Differences in ill health and in socioeconomic inequalities in health by ethnic groups: a cross-sectional study using 2011 Scottish census

Allik, Mirjam; Brown, Denise; Dundas, Ruth; Leyland, Alastair H.

doi:10.1080/13557858.2019.1643009

Cited by 10 publications

(13 citation statements)

References 51 publications

(79 reference statements)

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“…However, the relationship between ethnicity and health is complex as risk factors are likely to interact and are inextricably linked with wider social determinants of disease. The ethnic disparities identified during the COVID-19 pandemic reflect those consistently demonstrated across chronic conditions such as cardiovascular disease, diabetes, stroke, and hypertension prior to the pandemic [15] , [16] , [17] . These studies demonstrate that ethnic minorities tend to have poorer baseline health compared to majority ethnic groups and coupled with recent findings suggest that imbalances in outcomes following illness persist between ethnic groups.…”

Section: Introductionmentioning

confidence: 93%

Ethnicity and acute hospital admissions: Multi-center analysis of routine hospital data

et al. 2021

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Background: The effects of ethnic and social inequalities on patient outcomes in acute healthcare remain poorly understood. Methods: Prospectively-defined analysis of registry data from four acute NHS hospitals in east London including all patients ≥ 18 years with a first emergency admission between 1st January 2013 and 31st December 2018. We calculated adjusted one-year mortality risk using logistic regression. Results are presented as n (%), median (IQR), and odds ratios (OR) with 95% confidence intervals. Findings: We included 203,182 patients. 43,101 (21%) patients described themselves as Asian, 21,388 (10.5%) Black, 2,982 (1.4%) Mixed, 13,946 (6.8%) Other ethnicity, and 100,065 (49%) White. We excluded 21,700 (10.7%) patients with undisclosed ethnicity. 16,054 (7.9%) patients died within one year. Non-white patients were younger (Asian: 43 [31–62] years; Black: 48 [33–63] years; Mixed 36 [26–52] years) than White patients (55 [35–75] years), with a higher incidence of comorbid disease. In each age-group, non-white patients were more likely to be admitted to hospital. This effect was greatest in the ≥ 80 years age-group (32% non-white admitted to hospital versus 23% non-white in community population). Deprivation was associated with increased mortality in all ethnic groups (OR 1.41 [1.33–1.50]; p < 0.001). However, when adjusted for age, Asian (0.69 [0.66–0.73], p < 0.0001) and Black patients (0.79 [0.74–0.85]; p < 0.0001) experienced a lower mortality risk than White patients. Interpretation: Ethnic and social disparities are associated with important differences in acute health outcomes. However, these differences are masked by statistical adjustment because patients from ethnic minorities present at a younger age. Funding: None

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Section: Introductionmentioning

confidence: 93%

Ethnicity and acute hospital admissions: Multi-center analysis of routine hospital data

et al. 2021

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“…The proposal for the more intensive use of census data in health monitoring of the Roma population can be supported by the success of policies to reduce ethnic/racial inequalities in the United States and in the United Kingdom, which use census-derived ethnicity- and race-specific data in establishing and evaluating interventions [37,38,40].…”

Section: Discussionmentioning

confidence: 99%

“…Self-declared ethnicity-related data based on national censuses have been available for decades in many countries [37,38,39,40]. To avoid the well-known under-registration of Roma ethnicity, multiple questions used to be applied in census questionnaires.…”

Section: Introductionmentioning

confidence: 99%

Prevalence of Chronic Diseases and Activity-Limiting Disability among Roma and Non-Roma People: A Cross-Sectional, Census-Based Investigation

Vincze

Földvári

Pálinkás

et al. 2019

IJERPH

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The lack of recommended design for Roma health-monitoring hinders the interventions to improve the health status of this ethnic minority. We aim to describe the riskiness of Roma ethnicity using census-derived data and to demonstrate the value of census for monitoring the Roma to non-Roma gap. This study investigated the self-declared occurrence of at least one chronic disease and the existence of activity limitations among subjects with chronic disease by the database of the 2011 Hungarian Census. Risks were assessed by odds ratios (OR) and 95% confidence intervals (95% CI) from logistic regression analyses controlled for sociodemographic factors. Roma ethnicity is a risk factor for chronic diseases (OR = 1.17; 95% CI: 1.16–1.18) and for activity limitation in everyday life activities (OR = 1.20; 95% CI: 1.17–1.23), learning-working (OR = 1.24; 95% CI: 1.21–1.27), family life (OR = 1.22; 95% CI: 1.16–1.28), and transport (OR = 1.03; 95% CI: 1.01–1.06). The population-level impact of Roma ethnicity was 0.39% (95% CI: 0.37–0.41) for chronic diseases and varied between 0 and 1.19% for activity limitations. Our investigations demonstrated that (1) the Roma ethnicity is a distinct risk factor with significant population level impact for chronic disease occurrence accompanied with prognosis worsening influence, and that (2) the census can improve the Roma health-monitoring system, primarily by assessing the population level impact.

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“…These inequalities are a result of differences in health outcomes achieved among various groups of the population, leading to an economic burden in the form of considerable social and economic costs (WHO, 2017). At the same time, socio-economic aspects such as employment status, level of education, income level, place of residence, behavioural and living conditions are key factors in creating these differences (Adler et al Differences in health occur in various groups, and can be also seen from different perspectives, for example in terms of colour (Patterson & Veenstra, 2016) or ethnicity (Allik et al, 2019). From a territorial point of view, it can be stated that the population in Northern and Southern Europe shows better health outcomes than the population in Eastern Europe (Pinillos-Franco & Somarriba-Arechavala, 2019).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

How Do Gender Inequalities in Health Relate to the Competitiveness of Developed Countries? An Empirical Study

Gavurová¹,

Ivanková²,

Rigelský³

et al. 2020

JOC

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Public health plays an important role in the spectrum of economic indicators. Simultaneously, the competitiveness of countries is a key economic indicator, and this interconnection requires special attention, especially in the decision-making process of public policies. The main objective of the presented study was to evaluate the effects of selected health indicators on the competitiveness of developed countries. The following health variables were collected for the analysed period from 2010 to 2018: four variables of Life Expectancy (LE) and three variables of Perceived Health Status (PHS). Each variable was observed from the perspective of gender differentiation and gender inequalities. The Global Competitiveness Index (GCI) was also used in the analyses as an economic variable. The research sample included all countries of the Organisation for Economic Co-operation and Development (OECD). The analytical data processing consisted of descriptive analysis, difference analysis (Wilcoxon Test), regression analysis (Panel regression model) and correlation analysis (Spearman's ρ). Regarding the results, all health variables showed differences between men and women. The results of the regression analysis revealed a very strong and significant effect of LE and PHS on the competitiveness of individual economies. The correlation analysis confirmed all relations. Improving the health of men and women is likely to increase the competitiveness of developed countries. As a result, it provides space for further research and policy-making in each country.

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Differences in ill health and in socioeconomic inequalities in health by ethnic groups: a cross-sectional study using 2011 Scottish census

Cited by 10 publications

References 51 publications

Ethnicity and acute hospital admissions: Multi-center analysis of routine hospital data

Ethnicity and acute hospital admissions: Multi-center analysis of routine hospital data

Prevalence of Chronic Diseases and Activity-Limiting Disability among Roma and Non-Roma People: A Cross-Sectional, Census-Based Investigation

How Do Gender Inequalities in Health Relate to the Competitiveness of Developed Countries? An Empirical Study

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