ஆரோக்கியமான வயதான ஆராய்ச்சி
திறந்த அணுகல்

சுருக்கம்

Intimate partner violence and the risk factors for cardiovascular disease in women: A review of the preponderance of the literature evidence

Rose Constantino

Background: Data surrounding intimate partner violence (IPV) and risk factors for cardiovascular disease (CVD) in women are global health and social problems. IPV is a spectrum of abuse experienced in acute and chronic instances. Globally, 35% of women report experiencing IPV in their lifetime. In the United States, 1 in 4 women dies from cardiovascular disease, making it the leading cause of death in women. A literature review of the pathways between CVD and IPV in women may further demonstrate the biopsychosocial factors that mediate a link between the two chronic illnesses for healthcare providers to develop prevention and intervention programs for both occurrences. Purpose: This paper examines the relationship between intimate partner violence (IPV) experience and cardiovascular disease (CVD) and determines if there is a preponderance of literature evidence. Methods: We reviewed research on the different biopsychosocial factors affecting the relationship between IPV and CVD of women. Results: As a result of our review of the literature, we formed a framework on the biopsychosocial pathway of IPV as a risk factor for CVD in women. Our proposed framework portrays how IPV experiences contribute to long-term biopsychosocial changes that increase the risk of CVD among female survivors. These biopsychosocial changes include chronic inflammation and hypothalamus-pituitary-adrenal axis dysfunction, metabolic or endocrine dysfunction, and mood symptomatology. Implications: Because gender disparities exist when examining CVD risk and development, the correlation between IPV and CVD risk in women needs to be explored. Conclusions: The Biopsychosocial Pathway of IPV and CVD and the Three Levels of Prevention conceptual framework, could provide a theoretical foundation and science for further research in developing algorithms on the relationship between IPV and CVD.