Cardiovascular risk in young healthcare professionals: A cross-sectional study

1 Introduction

Cardiovascular disease (CVD) is a general term that describes a disease of the heart and blood vessels [1]. The World Health Organization (WHO) approximates an annual global CVD-related mortality rate of 17.9 million individuals, constituting about 32% of total worldwide deaths [1]. Within Italy, CVDs persist as the primary cause of mortality, attributing to 34.8% of all recorded deaths [2]. Risk factors (RFs) for CVDs include high blood pressure, tobacco use, raised blood lipids, and diabetes, physical inactivity, and excessive use of alcohol [1]. Research has shown that the adoption of appropriate lifestyle changes could mitigate over 75% of fatal CVD occurrences [3].

In order to be able to adopt specific therapeutic interventions as part of primary prevention, it is useful to have a simple and straightforward tool to assess the cardiovascular risk (CVR) in an individual. Several CVR calculation scores that aim to assess the likelihood of developing a cardiovascular event (CVE) in the future can be found in the literature, including the Framingham risk score and the CUORE score.

The progress made in the prevention and treatment of CVDs over the last 40 years have led to a 40% reduction in mortality from these diseases. However, this reduction seems to have subsided despite optimal treatment of traditional RFs. Up to 50% of patients with known coronary artery disease have recurrent cardiac events, such as myocardial infarction and sudden cardiac death, even with aggressive treatment against traditional RFs. This evidence suggests that further interventions, particularly those implemented against non-traditional RFs, could be useful in continuing the reduction of cerebrovascular events.

In the past two decades there has been an increase in the prevalence of overweight or obesity among young adults resulting in the development of an ascending unhealthy cardiovascular profile [4–9]. Furthermore, e-cigarette use, substance abuse, and rates of diabetes have increased in this population [10–12]. Trends in the incidence of CVDs in the las two decades show a decrease in the elderly while are mostly stable or slightly increasing in young adults [13] which may result in an increased burden of CVDs in the future if appropriate strategies are not put in place.

Shift work is associated with increased risk of cardiovascular diseases or cardiovascular risk factors, such as diabetes (increase of about 10%), overweight (increase of 25–38%), obesity (increase of 5–18%) [14] and healthcare workers (HCWs) are continuously exposed to shift work, high demand from the superiors and the patients, and high levels of physical and mental stress which exposes them to a high risk of a cardiovascular event. Despite these findings, scant attention has been directed towards the exploration of CVR among young HCWs. Therefore, the present study aims (i) to calculate CVR at ten years in HCWs at the teaching hospital Policlinico Umberto I of Rome, using two different scores. The choice of the HCW category was due to the possibility to start a follow-study due to the availability of surveillance health checks. Moreover, we aimed at (ii) identifying the associated factors, in order to design and implement interventions in the workplace to reduce this risk.

2 Methods

3 Results

Table 1 summarizes the characteristics of the study population.

A total population of 638 HCWs who had undergone a medical visit by the occupational medicine service in the period considered had all the clinical records needed for this study. Of them, 525 met the inclusion criteria of age and were included in the study. As for occupation, the most represented category is physicians (58.5%) followed by nurses (32.1%).

3.2 Cuore score

The histogram depicted in Fig. 1 shows the distribution of CVR in the study population, regardless of gender. As can be seen from this histogram, the majority of participants (519 participants, i.e. 98.9% of the sample) has a risk of less than 1% of having a CVE in the next ten years.

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Fig. 1

Risk of cardiovascular event calculated at 10 years using the CUORE score.

3.2.1 Multivariate analysis

For the same reason, as noted before, a multivariate analysis was carried out only for men. Using the linear regression model, as can be seen from Table 4, qualification as a physician (p < 0.001) is associated with a lower risk of having a CVE in the next ten years, while age (p < 0.001) is directly proportional to this risk (Table 4).

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Table 4

Multivariate analysis of cardiovascular risk using CUORE score for males

	Full model	Stepwise model
	β (p) standardized	β (p) standardized
Shift worker	0.009 (0.879)	–
Physician	–0.098 (0.243)	–0.116 (0.037)
Nurse	0.022 (0.801)	–
Age	0.715 (<0.001)	0.720 (<0.001)
R2	0.716	0.716

The goodness of fit using the R² were high for both models (0.26 and 0.716). The assumptions for linear regression indicated a non-violation only for the models carried out for males (Annex 1).

In this study, we calculated the risk of having a CVE at ten years among healthcare workers aged 20–40 years at the teaching hospital Policlinico Umberto I through two scores, the Framingham score and the CUORE score.

Using the Framingham risk score, we found that there is a significant difference between women (median 1%) and men (median 3%), the latter having a higher CVR. In fact, the female population has a CVR within the limits of the average CVR calculated by age while in the male population it appears that about 15% have a higher CVR than the average CVR calculated by age [20]. This issue is an important issue to consider in interpreting our results. The distribution of the risk scores was not normal for the whole population, especially for the contribution of females. This result is in line with data from other studies in the literature. Actually, it is well known that the incidence of CVD is low in premenopausal women and increases after menopause. Indeed, the transition to menopause is associated with a worsening of CVR [21]. The endogenous estrogen plays a protective role against atherosclerotic manifestations during childbearing age [22]. In premenopausal age the rate of CVE in women is low and is mainly ascribed to smoking [23]. From the methodological point of view, some authors have explored the possibility that adding female-specific factors to models containing established cardiovascular risk factors could have been a tool for improve the prediction of cardiovascular events. However, they demonstrated that doing this improved a little bit the prediction and in a non-significant way [24].

We need to recognize that traditional risk assessment tools, such as the Framingham Risk Score, can underestimate in a significant way the risk in women, just classifying women as having a low risk for CVD, and other factors are needed to improve the assessment, including autoimmune conditions (i.e., systemic lupus erythematosus, rheumatoid arthritis). depression and other psycho-social factors [25].

Furthermore, data obtained from the first analysis of the lifetime risk of developing coronary heart disease in the general population produced by the Framingham Heart Study showed that the risk of developing Acute Myocardial Infarction at the age of 40 has been calculated. This risk is 1 in 2 for males and 1 in 3 for females. The difference is confirmed, although attenuated, at age 70 where the risk is 1 in 3 for males and 1 in 4 for females [26].

Another factor found to lead to an increase in RCV is night shifts. In the literature, there are numerous studies that have evaluated this correlation, also due to the progressive increase in shift work. In fact, it has been reported that up to one-third of the workers in Europe and in the United States are employed in shift working [27], and this trend is increasing [28]. Shift work increases the risk of CVDs through several pathways, including disruption of circadian rhythm, lifestyle changes, workplace tension, and social stress, [27, 29–31].

A recent meta-analysis[26] performed a quantitative dose-response assessment between the duration of shift work and morbidity and mortality from cardiovascular causes. A 5-year increase in shift work was shown to be associated with a 5% increase in the risk of developing CVD, and a 6% and 4% increase in the risk of morbidity and mortality from cardiovascular causes, respectively. The authors concluded that shift work could increase CVR in a dose-responsive manner, which has never been reported, including CVD morbidity and mortality.

Another point to underscore is the influence of increasing age in increase the risk, calculated using both the Framingham and the CUORE score, and this is in line with the scientific literature. This issue needs to be considered with care, since large proportion of adults are not adequately classified for primary prevention of CVD, due to their low of very low short-time predicted CVD risk, and there is evidence of the utility of using lifetime risk [32].

In our analysis, a direct relationship between CVR and age was seen, i.e., as age increases, CVR also increases (β = 0.104 and p < 0.001). In fact, age is one of the non-modifiable, well-known RFs with regard to CVDs due to its effect on the arterial system and the heart [33].

With regard to the calculation of CVR with the CUORE score, it was found that the majority of the participants had a risk of having a CVE in the next ten years between 0.25% and 0.75%, with 98.9% of the sample having a risk of less than 1% and an average of this risk for the entire study population of 0.73%. The multivariate analysis carried out for males showed that, using the CUORE score as the dependent variable, physicians (β = -0.116; p = 0.037) were associated with a lower risk of having a CVE in the next ten years, while age was directly proportional to this risk (β = 0, 720; p < 0,001). On the other hand, using the Framingham score as the dependent variable, the only variable associated to the increasing of the risk was age (β = 0, 260;p < 0,001).

To our knowledge, there are two studies that have assessed CVR in HCWs using the FRS. One of them [34] did not assess risk by job category while the other study [35] reported an increased risk for doctors compared to nurses, however, these results were not statistically significant. Other studies that have investigated cardiovascular RFs among HCWs have reported greater occurrence among doctors than nurses [36, 37], in contrast to what we found using the CUORE score. Furthermore, a recent systematic review [38] reported that although physicians were more aware of their cardiovascular RFs, they were more prone to obesity and cardiovascular disorders and more at risk than nurses.

A similar study was conducted by Gonzalez-Velàzquez and Mendez in 2007 in Veracruz, Mexico [39]. In this study, CVR was calculated using the SCORE system in a population of 96 HCWs under 40 years of age and found that 14% of these participants had a 10-year CVR greater than 2% (which is twice what is expected in a young population of HCWs) and 51% of the population had a risk less than 1%.

Considering the fact that CUORE score, unlike the Framingham risk score, (I) did not identify shift work as a risk factor for CVDs, as has been well documented in the literature [28, 40–42], and (II) found that physicians have a lower risk of CVE than nurses while several studies in the literature suggesting the opposite although there is not a clear consensus [35–38, 44], we think that FRS presents a better fitting for measuring CVR in this particular group of HCW population.

This study has strengths and weaknesses.

The weaknesses are related to the methodology of the study. In fact, we were able to measure CVR in HCWs but cause-and-effect relationships cannot be determined. Also, being carried out in a specific Roman hospital, the results are not generalizable. Finally, we can mention selection bias as only young HCWs that had scheduled a visit in the period considered were included in the study.

We need to recognize that the provided P-P plots and scatterplot of the standardized predicted dependent variable against the standardized residuals, either for Framingham risk score and CUORE risk score (not transformed) show that the residuals from the two multiple linear regression models are not normally distributed for the whole population under study (males and females together). However, the model with only males for both scores (Framingham and CUORE) as dependent variables indicates that the residuals are not heavy tailed, which means that the outliers are more or less what we would expect in a normally distributed dataset.

This is the first study in Italy to evaluate CVR in healthcare workers and, in particular, in young healthcare workers. This study can be a starting point for subsequent evaluation of CVR over the years in order to identify RFs and plan targeted interventions with the aim of reducing this risk.

Other strengths are the large number of healthcare professionals who participated in the study and the reduction in response bias related to the methodology used.

5 Conclusions

In conclusion, we found a higher cardiovascular risk among male healthcare workers compared to the average cardiovascular risk calculated by age and in shift workers, while females have a cardiovascular risk within the limits. It is interesting to underline that we found a lower cardiovascular risk among Doctors (using the CUORE score as a dependent variable). It is plausible that future studies that compare the difference between these scores can be useful for helping researchers to choose the most appropriate one. Over the past two years, healthcare personnel have faced a constant barrage of intense physical and psychological strain, primarily stemming from the ongoing pandemic. This unrelenting pressure places them at a significant vulnerability to experiencing cardiovascular incidents. Healthcare organizations should put attention into protecting health professionals from the risk of cardiovascular events. Scheduled frequent visits should be implemented especially in those at higher risk. This study can be a starting point for subsequent cardiovascular risk assessment over the years in order to identify risk factors and plan targeted interventions to reduce this risk.

Funding

This research received no external funding.