Socio-economic mortality inequalities in Lithuania during 2001-2009: the record linkage study

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.

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.

Education inequalities in adult all-cause mortality: first national data for Australia using linked census and mortality data

Background

National linked mortality and census data have not previously been available for Australia. We estimated education-based mortality inequalities from linked census and mortality data that are suitable for international comparisons.

Methods

We used the Australian Bureau of Statistics Death Registrations to Census file, with data on deaths (2011–2012) linked probabilistically to census data (linkage rate 81%). To assess validity, we compared mortality rates by age group (25–44, 45–64, 65–84 years), sex and area-inequality measures to those based on complete death registration data. We used negative binomial regression to quantify inequalities in all-cause mortality in relation to five levels of education [‘Bachelor degree or higher’ (highest) to ‘no Year 12 and no post-secondary qualification’ (lowest)], separately by sex and age group, adjusting for single year of age and correcting for linkage bias and missing education data.

Results

Mortality rates and area-based inequality estimates were comparable to published national estimates. Men aged 25–84 years with the lowest education had age-adjusted mortality rates 2.20 [95% confidence interval (CI): 2.08‒2.33] times those of men with the highest education. Among women, the rate ratio was 1.64 (1.55‒1.74). Rate ratios were 3.87 (3.38‒4.44) in men and 2.57 (2.15‒3.07) in women aged 25–44 years, decreasing to 1.68 (1.60‒1.76) in men and 1.44 (1.36‒1.53) in women aged 65–84 years. Absolute education inequalities increased with age. One in three to four deaths (31%) was associated with less than Bachelor level education.

Conclusions

These linked national data enabled valid estimates of education inequality in mortality suitable for international comparisons. The magnitude of relative inequality is substantial and similar to that reported for other high-income countries.

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.

Changes in inequalities of mortality by education level in Lithuania between 2001 and 2014

OBJECTIVE

The aim of the study is to analyse the changes in inequalities of mortality by education level in Lithuania between 2001 and 2014.

STUDY DESIGN

This is a record-linked cohort study.

METHODS

Information on deaths (in the population aged ≥30 years) from all causes and cardiovascular diseases, cancer, external causes and diseases of the digestive system was obtained from Statistics Lithuania. Mortality rates for these causes were calculated by the level of education per 100,000 person-years. Inequalities in mortality were assessed using a rate ratio and a relative index of inequality with 95% confidence intervals (CIs). Joinpoint regression analysis was used to assess inequality trends between 2001 and 2014.

RESULTS

During the study period, mortality from all causes and from cardiovascular diseases, cancer, external causes and diseases of the digestive system was statistically significantly higher in the group with less education for both men and women, with the exception for female mortality from cancer in 2001. The highest decline was observed in the inequalities of mortality from external causes, whereas a major increase was observed in the inequalities of mortality from diseases of the digestive system. A large increase in inequalities was observed in mortality from external causes for men (on average by 3.5% per year [95% CI = 2-5.1]), whereas, for women, the highest increase in inequalities was observed in mortality from diseases of the digestive system (on average by 3% per year [95% CI = 0.6-5.5]). The slowest increase in mortality inequalities was noted for cardiovascular diseases for both men (on average by 1.1% per year [95% CI = 0.4-1.9]) and women (on average by 0.8% per year [95% CI = 0.3-1.3]).

CONCLUSION

Between 2001 and 2014, the inequalities in mortality by level of education in Lithuania significantly increased in terms of mortality from all causes, cardiovascular diseases, cancer, external causes and diseases of the digestive system.

Alcohol-related emergency department visits and income inequality in New York City, USA: an ecological study

OBJECTIVES

Previous research has found that greater income inequality is related to problematic alcohol use across a variety of geographical areas in the USA and New York City (NYC). Those studies used self-reported data to assess alcohol use. This study examined the relationship between within-neighborhood income inequality and alcohol-related emergency department (ED) visits.

METHODS

The study outcome was the alcohol-related ED visit rate per 10,000 persons between 2010 and 2014, using data obtained from the New York Statewide Planning and Research Cooperative System. The main predictor of interest was income inequality, measured using the Gini coefficient from the American Community Survey (2010-2014) at the public use microdata area (PUMA) level (n=55) in NYC. Variables associated with alcohol-related ED visits in bivariate analyses were considered for inclusion in a multivariable model.

RESULTS

There were 420,568 alcohol-related ED visits associated with a valid NYC address between 2010 and 2014. The overall annualized NYC alcohol-related ED visit rate was 100.7 visits per 10,000 persons. The median alcohol ED visit rate for NYC PUMAs was 88.0 visits per 10,000 persons (interquartile range [IQR], 64.5 to 133.5), and the median Gini coefficient was 0.48 (IQR, 0.45 to 0.51). In the multivariable model, a higher neighborhood Gini coefficient, a lower median age, and a lower percentage of male residents were independently associated with the alcohol-related ED visit rate.

CONCLUSIONS

This study found that higher neighborhood income inequality was associated with higher neighborhood alcohol-related ED visit rates. The precise mechanism of this relationship is not understood, and further investigation is warranted to determine temporality and to assess whether the results are generalizable to other locales.

The Socio-Economic Health Deprivation Index and its association with mortality and attitudes towards influenza vaccination among the elderly in Palermo, Sicily

Introduction

Socio-economic status (SES) seems to be a determinant of health and is associated with vaccination coverage among older and at-risk populations. The aim of this study was to evaluate trends in health outcomes and the Socio-Economic and Health Deprivation Index (SEHDI) among elderly people in the city of Palermo.

Methods

In the 2015 CCM project, the Palermo Unit collected mortality data for use in validating the SEHDI. Italian census data from 2009 to 2015 on overall mortality and causes of death were used. The outcome used to validate the SEHDI was vaccination coverage from the 2009-2010 to 2014-2015 influenza seasons among the elderly in Palermo.

Results

The SEHDI correlated significantly with all-cause mortality (p < 0.05), though this correlation displayed a decreasing trend. Regarding mortality due to influenza or pneumonia, however, the significant correlation (p < 0.05) showed an increasing trend. A linear trend was observed in the inverse correlation between the SEHDI and vaccination coverage rates (p < 0.05), with an overall 27% vaccination coverage among older people. Elderly subjects living in a census district with more regular immigrants, divorced people and single-parent families were more reluctant to undergo influenza vaccination.

Conclusions

This study allowed us to identify subgroups of elderly people who are less likely to adhere to influenza vaccination, and to whom health promotion interventions could be addressed in order to facilitate "healthy aging".

Priorities in effective management of primary health care institutions in Lithuania: Perspectives of managers of public and private primary health care institutions

Background

Primary health care institutions are looking for opportunities to create value for patients and to increase the competitiveness of the health care institution. Determination of competitive priorities for creation of value for patients in the management of primary health care institutions allows improving competitiveness and achieving a competitive advantage in the market.

The aim of the study

To determine the priorities in the management of public and private primary health care institutions by using the focus group discussion method with managers.

Methods

The study was exploratory with intention to find a ground for a management theory and to be the root for the development of health care reform in Lithuania. Focus group discussions were held in 10 Lithuanian counties; 10 focus group sessions were carried out. A total of 48 primary health care executives were interviewed. The participants of this qualitative study were given 8 questions related to value creation of the primary health care institution to patients and rise in competitiveness. The main question of the focus group discussion was “What are the main priorities of management of primary health care institution?” The criteria of data collection based on the deep understanding of the phenomenon and the richness of data expressed by participants of the research.

Results

Qualitative research showed that the priorities of management of primary health care institutions were work management of an organization; human resources management; patient management; and health policy decision making. The participants of focus groups pointed out that effective work of primary health care institutions is ensured by the model of management, doctor-patient communication, quality and timely delivery of health care services, and financial resources. The major decisions involving the management of patients were as follows: meeting patients’ expectations, quality and timely satisfaction of patients’ needs, effective solution of patients’ problems, patient-centered services, patient satisfaction, and communication with the patient. Accessibility to services, quality, geographical accessibility, disease prevention, strengthening of patients’ health and adequate funding were mentioned as the priorities of health policy.

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.

Trends in major risk factors and mortality from main non-communicable diseases in Lithuania, 1985-2013

Background

This study aimed to assess the trends in the prevalence and levels of risk factors and mortality from main non-communicable diseases in the Lithuanian population aged 45–64 years during 1985 to 2013.

Methods

Data from four general population surveys conducted between 1985 and 2008 were used. All these surveys were carried out in Kaunas city and five randomly selected municipalities of Lithuania. Risk factors measured at each survey included regular smoking, overweight, obesity, arterial hypertension, and high levels of blood lipids. In total, data of 10,719 subjects (4,965 men and 5,754 women) aged 45–64 were analysed. Trends in standardized all-cause mortality and mortality from cardiovascular disease (CVD), coronary heart disease (CHD), and malignant neoplasms were estimated for both sexes by joinpoint regression analysis.

Results

In 1985–2013, some favourable trends were observed in the age-standardized mean levels and prevalence of risk factors and mortality from main non-communicable diseases in the Lithuanian middle-aged population. The mean values of blood lipids (with the exception of triglycerides) and the prevalence of dyslipidemias declined. In women, mean levels of systolic blood pressure and body mass index decreased, while in men, the levels of these factors increased. The prevalence of arterial hypertension and obesity increased in men. The proportion of obese women decreased. Smoking prevalence increased in both men and women. From 2007 to 2008, significant downward trends, which were steeper in women than in men, were observed in all-cause, CVD, and CHD mortality.

Conclusions

Despite the favourable changes in some risk factors and mortality rates, the prevalence of risk factors and mortality from main non-communicable diseases in Lithuania are still high. This indicates the importance of the ongoing primary and secondary prevention and optimal treatment of these diseases.