A GBD 2019 study of health and Sustainable Development Goal gains and forecasts to 2030 in Spain.

Introduction

Spain’s public health system is primarily funded by public sources and covers over 99% of the population, with primary care serving as the first point of access for nearly all patients 1 . Health system management has been decentralised since 2002, with devolved authority at the regional ( comunidad autónoma ) level. The national government is responsible for the overall coordination and monitoring of health system performance and for contributing to health equity among regions through, for instance, its monitoring efforts and funding 1 . In addition to the functioning of the national health system, which plays a crucial role in determining and maintaining population health 2 , health in Spain is shaped by several social determinants including income, educational attainment level, household structure, and gender 3 – 5 .

To improve health system monitoring and public health research efforts to reduce health inequalities, we assess the state of health in Spain using data from the 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study, which measures communicable, maternal, neonatal, and nutritional diseases (CMNNDs), non-communicable diseases (NCDs), and injuries among populations around the world, in a comparable format. The GBD facilitates the monitoring and comparison of health indicators within and among countries to help achieve national 1 and global 6 health targets, including the health-related United Nations’ Sustainable Development Goals (SDGs) 7 .

Previous Spain-specific GBD studies were published in 2014 8 and 2018 9 , in addition to 11 reports employing GBD methodology and/or data in Spain (see Supplementary Appendix 1 ). Here, using GBD 2019 data, we assess the state of health in Spain immediately before the COVID-19 pandemic and present the results of trends from 1990 to 2019. In addition, we develop projections for meeting the SDG targets by 2030, in order to better identify unmet health needs, inform appropriate interventions, and provide relevant insight into future health trends. This manuscript was produced as part of the GBD Collaborator Network and in accordance with the GBD Protocol.

Methods

Overview

The GBD 2019 estimated disease burden worldwide and in Spain from 369 diseases, injuries, and impairments, as well as 87 risk factors and combinations of risk factors, through systematic assessment of published, publicly available, and nationally-contributed data on incidence, prevalence, and mortality, for a mutually exclusive and collectively exhaustive list of diseases and injuries 10 , 11 . The GBD 2019 produced age- and sex-specific estimates globally, regionally, and for 204 countries and territories (including selected subnational units) using the comparative risk assessment (CRA) framework of cause-specific risk factor exposure, morbidity, and mortality attributable to these risks, and a range of health system characteristics, with details of this methodology being available elsewhere 11 . The CRA framework systematically evaluates changes in population health that would arise from modifying the population distribution of exposure to a single risk factor or groups of risk factors. For this study, summary measures were computed using standardised and validated approaches that adjust for major sources of bias (see Supplementary Appendix 2 ). Notably, GBD 2019 used newly available risk factors for non-optimal global earth temperatures, measuring the environmental effects of changes in ambient temperatures on disease outcomes, and standardisation methods to improve the quality of available statistical data to calculate these risks 12 . Data on life expectancy, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) in Spain from 1990 to 2019 were extracted from GBD 2019, full details of which are published elsewhere 10 . Inequality in disease burden was examined using the Gini coefficient.

The GBD estimates levels and trends in exposure, attributable deaths, and attributable DALYs, using the CRA framework. These variables are disaggregated by age group, sex, year, and level 1 category of risks (i.e. behavioural, environmental and occupational, and metabolic) or clusters of risks from 1990 to 2019 12 . The GBD also uses various statistical models to address data quality issues, to establish the disease burden and attributable risk for each disease, injury, and impairment. The GBD classifies diseases and injuries in a hierarchy containing four levels, each with increasing details of risk. This study reports those at level three, which represent specific causes of disease and injury (e.g. tuberculosis and road injuries). For example, ischemic stroke is a level 4 cause in the level 3 stroke group, which is in the level 2 cardiovascular diseases group. Level three was chosen for this analysis because level two is considered as ‘too aggregate’ to suitably capture certain diseases, while level four is ‘too detailed’ and is primarily used for specific disease papers. For risk factors, the GBD 2019 estimation of attributable burden followed the general framework established for CRA used in GBD since 2002, with changes for 2019 detailed elsewhere 11 . This study presents life expectancy, main causes of death, YLLs, YLDs, and DALYs, along with their causes, stratified by sex at the national level in Spain. As stated above, non-optimal earth temperature is a new risk factor from GBD 2019; it represents an aggregate of the burden attributable to low and high temperatures. Heat and cold effects relate to effects above and below the theoretical minimum risk exposure level (TMREL). The population-weighted mean TMREL is 25.6 °C 13 , 14 .

Data obtention and processing

The GBD estimation process is based on identifying multiple relevant data sources for each disease or injury. The exact data sources for Spanish estimates are accessible at its Institute of Health Metrics and Evaluation (IHME) country profile 15 . The primary sources for the cause of death data were the Mortality Information System hosted by the Instituto Nacional de Estadística (INE) and the World Health Organization (WHO) 16 . IHME collects data to calculate relative risks from cohort studies, randomised control trials, literature reviews, and other sources (see Supplementary Appendix 2 ). The GBD uses this data and corrects for the underreporting of deaths and garbage codes (i.e. anything marked as a cause of death that cannot be an underlying cause or is an unspecified cause) 17 based on the medical literature, expert opinions, and statistical techniques used to assign the most probable causes of death to each item 18 .

Sustainable Development Goal indicators

We also report IHME estimates for Spain’s health-related SDG index score. This measure is the overall measure of all health-related SDGs. The SDG assessment measured progress on 41 health-related SDG indicators, including smoking prevalence, air pollution, intimate partner violence, and vaccine coverage, from 1990 to 2017 for 195 countries and territories 7 . To construct the health-related SDG index, the value for each indicator was transformed on a scale from 0 to 100. This was based on 1000 observed or projected random samples calculated from 1990 to 2030, to reduce sensitivity to extreme outliers in the overall sample. For this scale, 0 represents the 2.5th percentile and 100 represents the 97.5th percentile. The geometric mean of the scaled indicators was also taken for each target.

To generate projections through 2030, IHME used a forecasting framework that compiles the impacts of independent drivers of population health into the future, to assess the probability of each country’s attainment for defined SDG targets. As a tool for projections, we used a meta-regression Bayesian, regularised, trimmed (MR-BRT) mixed effects model, that provides an easy interface for formulating and solving common linear and non-linear mixed effects models used in the most recent GBD iterations 7 . This framework drew estimates from the broader GBD study and weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 7 . The impact of the COVID-19 pandemic is not part of this analysis, with such projections having been estimated elsewhere 19 .

We derived 95 percent uncertainty intervals of all estimates using simulation methods, which resemble but are not the same as 95% confidence intervals. We constructed 1000 draws with the required correlation structure between variables separately for each cause, and the 2.5th percentile and the 97.5th percentile of expected events were taken to be the lower and upper bounds of the corresponding uncertainty interval. These ranges provide guidance on uncertainty in the underlying cause-specific rates, as expressed in terms of expected events in the population 7 . All methods were performed in accordance with the relevant guidelines and regulations; this study conforms to international ethical standards, including the 1975 Declaration of Helsinki.

Results

In 2019, Spain had a total population of 46.0 million people (51.1% female). Spain has an ageing population (see Supp Fig. S1 ), which is expected to continue through 2030. By 2030, life expectancy in Spain is projected to reach 84.8 years (uncertainty interval (UI): 83.1–86.0); 87.2 (UI: 85.3–88.6) for females and 82.3 (UI: 80.6–83.7) for males (see Supp Fig. S2 ). Recent projections show that, in the absence of health system and social impacts from COVID-19, Spain would have continued to experience declines in death rates for both sexes, with a more rapid decline for males (Fig. 1 ).

Mortality and morbidity

The main causes of death and YLLs by sex are shown in Table 1 . In 2019, an estimated 428,577 deaths (UI: 421,705–435,908) occurred in Spain. NCDs caused 92.0% (UI: 91.3–93.0) of all deaths. Of the NCDs, the highest-ranking specific causes of death were ischaemic heart disease (IHD) (53,632, UI: 46,434–59,832), stroke (37,092, UI: 30,981–42,048), chronic obstructive pulmonary disease (COPD) (31,245, UI: 25,155–36,629), Alzheimer’s disease and other dementias (29,208, UI: 7,447–72,045), and tracheal, bronchus, and lung cancer (24,523, UI: 22,753–25,958). Of the cancers, tracheal, bronchus, and lung cancer caused the most frequent deaths with 24,523 (UI: 22,753–25,958), followed by colorectal cancers with 20,011 (UI: 17,768–21,746). Breast cancer accounted for 7981 deaths (UI: 7002–8763) in females and prostate cancer accounted for 8406 deaths (UI: 6964–12,143) in males.

Following NCDs, 4.2% of deaths in 2019 were caused by CMNNDs (18,134, UI: 15,251–20,376) and 3.8% by injuries (16,176, UI: 14,784–17,140). Among CMNNDs, respiratory infections and tuberculosis, diarrheal diseases, and other infectious diseases accounted for 14,583 (UI: 12,105–16,536), 1213 (UI: 953–1485), and 647 deaths (UI: 562–796), respectively. HIV/AIDS accounted for 679 deaths (UI: 640–718). Of deaths related to injuries, the top three causes were falls at 4621 deaths (UI: 3952–5128), self-harm at 3759 (UI: 3539–3989), and road injuries at 2570 (UI: 2407–2718) deaths.

Total YLLs in 2019 were 6,330,140 (UI: 6,205,667–6,464,235); 3,644,301 in males and 2,685,839 in females. Similar to causes of death totals, 89.2% of YLLs were due to NCDs (5,643,796, UI: 5,530,194–5,762,752), followed by 6.6% due to injuries (416,154, UI: 398,959–432,355), and 4.3% due to CMNNDs (270,190, UI: 241, 863–293,260). The YLLs caused by injury disproportionately affected males at 299,246 YLLs, compared to 116,908 among females.

In 2019, IHD accounted for 12.5% (UI: 10.8–13.9) of all deaths (53,632, UI: 46,434–59,832), with an annual rate of change (ARC) of -0.8% from 1990; stroke accounted for 8.7% (UI: 7.2–9.8) of all deaths (37,092, UI: 30,981–42,048), with an ARC of -1.4%; and COPD accounted for 7.3% (UI: 5.9–8.6) of all deaths (31, 246, UI: 25,155–36,629), with an ARC of 1.2% (Fig. 2 a, UI and changes since 1990 not shown in figure). Of the total YLDs, low back pain attributed to 8.2% (UI: 6.8–9.7), with an ARC of -0.2% (1121.0 YLDs per 100,000, UI: 806.2–1527.9), depressive disorders attributed to 7.4% (UI: 5.9–9.2), with an ARC of 0.9% (1021.5 YLDs per 100,000, UI: 724.4–1392.7), and diabetes attributed to 6.4% (UI: 5.2–7.9), with an ARC of 2.0% (885.2 YLDs per 100,000, UI: 572.5–1247.5) (Fig. 2 b). Similar to deaths and YLDs, the top contributors to DALYs include IHD, which contributed to 5.9% (UI: 5.0–6.8) and had an ARC of -1.6% (1617 DALYs per 100,000, UI: 1474–1755), diabetes, which contributed to 4.2% (UI: 3.4–5.1) and had an ARC of 0.8% (1146 DALYs per 100,000, UI 842–1514), and lung cancer, which contributed to 4.2% (UI: 3.6–4.8) and had an ARC of 0.4% (1,139 DALYs per 100,000, UI: 1066–1202) (see Fig. 2 c). The top contributors to YLLs also include IHD at 11.1% (UI: 10.1–12.1), with an ARC of -1.6% (702,210 YLLs, UI: 638,688–765,172); lung cancer at 8.2% (UI: 7.7–8.6), with an ARC of 0.3% (516,790 YLLs, UI: 484,690–545,363); and stroke at 6.7% (UI: 5.9–7.5), with an ARC of -2.3% (426,742 YLLs, UI: 371,628–473.043; Table 1 , Fig. 2 d).

IHD, stroke, and COPD were the three leading causes of death in Spain in both 1990 and 2019. In 2019, IHD caused 116.5 (UI: 100.9–130.0) deaths per 100,000 and stroke caused 80.6 (UI: 67.3–91.4) deaths per 100,000. While IHD and stroke related deaths decreased from 1990 to 2019, COPD-related deaths increased from 47.7 (UI: 43.4–50.9) to 67.9 (UI: 54.7–79.6) per 100,000, between 1990 and 2019. The main causes of death remained relatively similar from 1990 to 2019, with the exception of Alzheimer’s disease and lung cancer switching places as the fourth and fifth causes of death in 2019, compared to 1990 (Supp Fig. S3 ).

The leading conditions causing YLDs in Spain in 2019 were low back pain (1121.0, UI: 806.2–1527.9), depressive disorders (1021.5, UI: 724.4–1392.7), and diabetes (885.2, UI: 572.5–1247.5). Diabetes moved up from sixth position in 1990 and displaced headache disorders (792.8, UI: 189.2–1692.9), which covers the fourth position in 2019. Falls increased from eighth in 1990 to fifth in 2019, with 623.4 YLDs (433.2–882.7) per 100,000 (Supp Fig. S4 ).

IHD was the leading cause of DALYs in both 1999 and 2019. In 2019, IHD contributed to 1613.6 (UI: 1474.9–1755.4) DALYs per 100,000. In order of ranking, diabetes (1145.5, UI: 842.3–1513.6), lung cancer (1139.2, UI: 1065.8–1202.2), low back pain (1121.1, UI: 806.2–1527.9), and stroke (1113.4, UI: 989.8–1221.6) were the top five causes of DALYs in 2019 (see Supp Fig. S5 ).

For males, leading causes of DALYs were, in descending order, IHD (2014.8, UI: 1896.8–2148.0), lung cancer (1822.7, UI: 1695.5–1936.0), and COPD (1461.6, UI: 1284.7–1640.5) (see Supp Fig. S6 a). In contrast, for females, leading causes of DALYs were low back pain (1368.4, UI: 980.4–1864.3), depressive disorders (1356.0, UI: 959.1–1835.0), and IHD (1229.0, UI:1051.3–1400.3) (see Supp Fig. S6 b).

The same top six conditions contribute to DALYs in Spain, compared to other high-income countries, with IHD as the number one contributor to DALYs (see Supp Fig. S7 ). Globally, IHD ranks second as contributor to DALYs, while overall CMNNDs primarily contribute to DALYs.

Similar to DALYs, IHD has been the leading contributor to YLLs in Spain since 1990. Currently, IHD contributes to 1525.8 (UI: 1387.8–1662.7) YLLs per 100,000, followed by lung cancer with 1122.9 (1053.2–1185.0), which rose from fourth place in 1990, and stroke with 927.3 (UI: 807.5–1027.9), which dropped from second place in 1990 to third in 2019. Road injuries dropped from the third to the seventeenth position from 1990 to 2019, causing 209.1 (UI: 195.9–221.5) YLLs per 100,000 (Supp Fig. S8 ).

When YLLs are disaggregated by sex, results remain similar (see Supp Fig. S9 a,b). IHD was the leading cause for both sexes; 1914.5 (UI: 1800.9–2042.0) for males and 1153.2 (UI: 970.7–1317.9) for females. For males, the next leading causes, in descending order, were lung cancer (1796.1, UI: 1672.6–1907.2), COPD (1050.4, UI: 908.4–1189.7), stroke (886.3, UI: 801.6–970.6), and colorectal cancer (865.4, 792.4–932.2). For females, the next leading causes, in descending order, were stroke (966.5, UI: 797.5–1112.8), Alzheimer’s disease (782.9, UI: 203.4–1938.7), breast cancer (689.4, 632.2–738.3), and colorectal cancer (555.8, UI: 490.8–607.5).

Risk factors

For males, smoking consistently ranked as the top risk factor for 2010 and 2019, attributable to DALYs (5453.2, UI: 5112.7–5811.4). High body mass index (BMI) (2255.2, UI: 1350.5–3252.9) and high fasting blood glucose (FPG) (2193.8, UI: 1701.8–2746.1) were the second and third ranked risk factors in both 2010 and 2019, for males (Fig. 3 a). For females, in both 2010 and 2019, smoking (1733.9, UI: 1518.2–1954.1) ranked third, while high BMI (2300.2, UI: 1513.4–3200.2) and high FPG (1961.8, UI: 1496.5–2543.4) ranked first and second, respectively (Fig. 3 b). For both sexes, a plurality of the top twenty risk factors were related to poor diet, and the new risk factor, low non-optimal ambient temperature, was among the top five risks in 2019.

The leading YLD risks in 2019 were, in descending order, high FPG, causing 987.4 YLDs (UI: 660.5–1372.4), high BMI, 955.8 (UI: 565.2–1470.0), and smoking, 838.8 (UI: 618.4–1080.9), each of which, similar to DALYs, have remained the three leading risks since 2010 (Supp Fig. S10 ).

For males, the leading risks for YLDs mirrored DALYs in 2019. These were, in descending order, smoking (1021.8, UI: 768.5–1300.5), high FPG (1006.9, UI: 671.8–1401.9), and high BMI (850.2, UI: 474.3–1344.3) (see Supp Fig. S11 ). In comparison, leading risks in females for YLDs were, in descending order, high BMI (1057.1, UI: 634.1–1576.9), high FPG (968.8, UI: 643.8–1350.2), and smoking (663.3, UI: 476.2–875.8) (see Supp Fig. S11 b).

Sustainable Development Goals

The SDG health-related indicators for Spain result in an overall index score of 74 (Fig. 4 ), similar to Japan (76), the United States (75), and the European Union (EU) (74) (Fig. 5 ). Spain ranks 20 out of 195 countries and territories included in the index. It also achieved its highest performance (100) in hygiene, sanitation, intimate partner violence, skilled birth attendance, child stunting, and physical violence. Spain performed lowest in alcohol use (8), smoking prevalence (28), child overweight (38), and HIV incidence (50).

The health-related index score for Spain is projected to reach 80 by 2030, outpacing Japan (77), the United States (76), and the EU (77; Fig. 5 ). Although, it is projected that indicators for alcohol use (12), child overweight (32), smoking prevalence (36), and child sex abuse (59) will remain poor in 2030.

Discussion

This study presents internationally comparable estimates of mortality, morbidity, and their risk factors in Spain and is the only study that has produced these estimates, with life expectancy being reported in this study and by the INE in Spain . GBD estimates for life expectancy are slightly higher compared to INE, as women were expected to live up to 86.2 years and men were expected to live up to 80.8 years; both sexes were expected to live, on average, 83.6 years.

The GBD 2019 study confirmed that NCDs, in particular IHD and cancers, are the largest contributors to morbidity and mortality in Spain. These results are similar to neighbouring European countries 10 , 20 , 21 . Musculoskeletal pathology, specifically low back pain and depression, also considerably contribute to the burden of disease, especially for women. These results highlight the influence of sedentary lifestyles 22 , 23 and population ageing on the disease burden in Spain, the latter partially a positive consequence of the long-term benefits associated with improvements to the built environment that foster more physical activity 24 , advancement in occupational health and safety 25 , increases in educational attainment 26 , and universal healthcare 1 . In particular, in its 2018 review of SDG processes in Spain, the national government highlighted the importance of population-wide free-of-charge universal access to the health system, so as to enable attainment of the health targets under SDG 3: “Ensure healthy lives and promote well-being for all at all ages” 27 . In 2021, Spain formally renewed its commitment to the SDGs and issued a detailed 350-page report identifying 8 major challenges, of which health and public health are cross-cutting themes 28 . Several of the authors of this article contributed to this report, based on preliminary findings. Operationally, concrete actions to reach the SDGs will be largely within the purview of the 17 regions.

Like much of Europe, Spain has experienced rapid levels of population ageing due to increases in life expectancy and decreases in mortality and fertility since the mid-1990s 29 . Addressing population ageing requires a focus on health promotion and elderly care through strengthening long-term care facilities, social support services, and telehealth. In particular, monitoring of quality of life, functionality, and multimorbidity is even more important as the population ages 30 , 31 . Social protection benefits, such as pensions or sick leave, are key public health interventions that can help to offset cost-related issues of population ageing 32 . However, it is important to note that these policies may not reach those employed outside of the formal employment system. The influence of the Mediterranean diet has offered protective health benefits for aging populations, including in Spain 33 – 36 . However, such benefits are threatened by results in 2019, such as high FPG and high BMI, which are risk factors for cardiovascular 37 and metabolic diseases such as diabetes 38 , which are among the top 10 causes of death.

Additionally, targeted approaches in national planning and the decentralised subnational service delivery of healthcare services should address the burden of other NCDs such as IHD, low back pain, and depressive disorders, which drive DALYs and YLDs. Consistent with our results, recent research in Spain identified a disproportionate burden of low back pain among women compared to men 39 , while earlier studies identified the reverse relationship 40 , 41 . Low back pain significantly impacts economic productivity and worker health 42 , and is important to address through occupational health interventions 43 in addition to health services, which are already well-used 39 . In contrast, mental health services are underutilised in Spain 44 , possibly indicating problems with access to such services. Improving mental health services is also challenged by a lack of coordination across regions and sectors in the past decade 45 , 46 . Symptoms of depression and other mental health issues, which are disproportionately experienced by women 47 – 49 and vulnerable groups 50 , 51 , have become more prevalent 52 and are most associated with lower education and income 49 . Gender inequalities in the diagnoses of mental health disorders may be attributed to socio-cultural factors. Notably, the pathologisation of “feminine attributes”, such as emotional expression, may lead women to be more diagnosed with mental health problems than men, who are more likely to conceal their emotions 49 . Further intersecting with gender is age and social vulnerability, whereby older and other vulnerable patients, viewed as less resilient to suffering, are more likely to be diagnosed with mental health problems. This issue should also be addressed through a public health approach, recognising the overlapping and intersecting nature of the social determinants of health 2 .

This study’s results show that some behavioural and metabolic factors, such as smoking, diet, BMI, and FPG contribute heavily to the burden of disease in Spain, much like neighbouring European countries 20 . This must be adequately addressed by public health approaches that address population risk factors. For example, public policy should consider obesogenic environments that contribute to sedentary lifestyles and should be re-designed using a public health approach by, for instance, encouraging regular physical activity, healthy eating, and smoking cessation and prevention 2 , 53 – 56 . Improving primary care services will enable better implementation of interventions to promote behavioural changes related to health habits and mental health promotion. For example, the incorporation of behavioural health and quality of life or well-being tools with patient-reported outcomes into primary care delivery can improve system diagnostic and referral capacities 57 , 58 . Furthermore, anti-smoking legislation, such as removing tobacco vending machines, should be strengthened to address child and adolescent smoking, particularly in males 59 , 60 , and to better align with the WHO Framework Convention on Tobacco Control, of which Spain is a signatory 61 .

Policymakers must also consider non-optimal ambient temperatures, which, despite decreases in recent years of low-temperature related mortality 62 , have significantly contributed to morbidity in Spain. It might be useful to extend the National Plan for Preventive Actions Against the Health Effects of Excess Temperatures, to implement both low temperature and heat adaptation strategies sub-nationally, which have demonstrated effectiveness in other high-income countries 63 . In addition to warmer temperatures, which are projected to increase, policymakers must also consider sub-national approaches to address the continued impacts of low temperatures, which may contribute to higher mortality among vulnerable groups in some regions of in Spain 64 , 65 .

Between March and May 2020, COVID-19 ranked as the leading cause of mortality in Spain 66 and in November 2022 Spain continued to rank among the first dozen countries in total number of confirmed cases 67 . The pandemic has led to a healthcare provision crisis that greatly decreased access to many routine health services and, during peak waves, access to critical equipment such as intensive care unit beds and artificial ventilators. The downstream effects of unattended acute and chronic conditions 68 , especially mental health problems, will exacerbate morbidity and mortality projections in Spain. Multiple sets of concrete recommendations to manage COVID-19 have been issued targeting Spain specifically 69 , and in a recent global Delphi study, co-led by Spanish authors 70 . However, a major challenge in Spain remains to be coordination among the 17 regions and the national government. Our study provides the 2019 results of disease burden and risk factors in Spain, so that health researchers and decision makers have a pre-pandemic baseline to compare pandemic findings to.

Future avenues

While it is important to understand mortality and morbidity and their drivers, this data is insufficient to inform adequate public health interventions. Further studies, based on the results presented, are necessary to create appropriate and equitable evidence-based interventions for public health. Future research must focus on health equity within Spain that, in addition to sex and age disparities, investigates the drivers of disparities among vulnerable groups, who may be disproportionately impacted by policies. Spain should strive to ensure that standardised data at the regional level is available to inform research and decision making, and, where possible, include disaggregated data by specific vulnerable groups, such as migrants and people experiencing homelessness, as well as different occupational categories. GBD should endeavour to assess mortality, morbidity, and risk by these populations as well. Future studies should consider examining further lifestyle and behavioural factors that contribute significantly to morbidity and mortality in Spain, especially smoking, alcohol use, and sedentary lifestyles. Considering the 2008 financial crisis and the ongoing COVID-19 pandemic, future research should aim to examine how these experiences have influenced and will continue to impact on the health trajectory of Spain, including in each of the 17 regions, especially in terms of mental health and access to care more broadly. In particular, the at least eight waves of the COVID-19 pandemic experienced to date in Spain, and any subsequent ones, will require a paradigm shift. A change in care models in primary care services and selected hospital services is envisaged, given the expected high frequency of Long COVID patients and all sequelae of COVID-19, which will require care and attention within often limited available resources 71 . Finally, the relatively low burden of infectious diseases in Spain has led to their de-prioritisation in public health research focused on Spain. This field would benefit from an analysis of infectious diseases pre-, during, and after the pandemic and in relation to changing trends in ambient temperatures.

Strengths and limitations

The primary limitation of the GBD Study is the availability of primary data. In the case of Spain, coding was performed by Spain’s INE , the most important data source for GBD estimates for Spain, and is considered among the best in terms of validity and completeness of data within WHO’s European Region. Despite this, there might be difficulties representing the full uncertainty around estimates due to discrepancies in coding and definitions between INE and GBD. However, this study did not compare GBD estimates for Spain with data from Spain. Detailed explanations of the limitations of each specific model in GBD 2019 are reported elsewhere 57 .

Additionally, GBD data are available at the subnational level for 22 countries but not for Spain, which should provide this information as well. Furthermore, Spain does not have its own disability weights, and these are derived from studies in other countries, which challenges the accuracy of these results.

Regarding the SDG projections, a major strength is that it is a single and robust measurement that is useful for policymakers to interpret and compare the performance on all health-related SDG measures. Moreover, it can help to better understand progress overtime for all indicators. However, data sparsity and variations in case-definitions may lead to underreporting and uncertainty of particular outcomes. Furthermore, the COVID-19 pandemic will have likely affected several health dimensions in 2020 and 2021, and possibly beyond. However, the research presented in this study establishes a unique baseline for future research on the impact of the COVID-19 pandemic.

Conclusion

Similar to recent analyses of the burden of disease in Spain, non-communicable diseases, particularly cardiovascular diseases, continued to be the predominant cause of morbidity and mortality in 2019. Behavioural risks, such as smoking and poor diet, and environmental risks, such as non-optimal temperatures, contributed substantially to the disease burden, indicating focus areas for prevention for health authorities. The health system should also address the consequences of population ageing, such as morbidity from musculoskeletal conditions and Alzheimer’s disease, in addition to the long-term impacts of the COVID-19 pandemic, including Long COVID, which threaten health-related SDG progress.

Supplementary Information

Supplementary Information.

Acknowledgements

The GBD Study is funded by the Bill and Melinda Gates foundation. J.V.L., D.G., and T.M.W. acknowledge support to ISGlobal from the Spanish Ministry of Science, Innovation and Universities through the ‘‘Centro de Excelencia Severo Ochoa 2019-2023’’ Programme (CEX2018-000806-S), and from the Government of Catalonia, Spain, through the CERCA Programme. J.L.A-M. was funded by the Instituto de Salud Carlos III (Grant Number PI19/00150). I.G-V. was supported by the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación. A.O. was funded by the Instituto de Salud Carlos III (ISCIII) RICORS program to RICORS2040 (RD21/0005/0001), European Union—NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR) and SPACKDc PMP21/00109, and FEDER. E.F. is partly supported by the Ministry of Universities and Research, Government of Catalonia (2017SGR319) and receives institutional support from IDIBELL. R.T-S. is supported by the Spanish Ministry of Science and Innovation, Institute of Health Carlos III, and INCLIVA (PID2021-129099OB-I00).

Author contributions

J.V.L., J.B.S., A.O., S.T., E.F., D.G., T.M.W., and R.M. prepared the first manuscript draft. S.I.H. and M.N. provided overall guidance upon further revision. J.V.L., J.B.S., D.G., T.M.W., and R.M. analysed the data and prepared the tables and figures. GBD Spain Collaborators finalised the manuscript on the basis of comments from other authors and the reviewers’ feedback. J.V.L. and J.B.S. were responsible for the decision to submit. All other authors provided data, developed models, reviewed results, provided guidance on methods, and/or reviewed the manuscript.

Data availability

To download the data used in these analyses, please visit the Global Health Data Exchange GBD 2019 website ( http://ghdx.healthdata.org/gbd-2019 ).

Competing interests

J.V.L. reports grants from AbbVie, Gilead Sciences, MSD, and Roche Diagnostics; consulting fees from NovoVax; payment or honoraria for lectures, presentations, speakers’ bureaus, and educational events from AbbVie, Gilead, Sciences, Intercept, and Janssen; participation on a Data Safety Monitoring Board with the QuickStart Study; and leadership, unpaid, with the EASL international Liver Foundation and HIV Outcomes; all outside the submitted work. A.O. reports (all outside the submitted work) grants from Sanofi and consultancy or speaker fees or travel support from Advicciene, Astellas, Astrazeneca, Amicus, Amgen, Fresenius Medical Care, GSK, Bayer, Sanofi-Genzyme, Menarini, Kyowa Kirin, Alexion, Idorsia, Chiesi, Otsuka, Novo-Nordisk, and Vifor Fresenius Medical Care Renal Pharma and is Director of the Catedra Mundipharma-UAM of diabetic kidney disease and the Catedra Astrazeneca-UAM of chronic kidney disease and electrolytes. All other authors declare no competing interests.

Footnotes

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Contributor Information

Jeffrey V. Lazarus, Email: Jeffrey.Lazarus@isglobal.org

The GBD 2019 Spain Collaborators:

Alberto L. García-Basteiro , Jose L. Ayuso-Mateos , Quique Bassat , Fernando G. Benavides , Iago Giné-Vázquez , Josep Maria Haro , Ai Koyanagi , Jose Martinez-Raga , Alicia Padron-Monedero , José L. Peñalvo , Jorge Pérez-Gómez , David Rojas-Rueda , Rodrigo Sarmiento-Suárez , and Rafael Tabarés-Seisdedos

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-022-24719-z.

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Associated Data

Supplementary Materials

Supplementary Information.

Data Availability Statement

To download the data used in these analyses, please visit the Global Health Data Exchange GBD 2019 website ( http://ghdx.healthdata.org/gbd-2019 ).