Geographical Inequalities In Health Research Articles

Socioenvironmental sugar promotion and geographical inequalities in dental health of 5-year-old children in England.

To investigate the relationship between socioenvironmental sugar promotion and geographical inequalities in the prevalence of dental caries amongst 5-year-olds living across small areas within England. Ecological data from the National Dental Epidemiology Programme (NDEP) 2018-2019, comprising information on the percentage of 5-year-olds with tooth decay (≥1 teeth that are decayed into dentine, missing due to decay, or filled), and untreated tooth decay (≥1 decayed but untreated teeth), in lower-tier local authorities (LAs) of England. These were analysed for association with a newly developed Index of Sugar-Promoting Environments Affecting Child Dental Health (ISPE-ACDH). The index quantifies sugar-promoting determinants within a child's environment and provides standardized scores for the index, and its component domains that is, neighbourhood-, school- and family-environment, with the highest scores representing the highest levels of sugar promotion in lower-tier LAs (N = 317) of England. Linear regressions, including unadjusted models separately using index and each domain, and models adjusted for domains were built for each dental outcome. Participants lived across 272 of 317 lower-tier LAs measured within the index. The average percentage of children with tooth decay and untreated tooth decay was 22.5 (SD: 8.5) and 19.6 (SD: 8.3), respectively. The mean index score was (0.1 [SD: 1.01]). Mean domain scores were: neighbourhood (0.02 [SD: 1.03]), school (0.1 [SD: 1.0]), and family (0.1 [SD: 0.9]). Unadjusted linear regressions indicated that the LA-level percentage of children with tooth decay increased by 5.04, 3.71, 4.78 and 5.24 with increased scores of the index, and neighbourhood, school and family domains, respectively. An additional model, adjusted for domains, showed that this increased percentage predicted by neighbourhood domain attenuated to 1.37, and by family domain it increased to 6.33. Furthermore, unadjusted models indicated that the LA-level percentage of children with untreated tooth decay increased by 4.72, 3.42, 4.45 and 4.97 with increased scores of the index, and neighbourhood, school, and family domains, respectively. The model, adjusted for domains, showed that this increased percentage predicted by neighbourhood domain attenuated to 1.24 and by family domain rose to 6.47. School-domain was not significantly associated with either outcome in adjusted models. This study reveals that socioenvironmental sugar promotion, particularly within neighbourhood- and family-environments, may contribute to geographical inequalities in dental caries in children. Further research involving data on individual-level dental outcomes and confounders is required.

A health inequality analysis of childhood asthma prevalence in urban Australia.

Long-standing health inequalities in Australian society that were exposed by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic were described as "fault lines" in a recent call to action by a consortium of philanthropic organizations. With asthma a major contributor to childhood disease burden, studies of its spatial epidemiology can provide valuable insights into the emergence of health inequalities early in life. The aims of this study were to characterize the spatial variation of asthma prevalence among children living within Australia's 4 largest cities and quantify the relative contributions of climatic and environmental factors, outdoor air pollution, and socioeconomic status in determining this variation. A Bayesian model with spatial smoothing was developed to regress ecologic health status data from the 2021 Australian Census against groups of explanatory covariates intended to represent mechanistic pathways. The prevalence of asthma in children aged 5 to 14 years averages 7.9%, 8.2%, 8.5%, and 7.6% in Sydney, Melbourne, Brisbane, and Perth, respectively. This small inter-city variation contrasts against marked intracity variation at the small-area level, which ranges from 6% to 12% between the least and most affected locations in each. Statistical variance decomposition on a subsample of Australian-born, nonindigenous children attributes 66% of the intracity spatial variation to the assembled covariates. Of these covariates, climatic and environmental factors contribute 30%, outdoor air pollution contributes 19%, and areal socioeconomic status contributes the remaining 51%. Geographic health inequalities in the prevalence of childhood asthma within Australia's largest cities reflect a complex interplay of factors, among which socioeconomic status is a principal determinant.

Geographical and gender inequalities in health sciences studies: testing differences in research productivity, impact and visibility

PurposeGender and geographical imbalance in production and impact levels is a pressing issue in global knowledge production. Within Health Sciences, while some studies found stark gender and geographical biases and inequalities, others found little empirical evidence of this marginalization. The purpose of the study is to clear the ambiguity concerning the topic.Design/methodology/approachBased on a comprehensive and systematic analysis of Health Sciences research data downloaded from the Scival (Scopus/Scimago) database from 2017 to 2020 (n = 7,990), this study first compares gender representation in research productivity, as well as differences in terms of citation per document, citations per document view and view per document scores according to geographical location. Additionally, the study clarifies whether there is a geographic bias in productivity and impact measures (i.e. citation per document, citations per document view and view per document) moderated by gender.FindingsResults indicate that gender inequalities in productivity are systematic at the overall disciplinary, as well as the subfield levels. Findings also suggest statistically significant geographical differences in citation per document, citations per document view, and view per document scores, and interaction effect of gender over the relation between geography and (1) the number of citations per view and (2) the number of views per document.Originality/valueThis study contributes to scientometric studies in health sciences by providing insightful findings about the geographical and gender bias in productivity and impact across world regions.

Inequalities in local government spending on cultural, environmental and planning services: a time-trend analysis in England, Scotland, and Wales

BackgroundLocal government provides Cultural, Environmental, and Planning (CEP) services, such as parks, libraries, and waste collection, that are vital for promoting health and wellbeing. There have been significant changes to the funding of these services over the past decade, most notably due to the UK government’s austerity programme. These changes have not affected all places equally. To understand potential impacts on health inequalities, we investigated geographical patterning of recent CEP spending trends.MethodsWe conducted a time trend analysis using routinely available data on local government expenditure. We used generalised estimating equations to determine how expenditure trends varied across 378 local authorities (LAs) in Great Britain between 2009/10 and 2018/19 on the basis of country, deprivation, rurality, and local government structure. We investigated the gross expenditure per capita on CEP services, and the CEP expenditure as a proportion of total local authority budgets. We present the estimated annual percentage change in these spend measures.ResultsExpenditure per capita for CEP services reduced by 36% between 2009/10 and 2018/19. In England, the reduction in per capita spending was steepest in the most deprived quintile of areas, falling by 7.5% [95% CI: 6.0, 8.9] per year, compared to 4.5% [95% CI: 3.3, 5.6] per year in the least deprived quintile. Budget cuts in Scotland and Wales have been more equitable, with similar trends in the most and least deprived areas. Welsh LAs have reduced the proportion of total LA budget spent on CEP services the most (-4.0% per year, 95% CI: -5.0 to -2.9), followed by Scotland (-3.0% per year, 95% CI: -4.2 to -1.7) then England (-1.4% per year, 95% CI: -2.2 to -0.6). In England, rural and unitary LAs reduced their share of spending allocated to CEP more than urban and two-tier structured LAs, respectively.ConclusionFunding for cultural, environmental and planning services provided by local government in the UK has been cut dramatically over the last decade, with clear geographical inequalities. Local areas worst affected have been those with a higher baseline level of deprivation, those with a single-tier local government structure, and English rural local authorities. The inequalities in cuts to these services risk widening geographical inequalities in health and wellbeing.

HPR58 Identifying Geographically Clustered Health Inequalities in England

Inequalities in health and their determinants are widening, and it is unclear whether these indicators are correlated and how policy should best address these inequalities. We therefore aimed to 1) identify and characterise geographical clusters in health and socio-economic inequalities in England; and, 2) assess the effect of reducing geographical inequalities in health.

Placing intersectional inequalities in health.

Research into geographical inequalities in health has focused almost exclusively on examining the effects of area-level deprivation and has been largely framed through a compositional-contextual lens, their inter-relationship and the influence of vertical macro-economic and political/policy drivers. However, in the broader health inequalities field, intersectionality has recently emerged as a critical theoretical and methodical approach which examines the concurrent and interacting influences on health of multiple axes of inequality (such as socio-economic status, gender, race/ethnicity and sexuality or gender-identity). Simultaneously, social geography has been explicitly using intersectionality to analyse how mutually constitutive forms of social oppression interact and interrelate with place. This paper exploits the analytical space opened up by this 'intersectional turn' by outlining the benefits for research into geographical inequalities in health that can be achieved by taking a more explicit approach to intersectional inequalities. It argues that: (1) geographical research into health inequalities should more explicitly and widely apply an intersectional lens; and relatedly that, in turn, (2) place needs to be considered as an aspect of intersectionality and integrated into the wider intersectional inequalities in health literature. The paper summarises the evolution of theories of place and health inequalities and outlines intersectional theory and the work to date that has been undertaken to integrate this perspective into our understanding of health inequalities. Drawing on the social geography literature into place and intersectionality, the paper explores how this perspective is being used to enhance our understanding of place effects more generally - and how place itself can be considered as an element of intersectional inequalities. Drawing these different bodies of work together, the paper concludes by considering the implications for theories of geographical inequalities in health.

Potential determinants of unfavourable healthcare utilisation trajectories during the last year of life of people with incident Alzheimer Disease or Related Syndromes: a nationwide cohort study using administrative data

people approaching the end-of-life frequently face inappropriate care. With Alzheimer Disease or Related Syndromes (ADRS), end-of-life is characterised by progressive decline, but this period remains difficult to identify. This leads to a lack of anticipation and sometimes with unfavourable healthcare utilisation trajectories (HUTs). to quantify unfavourable HUTs during the last year of life and identify their potential determinants in both community and nursing-home settings. nationwide cohort study using administrative database. French community and nursing-home residents. incident ADRS people identified in 2012, who died up to 31 December 2017. we used multidimensional clustering to identify 15 clusters of HUTs, using 11 longitudinal healthcare dimensions during the last year of life. Clusters were qualitatively assessed by pluri-disciplinary experts as favourable or unfavourable HUTs. Individual and contextual potential determinants of unfavourable HUTs were studied by setting using logistic random-effect regression models. 62,243 individuals died before 31 December 2017; 46.8% faced unfavourable end-of-life HUTs: 55.2% in the community and 31.8% in nursing-homes. Individual potential determinants were identified: younger age, male gender, ADRS identification through hospitalisation, shorter survival, life-limiting comorbidities, psychiatric disorders, acute hospitalisations and polypharmacy. In the community, deprivation and autonomy were identified as potential determinants. Contextual potential determinants raised mostly in the community, such as low nurse or physiotherapist accessibilities. Nearly half of people with ADRS faced unfavourable HUTs during their last year of life. Individual potential determinants should help anticipate advance care planning and palliative care needs assessment. Contextual potential determinants suggest geographical disparities and health inequalities.

Excess years of life lost to COVID-19 and other causes of death by sex, neighbourhood deprivation, and region in England and Wales during 2020: A registry-based study.

Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups. We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording. In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.

Socioeconomic level and associations between heat exposure and all-cause and cause-specific hospitalization in 1,814 Brazilian cities: A nationwide case-crossover study

BACKGROUND AND AIM: Little is known about socioeconomic disparities in vulnerability to heat. We aimed to evaluate whether there were socioeconomic disparities in vulnerability to heat-related all-cause and cause-specific hospitalization among Brazilian cities. METHODS: We collected daily hospitalization and weather data in the hot season (city-specific 4 adjacent hottest months each year) during 2000–2015 from 1,814 Brazilian cities covering 78.4% of the Brazilian population. A time-stratified case-crossover design modeled by quasi-Poisson regression and a distributed lag model was used to estimate city-specific heat–hospitalization association. Then meta-analysis was used to synthesize city-specific effect estimates according to different socioeconomic quartiles or levels. RESULTS:We included 49 million hospitalizations (58.5% female; median [interquartile range] age: 33.3 [19.8–55.7] years). For cities of lower middle income (LMI), upper middle income (UMI), and high income (HI) according to the World Bank’s classification, every 5°C increase in daily mean temperature during the hot season was associated with a 5.1% (95% CI 4.4%–5.7%,), 3.7% (3.3%–4.0%), and 2.6% (1.7%–3.4%) increase in all-cause hospitalization, respectively. The inter-city socioeconomic disparities in the association were strongest for children and adolescents (0–19 years) (effect estimates: 9.9% in LMI cities vs 5.2% in HI cities). The disparities were particularly evident for hospitalization due to certain diseases, including ischemic heart disease (effect estimates: 5.6% in LMI cities vs 0.5% in HI cities), asthma (3.7% vs −6.4%), pneumonia (8.0% vs 3.8%), renal diseases (9.6% vs 4.9%), mental health conditions (17.2% vs 5.5%), and neoplasms (3.1% vs −0.1%). The disparities were similar when stratifying the cities by other socioeconomic indicators (urbanization rate, literacy rate, and household income). CONCLUSIONS:Less developed cities displayed stronger associations between heat exposure and all-cause hospitalizations and certain types of cause-specific hospitalizations in Brazil. This may exacerbate the existing geographical health and socioeconomic inequalities under a changing climate. KEYWORDS: Temperature, Socio-economic factors (non-chemical stressors), Environmental disparities, Environmental justice, Big data

A spatiotemporal analysis of inequalities in life expectancy and 20 causes of mortality in sub-neighbourhoods of Metro Vancouver, Canada, 1990-2016

BACKGROUND AND AIM: There is limited evidence on the magnitude and contributing causes of intra-urban inequalities. Spatially varying baseline data are needed to better understand geographical health inequalities as a first step in identifying and acting upon determinants. METHODS: Mortality data (1990-2016) in British Columbia (BC), Canada were linked to three national and provincial demographic data sources and assigned to 20 Global Burden of Disease Study cause categories with further cause differentiation for neoplasms and cardiovascular diseases. All data were restricted, aggregated and merged to 368 Census Tracts (CTs) in Metro Vancouver. Bayesian small area, mixed-effects estimation models were used to estimate life expectancy (LE) at birth and 20 cause-specific and age-standardized mortality rates by sex and year. RESULTS:Over the 27-year period, the gap in LE for CTs in the 90th percentile (P90) and 10th percentile (P10) for both males and females ranged from 6.9 years to 9.5 years. The two largest increases in percentage of total deaths from 1990-2016 were neurological diseases (10.0%) and other non-communicable diseases (3.7%). Relative inequality increased for almost all causes, especially for HIV and sexually transmitted infections, maternal and neonatal disorders, and neoplasms (especially pancreatic cancer in females and prostate cancer in males), whereby CTs in the P90 were 17.4 (P90: 1.2/100,000; P10: 0.2/100,000), 10.0 (16.4; 1.3), and 3.8 (367.7; 95.9) times higher, respectively, compared to CTs in the P10. CONCLUSIONS:Spatial heterogeneity and clusters of cause-specific deaths were observed in one of the healthiest cities in Canada, with widening inequality in more recent years. These results and application of similar methodology to other locations can be used to support more in-depth analysis and prioritisation of policies and programs to advance urban sustainability and health equity. KEYWORDS: Health equity, small area analysis, life expectancy, cause-specific mortality, urban health, spatial analysis

Geographic health inequalities in Madrid City: exploring spatial patterns of respiratory disease mortality

The unequal geographic distribution of health determinants could denote situations of environmental injustice. This work aims to identify spatial patterns of respiratory disease mortality and their association with the education level and the atmospheric pollution in Madrid. To this purpose, we applied spatial analysis through statistical techniques and Geographic Information Systems at the census tract level. The analysis showed a slight but significantly higher risk of mortality in areas with more unfavourable socioeconomic and environmental conditions. This work has the potential to inform public policy and research on links among social, environmental and health inequalities in Madrid City.

Improving treatment outcomes for leprosy in Pernambuco, Brazil: a qualitative study exploring the experiences and perceptions of retreatment patients and their carers

BackgroundBrazil has a high leprosy burden and poor treatment outcomes (TOs), manifesting in high relapse rates. Pernambuco, an impoverished Brazilian state suffering notable geographical health inequalities, has ‘hyperendemic’ leprosy. Although current literature identifies barriers and facilitators influencing leprosy treatment compliance, inadequate investigation exists on other factors influencing TOs, including carers’ roles and psycho-dermatological impact. This qualitative study explores experiences and perceptions of leprosy patients and their carers in Pernambuco, Brazil; to identify location-specific factors influencing TOs, and consequently inform future management.Methods27, semi-structured, in-depth interviews were conducted with 14 patients and 13 carers. Participants were recruited using maximum variation and snowball sampling from three clinics in Petrolina, Pernambuco. Transcripts and field notes from both participant groups were separately analysed using conventional thematic and deviant case analysis. The University of Birmingham Internal Research Ethics Committee and Instituto Lauro de Souza Lima provided ethical approval.ResultsTwo homologous sets of four, primary, interdependent themes influencing leprosy TOs emerged: ‘personal factors’; ‘external factors’; ‘clinical factors’; and ‘the healthcare professional (HCP)-patient-carer relationship’. Poor participant knowledge and lack of symptomatic relief caused patients to distrust treatment. However, because participants thought HCP-led interventions were vital for optimal TOs, patients were effectively persuaded to adhere to pharmaceutical treatments. High standard patient and population education facilitated treatment engagement by encouraging evidence-based medicine belief, and dispelling health myths and stigma. Healthcare, on occasions, was perceived as disorganised, particularly in resource-scarce rural areas, and for those with mental health needs. Participants additionally experienced incorrect/delayed diagnoses and poor contact tracing. Leprosy’s negative socio-economic impact on employment – together with stigma, dependency and changing relationships – caused altered senses of identity, negatively impacting TOs. Better dialogue between patients, HCPs and carers facilitated individualised patient support.ConclusionThis study highlights the importance of: effective evidence-based leprosy education; communication between HCPs, patients and carers; state-funded support; and healthcare resource distribution. These findings, if prioritised on governmental scales, provide the valuable insight needed to inform location-specific management strategies, and consequently improve TOs. Future research should evaluate the effectiveness of these implementations. Failure to address these findings will hinder regional elimination efforts.

'It is surprising how much nonsense you hear': How residents experience and react to living in a stigmatised place. A narrative synthesis of the qualitative evidence.

There are significant geographical inequalities in health. Spatial stigma - negative representations of particular localities - could be an important mechanism through which place influences population health. To explore this, we undertook a narrative synthesis of studies reporting residents' perspectives of living in stigmatised localities. Qualitative research (38 studies) was reviewed to identify how spatial stigma manifested in residents' lives, their strategies to cope with stigma and the health consequences. The review found residents internalised stigma, but also resisted it differently. Although relatively few studies purposefully investigated health, living somewhere stigmatised had psychological effects and constrained life opportunities that have implications for health.

Harmonizing child mortality data at disparate geographic levels.

There is an increasing focus on reducing inequalities in health outcomes in developing countries. Subnational variation is of particular interest, with geographically-indexed data being used to understand the spatial risk of detrimental outcomes and to identify who is at greatest risk. While some health surveys provide observations with associated geographic coordinates (point data), many others provide data that have their locations masked and instead only report the strata (polygon information) within which the data resides (masked data). How to harmonize these data sources for spatial analysis has been previously considered although only ad hoc methods and comparison of methods is lacking. In this paper, we present a new method for analyzing masked survey data, using a method that is consistent with the data-generating process. In addition, we critique two previously proposed approaches to analyzing masked data and illustrate that they are fundamentally flawed methodologically. To validate our method, we compare our approach with previously formulated solutions in several realistic simulation environments in which the underlying structure of the risk field is known. We simulate samples from spatiotemporal fields in a way that mimics the sampling frame implemented in the most common health surveys in low- and middle-income countries, the Demographic and Health Surveys and Multiple Indicator Cluster Surveys. In simulations, the newly proposed approach outperforms previously proposed approaches in terms of minimizing error while increasing the precision of estimates. The approaches are subsequently compared using child mortality data from the Dominican Republic where our findings are reinforced. The ability to accurately increase precision of child mortality estimates, and health outcomes in general, by leveraging various types of data, improves our ability to implement precision public health initiatives and better understand the landscape of geographic health inequalities.

Socioeconomic status influences delays in the management of acute ST-elevation myocardial infarction

Abstract Background A prompt diagnosis to initiate the appropriate reperfusion therapy is crucial to improve clinical outcomes in acute ST-elevation myocardial infarction (STEMI) patients. Socio-economic status (SES) refers to parameters like income, educational status and occupation. A low SES negatively interferes with the prognosis of STEMI patients. However, the impact of SES on delay time in acute STEMI remains matter of debate. Methods We used databases from two French multicentric and prospective registries: ACIRA (patients undergoing coronary angiography in any catheterization laboratories of Aquitaine) and REANIM (acute STEMI patients supported by emergency medical system (EMS) in Aquitaine). An ecological indicator of social deprivation Fdep09 was calculated to describe geographical inequalities in health based on municipality of residence. The higher the value, the more disadvantaged the population. Low SES was defined as Fdep09 > median value. Results Two-thousand-eight-hundred-and-forty consecutive patients with acute STEMI undergoing coronary angiography from January 2017 to December 2018 in Aquitaine were included. Patients with lower SES were more often initially referred to emergency departments of non-percutaneous coronary intervention capable centers whereas patients with higher SES were more often directly transferred to PCI centers by the mobile emergency care units as recommended by the most recent European guidelines (p<10–4). Patients with low SES had longer delays from symptom onset to first medical contact (FMC) (116 [60–119] vs 98 [55–233] min, p=0.0078) and were more likely to receive fibrinolysis (9.9 vs 5.2%, p<10–4). Linear regression modeling showed that each point of the Fdep09 index was associated with increase in the delay from symptom onset to FMC by a factor 1.1 (95% CI: 1.04–1.17, p<10–3) after adjusting for potential confounders. Conclusion SES inequality has negative influence on the delays in the management of acute STEMI patients. Efforts to raise awareness of suspicious signs of acute MI among individuals in lower SES could be valuable. FDep09 distribution Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): ARS Nouvelle-Aquitaine

Socioeconomic level and associations between heat exposure and all-cause and cause-specific hospitalization in 1,814 Brazilian cities: Anationwide case-crossover study.

Heat exposure, which will increase with global warming, has been linked to increased risk of a range of types of cause-specific hospitalizations. However, little is known about socioeconomic disparities in vulnerability to heat. We aimed to evaluate whether there were socioeconomic disparities in vulnerability to heat-related all-cause and cause-specific hospitalization among Brazilian cities. We collected daily hospitalization and weather data in the hot season (city-specific 4 adjacent hottest months each year) during 2000-2015 from 1,814 Brazilian cities covering 78.4% of the Brazilian population. A time-stratified case-crossover design modeled by quasi-Poisson regression and a distributed lag model was used to estimate city-specific heat-hospitalization association. Then meta-analysis was used to synthesize city-specific estimates according to different socioeconomic quartiles or levels. We included 49 million hospitalizations (58.5% female; median [interquartile range] age: 33.3 [19.8-55.7] years). For cities of lower middle income (LMI), upper middle income (UMI), and high income (HI) according to the World Bank's classification, every 5°C increase in daily mean temperature during the hot season was associated with a 5.1% (95% CI 4.4%-5.7%, P < 0.001), 3.7% (3.3%-4.0%, P < 0.001), and 2.6% (1.7%-3.4%, P < 0.001) increase in all-cause hospitalization, respectively. The inter-city socioeconomic disparities in the association were strongest for children and adolescents (0-19 years) (increased all-cause hospitalization risk with every 5°C increase [95% CI]: 9.9% [8.7%-11.1%], P < 0.001, in LMI cities versus 5.2% [4.1%-6.3%], P < 0.001, in HI cities). The disparities were particularly evident for hospitalization due to certain diseases, including ischemic heart disease (increase in cause-specific hospitalization risk with every 5°C increase [95% CI]: 5.6% [-0.2% to 11.8%], P = 0.060, in LMI cities versus 0.5% [-2.1% to 3.1%], P = 0.717, in HI cities), asthma (3.7% [0.3%-7.1%], P = 0.031, versus -6.4% [-12.1% to -0.3%], P = 0.041), pneumonia (8.0% [5.6%-10.4%], P < 0.001, versus 3.8% [1.1%-6.5%], P = 0.005), renal diseases (9.6% [6.2%-13.1%], P < 0.001, versus 4.9% [1.8%-8.0%], P = 0.002), mental health conditions (17.2% [8.4%-26.8%], P < 0.001, versus 5.5% [-1.4% to 13.0%], P = 0.121), and neoplasms (3.1% [0.7%-5.5%], P = 0.011, versus -0.1% [-2.1% to 2.0%], P = 0.939). The disparities were similar when stratifying the cities by other socioeconomic indicators (urbanization rate, literacy rate, and household income). The main limitations were lack of data on personal exposure to temperature, and that our city-level analysis did not assess intra-city or individual-level socioeconomic disparities and could not exclude confounding effects of some unmeasured variables. Less developed cities displayed stronger associations between heat exposure and all-cause hospitalizations and certain types of cause-specific hospitalizations in Brazil. This may exacerbate the existing geographical health and socioeconomic inequalities under a changing climate.

Contextualising lifestyles: how socially contrasting places in Fife, Scotland influence lay understandings of lifestyle and health behaviours in relation to coronary heart disease

Coronary heart disease (CHD) is a significant public health issue showing persistent geographical health inequalities. However, little attention has focussed on lay perspectives of how contrasting social contexts influence lifestyles and health behaviour in relation to CHD. The aim of this qualitative study is to explore lay perspectives of lifestyle and behaviour in socioeconomically contrasting places, with women and men who had survived a heart attack in Fife, Scotland. This study contributes to knowledge on CHD health inequalities and health promotion, particularly cardiac rehabilitation, emphasising the importance of situating experiences and understandings of health, geographically.

Abstract P468: Geographic and Socioeconomic Inequalities in Poor Cardiovascular Health in Canada

Background: Poor cardiovascular health (CVH), characterized by clinical risk and unhealthy lifestyle habits, is a leading cause of death and disease worldwide. Despite advances in healthcare and policy, there remains an inequitable burden of poor CVH among Canadian sub-populations based on socioeconomic status and geographic region. Using recently published data and a national toolkit, this study aimed to quantify inequalities in poor CVH across the Canadian population. Methods: We conducted a cross-sectional study on Canadian adults, ≥20 years, from the nationally representative Canadian Community Health Survey 2017. Using the American Heart Association’s CVH Index, CVH was defined for each individual as a summed score of 7 components, where 1 point was awarded for achieving ideal health in each component. A total score of 0-2 points indicated poor overall CVH. The Canadian Institute for Health Information (CIHI) Measuring Health Inequalities Toolkit, a standardized methodological approach to analyzing health inequalities in population-based data using pre-defined stratifications and second-level interactions, was used to quantify inequalities in poor CVH based on Toolkit-defined stratifications in sex, income, urban/rural status, and region of residence. The regional distribution of CVH was mapped using ArcGIS software. Results: Approximately 7% of Canadians had poor CVH, representing 2 million Canadians. Poor dietary habits were noted in 99.0% of the population, with poor body mass index and poor physical activity noted in 58.1% and 42.3%, respectively. The eastern provinces of Newfoundland and Labrador and New Brunswick had the greatest proportion of health regions with poor CVH. An examination of the largest CVH inequalities across provinces revealed that females in the lowest income tercile residing in Prince Edward Island were 8-times more likely to experience poor CVH than females in the highest income tercile (RR 8.43, 95%CI 7.09-10.04). Additionally, females in New Brunswick residing in rural regions were almost 3-times more likely to experience poor CVH than females residing in urban regions (RR 3.07, 95%CI 1.07-4.87). In most provinces, income and urban/rural inequalities among males were observed but were of smaller magnitude than the inequalities among females. Conclusion: The greatest inequalities in poor CVH were experienced by females in the lowest income groups. Urban/rural inequalities in CVH were complex and varied by geographic region. The CIHI toolkit is a robust and systematic approach to understanding health inequalities that will enable comparison between studies and health/disease states, and thus facilitate comparative policy evaluation and population health priority setting.

Who still dies young in a rich city? Revisiting the case of Oxford

There are substantial inequalities in mortality and life expectancy in England, strongly linked to levels of deprivation. Mortality rates among those who are homeless are particularly high. Using the city of Oxford (UK) as a case study, we investigate ward‐level premature standardised mortality ratios for several three‐year and five‐year periods between 2002 and 2016, and explore the extent to which the mortality of people who become homeless contributed to any rise or fall in geographical inequalities during this period. Age–sex standardised mortality ratios (SMRs) for people aged under 65 years old, with and without deaths among the homeless population, were calculated using Office for National Statistics Death Registration data for England and Wales 2002−2016. Individuals who were homeless or vulnerably housed were identified using records supplied by a local Oxford homeless charity. We found that in an increasingly wealthy, and healthy, city there were persistent ward‐level inequalities in mortality, which the city‐wide decrease in premature mortality over the period masked. Premature deaths among homeless people in Oxford became an increasingly important contributor to the overall geographical inequalities in health in this city. In the ward with the highest SMR, deaths among the homeless population accounted for 73% of all premature deaths of residents over the whole period; in 2014–2016 this proportion rose to 88%. Homelessness among men (the vast majority of the known homeless population) in this gentrifying English city rose to become the key explanation of geographical mortality patterns in deaths before age 65 across the entire city, particularly after 2011. Oxford reflects a broader pattern now found in many places across England of increasing homeless deaths, widening geographical inequalities in life expectancy, and sharp increases in all‐age SMRs. The answer to the question, “Who dies young in a rich, and in fact an even richer, place?” is – increasingly – the homeless.

Developing a deprivation index to study geographical health inequalities in Ecuador.

ABSTRACTOBJECTIVES:To develop a deprivation index to study health inequalities in 221 areas of Ecuador, to describe the pattern of deprivation in Ecuador, and to explore the applications of the index to study health inequalities by analysing the association between deprivation and mortality in the study areas.METHODS:We performed principal component analyses of available indicators of the 221 cantons of Ecuador. A set of 41 sociodemographic, social capital, and subjective well-being variables were obtained from the 2010 National Population Census and the National Living Conditions Survey 2013–2014. To explore the application of the index in public health, the association between the index and standardised mortality ratios was estimated through a Poisson regression model.RESULTS:The final index was constructed with 17 indicators. The first component explained 51.8% of the total variance of the data. A geographic pattern and a positive association of the index with the standardised mortality ratios of the cantons were observed in both men and women.CONCLUSIONS:We constructed a deprivation index that can identify disadvantaged areas in Ecuador. This index could be a valuable tool for the detection of vulnerabilised populations and the development of interventions and policies adapted to local needs.