Cardiovascular disease (CVD) remains the leading cause of premature death in Europe. Unhealthy lifestyles and psychosocial burden are commonly associated with CVD, and not surprisingly, most of its mortality is preventable through appropriate changes in lifestyle.1 It is well established that psychosocial risk factors interact with biomedical vulnerabilities in the development of CVD, and approximately one third of the attributable risk of acute myocardial infarction can be related to major life events, depression or stress related to work, family or finances. Furthermore, when several psychosocial risk factors cluster in the same individual, the risk for both cardiac events and severe atherosclerosis is substantially increased.2

Men and women have similar biomedical risk factors for CVD, but their relative weight and impact on the pathophysiology of the disease differ markedly.3 Prevention strategies could benefit from taking these risk profile differences into account. Further, gender differences in both disease progression and impact of risk factors could explain why prevalence rates, symptom profiles and medical outcomes still have different prevalences between genders.4,5 Specifically, women with ischemic heart disease have worse outcomes than men regardless of age,4 but usually present much less severe anatomical obstructive lesions and better preserved systolic function.4,6 Clearly, other factors are at play in this apparent contradiction.

It is well established that psychosocial factors such as negative affect and personality traits can increase the risk for CVD.2 However, it is unknown whether they also impact cardiovascular health differentially by gender, thereby contributing to higher CVD morbidity and mortality among women. Specifically, depression is an established risk factor for both CVD patients and healthy individuals, increasing both cardiac morbidity and mortality,7–9 while anxiety has been identified as an independent risk factor for CVD in the community.10,11 Similarly, type D personality is a stable personality construct marked by negative affectivity and social inhibition that combine to produce sustained high levels of mental distress and increased physical symptoms in both CVD patients and healthy participants.12–14 Overall, these psychosocial factors have been consistently linked to CVD risk, but little progress has been made in examining their differential impact by gender.

Self-reported health is an independent predictor of overall and cardiovascular mortality in most studies, and individuals who assess their health as fair or poor have a higher mortality risk than those whose assessment is better.15,16 Moreover, after controlling for sociodemographic characteristics, health care access and risk factors, self-reported health is still a significant and independent predictor of both global morbidity onset15 and CVD incidence.17,18 Specifically, the Medical Outcomes Study Short Form (SF-36) has been shown to predict mortality in community samples.19,20 In particular, the physical component summary of the SF-36 (derived from the sum of scores obtained on the physical functioning, role-physical, bodily pain and general health subscales) exhibits a strong association with mortality, estimates being independent of other physical factors like obesity, physical inactivity or a low-fiber diet.19,20

This study aimed to assess how gender patterns of known cardiovascular risk factors (biomedical and psychosocial) influence self-reported quality of life in a sample of primary health care users without a CVD diagnosis. To the best our knowledge, this study is pioneering in bridging these two important issues.

This study sought to examine how gender patterns of cardiovascular risk factors associate with self-reported quality of life in a sample of primary health care users without a CVD diagnosis. Our main findings pinpointed gender differences in risk factors mostly related to participants’ life style and mental/affective status. Specifically, women revealed significantly lower rates of alcohol consumption and exercise but presented more depressive symptoms and negative affectivity. In agreement with these findings, a history of antidepressant use and psychiatric referrals was also more common among women. Further, our multivariate analysis expanded these findings to confirm most of these risk factors as independent correlates for females.

Interestingly, traditional biomedical CVD risk factors, such as smoking, hypertension, diabetes and dyslipidemia, did not differ between genders. This finding partially supports the hypothesis of a different pathophysiological impact of CVD risk for female gender, possibly through the deleterious action of psychosocial risk factors like those mentioned above. In line with this suggestion, the quality of life assessment for female participants indicated overall poorer health and well-being, despite the absence of any objective gender difference in biomedical risk factors, which is in agreement with other studies that also reported lower quality of life scores for women.28

It is still not fully understood how educational level can influence the risk for CVD. Several studies have examined this and suggest that education partially affects this risk through increased prevalence of CVD risk factors at lower educational levels.29 In our study, despite the high educational level of the participants, we found a relatively high prevalence of risk factors which are mostly lifestyle dependent. We cannot exclude the possibility that our high educational level sampling masked any latent differences in traditional CVD risk factors. However, 36.1% of the women in our study did not exercise at all, which is higher than expected as studies have shown that lower education or occupation levels are usually associated with a higher prevalence of sedentariness among women.30 Also, no gender differences were found in smoking patterns, with the majority of participants being non-smokers. This follows the trend of western populations, where the prevalence of smoking is declining for both genders and increasing in lower social classes.31

Women had a prevalence of depressive symptoms that was more than twice that reported by men. In addition, psychiatric referrals and antidepressant use were also more prevalent among women. These data are in line with previous evidence showing that women are about twice as likely as men to experience depression.32 In addition, 22.3% of men and 25.9% of women were classified as anxious according to the HADS-A. This finding is apparently at odds with studies indicating a protective effect of educational level against anxiety and depression,33 but it might derive from an overall young sample. Finally, the prevalence of type D personality was similar between genders, replicating previous research.34,35 Nevertheless, women did score significantly higher than men on the negative affectivity subscale of the DS14, which has been considered elsewhere as a key predictor of worse subjective health outcomes.36

This study examined how gender patterns in CVD risk influence self-reported health and quality of life perception. Women reported significantly worse levels of well-being and health across most subscales of the SF-36 questionnaire, with the exception of the general health subscale (for which scores did not reach statistical significance, although they were still lower). Based on the findings of others,15,17,18 this could indicate that, in this study, women faced a higher risk for cardiovascular morbidity and mortality. Firstly, recent evidence indicates that poor self-rated health is strongly associated with cardiovascular mortality, irrespective of prior CVD,16 and with the incidence of coronary heart disease.17,18 Secondly, the physical health component of the SF-36 has been specifically identified as a strong predictor of CVD incidence and death in post-menopausal women.20 Thirdly, although the mechanisms underlying this association remain speculative, the fact is that the SF-36 physical health component exhibits a strong association with mortality, while this effect is independent of other risk factors like obesity, physical inactivity or diet.19,20

Among the gender distinctiveness apparent in the multivariate linear regression profiles of the quality of life scores, role limitations due to physical problems (‘role-physical’) and more pain complaints (‘bodily pain’) were predicted by psychosocial risk factors such as depression and negative affectivity in women, whereas in men these two dimensions appear to depend more on biomedical factors such as diabetes, hypertension, exercise and chronic illness. A recent study with healthy participants found that type D personality was significantly associated with lower quality of life and more physical symptoms, with the negative affectivity component standing out as the key predictor of subjective health outcomes.36 In our study, high negative affectivity was a strong independent predictor of worse general health for women, whereas high social inhibition and high anxiety had a comparable role for men. These results are worth highlighting given the predictive value of the SF-36 physical health component for CVD mortality and morbidity. Indeed, this distinct gender pattern may be the key to the differential impact of psychosocial risk factors on CVD risk, and should therefore be examined.

This study involves a population with highly specific characteristics, which is relevant for the following reasons. Firstly, our participants were relatively young and had a high educational level. While this requires caution regarding the generalization of findings to other populations, the fact is that studies aiming to enhance CVD prevention tend to be conducted with increasingly young samples.37,38 Secondly, our investigation followed an observational cross-sectional design, which precludes any generalization concerning longitudinal trends of the associations found. Thirdly, most of the data collection relied on self-reporting, hence reflecting the individual's assessment of currently experienced symptoms. Although memory bias could have distorted the data, such an effect is likely to be reflected similarly within the whole sample. Finally, multivariate analyses of quality of life scores were conducted separately by gender. On the one hand, sample size was limited in order to run meaningful multivariate linear regression comparisons between genders. On the other hand, the available evidence regarding self-rated health by gender is still inconsistent, with studies indicating no differences,39 a tendency for men to assess their health more positively than women,28 or even the opposite.40

This study shows that community participants without documented CVD present gender-specific patterns of CVD risk factors and that these impact quality of life differentially. In our view, these gender specifics need to be considered in health prevention strategies, given the predictive value of quality of life for cardiovascular morbidity and mortality.

The lead author received funding from Fundação para a Ciência e a Tecnologia in the form of a PhD grant (SFRH/BD/70327/2010). The other authors have no conflicts of interest to declare.