Comparing gender-specific suicide mortality rate trends in the United States and Lithuania, 1990-2019: putting one of the "deaths of despair" into perspective.

INTRODUCTION: The increase in the suicide mortality rate among middle-aged adults in the United States (US) has been well documented. Aside from a few studies from the United Kingdom, it is unclear whether the suicide mortality rate trend in the US is also occurring in other developed countries. Accordingly, we aimed to compare the suicide mortality rate trends over the past 30 years in the US to a country in the European Union-Lithuania. METHODS: Joinpoint regression analyses were performed to identify secular trends in the gender-specific age-standardized suicide mortality rate among individuals 15 + years of age, as well as middle-aged adults (45-54 years of age), and suicide mortality rate ratio for men-to-women. RESULTS: Age-standardized suicide mortality rates among middle-aged adults in the US increased annually, on average, by 0.89% (95% CI: 0.66%, 1.12%) among men and 1.21% (95% CI: 0.75%, 1.66%) among women between 1990 and 2019. In contrast to the US, there was an overall downward trend in the suicide mortality rates among middle-aged adults in Lithuania across the study period. The average annual percent change in the suicide mortality rate ratio for men-to-women were not statistically significant for either country. CONCLUSION: The suicide mortality rate trend in the US does not appear to be an indicator of an upcoming global trend, but rather should be regarded as a cautionary example of what other countries should strive to avoid.

Interrupted time series analyses to assess the impact of alcohol control policy on socioeconomic inequalities in mortality in Lithuania: a study protocol.

INTRODUCTION: Alcohol use is a major risk factor for mortality. Previous studies suggest that the alcohol-attributable mortality burden is higher in lower socioeconomic strata. This project will test the hypothesis that the 2017 increase of alcohol excise taxes linked to lower all-cause mortality rates in previous analyses will reduce socioeconomic mortality inequalities. METHODS AND ANALYSIS: Data on all causes of deaths will be obtained from Statistics Lithuania. Record linkage will be implemented using personal identifiers combining data from (1) the 2011 whole-population census, (2) death records between 1 March 2011 (census date) and 31 December 2019, and (3) emigration records, for individuals aged 40-70 years. The analyses will be performed separately for all-cause and for alcohol-attributable deaths. Monthly age-standardised mortality rates will be calculated by sex, education and three measures of socioeconomic status (SES). Inequalities in mortality will be assessed using absolute and relative indicators between low and high SES groups. We will perform interrupted time series analyses, and test the impact of the 2017 rise in alcohol excise taxation using generalised additive mixed models. In these models, we will control for secular trends for economic development. ETHICS AND DISSEMINATION: This work is part of project grant 1R01AA028224-01 by the National Institute on Alcohol Abuse and Alcoholism. It has been granted research ethics approval 050/2020 by Centre for Addiction and Mental Health Research Ethics Board on 17 April 2020, renewed on 30 March 2021. The time series of mortality inequalities as well as the statistical code will be made publicly available, allowing other researchers to adapt the proposed method to other jurisdictions.

Cardiovascular diseases mortality and alcohol control policy in Lithuania: exploring a possible link.

BACKGROUND: Lithuania possesses one of the highest alcohol per capita consumption and has previously implemented alcohol control policies to reduce the alcohol-attributable burden. The aim of this study was to investigate Lithuanian cardiovascular disease (CVD) mortality rate trends between 2001 and 2018 and to explore a possible link between CVD mortality rate and alcohol control policy implementation. METHODS: Lithuanian population mortality and alcohol consumption data for 2001-2018 were obtained from Statistics Lithuania and The State Register of Death Cases and Their Causes, Institute of Hygiene. Sex-specific CVD mortality rates were directly standardized to the European standard population by five-year age groups and categorized according to the ICD-10 codes for all CVDs (I00-I99), ischemic heart disease (IHD) (I20-I25), cerebrovascular diseases (I60-I69) and alcoholic cardiomyopathy (ACM) (I42.6). Joinpoint regression analyses were performed to identify points of inflection to explore their alignment with five selected alcohol policy enactments. RESULTS: Overall, the 2001-2018 yearly mortality rates for all CVDs significantly decreased on average by - 1.6% (95% CI -2.0, - 1.2%) among men and - 2.1% (95% CI -2.5, - 1.8%) among women. Yearly changes in all CVDs, IHD, cerebrovascular diseases and ACM mortality rates were insignificant prior to their respective critical year points in 2006, 2005, 2008 and 2007, but significantly decreased afterwards by an average of - 2.4% (95% CI -2.7, - 2.0%), - 1.6% (95% CI -2.1, - 1.1%), - 1.2% (95 CI -1.7, - 0.6%) and - 4.5% (95% CI -7.3, - 1.6%) among men, and by - 2.7% (95% CI -3.0, - 2.3%), - 2.0% (95% CI -2.6, - 1.4%), - 1.8% (95% CI 2.4, - 1.3%) and - 6.6% (95% CI -10.7, - 2.2%) among women, respectively. The changes in the mortality rate trends for all CVDs, IHD, cerebrovascular diseases and especially ACM coincided with alcohol policies enacted on the January 1, 2008, January 1, 2009, April 1, 2014 and March 1, 2017. CONCLUSIONS: Yearly mortality rates for all CVDs, IHD, cerebrovascular diseases and ACM have declined in Lithuania between 2001 and 2018, and declining trends were more prominent in women than in men. Among the ICD-10 CVD categories investigated, the points of inflection identified for the ACM mortality rate trend coincided best with the selected alcohol policy enactment dates.

Changes in Mortality Inequalities in Urban and Rural Populations during 1990-2018: Lithuanian Experience.

Background and Objectives: Reduction in health inequalities is a highly important task in public health policies worldwide. In Lithuania, inequalities in mortality by place of residence are among the greatest, compared to other European Union (EU) countries. However, studies on inequalities in mortality by place of residence over a long-term period have not been investigated in Lithuania. The aim of this study was to present changes in mortality inequalities in urban and rural populations during 1990-2018. Materials and Methods: Mortality rates from all causes, cardiovascular diseases, cancer, external causes, and gastrointestinal diseases in urban and rural population by sex were calculated per 100,000 populations and were standardized by age. Inequalities in mortality were assessed using rate differences and rate ratio. For the assessment of inequality trends during 1990-2018, the joinpoint regression analysis was applied. Results: Mortality between urban and rural populations varied. In rural areas, mortality lower than that in urban areas was observed only in 1990 among women, in case of mortality from cancer and gastrointestinal diseases (compared with in 2018) (p < 0.05). In 2018, mortality from all causes, cardiovascular diseases, and external causes in urban and rural areas was lower than in 1990 in both sexes. However, mortality from gastrointestinal diseases was higher (p < 0.05). In 2018, mortality from cancer among both sexes was lower only in urban areas (p < 0.05). Mortality inequalities between rural and urban areas decreased statistically significantly only among men from external causes and from all causes (respectively, on average, by 0.52% per year and, on average, by 0.21% per year). Meanwhile, mortality from cardiovascular and gastrointestinal diseases increased in both sexes, and mortality from cancer and all causes of death increased among women. The increase in the inequalities of mortality from gastrointestinal diseases was the most rapid: among men-on average, by 0.69% per year, and among women-on average, by 1.43% per year, p < 0.0001. Conclusions: During 1990-2018, the inequalities in mortality by place of residence in Lithuania statistically significantly decreased only among men, in terms of mortality from external causes and from all causes. Therefore, reduction in inequalities in mortality must be the main the health policy challenge in Lithuania.

Alcohol control policies add to secular trends in all-cause mortality rates in young adults.

Alcohol consumption is a major risk factor for premature mortality. Although alcohol control policies are known to impact all-cause mortality rates, the effect that policies have on specific age groups is an important area of research. This study investigates the effect of alcohol control policies implemented in 2009 and 2017 in Lithuania on all-cause mortality rates. All-cause mortality rates (deaths per 100,000 people) were obtained for 2001-2018 by 10-year age groups (20-29, 30-39, 40-49 years, etc.). All-cause mortality rates, independent of macro-level secular trends (e.g., economic trends) were examined. Following a joinpoint analysis to control for secular trends, an interrupted time series analysis showed that alcohol control policies had a significant effect on all-cause mortality rates (p = .018), with the most significant impact occurring among young adults (20-29 and 30-39 years of age). For these age groups, their mortality rate decreased during the 12 months following policy implementation (following the policy in 2009 for those 20-29 years of age, p = .0026, and following the policy in 2017 for those 30-39 years of age, p = .011). The results indicate that alcohol control policy can impact all-cause mortality rates, above and beyond secular trends, and that the impact is significant among young adults.

Inequalities in Life Expectancy by Education and Its Changes in Lithuania during 2001-2014.

Background and Objectives: Reduction of health inequalities is a highly important task in public health policies worldwide. In Lithuania, inequalities in life expectancy (LE) by education level are among the greatest, compared to other European countries. However, studies on inequalities in LE by level of education over a long-term period are quite scarce in Lithuania. The aim of the study was to analyze inequalities in life expectancy by education and its changes in Lithuania during 2001-2014. Materials and Methods: Information on deaths (in population aged ≥30 years) was obtained from Statistics Lithuania. Life expectancy at age 30 (LE30) and 95% confidence intervals (CIs) were calculated using life tables. Inequalities in LE30 were assessed using rate differences. Joinpoint regression analysis was used to assess the trends and inequalities of LE30 during 2001-2014. Results: During 2001-2014, LE30 in males and females with post-secondary education was higher than in those with up-to-secondary education (p < 0.05). Among males and females, LE30 increased in both education groups, except for males with up-to-secondary education. Among individuals with post-secondary education, LE30 started increasing earlier and more quickly than in those with up-to-secondary education. Over the analyzed period, greater differences in LE30 between post-secondary and up-to-secondary education groups were found among males. Differences in LE30 due to different educational background were statistically significantly, increasing across the sexes with a more rapid increase for females than for males. During 2001 and 2014, the highest number of years of LE30 lost in both education groups was due to cardiovascular diseases. Conclusions: Throughout the period of 2001-2014, life expectancy in Lithuania in the post-secondary education group was statistically significantly longer and was increasing more rapidly compared to the up-to secondary education group. Inequalities in life expectancy by level of education significantly increased among both males and females.

Monitoring Health Inequalities at the Municipal Level: Lithuanian Experience.

This study aimed to assess the attitudes of Lithuanian public health professionals towards health inequality monitoring in municipalities. The survey was conducted in public health bureaus (PHBs) and administrations of municipalities in March 2015. All employees of PHBs, all municipal doctors and all employees of health departments were invited to participate in the study (N=318; response rate, 47.2%). The study participants had positive attitudes towards the importance of health inequality monitoring at the municipal level, meanwhile systematic health inequality monitoring was assessed moderately. The majority of the interviewed professionals working at PHBs and municipalities (91.4% and 88.2%, respectively) declared that health indicators were monitored and analysed in their institutions. The respondents acknowledged the importance of routine monitoring of health indicators for assessment of inequalities, but these indicators were not monitored systematically in every municipality and PHB. Public health professionals identified the following measures for better health inequality monitoring: to strengthen intersectoral collaboration, formulate specific objectives of health programmes, promote actions in reducing health inequalities. CONCLUSIONS: Public health professionals working at the municipal level outlined the importance of monitoring and reducing health inequalities. However, health inequality monitoring at the municipal level was considered as insufficient.