Effect of seasonal variation on hospital admission due to cardiovascular disease - findings from an observational study in a divisional hospital in Bangladesh
Department of Cardiology, Sher-e-Bangla Medical College, Barisal, Bangladesh
BMC Cardiovascular Disorders 2014, 14:76 doi:10.1186/1471-2261-14-76Published: 13 June 2014
Seasonal variation in the hospital admission due to cardiovascular disease (CVDs) has been widely reported. However, very limited data on Bangladesh is available regarding this matter. The aim of the current study was to investigate the effect of seasonal variation on hospital admission due to CVDs in a leading hospital of Bangladesh.
Over a period of two years (from May 2010 to April 2012), the number of patients hospitalized due to various CVDs and number of death among these hospitalized patients were recorded on a day-to-day basis. The data were recorded according to the chief reason of hospital admission such as myocardial infarction or MI (acute, old and non-ST elevation), unstable angina (UA), exaggeration of stable angina, acute left ventricular failure (LVF), cardiomyopathy (ischemic and dilated) or heart failure, syncope and arrhythmia. The data were cumulated and analyzed on month-wise and season-wise manner.
A total of 8371 patients were admitted over the study period (5909 male and 2462 female; M/F ratio - 2.4:1). The highest number of patients were admitted during winter (n = 2839, 33.9%) and lowest during summer (n = 1648, 19.7%). The hospital admission was also significantly higher in winter compared to other seasons (p-value versus summer, autumn and spring was 0.018, 0.020 and 0.023 respectively). Acute MI (n = 2374), Acute LVF (n = 1582) and UA (n = 1277) were the top three reasons for hospitalization. Number of death also significantly higher in winter compared to other seasons (p-value versus summer, winter and spring was 0.044, 0.050 and 0.014 respectively).
A seasonal variation in the hospital admission due to CVDs with a peak in winter was clearly demonstrated in the study. These data could be useful to improve causative prevention measures, therapeutic management, and educational strategies.