Inequalities in the disease burden in Scotland: an area level analysis

Abstract In the context of increasing demand for evidence-based policy, attempts to address or mitigate the effects of disadvantage have been usefully informed by comprehensive indices of multiple deprivation. These indices combine indicators on a range of dimensions of deprivation to classify neighborhoods or localities. Through combining information on fatal and non-fatal health loss, burden of disease studies allow planners and policy-makers to have a better understanding of the contribution of different diseases and injuries to the total burden of disease. These estimates can be augmented through studies, stratified by investigating inequalities in the burden of disease due to area-based deprivation. Doing so, helps contribute to discussions about where prevention and service activity should be focused to address health inequalities. The Scottish Burden of Disease study uses the Scottish Index of Multiple Deprivation (SIMD) as means to report on of the extent of inequality in the burden of disease in Scotland between people living in the areas of greatest, and of least, multiple deprivation. The SIMD quantifies deprivation based on data zones, a geographical unit comparable to a postcode. Using pooled and weighted data from seven domains (employment, income, crime, housing, health, education and geographic access), each data zone is given a composite rank out of 6,505 data zones. The composite rank was then converted to a decile, with 1 assigned to the 10% most deprived data zones and 10 to the 10% least deprived. In this presentation we will show the key steps involved in undertaking an area-based analysis of health inequalities in the burden of disease in Scotland using results from the Scottish Burden of Disease 2019 study, and from our monitoring of COVID-19 disability-adjusted life years.

Driven by the influential Global Burden of Disease (GBD) study, the burden of disease (BOD) approach has gained wide interest at national and international level to quantify the state of health and health inequalities. Central to the BOD approach is the Disability-Adjusted Life Year (DALY) metric, which quantifies the health impact of diseases, injuries and risk factors as the number of healthy life years lost compared to a counterfactual scenario of perfect health all life long. The BOD approach offers a valuable platform to quantify social inequalities in health, i.e., differences in health status by socioeconomic and sociodemographic characteristics. This is highly relevant, as health inequalities penalising socially disadvantaged groups are one of the most consistent, and persistent, findings in epidemiology, for almost every health outcome and socioeconomic indicator. Monitoring social inequalities in health is therefore a key priority for national health authorities. There are different ways by which social inequalities can be integrated in the BOD framework, but all come with important data challenges. Individual-level stratification is a common approach for quantifying inequalities by age and sex, but is more challenging for other sociodemographic and socioeconomic indicators. Area-level stratification allows for ecological analyses between BOD estimates and indices of social deprivation. Social inequalities can also be assessed using comparative risk assessment, by which the relative risk for adverse health outcomes in function of social position is to be quantified. This skills building workshop will present the methods that have been applied in different national burden of disease studies to include social inequalities, including a discussion of their strengths and weaknesses. By providing a step-by-step presentation of how the methods have been applied, attendees will gain unique insights in the different ways by which social inequalities can be integrated in the BOD framework. Key messages: The burden of disease framework offers a valuable platform to quantify and monitor social inequalities in health, which is a key priority for health authorities. Attendees will receive an overview of the different ways by which social inequalities can be integrated in the burden of disease framework, including a discussion of their strengths and weaknesses.
Abstract citation ID: ckac129.400 Using individual-level stratification as an approach to integrating social inequalities into the burden of disease Substantial social inequalities in almost all non-fatal and fatal health outcomes are one of the most consistent and universal epidemiological findings. Therefore, monitoring social inequalities in health is considered a key priority for researchers and policy makers. The Global Burden of Disease Injuries, and Risk Factors Study (GBD) is the most comprehensive worldwide observational epidemiological synthesis of data to date. However, currently, the GBD Study does not include the potential to stratify associated metrics, such as the disability-adjusted life years metric, by different socioeconomic factors, such as education or income level. Although The GBD Study does include the Socio-Demographic Index, this measure is only useful when comparing between, and not within, countries or regions. We conducted a Cox regression analysis using a national longitudinal prospective cohort study design and registrybased data linked at the individual-level. We stratified on educational groups and investigated cause-specific mortality rates over a 30-year period, adjusting for age, sex and 5-year age cohorts. We also calculate years of life lost (YLLs) stratified by educational groups, standardised by age, and presented for specific years -to investigate trends over time. We discuss the benefits and limitations of this ''individual-level'' stratification approach as one possible solution to the integration of social inequalities into the GBD study or when using a burden of disease framework approach more generally.
Abstract citation ID: ckac129.401 Inequalities in the disease burden in Scotland: an area level analysis In the context of increasing demand for evidence-based policy, attempts to address or mitigate the effects of disadvantage have been usefully informed by comprehensive indices of multiple deprivation. These indices combine indicators on a range of dimensions of deprivation to classify neighborhoods or localities. Through combining information on fatal and nonfatal health loss, burden of disease studies allow planners and policy-makers to have a better understanding of the contribution of different diseases and injuries to the total burden of disease. These estimates can be augmented through studies, stratified by investigating inequalities in the burden of disease due to area-based deprivation. Doing so, helps contribute to discussions about where prevention and service activity should be focused to address health inequalities. The Scottish Burden of Disease study uses the Scottish Index of Multiple Deprivation (SIMD) as means to report on of the extent of inequality in the burden of disease in Scotland between people living in the areas of greatest, and of least, multiple deprivation. The SIMD quantifies deprivation based on data zones, a geographical unit comparable to a postcode. Using pooled and weighted data from seven domains (employment, income, crime, housing, health, education and geographic access), each data zone is given a composite rank out of 6,505 data zones. The composite rank was then converted to a decile, with 1 assigned to the 10% most deprived data zones and 10 to the 10% least deprived. In this presentation we will show the key steps involved in undertaking an area-based analysis of health inequalities in the burden of disease in Scotland using results from the Scottish Burden of Disease 2019 study, and from our monitoring of COVID-19 disability-adjusted life years. Educational inequalities in mortality are increasingly recognized as one of the main challenges for health policy. Studies comparing European countries have shown that such inequalities are substantial almost everywhere, but that there are important variations between countries, suggesting great scope for reduction. However, identifying this scope is difficult because it requires comparative information about the educational distribution of mortality rates, risk factors and relative risks. In this presentation I show how this can be done, by quantifying the impact of a theoretical equalization of the distribution of several known risk factors for mortality, in a comparative risk assessment approach. Harmonized data set on mortality (from register data) and risk factors (from survey data) by educational level for 21 European populations in the early 2000s were applied. The impact of the risk factors on mortality in each educational group was determined using Population Attributable Fractions (PAF). The impact on inequalities in mortality was estimated applying two counterfactual scenarios: a theoretical upward levelling scenario in which it is assumed that inequalities in the risk factor were completely eliminated, and a more realistic best practice scenario, in which it is assumed that inequalities in a risk factor were to be reduced to those seen in the country with the smallest inequalities for that risk factor. The analysis shows how information on risk factors, mortality rates and relative risks can be combined from different data sources and provide a meaningful analysis of the European mortality burden that can be linked to educational inequalities in risk factors. The analysis also shows that upward levelling scenarios and best practice scenarios demonstrate a theoretical potential for reducing inequalities in mortality. Refugees are also at increased risk of mental disorders due to exposure to trauma and ongoing daily stressors. Host country health systems are faced with the challenge of ensuring accessible and affordable care for NCDs and mental disorders to this population. There is no consensus on the most effective and sustainable approaches for achieving this.

Objectives:
This workshop will provide a platform for sharing knowledge to support host country health systems. The objectives of the workshop are to i) identify sustainable health system approaches to providing quality health care for NCDs and mental disorders to refugees from Ukraine, and ii) establish research priorities to support host country health system decision-making.

Format:
The workshop will consist of a panel with 4 speakers, followed by a roundtable discussion. Each panel member will make a short presentation (5 min) related to health system responses for NCDs and mental disorders in refugee populations. They