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Both acute and chronic cardiovascular conditions show seasonality: the need of looking beyond conventional risk factors

Both acute and chronic cardiovascular conditions show seasonality: the need of looking beyond... We read with great interest the study by Barnett et al. presenting the seasonality in cardiovascular disease (CVD) deaths in Australian capital cities. They reported a predominantly winter peak for the CVD mortality. The peak months were broadly similar across the seven cardiovascular disease categories they presented based on the ICD 10. It was interesting to note that both the chronic and acute CVD conditions showed a winter excess mortality. In our own works, with population‐based cardiovascular disease registration system in Japan, we observed that the acute incidence of stroke and acute myocardial infarction (AMI) have a tendency of higher occurrence during colder times of the year. We also observed the similar pattern of seasonality in our study population for the acute case‐fatalities of both the diseases, which would be contributing substantially to the seasonal trend in mortality of these diseases as well. Bringing together our results with Barnett et al's study, we might fairly conclude that both acute and chronic CVD conditions shows seasonality of higher incidence, acute fatality, or mortality during colder periods. Though the focus of the paper of Barnett et al. did not include the issue of the effect of the CVD risk factor on the seasonal pattern observed, in our study we observed that regardless of the presence or absence of a history of these risk factors, there was an elevated CVD risk in the winter‐spring period. Our results suggest that those patients who suffer a stroke or AMI during the winter‐spring seasons have a substantially worse prognosis than patients who have a stroke at other times of the year irrespective of the risk factor status. In a cohort study conducted in the UK, the researchers found no evidence that conventional risk factors identified groups in whom the seasonality effect was greater. The seasonality effects were found consistently across disease‐specific risk groups. Further exploration by the researchers whether high‐risk groups defined by the Framingham risk equation for CVD were associated with greater seasonality did not reveal any association. Judging the results of these studies, we might conclude that both the acute and chronic CVD events show seasonality for both presence and absence of CVD risk factors. This suggests the importance of additional, as yet unidentified, factors in characterising groups in whom seasonality effects are prominent. The probable mechanisms underlying seasonal variation of CVD are not fully understood yet. Possible major contributing factors might be the weather components which could serve as influencer for seasonal variation of CVD. The physiological processes related to these weather components may trigger the acute occurrence of CVD event and contribute towards the excess mortality during the winter months. We would like to suggest an approach to this issue by treating the weather factors (e.g. temperature, humidity, sunlight, rainfall, barometric pressure, etc) as primary contributing factor or independent factor which influences the mediating factors (daily‐life activity pattern, blood pressure level, influenza and respiratory infections, air pollution, serum lipids, some blood component levels, hypercoagulable state, etc which have shown to have seasonal fluctuations and is associated with CDV risk) leading to the outcome of seasonal fluctuation CVD occurrence and mortality. Figure 1 shows the hypothetical flow chart of this notion. As this phenomenon will be occurring for both people having or without having CVD risk factors, thus there is a need also to focus beyond the conventional CVD risk factors. We need to undertake further research to understand the potential interaction between these primary determinant factors, intermediate mediators and the CVD occurrence/mortality Understanding of these may provide novel avenues for research in prevention of CVD. 1 The flowchart for the plausible interaction between primary determinants, intermediate mediating factors and cardiovascular diseases. Funding Supported in part by Research Grants‐In‐Aid (P‐20.08124) from the Japan Society for the Promotion of Science (JSPS). Tanvir Chowdhury Turin is supported by the fellowship from the JSPS. There is no conflict of interest. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Australian and New Zealand Journal of Public Health Wiley

Both acute and chronic cardiovascular conditions show seasonality: the need of looking beyond conventional risk factors

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References (15)

Publisher
Wiley
Copyright
© The Authors. Journal Compilation © 2008 Public Health Association of Australia
ISSN
1326-0200
eISSN
1753-6405
DOI
10.1111/j.1753-6405.2008.00318.x
pmid
19076757
Publisher site
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Abstract

We read with great interest the study by Barnett et al. presenting the seasonality in cardiovascular disease (CVD) deaths in Australian capital cities. They reported a predominantly winter peak for the CVD mortality. The peak months were broadly similar across the seven cardiovascular disease categories they presented based on the ICD 10. It was interesting to note that both the chronic and acute CVD conditions showed a winter excess mortality. In our own works, with population‐based cardiovascular disease registration system in Japan, we observed that the acute incidence of stroke and acute myocardial infarction (AMI) have a tendency of higher occurrence during colder times of the year. We also observed the similar pattern of seasonality in our study population for the acute case‐fatalities of both the diseases, which would be contributing substantially to the seasonal trend in mortality of these diseases as well. Bringing together our results with Barnett et al's study, we might fairly conclude that both acute and chronic CVD conditions shows seasonality of higher incidence, acute fatality, or mortality during colder periods. Though the focus of the paper of Barnett et al. did not include the issue of the effect of the CVD risk factor on the seasonal pattern observed, in our study we observed that regardless of the presence or absence of a history of these risk factors, there was an elevated CVD risk in the winter‐spring period. Our results suggest that those patients who suffer a stroke or AMI during the winter‐spring seasons have a substantially worse prognosis than patients who have a stroke at other times of the year irrespective of the risk factor status. In a cohort study conducted in the UK, the researchers found no evidence that conventional risk factors identified groups in whom the seasonality effect was greater. The seasonality effects were found consistently across disease‐specific risk groups. Further exploration by the researchers whether high‐risk groups defined by the Framingham risk equation for CVD were associated with greater seasonality did not reveal any association. Judging the results of these studies, we might conclude that both the acute and chronic CVD events show seasonality for both presence and absence of CVD risk factors. This suggests the importance of additional, as yet unidentified, factors in characterising groups in whom seasonality effects are prominent. The probable mechanisms underlying seasonal variation of CVD are not fully understood yet. Possible major contributing factors might be the weather components which could serve as influencer for seasonal variation of CVD. The physiological processes related to these weather components may trigger the acute occurrence of CVD event and contribute towards the excess mortality during the winter months. We would like to suggest an approach to this issue by treating the weather factors (e.g. temperature, humidity, sunlight, rainfall, barometric pressure, etc) as primary contributing factor or independent factor which influences the mediating factors (daily‐life activity pattern, blood pressure level, influenza and respiratory infections, air pollution, serum lipids, some blood component levels, hypercoagulable state, etc which have shown to have seasonal fluctuations and is associated with CDV risk) leading to the outcome of seasonal fluctuation CVD occurrence and mortality. Figure 1 shows the hypothetical flow chart of this notion. As this phenomenon will be occurring for both people having or without having CVD risk factors, thus there is a need also to focus beyond the conventional CVD risk factors. We need to undertake further research to understand the potential interaction between these primary determinant factors, intermediate mediators and the CVD occurrence/mortality Understanding of these may provide novel avenues for research in prevention of CVD. 1 The flowchart for the plausible interaction between primary determinants, intermediate mediating factors and cardiovascular diseases. Funding Supported in part by Research Grants‐In‐Aid (P‐20.08124) from the Japan Society for the Promotion of Science (JSPS). Tanvir Chowdhury Turin is supported by the fellowship from the JSPS. There is no conflict of interest.

Journal

Australian and New Zealand Journal of Public Health – Wiley

Published: Dec 1, 2008

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