{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T22:49:35Z","timestamp":1784328575746,"version":"3.55.0"},"reference-count":71,"publisher":"Walter de Gruyter GmbH","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:bold>Background:<\/jats:bold>\n                    Human health is affected by space weather component [solar (SA), geomagnetic (GMA), cosmic ray (CRA) \u2013 neutrons, space proton flux] activity levels. The aim of this study was to check possible links between timing of human (both genders) monthly deaths distribution and space weather activity.\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Methods:<\/jats:bold>\n                    Human deaths distribution in the Republic of Lithuania from 1989 to 2013 (25 years, i.e., 300 consecutive months) was studied, which included 1,050,503 deaths (549,764 male, 500,739 female). Pearson correlation coefficients (\n                    <jats:italic>r<\/jats:italic>\n                    ) and their probabilities (p) were obtained for years: months 1\u201312, sunspot number, smoothed sunspot number, solar flux (2800 MGH, 10.7 cm), adjusted solar flux for SA; A, C indices of GMA; neutron activity at the earth\u2019s surface (imp\/min) for CRA. The cosmophysical data were obtained from space science institutions in the USA, Russia and Finland. The mentioned physical parameters were compared with the total number of deaths, deaths from ischemic heart disease (n=376,074), stroke (n=132,020), non-cardiovascular causes (n=542,409), accidents (n=98,805), traffic accidents (n=21,261), oncology (n=193,017), diabetes mellitus (n=6631) and suicide (n=33,072).\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Results:<\/jats:bold>\n                    Space factors were interrelated as follows for the considered period: CRA was inversely related to SA and GMA, CRA\/SA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.86, p&gt;0.0001), CRA\/GMA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.70, p&lt;0.0001); SA and GMA were correlated (\n                    <jats:italic>r<\/jats:italic>\n                    =0.50, p&lt;0.0001). The total deaths distribution was inversely related to SA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.31, p&lt;0.0001) and correlated with CRA (neutron) activity (\n                    <jats:italic>r<\/jats:italic>\n                    =0.234, p&lt;0.0001). Ischemic heart disease (IHD) deaths (most at home) show a drop yearly (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.2551), more for men. It was correlated with GMA for the total IHD population and men. Stroke deaths were inversely related to SA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.38, p&lt;0.0001) and correlated with CRA (\n                    <jats:italic>r<\/jats:italic>\n                    =0.41, p&lt;0.0001) and year (\n                    <jats:italic>r<\/jats:italic>\n                    =0.49, p&lt;0.0001), showing a steady rise. The IHD\/stroke deaths ratio was negatively correlated with the years of observation (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.754, p=0.0001). Non-cardiovascular deaths were inversely related to SA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u2212039, p&lt;0.0001) and correlated with CRA (\n                    <jats:italic>r<\/jats:italic>\n                    =0.263, p&lt;0.0001). Oncology deaths that now are dominating in many places were inversely related to SA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.475, p&lt;0.0001) and correlated with CRA (\n                    <jats:italic>r<\/jats:italic>\n                    =0.426, p&lt;0.0001). Suicide showed a drop with years (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.29, p&lt;0.0001), possibly related to excessive immigration of young population (18\u201334 years) in the last decade and correlated with two of three GMA indices. Traffic accidents were correlated with SA and GMA (\n                    <jats:italic>r<\/jats:italic>\n                    =0.392\u20130.461, p&lt;0.0001) and inversely related to CRA (\n                    <jats:italic>r<\/jats:italic>\n                    =\u22120.436).\n                  <\/jats:p>\n                  <jats:p>\n                    <jats:bold>Conclusions:<\/jats:bold>\n                    Most groups of deaths are related to space weather component activity. Extreme levels of activities of both groups (SA, GMA, and opposite CRA \u2013 neutron) are related to some health risks. In the considered period, there were relatively few GMA storms and low GMA was dominating, accompanied by higher CRA (neutron) activity. The ways of action of the components of space weather on the human body need additional studies. There is a special need for the prevention of rising cerebral vascular accidents and oncology malignancies as the causes of death.\n                  <\/jats:p>","DOI":"10.1515\/jbcpp-2014-0125","type":"journal-article","created":{"date-parts":[[2015,6,12]],"date-time":"2015-06-12T10:40:10Z","timestamp":1434105610000},"page":"433-441","source":"Crossref","is-referenced-by-count":14,"title":["Space weather and human deaths distribution: 25 years\u2019 observation (Lithuania, 1989\u20132013)"],"prefix":"10.1515","volume":"26","author":[{"given":"Eliyahu G.","family":"Stoupel","sequence":"first","affiliation":[{"name":"Division of Cardiology, Sackler Faculty of Medicine, Rabin Medical Center, Tel Aviv University, Denmark 2, Petah Tiqwa, 49100, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jadvyga","family":"Petrauskiene","sequence":"additional","affiliation":[{"name":"Lithuanian Medical Science University, Kaunas, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramune","family":"Kalediene","sequence":"additional","affiliation":[{"name":"Lithuanian Medical Science University, Kaunas, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Skirmante","family":"Sauliune","sequence":"additional","affiliation":[{"name":"Lithuanian Medical Science University, Kaunas, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evgeny","family":"Abramson","sequence":"additional","affiliation":[{"name":"Management Data Center, Rabin Medical Center, Petah Tiqwa, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tzippy","family":"Shochat","sequence":"additional","affiliation":[{"name":"Statistics, Rabin Medical Center, Petah Tiqwa, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2015,6,12]]},"reference":[{"key":"2025121209130300753_j_jbcpp-2014-0125_ref_001_w2aab2b8c63b1b7b1ab2b1b1Aa","unstructured":"Tchijevsky A. 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