Socioeconomic inequalities in the non-fatal and fatal burden of disease: findings from Scottish Burden of Disease (SBoD) 2016 Scottish Burden of Disease Project Team

Background SBOD2015 was the first endeavour to produce burden of disease estimates in Scotland using linkage of routine health records. In 2017, the study highlighted disparities in burden due to morbidity and mortality with respect to age and gender for 132 conditions, diseases and injuries. Objectives The aim of SBOD2016 is to report on socioeconomic inequalities to provide further evidence to support preventable public health. Methods Morbidity estimates were estimated using an extensive range of administrative datasets to provide a transparent and systematic approach to describe non-fatal population health loss. Combining these estimates with the Global Burden of Disease 2016 study’s relative assessment of severity and disability for each condition, we were able to calculate the Years Lived with Disability (YLD). Death registrations were used alongside life expectancy data to calculate the Years of Life Lost to premature mortality (YLL) as a measure of fatal burden. Findings Preliminary findings show a three-fold increase in the burden of disease between individuals living in the most deprived areas compared to the least deprived areas. The profile of diseases contributing the largest burden also varies between the most and least deprived areas. Conclusions By combining information on fatal burden with the burden of living in less than ideal health (non-fatal burden), planners and policymakers have a better idea of the contribution that different diseases, conditions and injuries make to the total burden of disease and how this varies by levels of deprivation. This in turn provides information to support decisions about where prevention and service activity should be focused. It also provides a way of looking at the proportion of the burden that can be explained by a range of exposures in the population such as poverty or smoking

What causes the burden of stroke in Scotland? A comparative risk assessment approach linking the Scottish Health Survey to administrative health data

Background: The availability of robust evidence to inform effective public health decision making is becoming increasingly important, particularly in a time of competing health demands and limited resources. Comparative Risk Assessments (CRA) are useful in this regard as they quantify the contribution of modifiable exposures to the disease burden in a population. The aim of this study is to assess the contribution of a range of modifiable exposures to the burden of disease due to stroke, an important public health problem in Scotland. Methods: We used individual-level response data from eight waves (1995–2012) of the Scottish Health Survey linked to acute hospital discharge records from the Scottish Morbidity Record 01 (SMR01) and cause of death records from the death register. Stroke was defined using the International Classification of Disease (ICD) 9 codes 430–431, 433–4 and 436; and the ICD10 codes I60-61 and I63-64 and stroke incidence was defined as a composite of an individual’s first hospitalisation or death from stroke. A literature review identified exposures causally linked to stroke. Exposures were mapped to the layers of the Dahlgren & Whitehead model of the determinants of health and Population Attributable Fractions were calculated for each exposure deemed a significant causal risk of stroke from a Cox Proportional Hazards Regression model. Population Attributable Fractions were not summed as they may add to more than 100% due to the possibility of a person being exposed to more than one exposure simultaneously. Results: Overall, the results suggest that socioeconomic factors explain the largest proportion of incident stroke hospitalisations and deaths, after adjustment for confounding. After DAG adjustment, low education explained 38.8% (95% Confidence Interval 26.0% to 49.4%, area deprivation (as measured by the Scottish Index of Multiple Deprivation) 34.9% (95% CI 26.4 to 42.4%), occupational social class differences 30.3% (95% CI 19.4% to 39.8%), high systolic blood pressure 29.6% (95% CI 20.6% to 37.6%), smoking 25.6% (95% CI 17.9% to 32.6%) and area deprivation (as measured by the Carstairs area deprivation Index) 23.5% (95% CI 14.4% to 31.7%), of incident strokes in Scotland after adjustment. Conclusion: This study provides evidence for prioritising interventions that tackle socioeconomic inequalities as a means of achieving the greatest reduction in avoidable strokes in Scotland. Future work to disentangle the proportion of the effect of deprivation transmitted through intermediate mediators on the pathway between socioeconomic inequalities and stroke may offer additional opportunities to reduce the incidence of stroke in Scotland

Quantifying the fatal and non-fatal burden of Stroke and its modifiable determinants using routine Scottish healthcare datasets

ABSTRACT Objectives The gap between a population’s actual and ideal health can be quantified by Disability-Adjusted Life Years (DALY). This metric combines the Years Lived with Disability (YLD) and Years of Life Lost (YLL). When supplemented by a Comparative Risk Assessment (CRA) it can depict the magnitude of disease burden and the effect that modifiable exposures contribute. We aim to utilise routine healthcare records to quantify the burden and potential reduction in DALY caused by stroke. Approach Hospital stays involving a stroke diagnosis (ICD-9: 430-431, 433-34, 436; ICD-10: I60-61, I63-64) were identified through secondary care primary diagnoses from 1981-2013 and used to derive the incidence of acute stroke and the point-prevalence of chronic stroke. Disability weights for each health state of stroke sequelae were sourced from the Global Burden of Disease 2013 study and used to derive YLD. YLL for each death was calculated using Scotland-specific life tables for deaths where stroke was the underlying cause. Eight waves of the Scottish Health Survey (SHES) from 1995-2012 were linked to secondary care and mortality records. Risk factors were identified from SHES then mapped to levels in the Dahlgren and Whitehead model and Population Attributable Fractions (PAFs) were calculated for each risk factor that was a significant casual risk of stroke from a Cox-proportional hazard regression model. Results Stroke was responsible for 47,836 DALY in Scotland during 2013 which was a reduction of 33.3% from 2000. The proportion of YLD contributing to DALY was 7.6% in 2000 rising to 14.4% in 2013. The main reasons for the changing profile of DALY are due to the large reduction in mortality and influence of the rising prevalence of chronic stroke. Stroke mortality reduced 34.3% during the period 2000-2013 from 7,013 deaths in 2000 to 4,610 in 2013, whilst chronic prevalence increased from 46,184 in 2000 to 59,367 in 2013. Between 23.5 to 38.8% of excess first stroke incidence can be explained by education, social class and area deprivation, which were all significant predictors of stroke after adjusting for confounding. Altering the exposure distribution for each independent risk factor to its theoretical minimum risk exposure level could potentially reduce the DALY by between 9,615 to 15,882 in 2013. Conclusion This study highlights the benefit of using linked administrative health records to quantify the burden of stroke on the population and how public health interventions to tackle inequalities would be a method of reducing strokes in Scotland

Trends and inequalities in the burden of mortality in Scotland 2000-2015.

BACKGROUND:Cause-specific mortality trends are routinely reported for Scotland. However, ill-defined deaths are not routinely redistributed to more precise and internationally comparable categories nor is the mortality reported in terms of years of life lost to facilitate the calculation of the burden of disease. This study describes trends in Years of Life Lost (YLL) for specific causes of death in Scotland from 2000 to 2015. METHODS:We obtained records of all deaths in Scotland by age, sex, area and underlying cause of death between 2000 and 2015. We redistributed Ill-Defined Deaths (IDDs) to more exact and meaningful causes using internationally accepted methods. Years of Life Lost (YLL) using remaining life expectancy by sex and single year of age from the 2013 Scottish life table were calculated for each death. These data were then used to calculate the crude and age-standardised trends in YLL by age, sex, cause, health board area, and area deprivation decile. RESULTS:Between 2000 and 2015, the annual percentage of deaths that were ill-defined varied between 10% and 12%. The proportion of deaths that were IDDs increased over time and were more common: in women; amongst those aged 1-4 years, 25-34 years and >80 years; in more deprived areas; and in the island health boards. The total YLL fell from around 17,800 years per 100,000 population in 2000 to around 13,500 years by 2015. The largest individual contributors to YLL were Ischaemic Heart Disease (IHD), respiratory cancers, Chronic Obstructive Pulmonary Disease (COPD), cerebrovascular disease and Alzheimer's/dementia. The proportion of total YLL due to IHD and stroke declined over time, but increased for Alzheimer's/dementia and drug use disorders. There were marked absolute inequalities in YLL by area deprivation, with a mean Slope Index of Inequality (SII) for all causes of 15,344 YLL between 2001 and 2015, with IHD and COPD the greatest contributors. The Relative Index of Inequality (RII) for YLL was highest for self-harm and lower respiratory infections. CONCLUSION:The total YLL per 100,000 population in Scotland has declined over time. The YLL in Scotland is predominantly due to a wide range of chronic diseases, substance misuse, self-harm and increasingly Alzheimer's disease and dementia. Inequalities in YLL, in both relative and absolute terms, are stark

Trend in the slope index of inequality in age-standardised YLL per 100,000 population per year for the ten largest contributors of YLL (2001–2015, cumulative in upper panel, individual causes in lower panel).

<p>Trend in the slope index of inequality in age-standardised YLL per 100,000 population per year for the ten largest contributors of YLL (2001–2015, cumulative in upper panel, individual causes in lower panel).</p

Temporal trends in the crude YLL per 100,000 population by cause (Scotland, 2000–2015, cumulative in upper panel, individual causes in lower panel).

<p>Temporal trends in the crude YLL per 100,000 population by cause (Scotland, 2000–2015, cumulative in upper panel, individual causes in lower panel).</p

Percentage of total Age-Standardised YLL accounted for by specific causes (Scotland, 2000–2015).

<p>Percentage of total Age-Standardised YLL accounted for by specific causes (Scotland, 2000–2015).</p

Temporal trends in the age-standardised YLL by cause (Scotland, 2000–2015, cumulative in upper panel, individual causes in lower panel).

<p>Temporal trends in the age-standardised YLL by cause (Scotland, 2000–2015, cumulative in upper panel, individual causes in lower panel).</p