Socioeconomic Differences In Mortality Research Articles

Modelling mortality by cause of death and socio-economic stratification: an analysis of mortality differentials in England

Abstract It is well known that more advantaged socio-economic groups – whether defined by educational attainment, occupation, income or area deprivation – have lower mortality rates and longer lives than less advantaged socio-economic groups. In many cases, affluent subpopulations also experience faster rates of improvement in mortality. Socio-economic differentials in mortality and longevity pose important challenges when designing public policies for tackling social inequalities; and for managing longevity risk in pension funds and annuity portfolios. The successful addressing of these social and financial challenges requires the best possible understanding of the drivers of socio-economic mortality differentials. A key step in achieving this understanding is to investigate how mortality trends for leading causes of death differ between socio-economic groups. Accordingly, the main purpose of this paper is to propose modelling techniques that enable the modelling and projection of mortality trends by cause of death and socio-economic stratification. We first extend the Lee-Carter model to allow for the consideration of coding changes in cause-specific mortality data. We then embed this model into a multiple population setting to allow for the quantification of socio-economic differences in cause-specific mortality. Using England mortality data for socio-economic subpopulations defined using the Index of Multiple Deprivation (IMD), we show that this modelling approach can be satisfactorily employed both in the assessment of the magnitude of historical mortality differentials for the main causes of death and in the projection of the possible future evolution of these differentials.

Comparing SEER and NCDB: a case study using colorectal cancer.

Nationwide datasets are frequently used to examine cancer trends and outcomes in the U.S. Understanding the strengths and limitations of the commonly used Surveillance, Epidemiology, and End Results (SEER) Program and the National Cancer Database (NCDB) is important when designing studies and interpreting results. We used colorectal cancer (CRC) as a case study to compare information available. We identified 575,128 (SEER) and 1,578,046 (NCDB) adults diagnosed with CRC between 2004 and 2021. The distribution of age, tumor location, stage, and treatment did not meaningfully differ between SEER and NCDB. SEER represents racially and ethnically diverse populations, including a higher proportion of Hispanic (11.7% vs 5.8%) and Asian/Pacific Islander (8.6% vs 3.3%) persons. SEER includes more information on area-level characteristics, such as county-level measures of poverty, unemployment, and migration and census tract-level measures of socioeconomic status. Age-adjusted incidence, mortality rates, and cause-specific survival are only available in SEER, facilitating detailed analyses of racial, ethnic, and socioeconomic differences in cancer incidence and mortality. NCDB provides information on tumor characteristics and treatment not available in SEER, including microsatellite instability, KRAS mutation, palliative treatment, unplanned readmissions, and 30-day mortality after surgery, facilitating analyses of treatment effectiveness and outcomes. Five-year overall survival was similar in SEER (55.6%) vs NCDB (57.5%).

From test to rest: evaluating socioeconomic differences along the COVID-19 care pathway in the Netherlands

IntroductionThe COVID-19 pandemic exacerbated healthcare needs and caused excess mortality, especially among lower socioeconomic groups. This study describes the emergence of socioeconomic differences along the COVID-19 pathway of testing, healthcare use and mortality in the Netherlands.MethodologyThis retrospective observational Dutch population-based study combined individual-level registry data from June 2020 to December 2020 on personal socioeconomic characteristics, COVID-19 administered tests, test results, general practitioner (GP) consultations, hospital admissions, Intensive Care Unit (ICU) admissions and mortality. For each outcome measure, relative differences between income groups were estimated using log-link binomial regression models. Furthermore, regression models explained socioeconomic differences in COVID-19 mortality by differences in ICU/hospital admissions, test administration and test results.ResultsAmong the Dutch population, the lowest income group had a lower test probability (RR = 0.61) and lower risk of testing positive (RR = 0.77) compared to the highest income group. However, among individuals with at least one administered COVID-19 test, the lowest income group had a higher risk of testing positive (RR = 1.40). The likelihood of hospital admissions and ICU admissions were higher for low income groups (RR = 2.11 and RR = 2.46, respectively). The lowest income group had an almost four times higher risk of dying from COVID-19 (RR = 3.85), which could partly be explained by a higher risk of hospitalization and ICU admission, rather than differences in test administration or result.DiscussionOur findings indicated that socioeconomic differences became more pronounced at each step of the care pathway, culminating to a large gap in mortality. This underlines the need for enhancing social security and well-being policies and incorporation of health equity in pandemic preparedness plans.

Has it always paid to be rich? Income and cause-specific mortality in southern Sweden 1905–2014

Socio-economic differences in mortality are among the most pervasive characteristics of Western societies. While the mortality gradient by income is well established for the period after 1970, knowledge about the origins of this gradient is still rudimentary. We analyse the association between income and cause-specific adult mortality during the period 1905–2014 in an area of southern Sweden, using competing-risk hazard models with individual-level longitudinal data for over 2.2 million person-years and over 35,000 deaths. We find that the present-day income gradient in adult mortality emerged only in the period after the Second World War and did so for the leading causes of death and for men and women largely simultaneously.

Socioeconomic mortality differences during the Great Influenza in Spain

Despite being one of the deadliest viruses in history, there is limited information on the socioeconomic factors that affected mortality rates during the Great Influenza Pandemic. In this study, we use occupation-province level data to investigate the relationship between influenza excess mortality rates and occupation-related status in Spain. We obtain three main results. Firstly, individuals in low-income occupations experienced the highest excess mortality, pointing to a notable income gradient. Secondly, professions that involved more social interaction were associated with a higher excess of mortality, regardless of income. Finally, we observe a substantial rural mortality penalty, even after controlling for income-related occupational groups. Based on this evidence, it seems that the high number of deaths was caused by not self-isolating. Some individuals did not quarantine themselves because they could not afford to miss work. In rural areas, home confinement was likely more limited because their inhabitants did not have immediate access to information about the pandemic or fully understand its impact due to their limited experience handling influenza outbreaks.

Old-age mortality and social class in northern Norway in the first half of the twentieth century

ABSTRACT The number of studies on social inequality in mortality in Norway before 1960 is limited and they often focus on early life outcomes. Little is known about socioeconomic differences in old-age mortality before the emergence of the welfare state. Linked census and church records from the Historical Population Register of Norway were used to study a sample of 10,457 men and women born 1841–1870 who lived in Troms, a province in northern Norway, in the early twentieth century. We analysed the association between social class, measured in adulthood, and mortality at age 60 and older using Cox proportional hazards models. The results do not indicate a clear social gradient in mortality. Differences between social classes varied in the magnitude and direction of effects, depending on gender and place of residence. For women, the association between social class and mortality was weaker overall. Only farming was significantly associated with decreased mortality risk compared to the group of lower-skilled and unskilled workers. Differences were more pronounced among men, with higher mortality for non-manual classes in towns, and lower mortality for skilled workers and farmers in rural areas. The advantage for farmers was amplified in combination with manual or non-manual work.

Factors in the differentiation of regional mortality in developed countries

The aim of this article is to discuss factors that influence the distribution and differences in mortality between both regions and subpopulations in developed countries. The article provides an outline of basic theories that attempt to explain socioeconomic differences in mortality. A range of socioeconomic factors is analysed from both the micro-level and macro-level perspectives. Based on the study of the relevant literature, it was determined that more privileged groups enjoy better health and longer lives. A strong association between socioeconomic factors and total mortality and mortality by the cause of death was revealed at both the individual and aggregated levels. The relationship between socioeconomic variables and health status and mortality is explained via various mechanisms through which this association arises. Socioeconomic variables that act to influence health status and mortality have been shown to be strongly interrelated. These factors, in turn, impact the lifestyle and psychological state of individuals. Existing socioeconomic health and mortality determinants represent one of the main problems and challenges for the public health sectors in both more and less developed countries.

Socioeconomic differences in COVID-19 infection, hospitalisation and mortality in urban areas in a region in the South of Europe

BackgroundTo analyse differences in confirmed cases, hospitalisations and deaths due to COVID-19 related to census section socioeconomic variables. MethodsEcological study in the 12 largest municipalities in Andalusia (Spain) during the first three epidemic waves of the COVID-19 (02/26/20—03/31/21), covering 2,246 census sections (unit of analysis) and 3,027,000 inhabitants. Incidence was calculated, standardised by age and sex, for infection, hospitalisation and deaths based on average gross income per household (AGI) for the census tracts in each urban area. Association studied using a Poisson Bayesian regression model with random effects for spatial smoothing.ResultsThere were 140,743 cases of COVID-19, of which 12,585 were hospitalised and 2,255 died. 95.2% of cases were attributed to the second and third waves, which were jointly analysed. We observed a protective effect of income for infection in 3/12 cities. Almeria had the largest protective effect (smoothed relative risk (SRR) = 0.84 (0.75–0.94 CI 95%). This relationship reappeared with greater magnitude in 10/12 cities for hospitalisation, lowest risk in Algeciras SRR = 0.41 (0.29–0.56). The pattern was repeated for deaths in all urban areas and reached statistical significance in 8 cities. Lowest risk in Dos Hermanas SRR = 0.35 (0.15–0.81).ConclusionsIncome inequalities by geographical area were found in the incidence of COVID-19. The strengths of the association increased when analysing the severe outcomes of hospitalisations and, above all, deaths.

Income differences in partial life expectancy between ages 35 and 64 from 1988 to 2017: the contribution of living arrangements.

Socioeconomic differences in mortality among the working-age population have increased in several high-income countries. The aim of this study was to assess whether changes in the living arrangement composition of income groups have contributed to changing income differences in life expectancy during the past 30 years. We used Finnish register data covering the total population to calculate partial life expectancies between ages 35 and 64 by income quartile in 1988-2017. The contribution of living arrangements to these differences was assessed by direct standardization. Decomposition methods were used to determine the extent of life expectancy differences due to external (accidental, violent and alcohol-related) causes of death. The life expectancy gap between the highest and lowest income quartile increased until 2003-07, but decreased thereafter. The contribution of living arrangements to these differences remained mostly stable: 36-39% among men and 15-23% among women. Those living without children consistently showed the greatest life expectancy differences by income. External causes of death significantly contributed to income differences in life expectancy. The living arrangement composition of income groups explained part of the differences in life expectancy, but not their changes. Our results on the contribution of external causes of death imply that both the persistent income gradient in mortality as well as the mortality disparities by living arrangements are at least partially related to similar selection or causal mechanisms.

Geographic and socioeconomic differences in heat-related mortality among the Dutch population: a time series analysis

ObjectivesThis study was conducted to examine modification in heat-related mortality in the Netherlands by sociodemographic and geographical factors including socioeconomic position and population density (PD).DesignThis observational study applied time series...

Unequal excess mortality during the Spanish Flu pandemic in the Netherlands

A century after the Spanish Flu, the COVID-19 pandemic has brought renewed attention to socioeconomic and occupational differences in mortality in the earlier pandemic. The magnitude of these differences and the pathways between occupation and increased mortality remain unclear, however. In this paper, we explore the relation between occupational characteristics and excess mortality among men during the Spanish Flu pandemic in the Netherlands. By creating a new occupational coding for exposure to disease at work, we separate social status and occupational conditions for viral transmission. We use a new data set based on men’s death certificates to calculate excess mortality rates by region, age group, and occupational group. Using OLS regression models, we estimate whether social position, regular interaction in the workplace, and working in an enclosed space affected excess mortality among men in the Netherlands in the autumn of 1918. We find some evidence that men with occupations that featured high levels of social contact had higher mortality in this period. Above all, however, we find a strong socioeconomic gradient to excess mortality among men during the Spanish Flu pandemic, even after accounting for exposure in the workplace.

Socioeconomic differentials in mortality: implications on index-based longevity hedges

In this paper, we address the mortality modeling needs for pension plan sponsors who wish to use index-based solutions to mitigate their longevity risk exposures. Specifically, we propose the three-way Li-Lee (TWLL) model, which enforces a certain extent of coherence between the population to which the index-based hedging instrument is linked and the population of pension plan members, and at the same time incorporates the empirical fact that mortality improvement rates of different socioeconomic subgroups in the pension plan are persistently different. We further develop a delta longevity hedging strategy that is compatible with the TWLL model. With the aid of real mortality data, we demonstrate that if persistent socioeconomic differentials in mortality improvement rates exist but are not considered in an index-based longevity hedge, the performance of the hedge could be compromised, and the extent of underperformance would depend on the distributions of pension plan members and pension amounts across different socioeconomic subgroups. This problem can be alleviated if the longevity hedge is calibrated on the basis of the TWLL model.

Educational inequalities in epilepsy mortality in the Baltic countries and Finland in 2000\u20132015

Little is known about socioeconomic differences in epilepsy mortality. This study examined educational inequalities in epilepsy mortality in the general population in the Baltic countries and Finland in 2000–2015. Education-specific mortality estimates for individuals aged 30–74 in Estonia, Latvia and Lithuania were obtained from census-linked mortality datasets while data for Finland came from the register-based population and death data file of Statistics Finland. Trends and educational inequalities in epilepsy mortality were assessed using age-standardised mortality rates (ASMRs) per 100,000 person years and age-adjusted mortality rate ratios (RRs) calculated using Poisson regression. ASMRs were higher in men than women in all countries. ASMRs reduced in 2000–2015 among all men and women except for Finnish women. Among men, an inverse educational gradient in epilepsy mortality in 2000–2007 widened in 2008–2015 with ASMRs falling among high and mid educated men in all countries but increasing among low educated men in three countries. An inverse educational gradient in female mortality remained in all countries throughout 2000–2015. Although epilepsy mortality fell in the Baltic countries and Finland (men only) in 2000–2015, this masked a clear inverse educational gradient in mortality that became steeper across the period.

Mortality by socio-economic class and its impact on the retirement schemes: how to render the systems fairer?

Many OECD countries have addressed the issue of increased longevity by mainly increasing the retirement age. However, this kind of reforms may lead to substantial transfers from those with shorter lifespans to those that will live longer than the average, as they do not necessarily take into account the socio-economic differences in mortality. The contribution of our paper is therefore twofold. Firstly, we illustrate how both a Defined Benefit and a Notional Defined Contribution pay-as-you-go scheme can put the lower social economic classes at a disadvantage, when compared to the actuarially fair pensions. In contrast to that, higher classes experience a gain. This is due to the fact that mortality rates per socio-economic class are not considered by either scheme. Consequently, we propose a model that determines the parameters for each scheme and class which would render the pensions fairer even when no socio-economic mortality differences are considered.

Changes in life expectancy and lifespan variability by income quartiles in four Nordic countries: a study based on nationwide register data

ObjectivesLevels, trends or changes in socioeconomic mortality differentials are typically described in terms of means, for example, life expectancies, but studies have suggested that there also are systematic social disparities...

Temporal trends and socioeconomic differences in treatment and mortality following a diagnosis of aortic stenosis

AimsThis study aims at determining the temporal trends and the socioeconomic differences in treatment and mortality following a diagnosis of aortic stenosis. Methods and resultsA total of 45,026 patients with a first-time diagnosis of aortic stenosis were identified in the Danish National Patient Registry in the period 2000–17. The risk of AVR within the first year after diagnosis decreased (OR = 1.84 in 2000–02 compared to 2015–16) and the risk was lower in the low-level educational group (OR = 0.85) and in the medium-level group (OR = 0.94) compared to high-level education. The risk of death after AVR within the first year decreased (OR = 2.25 in 2000–02 compared to 2015–16) and the risk was higher in the low-level educational group (OR = 1.32) and in the medium-level group (OR = 1.28) compared to high-level education. The risk of death within the first year after diagnosis, for those patients who did not get an AVR during the follow-up, decreased (OR = 3.08 in 2000–02 compared to 2015–16) and the risk was higher in the low-level educational group (OR = 1.21) and in the medium-level group (OR = 1.10) compared to high-level education. ConclusionSince 2000 there has been a decrease in both AVR treatment rate, mortality rate after AVR and mortality rate in patients not receiving AVR. For patients with lower-level education there is lower AVR treatment rate, higher mortality rate after AVR and higher mortality rate in patients not receiving AVR.

Foreword

In 2018, Janet Currie visited the Institute for Fiscal Studies and delivered its Annual Lecture.11 Watch Janet's lecture here: https://www.ifs.org.uk/publications/13452. The lecture focused on Janet's latest research work, investigating socio-economic differences in health and mortality, and the extent to which access to health care early in life matters for mortality and other health outcomes in the short and longer term, as children grow up and become adults. In her lecture, Janet compares inequality in mortality in the US, Canada and France, as well as across states in the US, to investigate the value of publicly provided health insurance for children in tackling inequalities in health outcomes and in increasing health outcomes for all. Her work clearly demonstrates the power and value of looking across countries to understand trends in inequality and the role of institutions in shaping them. Following her fascinating and inspiring lecture, we joined forces with Sonya Krutikova and invited Janet to collaborate with us in extending her agenda to a wider group of countries and produce a special issue of Fiscal Studies, showing how inequalities in mortality changed in these countries, which trends and patterns were common and where they differed. We were delighted that Janet was just as excited to embark on this project. Papers were commissioned from research teams working on related issues in North and South, West and East European countries, a combination that we felt would extend the existing analysis of US, Canada and France to a richer and wider variety of contexts in the developed world. We were also incredibly fortunate that the group of lead researchers behind the comparative project, including James Banks, Kjell Salvanes and Hannes Schwandt, joined Janet and Sonya as guest editors for this special issue. This issue contains an introductory piece from the guest editors, a three-country paper by Janet and co-authors that updates her annual lecture, and eight single country papers from different research teams across Europe. The resulting issue makes a terrific contribution to the understanding of how inequalities in health and income have evolved together over the last three decades, demonstrating the diversity of experiences across countries and relating these differences to the historical and institutional features of each country. The Editors of Fiscal Studies,

Measurement error as an explanation for the alcohol harm paradox: analysis of eight cohort studies.

Despite reporting lower levels of alcohol consumption, people with lower socio-economic status (SES) experience greater alcohol-related harm. Whether differential biases in the measurement of alcohol use could explain this apparent paradox is unknown. Using alcohol biomarkers to account for measurement error, we examined whether differential exposure to alcohol could explain the socio-economic differences in alcohol mortality. Participants from eight representative health surveys (n = 52164, mean age 47.7 years) were linked to mortality data and followed up until December 2016. The primary outcome was alcohol-attributable mortality. We used income and education as proxies for SES. Exposures include self-reported alcohol use and four alcohol biomarkers [serum gamma-glutamyl transferase (available in all surveys), carbohydrate-deficient transferrin, alanine aminotransferase and aspartate aminotransferase (available in subsamples)]. We used shared frailty Cox proportional hazards to account for survey heterogeneity. During a mean follow-up of 20.3 years, totalling 1 056 844 person-years, there were 828 alcohol-attributable deaths. Lower SES was associated with higher alcohol mortality despite reporting lower alcohol use. Alcohol biomarkers were associated with alcohol mortality and improved the predictive ability when used in conjunction with self-reported alcohol use. Alcohol biomarkers explained a very small fraction of the socio-economic differences in alcohol mortality, since hazard ratios either slightly attenuated (percent attenuation range 1.0-12.1%) or increased. Using alcohol biomarkers in addition to self-reported alcohol use did not explain the socio-economic differences in alcohol mortality. Differential bias in the measurement of alcohol use is not a likely explanation for the alcohol-harm paradox.

The effects of socioeconomic conditions on old-age mortality within shared disability pathways.

ObjectiveHow disability manifests itself in an individual is a highly complex process influenced by a wide range of individual and environmental factors. Its complexity makes the search for generalizable characteristics of the disablement process a challenging task. Consequentially, little is known about how the effect on other health outcomes such as life expectancy are modified after the onset of chronic ailments. In this paper we posit an alternative approach to generalize health trajectories of older people with disability and then analyze how socioeconomic conditions affect the longevity within these trajectory groups.MethodsIndividual level information about the first three successive onsets of chronic disability after age 50 is transformed into state-sequences. We extract trajectory groups based on onset time and the time spent in a certain state. Mortality hazards are then estimated with a Gompertz proportional hazards model to compare effects of different socioeconomic measures within the trajectory groups.ResultsThree distinct trajectory groups are identified, the mild (1), the early severe (2), and late severe (3) pathway. Estimates of the mortality analysis suggest that social inequalities in longevity are less pronounced after onset of old-age disability. We found a consistent survival prolonging effect for individuals who engage in daily activities (such as meeting with friends, walking) that ranged between 33.2% and 77.3%. The importance of other variables varies between trajectory groups.DiscussionThis study shows how health trajectories of individuals with disability can be generalized when information on the onset and severity of single conditions is available. Such an approach may help us to better predict health and care expenditures and help families and individuals with their personal care planning. The findings from the subsequent survival analysis suggest a substantial reduction of socioeconomic mortality differences after onset of old-age disability, which appears to be independent of its nature.

Midlife socioeconomic position and old-age dementia mortality: a large prospective register-based study from Finland

ObjectivesTo assess the association between multiple indicators of socioeconomic position and dementia-related death, and to estimate the contribution of dementia to socioeconomic differences in overall mortality at older ages.DesignProspective population-based...