EDITORIAL: PSYCHOCARDIOLOGY IN SOCIALLY DISADVANTAGED GROUPS

Don Byrne^1*Marlies Alvarenga²Kai G. Kahl³

• ¹Australian National University, Canberra, Australia
• ²Federation University Australia Institute of Health and Wellbeing, Ballarat, Australia
• ³Medizinische Hochschule Hannover, Hanover, Germany

inadequate or unavailable housing. An Oxford Research Briefing on Disadvantaged Groups (undated) adds low income and poverty, discrimination (racial, ethnic and sexual) and gender to the potential drivers of SD. And the review goes on to suggest that manifest SD may impose barriers on such essentials as education, health care and employment. Moreover, as we have earlier suggested, domains of disadvantage are unlikely to exist as absolutes but may be seen as statistical cascades and gradients, accumulating over time and impacting onto the ultimate risk of CVD (Krokstad et al, 2016;Hahad et al., 2024). Thus, while socio-economic disadvantage -poverty, as Kennedy (2023) sees it in its most extreme form -offers a strong starting point to consider aspects of the social environment as constituting health risks, it is now clear that socio-economic disadvantage alone is too simple a metric to account for how SD as a more refined construct may endow elevated risk of CVD.At a population level, the Australian Institute of Health and Welfare (AIHW) published a major report in 2019 drawing on census data from the entire Australian population to persuasively argue that socioeconomic disadvantage (so-called, since the overall metric also included measures of education and of housing suitability and tenure, as well as income alone) had a significant negative effect on both CVD morbidity and mortality, and in both men and women.In the light of the brief discussion presented above, three questions have immediately begged our attention.First, we asked, can SD, broadly defined, influence risk of CVD through the intervening effect of already historically identified risk factors (RFs) for CVD? Here, the recent evidence is voluminous. SD has been individually (negatively) linked to diabetes (Hill-Briggs et al., 2021), Chatuvedi et al., 2024), dyslipidemia (Espirito Santo et al., 2022), obesity (Carroll et al., 2023;Anekwe et al., 2020), and smoking (Denney, Sharp & Kimbro, (2022) 2022) such that manifest SD is statistically coupled with elevated levels of CVD RFs. SD has also been multi-variately related to a collective basket of historical RFs including arterial hypertension, Body Mass Index (BMI) and obesity, dyslipidemia, and smoking (Dumitrescu et al (2024). It seems undeniable then that reported links between SD and CVD may arise through the intervening influence of one or more of a set of historically identified RFs for CVD.Second, we asked, can SD create a social environment which, in turn, elevates risk of CVD?There is good evidence (Jamalishahmi et al., 2023) that SD is closely linked to social isolation and loneliness, and that this psychosocial condition elevates risk of CVD (Golaszewski et al., 2021). We see this as another plausible hypothesis to link SD with CVD.And thirdly, we asked, could SD influence the risk of CVD through the intervening effects of emotional distress. Good evidence (Learnihan et al., 2022) now supports the view that SD elevated the risk of depression, and that depression in turn is now undeniably linked to a high risk of CVD (Kwapong et al., 2022;Krittanawong et al., 2023). Once more, a creditable (albeit indirect) link between SD and CVD is clearly indicated.Of course, it is well beyond the scope of this Editorial to do full justice to examining all the potential drivers of disadvantage in relation to CVD risk. The corpus of existing literature is enormous, and it would take a volume of significant size -and perhaps more -to achieve this. Rather, it is the intention of this brief narrative to underscore the true complexity of what, on the surface, might appear to be a simple link between SD and CVD. And in doing so we have striven to provide a suitable context for the original works which have been presented for publication in this Special Issue of Frontiers in Psychiatry.Recognising the complex bio-psycho-social network which associates SD with CVD then, five original papers have been published in the Special Issue. Schaefer et al have demonstrated that those with Borderline Personality Disorder (BPD) are inordinately prone to elevated epicardial adiposity, and through this, to a potentially elevated risk of CVD. In the light of an historically established association between BPD and SD, the implicit link to SD and CVD risk is clear.Kennedy has persuasively argued that SD is linked to sleep insufficiency, and through that potential mechanism, to elevated risk of CVD. Friedman et al have reported associations between obesity and distress/depression, and thence hypothetically to an elevated risk of CVD.And as we have noted earlier in this editorial, obesity has an historically established association with SD, thus drawing SD into play in this complex network of CVD risk. Kirchberger et al have shown that a significant number of survivors of incident CVD experience distress and depression on the 5-year post-incident period, and many of these exhibit poor mental health literacy (MHL). Among those, the elderly and poorly educated -very characteristic of SDhave the poorest MHL. It would be interesting to see whether these people went on to experience elevated levels of repeat incident CVD. And finally, Accinni et al have told us that those suffering from supraventricular tachyarrhythmias (STs) not infrequently suffer from comorbid demoralisation. Demoralisation is also associated with SD and, via postulated links with depression, may also presage elevated risk for CVD.It is with pleasure, therefore, that we can recommend each of these persuasive new works as further evidence of the now emerging, if albeit complex, association between SD and CVD.