Developing a new small-area measure of deprivation using 2001 and 2011 census data from Scotland

Trends in socioeconomic inequalities in cause-specific premature mortality in Belgium, 1998-2019

BACKGROUND

Higher levels of socioeconomic deprivation have been consistently associated with increased risk of premature mortality, but a detailed analysis by causes of death is lacking in Belgium. We aim to investigate the association between area deprivation and all-cause and cause-specific premature mortality in Belgium over the period 1998-2019.

METHODS

We used the 2001 and 2011 Belgian Indices of Multiple Deprivation to assign statistical sectors, the smallest geographical units in the country, into deprivation deciles. All-cause and cause-specific premature mortality rates, population attributable fraction, and potential years of life lost due to inequality were estimated by period, sex, and deprivation deciles.

RESULTS

Men and women living in the most deprived areas were 1.96 and 1.78 times more likely to die prematurely compared to those living in the least deprived areas over the period under study (1998-2019). About 28% of all premature deaths could be attributed to socioeconomic inequality and about 30% of potential years of life lost would be averted if the whole population of Belgium faced the premature mortality rates of the least deprived areas.

CONCLUSION

Premature mortality rates have declined over time, but inequality has increased due to a faster pace of decrease in the least deprived areas compared to the most deprived areas. As the causes of death related to poor lifestyle choices contribute the most to the inequality gap, more effective, country-level interventions should be put in place to target segments of the population living in the most deprived areas as they are facing disproportionately high risks of dying.

Prevalence of adult smokers in Brazilian capitals according to socioeconomic deprivation

OBJECTIVE

To estimate the prevalence of adult smokers in the 26 capitals and the Federal District according to the Brazilian Deprivation Index (Índice Brasileiro de Privação - IBP).

METHODS

Dataset on smoking were obtained from the Surveillance of Risk and Protective Factors for Noncommunicable Diseases by Survey (Vigitel) system for the 26 capitals and the Federal District, in the period from 2010 to 2013. The IBP classifies the census sectors according to indicators such as: income less than ½ minimum wage, illiterate population and without sanitary sewage. In the North and Northeast regions, the census sectors were grouped into four categories (low, medium, high and very high deprivation) and in the South, Southeast and Midwest regions into three (low, medium and high deprivation). Prevalence estimates of adult smokers were obtained using the indirect estimation method in small areas. To calculate the prevalence ratios, Poisson models are used.

RESULTS

The positive association between prevalence and deprivation of census sector categories was found in 16 (59.3%) of the 27 cities. In nine (33.3%) cities, the sectors with the greatest deprivation had a higher prevalence of smokers when compared to those with the least deprivation, and in two (7.4%) there were no differences. In Aracaju, Belém, Fortaleza, João Pessoa, Macapá and Salvador, the prevalence of adult smokers was three times higher in the group of sectors with greater deprivation compared to those with less deprivation.

CONCLUSION

Sectors with greater social deprivation had a higher prevalence of smoking, compared with less deprivation, pointing to social inequalities.

Aircraft noise and cardiovascular morbidity and mortality near Heathrow Airport: A case-crossover study

Aircraft noise causes annoyance and sleep disturbance and there is some evidence of associations between long-term exposures and cardiovascular disease (CVD). We investigated short-term associations between previous day aircraft noise and cardiovascular events in a population of 6.3 million residing near Heathrow Airport using a case-crossover design and exposure data for different times of day and night. We included all recorded hospitalisations (n = 442,442) and deaths (n = 49,443) in 2014-2018 due to CVD. Conditional logistic regression was used to estimate the ORs and adjusted for NO2 concentration, temperature, and holidays. We estimated an increase in risk for 10 dB increment in noise during the previous evening (Leve OR = 1.007, 95% CI 0.999-1.015), particularly from 22:00-23:00 h (OR = 1.007, 95% CI 1.000-1.013), and the early morning hours 04:30-06:00 h (OR = 1.012, 95% CI 1.002-1.021) for all CVD admissions, but no significant associations with day-time noise. There was effect modification by age-sex, ethnicity, deprivation, and season, and some suggestion that high noise variability at night was associated with higher risks. Our findings are consistent with proposed mechanisms for short-term impacts of aircraft noise at night on CVD from experimental studies, including sleep disturbance, increases in blood pressure and stress hormone levels and impaired endothelial function.

Levelling Up for health in towns? Development of a new deprivation index: the 'Stronger Towns Index' and its association with self-rated health and migration in England, between 2001 and 2011

Aim

To develop the 'Stronger Towns Index': a deprivation index that took into account characteristics of areas encompassing towns that may be eligible for redevelopment funding and explore how this index was associated with self-rated health and migration within England between 2001 and 2011.

Subject and methods

All members of the ONS Longitudinal Study in England aged 16 and over in 2001 whose records included a self-rated health response and a valid local authority code.Local authorities in England were ranked using a composite index developed using the five metrics set out in the Stronger Towns Funding: productivity, income, skills, deprivation measures, and the proportion of people living in towns.The index was split into deciles, and logistic regression carried out on the association between decile and self-rated health in 2001 in the main sample (n = 407,878) and decile change and self-rated health in 2011 in a subsample also present in 2011, with migration information (n = 299,008).

Results

There were areas in the lowest deciles of Town Strength who did not receive funding. After multiple adjustment, LS members living in areas with higher deciles were significantly more likely (7% to 38%) to report good health than those in the lowest decile in 2001. Remaining in the same decile between 2001 and 2011 was associated with 7% lower odds of good self-rated health in 2011.

Conclusion

It is important to consider health in towns when allocating funding. Areas in the Midlands may have missed out on funding which might help mitigate poor health.

Measuring small-area level deprivation in Belgium: The Belgian Index of Multiple Deprivation

BACKGROUND

In the past, deprivation has been mostly captured through simple and univariate measures such as low income or poor educational attainment in research on health and social inequalities in Belgium. This paper presents a shift towards a more complex, multidimensional measure of deprivation at the aggregate level and describes the development of the first Belgian Indices of Multiple Deprivation (BIMDs) for the years 2001 and 2011.

METHODS

The BIMDs are constructed at the level of the smallest administrative unit in Belgium, the statistical sector. They are a combination of six domains of deprivation: income, employment, education, housing, crime and health. Each domain is built on a suite of relevant indicators representing individuals that suffer from a certain deprivation in an area. The indicators are combined to create the domain deprivation scores, and these scores are then weighted to create the overall BIMDs scores. The domain and BIMDs scores can be ranked and assigned to deciles from 1 (the most deprived) to 10 (the least deprived).

RESULTS

We show geographical variations in the distribution of the most and least deprived statistical sectors in terms of individual domains and overall BIMDs, and we identify hotspots of deprivation. The majority of the most deprived statistical sectors are located in Wallonia, whereas most of the least deprived statistical sectors are in Flanders.

CONCLUSION

The BIMDs offer a new tool for researches and policy makers for analyzing patterns of deprivation and identifying areas that would benefit from special initiatives and programs.

Assessing the risk of endogeneity bias in health and mortality inequalities research using composite measures of multiple deprivation which include health-related indicators: A case study using the Scottish Index of Multiple Deprivation and population health and mortality data

The inclusion of health-related indicators in composite measures of multiple deprivation introduces a risk of endogeneity bias when using the latter in health inequalities research. This bias may ultimately result in the inappropriate allocation of healthcare resources and maintenance of preventable health inequalities. Mitigation strategies to avoid this bias include removing the health-related indicators or using single constituent domains (such as income or employment class) in isolation. These strategies have not been widely validated. This study used population-level health and mortality data with a contemporary composite measure of multiple deprivation (Scottish Index of Multiple Deprivation; SIMD) to assess these mitigation strategies. The differences between deprivation methods (original, health excluded, and income domain) were negligible. The results of quantitative research on health inequalities are unlikely to be affected by endogeneity bias.

Measuring disadvantage: A systematic comparison of United States small-area disadvantage indices

Extensive evidence demonstrates the effects of area-based disadvantage on a variety of life outcomes, such as increased mortality and low economic mobility. Despite these well-established patterns, disadvantage, often measured using composite indices, is inconsistently operationalized across studies. To address this issue, we systematically compared 5 U.S. disadvantage indices at the county-level on their relationships to 24 diverse life outcomes related to mortality, physical health, mental health, subjective well-being, and social capital from heterogeneous data sources. We further examined which domains of disadvantage are most important when creating these indices. Of the five indices examined, the Area Deprivation Index (ADI) and Child Opportunity Index 2.0 (COI) were most related to a diverse set of life outcomes, particularly physical health. Within each index, variables from the domains of education and employment were most important in relationships with life outcomes. Disadvantage indices are being used in real-world policy and resource allocation decisions; an index's generalizability across diverse life outcomes, and the domains of disadvantage which constitute the index, should be considered when guiding such decisions.

Data report on three datasets: Mortality patterns between agricultural and non-agricultural ward areas

The health of the farming community in Northern Ireland (NI) requires further research as previous mortality studies have reported contradictory results regarding farmers' health outcomes compared against other occupations and the general population. This study collated the NINIS area-level farm census with the population census information across 582 non-overlapping wards of NI to compile three mortality datasets (2001, 2011, and pooled dataset) (NISRA 2019). These datasets allow future researchers to investigate the influence of demographic, farming, and economic predictors on all-cause mortality at the ward level. The 2001 and 2011 mortality datasets were compiled for cross-sectional analyses and subsequently pooled for longitudinal analyses. Findings from these datasets will provide evidence of the influence of Farming Intensity scores influence on death risk within the wards for future researchers to utilise. This data report will aid in the understanding of socio-ecological variables' additive contribution to the risk of death at the ward level within NI. This data report is of interest to the One Health research community as it standardises the environment-human-animal data to pave the way towards a new One Health research paradigm. For example, future researchers can use this nationally representative data to investigate whether agriculturally saturated wards have a higher mortality risk than non-agriculturally based wards of NI.

Monitoring Health Inequalities in 12 European Countries: Lessons Learned from the Joint Action Health Equity Europe

To raise awareness about health inequalities, a well-functioning health inequality monitoring system (HIMS) is crucial. Drawing on work conducted under the Joint Action Health Equity Europe, the aim of this paper is to illustrate the strengths and weaknesses in current health inequality monitoring based on lessons learned from 12 European countries and to discuss what can be done to strengthen their capacities. Fifty-five statements were used to collect information about the status of the capacities at different steps of the monitoring process. The results indicate that the preconditions for monitoring vary greatly between countries. The availability and quality of data are generally regarded as strong, as is the ability to disaggregate data by age and gender. Regarded as poorer is the ability to disaggregate data by socioeconomic factors, such as education and income, or by other measures of social position, such as ethnicity. Few countries have a proper health inequality monitoring strategy in place and, where in place, it is often regarded as poorly up to date with policymakers’ needs. These findings suggest that non-data-related issues might be overlooked aspects of health inequality monitoring. Structures for stakeholder involvement and communication that attracts attention from policymakers are examples of aspects that deserve more effort.

The association between area deprivation and COVID-19 incidence: a municipality-level spatio-temporal study in Belgium, 2020–2021

Background

In Belgium, current research on socio-economic inequalities in the coronavirus disease 2019 (COVID-19) crisis has mainly focused on excess mortality and data from the first epidemiological wave. The current study adds onto this by examining the association between COVID-19 incidence and area deprivation during the first five wave and interwave periods, thus adding a temporal gradient to the analyses.

Methods

We use all confirmed COVID-19 cases between March 2020 and June 2021 in Belgium, aggregated at the municipality-level. These data were collected by the national laboratory-based COVID-19 surveillance system. A level of area deprivation was assigned to each Belgian municipality using data of three socio-economic variables: the share of unemployed persons in the active population, the share of households without a car and the share of low-educated persons. The spatio-temporal association between COVID-19 incidence and area deprivation was assessed by performing multivariate negative-binomial regression analyses and computing population attributable fractions.

Results

A significant association between COVID-19 incidence and area deprivation was found over the entire study period, with the incidence in the most deprived areas predicted to be 24% higher than in the least deprived areas. This effect was dependent on the period during the COVID-19 crisis. The largest socio-economic inequalities in COVID-19 infections could be observed during wave 2 and wave 3, with a clear disadvantage for deprived areas.

Conclusion

Our results provide new insights into spatio-temporal patterns of socio-economic inequalities in COVID-19 incidence in Belgium. They reveal the existence of inequalities and a shift of these patterns over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13690-022-00856-9.

Can an Ecological Index of Deprivation Be Used at the Country Level? The Case of the French Version of the European Deprivation Index (F-EDI)

Most ecological indices of deprivation are constructed from census data at the national level, which raises questions about the relevance of their use, and their comparability across a country. We aimed to determine whether a national index can account for deprivation regardless of location characteristics. In Metropolitan France, 43,853 residential census block groups (IRIS) were divided into eight area types based on quality of life. We calculated score deprivation for each IRIS using the French version of the European Deprivation Index (F-EDI). We decomposed the score by calculating the contribution of each of its components by area type, and we assessed the impact of removing each component and recalculating the weights on the identification of deprived IRIS. The set of components most contributing to the score changed according to the area type, but the identification of deprived IRIS remained stable regardless of the component removed for recalculating the score. Not all components of the F-EDI are markers of deprivation according to location characteristics, but the multidimensional nature of the index ensures its robustness. Further research is needed to examine the limitations of using these indices depending on the purpose of the study, particularly in relation to the geographical grid used to calculate deprivation scores.

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

Objectives: We compare rates of ill health and socioeconomic inequalities in health by ethnic groups in Scotland by age. We focus on ethnic differences in socioeconomic inequalities in health. There is little evidence of how socioeconomic inequalities in health vary by ethnicity, especially in Scotland, where health inequalities are high compared to other European countries.Design: A cross-sectional study using the 2011 Scottish Census (population 5.3 million) was conducted. Directly standardized rates were calculated for two self-rated health outcomes (poor general health and limiting long-term illness) separately by ethnicity, age and small-area deprivation. Slope and relative indices of inequality were calculated to measure socioeconomic inequalities in health.Results: The results show that the White Scottish population tend to have worse health and higher socioeconomic inequalities in health than many other ethnic groups, while White Polish and Chinese people tend to have better health and low socioeconomic inequalities in health. These results are more salient for ages 30-44. The Pakistani population has high rates of poor health similar to the White Scottish for ages 15-44, but at ages 45 and above Pakistani people have the highest rates of poor self-rated health. Compared to other ethnicities, Pakistani people are also more likely to experience poor health in the least deprived areas, particularly at ages 45 and above.Conclusions: There are statistically significant and substantial differences in poor self-rated health and in socioeconomic inequalities in health between ethnicities. Rates of ill health vary between ethnic groups at any age. The better health of the younger minority population should not be taken as evidence of better health outcomes in later life. Since socioeconomic gradients in health vary by ethnicity, policy interventions for health improvement in Scotland that focus only on deprived areas may inadvertently exclude minority populations.

Cancer mortality 1981-2016 and contribution of specific cancers to current socioeconomic inequalities in all cancer mortality: A population-based study

BACKGROUND

In many high-income countries cancer mortality rates have declined, however, socioeconomic inequalities in cancer mortality have widened over time with those in the most deprived areas bearing the greatest burden. Less is known about the contribution of specific cancers to inequalities in total cancer mortality.

METHODS

Using high-quality routinely collected population and mortality records we examine long-term trends in cancer mortality rates in Scotland by age group, sex, and area deprivation. We use the decomposed slope and relative indices of inequality to identify the specific cancers that contribute most to absolute and relative inequalities, respectively, in total cancer mortality.

RESULTS

Cancer mortality rates fell by 24 % for males and 10 % for females over the last 35 years; declining across all age groups except females aged 75+ where rates rose by 14 %. Lung cancer remains the most common cause of cancer death. Mortality rates of lung cancer have more than halved for males since 1981, while rates among females have almost doubled over the same period.

CONCLUSION

Current relative inequalities in total cancer mortality are dominated by inequalities in lung cancer mortality, but with contributions from other cancer sites including liver, and head and neck (males); and breast (females), stomach and cervical (younger females). An understanding of which cancer sites contribute most to inequalities in total cancer mortality is crucial for improving cancer health and care, and for reducing preventable cancer deaths.

Estimates of hypertension and diabetes mellitus prevalence according to Health Vulnerability Index in Belo Horizonte, MG, Brazil

OBJECTIVE

To estimate the prevalences of hypertension and diabetes for small areas in Belo Horizonte, according to the Health Vulnerability Index (HVI).

METHODS

Ecological study with data from the Surveillance of Risk and Protection Factors for Chronic Diseases by Telephone Survey (Vigitel) conducted in Belo Horizonte, from 2006 to 2013. The self-reported diagnosis of diabetes and hypertension were evaluated. The estimates of prevalence and the 95% confidence interval (95%CI) were calculated using the direct and indirect method by HVI grouped into four categories: low, medium, high and very high health risk.

RESULTS

During the period evaluated, 26% (95%CI 25.2 - 26.8) and 6.1% (95%CI 6.7 - 6.5) of the adult population from Belo Horizonte reported being hypertensive and diabetic, respectively. According to the indirect method to obtain estimates of hypertension and diabetes prevalences per HVI, it was found that areas of very high risk had a higher prevalence of adults with hypertension (38.6%; 95%CI 34.8 - 42.4) and diabetes (16.2%; 95%CI 13.1 - 19.3) when compared to the low risk (28.2%; 95%CI 27.0 - 29.4 and 6%; 95%CI 5.4 - 6.7, respectively).

CONCLUSION

The adult population living in areas at high risk for health had a higher prevalence of hypertension and diabetes compared to those with a lower risk.

Reporting of social deprivation in musculoskeletal trials: An analysis of 402 randomised controlled trials

BACKGROUND

Social deprivation is broadly defined as the restriction of access an individual has to social or cultural interactions due to poverty, discrimination or other disadvantages. While social deprivation is a widely acknowledged determinant of outcome in musculoskeletal conditions, it remains unclear how this is considered in the conduct and interpretation of musculoskeletal trials.

AIM

To determine the frequently to which measures of social deprivation are reported in trials recruiting people with musculoskeletal diseases.

MATERIALS AND METHODS

We conducted a Pubmed search of randomised controlled trials published between 01 January 2019 and 01 June 2020. We included full-text papers of trials recruiting people with musculoskeletal diseases, irrespective of intervention type or origin. We extracted data relating to trial characteristics, setting, trial design, funding source and musculoskeletal disease. We extracted data on any reported social deprivation index or measure of social deprivation based on internationally adopted indicators. We analysed data descriptively to summarise the reporting of each social deprivation index and measure of social deprivation within trials.

RESULTS

From 2133 potentially eligible citations, 402 were eligible. Mean age of participants was 51.7 years; 63% were female. Trials most frequently recruited people with spinal pain (24.6%) or osteoarthritis (10.0%). Two trials (0.5%) reported social deprivation indices/scores. When assessed by discrete measures of social deprivation, 164 trials (40.8%) reported one or more social deprivation measures. The most commonly reported measures were morbidity (20.2%), employment status (17.7%) and educational attainment (15.5%). Race (6.7%), ethnicity (6.2%) and annual salary (1.3%) were infrequently reported. One trial (0.3%) presented subgroup results by social deprivation measures.

DISCUSSION AND CONCLUSION

Social deprivation is inconsistently reported in musculoskeletal trials. Trialists should report baseline measures of social deprivation in trial reports and aid generalisability to target population, and to examine whether social deprivation might modify treatment effects of interventions for musculoskeletal conditions.

All-cause and cause-specific mortality in Scotland 1981-2011 by age, sex and deprivation: a population-based study

Background

Average life expectancy has stopped increasing for many countries. This has been attributed to causes such as influenza, austerity policies and deaths of despair (drugs, alcohol and suicide). Less is known on the inequality of life expectancy over time using reliable, whole population, data. This work examines all-cause and cause-specific mortality rates in Scotland to assess the patterning of relative and absolute inequalities across three decades.

Methods

Using routinely collected Scottish mortality and population records we calculate directly age-standardized mortality rates by age group, sex and deprivation fifths for all-cause and cause-specific deaths around each census 1981–2011.

Results

All-cause mortality rates in the most deprived areas in 2011 (472 per 100 000 population) remained higher than in the least deprived in 1981 (422 per 100 000 population). For those aged 0–64, deaths from circulatory causes more than halved between 1981 and 2011 and cancer mortality decreased by a third (with greater relative declines in the least deprived areas). Over the same period, alcohol- and drug-related causes and male suicide increased (with greater absolute and relative increases in more deprived areas). There was also a significant increase in deaths from dementia and Alzheimer’s disease for those aged 75+.

Conclusions

Despite reductions in mortality, relative (but not absolute) inequalities widened between 1981 and 2011 for all-cause mortality and for several causes of death. Reducing relative inequalities in Scotland requires faster mortality declines in deprived areas while countering increases in mortality from causes such as drug- and alcohol-related harm and male suicide.

Visualizing Opportunity Index Data Using a Dashboard Application: A Tool to Communicate Infant Mortality-Based Area Deprivation Index Information

BACKGROUND

An area deprivation index (ADI) is a geographical measure that accounts for socioeconomic factors (e.g., crime, health, and education). The state of Ohio developed an ADI associated with infant mortality: Ohio Opportunity Index (OOI). However, a powerful tool to present this information effectively to stakeholders was needed.

OBJECTIVES

We present a real use-case by documenting the design, development, deployment, and training processes associated with a dashboard solution visualizing ADI data.

METHODS

The Opportunity Index Dashboard (OID) allows for interactive exploration of the OOI and its seven domains-transportation, education, employment, housing, health, access to services, and crime. We used a user-centered design approach involving feedback sessions with stakeholders, who included representatives from project sponsors and subject matter experts. We assessed the usability of the OID based on the effectiveness, efficiency, and satisfaction dimensions. The process of designing, developing, deploying, and training users in regard to the OID is described.

RESULTS

We report feedback provided by stakeholders for the OID categorized by function, content, and aesthetics. The OID has multiple, interactive components: choropleth map displaying OOI scores for a specific census tract, graphs presenting OOI or domain scores between tracts to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. Changes based on parameter and filter selections are described using a general use-case. In the usability evaluation, the median task completion success rate was 83% and the median system usability score was 68.

CONCLUSION

The OID could assist health care leaders in making decisions that enhance care delivery and policy decision making regarding infant mortality. The dashboard helps communicate deprivation data across domains in a clear and concise manner. Our experience building this dashboard presents a template for developing dashboards that can address other health priorities.

A methodology for small area prevalence estimation based on survey data

BACKGROUND

Brazil conducts many health surveys to provide estimates by national level, macro-regions, states, metropolitan regions and capitals. However, estimates for smaller areas are lacking due to their high cost. The Health Vulnerability Index (in Portuguese, Índice de Vulnerabilidade em Saúde, IVS) is a measure that combines socioeconomic and environmental variables in the same indicator and allows for the analysis of the characteristics of population groups residing in census tracts, grouping them into four health risk areas (low, medium, high and very high risk) in addition to showing inequalities in the epidemiological profile of different social groups. This index was developed by the Municipal Health Secretariat of Belo Horizonte to guide health planning.

OBJECTIVE

The aim of the study is to produce a methodology for obtaining reliable estimates for tobacco smoking in small areas for which the IVS was not designed.

METHODS

The Vigitel dataset from 2006 to 2013 was used to obtain estimates of the prevalence of smokers based on the IVS employing small area estimation methods that use data from a larger domain to obtain estimates in smaller areas. For indirect estimates, the covariates included were sanitation, housing, education, income, and social and health factors. Post-stratification weights were used according to the IVS based on the population of the 2010 census.

RESULTS

From 2006 to 2009, 16.2% (95% CI: 13.6-14.8%) of the adult population in Belo Horizonte were smokers, and 14.8% (95% CI: 14.0-15.6%) were smokers between 2010 and 2013. The very high-risk population maintained a high prevalence over the same period of 21.1% (95% CI: 17.1-25.0%) between 2006 and 2009 and 20.8% (95% CI: 17.0-24.6%) between 2010 and 2013, while in the low-risk group, the prevalence in the same period fell from 14.9% (95% CI: 13.7-16.2%) to 11.8% (95% CI, 10.6-13.1%).

CONCLUSIONS

The present study identified differences in the profile of smokers by the IVS in the city of Belo Horizonte. While the smoking prevalence declined in richer areas, it remained high in poor areas. This methodology can be used to produce reliable estimates for subgroups with greater vulnerability in small areas and thus subsidize the formulation, monitoring and evaluation of public health policies and programmes aimed at smoking.

Dealing with spatial misalignment to model the relationship between deprivation and life expectancy: a model-based geostatistical approach

BACKGROUND : Life expectancy at birth (LEB), one of the main indicators of human longevity, has often been used to characterise the health status of a population. Understanding its relationships with the deprivation is key to develop policies and evaluate interventions that are aimed at reducing health inequalities. However, methodological challenges in the analysis of LEB data arise from the fact that different Government agencies often provide spatially aggregated information on LEB and the index of multiple deprivation (IMD) at different spatial scales. Our objective is to develop a geostatistical framework that, unlike existing methods of inference, allows to carry out spatially continuous prediction while dealing with spatial misalignment of the areal-level data. METHODS : We developed a model-based geostatistical approach for the joint analysis of LEB and IMD, when these are available over different partitions of the study region. We model the spatial correlation in LEB and IMD across the areal units using inter-point distances based on a regular grid covering the whole of the study area. The advantages and strengths of the new methodology are illustrated through an analysis of LEB and IMD data from the Liverpool district council. RESULTS : We found that the effect of IMD on LEB is stronger in males than in females, explaining about 63.35% of the spatial variation in LEB in the former group and 38.92% in the latter. We also estimate that LEB is about 8.5 years lower between the most and least deprived area of Liverpool for men, and 7.1 years for women. Finally, we find that LEB, both in males and females, is at least 80% likely to be above the England wide average only in some areas falling in the electoral wards of Childwall, Woolton and Church. CONCLUSION : The novel model-based geostatistical framework provides a feasible solution to the spatial misalignment problem. More importantly, the proposed methodology has the following advantages over existing methods used model LEB: (1) it can deliver spatially continuous inferences using spatially aggregated data; (2) it can be applied to any form of misalignment with information provided at a range of spatial scales, from areal-level to pixel-level.

Socioeconomic gradients of adverse birth outcomes and related maternal factors in rural and urban Alberta, Canada: a concentration index approach

OBJECTIVE

Using a summary measure of health inequalities, this study evaluated the distribution of adverse birth outcomes (ABO) and related maternal risk factors across area-level socioeconomic status (SES) gradients in urban and rural Alberta, Canada.

DESIGN

Cross-sectional study using a validated perinatal clinical registry and an area-level SES.

SETTING

The study was conducted in Alberta, Canada. Data about ABO and related maternal risk factors were obtained from the Alberta Perinatal Health Program between 2006 and 2012. An area-level SES index derived from census data (2006) was linked to the postal code at delivery.

PARTICIPANTS

Women (n=3 30 957) having singleton live births with gestational age ≥22 weeks.

PRIMARY AND SECONDARY OUTCOME MEASURES

We estimated concentration indexes to assess inequalities across SES gradients in both rural and urban areas (CIdx_R and CIdx_U, respectively) for spontaneous preterm birth (PTB), small for gestational age (SGA), large for gestational age (LGA), gestational hypertension, gestational diabetes, smoking and substance use during pregnancy and pre-pregnancy weight >91 kg.

RESULTS

The highest health inequalities disfavouring low SES groups were identified for substance abuse and smoking in rural areas (CIdx_R-0.38 and -0.23, respectively). Medium inequalities were identified for LGA (CIdx_R-0.08), pre-pregnancy weight >91 kg (CIdx_R-0.07), substance use (CIdx_U-0.15), smoking (CIdx_U-0.14), gestational diabetes (CIdx_U-0.10) and SGA (CIdx_U-0.07). Low inequalities were identified for PTB (CIdx_R-0.05; CIdx_U-0.05) and gestational diabetes (CIdx_R-0.04). Inequalities disfavouring high SES groups were identified for gestational hypertension (CIdx_R+0.04), SGA (CIdx_R+0.03) and LGA (CIdx_U+0.03).

CONCLUSIONS

ABO and related maternal risk factors were unequally distributed across the socioeconomic gradient in urban-rural settings, with the greatest concentrations in lower SES groups of rural areas. Future research is needed on underlying mechanisms driving SES gradients in perinatal health across the rural-urban spectrum.

Geodemographic Area Classification and Association with Mortality: An Ecological Study of Small Areas of Cyprus

Geographical investigations are a core function of public health monitoring, providing the foundation for resource allocation and policies for reducing health inequalities. The aim of this study was to develop geodemographic area classification based on several area-level indicators and to explore the extent of geographical inequalities in mortality. A series of 19 area-level socioeconomic indicators were used from the 2011 national population census. After normalization and standardization of the geographically smoothed indicators, the k-means cluster algorithm was implemented to classify communities into groups based on similar characteristics. The association between geodemographic area classification and the spatial distribution of mortality was estimated in Poisson log-linear spatial models. The k-means algorithm resulted in four distinct clusters of areas. The most characteristic distinction was between the ageing, socially isolated, and resource-scarce rural communities versus metropolitan areas with younger population, higher educational attainment, and professional occupations. By comparison to metropolitan areas, premature mortality appeared to be 44% (95% Credible Intervals [CrI] of Rate Ratio (RR): 1.06-1.91) higher in traditional rural areas and 36% (95% CrI of RR: 1.13-1.62) higher in young semi-rural areas. These findings warrant future epidemiological studies investigating various causes of the urban-rural differences in premature mortality and implementation policies to reduce the mortality gap between urban and rural areas.

The increasing lifespan variation gradient by area-level deprivation: A decomposition analysis of Scotland 1981-2011

Life expectancy inequalities are an established indicator of health inequalities. More recent attention has been given to lifespan variation, which measures the amount of heterogeneity in age at death across all individuals in a population. International studies have documented diverging socioeconomic trends in lifespan variation using individual level measures of income, education and occupation. Despite using different socioeconomic indicators and different indices of lifespan variation, studies reached the same conclusion: the most deprived experience the lowest life expectancy and highest lifespan variation, a double burden of mortality inequality. A finding of even greater concern is that relative differences in lifespan variation between socioeconomic group were growing at a faster rate than life expectancy differences. The magnitude of lifespan variation inequalities by area-level deprivation has received limited attention. Area-level measures of deprivation are actively used by governments for allocating resources to tackle health inequalities. Establishing if the same lifespan variation inequalities emerge for area-level deprivation will help to better inform governments about which dimension of mortality inequality should be targeted. We measure lifespan variation trends (1981-2011) stratified by an area-level measure of socioeconomic deprivation that is applicable to the entire population of Scotland, the country with the highest level of variation and one of the longest, sustained stagnating trends in Western Europe. We measure the gradient in variation using the slope and relative indices of inequality. The deprivation, age and cause specific components driving the increasing gradient are identified by decomposing the change in the slope index between 1981 and 2011. Our results support the finding that the most advantaged are dying within an ever narrower age range while the most deprived are facing greater and increasing uncertainty. The least deprived group show an increasing advantage, over the national average, in terms of deaths from circulatory disease and external causes.

Small-area socioeconomic deprivation indices in Cyprus: development and association with premature mortality

Background

Area-level measures of socioeconomic deprivation are important for understanding and describing health inequalities. The aim of this study was the development and validation of a small-area index of socioeconomic deprivation for Cypriot communities and the investigation of its association with the spatial distribution of all-cause premature adult mortality.

Methods

Six area-level socioeconomic indicators were used from the 2011 national population census (low educational attainment, unemployment, not owner occupied household, single-person household, divorced or widowed and single-parent households). After normalization and standardization of the geographically smoothed indicators, Principal Component Analysis (PCA) was used to construct indicator weights. The association between deprivation indices and the spatial distribution of all-cause premature adult mortality was estimated in Poisson log-linear spatial models.

Results

PCA resulted in two principal components explaining the 65.7% of the total variance. The first principal component included four indicators (low educational attainment, single-person households, divorced or widowed and single-parent households, the latter however with a negative loading) and it thought more likely to capture rural-related aspects of deprivation. The second principal component included the other two indicators (unemployment and not owner occupied households) and it is more likely to capture urban-related aspects of material deprivation. Restricting the analysis in the metropolitan areas of the island resulted in a different set of indicators for the urban-specific deprivation index. All developed indices were linearly associated with all-cause premature adult mortality. The all-cause premature adult mortality increased by 17% per 1 standard deviation (SD) increase in rural-related socioeconomic deprivation (95% CrI: 8–27%) and 8% per 1 SD increase in urban-related aspects of material deprivation (95% CrI: 3–15%) in the nationwide analysis and 9% per 1 SD increase in urban-specific socioeconomic deprivation (95% CrI: 4–15%) across metropolitan areas.

Conclusions

The results of this study demonstrate that a set of small-area indices of socioeconomic deprivation across Cypriot communities have good construct and predictive validity. However, the study indicates that different aspects of socioeconomic deprivation may be important in rural and urban areas in Cyprus. The developed socioeconomic deprivation indices could offer a valid new tool for Cypriot public health research and policy in terms of identifying areas in greatest need, guiding resource allocation and developing area-targeted public health programmes and policies.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6973-0) contains supplementary material, which is available to authorized users.

Changing contribution of area-level deprivation to total variance in age at death: a population-based decomposition analysis

OBJECTIVES

Two processes generate total variance in age at death: heterogeneity (between-group variance) and individual stochasticity (within-group variance). Limited research has evaluated how these two components have changed over time. We quantify the degree to which area-level deprivation contributed to total variance in age at death in Scotland between 1981 and 2011.

DESIGN

Full population and mortality data for Scotland were obtained and matched with the Carstairs score, a standardised z-score calculated for each part-postcode sector that measures relative area-level deprivation. A z-score above zero indicates that the part-postcode sector experienced higher deprivation than the national average. A z-score below zero indicates lower deprivation. From the aggregated data we constructed 40 lifetables, one for each deprivation quintile in 1981, 1991, 2001 and 2011 stratified by sex.

PRIMARY OUTCOME MEASURES

Total variance in age at death and the proportion explained by area-level deprivation heterogeneity (between-group variance).

RESULTS

The most deprived areas experienced stagnating or slightly increasing variance in age at death. The least deprived areas experienced decreasing variance. For males, the most deprived quintile life expectancy was between 7% and 11% lower and the SD is between 6% and 25% higher than the least deprived. This suggests that the effect of deprivation on the SD of longevity is comparable to its effect on life expectancy. Decomposition analysis revealed that contributions from between-group variance doubled between 1981 and 2011 but at most only explained 4% of total variance.

CONCLUSIONS

This study adds to the emerging body of literature demonstrating that socio-economic groups have experienced diverging trends in variance in age at death. The contribution from area-level deprivation to total variance in age at death, which we were able to capture, has doubled since 1981. Area-level deprivation may play an increasingly important role in mortality inequalities.

The geographic harmonisation of Scotland's small area census data, 1981 to 2011

Previous research in Scotland used a merging approach to combine census boundary data for geographies specific to 1981, 1991 and 2001 to create Consistent Areas Through Time (CATTs) for the analysis of health and social data for small areas. In this paper, we adopt the same methodology to integrate the 2011 Scottish Output Areas to the CATTs. First, we overlaid the 2001 Output Areas upon the 2011 Output Areas to create SUPER OAs, which were then combined with SUPER EDs, which represented a consistent small area geography for 1981 and 1991. This resulted in 8,548 CATTs providing a consistent geography for the 1981, 1991, 2001 and 2011 Censuses in Scotland. We demonstrate the utility of the CATTs by exploring the correlations between deprivation, the proportion of the population who were permanently sick and those with degree qualifications, across the 4 censuses, a research angle impossible without consistent geographies. We have provided a resource that enables users to deepen their understanding of small area social changes in Scotland between the 1981 and 2011 Censuses.

Using population surfaces and spatial metrics to track the development of deprivation landscapes in Glasgow, Liverpool, and Manchester between 1971 and 2011

Measuring change in the spatial arrangement of deprivation over time, and making international, inter-city comparisons, is technically challenging. Meeting these challenges offers a means of furthering understanding and providing new insights into the geography of urban poverty and deprivation. In this paper, we introduce a novel approach to mapping and analysing spatio-temporal patterns of household deprivation, assessing the distribution at the landscape level. The approach we develop has advantages over existing techniques because it is applicable in situations where i) conventional approaches based on choropleth mapping are not feasible due to boundary change and/or ii) where spatial relationships at a landscape level are of interest. Through the application of surface mapping techniques to disaggregate census count data, and by applying spatial metrics commonly used in ecology, we were able to compare the development of the spatial arrangement of deprivation between 1971 and 2011 in three UK cities of particular interest: Glasgow, Manchester and Liverpool. Applying three spatial metrics - spatial extent, patch density, and mean patch size - revealed that over the 40 year period household deprivation has been more spatially dispersed in Glasgow. This novel approach has enabled an analysis of deprivation distributions over time which is less affected by boundary change and which accurately assesses and quantifies the spatial relationships between those living with differing levels of deprivation. It thereby offers a new approach for researchers working in this area.

Patterns of referral and waiting times for specialist Child and Adolescent Mental Health Services

BACKGROUND

During 12-month period (2012/13) around 21,480 children and young people (CYP) were referred to Child and Adolescent Mental Health Service (CAMHS) in Scotland (NHS Scotland, 2013, Child and Adolescent Mental Health Services waiting times in Scotland). At the end of September 2012, there were 3,602 CYP still waiting for 'start of treatment' or 'removal from the waiting list', 375 (10%) CYP had waited over 26 weeks and 1,204 (33%) CYP had waited over 18 weeks (NHS Scotland, 2013, Child and Adolescent Mental Health Services waiting times in Scotland). Referral source, referral reason and the sociodemographic characteristics of CYP are not routinely collected, and therefore, associations between these factors and wait times for 'start of treatment' or 'removal from the waiting list' (i.e. the referral outcome) are unknown.

METHOD

In this exploratory study, a retrospective analysis of referral data was conducted in one CAMHS. Data for 476 referrals between 1st May 2013 and 31st May 2014 were initially analysed to define categories for each of the following key variables: referral source, referral reason and referral outcome. Data on CYP sociodemographic characteristics were extracted from referral records, including age, gender and postcode, from which Scottish Index of Multiple Deprivation quintile of residence was derived. Descriptive statistics were calculated for referral source, referral reason and CYP sociodemographic characteristics. Regression models were then built to determine predictors of a referral being rejected by CAMHS and waiting time for referrals accepted by CAMHS. Data were analysed in SPSS (Version 20).

RESULTS

Of the 476 referrals, 72% (n = 342) were accepted and 12% (n = 59) were rejected. Most referrals were made by general practitioners. Just under a third of referrals to CAMHS (31%) were for CYP with emotional and behavioural difficulties. The odds of being rejected by CAMHS were significantly higher if referred by teachers and for CYP with emotional and behavioural difficulties. Age and referral reason were significant independent predictors of waiting time after referral to CAMHS, with CYP referred for hyperactivity/inattention waiting significantly longer.

CONCLUSIONS

Policymakers should consider ways to foster dialogue and collaboration between different groups of professionals making and accepting referrals to CAMHS in order to improve timely access to appropriate mental health support services for CYP. Research is urgently needed to investigate the experiences of CYP who are either rejected by CAMHS or wait lengthy periods of time before starting their treatment with CAMHS.

Comparing Classic and Interval Analytical Hierarchy Process Methodologies for Measuring Area-Level Deprivation to Analyze Health Inequalities

Deprivation indices are useful measures to study health inequalities. Different techniques are commonly applied to construct deprivation indices, including multi-criteria decision methods such as the analytical hierarchy process (AHP). The multi-criteria deprivation index for the city of Quito is an index in which indicators are weighted by applying the AHP. In this research, a variation of this index is introduced that is calculated using interval AHP methodology. Both indices are compared by applying logistic generalized linear models and multilevel models, considering self-reported health as the dependent variable and deprivation and self-reported quality of life as the independent variables. The obtained results show that the multi-criteria deprivation index for the city of Quito is a meaningful measure to assess neighborhood effects on self-reported health and that the alternative deprivation index using the interval AHP methodology more thoroughly represents the local knowledge of experts and stakeholders. These differences could support decision makers in improving health planning and in tackling health inequalities in more deprived areas.

How do trends in mortality inequalities by deprivation and education in Scotland and England & Wales compare? A repeat cross-sectional study

OBJECTIVE

To compare the trends in mortality inequalities by educational attainment with trends using area deprivation.

SETTING

Scotland and England & Wales (E&W).

PARTICIPANTS

All people resident in Scotland and E&W between 1981 and 2011 aged 35-79 years.

PRIMARY OUTCOME MEASURES

Absolute inequalities (measured using the Slope Index of Inequality (SII)) and relative inequalities (measured using the Relative Index of Inequality (RII)) in all-cause mortality.

RESULTS

Relative inequalities in mortality by area deprivation have consistently increased for men and women in Scotland and E&W between 1981-1983 and 2010-2012. Absolute inequalities increased for men and women in Scotland, and for women in E&W, between 1981-1983 and 2000-2002 before subsequently falling. For men in E&W, absolute inequalities were more stable until 2000-2002 before a subsequent decline. Both absolute and relative inequalities were consistently higher in men and in Scotland. These trends contrast markedly with the reported declines in mortality inequalities by educational attainment and apparent improvement of Scotland's inequalities with those in E&W.

CONCLUSIONS

Trends in health inequalities differ when assessed using different measures of socioeconomic status, reflecting either genuinely variable trends in relation to different aspects of social stratification or varying error or bias. There are particular issues with the educational attainment data in Great Britain prior to 2001 that make these education-based estimates less certain.

Small-area deprivation measure datasets for Scotland, 2001 and 2011

These data present a new small-area deprivation measure, but also include a variety of other indicators, such as the Scottish Index of Multiple Deprivation (SIMD) and the Carstairs score. The data are for Scottish 2001 Datazones and for the years 2001 and 2011. In addition the data provide standardised self-reported measures of general health and limiting long-term illness. The theoretical background for developing the new deprivation measure, and the implications of using different measures to study health inequalities are discussed in "Developing a new small-area measure of deprivation using 2001 and 2011 census data from Scotland" (Allik et al., 2016) [1].