective prevention intervention included the invitation and CVD-risk assessment of primary care patients and was implemented in the Czech Republic, Denmark, Greece, the Netherlands and Sweden. In all countries, primary care practices were purposively selected (with the exception of the Netherlands) as study sites: ten practices in the Czech Republic (average practice size: 1900 persons), two in Denmark (average practice size: 1600 persons), three in Greece (average practice size: 1500 persons), five in the Netherlands (average practice size: 2350 persons), and one in Sweden (20,000 listed persons).

Participants
Participants were patients of the selected primary care practices in the five countries. In the Netherlands and Denmark participants were randomly selected, while in the other settings consecutively.
Patients were eligible to participate if they were between 40-65 years of age and had not been diagnosed with a CMD, such as hypertension, CVD, T2DM, chronic renal disease, and/or hypercholesterolemia. In Denmark, the Netherlands and Sweden eligible participants were neither diagnosed with nor in current treatment for CMD.
Since this was a descriptive study assessing implementation feasibility, patient-level sample size estimation was not performed. Rather, a convenience sample of 200 participants per country was set as recruitment goal.

Procedures and outcomes
Details regarding procedural aspects per participating county are presented in the Supplementary

3.
Comprehensive CVD-risk assessment: Each country selected a tool for CVD-risk measurement, based on the ESC or national guidelines (6). Locally validated tools used in clinical practice of each country were selected to facilitate the local adaptation of the intervention. In the Czech Republic and Greece, country-adjusted versions of the European Heart SCORE were used (12). In Sweden, Svenska Score (or SCORE Sweden) was selected (13). In Denmark and the Netherlands, the modified Heartscore BMI score (14)

and the Dutch Prevention Consultation Cardiometabolic
Risk (PC CMR) (15) were used respectively.

4.
Participant evaluation of the intervention: On a ten-point Likert scale, participants were asked to assess the relevance, usefulness, and feasibility of the selective prevention intervention, as well as the extent to which it encouraged a healthier lifestyle. Participants' willingness to change risk behavior, as well as any encountered barriers to lifestyle-style modification, were also assessed.
Upon intervention completion, participants were verbally informed about their CVD-risk and were provided with practical advice on how to reduce it.
Numbers and proportions of patients who accepted the invitation and completed their CMD-risk profiling (feasibility).

2.
Numbers and proportions of participants who completed the comprehensive CVD-risk assessment (feasibility).

3.
Participant-reported intervention relevance, usefulness, feasibility and impact in pursuing a healthier lifestyle, along with respective barriers (evaluation). (total N=1,000). In total, less than half of invited individuals (47.4%, n=474) accepted the invitation.

Perception and barriers towards lifestyle modification
In response to the risk assessment, the vast majority of participants in the Czech Republic [ Figure 2 approximately here]

Discussion
Our study showed the substantial cross-country variations in the implementation of the selective CMD prevention intervention, as well as in participant receptiveness. These variations could be interpreted in terms of the differences between the specific primary care systems included in our study and, as such, underline the necessity for European health policies and CMD prevention strategies.
Another important finding concerns the substantial differences between study participants regarding various lifestyle factors. Participants from Greece, followed by the Czech Republic, presented the most unfavorable health profile which was also reflected in their CVD-risk scores. This finding is in agreement with the international statistics and warrants further attention (16). Remarkably, no individuals with elevated CVD risk were identified in Sweden. This may be partially attributed to the selective participation of respondents who are, often, more healthy than the average person.
However, although Sweden has no primary prevention program, another possible explanation could be that Sweden is a quick adopter of healthy lifestyle modifications as indicated, for example, by the fact that it is the first country with a daily smoking prevalence below 10% (17).
Differences were also observed in the acceptance of the selective prevention intervention, with the Czech Republic and Greece presenting the highest rates. Although these variations may be partially attributed to differences in the invitation processes implemented in each country, specifically for Greece this finding may reflect the generalized lack of systematic preventive activities provided by interdisciplinary teams in primary care, an issue reported since years (18). This may serve as a key message for health policy actions, especially in settings where coordinated reforms are evolving.
The implemented selective prevention intervention succeeded to engage 65-100% of participants in CVD-risk assessment, resulting in the identification of substantial proportions of high CVD-risk individuals (6.9-36.8%). A similar Dutch study identified 64% of participants as being at high-risk, with 22% of them classified as newly diagnosed patients suffering from various conditions such as hypertension, hypercholesterolemia, and diabetes (19). Furthermore, our intervention's usefulness and feasibility where highly scored by participants, with significant proportions indicating that they, in response to the intervention, would be willing to try a lifestyle modification program for CMD-risk reduction (82.1-92.8%). Although our results are not comparable across study sites due to contextual and procedural differences, they still contribute to the existing evidence regarding the necessity of CMD selective prevention actions within each study country.
Finally, the most commonly reported reason to change lifestyle behavior was willingness to be healthy (61.4-71.3%). This finding is consistent with a recent systematic review conducted in the context of SPIM-EU, where prioritizing and feeling responsible for one's own health were recognized as facilitators for participating in a CMD health check in primary care (20).

Strengths and limitations
The main strength of this study was that was designed to include a set of characteristics and recommendations for a selective CMD prevention program, formed on the basis of an expert consensus.
However, this study was not implemented without several limitations. Firstly, it was a descriptive study, without formal sample size calculation or statistical power to perform significance testing. As such, our study may have under-reported the true proportions of patients with increased CVD-risk.
However, the aim of the study was to report on the feasibility of implementing selective prevention, rather than to identify the magnitude of CVD in primary care. Our design also does not allow for any type of comparisons or causality determination. Moreover, the purposive selection of study sites (in four out of five settings) does not allow for a random representation of either practices or patients.
Although the overall intervention was followed in the same way in all countries, different risk assessment tools and communication strategies were used, according to the diverse local contexts.
This may affect the comparability of participation and acceptance rates, as well as participants' assessment of the intervention. However, similar patterns have been reported in literature, with participation in health checks in primary care varying widely according to activity type (e.g. response rates ranging from a low 1.2% for an online risk estimation to a high of 84% for T2DM screening) (19,20). Additionally, the selection of country-specific and locally validated risk assessment tools allowed for better adaptation of the intervention in the local contexts and aimed at enhancing their routine use in daily practice, even upon project completion. Furthermore, there are different barriers for CMD selective prevention in primary care, including structural, organizational and attitudinal factors, while the way of invitation may have a significant impact on patient participation (21).

Study implications
The action plan of the World Health Organization for the prevention and control of non-communicable diseases sets CMD-risk assessment and management among its five focus areas for priority interventions. Moreover, it acknowledges that further development of primary care services, together with public health services, is essential for improving health promotion, disease prevention, early detection and integrated care (2). The issue of an evidence-informed integration of public health and primary health care has been also discussed in local reports from Greece (22). Within this study, a directed implementation of a selective CMD prevention intervention in diverse primary care settings was conducted. Lessons learned can be used to refine similar interventions, accounting for specific factors that may influence implementation.
This study arrived timely in Europe, where strategies for CVD prevention vary across countries and

Conclusions
This study affirmed the variations in the implementation of selective prevention interventions across Europe and underlined its importance in several countries, where CMD is a major public health issue.
Findings indicate that preventive strategies need to be adapted to local contexts and adjusted to already existing programs, since their acceptance as well as potential benefit is highly dependent on that.