Determining the gap in life expectancy between the population with high and low educational levels is a useful way to summarise social inequalities in mortality in a single measure. Although mortality rates have followed a downward trend in western European countries in the last few decades, inequalities by educational level have tended to persist or even widen.1,2 Previous studies have reported that the gap in life expectancy at age 35 years across 14 European countries was 6.9 years for men and 3.2 years for women3, with eastern European countries showing larger gaps.4,5

For several decades, the Spanish population has experienced overwhelming sociodemographic and institutional changes along with increases of life expectancy of more than 40 years between 1910 and 2009.6 Pioneering studies have found territorial inequalities in mortality.7–9 However, fewer studies have analysed the gap in life expectancy by educational level in Spain.10–12 Looking at long-term inequalities, one study found that between 1960 and 2015 life expectancy increased for all education groups but particularly among the highly educated, thus widening inequalities between the populations with the lowest and highest educational levels.13

The life expectancy gap between two groups can be expressed through the contribution, positive or negative, of the underlying causes of death and age. Decomposition methods are ideal for determining whether life expectancy gaps are the result of different patterns. For instance, the decomposition of the gap across European countries shows much higher mortality rates from all the main causes of death among low-educated prime-age men, and half of the gap in mortality rate among men in this age group is due to higher death rates from circulatory diseases and cancer and to external causes of death (e.g. accidents and suicide).4 In Spain, the long-term increase in life expectancy by age in 1910 and 2009 has been attributed to the reduction in infant mortality until 1970; since then, the largest contribution has been found at older ages, mainly due to the decrease in mortality from diseases of the circulatory system.6 A 7-year follow-up study performed in Spain in 2001 on decomposition of inequalities in mortality patterns by educational level found that the main contributors for both sexes were cardiovascular and respiratory diseases.14 The relevance of decomposition analysis is that, if the ages or causes of death are sensitive to preventive interventions, decomposition approaches can provide public policy initiatives with evidence on which age groups or causes of death need to be targeted to reduce mortality.15 Because the largest share of the population lives in urban areas, there is increasing interest in the availability of official records of inequalities in life expectancy at the city level, as reflected by several international projects.16,17 In Spain, studies on socio-economic inequalities in life expectancy have been carried out at territorial level, for instance, the mortality atlas MEDEA3 in Spain analyses 26 cities at small area level including Barcelona city. However, a decomposition by age and causes of death by area would represent an excess of information that is difficult to handle and interpret. In contrast, the decomposition by educational level is easier to obtain and meaningful. To our knowledge this is the first study that applies decomposition techniques in a city in Spain. In doing so, we aim to contribute to a better understanding of the inequalities in life expectancy at city level. In this study, we analysed the gap in life expectancy by educational level in the city of Barcelona from 2004 to 2018 and analysed the decomposition of this gap by age and broad causes of death.

Using linked data between mortality registers and the census for Barcelona from 2004 to 2018 (except for 2009), we found a statistically significant gap in life expectancy by educational level for men and women, of 3.08 and 1.93 years, respectively. Decomposition of the gap by age group among men showed a larger contribution in the middle-aged group that shifted to the older age group over time, while the contribution among women was concentrated at older ages and remained stable. Decomposition of the gap by cause of death showed that the main contributor was neoplasms for men and circulatory diseases for women. There was a downward contribution of external causes in men and of infectious disease in men and women, but an upward trend in the contribution of respiratory diseases in both sexes, with a higher increase in women.

Trends were not apparently affected by the potential adverse effect of the economic crisis since 2008. Other studies conducted in the Spanish population during the post-crisis period have also found a constant downward trend in mortality from 2001 to 2011 and consequently an upward trend in life expectancy by educational level.21 Similarly, a study analysing inequalities in mortality through an index of deprivation in small areas in nine Spanish cities between 2001 and 2012 found stable trends, despite some heterogeneity by causes of death, with traffic injuries accounting for the only decrease in the post-crisis period for some cities, including Barcelona.22 For the longer period from 1996 to 2015 in Spain, cuts to medical staff and reductions in hospital beds appear to have significantly increased mortality rates from circulatory diseases and external causes, but not mortality from other causes of death. These increases appear to be driven by deaths occurring during emergency treatment, suggesting accessibility problems,23 which have a limited impact in densely populated cities such as Barcelona.

As already mentioned, prior research has also found similar results to our own in terms of a persistence of social inequalities in life expectancy.1,2 However, even a small gap in years may imply different patterns by age and causes of death. In our study, decomposition methods by age showed an improvement due to a decreasing contribution to the gap by persons aged less than 49 years and a shift to older ages between 2004 and 2018, especially for men. Decomposition by broad causes of death showed a favourable downward trend in the contribution of external causes of death among men (mainly due to traffic injuries and overdoses). Official records show that road traffic injuries decreased by 49.2% for men and 43.2% for women during the period analysed, but data is not available by education level.24 Our results suggest that this downward trend was more favourable among men with a low educational level, thus contributing to a narrowing of the life expectancy gap, but not for women.

Conversely, our finding of the relative importance and the adverse trend in the contribution of respiratory diseases to the life expectancy gap among men and women needs further investigation in relation to risk factors. Obviously, tobacco smoking can affect several causes of death, especially cardiovascular and respiratory diseases and neoplasms. Cardiovascular and respiratory diseases are also the main contributors to inequalities in mortality by educational level for men and women in Spain.14 In turn, tobacco smoking is influenced by social class. The international evidence indicates that tobacco smoking is the leading risk factor contributing to the gap in life expectancy by educational level (19.8% among men and 18.9% among women),25 while relative inequalities in respiratory diseases are often larger in younger age groups.26 In Spain, tobacco smoking is also the leading risk factor in disability-adjusted years lost attributable to neoplasms and cardiovascular and respiratory diseases among men and is the sixth among women, with high body mass index being the first.27 Despite the large reductions in smoking since the introduction of the law restricting smoking in 2005, inequalities in tobacco consumption are still present, with differences by sociodemographic groups and the phase of the epidemic wave.28

The persistence of inequalities in life expectancy is a matter of concern for public health policy to the extent that these inequalities can be reduced by improving the socioeconomic conditions in which people live and work, promote the adoptions of healthier behaviours, facilitate access to appropriate health care and provide healthier urban environments. Decomposition analysis can provide an integrated framework for monitoring inequalities in life expectancy that reflect partial targets for reducing mortality by age and cause.

Our research has several limitations. Official census registers can under-report the immigrant population; in addition, a “healthy migrant effect” has been reported for Barcelona,29 and this phenomenon may have reduced the gap in life expectancy through lower mortality rates among the low-income population. Our results should be interpreted as an initial approach but further analysis by cause-specific deaths is strongly recommended because broad causes of death can hide divergent trends within specific causes. The life expectancy gap reported in the presented study can be interpreted as a conservative estimate as we conflated educational levels in two categories in order to obtain reliable estimates instead of using the extreme categories. Nonetheless, the effect is probably small, as the life expectancy of the conflated categories is very close to our final classification. Finally, other methods have been suggested to account for uncertainty in life expectancy in the final open-ended age30. However, both methods produce almost identical life expectancy estimates across a large range of population sizes31, as is the case in the present study according to the reliability measures of the RSE.

To sum up, the stability in the life expectancy gap by educational level during the period analysed resulted from the combination of divergent trends by age and causes of death among high and low educational levels. Decomposition by age and cause of death may help to compute contrafactual hypotheses and allow the design of policies to reduce inequalities in life expectancy.

Statistical codes to generate life tables and decomposition by cause and age are provided in the online Appendix.

Data available to persons on request to xbartoll@aspb.cat from the Institut d’Investigació Biomèdica Sant Pau, Barcelona (Spain), in accordance with the data policy applicable to the Barcelona health survey.

Miguel Ángel Negrín Hernández.

The corresponding author on behalf of the other authors guarantee the accuracy, transparency and honesty of the data and information contained in the study, that no relevant information has been omitted and that all discrepancies between authors have been adequately resolved and described.

X. Bartoll-Roca designed the study and carried it out. M. Rodríguez-Sanz contributed to the methodological discussion. M. Rodríguez-Sanz, E. Sánchez, K. Pérez and C. Borrell have contributed corrections and improvements in the writing and final presentation of the study.

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