title: Distribution of monthly deaths, solar (SA) and geomagnetic (GMA) activity: their interrelationship in the last decade of the second millennium: the Lithuanian study 1990-1999.
abstract: Thirty percent of cardiovascular deaths cannot be explained by known risk factors. In this study, we sought links between 1) circannual rhythmicity, solar activity (SA) - sunspot number, solar radioflux and geomagnetic activity (GMA) - Ap., Cp., Am. with monthly number of deaths looking for environmental influence on mortality at the end of the second millennium. The Lithuanian national death data from for 120 consecutive months according to the IDC (1990 - 1999, n = 424925 deaths) was studied: 157189 from IHD (72144 male, 85045 female), 50228 from stroke (19062 male, 31166 female), 33722 from accidents (26193 male, 7529 female), 10655 from road accidents (8127 male, 2528 female) and 14810 from suicide (12137 male, 2673 female), 217508 - non cardiovascular (134308 male, 83200 female). Monthly death numbers (total, < 65y, 65-74, > 74y old for IHD and Stroke, and by gender) were compared with time of year, SA and GMA indices obtained from the National Geophysical Data and National Space Services Center, USA. Circannual rhythmicity indices, Pearson correlation coefficients and their probabilities were obtained and analyzed. The interrelationships of deaths from IHD and stroke and some other pathologies were also studied. In addition a multivariate linear regression analysis was done in order to evaluate the influence of time (month), Solar (S.A.) and Geomagnetic (GMA) activity on the temporal distribution of deaths. The total IHD monthly death number was significantly linked with GMA indices (r = 0.2-0.24, p = 0.03-0.075), but not with SA. IHD correlated with SA (r = 0.25-0.27, p = 0.006-0.0026), only in the 74 year age group. p = 0.0001) In the 65-74 age group, there was an inverse relationship with SA (r = -0.46-0.44) and no significant relationship to GMA. The IHD death number was correlated with GMA only in the < 65 and > 74 year age group (r = 0.30-0.36, p = 0.001-0.001). 2) Stroke-related deaths showed an inverse correlation with SA and GMA only for the 65-74y age group (r = -0.5, p = 0.0001 - SA, r = -0.4, p = 0.0001- GMA) and with GMA at age < 65 only for males (r = 0.20-0.25, p = 0.03-0.04). 3) Both IHD and stroke were strongly circannual rhythmic with acrophase at month 1.27 (IHD) and 1.32 (stroke) - first half of February, (p = 0.0001). 4) The IHD / stroke death ratio was correlated both with SA and GMA (r = 0.35, p 0.0001 - SA, r = 0.40-0.44, p = 0.0001 - GMA). 5) There was a strong inverse monthly deaths correlation between IHD and suicide (n = 14,810, r = -0.53, p = 0.0001). Stroke and suicide were also related, but to a much weaker extent (r = -0.217, p = 0.017). Accidents were inverse related to S.A. (r = -0.286, p = 0.0015), but not to GMA. Road Accidents - with both S.A. (r = 0.427, p < 0.0001) and GMA (r = 0.258, p = 0.004); with acrophases in October for road and November for other fatal accidents. Non cardiovascular deaths were annually rhythmic only for female - acrophase in early February, and for both gender inverse related to S.A. (r = -0.57, p < 0.0001) but not with GMA. Suicide victims had their acrophase in July (p < 0.0001) and were inverse related to S.A. (r = -0.6, p < 0.0001) and GMA (r = -0.27, p = 0.002). At the onset of the third millennium, the temporal distribution of deaths is still related to environmental physical activity. Those links differ for each of the pathologies, and by age and gender.
authors.affiliation: Division of Cardiology and Epidemiology Unit, Rabin Medical Center, Beilinson Campus, Petah Tikva, Israel. Stoupel@inter.net.il
authors.forename: E
authors.initials: E
authors.lastname: Stoupel
authors.forename: J
authors.initials: J
authors.lastname: Petrauskiene
authors.forename: E
authors.initials: E
authors.lastname: Abramson
authors.forename: R
authors.initials: R
authors.lastname: Kalediene
authors.forename: J
authors.initials: J
authors.lastname: Sulkes
mesh_terms: D000368:Aged; D004574:Electromagnetic Fields / Q000009:adverse effects; D005260:Female; D006801:Humans; D008097:Lithuania / Q000453:epidemiology; D008297:Male; D009026:Mortality / Q000639:trends*; D015999:Multivariate Analysis; D010507:Periodicity; D019445:Solar Activity; D016008:Statistical Distributions