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. 2024 Mar 7:11:1308337.
doi: 10.3389/fcvm.2024.1308337. eCollection 2024.

The heart-mind relationship in women cardiovascular primary prevention: the role of depression, anxiety, distress and Type-D personality in the 10-years cardiovascular risk evaluation

Affiliations

The heart-mind relationship in women cardiovascular primary prevention: the role of depression, anxiety, distress and Type-D personality in the 10-years cardiovascular risk evaluation

Mattia Giuliani et al. Front Cardiovasc Med. .

Abstract

Introduction: Cardiovascular diseases are the leading cause of death among women. Prevention programmes underscore the need to address women-specific risk factors. Additionally, mental well-being is a significant aspect to consider when grappling with cardiovascular disease in women, particularly depression, anxiety, distress, and personality traits. This study aimed to create "at-risk" psychological profiles for women without prior cardiovascular disease history and to evaluate the association between anxiety, depression, distress, and Type-D personality traits with increased cardiovascular risk over 10 years.

Methods: 219 women voluntarily participated in the "Monzino Women's Heart Centre" project for primary prevention and early diagnosis of cardiovascular diseases. Psychological profiles were developed utilising cluster analysis.

Results: The primary finding indicating that belonging to the "at-risk" psychological cluster was associated with a surge in the 10-year cardiovascular risk prediction score, despite the number of comorbid risk factors (Psychological "at-risk" cluster: β = .0674; p = .006; Risk factors: β = .0199; p = .242).

Conclusions: This finding suggests that psychological well-being of women should be assessed from the very beginning of cardiovascular prevention programmes.

Keywords: Type-D personality; anxiety; cardiovascular prevention; depression; distress; gender medicine.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Scree plot for k-means clustering of psychological data. The scree plot shows how Within-Cluster-Sum of Squares (WSS) changes as a function of the number of clusters identified using the k-means algorithm. The elbow method identified an optimal number of clusters equal to two, the point at which the graph shows a distinct change in slope.
Figure 2
Figure 2
Classic and women specific RF trends in PR and NPR clusters.

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