Changes in socioeconomic mortality inequalities at adult and old ages in Lithuania, 2001-05 to 2011-15.

This article provides evidence about changes in mortality inequalities by education and economic activity status among adults aged 30-64 and older adults aged 65 and over in Lithuania between 2001-05 and 2011-15. The study shows that the overall mortality decline in Lithuania was not homogeneous across socio-economic groups. The inequitable progress resulted in a widening in absolute and relative mortality inequalities among older adults and notable increases in relative mortality inequalities among adults aged 30-64. The total public health burden of mortality inequalities remained very pronounced or even increased further.

Individual- and area-level characteristics associated with alcohol-related mortality among adult Lithuanian males: A multilevel analysis based on census-linked data.

BACKGROUND: Although excessive alcohol-related mortality in the post-Soviet countries remains the major public health threat, determinants of this phenomenon are still poorly understood. AIMS: We assess simultaneously individual- and area-level factors associated with an elevated risk of alcohol-related mortality among Lithuanian males aged 30-64. METHODS: Our analysis is based on a census-linked dataset containing information on individual- and area-level characteristics and death events which occurred between March 1st, 2011 and December 31st, 2013. We limit the analysis to a few causes of death which are directly linked to excessive alcohol consumption: accidental poisonings by alcohol (X45) and liver cirrhosis (K70 and K74). Multilevel Poisson regression models with random intercepts are applied to estimate mortality rate ratios (MRR). RESULTS: The selected individual-level characteristics are important predictors of alcohol-related mortality, whereas area-level variables show much less pronounced or insignificant effects. Compared to married men, never married (MRR = 1.9, CI:1.6-2.2), divorced (MRR = 2.6, CI:2.3-2.9), and widowed (MRR = 2.4, CI: 1.8-3.1) men are disadvantaged groups. Men who have the lowest level of educational attainment have the highest mortality risk (MRR = 1.7 CI:1.4-2.1). Being unemployed is associated with a five-fold risk of alcohol-related death (MRR = 5.1, CI: 4.4-5.9), even after adjusting for all other individual variables. Lithuanian males have an advantage over Russian (MRR = 1.3, CI:1.1-1.6) and Polish (MRR = 1.8, CI: 1.5-2.2) males. After adjusting for all individual characteristics, only two out of seven area-level variables-i.e., the share of ethnic minorities in the population and the election turnout-have statistically significant direct associations. These variables contribute to a higher risk of alcohol-related mortality at the individual level. CONCLUSIONS: The huge and increasing socio-economic disparities in alcohol-related mortality indicate that recently implemented anti-alcohol measures in Lithuania should be reinforced by specific measures targeting the most disadvantaged population groups and geographical areas.

Educational differences in incidence of cancer in Lithuania, 2001-2009: evidence from census-linked cancer registry data.

This study used population-based census-linked cancer incidence data to identify patterns of educational differentials in the risk of cancer by detailed sites of cancer in Lithuania. The study is based on the linkage between all records of the 2001 population census, all records from the Lithuanian Cancer Registry (cancer incidence), and all death and emigration records from Statistics Lithuania for the period between 6 April 2001 and 31 December 2009. The study population (cohort) includes all permanent residents of Lithuania aged 30-74 years on the day of the census (6 April 2001). The study found that cancers of the lip, mouth, and pharynx, esophagus, stomach, larynx, urinary bladder, pancreas, and lung for men and cancers of the cervix uteri, lung, and colon for women show a statistically significant inverse educational gradient with excess incidence in the lowest educational group. At the same time, a reversed cancer risk gradient with the highest incidence for the higher education group was observed for thyroid cancer, melanoma, nonmelanoma skin cancers, and non-Hodgkin lymphomas. This group also includes prostate cancer, kidney cancer, and multiple myeloma for men and cancer of the pancreas, breast cancer, cancer of the colon, and cancer of the uterus for women. The associations between education and cancer incidence observed in this study reflect the concordance between social status and lifestyle-related risk factors for cancer. Cancer awareness in society has also contributed toward the observed higher risk of cancer, which is usually promoted more by patients with higher education.

Suicides among cancer patients in Lithuania: a population-based census-linked study.

BACKGROUND: This study aims to estimate suicide risk and its socio-demographic determinants among cancer patients in the country showing the highest suicide rates among developed countries. METHODS: The study is based on a unique census-linked dataset based on the linkages between the records from death and cancer registers and the 2001 population census records. Standardized mortality ratios for suicide (SMRs) were calculated for patients diagnosed with cancer in Lithuania between April 6, 2001 and December 31, 2009, relative to suicide rates in the general population. RESULTS: We found that the relative suicide risk was elevated for both males and females, with SMRs of 1.43 (95% CI 1.23-1.66) and 1.32 (95% CI 0.95-1.80), respectively. This relationship for females became statistically significant and stronger after excluding skin cancers. The highest suicide risks were observed at older ages and during the period shortly after the diagnosis. The groups showing an increased suicide risk include lower educated, non-married, and rural male patients. CONCLUSION: The results of our study point to inadequacies of the health care system in dealing with mental health problems of cancer patients. Interventions allowing early detection of depression or suicidal ideation may help to prevent suicide among cancer patients in Lithuania.

Linked versus unlinked estimates of mortality and length of life by education and marital status: evidence from the first record linkage study in Lithuania.

Earlier studies have found large and increasing with time differences in mortality by education and marital status in post-Soviet countries. Their results are based on independent tabulations of population and deaths counts (unlinked data). The present study provides the first census-linked estimates of group-specific mortality and the first comparison between census-linked and unlinked mortality estimates for a post-Soviet country. The study is based on a data set linking 140,000 deaths occurring in 2001-2004 in Lithuania with the population census of 2001. The same socio-demographic information about the deceased is available from both the census and death records. Cross-tabulations and Poisson regressions are used to compare linked and unlinked data. Linked and unlinked estimates of life expectancies and mortality rate ratios are calculated with standard life table techniques and Poisson regressions. For the two socio-demographic variables under study, the values from the death records partly differ from those from the census records. The deviations are especially significant for education, with 72-73%, 66-67%, and 82-84% matching for higher education, secondary education, and lower education, respectively. For marital status, deviations are less frequent. For education and marital status, unlinked estimates tend to overstate mortality in disadvantaged groups and they understate mortality in advantaged groups. The differences in inter-group life expectancy and the mortality rate ratios thus are significantly overestimated in the unlinked data. Socio-demographic differences in mortality previously observed in Lithuania and possibly other post-Soviet countries are overestimated. The growth in inequalities over the 1990s is real but might be overstated. The results of this study confirm the existence of large and widening health inequalities but call for better data.