In this study, we aimed to establish whether specific indicators of the Scottish Index of Multiple Deprivation (SIMD) were associated with mortality in a prospective cohort of patients admitted to hospital with Covid-19 disease in the Lothian Region between March 1st and June 30th, 2020.
Previous studies have demonstrated an increased risk of death in patients living in more deprived communities in multiple countries3,6,7,11. We found an increased risk of death among age- and sex-adjusted patients in quintiles 1 and 3 (OR 1.75, CI 0.99-3.08, p=0.053 and OR 2.17, CI 1.22-3.86, p=0.009, respectively), but this association was not upheld in our multivariable model when adjusted for co-morbidities and clinical parameters of severity at presentation. We found no association between ICU admission and greater deprivation.
Importantly, SIMD scores are weighted calculations of each of the seven domains; Income and Employment domain are weighted twice as heavily as Health or Education in final aggregate scores10. We therefore selected 12 indicators of deprivation within the SIMD that could plausibly be linked to poorer outcomes in our cohort10. In our multivariable, age- and sex-adjusted regression model, we found a statistically significant risk of mortality among patients in areas that were more income deprived or reported higher-than-average numbers of alcohol-related hospital admissions.
We identified several factors that may explain the divergence in our results and contribute to the complexity of defining how deprivation, a multi-faceted entity where environmental, biological, social, economic, and educational factors interact over time, contributes to poorer outcomes in health.
Deprivation is a well-established risk factor for poorer health outcomes, but the underlying physiological mechanisms remain controversial. Some studies have proposed a biological link whereby increased inflammatory responses triggered by chronic social and environmental stress more common in deprived communities accelerate atherosclerosis and progression of dementia14–16, but few studies have sufficiently long follow-up periods to adequately account for confounders given the multifactorial nature of deprivation17–20.
Deprivation has also been described as a barrier to accessing healthcare and, in Lothian, this is supported by recent evidence from the Infectious Diseases Outpatient Antibiotic Treatment (OPAT) that demonstrated that referrals were twice as likely to occur among patients belonging to the least deprived SIMD quintile21.
Because deprivation is multifactorial, its study relies on amalgamating a range of indicators to develop a detailed picture of residents in a specific location10,22,23. Indices of multiple deprivation (IMDs) such as the SIMD have gained traction as useful tools for governments to use to direct funds to specific locations based on the assumption that the spatial characteristics of a geographical locality’s deprivation indicators affects the opportunities for poverty reduction for the entire population22,24.
The limitations of this approach are that IMDs fail to capture the key aspects of deprivation affecting any one individual and experienced general practitioners operating in “Deep End” practices that serve the most deprived communities in Scotland have called for increased devolution of healthcare in at-risk communities as well as heightened awareness of the impact of deprivation on health and health-seeking behaviour to reduce inequities in health25,26.
The Lothian region is comparatively more affluent than other regions of Scotland, and it is likely that using SIMD as a marker for individual deprivation fails to account for pockets of deprivation in the region that are not captured in the traditional quintile distribution of SIMD. Whilst we were not able to establish that deprivation by SIMD quintile was a risk factor for poorer outcomes in our cohort, the finding that patients who resided in datazones with greater income deprivation and greater-than-average admissions to hospital due to excess alcohol consumption had a significantly greater risk of death, suggests that a more granular analysis of deprivation indicators may help to identify individuals or groups at risk of greater mortality in areas where deprivation may be masked by greater overall affluence. The association between income deprivation and increased incidence and higher rates of hospitalization and mortality due to Covid-19 is now well-established in both high- and low-income settings, further demonstrating the need for public health interventions to reduce barriers to testing, access to medical services, and mitigation of correlated risk factors for increased mortality such as obesity and co-morbidities27–30. Alcohol consumption, has, in contrast, not been found to be significantly associated with poorer outcomes, whether measured in terms of harmful intake in individuals31 or in spatial analyses of excessive alcohol consumption32. In our correlation matrix of our 12 pre-selected SIMD indicators of deprivation, our variable for higher-than-average admissions due to excessive alcohol consumption was strongly correlated to comparative illness factor – which measures how many individuals receive contributions for chronic disability – and employment, income, emergency room and drug-related admission rates per data zone. Our findings may reflect the situation in Scotland, where excess hospitalizations and mortality due to harmful alcohol consumption are potentiated by inequality in income, educational attainment, and socio-economic class and may be a useful proxy marker for deprivation not captured elsewhere in the SIMD33.
Our study has several strengths. We were able to analyse a rich dataset of prospectively recruited individuals benefiting from integration of healthcare data extracted from multiple digital platforms into a centralized database. Our cohort study design enabled us to carry out a detailed analysis of deprivation-related exposures in relation to our outcomes of interest. We believe this is one of the few studies examining the role that specific indicators of deprivation in an IMD may play in contributing to poorer outcomes in patients hospitalized with Covid-19 disease.
Our study has several limitations. First, our study was restricted to hospitalized patients, and we are therefore unable to capture data on community transmission and outcomes in those not admitted to hospital. Another limitation is that the Lothian region is itself less representative than Scotland as a whole, with a greater proportion of its population being both more affluent and less likely to be from a minority ethnic group34. Other SIMD indicators not selected for logistic regression analysis may be strongly influencing results of SIMD that our researchers did not think relevant to health.
Finally, The SIMD is recognized as an imperfect tool that relies on area-specific characteristics to determine deprivation, and fails to capture non-spatial deprivation factors that contribute to poorer health outcomes among individuals17,20. Further, aggregate scores are weighted according to domain and assign a greater weight to income and employment deprivation than to health. Lastly, SIMD rankings are reviewed based on ten-year census data, which fail to capture between-census demographic change that may influence a specific data-zone’s evolving deprivation ranking, for example, because of gentrification.
Our pilot study highlights interesting findings that shed light on the applicability of SIMD in determining outcomes in patients hospitalized with Covid-19. We plan to apply our model on a nationwide dataset to determine whether SIMD indicators may prove useful in targeting public health interventions to specific populations to improve outcomes. Further research could also consider increasing population-level subgrouping by applying our model to deciles of deprivation to better capture pockets of deprivation present in more affluent data-zones.