Shifts in Chronic Disease Patterns Among Spanish Older Adults With Multimorbidity Between 2006 and 2017.

Objectives: To investigate changes in multimorbidity patterns among Spanish older adults. Methods: Data come from the Spanish National Health Survey (ENSE) for individuals aged 60-89 years (2006: n = 9,758; 2017: n = 8,535). Prevalence rates and relative risks of 20 chronic conditions are estimated for the multimorbidity (3+ chronic conditions) sample, along with observed-to-expected prevalence of three-way disease combinations. Principal component and cluster analyses identify multimorbidity patterns and track temporal changes. Results: Overall, multimorbidity remained stable [2006: 59.6% (95% CI: 58.7%-60.6%); 2017: 60.3% (CI: 59.3%-61.3%)], except at older ages. Women exhibited higher multimorbidity prevalence, but sex differences declined by five percentage points. Low-high education differences widened by three percentage points. In 2017 most individuals living with multimorbidity experienced hypertension (63.4%), osteoarthrosis (62.4%) and chronic back pain (55.9%). These chronic conditions also dominate the most common triadic combinations. Multimorbid men also saw increases in cholesterol and diabetes. Conclusion: Multimorbidity trends and the most common combination of diseases can help plan healthcare for an ageing population. Sex and socioeconomic differences pose additional public health challenges as women and deprived populations tend to have more health complexities.

Educational disparities in disability-free life expectancy across Europe: A focus on the East-West gaps from a gender perspective.

Education plays a crucial role in shaping the health outcomes of adults. This study examines the relationship between educational attainment and health across Europe. Using data from the Survey of Health, Ageing and Retirement in Europe (SHARE), we estimate educational inequalities in disability-free life expectancy (DFLE) by gender in seven Western European (2004-2019) and three Central and Eastern European (CEE) (2010-2019) countries. We exploit a novel approach that combines the Sullivan method and multivariate life tables to calculate DFLE using SHARE data. We find that educational differences in DFLE favoring the better-educated exist in both CEE and Western European countries, but also that the differences across countries are more pronounced among the low-educated. While the absolute gaps in DFLE between low- and high-educated individuals in CEE and Western European countries are similar, the educational disparities in DFLE impose a more significant burden on the CEE populations due to their overall lower life expectancy. Educational inequalities are larger among women than among men in CEE countries, while the results for Western European countries are mixed. Our findings further highlight the important role of the institutional context in mitigating or exacerbating educational inequalities in health.

Age and cause-of-death contributions to educational inequalities in life expectancy and lifespan variation in a low-mortality country: A cross-sectional study of 1.67 million deaths in Spain (2016-19).

Background: We aim to assess the age- and cause-specific contributions to differences in life expectancy and lifespan variation between the high- and low-educated groups in Spain. Methods: We use sex-, age-, education- and cause-specific mortality and population data for individuals aged 30 and over for 2016-19 in Spain. We estimated life expectancies, and standard deviations of the age-at-death distribution (lifespan variation), and we disentangled the contribution of age-causes of death to educational differences in both indicators. Findings: Life expectancy at age 30 was higher for high-educated groups compared to low-educated groups, 5.5 years for males and 3.0 years for females. Lifespan variation was higher for low-educated groups compared to high-educated groups, 2.9 years for males and 2.2 years for females. The main contributors to the life expectancy gaps in males were lung cancer (0.58 years) and ischaemic heart diseases (0.42 years), and in females were other cardiovascular causes (0.26 years), and ischaemic heart diseases (0.22 years). The main contributors to the lifespan variation gaps were in males lung cancer (-0.25 years) and ischaemic heart diseases (-0.22 years), while in females were other neoplasms and other diseases of the nervous system. Interpretation: Whereas behavioural causes are more important in explaining educational inequalities in mortality among men, ageing-related causes of death seem more important among women. Attempts at narrowing socioeconomic gaps in mortality may benefit from applying gender-specific preventive policy measures.

Trends in cause-specific mortality: deaths of despair in Spain, 1980-2019.

BACKGROUND: Research from various countries has shown increases in alcohol- and drug-related deaths and suicide, known as 'deaths of despair' over recent decades, particularly among low-educated middle-aged individuals. However, little is known about trends in death-of-despair causes in Spain. Therefore, we aim to descriptively examine this among 25-64-year-olds from 1980 to 2019 and by educational attainment for the years 2017-19. METHODS: We obtained mortality and population data from the National Institute of Statistics to estimate age-standardized mortality rates and assess educational inequalities using the relative index of inequality (RII). RESULTS: Deaths of despair as a share of total mortality slightly increased from 2000 onwards, particularly among 25-64-year-old men (from 9 to 10%). Only alcohol-related mortality declined relatively more since 1980 compared with all-cause mortality. Regarding educational differences, low-educated men presented higher mortality rates in all death-of-despair causes (alcohol-related: RII 3.54 (95% CI: 2.21-5.66); drug-related: RII 3.49 (95% CI: 1.80-6.77); suicide: RII 1.97 (95% CI: 1.49-2.61)). Women noteworthy differences were only observed for alcohol-related (RII 3.50 (95% CI: 2.13-5.75)). CONCLUSIONS: Findings suggest an increasing proportion of deaths of despair among 25-64-year-olds since 2000, particularly among men. Public health policies are needed to reduce and prevent these premature and preventable causes of mortality.

Cause-specific mortality in Spain during the pandemic: educational differences and its impact on life expectancy.

BACKGROUND: Life expectancy in Spain fell by 1 year between 2018/19 and 2020. Yet, little is known on the impact on cause-of-death (COD) dynamics and educational inequalities therein. METHODS: We use individual-level death counts data by age, sex, education and multiple causes of death (MCOD) and the corresponding population exposures from national registers in Spain. Deaths were examined both as underlying cause of death (UCOD) and as contributory cause. We estimated life expectancies and lifespan inequalities by subpopulation groups and decomposed life expectancy differences between 2018/19 and 2020 by age groups and COD to assess the impact of COVID-19 (as MCOD) and major UCOD. RESULTS: COVID-19 contributed to a decline in male and female life expectancy in Spain between 2018/19 and 2020 (respectively, -1.7 and -1.4 years). Conversely, cancer, respiratory and circulatory system diseases and ill-defined causes as UCOD contributed to life expectancy increases. Life expectancy declines equalled -1.4 years among the low-educated in both sexes (population 30+), -1.0 and -0.7 years among middle-educated and -1.1 and -0.9 years among high-educated men and women. Without COVID-19, educational inequalities in life expectancy would have remained at similar levels, whereas lifespan variation would have been lower (-22% for women and -8% for men). CONCLUSIONS: Life expectancy declines in Spain in 2020 were mainly driven by COVID-19, with possible substitution effects, especially for respiratory system diseases (fewer deaths compared to 2018/19 when coded as UCOD but more as contributing cause). We therefore advocate analysing MCOD when studying changing COD patterns during the pandemic.

Combining remaining life expectancy and time to death as a measure of old-age dependency related to health care needs.

Public concern about the rising number of older dependent citizens is still based mainly on standard population aging indicators. This includes the old-age dependency ratio (OADR), which divides the state pension age population by the working age population. However, the OADR counts neither the dependent elderly nor those who provide for them. This paper builds on previous research to propose several alternative indicators, including the health care (HC) need-adjusted real elderly dependency ratio and the HC need-adjusted dependent population-to-tax rate. These indicators consider improvements in old-age survival and time to death in order to better define the health care needs of the dependent old-age population and to better approximate their financial burden. We define the old-age population dependent on health care as those above the age at which remaining life expectancy is 15 years or less and are expected to die within 5 years. We use data from the US to illustrate differences between the proposed new and standard measures. Results show that, as a share of the total population, the old-age population dependent on health care has virtually not changed since 1950. Moreover, increases in GDP and state tax revenue have outstripped population aging almost continuously since 1970, irrespective of the indicator used, and they are expected to continue to do so during the coming decade. The demand for health care services is therefore not being fueled by population aging but instead by other factors such as progress in medical knowledge and technology, costs of hospitalization, and the increasing use of long-term care facilities.

The impact of Covid-19 on demographic components in Spain, 2020-31: A scenario approach.

While considerable attention has been paid to the impact of Covid-19 on mortality and fertility, few studies have attempted to evaluate the pandemic's effect on international migration. We analyse the impact of Covid-19 on births, deaths, and international migration in Spain during 2020, comparing observed data with estimated values assuming there had been no pandemic. We also assess the consequences of three post-pandemic scenarios on the size and structure of the population to 2031. Results show that in 2020, excess mortality equalled 16.2 per cent and births were 6.5 per cent lower than expected. Immigration was the most affected component, at 36.0 per cent lower than expected, while emigration was reduced by 23.8 per cent. If net migration values recover to pre-pandemic levels in 2022, the size and structure of the population in 2031 will be barely affected. Conversely, if levels do not recover until 2025, there will be important changes to Spain's age structure.

Estimation of smoking-related mortality and its contribution to educational inequalities in life expectancy in Spain: an observational study, 2016-2019.

OBJECTIVE: To estimate smoking-related mortality and its contribution to educational inequalities in life expectancy in Spain. DESIGN: Nationwide, observational study from 2016 to 2019. Population-attributable fractions were used to estimate age, sex and education-specific cause-of-death smoking-attributable mortality. Life table techniques and decomposition methods were used to estimate potential gains in life expectancy at age 35 and the cause-specific contributions of smoking-related mortality to life expectancy differences across educational groups. SETTING: Spain. PARTICIPANTS: We use cause-specific mortality data from population registers and smoking prevalence from the National and the European Health Survey for Spain from 2017 and 2019/2020, respectively. RESULTS: We estimated 219 086 smoking-related deaths during 2016-2019, equalling 13% of all deaths, 83.7% of those in men. In the absence of smoking, potential gains in male life expectancy were higher among the low-educated than the high-educated (3.1 vs 2.1 years). For women, educational differences were less and also in the opposite direction (0.6 vs 0.9 years). The contribution of smoking to life expectancy differences between high-educated and low-educated groups accounted for 1.5 years among men, and -0.2 years among women. For men, the contribution of smoking to these differences was mostly driven by cancer in middle age, cardiometabolic diseases at younger ages and respiratory diseases at older ages. For women, the contribution to this gap, although negligible, was driven by cancer at older ages among the higher educated. CONCLUSIONS: Smoking remains a relevant preventable risk factor of premature mortality in Spain, disproportionately affecting life expectancy of low-educated men.

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.

Educational differences in alcohol-related mortality and their impact on life expectancy and lifespan variation in Spain (2016-2018): a cross-sectional analysis using multiple causes of death.

BACKGROUND: Socioeconomic inequalities in alcohol-related mortality in Spain exists, and are postulated to contribute to inequalities in all-cause mortality. We aim to assess absolute and relative educational inequalities in alcohol-related mortality, and to estimate the role of alcohol in educational inequalities in both life expectancy and lifespan variation in Spain. METHODS: We used multiple cause-of-death (MCOD) mortality data for individuals aged 30 and over for Spain (2016-2018) by educational attainment. We estimated by sex and educational attainment age-standardised alcohol-attributable mortality rates, relative and absolute indices of educational inequalities; and total life expectancy and lifespan variation at age 30 for all-cause mortality and after eliminating alcohol-attributable mortality. RESULTS: The use of MCOD resulted in an additional 2543 annual alcohol-related deaths (+75% among men and +50% among women) compared with estimates derived from underlying causes of death. In absolute terms, educational inequalities were the highest among men aged 45-84 and among women aged 45-64. In relative terms, higher inequalities raised in working ages, whereas at older ages inequalities tended to be lower, although still important among men. Alcohol contributed to educational inequalities in life expectancy (men: 0.13 years (3.2%); women 0.02 years (0.7%)) and lifespan variation (2.1% and 1.4% for men and women, respectively). CONCLUSION: Alcohol consumption remains an important lifestyle habit to be tackled in order to reduce socioeconomic inequalities in mortality in Spain, particularly among men.

The influence of social and economic ties to the spread of COVID-19 in Europe.

By late January 2020, the 2019 novel coronavirus (SARS-CoV-2) had reached Europe and most European countries had registered cases by March 1. However, the spread of the virus has been uneven in both prevalence and speed of propagation. We analyse the association of social, economic, and demographic factors in the initial spread of the coronavirus disease COVID-19 across 23 European countries between March 1 and April 30, 2020. Diagnosed COVID-19 cases from Johns Hopkins University and data from the European Social Survey and other sources were used to estimate bivariate associations between cumulative reported case numbers at ten-day intervals and nine social, demographic, and economic variables. To avoid overfitting, we first reduce these variables to three factors by factor analysis before conducting a multiple regression analysis. We also perform a sensitivity analysis using rates and new cases between two time periods. Results showed that social and economic factors are strongly and positively associated with COVID-19 throughout the studied period, while the association with population density and cultural factors was initially low, but by April, was higher than the earlier mentioned factors. For future influenza-like pandemics, implementing strict movement restrictions from early on will be crucial to curb the spread of such diseases in economically, socially, and culturally vibrant and densely populated countries. Supplementary Information: The online version contains supplementary material available at 10.1007/s12546-021-09257-1.

Sociodemographic determinants of intraurban variations in COVID-19 incidence: the case of Barcelona.

BACKGROUND: Intraurban sociodemographic risk factors for COVID-19 have yet to be fully understood. We investigated the relationship between COVID-19 incidence and sociodemographic factors in Barcelona at a fine-grained geography. METHODS: This cross-sectional ecological study is based on 10 550 confirmed cases of COVID-19 registered during the first wave in the municipality of Barcelona (population 1.64 million). We considered 16 variables on the demographic structure, urban density, household conditions, socioeconomic status, mobility and health characteristics for 76 geographical units of analysis (neighbourhoods), using a lasso analysis to identify the most relevant variables. We then fitted a multivariate Quasi-Poisson model that explained the COVID-19 incidence by neighbourhood in relation to these variables. RESULTS: Neighbourhoods with: (1) greater population density, (2) an aged population structure, (3) a high presence of nursing homes, (4) high proportions of individuals who left their residential area during lockdown and/or (5) working in health-related occupations were more likely to register a higher number of cases of COVID-19. Conversely, COVID-19 incidence was negatively associated with (6) percentage of residents with post-secondary education and (7) population born in countries with a high Human Development Index. CONCLUSION: Like other historical pandemics, the incidence of COVID-19 is associated with neighbourhood sociodemographic factors with a greater burden faced by already deprived areas. Because urban social and health injustices already existed in those geographical units with higher COVID-19 incidence in Barcelona, the current pandemic is likely to reinforce both health and social inequalities, and urban environmental injustice all together.

Are partner's features important to understand health at older ages? The Spanish case / ¿Son importantes las características de la pareja para entender la salud en edades avanzadas? El caso español

Objective: To analyse health differences among partnered individuals in Spain aged 65-81 considering their combined (education of both partners and age gap) and household (economic capacity of the household) characteristics. Method: A cross-sectional study of the 2015 Spanish sample of the European Union Statistics on Income and Living Conditions survey (EU-SILC) on partnered individuals aged 65-81 years (N=1787). Using logistic regression models separately for women and men we obtained odds and predicted probabilities of having less than good health (95% confidence intervals) according to combined information from both partners on education and age, the household's economic capacity and partner's health status. Results: Probabilities of not having good health are significantly less among lower educated women whose partners are more highly educated (compared to both partners being lower educated) and among women whose partner is younger or has good health status. The latter also applies to men. Living in a household without economic difficulties also favours health (both sexes). Conclusions: For both sexes a partner's health status is the variable that shows the largest effect on elderly partnered Spanish people's health but women's health appears to be more sensitive to their partner's educational attainment and the household's economic situation. (AU)

Objetivo: Analizar las diferencias de salud entre la población española de 65 a 81 años de edad que vive en pareja, considerando características individuales, combinadas de ambos miembros y generales de la pareja. Método: Estudio transversal de la muestra española del año 2015 de la Encuesta Europea de Condiciones de Vida de personas mayores (edades 65-81 años) que conviven en pareja (N=1787). Mediante modelos de regresión logística independientes para mujeres y hombres se obtuvo la estimación de las probabilidades de no tener buena salud autopercibida (intervalos de confianza del 95%) según la combinación del nivel de estudios y la edad de ambos miembros de la pareja, así como la capacidad económica del hogar y el estado de salud del cónyuge. Resultados: Las probabilidades de no tener buena salud son significativamente menores entre las mujeres con menor nivel de educación cuyas parejas son más educadas (en comparación con las que tienen menos educación) y entre las mujeres cuya pareja es más joven o tiene un buen estado de salud. Esto último también se aplica a los hombres. Vivir en un hogar sin dificultades económicas también favorece la salud en ambos sexos. Conclusiones: Para ambos sexos, el estado de salud de la pareja es la variable que muestra el mayor efecto sobre la salud de la población mayor española que vive en pareja, aunque la salud de las mujeres parece ser más sensible al nivel educativo de su pareja y a la situación económica general del hogar. (AU)

The contribution of social participation to differences in life expectancy and healthy years among the older population: A comparison between Chile, Costa Rica and Spain.

We study the health trajectories of the population aged over 60, comparing between one European and two Latin American countries (Spain, Chile and Costa Rica) which have similar longevity patterns. Our focus is on functional limitation and mortality risks, considering differences by gender, education and social participation. Data come from national panel surveys (EPS, CRELES, SHARE). Multistate modelling is used to estimate transition probabilities between two health states: healthy to unhealthy, unhealthy to healthy as well as the transition to death from healthy or unhealthy states, to estimate the duration of stay in a specific state (computing healthy and unhealthy life expectancies) and the effect of the selected covariates. Results show that older Costa Ricans have the smallest gender gap in life expectancy but women have a lower healthy life expectancy compared to those in Chile and Spain. Participation in social activities leads to higher healthy life expectancy among the elderly in Costa Rica and Spain, whilst there were no relevant educational differences observed in longevity in the analysed countries. To conclude: despite the different patterns observed in health transitions and survival across the three countries, social participation is associated with greater health and longevity among people of old age, with little effect coming from educational attainment. Public policies should therefore be aimed at reducing unhealthy life years and dependency at advanced ages by promoting more engagement in social activities, especially among vulnerable groups who are more likely to experience impairment from a younger age.

Are partner's features important to understand health at older ages? The Spanish case.

OBJECTIVE: To analyse health differences among partnered individuals in Spain aged 65-81 considering their combined (education of both partners and age gap) and household (economic capacity of the household) characteristics. METHOD: A cross-sectional study of the 2015 Spanish sample of the European Union Statistics on Income and Living Conditions survey (EU-SILC) on partnered individuals aged 65-81 years (N=1787). Using logistic regression models separately for women and men we obtained odds and predicted probabilities of having less than good health (95% confidence intervals) according to combined information from both partners on education and age, the household's economic capacity and partner's health status. RESULTS: Probabilities of not having good health are significantly less among lower educated women whose partners are more highly educated (compared to both partners being lower educated) and among women whose partner is younger or has good health status. The latter also applies to men. Living in a household without economic difficulties also favours health (both sexes). CONCLUSIONS: For both sexes a partner's health status is the variable that shows the largest effect on elderly partnered Spanish people's health but women's health appears to be more sensitive to their partner's educational attainment and the household's economic situation.

What factors enable mid-life carers to re-enter the labour market in New Zealand?

OBJECTIVE: To assess the characteristics of carers and the caregiving situation associated with return to paid employment among older unemployed carers in New Zealand. METHODS: A baseline sample of 280 unemployed carers was identified from responses by people aged 55-70 to the 2012-2016 biennial waves of the New Zealand Health, Work and Retirement longitudinal survey. Multiple logistic regression analysis was used to assess characteristics uniquely predicting employment status at two-year follow-up. RESULTS: Sixteen percent were employed at follow-up. Economic living standards, physical health and preference to be in paid employment were positively associated with being employed at follow-up. There were no statistical differences according to age, gender, ethnicity, marital status, education and care characteristics. CONCLUSION: Individual preferences were the strongest predictor of return to paid employment. Despite New Zealand employment legislation allowing all employees to request flexible working arrangements, economic and health differences in workforce retention among carers persist.

Until Death Do Us Part. The Influence of Own and Partner's Socioeconomic Status on the Health of Spanish Middle-Aged Population.

OBJECTIVES: To explore whether the influence of a partner's socioeconomic status (SES) on health has an additive or a combined effect with the ego's SES. METHODS: With data on 4533 middle-aged (30-59) different-sex couples from the 2012 Spanish sample of the European Union Statistics on Income and Living Conditions (EU-SILC) survey, we apply separate sex-specific logistic regression models to calculate predicted probabilities of having less than good self-perceived health according to individual and partner's characteristics separately and combined. RESULTS: Both approaches led to similar results: Having a partner with better SES reduces the probabilities of not having good health. However, the combined approach is more precise in disentangling SES effects. For instance, having a higher educated partner only benefits health among Spanish low-educated men, while men's health is worse if they have a working spouse. Conversely, women's health is positively influenced if at least one couple member is economically active. CONCLUSIONS: There are significant health differences between individuals according to their own and their partner's SES in an apparently advantageous population group (i.e., individuals living with a partner). The combinative approach permits obtaining more precise couple-specific SES profiles.

Los efectos de la Gran Recesión y las políticas de austeridad en la salud de la población española / The effects of the Great Recession and austerity policies on the health of the Spanish population

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