Socioeconomic status, life expectancy and mortality in a universal healthcare setting: An individual-level analysis of >6 million Catalan residents

The Dynamic Nature of the Socioeconomic Determinants of Cardiovascular Health: A Narrative Review

Despite decades of social epidemiologic research, health inequities remain pervasive and ubiquitous in Canada and elsewhere. One reason may be our use of socioeconomic measurement, which has often relied on single point-in-time exposures. To explore the extent to which researchers have incorporated dynamic socioeconomic measurement into cardiovascular health outcome evaluations, we performed a narrative review. We estimated the prevalence of socioeconomic longitudinal cardiovascular research studies that identified socioeconomic exposures at 2 or more points in time between the years of 2019 and 2023. We defined cardiovascular outcome studies as those that examined coronary artery disease, myocardial infarction, acute coronary syndrome, stroke, heart failure, cardiac arrhythmias, cardiac death, cardiometabolic factors, transient ischemic attacks, peripheral artery disease, or hypertension. Socioeconomic exposures included individual income, neighbourhood income, intergenerational social mobility, education, occupation, insurance status, and economic security. Seven percent of socioeconomic cardiovascular outcome studies have measured socioeconomic status at 2 or more points in time throughout the follow-up period, hypothesized mechanisms by which dynamic socioeconomic measures affected outcome focused on social mobility, accumulation, and critical period theories. Insights, implications, and future directions are discussed, in which we highlight ways in which postal code data can be better used methodologically as a dynamic socioeconomic measure. Future research must incorporate dynamic socioeconomic measurement to better inform root causes, interventions, and health-system designs if health equity is to be improved.

Incidence of Perinatal Post-Traumatic Stress Disorder in Catalonia: An Observational Study of Protective and Risk Factors

Pregnancy and childbirth have a great impact on women's lives; traumatic perinatal experiences can adversely affect mental health. The present study analyzes the incidence of perinatal post-traumatic stress disorder (PTSD) in Catalonia in 2021 from data obtained from the Registry of Morbidity and Use of Health Resources of Catalonia (MUSSCAT). The incidence of perinatal PTSD (1.87%) was lower than in comparable studies, suggesting underdiagnosis. Poisson regression adjusting for age, income, gestational weeks at delivery, type of delivery, and parity highlighted the influence of sociodemographics, and characteristics of the pregnancy and delivery on the risk of developing perinatal PTSD. These findings underline the need for further research on the risk factors identified and for the early detection and effective management of PTSD in the perinatal setting.

Healthcare risk stratification model for emergency departments based on drugs, income and comorbidities: the DICER-score

BACKGROUND

During the last decade, the progressive increase in age and associated chronic comorbidities and polypharmacy. However, assessments of the risk of emergency department (ED) revisiting published to date often neglect patients' pharmacotherapy plans, thus overseeing the Drug-related problems (DRP) risks associated with the therapy burden. The aim of this study is to develop a predictive model for ED revisit, hospital admission, and mortality based on patient's characteristics and pharmacotherapy.

METHODS

Retrospective cohort study including adult patients visited in the ED (triage 1, 2, or 3) of multiple hospitals in Catalonia (Spain) during 2019. The primary endpoint was a composite of ED visits, hospital admission, or mortality 30 days after ED discharge. The study population was randomly split into a model development (60%) and validation (40%) datasets. The model included age, sex, income level, comorbidity burden, measured with the Adjusted Morbidity Groups (GMA), and number of medications. Forty-four medication groups, associated with medication-related health problems, were assessed using ATC codes. To assess the performance of the different variables, logistic regression was used to build multivariate models for ED revisits. The models were created using a "stepwise-forward" approach based on the Bayesian Information Criterion (BIC). Area under the curve of the receiving operating characteristics (AUCROC) curve for the primary endpoint was calculated.

RESULTS

851.649 patients were included; 134.560 (15.8%) revisited the ED within 30 days from discharge, 15.2% were hospitalized and 9.1% died within 30 days from discharge. Four factors (sex, age, GMA, and income level) and 30 ATC groups were identified as risk factors and combined into a final score. The model showed an AUCROC values of 0.720 (95%CI:0.718-0.721) in the development cohort and 0.719 (95%CI.0.717-0.721) in the validation cohort. Three risk categories were generated, with the following scores and estimated risks: low risk: 18.3%; intermediate risk: 40.0%; and high risk: 62.6%.

CONCLUSION

The DICER score allows identifying patients at high risk for ED revisit within 30 days based on sociodemographic, clinical, and pharmacotherapeutic characteristics, being a valuable tool to prioritize interventions on discharge.

Economic impact of inflammatory bowel disease in Catalonia: a population-based analysis

Background

Inflammatory bowel disease (IBD) has a major economic impact on healthcare costs.

Objectives

The aim of this study was to evaluate the current healthcare expenditure associated with IBD in a population-wide study in Catalonia.

Design

Retrospective observational study.

Methods

All patients with IBD included in the Catalan Health Surveillance System (CHSS) were considered eligible. The CHSS compiles data on more than 7 million individuals in 2020 (34,823 with IBD). Data on the use of healthcare resources and its economic impact were extracted applying the International Classification of Diseases, 10th revision, Clinical Modification codes (ICD-10-CM codes). Health expenditure, comorbidities, and hospitalization were calculated according to the standard costs of each service provided by the Department of Health of the Catalan government. The data on the IBD population were compared with non-IBD population adjusted for age, sex, and income level. IBD costs were recorded separately for Crohn's disease (CD) and ulcerative colitis (UC).

Results

Prevalence of comorbidities was higher in patients with IBD than in those without. The risk of hospitalization was twice as high in the IBD population. The overall healthcare expenditure on IBD patients amounted to 164M€. The pharmacy cost represents the 60%. The average annual per capita expenditure on IBD patients was more than 3.4-fold higher (IBD 4200€, non-IBD 1200€). Average costs of UC were 3400€ and 5700€ for CD.

Conclusion

The risk of comorbidities was twice as high in patients with IBD and their use of healthcare resources was also higher than that of their non-IBD counterparts. Per capita healthcare expenditure was approximately 3.4 times higher in the population with IBD.

Trial registration

The study was not previously registered.

A Scoping Review of Possible Solutions for Decreasing Socioeconomic Inequalities in Type 2 Diabetes Mellitus

Background

As socioeconomic inequalities are key factors in access and utilization of type 2 diabetes (T2D) services, the purpose of this scoping review was to identify solutions for decreasing socioeconomic inequalities in T2D.

Methods

A scoping review of scientific articles from 2000 and later was conducted using PubMed, Web of Science (WOS), Scopus, Embase, and ProQuest databases. Using the Arksey and O'Malley framework for scoping review, articles were extracted, meticulously read, and thematically analyzed.

Results

A total of 7204 articles were identified from the reviewed databases. After removing duplicate and nonrelevant articles, 117 articles were finally included and analyzed. A number of solutions and passways were extracted from the final articles. Solutions for decreasing socioeconomic inequalities in T2D were categorized into 12 main solutions and 63 passways.

Conclusions

Applying identified solutions in diabetes policies and interventions would be recommended for decreasing socioeconomic inequalities in T2D. Also, the passways could be addressed as entry points to help better implementation of diabetic policies.

Population-based evaluation of the impact of socioeconomic status on clinical outcomes in patients with heart failure in integrated care settings

INTRODUCTION AND OBJECTIVES

Low socioeconomic status (SES) is associated with poor outcomes in patients with heart failure (HF). We aimed to examine the influence of SES on health outcomes after a quality of care improvement intervention for the management of HF integrating hospital and primary care resources in a health care area of 209 255 inhabitants.

METHODS

We conducted a population-based pragmatic evaluation of the implementation of an integrated HF program by conducting a natural experiment using health care data. We included all individuals consecutively admitted to hospital with at least one ICD-9-CM code for HF as the primary diagnosis and discharged alive in Catalonia between January 1, 2015 and December 31, 2019. We compared outcomes between patients exposed to the new HF program and those in the remaining health care areas, globally and stratified by SES.

RESULTS

A total of 77 554 patients were included in the study. Death occurred in 37 469 (48.3%), clinically-related hospitalization in 41 709 (53.8%) and HF readmission in 29 755 (38.4%). On multivariate analysis, low or very low SES was associated with an increased risk of all-cause death and clinically-related hospitalization (all Ps <.05). The multivariate models showed a significant reduction in the risk of all-cause death (HR, 0.812; 95%CI, 0.723-0.912), clinically-related hospitalization (HR, 0.886; 95%CI, 0.805-0.976) and HF hospitalization (HR, 0.838; 95%CI, 0.745-0.944) in patients exposed to the new HF program compared with patients exposed to the remaining health care areas and this effect was independent of SES.

CONCLUSIONS

An intensive transitional HF management program improved clinical outcomes, both overall and across SES strata.

Clinical characterization of patients with anal fistula during follow-up of anorectal abscess: a large population-based study

PURPOSE

Approximately 15-50% of patients with an anorectal abscess will develop an anal fistula, but the true incidence of this entity is currently unknown. The aim of the study was to determine the incidence of anorectal abscess and development of a fistula in a specific population area and to identify potential risk factors associated with demographic, socioeconomic and pre-existing disease (e.g. diabetes and inflammatory bowel disease).

METHODS

A longitudinal observational study was designed including a large cohort study in an area with 7,553,650 inhabitants in Spain 1st january 2014 to 31st december 2019. Adults who attended for the first time with an anorectal abscess and had a minimum of 1-year follow-up were included. The diagnosis was made using ICD-10 codes for anorectal abscess and anal fistula.

RESULTS

During the study period, we included 27,821 patients with anorectal abscess. There was a predominance of men (70%) and an overall incidence of 596 per million population. The overall incidence of anal fistula developing from abscesses was 20%, with predominance in men, and a lower incidence in the lowest income level. The cumulative incidence of fistula was higher in men and in younger patients (p < 0.0001). On multivariate analysis, patients aged 60-69 years (hazard ratio 2.0) and those with inflammatory bowel disease (hazard ratio 1.8-2.0) had a strong association with fistula development (hazard ratio 2.0).

CONCLUSIONS

One in five patients with an anorectal abscess will develop a fistula, with a higher likelihood in men. Fistula formation was strongly associated with inflammatory bowel disease.

Low Household Income Status and Death from Pneumonia in People with Type 2 Diabetes Mellitus: A Nationwide Study

BACKGRUOUND

We explored the risk of death from pneumonia according to cumulative duration in low household income state (LHIS) among adults with type 2 diabetes mellitus (T2DM).

METHODS

Using Korean National Health Insurance Service data (2002 to 2018), the hazards of mortality from pneumonia were analyzed according to duration in LHIS (being registered to Medical Aid) during the 5 years before baseline (0, 1-4, and 5 years) among adults with T2DM who underwent health examinations between 2009 and 2012 (n=2,503,581). Hazards of outcomes were also compared in six groups categorized by insulin use and duration in LHIS.

RESULTS

During a median 7.18 years, 12,245 deaths from pneumonia occurred. Individuals who had been exposed to LHIS had higher hazards of death from pneumonia in a dose-response manner (hazard ratio [HR], 1.726; 95% confidence interval [CI], 1.568 to 1.899 and HR, 4.686; 95% CI, 3.948 to 5.562 in those exposed for 1-4 and 5 years, respectively) compared to the non-exposed reference. Insulin users exposed for 5 years to LHIS exhibited the highest outcome hazard among six groups categorized by insulin use and duration in LHIS.

CONCLUSION

Among adults with T2DM, cumulative duration in LHIS may predict increased risks of mortality from pneumonia in a graded dose-response manner. Insulin users with the longest duration in LHIS might be the group most vulnerable to death from pneumonia among adults with T2DM.

Risk Factors of Severe COVID-19: A Review of Host, Viral and Environmental Factors

The clinical course and outcome of COVID-19 are highly variable, ranging from asymptomatic infections to severe disease and death. Understanding the risk factors of severe COVID-19 is relevant both in the clinical setting and at the epidemiological level. Here, we provide an overview of host, viral and environmental factors that have been shown or (in some cases) hypothesized to be associated with severe clinical outcomes. The factors considered in detail include the age and frailty, genetic polymorphisms, biological sex (and pregnancy), co- and superinfections, non-communicable comorbidities, immunological history, microbiota, and lifestyle of the patient; viral genetic variation and infecting dose; socioeconomic factors; and air pollution. For each category, we compile (sometimes conflicting) evidence for the association of the factor with COVID-19 outcomes (including the strength of the effect) and outline possible action mechanisms. We also discuss the complex interactions between the various risk factors.

Influence of Comorbidity Burden, Socioeconomic Status, and Race and Ethnicity on Survival Disparities in Patients With Cancer

PURPOSE

The purpose of this study was to assess the association of comorbidity burden with overall survival, accounting for racial/ethnic and socioeconomic differences in patients with cancer.

METHODS

In this retrospective cohort study, patients newly diagnosed with cancer between 2010 and 2018 were identified from a large health plan in southern California. Cancer registry data were linked with electronic health records (EHR). Comorbidity burden was defined by the Elixhauser comorbidity index (ECI). Patients were followed through December 2019 to assess all-cause mortality. Association of comorbidity burden with all-cause mortality was evaluated using Cox proportional hazards model. Crude and adjusted hazard ratio (HR, 95%CI) were determined.

RESULTS

Of 153,270 patients included in the analysis, 29% died during the ensuing 10-year follow-up. Nearly 49% were patients of color, and 32% had an ECI > 4. After adjusting for age, sex, race/ethnicity, cancer stage, smoking status, insurance payor, medical center, year of cancer diagnosis, and cancer treatments, we observed a trend demonstrating higher mortality risk by decreasing socioeconomic status (SES) (P-trend<.05). Compared to patients in the highest SES quintile, patients in the lowest, second lowest, middle, and second highest quintiles had 25%, 21%, 18%, and 11% higher risk of mortality, respectively [(HR, 95%CI): 1.25 (1.21-1.29), 1.21 (1.18-1.25), 1.18 (1.15-1.22), and 1.11 (1.07-1.14), respectively]. When we additionally adjusted for ECI, the adjusted HRs for SES were slightly attenuated; however, the trend persisted. Patients with higher comorbidity burden had higher mortality risk compared to patients with ECI score = 0 in the adjusted model [(HR, 95%CI): 1.22 (1.17-1.28), 1.48 (1.42-1.55), 1.80 (1.72-1.89), 2.24 (2.14-2.34), and 3.39 (3.25-3.53) for ECI = 1, 2, 3, 4, and >5, respectively].

CONCLUSIONS

Comorbidity burden affects overall survival in cancer patients irrespective of racial/ethnic and SES differences. Reducing comorbidity burden can reduce some, but not all, of the mortality risk associated with lower SES.

Cumulative Social Disadvantage and All-Cause Mortality in the United States: Findings from a National Study

The extent to which cumulative social disadvantage-defined as aggregate social risk resulting from multiple co-occurring adverse social determinants of health (SDOH)-affects the risk of all-cause mortality, independent of demographic and clinical risk factors, is not well understood. The objective of this study was to examine the association between cumulative social disadvantage, measured using a comprehensive 47-factor SDOH framework, and mortality in a nationally representative sample of adults in the United States. The authors conducted secondary analysis of pooled data for 63,540 adult participants of the 2013-2015 National Death Index-linked National Health Interview Survey. Age-adjusted mortality rates (AAMRs) were reported by quintiles of aggregate SDOH burden, with higher quintiles denoting greater social disadvantage. Cox proportional hazards models were used to examine the association between cumulative social disadvantage and risk of all-cause mortality. AAMR increased significantly with greater SDOH burden, ranging from 631 per 100,000 person-years (PYs) for participants in SDOH-Q1 to 1490 per 100,000 PYs for those in SDOH-Q5. In regression models adjusted for demographics, being in SDOH-Q5 was associated with 2.5-fold higher risk of mortality, relative to Q1 (adjusted hazard ratio [aHR] = 2.57 [95% confidence interval, CI = 1.94-3.41]); the observed association persisted after adjusting for comorbidities, with over 2-fold increased risk of mortality for SDOH-Q5 versus Q1 (aHR = 2.02 [95% CI = 1.52-2.67]). These findings indicate that cumulative social disadvantage is associated with increased risk of all-cause mortality, independent of demographic and clinical factors. Population level interventions focused on improving individuals' social, economic, and environmental conditions may help reduce the burden of mortality and mitigate persistent disparities.

The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

BACKGROUND

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

METHODS

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist-hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

RESULTS

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24-1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15-1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32-1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20-1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53-0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66-0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

CONCLUSION

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.

Inequalities by Income in the Prevalence of Cardiovascular Disease and Its Risk Factors in the Adult Population of Catalonia

Background Understanding the magnitude of cardiovascular disease (CVD) inequalities is the first step toward addressing them. The linkage of socioeconomic and clinical data in universal health care settings provides critical information to characterize CVD inequalities. Methods and Results We employed a prospective cohort design using electronic health records data from all residents of Catalonia aged 18+ between January and December of 2019 (N=6 332 228). We calculated age-adjusted sex-specific prevalence of 5 CVD risk factors (diabetes, hypertension, hyperlipidemia, obesity, and smoking), and 4 CVDs (coronary heart disease, cerebrovascular disease, atrial fibrillation, and heart failure). We categorized income into high, moderate, low, and very low according to individual income (tied to prescription copayments) and receipt of welfare support. We found large inequalities in CVD and CVD risk factors among men and women. CVD risk factors with the largest inequalities were diabetes, smoking, and obesity, with prevalence rates 2- or 3-fold higher for those with very low (versus high) income. CVDs with the largest inequalities were cerebrovascular disease and heart failure, with prevalence rates 2 to 4 times higher for men and women with very low (versus high) income. Inequalities varied by age, peaking at midlife (30-50 years) for most diseases, while decreasing gradually with age for smoking. Conclusions We found wide and heterogeneous inequalities by income in 5 CVD risk factors and 4 CVD. Our findings in a region with a high-quality public health care system and universal coverage stress that strong equity-promoting policies are necessary to reduce disparities in CVD.

Socioeconomic Status and Distance to Reference Centers for Complex Cancer Diseases: A Source of Health Inequalities? A Population Cohort Study Based on Catalonia (Spain)

The centralization of complex surgical procedures for cancer in Catalonia may have led to geographical and socioeconomic inequities. In this population-based cohort study, we assessed the impacts of these two factors on 5-year survival and quality of care in patients undergoing surgery for rectal cancer (2011-12) and pancreatic cancer (2012-15) in public centers, adjusting for age, comorbidity, and tumor stage. We used data on the geographical distance between the patients' homes and their reference centers, clinical patient and treatment data, income category, and data from the patients' district hospitals. A composite 'textbook outcome' was created from five subindicators of hospitalization. We included 646 cases of pancreatic cancer (12 centers) and 1416 of rectal cancer (26 centers). Distance had no impact on survival for pancreatic cancer patients and was not related to worse survival in rectal cancer. Compared to patients with medium-high income, the risk of death was higher in low-income patients with pancreatic cancer (hazard ratio (HR) 1.46, 95% confidence interval (CI) 1.15-1.86) and very-low-income patients with rectal cancer (HR 5.14, 95% CI 3.51-7.52). Centralization was not associated with worse health outcomes in geographically dispersed patients, including for survival. However, income level remained a significant determinant of survival.

The Reciprocal Relationship between Socioeconomic Status and Health and the Influence of Sex: A European SHARE-Analysis Based on Structural Equation Modeling

It is well recognized that socioeconomic status (SES) is an important determinant of health, but many studies fail to address the possibility of reverse causation. We aim to investigate the reciprocal relationship between trajectories of SES and health, and how these associations differ by sex. We performed a longitudinal study including 29,824 men and 37,263 women aged 50+ participating in at least two consecutive waves of the Survey of Health, Ageing and Retirement in Europe (SHARE). Using structural equation modeling, we found that baseline household income and wealth led to improvements in cognitive function, grip strength, quality of life and depressive symptoms, and a better initial health led to higher income and wealth for both sexes. However, the results indicated that the relative effect of cognitive function and grip strength on SES trajectories was overall greater than the corresponding effect of SES on health changes, particularly regarding income among women, but for quality of life and depressive symptoms, the reverse was indicated, though most pronounced for the associations with wealth. The reciprocal associations between SES and physical function were stronger for men than for women, whereas most associations with cognitive function and mental health were similar between sexes. This study demonstrates that both social causation and health selection contribute to social inequalities in health, but the influence of each direction and the importance of sex differences may vary according to the health outcomes investigated.

The situation of infection in the elderly in Spain: a multidisciplinary opinion document

Infection in the elderly is a huge issue whose treatment usually has partial and specific approaches. It is, moreover, one of the areas where intervention can have the most success in improving the quality of life of older patients. In an attempt to give the widest possible focus to this issue, the Health Sciences Foundation has convened experts from different areas to produce this position paper on Infection in the Elderly, so as to compare the opinions of expert doctors and nurses, pharmacists, journalists, representatives of elderly associations and concluding with the ethical aspects raised by the issue. The format is that of discussion of a series of pre-formulated questions that were discussed by all those present. We begin by discussing the concept of the elderly, the reasons for their predisposition to infection, the most frequent infections and their causes, and the workload and economic burden they place on society. We also considered whether we had the data to estimate the proportion of these infections that could be reduced by specific programmes, including vaccination programmes. In this context, the limited presence of this issue in the media, the position of scientific societies and patient associations on the issue and the ethical aspects raised by all this were discussed.

How are lifestyle factors associated with socioeconomic differences in health care costs? Evidence from full population data in the Netherlands

INTRODUCTION

There is a strong socioeconomic gradient in health care costs. However, little is known about the role of lifestyle factors in the association between health care costs and socioeconomic status (SES). This study investigates variation in the association between lifestyle indicators and health care costs between and within neighborhoods with similar SES.

METHOD

Using 2016 whole-population data for all 790 neighborhoods of the Netherlands, we estimated the association between neighborhood average health care cost performance (i.e., health care costs adjusted for population age and gender) and neighborhood socioeconomic status (NSES) and four lifestyle indicators - smoking, alcohol consumption, exercise and sport club membership. Additionally, using regression analysis, we explored the multivariate relationship between average health care cost performance, NSES and lifestyle indicators.

RESULTS

Neighborhoods with proportionally fewer smokers and more sport club members had significantly lower average health care costs. Remarkably, neighborhoods with more people who complied with the recommended maximum alcohol consumption had significantly higher health care costs. These findings were consistent within and between neighborhoods with different SES levels. Neighborhoods with more compliance with exercise guidelines had lower health care costs. However, this relationship was inconsistent across different NSES levels, with the largest cost reductions found in the most deprived neighborhoods.

CONCLUSION

Our findings suggest that prevention policies aimed at reducing the number of smokers and increasing sport club membership may reduce health care costs across all NSES groups, while increasing compliance with physical exercise norms may be effective mainly in low SES neighborhoods.

Sex differences in health and mortality by income and income changes

BACKGROUND

The adverse association between income, health and survival is well documented, but little is known about how income trajectories influence health and survival for men and women. We aim to investigate sex differences in mortality and hospitalisations by income and income changes.

METHODS

We performed a population-based, nationwide study including 1 063 787 Danes born 1935-1955 and residing in Denmark during 1980-2015. Income was calculated during two age intervals: 45-49 and 55-59 years. The average income was divided into quartiles for men and women separately, which formed the basis for the income trajectories. Individuals were followed up from age 60 until 2014/2015 for hospital admission and mortality, respectively.

RESULTS

Men had higher mortality and were more hospitalised than women. Sex differences in mortality were most pronounced for people with stable low income (relative difference in hazard=1.93; 95% CI 1.89 to 1.98) and a downward income trajectory (1.91; 95% CI 1.85 to 1.98) with smaller sex differences for people with an upward trajectory (1.59; 95% CI 1.56 to 1.62) and stable high income (1.37; 95% CI 1.33 to 1.41). A similar pattern was found for family income. Regarding hospitalisations, similar results were found, though less pronounced. Investigation of mortality and hospitalisations by all possible trajectories demonstrated that income at ages 55-59 was an important predictor of mortality, with increasing mortality for decreasing income quartile.

CONCLUSION

Income trajectories as a proxy for change in social position have a larger influence on men's than women's health and mortality. Income in the late 50s is an important predictor of mortality, particularly for men.