Area-level Inequalities Research Articles

Understanding the important characteristics of neighbourhoods to facilitate ageing in place and longevity.

This study investigates which local area characteristics, included in the Healthy Ageing/Vulnerable ENvironment (HAVEN) Index, are the strongest factors predicting transition into permanent residential aged care (PRAC) and mortality, and the geographic distribution of these factors. A retrospective cohort study of older individuals living in the community in Adelaide who received their first eligibility assessment for age care services between 2013 and 2015 (n = 16,939) was conducted. The study cohort, from the Registry of Senior Australians (ROSA), was linked by postcode to HAVEN Index items, selected following item response theory (IRT) analysis to determine the strongest local area factors associated with PRAC and mortality. Geospatial mapping of the factors determined the geographic distribution of these significant factors. Fourteen HAVEN Index items were associated with entry into PRAC and mortality. Three area-level items, lower educational attainment, financial housing stress and low levels of volunteering by older people, were risk factors for entry into PRAC and mortality while the remainder of the items identified were different for each outcome. The mapped local area risk factors for each outcome highlighted similar geographical areas of vulnerability. Local area characteristics are associated with entering PRAC and mortality. Our findings can inform area-level responses to make neighbourhoods more age-friendly, potentially allowing more people to age longer in place. Similar analyses, conducted for other areas, could provide evidence to support the widespread development of age-friendly neighbourhoods reducing area-level inequalities in ageing.

Estimating quality-adjusted life expectancy (QALE) for local authorities in Great Britain and its association with indicators of the inclusive economy: a cross-sectional study

ObjectivesQuantifying area-level inequalities in population health can help to inform policy responses. We describe an approach for estimating quality-adjusted life expectancy (QALE), a comprehensive health expectancy measure, for local authorities...

Secular trends of life expectancy and disability-free life expectancy at age 65 and associated gender and area-level socioeconomic inequalities in Hong Kong: a serial cross-sectional study between 2007 and 2020

Despite Hong Kong's world leading longevity, little is known about its associated disability burden and social patterning. Hence, this study assessed the gender-specific secular trends and area-level inequalities in life expectancy (LE) and disability-free life expectancy (DFLE) at age 65 in Hong Kong. Population structure, death records, and disability data in 2007, 2013, and 2020 were retrieved from the Census and Statistics Department to estimate LE and DFLE using the Sullivan Method. District-based sociodemographic indicators were used to compare LE and DFLE across 18 districts of Hong Kong in2013. Between 2007 and 2020, LE at age 65 increased by 3.7 years (from 18.3 to 22.0) in men and by 2.1 years (from 22.7 to 24.8) in women. By contrast, DFLE increased more slowly, by 1.8 years (from 14.6 to 16.3) in men and by only 0.1 year (from 16.4 to 16.5) in women, leading to a substantial increase in proportion of life spent with disability. Results from multiple linear regression using district-based data in 2013 showed a similar extent of associations of education with LE and DFLE (mean year difference: 0.81 [95% CI: 0.14, 1.48] and 0.68 [0.10, 1.27], respectively, per 10% increase in average education level), while female gender was more strongly associated with LE (4.44 [3.56, 5.31]) than with DFLE (2.00 [1.18, 2.82]). Expansion of disability burden and male-female health-survival paradox hold true in Hong Kong. Unlike Western countries with a stronger socioeconomic patterning of DFLE, the extent of area-level socioeconomic inequalities in LE and DFLE appears to be more comparable in Hong Kong. Health and Medical Research Fund (Ref.no.: 19202031) by the Health Bureau of Hong Kong.

Area-level inequalities in the provision of NHS orthodontic care in England from 2016 to 2019.

Objective To investigate geographic inequalities in the provision of NHS orthodontic care in England at the area level.Methods NHS dental activity data were analysed for the three financial years April 2016 to March 2019. The measures used were units of dental activity (UDA), units of orthodontic activity (UOA) and commencement of orthodontic treatment. Two orthodontic activity indices were created to assess relative volumes of care. Deprivation was measured using the index of multiple deprivations. Slope and relative inequality indices were used to assess inequality.Results Nearly 12.4 million UOA and 572,987 courses of treatment in England were reported under NHS arrangements in the three years studied. There were significant variations in the rates of UOA (0-716) and UDA (148-918) provided per 100 children (0-17 years) at the local authority level. The variation was not associated with deprivation at the local authority level.Conclusions There were significant disparities in the provision of NHS orthodontic treatment at the local authority level, but this was not associated with area-level measures of deprivation. Inequality in the uptake of orthodontic care may not be due to area-level disparities in service provision.

Area-level inequalities in Covid-19 outcomes in Brazil in 2020 and 2021: An analysis of 1,894,165 severe Covid-19 cases

The study aims to analyze inequalities in Covid-19 outcomes in Brazil in 2020/2021 according to the per capita Gross Domestic Product (pcGDP) of municipalities. All cases of Severe Acute Respiratory Syndrome (SARS) who were hospitalized or died, regardless of hospitalization, registered in Brazil in 2020 and 2021 were analyzed (n = 2,902,742), including those with a confirmed diagnosis of Covid-19 (n = 1,894,165). We calculated lethality due to Covid-19, the performance of diagnostic tests among patients with SARS, and the hospital care received by those with Covid-19 according to the pcGDP of the patients' municipalities of residence. Data were analyzed for each epidemiological week and the risk of each outcome was estimated using Poisson regression. Municipalities in the lowest pcGDP decile had (i) 30% (95%CI 28%–32%) higher lethality from Covid-19, (ii) three times higher proportion of patients with SARS without the collection of biological material for the diagnosis of Covid-19, (iii) 16% (95%CI 15%–16%) higher proportion of SARS patients testing in a period longer than two days from the onset of symptoms, (iv) 140% (95%CI 134%–145%) higher absence of CT scan use. There is deep socioeconomic inequality among Brazilian municipalities regarding the occurrence of Covid-19 negative outcomes.

Socioeconomic Inequalities in COVID-19 Incidence During Different Epidemic Phases in South Korea.

ObjectiveArea-level socioeconomic status (SES) is associated with coronavirus disease 2019 (COVID-19) incidence. However, the underlying mechanism of the association is context-specific, and the choice of measure is still important. We aimed to evaluate the socioeconomic gradient regarding COVID-19 incidence in Korea based on several area-level SES measures.MethodsCOVID-19 incidence and area-level SES measures across 229 Korean municipalities were derived from various administrative regional data collected between 2015 and 2020. The Bayesian negative binomial model with a spatial autocorrelation term was used to estimate the incidence rate ratio (IRR) and relative index of inequality (RII) of each SES factor, with adjustment for covariates. The magnitude of association was compared between two epidemic phases: a low phase (<100 daily cases, from May 6 to August 14, 2020) and a rebound phase (>100 daily cases, from August 15 to December 31, 2020).ResultsArea-level socioeconomic inequalities in COVID-19 incidence between the most disadvantaged region and the least disadvantaged region were observed for nonemployment rates [RII = 1.40, 95% credible interval (Crl) = 1.01–1.95] and basic livelihood security recipients (RII = 2.66, 95% Crl = 1.12–5.97), but were not observed for other measures in the low phase. However, the magnitude of the inequalities of these SES variables diminished in the rebound phase. A higher area-level mobility showed a higher risk of COVID-19 incidence in both the low (IRR = 1.67, 95% Crl = 1.26–2.17) and rebound phases (IRR = 1.28, 95% Crl = 1.14–1.44). When SES and mobility measures were simultaneously adjusted, the association of SES with COVID-19 incidence remained significant but only in the low phase, indicating they were mutually independent in the low phase.ConclusionThe level of basic livelihood benefit recipients and nonemployment rate showed social stratification of COVID-19 incidence in Korea. Explanation of area-level inequalities in COVID-19 incidence may not be derived only from mobility differences in Korea but, instead, from the country's own context.

The Effects of the First National Lockdown in England on Geographical Inequalities in the Evolution of COVID-19 Case Rates: An Ecological Study

Background: Socio-economic inequalities in COVID-19 case rates have been noted worldwide. Previous studies have compared case rates over set phases. There has been no analysis of how inequalities in cases changed overtime and were shaped by national mitigation strategies (e.g. lock downs). This paper provides the first analysis of the evolution of area-level inequalities in COVID-19 cases by deprivation levels in the first wave of the pandemic (January to July 2020) in England – with a focus on the effects of the first national lockdown (March – July 2020).Methods: Weekly case rates per Middle Super Output Area (MSOA, n=4412) in England from 2020-03-15 to 2020-07-04 were obtained, and characteristics of local epidemics were calculated, e.g. the highest case rate per area. Simple linear and logistic regression analyses were employed to assess the association of these metrics with index of multiple deprivation (IMD). Local authority-level (n=309) cases were used similarly in a sensitivity analysis, as these data were available daily and extended further back in time. The impact of lockdown was assessed by comparing the cumulative case rate in the most deprived 20% of MSOAs to the least deprived 20%, for the periods before the lockdown, and by the end of lockdown.Findings: Less deprived areas began recording COVID-19 cases earlier than more deprived areas and were more likely to have peaked by March 2020. More deprived areas’ case rates grew faster and peaked higher than less deprived areas. During the first national lockdown in the UK, the relative excess in case rates in the most deprived areas increased to 130% of that of the least deprived ones.Interpretation: The pattern of disease spread in England confirm the hypothesis that initial cases of a novel infectious disease are likely to occur in more affluent communities, but more deprived areas will overtake them once national mitigation strategies begin, and bear the brunt of the total case load. The strict first national lockdown served to increase case rate inequalities in England.Funding Information: This work was supported by a grant from The Health Foundation (Ref: 2211473).Declaration of Interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. Ethics Approval Statement: This study was approved by the Newcastle University Ethics Committee (Ref: 7543/2020).

Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

Do the classification of areas and distance matter to the assessment results of achieving the treatment targets among type 2 diabetes patients?

BackgroundType 2 diabetes is a major health concern all over the world. The prevention of diabetes is important but so is well-balanced diabetes care. Diabetes care can be influenced by individual and neighborhood socio-economic factors and geographical accessibility to health care services. The aim of the study is to find out whether two different area classifications of urban and rural areas give different area-level results of achieving the targets of control and treatment among type 2 diabetes patients exemplified by a Finnish region. The study exploits geo-referenced patient data from a regional primary health care patient database combined with postal code area-level socio-economic variables, digital road data and two grid based classifications of areas: an urban–rural dichotomy and a classification with seven area types.MethodsThe achievement of control and treatment targets were assessed using the patient’s individual laboratory data among 9606 type 2 diabetes patients. It was assessed whether hemoglobin A1c (HbA1c) was controlled and whether the recommended level of HbA1c was achieved in patients by different area classes and as a function of distance. Chi square test and logistic regression analysis were used for testing.ResultsThe study reveals that area-level inequalities exist in the care of type 2 diabetes in a detailed 7-class area classification but if the simple dichotomy of urban and rural is applied differences vanish. The patient’s gender and age, area-level education and the area class they belonged to were associated with achievements of control and treatment targets. Longer distance to health care services was not a barrier to good achievements of control or treatment targets.ConclusionsA more detailed grid-based area classification is better for showing spatial differences in the care of type 2 diabetes patients. Inequalities exist but it would be misleading to state that the differences are simply due to urban or rural location or due to distance. From a planning point of view findings suggest that detailed geo-coded patient information could be utilized more in resourcing and targeting the health care services to find the area-level needs of care and to improve the cost-efficient allocation of resources.

Is population structure sufficient to generate area-level inequalities in influenza rates? An examination using agent-based models.

BackgroundIn New Haven County, CT (NHC), influenza hospitalization rates have been shown to increase with census tract poverty in multiple influenza seasons. Though multiple factors have been hypothesized to cause these inequalities, including population structure, differential vaccine uptake, and differential access to healthcare, the impact of each in generating observed inequalities remains unknown. We can design interventions targeting factors with the greatest explanatory power if we quantify the proportion of observed inequalities that hypothesized factors are able to generate. Here, we ask if population structure is sufficient to generate the observed area-level inequalities in NHC. To our knowledge, this is the first use of simulation models to examine the causes of differential poverty-related influenza rates.MethodsUsing agent-based models with a census-informed, realistic representation of household size, age-structure, population density in NHC census tracts, and contact rates in workplaces, schools, households, and neighborhoods, we measured poverty-related differential influenza attack rates over the course of an epidemic with a 23 % overall clinical attack rate. We examined the role of asthma prevalence rates as well as individual contact rates and infection susceptibility in generating observed area-level influenza inequalities.ResultsSimulated attack rates (AR) among adults increased with census tract poverty level (F = 30.5; P < 0.001) in an epidemic caused by a virus similar to A (H1N1) pdm09. We detected a steeper, earlier influenza rate increase in high-poverty census tracts—a finding that we corroborate with a temporal analysis of NHC surveillance data during the 2009 H1N1 pandemic. The ratio of the simulated adult AR in the highest- to lowest-poverty tracts was 33 % of the ratio observed in surveillance data. Increasing individual contact rates in the neighborhood did not increase simulated area-level inequalities. When we modified individual susceptibility such that it was inversely proportional to household income, inequalities in AR between high- and low-poverty census tracts were comparable to those observed in reality.DiscussionTo our knowledge, this is the first study to use simulations to probe the causes of observed inequalities in influenza disease patterns. Knowledge of the causes and their relative explanatory power will allow us to design interventions that have the greatest impact on reducing inequalities.ConclusionDifferential exposure due to population structure in our realistic simulation model explains a third of the observed inequality. Differential susceptibility to disease due to prevailing chronic conditions, vaccine uptake, and smoking should be considered in future models in order to quantify the role of additional factors in generating influenza inequalities.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-2284-2) contains supplementary material, which is available to authorized users.

Geographic remoteness, area-level socioeconomic disadvantage and inequalities in colorectal cancer survival in Queensland: a multilevel analysis

BackgroundTo explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival.MethodsMultilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007.ResultsArea-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas.ConclusionsWe have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC.

Smoking initiation, continuation and prevalence in deprived urban areas compared to non-deprived urban areas in The Netherlands

Previous studies have shown that smoking prevalence is higher in deprived areas than in affluent areas. We aimed to determine whether smoking initiation or continuation contributes most to inequalities in current smoking, and in which population subgroups these area differences were largest. Therefore, we assessed the relationship between area deprivation and current smoking, initiation and continuation in urban areas, in subgroups defined by gender, generation and educational level. Cross-sectional data of 20,603 Dutch adults (18 years and over) living in 963 urban areas in The Netherlands were obtained from the annual national health survey (2003–2009). Three interrelated smoking outcomes were used: current smoking (smokers/total population), initiation (ever-smokers/total population) and continuation (smokers/ever-smokers). Area deprivation was dichotomised; deprived urban areas (as defined by the Dutch government) and non-deprived urban areas (reference group) were distinguished. Multilevel logistic regression models controlled for individual characteristics (including education and income) and tested for interaction with gender, generation and education. After controlling for individual characteristics, odds for smoking were not significantly higher in deprived areas (current smoking: OR = 1.04 [0.92–1.18], initiation: OR = 1.05 [0.93–1.18], continuation: OR = 1.03 [0.88–1.19]). For smoking initiation, significant differences between deprived areas and other areas remained in younger generations (OR = 1.19 [1.02–1.38]) and higher educated (OR = 1.23 [1.04–1.45]) respondents. For continuation and current smoking, after controlling for individual characteristics, no associations were found in any subgroups. In conclusion, area deprivation appears to be independently related to smoking initiation in, respectively, higher educated and younger generations. These results suggest that initiatives to reduce area-level inequalities in smoking should focus on preventing smoking initiation in deprived areas.

The impact of 20 mph speed zones on socio-economic inequalities in road casualties in London

While socio-economic inequalities in road casualty risk are well documented, there is little evidence available on what works to reduce them. As there is good evidence that reducing the speed...

A multilevel study of the determinants of area-level inequalities in colorectal cancer survival

BackgroundIn Australia, associations between geographic remoteness, socioeconomic disadvantage, and colorectal cancer (CRC) survival show that survival rates are lowest among residents of geographically remote regions and those living in disadvantaged areas. At present we know very little about the reasons for these inequalities, hence our capacity to intervene to reduce the inequalities is limited.Methods/DesignThis study, the first of its type in Australia, examines the association between CRC survival and key area- and individual-level factors. Specifically, we will use a multilevel framework to investigate the possible determinants of area- and individual-level inequalities in CRC survival and quantify the relative contribution of geographic remoteness, socioeconomic and demographic factors, disease stage, and access to diagnostic and treatment services, to these inequalities. The multilevel analysis will be based on survival data relating to people diagnosed with CRC in Queensland between 1996 and 2005 (n = 22,723) from the Queensland Cancer Registry (QCR), area-level data from other data custodians such as the Australian Bureau of Statistics, and individual-level data from the QCR (including extracting stage from pathology records) and Queensland Hospitals. For a subset of this period (2003 and 2004) we will utilise more detailed, individual-level data (n = 1,966) covering a greater range of risk factors from a concurrent research study. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to treatment centres. The analyses will be conducted using a multilevel Cox proportional hazards model with Level 1 comprising individual-level factors (e.g. occupation) and level 2 area-level indicators of remoteness and area socioeconomic disadvantage.DiscussionThis study focuses on the health inequalities for rural and disadvantaged populations that have often been documented but poorly understood, hence limiting our capacity to intervene. This study utilises and develops emerging statistical and spatial technologies that can then be applied to other cancers and health outcomes. The findings of this study will have direct implications for the targeting and resourcing of cancer control programs designed to reduce the burden of colorectal cancer, and for the provision of diagnostic and treatment services.

Association of functional outcome with both personal‐ and area‐level socioeconomic inequalities in patients with inflammatory polyarthritis

ObjectiveTo describe the relationship between baseline area- and person-level social inequalities and functional disability at 3 years in patients with early inflammatory polyarthritis (IP).MethodsA total of 1,393 patients with new-onset IP were recruited and allocated an Index of Multiple Deprivation (IMD) 2004 score based on their area of residence, and a social class based on baseline self-reported occupation. Differences in the Health Assessment Questionnaire (HAQ) score at baseline and 3 years by IMD or social class were tested. The mean 3-year change in HAQ score was compared by IMD and social class, and interactions between these measures examined.ResultsPatients from more deprived areas had poorer 3-year HAQ outcome than those from less deprived areas (P = 0.019, adjusted for baseline HAQ score, age, sex, and symptom duration). The mean difference in HAQ change was most notable between the most deprived (IMD4) and least deprived areas (IMD1) (0.22; 95% confidence interval [95% CI] 0.11, 0.34). There was also a significant difference in HAQ score change between patients of the highest (SCI and II) and lowest social class (SCIV and V) (0.11; 95% CI 0.02, 0.20). For the mean (95% CI) 3-year change in HAQ score, a significant interaction exists between IMD score and social class and their association with HAQ scores (P = 0.001) to modify outcome: IMD1/SC I and II −0.23 (95% CI −0.40, −0.06) versus IMD 4/SC IV and V 0.15 (95% CI −0.05, 0.34).ConclusionPerson- and area-level inequalities combine to modify outcome for rheumatoid arthritis. A person's social circumstance and residential environment have independent effects on outcome and are not just alternative measures of the same exposure.

Socio-spatial inequalities and the distribution of cash benefits to asthmatic children in Norway

BackgroundPrevious research has observed large inequalities in the distribution of welfare benefits. The Norwegian welfare state includes several schemes that give households with children the opportunity to apply for public income support to compensate for expenses related to chronic disease. The aims of this study were to examine the geographic distribution of children receiving compensatory cash benefits because of a chronic asthma condition and to determine whether social or geographic factors account for area variations in uptake independent of the associations with need.ResultsConsiderable variation between counties was evident, with rates of benefit uptake ranging from 10.5 recipients per 1,000 children younger than nine years in the highest-ranking county, to 1.5 per 1,000 in the lowest. It is argued that the observed area-level inequalities reflect more than variations in morbidity. In particular, the chance of receiving benefits reflects variations in the ability of street-level bureaucrats to inform families about their rights. Spatial variations also reflect, in part, the fact that families with different socio-economic standing inhabit different locations and that the threshold for receiving benefits is systematically lower for families with an academic background.ConclusionTo be able to refine the implementation of a welfare policy, a better understanding of the processes that generate the outcomes of the various welfare schemes and services is required. This can be achieved by adopting an approach to the study of outcomes of welfare policy that integrates both the social and geographic perspective, and that focuses on specific diagnoses or distributional procedures.