Viernes 3 de Octubre / Friday 3, October

18:00:00 a/to 19:30:00

Moderador/Chairperson:

Klim McPherson y Juan José Criado

449 REGIONAL DIFFERENCES IN LIFE EXPECTANCY AND THE INFLUENCE OF THE POLITICAL AND SOCIO-ECONOMIC CONTEXT IN GERMANY FROM 1986 TO 1998

Uwe Helmert*, Waldemar Streich*, Dieter Borgers**

*Center for Social Policy Research, University Bremen, Bremen, Germany. **Institute for General Medicine, Heinrich-Heine University, Duesseldorf, Germany.

Introduction: Regional trends in life expectancy in Germany have become an intriguing subject for scientists and health-policy makers, due to the rapid social, political, and economic changes in Central and Eastern Europe since the end of the 1980s. The aim of the study is to investigate to what extent trends in mean life expectancy are influenced by political variables and socioeconomic characteristics that play a role at the regional level of the federal states in Germany.

Methods: Data on life expectancy in males and females at birth are analysed from 1986 to 1998 for seven federal states in Western Germany and five federal states in Eastern Germany. These twelve federal states are classified into five types of political government since 1980: 1) long-term christian democratic 2) long-term social democratic 3) change from christian to social democratic 4) change from communist to social democratic 5) change from communist to christian democratic. Five state-specific socio-economic indicators are used: gross domestic product per capita in 1996, mean income white collar and mean income blue collar in 1999, unemployment rate in 1991 and 1998. Descriptive statistics and linear regression analysis were performed to estimate the impact of the political and socio-economic variables for the state-specific mean life expectancy between 1986 and 1998.

Results: The study showed three main results. First, mean life expectancy has been directly influenced by the major political forces that determined policies in East and West-Germany. Differences in life expectancy between Eastern and Western Germany increased during the phase of political stagnation in East Germany in the years before the collapse of the German Democratic Republic and decreased sharply after reunification in 1990. Second, mean life expectancy was higher in federal states with predominantly christian democratic governments than in those with predominantly social democratic governments. Third, mean life expectancy was strongly related to the economic power of the federal states. The lower the unemployment rate and the higher the gross national product, the higher was the mean life expectancy.

Conclusions: Because the federal states characterized by a more prosperous economic situation were those with a predominantly Christian democratic government, while federal states with a less prosperous situation were mostly governed by social democrats, it is difficult to disentangle the effects of economic and political factors on life expectancy. Nevertheless did this study underline the importance of politics and policies on such robust and more general health indicators like the mean life expectancy at birth.

450 IS SOCIAL CAPITAL ASSOCIATED WITH HEALTH?

Margaret Bright*, Natalie Baig*, Magnolia Cardona*, Christine McClintock**, Catherine Harper*, Paul Harris*, David Firman**, Sue Smyllie*

*Public Health Services, Queensland Health Department, Australia. **Health Information Centre, Queensland Health Department, Australia.

Introduction: This project aimed to provide a cross sectional measurement of social capital in the State of Queensland, Australia, and explore the relationships between social capital, lifestyle behaviours and health outcomes within a social determinants of health framework. Information will be used to progress the integration of social determinate indicators in health planning and monitoring, required to address health inequalities.

Methods: Social capital in the Queensland population was assessed using the Social Capital Index©, administered by telephone interviews of 2671 adults, with oversampling in remote and rural areas. The Index© reflects 7 dimensions of social capital; generalised reciprocity and cohesion, community identity, generalised trust, tolerance of diversity, civic trust, community involvement and informal social networks. In addition, questions exploring efficacy (sense of control over the decisions that affect life), quality of life, self reported health status, selected health behaviours and sociodemographics were included.

Using weighting algorithms, the separate dimension scores and a summary score of core social capital dimensions (reciprocity and cohesion, community identity and generalised trust) were generated. Good health behaviour was a dichotomous variable of three or more behaviours consistent with guidelines (BMI, smoking, physical activity, fruit, vegetables). Multiple regression, logistic regression and principal components factor analysis were used to explore the relationship of social capital and efficacy to health behaviours, outcome measures and sociodemographic variables.

Results: Logistic regression analysis showed that social capital and efficacy were the leading associates with health outcome measures, controlling for all other factors. The core social capital dimensions summary score was significantly associated with self-reported health (OR 1.7 95%CI 1.3-2.1), satisfaction with health (OR 1.7; 95%CI 1.4-2.0) and quality of life (OR 2.0; 95%CI 1.5-2.6). People with higher social capital, in particular community involvement and generalised trust, were more likely to report multiple good health behaviours (OR 1.2 95%CI 1.1-1.4; OR 1.2 95%CI 1.0-1.3 respectively). Efficacy were a highly influential factor in the reporting of higher quality of life (OR 3.2 95%CI 2.1-4.7), better health (OR 2.2 95%CI 1.6-3.2) and greater satisfaction with health (OR 1.9 95%CI 1.4-2.6). There was no significant difference in core social capital dimensions summary score in people living in rural, remote or urban communities in Queensland.

Conclusions: Social capital, characterised as higher levels of neighbourhood trust and reciprocity and a stronger sense of community identity, significantly contributes to quality of life, self reported health and satisfaction with health. In addition, this survey clearly sheds light on the diversity and complexity of the factors associated with health and wellbeing. Specifically, this survey provides further evidence that the social determinants are indeed important factors associated not only with subjective health outcomes but also the prevalence of good health behaviours.

451 IS VIOLENCE MODIFIER OF THE RELATIONSHIP BETWEEN INCOME INEQUALITY AND HEALTH?

Joaquín Beltrán Peribáñez*, Santiago Perez Hoyos**, Ildefonso Hernández Aguado*, Alberto Torres Cantero*, Alberto Torres Cantero*

*Departamento Salud Pública, Universidad Miguel Hernández, Alicante, España. **Escuela Valenciana de Estudios para la Salud (EVES), Valencia, España.

Introduction: Violence is considered a determinant of health independently of its direct effect, through the loss of social capital. Violence could interact negatively worsening the effect of income inequality in health. The objective of this communication is to study whether violence modifies the relationship between income inequality and health.

Methodology: World Bank and the World Report on Violence and Health from WHO data were used. Health outcome was as infant mortality rate and life expectancy for the years 1997-2000. The independent variable was the income inequality measured by the Gini coefficient for years 1994-1998. As modifier variable violence was measured as age standardized homicide mortality rates between 1990 and 2000. A multiple lineal regression model adjusted for variables of interest was performed. One hundred and ninety one countries from all continents were included, but data on the three relevant variables was limited. Country was the unit of analysis.

Results: Economic inequalities and infant mortality correlated positively (r=0.385, p <0.01). The stratification in three groups: high (more then 1/10000) and low homicide mortality rates, and those countries without homicide mortality data did not change the shape of the relation between income inequality and health. However, infant mortality was higher in those countries with high homicide rates and still much higher in those countries without data on homicide rates. The multiple lineal regression analysis included both variables (R2=40.5%, p <0.0001), Gini coefficient and homicide rates. Interaction between the two variables was not statistically significant. When health outcome was measured as life expectancy the results were not very different.

Conclusions: Using country as unit of analysis, violence does not modify the relation between income inequality and health. The role that violence plays in the relationship between income inequalities and health seems to be confusion rather then interaction. Quality of data and information bias could limit the validity of the observed results. Small area analysis avoiding these limitations, will better establish the effects of violence as a social determinant of health.

452 ANALYSIS OF TRENDS IN HUMAN HEALTH PARAMETERS IN THE REGION

Natalia Sorokovikova*, Arina Tankanag**

*Laboratory of functional ecology, Institute of Basic Biological Problems of the R AS, Pushchino, Moscow region, Russia. **Laboratory of Biophysics, Institute of Cell Biophysics of the RAS, Pushchino, Moscow region, Russia.

Introduction: On the population level, human health results from a great complex of causes: social, psychological, economic, ecological and so on. They are closely interrelated, and, at every stage of development, leading position belongs to some of them. The aim of the work was to find out, what factors were responsible for the increase in morbidity and sharp rise in mortality in Russian regions in the 1990s.

Methods: The relationships between human health and some impact factors have been studied by the example of the Oka River basin located in the central part of the European territory of Russia. The basin includes fully or partially the areas of 12 administrative regions. For Russia, trends in infant mortality (1960-2000), male and female death rates standardised by age (1965-2001) were analysed. Across the regions of the Oka Basin, dynamics of standardised death rates (1994-2001), death rates in working age (1990-2001), infant mortality (1985-2000), disability (1985-2000), prevalence (1989-2000) and incidence (1992-2000) sickness rates were examined. Changes in social, economic, ecological, demographic and medical service parameters were studied as well. Several analyses of correlation for data across the regions were carried out beginning from 1985 to 2000. To make the analysis more detailed the socio-economic, demographic and health data were examined on a larger scale, across 148 administrative districts and towns within 4 regions: Moscow, Orel, Vladimir and Ryazan.

Results: In 1985 no close relationship was found between parameters of human health and per capita income. It was due to the different way of distribution of salary and social payments at this period, whereas from 1994 this relation was fixed. The standardised death rate was inversely related to per capita income, per capita gross regional product, investments and other socio-economic parameters. The prevalence sickness rate was positively related to the part of people, having income below the survival level and to the index of income decrease. The correlation analysis of data across 148 administrative districts and towns has revealed the analogous inverse correlation for the death rate and per capita income and investments (in some regions). On the basis of data across the regions, the plausible relation between mortality and ecological and medical service parameters was missing.

Conclusions: The comparison of health state and health impact data showed that the health level essentially depends on the welfare of the socio-economic situation. In all regions with minimum social and economic parameters the worst health level was seen. And on the contrary, the relatively best health level was in the regions with favourable social and economic conditions. This analysis allowed us to identify specific regions, which require immediate measures to regulate the health state and social situation.

453 HAVE THE GLOBAL IMPROVEMENTS IN MORTALITY OVER THE PAST 50 YEARS BEEN ACCOMPANIED BY CONVERGENCE IN THE MORTALITY EXPERIENCE OF THE WORLD'S POPULATION?

Kath Moser*, Vladimir Shkolnikov**, Dave Leon*

*Epidemiology Unit, London School of Hygiene and Tropical Medicine, London, UK. **Data Laboratory, Max Planck Institute for Demographic Research, Rostock, Germany.

Introduction: Over the past 50 years most countries have experienced appreciable reductions in mortality particularly in infancy and childhood. In fact, the mortality of the world's population as a whole has steadily improved over this period. Little work has been done to look at how far these advances have been accompanied by convergence in the global mortality experience. The view that things were set on a path of inexorable improvement that would benefit all countries has been undermined in the last decade as the full scale of the HIV-AIDS epidemic has become apparent. The serious adverse health consequences of the collapse of the Soviet Union have provided further evidence that mortality reversals can no longer be regarded as rare and exceptional phenomena. This paper presents the first systematic analysis of mortality convergence over the second half of the 20th century using a novel index to assess whether humanity's mortality experience is becoming more or less equitable.

Methods: Analysis of United Nations mortality data (life expectancy at birth and infant mortality rate) for 1950-2000 for major world regions and all 152 countries with population exceeding 1M in 2000. Global convergence in mortality in any period is calculated using a novel application of a standard measure: the average absolute inter-country mortality difference between each and every pair of countries weighted by their population sizes (AWPD).

Results: During 1950-55 to 1965-70 all 152 countries showed increases in life expectancy. Most countries continued to show improving mortality during 1965-70 to 1980-85 although in parts of the Soviet Union life expectancy fell. Most recently (1980-85 to 1995-2000) life expectancy fell in 24 countries in eight of which (all in sub-Saharan Africa plus North Korea) it fell by over 5 years. Most countries with falling life expectancy did not experience increasing infant mortality suggesting the mortality increases were largely among adults. These trends led to a convergence of world mortality experience up until the late 1980s (decline in AWPD) since when this trend has been replaced by one of divergence (increase in AWPD).

Conclusions: This analysis provides the first attempt to quantify global mortality convergence. It has shown that since the late 1980s the distribution of mortality worldwide has become less equitable thus reversing the convergence of the previous 30 years. While some countries are progressing quickly others are lagging behind indicating that the improvement in world life expectancy is not being equally shared by all. This underlines the importance that the many global health initiatives incorporate some means of targeting their efforts at countries with worsening mortality. The average weighted pair difference measure proposed in this paper could provide an invaluable addition to current indicators making it possible to monitor what is happening globally.