Jadvyga Petrauskiene

Seasonal patterns of suicides over the period of socio-economic transition in Lithuania

BackgroundIn Lithuania, suicides are a grave public health problem, requiring more extensive investigation. The aim of the study was to assess the seasonal variations of suicides in Lithuania throughout the years 1993–2002, describing patterns by gender, age and method of suicide.MethodsThe study material consisted of all registered suicides (n = 16,147) committed throughout 1993–2002 in Lithuania. Smoothed trends were inspected. The seasonal effect was explored using monthly ratio statistics and spectral analysis.ResultsSuicides in Lithuania have a distinct annual rhythm with peaks in summer and troughs in December. The December frequencies fell by more than 23% in men and 30% in women, while June peak reached nearly 23% in men and July peak exceeded 29% in women, compare with the average levels, (p < 0.05). Hanging was the most common method of suicide both in men and women comprising up to 90% among all suicides in 1998–2002. Among different methods, only hanging suicides showed significant seasonal variations, especially in men. The seasonal amplitude has decreased over time.ConclusionSubstantial seasonal variations in suicides were associated with a high proportion of hanging. Extremely high suicide rates in Lithuania require further extensive studies and urgent preventive programs, taking into account the suggestions of this survey.

Inequalities in life expectancy in Lithuania by level of education

The purpose of this study was to examine educational inequalities in life expectancy of the Lithuanian population. The life-tables by level of education were calculated on the basis of the individual records of the 1989 census, which were linked to the death records of males and females, aged 25 - 70 years. In comparison with the group with university education, the life expectancy of males with primary or lower education was 11.7 years shorter, and of females 4.3 years shorter. The greatest impact of educational differentials on life expectancy was the inequality found in the mortality of the population, aged 25-44 years. Sex differences in life expectancy were greatest among those with primary or lower education. External causes of death contributed most to educational differences in life expectancy of males, whereas cardiovascular diseases had a major impact to educational differences in females.

Suicide-homicide temporal interrelationship, links with other fatalities, and environmental physical activity

UNLABELLED Homicide and suicide are extremes in human behavior. The aim of this study is to investigate the connection by time between suicide and homicide, between them and other fatalities, and their links with the level of cosmophysical activity. METHODS Using the national database of Lithuania (1990-2002) we found that 547,875 deaths, 4,638 homicides (3,374 male) and 19,527 (16,019 male) suicides were registered in that period. Their temporal distribution over 156 months was compared with solar and cosmic-ray activity. Pearson correlation coefficients and their probabilities were established. RESULTS There was a correlation between monthly rates of homicide and male groups. Female suicide rates correlated with male and total homicide numbers. Both homicide and suicide rates were inversely correlated with solar and cosmic-ray activity. Suicide numbers, but not homicides, were inversely related to geomagnetic activity. Suicide rates were inversely correlated with total, cardiovascular, traffic accident, and sudden deaths; homicide with total, traffic accident, and sudden deaths. CONCLUSION Temporal distribution of homicide and suicide is significantly interrelated. Both are linked to parameters of cosmophysical activity. The influence of cosmic rays deserves special attention.

Cosmic rays activity and monthly number of deaths: a correlative study.

We studied the relation between the intensity of cosmic rays, the level of solar/geomagnetic activity, and the monthly numbers of deaths in a large hospital in Israel and in all Lithuania. The Israeli data include 30526 hospital deaths, two groups of fatal suicides (2359, 2763), and 15435 suicidal attempts for two periods of 108 and 236 consecutive months. The national data for the entire Republic of Lithuania include 424925 deaths for the period of 120 consecutive months. Cosmic rays intensity was measured by an Apatity neutron monitor. We obtained the data on solar, geomagnetic radiovawe propagation, ionosphere ionization hours, proton flux of two energy levels (>90 and 60 MeV) from the National Geophysical Data Center at Goddard Space Flight Center, National Space Environment Center at Boulder, Colorado, USA, and from the Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation (IZMIRAN), Russia. We calculated Pearson coefficients and their probabilities for correlation between monthly space activity level and monthly number of male and female deaths from different causes. Cosmic rays activity revealed significant negative correlation with solar/geomagnetic activity indices and related physical phenomena levels. This activity strongly correlated with flux of protons with the energies >90 MeV proton flux and did not exhibit significant correlation with 60 MeV proton fluxes. Cosmic rays intensity correlation with monthly numbers of deaths was strong for noncardiovascular deaths, suicides, and traffic accidents. The correlation was much weaker for deaths caused by ishemic heart disease and strokes.

Distribution of Deaths from Ischemic Heart Disease and Stroke. Environmental and Aging Influences in Men and Women

UNLABELLED The goal of this study was to check: 1) links between month of the year (1-12), monthly solar activity (SA) and monthly geomagnetic activity (GMA) with the temporal distribution of deaths from ischemic heart disease (IHD) and stroke in Israel and Lithuania (48 months); 2) related age and gender differences; 3) temporal connection between deaths from IHD and suicide and their relationship to SA and GMA, as was suggested in our previous study in Israel. RESULTS Total deaths from IHD in Lithuania showed a trend towards a link with SA (r = 0.25, p = 0.09) and a highly significant correlation for females (r = 0.37, p = 0.00096) but not for males. Age < 74 showed no correlation with SA or GMA in females, but a negative correlation with SA in males (r = -0.513, p = 0.0002). At age > 74 both females (r = 0.467, p = 0.0006, n = 20763) and males (r = 0.476, p = 0.0006, n = 14682) showed a highly significant correlation with SA and a negative correlation with 1-12 months of the year, with deaths concentrating at the beginning of the year (r = -0.32, p = 0.002). Number of monthly suicide and IHD deaths were negatively related to each other (r = -0.45, p = 0.0014). CONCLUSIONS 1) Around age 70 an increasingly positive relationship between the temporal distribution of deaths from IDH and SA is seen. 2) Gender differences in links to SA are partially a consequence of the higher number of deaths in females from IHD at age > 74.3) Monthly number of suicides is inversely related to number of deaths from IHD.

Mortality from external causes in Lithuania: looking for critical points in time and place

Aim: A study was undertaken to analyse trends in mortality from major external causes of death, and to detect urban/rural differences by cut points over the period of socioeconomic transition. Methods: Information on deaths from major external causes (traffic accidents, suicides, and homicides) for the 1990 - 2000 period was obtained from Lithuanian Department of Statistics. Mortality rates were age standardized, using the European standard, and analysed, according to (urban/rural) residence and sex. The Jointpoint analysis was used to identify the best-fitting points, wherever a statistically significant change in mortality occurred. Results: The most critical point for external causes of mortality during the period of transition was the year 1994, when an increasing mortality trend reversed to a decreasing one. Mortality from suicides primarily caused these positive changes. Changes in mortality from traffic accidents were not significantly associated with the period under analysis. Numerous less favourable trends in rural areas, including suicide rates, traffic accidents, and homicides, are likely to stratify urban/rural health outcomes in the future. Conclusion: Despite a recent decline, mortality from external causes remains at an extremely high level in Lithuania. Future progress requires sustained improvements in prevention, and serious attention to external causes of death in health policy development.

Alcohol-Related Injuries and Alcohol Control Policy in Lithuania: Effect of the Year of Sobriety, 2008

AIMS To evaluate the changes in mortality and the years of potential life lost (YPLL) due to alcohol-related injuries, as well as the impact of alcohol-related injuries on life expectancy during the period of the implementation of comprehensive alcohol control policy in Lithuania. METHODS Data on deaths from injuries (ICD-10 codes V01-Y98) of the able-bodied population (aged 15-64 years) during 2006-2009 were obtained from the Lithuanian Department of Statistics. Age-standardized rates of alcohol-related mortality and YPLL per 100, 000 population due to injuries and the impact of alcohol-related injuries on life expectancy were calculated. The results of forensic autopsies were the basis for the alcohol-attributable fraction. RESULTS The age-standardized YPLL/100,000 of the able-bodied population due to alcohol-related injuries was 2285.6 (4067.5 for males and 573.6 for females) in 2009. In 2009, YPLL/100,000 due to alcohol-related injuries declined by 16.3%, while due to alcohol-related traffic accidents by 51.2% when compared with 2006. However, YPLL/100, 000 due to alcohol-related suicides increased among males. A 15 to 64-year-old decedent lost an average of 21.2 years of life due to alcohol-related injuries (21.6 years on average per male and 19.1 per female). The impact of alcohol-related injuries on life expectancy decreased from 1.14 years (1.86 for males and 0.34 for females) in 2006 to 0.97 years (1.62 for males and 0.26 for females) in 2009. CONCLUSION The positive changes in YPLL due to alcohol-related injuries and the impact of alcohol-related injuries on life expectancy indicate successful implementation of evidence-based alcohol control measures.

Space weather and human deaths distribution: 25 years' observation (Lithuania, 1989-2013).

Abstract Background: Human health is affected by space weather component [solar (SA), geomagnetic (GMA), cosmic ray (CRA) – 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. Methods: 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 (r) and their probabilities (p) were obtained for years: months 1–12, 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’s 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). Results: Space factors were interrelated as follows for the considered period: CRA was inversely related to SA and GMA, CRA/SA (r=−0.86, p>0.0001), CRA/GMA (r=−0.70, p<0.0001); SA and GMA were correlated (r=0.50, p<0.0001). The total deaths distribution was inversely related to SA (r=−0.31, p<0.0001) and correlated with CRA (neutron) activity (r=0.234, p<0.0001). Ischemic heart disease (IHD) deaths (most at home) show a drop yearly (r=−0.2551), more for men. It was correlated with GMA for the total IHD population and men. Stroke deaths were inversely related to SA (r=−0.38, p<0.0001) and correlated with CRA (r=0.41, p<0.0001) and year (r=0.49, p<0.0001), showing a steady rise. The IHD/stroke deaths ratio was negatively correlated with the years of observation (r=−0.754, p=0.0001). Non-cardiovascular deaths were inversely related to SA (r=−039, p<0.0001) and correlated with CRA (r=0.263, p<0.0001). Oncology deaths that now are dominating in many places were inversely related to SA (r=−0.475, p<0.0001) and correlated with CRA (r=0.426, p<0.0001). Suicide showed a drop with years (r=−0.29, p<0.0001), possibly related to excessive immigration of young population (18–34 years) in the last decade and correlated with two of three GMA indices. Traffic accidents were correlated with SA and GMA (r=0.392–0.461, p<0.0001) and inversely related to CRA (r=−0.436). Conclusions: Most groups of deaths are related to space weather component activity. Extreme levels of activities of both groups (SA, GMA, and opposite CRA – 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.

Inequalities in life expectancy in Lithuania by level of education: original article

The purpose of this study was to examine educational inequalities in life expectancy of the Lithuanian population. The life-tables by level of education were calculated on the basis of the individual records of the 1989 census, which were linked to the death records of males and females, aged 25-70 years. In comparison with the group with university education, the life expectancy of males with primary or lower education was 11.7 years shorter, and of females 4.3 years shorter. The greatest impact of educational differentials on life expectancy was the inequality found in the mortality of the population, aged 25-44 years. Sex differences in life expectancy were greatest among those with primary or lower education. External causes of death contributed most to educational differences in life expectancy of males, whereas cardiovascular diseases had a major impact to educational differences in females.