Health: Understanding the links between cardiovascular and psychiatric conditions
Individuals recently diagnosed with a cardiovascular disease are at higher risk of developing a mental illness, with mortality increasing when both conditions are present.
- Dalla Lana School of Public Health, Epidemiology Division, University of Toronto, Canada
- Centre for Global Health, Dalla Lana School of Public Health, University of Toronto, Canada
Cardiovascular diseases are the leading cause of mortality worldwide, accounting for approximately 32% of all deaths globally. Mental illnesses are similarly common, with approximately one in every eight individuals living with a mental health disorder in 2019 (World Health Organization, 2022). Given their high prevalence, these conditions are likely to exist alongside each other and this co-occurrence warrants rigorous scientific investigation.
The relationship between heart disease and mental illness is complex and bidirectional. For example, being diagnosed with heart failure can understandably cause stress and despair, and consequently elevate an individual’s risk of developing a major depressive disorder (Hare et al., 2014). Conversely, depressive disorders are known to manifest as sleep disturbances, reduced levels of physical activity and difficulty following health recommendations — all factors linked to an increased likelihood of developing cardiovascular conditions.
Evidence exists that the risks for mental and cardiovascular diseases increase in tandem (Schöttke and Giabbiconi, 2015; Ziegelstein, 2001). However, this body of work has important limitations that hinder drawing meaningful conclusions. For example, some studies only capture patient information at a single point in time, making it difficult to establish whether it was the cardiovascular or the psychiatric condition which appeared first in individuals with both illnesses (Almhdawi et al., 2021). In addition, research in this area has mainly focused on the relationship between cardiovascular health and depression or generalized anxiety disorder, with little attention paid to other psychiatric conditions such as psychosis and bipolar disorder. Lastly, no studies have so far adequately accounted for family-related mechanisms that may be driving any observed associations, such as certain genetic backgrounds or early childhood environments. Now, in eLife, Unnur Valdimarsdóttir, Qing Shen and colleagues report the results of a study designed to address some of these limitations (Shen et al., 2022).
The team (who are based in China, the United States, Iceland and Sweden) used the Swedish Patient Register to identify nearly 0.9 million individuals recently diagnosed with cardiovascular disease, and with no prior history of psychiatric disorders. Throughout the study period, these patients were then followed until they first received a mental health diagnosis within the study period. In addition, the study included a remarkable family-comparison design, whereby participants’ siblings who had no mental health or cardiovascular conditions at the time of the diagnosis were also tracked over time. The risk of developing any psychiatric condition in both patients and siblings could therefore be compared. This approach allowed Shen et al. to control for familial factors that are often difficult to measure and, if left unaccounted for in study design, could contribute to a spurious association between cardiovascular disorders and subsequent mental illness.
The results indicate that, compared to their unaffected siblings, study participants were 2.7 times more at risk of developing a psychiatric disorder within a year of having received their diagnoses of cardiovascular illness (even after accounting for familial factors, prior history of psychiatric illness and sociodemographic variables such as age, sex or socioeconomic status). Similar associations were observed when study participants were compared to non-sibling controls. In addition, individuals who developed a psychiatric disorder during that first year had a 55% increased risk of dying from a heart-related condition compared to patients who retained good mental health. In this cohort, the co-occurrence of any mental illness therefore negatively impacted the course of cardiovascular diseases.
Despite its strengths, this work also has some limitations. Notably, smoking behaviour and alcohol consumption were not adequately controlled for, despite being directly and independently associated with cardiovascular disease and mental illnesses (Dani and Harris, 2005; Mukamal, 2006). Not accounting for either of these lifestyle factors could overestimate the true relationship between these two conditions. In addition, various psychiatric subtypes with distinct phenotypes were combined — for example, all types of anxiety conditions, from generalized anxiety to post-traumatic stress disorder, were merged into a single mental health outcome. Each of these disorders is likely to have specific associations with cardiovascular health, which could not be captured by this experimental design.
The work by Shen et al. highlights how important it is to monitor psychiatric symptoms while treating cardiovascular diseases. Their findings should encourage the scientific community to fill existing knowledge gaps. In particular, it is becoming increasingly clear that evidence derived from high-income countries, where most research is conducted, cannot be directly translated to other settings. For instance, age-standardized mortality rates for cardiovascular disease are mostly decreasing in European and North American populations, while suicide mortality (as an indicator of mental health burdens) rises with age. By contrast, cardiac mortality rates are rising in certain low- and middle-income countries such as Mexico and India, with suicide mortality occurring at younger ages (Reynales-Shigematsu et al., 2018; Ke et al., 2018; World Health Organization, 2022; Phillips and Cheng, 2012). Context-specific data will therefore need to be collected for cardiovascular diseases to be appropriately managed across the world through integrated healthcare approaches.
References
-
Post-stroke depression, anxiety, and stress symptoms and their associated factors: a cross-sectional studyNeuropsychological Rehabilitation 31:1091–1104.https://doi.org/10.1080/09602011.2020.1760893
-
Nicotine addiction and comorbidity with alcohol abuse and mental illnessNature Neuroscience 8:1465–1470.https://doi.org/10.1038/nn1580
-
Depression and cardiovascular disease: a clinical reviewEuropean Heart Journal 35:1365–1372.https://doi.org/10.1093/eurheartj/eht462
-
The effects of smoking and drinking on cardiovascular disease and risk factorsAlcohol Research & Health 29:199–202.
-
The changing global face of suicideLancet 379:2318–2319.https://doi.org/10.1016/S0140-6736(12)60913-1
-
Post-stroke depression and post-stroke anxiety: prevalence and predictorsInternational Psychogeriatrics 27:1805–1812.https://doi.org/10.1017/S1041610215000988
-
Depression after myocardial infarctionCardiology in Review 9:45–51.https://doi.org/10.1097/00045415-200101000-00009
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Sonali Amarasekera
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© 2022, Amarasekera and Jha
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Health: Understanding the links between cardiovascular and psychiatric conditions
eLife 11:e84524.
https://doi.org/10.7554/eLife.84524
Further reading
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- Epidemiology and Global Health
Background:
Biological aging exhibits heterogeneity across multi-organ systems. However, it remains unclear how is lifestyle associated with overall and organ-specific aging and which factors contribute most in Southwest China.
Methods:
This study involved 8396 participants who completed two surveys from the China Multi-Ethnic Cohort (CMEC) study. The healthy lifestyle index (HLI) was developed using five lifestyle factors: smoking, alcohol, diet, exercise, and sleep. The comprehensive and organ-specific biological ages (BAs) were calculated using the Klemera–Doubal method based on longitudinal clinical laboratory measurements, and validation were conducted to select BA reflecting related diseases. Fixed effects model was used to examine the associations between HLI or its components and the acceleration of validated BAs. We further evaluated the relative contribution of lifestyle components to comprehension and organ systems BAs using quantile G-computation.
Results:
About two-thirds of participants changed HLI scores between surveys. After validation, three organ-specific BAs (the cardiopulmonary, metabolic, and liver BAs) were identified as reflective of specific diseases and included in further analyses with the comprehensive BA. The health alterations in HLI showed a protective association with the acceleration of all BAs, with a mean shift of –0.19 (95% CI −0.34, –0.03) in the comprehensive BA acceleration. Diet and smoking were the major contributors to overall negative associations of five lifestyle factors, with the comprehensive BA and metabolic BA accounting for 24% and 55% respectively.
Conclusions:
Healthy lifestyle changes were inversely related to comprehensive and organ-specific biological aging in Southwest China, with diet and smoking contributing most to comprehensive and metabolic BA separately. Our findings highlight the potential of lifestyle interventions to decelerate aging and identify intervention targets to limit organ-specific aging in less-developed regions.
Funding:
This work was primarily supported by the National Natural Science Foundation of China (Grant No. 82273740) and Sichuan Science and Technology Program (Natural Science Foundation of Sichuan Province, Grant No. 2024NSFSC0552). The CMEC study was funded by the National Key Research and Development Program of China (Grant No. 2017YFC0907305, 2017YFC0907300). The sponsors had no role in the design, analysis, interpretation, or writing of this article.
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- Epidemiology and Global Health
- Microbiology and Infectious Disease
Background:
In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.
Methods:
We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).
Results:
275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.
Conclusions:
In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.
Funding:
This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).
