**3.3 Gender effect in the risk of MI in individuals with unfavourable levels of PSF**

The risk of myocardial infarction for 16 years of follow-up was slightly higher among women with high anxiety compared to men (HR = 4.19 and HR = 3.7, respectively), but the inclusion of social characteristics and age in the model increased the risk value among women to HR = 5.16 (p for all <0.05). In men, the risk in the multivariate model decreased but remained significant HR = 1.79 (**Figure 2**). A great risk share in this model was explained by age over 54; however, these associations were not statistically significant in women.

The risk of a heart attack in men with depression was 2 and in women 2.5 times higher. In the multivariate model, the risk of MI in men was reduced but remained significant, and in women with D, statistics were no longer valid. In the age group

*Sex Differences in Long-Term Trends of Psychosocial Factors and Gender Effect on Risk… DOI: http://dx.doi.org/10.5772/intechopen.99767*

**Figure 2.**

*Gender differences in risk of myocardial infarction incidence in a cohort aged 25–64 years with anxiety traits, depression, vital exhaustion, hostility and low social support. Abbreviations: CI- confidence interval; ICC – Index of close contacts; MI- myocardial infarction; SNI – Social network index.*

of 55–64, the risk of MI was highest in men (HR = 6.8) and women (HR = 6.3). Marital status "single" (HR = 6), primary education (HR = 3.2), and manual labour (HR = 6.7) were predictors of high risk of MI in men with D (p for all <0.05). No such associations were found in women.

A recent publication of the ESC 2018 working group cites several studies concerning sex differences in the risk of coronary heart disease (CHD) and CVD mortality [9]. Studies of young population samples (under 40) found that the effect of depression on the risk of CHD was higher among women than in men. In the NHANES III study, a history of major depression was associated with an almost 15 fold increased risk of CHD in women and 3.5-fold in men [29]. This confirms our earlier findings [30], but in our present study, the sex differences were not as significant in risk.

In the simple risk model, VE did not affect the development of MI in women, whereas in men it was 2 times higher compared to those in whom vital exhaustion was not found. The multivariate model reduced the magnitude of risk after adjusting for socio-demographic characteristics, but the statistical significance for men remained the same. Living out of wedlock, age over 44, and blue-collar occupations were associated with a 3–7-fold increase in risk for men. Divorced status in women also increased the risk of myocardial infarction (5 times higher).

In our study, the moderate to high levels of hostility reduced the risk of MI by 70%. However, some social characteristics changed this ratio unfavourably. Living out of wedlock has been associated with the risk of MI in men who demonstrate hostility. The increase in risk was particularly significant among the widowed (12 times higher). Primary education and age over 44 also increased the risk of MI. Executive positions combined with hostility is associated with a 9-fold increased risk of MI compared to engineering professions. No significant associations and effects on the risk of MI in women with hostility during the 16-year follow-up period were found.

A recent meta-analysis assessing the impact of hostility showed that anxiety, depression, and psychological stress, but not anger or hostility, were associated with CHD risk in women. In men, on the contrary, anger is one of the leading psychosocial risk factors for cardiovascular events [31]. Our study complements these conclusions by showing that the risk of IM is manifested only in a certain social environment.

The risk of MI in individuals with low indices of close contacts and social ties was significantly higher but did not differ significantly depending on sex, slightly predominating in men. At the same time, the lack of close contacts increased the risk more significantly (5 times), rather than a poor social network (3 times). Interestingly, the multivariate model practically did not weaken the risk of MI in

women, which increased significantly among women with low ICC and primary education (HR = 15.4). In men, primary education had a comparatively smaller effect on risk, giving preference to age, living out of wedlock (single, divorced, widowed status), and having an engineering or technician occupation, or physical labour. Similar associations were found for the social network index (SNI) in the multivariate model, where the risk of MI was higher in women compared to men. In contrast to close contacts, the lack of social connections combined with age, primary education and physical labour increased the risk of MI 3-3.7 times in women. For men, such factors as marital status "single", age, primary education, and physical labour remained significant. Importantly, low SNI combined with a mid-level executive position also increased the risk of MI (2.5 times). A similar effect was not observed in women.
