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

Reassessing socioeconomic inequalities in mortality via distributional similarities

Commonly used measures of socioeconomic inequalities in mortality, such as the slope and the relative index of inequality, are based on summary measures of the group-specific age-at-death distributions (e.g. standardized mortality rate or life expectancy). While this approach is informative, it ignores valuable information contained in the group-specific distributions. A recent approach applied a measure of distributional dissimilarity (the non-overlap index) to measure lifespan stratification. In this paper, we rigorously evaluate and further implement the multi-group extension of the non-overlap index ( S P ) to measure socioeconomic inequalities in mortality across a number of groups, and assess whether differences across countries and over time are driven by mortality or compositional changes in two applications with different data availability: educational groups (Sweden and Denmark) and groups defined by an area-level deprivation measure (England). Our findings suggest that the multi-group S P is sensitive not only to changes in the means or variances, but also to broader mortality changes that affect distributional shapes. The method can be employed to any context where mortality rates by age are available by sub-groups. Furthermore, levels and trends in mortality inequalities computed with the multigroup S P often differ compared to other conventional summary-based measures. Moreover, we find that the contribution of mortality changes to changes in inequalities is generally greater than that of the changes in the population composition. Whereas levels and trends of inequalities may depend on whether life expectancy- or lifespan variation-based measures are employed, the multi-group S P provides a holistic perspective by capturing both dimensions simultaneously.

A Cross-Sectional Study of Symptom Prevalence, Frequency, Severity, and Impact of Long COVID in Scotland: Part I

BACKGROUND

Commonly reported symptoms of long COVID may have different patterns of prevalence and presentation across different countries. While some limited data have been reported for the United Kingdom, national specificity for Scotland is less clear. We present a cross-sectional survey to examine the symptom prevalence, frequency, and severity of long COVID for people living with the condition in Scotland.

METHODS

An online survey was created in the English language and was available between April 21, 2022 and August 5, 2022. Participants were included if they were ≥18 years old, living in Scotland, and had self-diagnosed or confirmed long COVID; and excluded if they were hospitalized during their initial infection. Within this article we quantify symptom prevalence, frequency, severity, and duration.

RESULTS

Participants (n = 253) reported the most prevalent long-COVID symptoms to be post-exertional malaise (95%), fatigue/tiredness (85%), and cognitive impairment (68%). Fatigue/tiredness, problems with activities of daily living (ADL), and general pain were most frequently occurring, while sleep difficulties, problems with ADL, and nausea were the most severe. Scottish Index of Multiple Deprivation associated with symptom number, severity, and frequency, whereas vaccine status, age, sex, and smoking status had limited or no association.

CONCLUSIONS

These findings outline the challenges faced for those living with long COVID and highlight the need for longitudinal research to ascertain a better understanding of the condition and its longer-term societal impact.

Healthcare delivery in Lebanon: a critical scoping review of strengths, weaknesses, opportunities, and threats

BACKGROUND

Lebanon, an Eastern Mediterranean country with a lower-middle income status, that once boasted a health care system that was functional despite its challenges and complexity. However, it has faced a series of crises-economic, an influx of refugees, political instability, and recent sanctions-that have significantly impacted its aim, principles and values that has impacted upon its ability to function. The objective of this study is to delve into the health service delivery within the Lebanese system and conduct a SWOT analysis (assessing strengths, weaknesses, opportunities, and threats).

METHODS

We conducted a scoping review, examining literature related to the Lebanese health system and its performance in delivering healthcare services. We followed the Arksey and O'Malley framework, which involves six key phases: identifying the research question, identifying relevant studies, study selection, charting the data, collating, summarizing, and reporting the results, consultation.

RESULTS

Despite Lebanon grappling with multiple crises in recent years-such as the COVID-19 pandemic and economic downturn-the health system has demonstrated resilience in service delivery. However, challenges persist. Healthcare providers, including physicians and nurses, must address these issues. Additionally, economic and political crises pose threats that have necessitated significant changes in healthcare service delivery.

CONCLUSION

In the system of healthcare in Lebanon, there have been remarkable achievements, but continuous attention by healthcare providers and the Ministry of Public Health (MoPH) is critical. Economic and political challenges exert constant pressure on service delivery and thus reveal a need for strategic changes, most importantly in health financing if Universal Health Coverage (UHC) is to be attained. Proper resources to strategic reform and system implementation in all parts of the country to ensure equitable access and quality care that is sustained are obligatory.

Life expectancy and geographic variation in mortality: an observational comparison study of six high-income Anglophone countries

OBJECTIVE

To compare life expectancy levels and within-country geographic variation in life expectancy across six high-income Anglophone countries between 1990 and 2018.

DESIGN

Demographic analysis using aggregated mortality data.

SETTING

Six high-income Anglophone countries (USA, UK, Canada, Australia, Ireland and New Zealand), by sex, including an analysis of subnational geographic inequality in mortality within each country.

POPULATION

Data come from the Human Mortality Database, the WHO Mortality Database and the vital statistics agencies of six high-income Anglophone countries.

MAIN OUTCOME MEASURES

Life expectancy at birth and age 65; age and cause of death contributions to life expectancy differences between countries; index of dissimilarity for within-country geographic variation in mortality.

RESULTS

Among six high-income Anglophone countries, Australia is the clear best performer in life expectancy at birth, leading its peer countries by 1.26-3.95 years for women and by 0.97-4.88 years for men in 2018. While Australians experience lower mortality across the age range, most of their life expectancy advantage accrues between ages 45 and 84. Australia performs particularly well in terms of mortality from external causes (including drug- and alcohol-related deaths), screenable/treatable cancers, cardiovascular disease and influenza/pneumonia and other respiratory diseases compared with other countries. Considering life expectancy differences across geographic regions within each country, Australia tends to experience the lowest levels of inequality, while Ireland, New Zealand and the USA tend to experience the highest levels.

CONCLUSIONS

Australia has achieved the highest life expectancy among Anglophone countries and tends to rank well in international comparisons of life expectancy overall. It serves as a potential model for lower-performing countries to follow to reduce premature mortality and inequalities in life expectancy.

Cross-sectional Average Length of Life Entropy ( H CAL ): International Comparisons and Decompositions

Keyfitz and Leser's life table entropy was proposed to serve as a relative inequality in mortality measure. Entropy considers the variation around the age at death relative to the length of lifespan in a population, allowing comparisons across time and populations. It is used widely in period and cohort applications. Here, we propose extending this measure and present an index that incorporates the history of survival of all cohorts present at a given time, namely the cross-sectional average length of life entropy, or CAL-entropy ( H CAL ). We decompose cross-population differences of CAL-entropy into the contribution of longevity and lifespan variation, and the change of those differences across time. Our illustrations show that populations are converging regarding lifespan inequality. Lifespan variation holds a noticeable share in the CAL-entropy gap among selected European populations. Longevity held once a pronounced share in CAL-entropy differences and their change, but its influence has receded over the years. The US demonstrates a unique trend where it performs worse across time compared to the selected European populations, and lifespan variation has played a major role in this process. This study signals the importance of lifespan variation in reducing inequality in mortality among developed and longevous populations.

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the "Inequality" component), (2) the total share of deaths attributable to each cause (the "Proportion" component), or (3) the cause-specific mean age at death (the "Mean" component). This so-called Inequality-Proportion-Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, "circulatory system" and "neoplasms") do not necessarily contribute the most to overall levels of lifespan inequality. In fact, "perinatal and congenital" causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Long-term cardiovascular risks and the impact of statin treatment on socioeconomic inequalities: a microsimulation model

BACKGROUND

UK cardiovascular disease (CVD) incidence and mortality have declined in recent decades but socioeconomic inequalities persist.

AIM

To present a new CVD model, and project health outcomes and the impact of guideline-recommended statin treatment across quintiles of socioeconomic deprivation in the UK.

DESIGN AND SETTING

A lifetime microsimulation model was developed using 117 896 participants in 16 statin trials, 501 854 UK Biobank (UKB) participants, and quality-of-life data from national health surveys.

METHOD

A CVD microsimulation model was developed using risk equations for myocardial infarction, stroke, coronary revascularisation, cancer, and vascular and non-vascular death, estimated using trial data. The authors calibrated and further developed this model in the UKB cohort, including further characteristics and a diabetes risk equation, and validated the model in UKB and Whitehall II cohorts. The model was used to predict CVD incidence, life expectancy, quality-adjusted life years (QALYs), and the impact of UK guideline-recommended statin treatment across socioeconomic deprivation quintiles.

RESULTS

Age, sex, socioeconomic deprivation, smoking, hypertension, diabetes, and cardiovascular events were key CVD risk determinants. Model-predicted event rates corresponded well to observed rates across participant categories. The model projected strong gradients in remaining life expectancy, with 4-5-year (5-8 QALYs) gaps between the least and most socioeconomically deprived quintiles. Guideline-recommended statin treatment was projected to increase QALYs, with larger gains in quintiles of higher deprivation.

CONCLUSION

The study demonstrated the potential of guideline-recommended statin treatment to reduce socioeconomic inequalities. This CVD model is a novel resource for individualised long-term projections of health outcomes of CVD treatments.

Area-based social inequalities in adult mortality: construction of French deprivation-specific life tables for the period 2016-2018

Background

In order to tackle social inequalities in mortality, it is crucial to quantify them. We produced French deprivation-specific life tables for the period 2016-2018 to measure the social gradient in adult all-cause mortality.

Methods

Data from the Permanent Demographic Sample (EDP) were used to provide population and death counts by age, sex and deprivation quintile. The European Deprivation Index (EDI), applied at a sub-municipal geographical level, was used as an ecological measure of deprivation. Smoothed mortality rates were calculated using a one-dimensional Poisson counts smoothing method with P-Splines. We calculated life expectancies by age, sex and deprivation quintile as well as interquartile mortality rate ratios (MRR).

Results

At the age of 30, the difference in life expectancy between the most and least deprived groups amounted to 3.9 years in males and 2.2 years in females. In terms of relative mortality inequalities, the largest gaps between extreme deprivation groups were around age 55 for males (MRR = 2.22 [2.0; 2.46] at age 55), around age 50 in females (MRR = 1.77 [1.48; 2.1] at age 47), and there was a decrease or disappearance of the gaps in the very older adults.

Conclusions

There is a strong social gradient in all-cause mortality in France for males and females. The methodology for building these deprivation-specific life tables is reproducible and could be used to monitor its development. The tables produced should contribute to improving studies on net survival inequalities for specific diseases by taking into account the pre-existing social gradient in all-cause mortality.

Contribution of avoidable mortality to life expectancy inequalities in Wales: a decomposition by age and by cause between 2002 and 2020

OBJECTIVES

To explore the contribution of avoidable mortality to life expectancy inequalities in Wales during 2002-2020.

DESIGN

Observational study.

SETTING

Wales, 2002-20, including early data from the COVID-19 pandemic.

METHODS

We used routine statistics for 2002-2020 on population and deaths in Wales stratified by age, sex, deprivation quintile and cause of death. We estimated the contribution of avoidable causes of death and specific age-categories using the Arriaga decomposition method to highlight priorities for action.

RESULTS

Life expectancy inequalities rose 2002-20 amongst both sexes, driven by serial decreases in life expectancy amongst the most deprived quintiles. The contributions of amenable and preventable mortality to life expectancy inequalities changed relatively little between 2002 and 2020, with larger rises in non-avoidable causes. Key avoidable mortality conditions driving the life expectancy gap in the most recent period of 2018-2020 for females were circulatory disease, cancers, respiratory disease and alcohol- and drug-related deaths, and also injuries for males.

CONCLUSIONS

Life expectancy inequalities widened during 2002-20, driven by deteriorating life expectancy in the most deprived quintiles. Sustained investment in prevention post-COVID-19 is needed to address growing health inequity in Wales; there remains a role for the National Health Service in ensuring equitable healthcare access to alongside wider policies that promote equity.

Comparison of Bayesian Spatiotemporal Models for Small-Area Life Expectancy: A Simulation Study

The purpose of this study was to assess the precision, uncertainty, and normality of small-area life expectancy estimates calculated using Bayesian spatiotemporal models. We hypothesized 6 scenarios in which all 247 districts of South Korea had the same year-specific female population of 500, 1,000, 2,000, 5,000, 10,000, and 25,000 individuals during the study period (2013-2017). We generated 1,000 hypothetical data sets for each scenario and calculated district-year life expectancies. The precision and uncertainty of life expectancy estimates were compared between 2 Bayesian spatiotemporal models and the traditional method and Bayesian spatial models. We examined the normality of the life expectancy distributions generated by each method and investigated an optimal cutoff value for the comparisons. The Bayesian spatiotemporal models produced precise life expectancy estimates. However, the 95% uncertainty interval contained the true value with a probability of less than 95%. The Bayesian spatiotemporal models violated the normality assumption in scenarios with small population sizes. Therefore, life expectancy comparisons should be conducted using a cutoff value that minimizes false-positive and false-negative rates. We propose 0.8 as a cutoff value for determining the statistical significance of the difference in life expectancy.

State-Level Trends in Lifespan Variability in the United States, 1960-2019: A Research Note

State-level disparities in life expectancy are wide, persistent, and potentially growing in the United States. However, the extent to which differences in lifespan variability by state have changed over time is unclear. This research note describes trends in lifespan variability for the United States overall and by state from 1960 to 2019 using period life table data from the United States Mortality Database. Lifespan disparity at birth (e0†) decreased over time in the United States overall from 14.0 years in 1960-1964 to 12.2 in 2015-2019. Lifespan variability decreased in all states, but states differed in the level and pace with which these changes occurred. Southern states and the District of Columbia exhibited consistently higher (i.e., less equitable) levels of lifespan variability than the nation overall. Conversely, lifespan variability was lower among several states in the Northeast (e.g., Connecticut and Massachusetts), Upper Midwest (e.g., Iowa, Minnesota, and Wisconsin), and West (e.g., California, Oregon, Utah, and Washington). We observe a particularly worrisome trend of increasing lifespan variability for the United States overall and for most states from 2010-2014 to 2015-2019. Monitoring state-level trends in lifespan variability has the potential to inform policies designed to ameliorate population health disparities.

Exploring inequalities in life expectancy and lifespan variation by race/ethnicity and urbanicity in the United States: 1990 to 2019

Background/Objective

Investigating trends in life expectancy and lifespan variation can highlight disproportionate mortality burdens among population subgroups. We examined inequalities in life expectancy and lifespan variation by race/ethnicity and by urbanicity in the US from 1990 to 2019.

Methods

Using vital registration data for 322.0 million people in 3,141 counties from the National Center for Health Statistics, we obtained life expectancy at birth and lifespan variation for 16 race/ethnicity-gender-urbanicity combinations in six 5-year periods (1990-1994 to 2015-2019). Race/ethnicity was categorized as Hispanic, and non-Hispanic White, Black, and Asian/Pacific Islander. Urbanicity was categorized as metropolitan vs nonmetropolitan areas, or in six further detailed categorizations. Life expectancy and lifespan variation (coefficient of variation) were computed using life tables.

Results

In 2015-2019, residents in metropolitan areas had higher life expectancies than their nonmetropolitan counterparts (79.6 years compared to 77.0 years). The widest inequality in life expectancy occurred between Asian/Pacific Islander women and Black men, with a 17.7-year gap for residents in metropolitan areas and a 16.9-year gap for residents in nonmetropolitan areas. Nonmetropolitan areas had greater dispersion around average age at death. Black individuals had the highest lifespan variations in both metropolitan and nonmetropolitan areas. Until the mid-2010s, life expectancy increased while lifespan variation decreased; however, recent trends show stagnation in life expectancy and increases in lifespan variation. Metropolitan-nonmetropolitan inequalities in both life expectancy and lifespan variation widened over time.

Conclusion

Despite previous improvements in longevity, life expectancy is now stagnating while lifespan variation is increasing. Our results highlight that early-life deaths (i.e., young- and middle-age mortality) disproportionately affect Black individuals, who not only live the shortest lifespans but also have the most variability with respect to age at death.

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.

Why we should monitor disparities in old-age mortality with the modal age at death

Indicators based a fixed “old” age threshold have been widely used for assessing socioeconomic disparities in mortality at older ages. Interpretation of long-term trends and determinants of these indicators is challenging because mortality above a fixed age that in the past would have reflected old age deaths is today mixing premature and old-age mortality. We propose the modal (i.e., most frequent) age at death, M, an indicator increasingly recognized in aging research, but which has been infrequently used for monitoring mortality disparities at older ages. We use mortality and population exposure data by occupational class over the 1971-2017 period from Finnish register data. The modal age and life expectancy indicators are estimated from mortality rates smoothed with penalized B-splines. Over the 1971-2017 period, occupational class disparities in life expectancy at 65 and 75 widened while disparities in M remained relatively stable. The proportion of the group surviving to the modal age was constant across time and occupational class. In contrast, the proportion surviving to age 65 and 75 has roughly doubled since 1971 and showed strong occupational class differences. Increasing socioeconomic disparities in mortality based on fixed old age thresholds may be a feature of changing selection dynamics in a context of overall declining mortality. Unlike life expectancy at a selected fixed old age, M compares individuals with similar survival chances over time and across occupational classes. This property makes trends and differentials in M easier to interpret in countries where old-age survival has improved significantly.

Normalized lifespan inequality: disentangling the longevity-lifespan variability nexus

Previous studies have documented a historically strong and negative association between countries’ life expectancy (i.e., average longevity) and length-of-life inequality (i.e., variability in ages at death). The relationship between both variables might be partially explained by life expectancy increasing at a faster pace than maximal length of life, a phenomenon that mechanically compresses the age-at-death distribution and has not been taken into consideration in previous studies. In this paper, we propose a new approach to lifespan inequality measurement that accounts for the (uncertainly) bounded nature of length-of-life. Applying the new approach to the countries of the Human Mortality Database, we observe that the decline in overall lifespan variability typically associated with increases in longevity seems to stop and even reverse at higher levels of life expectancy. This suggests the emergence of worrying ethical dilemmas, whereby higher achievements in longevity would only be possible at the expense of higher lifespan variability.

On the measurement of healthy lifespan inequality

Background

Current measures to monitor population health include indicators of (i) average length-of-life (life expectancy), (ii) average length-of-life spent in good health (health expectancy), and (iii) variability in length-of-life (lifespan inequality). What is lacking is an indicator measuring the extent to which healthy lifespans are unequally distributed across individuals (the so-called ‘healthy lifespan inequality’ indicators).

Methods

We combine information on age-specific survival with the prevalence of functional limitation or disability in Spain (2014–2017) by sex and level of education to estimate age-at-disability onset distributions. Age-, sex- and education-specific prevalence rates of adult individuals’ daily activities limitations were based on the GALI index derived from Spanish National Health Surveys held in 2014 and 2017. We measured inequality using the Gini index.

Results

In contemporary Spain, education differences in health expectancy are substantial and greatly exceed differences in life expectancy. The female advantage in life expectancy disappears when considering health expectancy indicators, both overall and across education groups. The highly educated exhibit lower levels of lifespan inequality, and lifespan inequality is systematically higher among men. Our new healthy lifespan inequality indicators suggest that the variability in the ages at which physical daily activity limitations start are substantially larger than the variability in the ages at which individuals die. Healthy lifespan inequality tends to decrease with increasing educational attainment, both for women and for men. The variability in ages at which physical limitations start is slightly higher for women than for men.

Conclusions

The suggested indicators uncover new layers of health inequality that are not traceable with currently existing approaches. Low-educated individuals tend to not only die earlier and spend a shorter portion of their lives in good health than their highly educated counterparts, but also face greater variation in the eventual time of death and in the age at which they cease enjoying good health—a multiple burden of inequality that should be taken into consideration when evaluating the performance of public health systems and in the elaboration of realistic working-life extension plans and the design of equitable pension reforms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12963-021-00279-8.

Developing Dashboards to Address Children's Health Disparities in Ohio

OBJECTIVES

Social determinants of health (SDoH) can be measured at the geographic level to convey information about neighborhood deprivation. The Ohio Children's Opportunity Index (OCOI) is a composite area-level opportunity index comprised of eight health domains. Our research team has documented the design, development, and use cases of a dashboard solution to visualize OCOI.

METHODS

The OCOI is a multidomain index spanning the following eight domains: (1) family stability, (2) infant health, (3) children's health, (4) access, (5) education, (6) housing, (7) environment, and (8) criminal justice. Information on these eight domains is derived from the American Community Survey and other administrative datasets. Our team used the Tableau Desktop visualization software and applied a user-centered design approach to developing the two OCOI dashboards-main OCOI dashboard and OCOI-race dashboard. We also performed convergence analysis to visualize the census tracts where different health indicators simultaneously exist at their worst levels.

RESULTS

The OCOI dashboard has multiple, interactive components as follows: a choropleth map of Ohio displaying OCOI scores for a specific census tract, graphs presenting OCOI or domain scores to compare relative positions for tracts, and a sortable table to visualize scores for specific county and census tracts. A case study using the two dashboards for convergence analysis revealed census tracts in neighborhoods with low infant health scores and a high proportion of minority population.

CONCLUSION

The OCOI dashboards could assist health care leaders in making decisions that enhance health care delivery and policy decision-making regarding children's health particularly in areas where multiple health indicators exist at their worst levels.

From convergence to divergence: Lifespan variation in US states, 1959-2017

BACKGROUND

Large disparities in life expectancy exist across US states and the gaps have been widening in recent decades. Less is known about the lifespan variability - a measure that can provide important insights into mortality inequalities both between and within states.

METHOD

Using yearly lifetables from the United States Mortality Database, we explore geographic and temporal patterns in lifespan variation (unconditional and conditional on survival to age 10, 35 and 65) across US states between 1959 and 2017. We also examine the contribution of state differences in life expectancy to overall lifespan variation using standard decomposition techniques.

RESULTS

Despite overall convergence in lifespan variation across states over the last six decades, in more recent years there has been notable divergence. Gender-specific analyses show that lifespan variation was generally greater among males than among females; but this pattern reverses for mortality past age 65. Much of the state disparities in lifespan variation, unconditional and conditional on survival to age 10 and 35, were due to mortality differences under the age 65. Decomposition analysis shows that while within-state variability remains the primary driver of overall lifespan variation, the contribution of cross-state differences in life expectancy is growing.

CONCLUSIONS

Variation in longevity is greater within US States than between them, yet cross-states disparities in mortality are increasing. This likely reflects the long-term consequences of rising social, economic, and political stratification for health inequalities both within and across states.

Spatial distribution of neighborhood-level housing prices and its association with all-cause mortality in Seoul, Korea (2013-2018): A spatial panel data analysis

Housing prices are known to be a relevant indicator of the socioeconomic position of the neighborhood. In a society where the market system mainly drives housing prices, residents' spatial patterning is formulated according to their socioeconomic position. Dividing the 2013-2018 entire study period into three periods, we explored the spatial distribution of housing prices and all-cause mortality and their association in Seoul, the country's capital city. The government authorities' data and 2015 census data were used for the study. We mapped the spatial distribution of housing prices and all-cause mortality and investigated the changes in distribution. We conducted a pooled ordinary least square (OLS) and spatial panel regression analysis to estimate housing prices elasticity of all-cause mortality. We also explored the possible mediating role of housing prices on the educational composition's effect on all-cause mortality. We found the common trends of increasing spatial patterning of housing prices and all-cause mortality. The magnitude of spatial patterning was far greater in housing prices than all-cause mortality. A pooled OLS regression analysis found that a 1% increase in housing price was associated with a 0.11% reduction in all-cause mortality after controlling the explanatory variables. Attenuation in the regression coefficient's magnitude was found after adding the neighborhood's educational composition to the model. As a result of spatial panel analysis, we found a direction and scale similar to the housing price elasticity of all-cause mortality in the final pooled OLS model. The results suggested that spatial health inequality in Korea's urban space mainly stems from socioeconomic inequality.

What can lifespan variation reveal that life expectancy hides? Comparison of five high-income countries

OBJECTIVES

In most countries, life expectancy at birth (e0) has improved for many decades. Recently, however, progress has stalled in the UK and Canada, and reversed in the USA. Lifespan variation, a complementary measure of mortality, increased a few years before the reversal in the USA. To assess whether this measure offers additional meaningful insights, we examine what happened in four other high-income countries with differing life expectancy trends.

DESIGN

We calculated life disparity (a specific measure of lifespan variation) in five countries -- USA, UK, France, Japan and Canada -- using sex- and age specific mortality rates from the Human Mortality Database from 1975 to 2017 for ages 0--100 years. We then examined trends in age-specific mortality to identify the age groups contributing to these changes.

SETTING

USA, UK, France, Japan and Canada.

PARTICIPANTS

aggregate population data of the above nations.

MAIN OUTCOME MEASURES

Life expectancy at birth, life disparity and age-specific mortality.

RESULTS

The stalls and falls in life expectancy, for both males and females, seen in the UK, USA and Canada coincided with rising life disparity. These changes may be driven by worsening mortality in middle-age (such as at age 40). France and Japan, in contrast, continue on previous trajectories.

CONCLUSIONS

Life disparity is an additional summary measure of population health providing information beyond that signalled by life expectancy at birth alone.

A syndemic of psychiatric morbidity, substance misuse, violence, and poor physical health among young Scottish men with reduced life expectancy

Background

Scotland has the shortest life expectancy in Western Europe, driven by high rates of cancer, suicides, alcohol-related causes and drug-related poisonings. These disparities cannot be explained solely by socioeconomic deprivation. Our aim was to investigate whether a syndemic in a socioeconomically deprived area of Glasgow might account for premature mortality among men.

Methods

We analysed data from two cross-sectional population surveys: a national sample of 1916 British men and another of 765 men in Glasgow East. The survey included men aged 18–34, and was undertaken in 2011 to study correlates of violence. Questionnaires covered current physical health, psychiatric symptoms, substance misuse, and crime and violence. Syndemic components were identified using confirmatory factor analysis. Associations and synergistic interactions between these variables and health status were estimated using logistic regression.

Results

An aggregation of multiple health conditions and health-related behaviours was found in Glasgow East. A syndemic model of joint effects, adducing a four-component latent variable (violence, substance dependence, psychiatric morbidity and a diathesis of biological/behavioural risk) showed synergy between components and explained persistent disparities in poor physical health/chronic health conditions. Effect modification was found between the general syndemic factor and contextual variables at individual and social environmental level according to location.

Conclusions

Syndemic effects from synergistic interactions were confirmed between psychiatric morbidity, substance misuse, violence, and biological/behavioural risk for physical health. A hypothetical model was developed to explain how the syndemic leads to potentially life-threatening risks to young men, both currently and as precursors of physical health conditions which may shorten their lives in the future.

•

Scotland has the shortest life expectancy in Western Europe, especially among men in areas of Glasgow. This has not responded to Public Health interventions.

•

A syndemic was identified among young men with synergism between violence, substance misuse, biological/behavioural physical health risks, and psychiatric morbidity.

•

Synergistic interactions between components of the syndemic may result in precursors of multiple physical health conditions which will shorten men's lives in the future.

Declining regional disparities in mortality in the context of persisting large inequalities in economic conditions: the case of Germany

BACKGROUND

Subnational regional mortality inequalities are large and appear to be mostly increasing within industrialized countries, although comparative studies across high-income countries are scarce. Germany is an important country to examine because it continues to experience considerable economic disparities between its federal states, in part resulting from its former division.

METHODS

We analyse state-level mortality in Germany utilizing data from a newly constructed regional database based on the methodology of the Human Mortality Database. We compare time trends (1991-2015) in the German state-level standard deviation in life expectancy to that of other large, wealthy countries and examine the association between mortality and economic inequalities at the regional level. Finally, using contour-decomposition methods, we investigate the degree to which age patterns of mortality are converging across German federal states.

RESULTS

Regional inequalities in life expectancy in Germany are comparatively low internationally, particularly among women, despite high state-level inequalities in economic conditions. These low regional mortality inequalities emerged 5-10 years after reunification. Mortality is converging over most ages between the longest- and shortest-living German state populations and across the former East-West political border, with the exception of an emerging East-West divergence in mortality among working-aged men.

CONCLUSIONS

The German example shows that large regional economic inequalities are not necessarily paralleled with large regional mortality disparities. Future research should investigate the factors that fostered the emergence of this unusual pattern in Germany.

Life expectancy inequalities in Wales before COVID-19: an exploration of current contributions by age and cause of death and changes between 2002 and 2018

OBJECTIVES

The COVID-19 pandemic in Wales and the UK has highlighted significant and historic inequalities in health between social groups. To better understand the composition of these inequalities and inform planning after the pandemic, we undertook a decomposition of life expectancy inequalities between the most and least deprived quintiles for men and women by age and cause of death and explored trends between 2002 and 2018.

STUDY DESIGN

Statistical decomposition of life expectancy inequalities by age and cause of death using routine population mortality datasets.

METHODS

We used routine statistics from the Office for National Statistics for the period 2002-2018 on population and deaths in Wales stratified by age, gender, Welsh Index of Multiple Deprivation (WIMD) 2019 quintile and cause of death, categorised by International Classification of Disease, version 10, code into 15 categories of public health relevance. We aggregated data to 3-year rolling figures to account for low numbers of events in some groups annually. Next, we estimated life expectancy at birth by quintile, gender and period using life table methods. Lastly, we performed a decomposition analysis using the Arriaga method to identify the specific disease categories and ages at which excess deaths occur in more disadvantaged areas to highlight potential areas for action.

RESULTS

Life expectancy inequalities between the most and least WIMD quintiles rose for both genders between 2002 and 2018: from 4.69 to 6.02 years for women (an increase of 1.33 years) and from 6.34 to 7.42 years for men (an increase of 1.08 years). Exploratory analysis of these trends suggested that the following were most influential for women: respiratory disease (1.50 years), cancers (1.36 years), circulatory disease (1.35 years) and digestive disease (0.51 years). For men, the gap was driven by circulatory disease (2.01 years), cancers (1.39 years), respiratory disease (1.25 years), digestive disease (0.79 years), drug- and alcohol-related conditions (0.54 years) and external causes (0.54 years). Contributions for women from respiratory disease, cancers, dementia and drug- and alcohol-related conditions appeared to be increasing, while among men, there were rising contributions from respiratory, digestive and circulatory disease.

CONCLUSIONS

Life expectancy inequalities in Wales remain wide and have been increasing, particularly among women, with indications of worsening trends since 2010 following the introduction of fiscal austerity. As agencies recover from the pandemic, these findings should be considered alongside any resumption of services in Wales or future health and public policy.

Spatio-temporal model to estimate life expectancy and to detect unusual trends at the local authority level in England

OBJECTIVES

To estimate life expectancy at the local authority level and detect those areas that have a substantially low life expectancy after accounting for deprivation.

DESIGN

We used registration data from the Office for National Statistics on mortality and population in England, by local authority, age group and socioeconomic deprivation decile, for both men and women over the period 2001-2018. We used a statistical model within the Bayesian framework to produce robust mortality rates, which were then transformed to life expectancy estimates. A rule based on exceedance probabilities was used to detect local authorities characterised by a low life expectancy among areas with a similar deprivation level from 2012 onwards.

RESULTS

We confirmed previous findings showing differences in the life expectancy gap between the most and least deprived areas from 2012 to 2018. We found variations in life expectancy trends across local authorities, and we detected a number of those with a low life expectancy when compared with others of a similar deprivation level.

CONCLUSIONS

There are factors other than deprivation that are responsible for low life expectancy in certain local authorities. Further investigation on the detected areas can help understand better the stalling of life expectancy which was observed from 2012 onwards and plan efficient public health policies.

Influence of deprivation and rurality on patient-reported outcomes of men living with and beyond prostate cancer diagnosis in the UK: A population-based study

BACKGROUND

In the UK, inequalities exist in prostate cancer incidence, survival and treatment by area deprivation and rurality. This work aimed to identify variation in patient-reported outcomes of men with prostate cancer by area type.

METHODS

A population-based survey of men 18-42 months after prostate cancer diagnosis (N = 35608) measured self-assessed health (SAH) using the EQ-5D and five functional domains using the Expanded Prostate Cancer Index Composite (EPIC-26).

RESULTS

Mean SAH was higher for men in least deprived areas compared to most deprived (difference 6.3 (95 %CI 5.6-7.2)). SAH scores were lower for men in most urban areas compared to most rural (difference 2.4 (95 %CI 1.8-3.0)). Equivalent estimates in the general population reported a 13 point difference by deprivation and a 4 point difference by rurality. For each EPIC-26 domain, functional outcomes were better for men in the least deprived areas, with clinically meaningful differences observed for urinary incontinence and hormonal function. There were no clinically meaningful differences in EPIC-26 outcomes by rurality with less than a three point difference in scores for each domain between urban and rural areas.

CONCLUSION

In men 18-42 months post diagnosis of prostate cancer in the UK, impacts of area deprivation and rurality on self-assessed health related quality of life were not greater than would be expected in the general population. However, clinically meaningful differences were identified for some prostate functional outcomes (urinary and hormonal function) by deprivation. No impact by rurality of residence was identified.