What does it drive the relationship between cardiovascular disease mortality and economic development? New evidence from Spain

Abstract

Background
During the last decades, there has been a great interest on the link between macroeconomic conditions and health. More precisely, many studies had studied as health outcome cardiovascular disease mortality, focusing in different countries, determinants, and using numerous econometric techniques. Due to its importance, in this paper, we analyse cardiovascular disease mortality across the 17 Spanish regions over the period 2002–2019.

Methods
In doing so, we estimated several panel data models considering differences by sub-periods of time while also considering gender differences. That is, we transmit a difference on previous evidence by considering a longer period of time and different explanatory factors, so we provide new highlights for Spain.

Results
Our empirical results show that: (i) both socioeconomic and environmental factors have a significant importance; (ii) political factors appear not to be significant; and (iii) there exists a Mediterranean (macro-region) cardiovascular disease mortality pattern.

Conclusions
These results may have usefulness for cardiovascular disease mortality prevention in Spain.

Full text

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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
https://doi.org/10.1186/s13561-025-00594-y
services and overall health outcomes. Precisely, there is a
particular interest in mortality [1]. In fact, since the semi-
nal paper of Ruhm [2] it could be said that there have
appeared several studies that analyse the relationship
between economic conditions and health, while using
both dierent data and econometric techniques. But,
there is not yet a consensus about mortality being coun-
tercyclical or procyclical.
In this regard, one of the main health outcomes stud-
ied in this literature on macroeconomic conditions and
health, is cardiovascular disease mortality (CVDM). is
circumstance is not unexpected since cardiovascular dis-
eases (coronary heart disease, cerebrovascular disease,
rheumatic heart disease and other conditions) are the
Background
ere is widely empirical literature on the link between
macroeconomic conditions and health, outcomes and
results. at is, the empirical literature shows that mac-
roeconomic conditions can signicantly inuence the
health of populations, aecting both access to health
Health Economics Review
*Correspondence:
Carla Blázquez-Fernández
carla.blazquez@unican.es
1Department of Economics, Universidad de Cantabria, Santander
39005, Spain
2Health Economics Research Group-Valdecilla Health Research Institute
(IDIVAL), Santander 39011, Spain
3Santander Financial Institute– SANFI, Santander, Spain
Abstract
Background During the last decades, there has been a great interest on the link between macroeconomic
conditions and health. More precisely, many studies had studied as health outcome cardiovascular disease mortality,
focusing in dierent countries, determinants, and using numerous econometric techniques. Due to its importance, in
this paper, we analyse cardiovascular disease mortality across the 17 Spanish regions over the period 2002–2019.
Methods In doing so, we estimated several panel data models considering dierences by sub-periods of time while
also considering gender dierences. That is, we transmit a dierence on previous evidence by considering a longer
period of time and dierent explanatory factors, so we provide new highlights for Spain.
Results Our empirical results show that: (i) both socioeconomic and environmental factors have a signicant
importance; (ii) political factors appear not to be signicant; and (iii) there exists a Mediterranean (macro-region)
cardiovascular disease mortality pattern.
Conclusions These results may have usefulness for cardiovascular disease mortality prevention in Spain.
Keywords Cardiovascular disease mortality, Economic development, Panel data, Spain
What does it drive the relationship
between cardiovascular disease mortality
and economic development? New evidence
from Spain
CarlaBlázquez-Fernández1,2* and DavidCantarero-Prieto1,2,3
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
leading cause of death around the globe, taking around
17.9million lives each year [3]. Moreover, it imposes a
substantial economic burden in developed countries [4].
e relationship between cardiovascular disease (CVD)
and gross domestic (Gross Domestic Product, GDP) is
multifaceted and is inuenced by several factors. Firstly, a
higher GDP can lead to better health outcomes, including
lower mortality rates from CVD due to improved treat-
ment options and healthcare access. Secondly, a higher
GDP typically correlates with socio-economic factors
such as better education levels, which promote healthier
lifestyle choices and greater awareness of health risks
associated with CVD. irdly, environmental factors
like pollution and urbanization can exacerbate the risk
of CVD; however, wealthier nations may invest in green
spaces that encourage physical activity, mitigating some
risks. Indeed, as pointed by Kelly and Fuster [5] there is
complex interaction among average per capita income in
a country, trends in lifestyle, and other risk factors, and
health systems capacity to control CVD.
en, dierent studies have analysed, using as proxies
for macroeconomics conditions data related with income
(GDP) or unemployment rates, CVDM. Besides, recent
studies have highlighted the harmful impact on several
health outcomes (including cardiovascular health) such
as concentration of pollutants [6–7] and/or economic
and policy uncertainly [8–9].
In this respect, Spiteri and von Brockdor [6] exam-
ined the connection between economic development
and health outcomes. Initially, they estimated an empiri-
cal model utilizing data on annual mortality rates from
cardiovascular diseases across a panel of European coun-
tries, along with the per capita GDP levels for each coun-
try. Additionally, they incorporated several other factors
inuencing health outcomes as outlined in the literature,
which include various socio-economic, lifestyle, and
environmental/contextual variables. For these environ-
mental/contextual variables, total emissions of ne par-
ticulate matter (PM2.5) were considered. In fact, in the
review by Al-Kindi et al. [7] it is highlighted how air pol-
lution is the most important environmental cardiovascu-
lar risk factor, with ne particulate matter (PM2.5) and
ozone gas being the most-studied air pollutants.
As for economic and policy uncertainly, both Kawachi
et al. [8] and Kyriopoulos et al. [9] found that economic
uncertainty is positively and signicantly associated with
cardiovascular disease mortality. So, they uncovered yet
another risk factor for cardiovascular health and empha-
sized the signicance of uncertainty alongside current
economic developments and conditions. at is to say,
they illustrated how uncertainty acts as a stressor and a
catalyst for cardiovascular mortality. In their approxima-
tions both trusted on the Economic Policy Uncertainty
(EPU) index.
In this framework, Spain provides a good scenario to
examine deaths from cardiovascular diseases because
since the ‘‘Great Recession’’ this country has experi-
enced one of the poorest economic circumstances [10].
In Spain, according to the latest report from the National
Institute of Statistics [11] on the causes of death, car-
diovascular disease continues to be the leading cause of
death, representing 26% of all deaths, being therefore
above cancer (24,8%) and respiratory system diseases
(19.3%).
Our main objective is to study the determinants/factors
and patters of CVDM using regional data for 2002–2019
from Spain. e analysis is also conducted for three dis-
tinct key business cycle periods of this century in Spain:
(i) ‘‘Great Expansion’’ (2002–2007), (ii) ‘‘Great Recession’’
(2008–2013), and (iii) “Recovery” (2014–2019). Besides,
the analysis is stratied by sex. erefore, we use panel
data models in the methodology. In order to do so, we
transmit a dierence on previous studies by considering
both a longer period of time and dierent explanatory
factors, so we provide new highlights for CVDM preven-
tion in Spain.
Methods
In order to analyse the dierent indicators/factors
through which deaths from cardiovascular diseases
may be aected in Spain, while also identifying patters,
three 6-year periods according to three dierent busi-
ness cycles scenarios are studied1,2: 2002–2007 (named
as “Great Expansion”), 2008–2013 (denoted as “Great
Recession”), and 2014–2019 (known as “Recovery”). e
units under examination are the 17 Spanish regions.
In doing so, we consider four subgroups of indicators/
factors: (i) socioeconomic, (ii) environmental, (iii) politi-
cal, and (iv) regional. All in all, the selected variables are
based on restrictions with data and the insights obtained
from previous empirical evidence (highlighted in the
Background section).
Precisely, we used regional annual data on deaths
from diseases of the circulatory system. To obtain data
for cause-specic mortality, we relied on the Span-
ish National Institute of Statistics (INE) after that, the
authors calculated the mortality rates adjusting by the
corresponding population data also available in the INE
(Population Structure Indicators - resident population
by date, sex and age (since 1971) by Autonomous Com-
munities). Being this variable our dependent one. is
variable is used both considering total population and
distinguishing by gender.
As for independent variables, annual gross domestic
product per capita, measured in current euros, would
1 e Covid-19 period in not considered.
2 Nonetheless, results are compared with the full sample period 2002–2019.
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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
be used to collect the socioeconomic context. is vari-
able is obtained through the Spanish regional accounting
section of the INE. Besides, population-weighted average
of annual average PM2.5 concentration (μg/m3) is the
one selected to measure the environmental regional fac-
tors. is information is available also through the INE.
Exactly, this can be found in the periodical publications-
quality of life indicators-environment and environment.
In addition, to capture political factors the Economic Pol-
icy Uncertainty Index for Spain is used. is indicator is
obtained from Andres-Escayola et al. [12]. e informa-
tion considered is the total annual average calculated by
the authors. is variable will be common for the entire
territory. Finally, a dummy for a macroregion, Mediter-
ranean, is created to study in deep the regional factors.
Table1 summarized the variables used and their sources
of information.
e empirical method is so based on panel data mod-
els. Our model generally becomes as follows:
lnCV DM it =f(xit ,β)+ ϵit
(1)
where:
i = Region (where i = 1,…, 17),
t = Year (where t = 2002,…, 2019),
Ln = Natural logarithm,
Xit
= Matrix of explanatory variables,
β
= Vector of parameters to be estimated,
ϵit
= Error term.
In our empirical estimates, in order to correct equally
possible problems of contemporaneous correlation and
heteroscedasticity, panel-corrected standard errors
(PCSE) are used.
en, derived from Eq.(1), the general specication in
this study can be described as follows:
lnCV DM it =(x′it β)+αi+ϵit
(2)
where
αi
is a region-specic eect.
As a result, Eq.(3) represents our nal specication:
lnCV DMit
=
αi
+
β1
(
lnGDP pcit
)+
β2(lnP m2.5it)+β3(l nEP Ut)+
β
4
(Mediterranean
i
)+ ϵ
it
(3)
Further information about the variables is provided both
in Tables2 and 3. Specically, in Table2, the summary
statistics are presented. Besides, cardiovascular disease
mortality (in persons) total and by sub-periods is shown
in Table3.
Based on our initial analysis of the data, we observe a
decline in mortality rates from cardiovascular disease
during the period from 2019 to 2022. Furthermore, it
appears that women are more signicantly impacted than
men. While cardiovascular disorders are a major cause
of death for both genders, women tend to have a poorer
prognosis. However, we will provide a more detailed
descriptive analysis, complete with gures, in the follow-
ing results section.
Table 1 Description of variables and sources
Category Variable Description Source
Dependent variable Cardiovascular disease
mortality rate (CVDM)
Deaths by cardiovascular diseases per 100 000 popu-
lation (crude rates)
Spanish National Institute
of Statistics (INE) and
authors’ elaboration.
Socioeconomic explanatory
variable
GDP per capita (GDPpc) Annual Gross Domestic Product (GDP) per capita,
measured in current euros
Spanish National Institute
of Statistics (INE).
Environmental explanatory
variable
PM2.5 Population-weighted average of annual average
PM2.5 concentration (μg/m3)
Spanish National Institute
of Statistics (INE).
Political explanatory variable EPU Economic Policy Uncertainty Index for Spain Andres-Escayola et al. [12]
Regional explanatory variable Mediterranean 1 if the region is located on the “Mediterranean area”
of Spain, 0 otherwise
Authors’ elaboration.
Source: Authors’ elaboration
Table 2 Summary statistics
Variable Mean Standard
Deviation
Maximum Minimum
CVDM_total 280.649 57.978 148.460 420.510
CVDM_females 260.355 52.199 143.930 381.410
CVDM_males 300.398 64.387 144.130 460.350
GDPpc 22,337.250 4750.933 11592.000 36206.000
PM2.5 12.536 3.610 6.300 29.000
EPU 111.633 41.577 57.910 222.483
Mediterranean 0.353 0.479 0 1
Notes: Observations are 306 for all variables except PM2.5 that equals 202
(information is not available for the entire period nor is it completely identical
for the regi ons)
Source: Authors’ elaboration
Table 3 Cardiovascular disease mortality (persons) by sub-
periods (Spain, total regions)
Full period
2002–2019
Great
expansion
2002–2007
Great
recession
2008–2013
Recovery
2014–
2019
Total 2,192,433 751,240 719,886 721,307
Females 1,190,640 408,924 392,410 389,306
Males 1,001,793 342,316 327,476 332,001
Source: Authors’ elaboration
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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
Results
In order to gain a better understanding of the data, we
explore cardiovascular disease mortality (our dependent
variable), both across time and regions. Hence, in Fig.1
it is plotted the evolution of CVDM (deaths per 100,000-
crude rates) by regions. Regarding gender dierences,
Fig.2 represents the distribution macro-regions.3,4
It can be observed, as was previously highlighted,
a reduction under the period under study. Moreover,
that the highest percentages are for Northern regions
whereas the lowest are form Mediterranean ones. As was
announced, higher percentages are for females.
3 As climatic factors could play a major role when explaining health results
from cardiovascular diseases [13], three macro-regions are considered:
North, Mediterranean and Centre.
4 North (Asturias, Cantabria, Galicia and Basque Country), Mediterranean
(Andalusia, Balearic Islands, Canary Islands, Catalonia, Valencian Commu-
nity and Murcia), Centre (Aragon, Castile and Leon, Castile-La Mancha,
Extremadura, Madrid, Navarre Community and La Rioja).
e empirical results are presented in Tables4, 5, 6 and
7. ereby, in Table4 results for the full period (2002–
2019) are presented both for totals and disaggregating by
gender.
Besides, Tables5, 6 and 7 contain by subsamples (total,
females, and males) the comparative results by the above-
mentioned sub-periods of time (“Great Expansion”,
“Great Recession”, and “Recovery”).
From all these tables it can be observed that the coef-
cients are statistically signicant and have, in most of
the cases, the expected sign. Besides, it can be appreci-
ated that the ndings are robust and consistent by gender
and by sub-periods of time. en, focusing in our four
subgroups of indicators/factors (socioeconomic, environ-
mental, political and regional) it can be highlighted the
following insights.
On the one hand, per capita GDP, has a negative/
reverse eect on the mortality rates due to cardiovas-
cular diseases. at is, an increase in GDP would lead a
Fig. 1 Evolution of cardiovascular disease mortality (deaths per 100,000-crude rates) by Autonomous community in Spain (17 regions)
Notes: Andalusia (region = 1), Aragon (region = 2), Asturias (region = 3), Balearic Islands (region = 4), Canary Islands (region = 5), Cantabria (region = 6), Cas-
tile and Leon (region = 7), Castile-La Mancha (region = 8), Catalonia (region = 9), Valencian Community (region = 10), Extremadura (region = 11), Galicia
(region = 12), Madrid (region = 13), Murcia (region = 14), Navarre Community (region = 15), Basque Country (region = 16), and La Rioja (region = 17)
Source: Authors’ elaboration
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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
reduction in mortality. On the other hand, PM2.5 concen-
tration shows a positive eect on cardiovascular disease
mortality. us, an increase in this pollutant would result
in an increase in mortality. Surprisingly, no signicant
eect is found for Economic Policy Uncertainty. Finally,
the Mediterranean regional factor appears to have a
negative relationship with CVDM. erefore, climatic
factors could play a major role when explaining health
results from cardiovascular diseases.
Discussion
is study complements to previous recent studies done
for Spain such as the one of Regidor el al. [14] or Cer-
vini-Plá and Vall-Castelló [1] that analysed economic
circumstances and mortality in Spain, or those form the
international perspective that specially focus on cardio-
vascular disease mortality and economic development
such as Spiteri and von Brockdor [6].
Our preliminary analysis showed a decrease in CVDM
during the period under consideration and that the low-
est values were found by Mediterranean regions. Indeed,
Table 4 Cardiovascular disease mortality (deaths per 100,000-crude rates), panel-corrected standard error (PCSE), considering gender
dierences, 2002–2019
Variable Log CVDM_total Log CVDM_females Log CVDM_males
Ln GDPpc -0.522 *** -0.558 *** -0.482 ***
(0.029) (0.029) (0.030)
Ln Pm2.5 0.184 *** 0.239 *** 0.122 ***
(0.046) (0.052) (0.041)
Ln EPU 0.029 0.051 0.004
(0.049) (0.050) (0.049)
Mediterranean -0.299 *** -0.330 *** -0.261 ***
(0.014) (0.015) (0.014)
Constant 10.319 *** 10.519 *** 10.110 ***
(0.313) (0.327) (0.313)
R-squared 0.454 0.497 0.384
Wald chi2 985.45 968.42 878.70
Prob > chi2 0.000 0.000 0.000
Notes: Standa rd errors are repor ted in parenthesis. ***, **, and * denote signic ant at 1%, 5%, and 10%. O bservations: 220
Fig. 2 Distribution of cardiovascular disease mortality (deaths per 100,000-crude rates) by macro-region (North, Mediterranean, Centre), mean 2002–2019
Source: Authors’ elaboration
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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
Table 5 Cardiovascular disease mortality (log CVDM_total), panel-corrected standard error (PCSE), considering sub-periods of time
Variable Full period
2002–2019
Great expansion
2002–2007
Great recession
2008–2013
Recovery
2014–2019
Ln GDPpc -0.522 *** -0.477 *** -0.555 *** -0.525 ***
(0.029) (0.026) (0.020) (0.041)
Ln Pm2.5 0.184 *** 0.274 *** 0.259 ***
(0.046) (0.063) (0.055)
Ln EPU 0.029 0.017 -0.013 -0.115
(0.049) (0.060) (0.025) (0.180)
Mediterranean -0.299 *** -0.170 *** -0.319 *** -0.332 ***
(0.014) (0.014) (0.017) (0.016)
Constant 10.319 *** 10.394 *** 10.610 *** 10.924 ***
(0.313) (0.396) (0.239) (0.915)
Observations 220 102 95 102
R-squared 0.454 0.487 0.493 0.515
Wald chi2 985.45 345.07 2427.70 1054.22
Prob > chi2 0.000 0.000 0.000 0.000
Notes: Standa rd errors are repor ted in parenthesis. ***, **, and * denote signic ant at 1%, 5%, and 10%
Table 6 Cardiovascular disease mortality (log CVDM_females), panel-corrected standard error (PCSE), considering sub-periods of time
Variable Full period
2002–2019
Great expansion
2002–2007
Great recession
2008–2013
Recovery
2014–2019
Ln GDPpc -0.558 *** -0.523 *** -0.581 *** -0.573 ***
(0.029) (0.028) (0.018) (0.040)
Ln Pm2.5 0.239 *** 0.339 *** 0.317 ***
(0.052) (0.075) (0.057)
Ln EPU 0.051 0.000 -0.002 -0.125
(0.050) (0.064) (0.027) (0.177)
Mediterranean -0.330 *** -0.173 *** -0.348 *** -0.364 ***
(0.015) (0.016) (0.020) (0.017)
Constant 10.519 *** 10.988 *** 10.746 *** 11.379 ***
(0.327) (0.427) (0.242) (0.901)
Observations 220 102 95 102
R-squared 0.497 0.502 0.532 0.561
Wald chi2 968.42 346.39 2036.57 731.38
Prob > chi2 0.000 0.000 0.000 0.000
Notes: Standa rd errors are repor ted in parenthesis. ***, **, and * denote signic ant at 1%, 5%, and 10%
Table 7 Cardiovascular disease mortality (log CVDM_males), panel-corrected standard error (PCSE), considering sub-periods of time
Variable Full period
2002–2019
Great expansion
2002–2007
Great recession
2008–2013
Recovery
2014–2019
Ln GDPpc -0.482 *** -0.423 *** -0.527 *** -0.472 ***
(0.030) (0.024) (0.024) (0.043)
Ln Pm2.5 0.122 *** 0.200 *** 0.194 ***
(0.041) (0.053) (0.056)
Ln EPU 0.004 0.033 -0.026 -0.100
(0.049) (0.058) (0.023) (0.185)
Mediterranean -0.261 *** -0.167 *** -0.284 *** -0.294 ***
(0.014) (0.011) (0.015) (0.016)
Constant 10.110 *** 9.725 *** 10.493 *** 10.393 ***
(0.313) (0.374) (0.261) (0.946)
Observations 220 102 95 102
R-squared 0.384 0.435 0.428 0.440
Wald chi2 878.70 334.90 2775.67 1361.43
Prob > chi2 0.000 0.000 0.000 0.000
Notes: Standa rd errors are repor ted in parenthesis. ***, **, and * denote signic ant at 1%, 5%, and 10%
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

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Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
dierent studies had addressed climatic inuences on
cardiovascular diseases [13]. In this regard, Achebak et al.
[15] studied, in Spain, the temporal changes in the eect
of ambient temperature on both age-specic and sex-
specic cardiovascular mortality risk. Also, the highest
values were for females [16].
Furthermore, our empirical results have highlighted the
relevance of both socioeconomic and environmental fac-
tors over time. en, our ndings are in accordance with
the results of the review by Lago-Peñas et al. [17] who
concluded that, in OECD countries, low socioeconomic
status appears to have a consistent and signicant eect
on mortality and morbidity caused by noncommunicable
diseases and with Hayes et al. [18] that pointed out the
relevance of air quality cardiovascular disease mortality.
However, no signicant eects for political factors
have been observed in this study. One possible explana-
tion is that we focus on cardiovascular disease mortality
and not study neither cardiovascular disease events nor
its derived hospitalizations. Besides, the ndings must
be considered in light of the Spanish national health care
system (universal). Furthermore, we relied on yearly data.
All in all, in spite not reporting in this study signicant
results for EPU, exploring more in deep its eects in
future research, when more data would be oered, would
be really interesting. Specically, analysing the COVID-
19 pandemic and later period outcomes (subsequent
6-year period: 2020–2025) and, when possible, using
monthly versus yearly data.
is study is subject to limitations and we must com-
ment on them. First of all, we only work with aggregate/
macro data, so we cannot control for individual char-
acteristics that could aect to CVDM. In second place,
other important factors, such as those related with life-
styles and/or psychological ones, due to lack of informa-
tion at a macro-region level could not be nally included.
Anyhow, our results may have some usefulness for
cardiovascular disease control and prevention in Spain.
at is, public health strategies should consider these
facts when trying to do an ecient use of (the scarce)
resources. As macro-level circumstances have been high-
lighted, it would be advantageous to create particular
policy measures to counter major events that give rise
to them, such as: low income and/or high concentra-
tion of pollutants. What is more, due to the importance
of CVDM it should be a priority of the national health
care system to guarantee equitable access to cardiovas-
cular technologies, which had been proved as stated by
De la Torre Hernández et al. [19] to have led to consid-
erable advances in cardiology and a notable reduction in
CVDM.
Conclusions
e goal of this study was to analyse the dierent deter-
minants/factors through which deaths from cardiovascu-
lar diseases may be aected in Spain while also identify
patterns and during the 21st century. e analysis has
been developed for the 17 Spanish regions during the
period 2002–2019, while considering dierent sub-peri-
ods, here understood as: (i) ‘‘Great Expansion’’, (ii) ‘‘Great
Recession’’, and (iii) “Recovery”. e results have high-
lighted: (i) the importance of both socioeconomic and
environmental factors; (ii) that political factors appear
not to be signicant; and (iii) that there exists a Mediter-
ranean (macro-region) cardiovascular disease mortality
rule.
Abbreviations
CVDM Cardiovascular disease mortality
CVD Cardiovascular disease
GDP Gross Domestic Product
INE Spanish National Institute of Statistics
Acknowledgements
Not applicable.
Author contributions
All the authors contributed to the writing of the manuscript and read
and approved the nal manuscript. Conceptualization: C.B-F. and D.C-P.;
Methodology: C.B-F. and D.C-P.; Formal analysis: C.B-F.; Writing - Original Draft:
C.B-F.; Writing - Review & Editing: C.B-F. and D.C-P.; Supervision: D.C-P. The
corresponding author, C.B-F., 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.
Funding
This work was partially supported by the European Commision (H2020-SC1-
DTH-2020-1-101017424; Project: A patient-centered early risk prediction,
prevention, and intervention platform to support the continuum of care in
coronary artery disease (CAD) using eHealth and articial intelligence), TIMELY
had no role in the design and collection, analysis, interpretation of data or in
writing the manuscript.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Received: 5 July 2024 / Accepted: 28 January 2025
References
1. Cervini-Plá M, Vall-Castelló J. Business cycle and mortality in Spain. Eur J
Health Econ. 2021;22(8):1289–99. h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 0 1 9 8 - 0 2 1 - 0 1 3 3
6 - 7
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 8 of 8
Blázquez-Fernández and Cantarero-Prieto Health Economics Review (2025) 15:6
2. Ruhm CJ. Are recessions good for your health? Qual J Econ. 2000;115(2):617–
50. h t t p s : / / d o i . o r g / 1 0 . 1 1 6 2 / 0 0 3 3 5 5 3 0 0 5 5 4 8 7 2
3. WHO. Cardiovascular diseases. 2023. Ocial website. Available at: h t t p s : / / w
w w . w h o . i n t / h e a l t h - t o p i c s / c a r d i o v a s c u l a r - d i s e a s e s # t a b = t a b _ 1 (Latest access:
November 8, 2023).
4. Luengo-Fernandez R, Walli-Attaei M, Gray A, Torbica A, Maggioni AP, Huculeci
R,…Leal J. Economic burden of cardiovascular diseases in the European
Union: a population-based cost study. Eur Heart J. 2023;44(45):4752-67. h t t p s :
/ / d o i . o r g / 1 0 . 1 0 9 3 / e u r h e a r t j / e h a d 5 8 3.
5. Kelly BB, Fuster V, editors. Promoting cardiovascular health in the developing
world: a critical challenge to achieve global health. 2010.
6. Spiteri J, von Brockdor P. Economic development and health outcomes:
evidence from cardiovascular disease mortality in Europe. Soc Sci Med.
2019;224:37–44. h t t p s : / / d o i . o r g / 1 0 . 1 0 1 6 / j . s o c s c i m e d . 2 0 1 9 . 0 1 . 0 5 0
7. Al-Kindi SG, Brook RD, Biswal S, Rajagopalan S. Environmental determinants
of cardiovascular disease: lessons learned from air pollution. Nat Rev Cardiol.
2020;17(10):656–72. h t t p s : / / d o i . o r g / 1 0 . 1 0 3 8 / s 4 1 5 6 9 - 0 2 0 - 0 3 7 1 - 2
8. Kawachi I, Kyriopoulos I, Vandoros S. Economic uncertainty and cardiovascu-
lar disease mortality. Health Econ. 2023;32(7):1550–60. h t t p s : / / d o i . o r g / 1 0 . 1 0 0
2 / h e c . 4 6 7 8
9. Kyriopoulos I, Vandoros S, Kawachi I. State-level economic uncertainty and
cardiovascular disease deaths: evidence from the United States. Eur J Epide-
miol. 2023;28:1175–83. h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 0 6 5 4 - 0 2 3 - 0 1 0 7 6 - 3
10. Blázquez-Fernández C, Cantarero-Prieto D, Pascual-Sáez M. What does it drive
the relationship between suicides and economic conditions? New evidence
from Spain. Soc Indic Res. 2017;130:1087–99. h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 1 2 0
5 - 0 1 6 - 1 2 3 6 - 2
11. INE. Death statistics according to cause of death. 2023. Latest data. Available
at: h t t p s : / / w w w . i n e . e s / d y n g s / I N E b a s e / e n / o p e r a c i o n . h t m ? c = E s t a d i s t i c a _ C % 2
6 ; c i d = 1 2 5 4 7 3 6 1 7 6 7 8 0 % 2 6 ; m e n u = u l t i D a t o s % 2 6 ; i d p = 1 2 5 4 7 3 5 5 7 3 1 7 5 (Latest
access: November 8, 2023).
12. Andres-Escayola E, Ghirelli C, Molina L, Perez JJ, Vidal E. Using newspapers
for textual indicators: guidance based on Spanish-and portuguese-speaking
countries. Comput Econ. 2023:1–50. h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 0 6 1 4 - 0 2 3 - 1 0 4
3 3 - z
13. Abrignani MG, Lombardo A, Braschi A, Renda N, Abrignani V. Climatic inu-
ences on cardiovascular diseases. World J Cardiol. 2022;14(3):152–69. h t t p s : / /
d o i . o r g / 1 0 . 4 3 3 0 / w j c . v 1 4 . i 3 . 1 5 2
14. Regidor E, Mateo A, Barrio G, Fuente LDL. Mortality in Spain in the
context of the economic crisis and austerity policies. Am J Public Health.
2019;109(7):1043–49. h t t p s : / / d o i . o r g / 1 0 . 2 1 0 5 / A J P H . 2 0 1 9 . 3 0 5 0 7 5
15. Achebak H, Devolder D, Ballester J. Trends in temperature-related age-
specic and sex-specic mortality from cardiovascular diseases in Spain: a
national time-series analysis. Lancet Planet Health. 2019;3(7):e297–306. h t t p s :
/ / d o i . o r g / 1 0 . 1 0 1 6 / S 2 5 4 2 - 5 1 9 6 ( 1 9 ) 3 0 0 9 0 - 7
16. Townsend N, Kazakiewicz D, Lucy Wright F, Timmis A, Huculeci R, Torbica A,…
Vardas P. Epidemiology of cardiovascular disease in Europe. Nat Rev Cardiol.
2022;19(2):133–43. h t t p s : / / d o i . o r g / 1 0 . 1 0 3 8 / s 4 1 5 6 9 - 0 2 1 - 0 0 6 0 7 - 3
17. Lago-Peñas S, Rivera B, Cantarero D, Casal B, Pascual M, Blázquez-Fernández
C, Reyes F. The impact of socioeconomic position on non-communicable dis-
eases: what do we know about it? Perspect Public Health. 2021;141(3):158–
76. h t t p s : / / d o i . o r g / 1 0 . 1 1 7 7 / 1 7 5 7 9 1 3 9 2 0 9 1 4 9 5 2
18. Hayes RB, Lim C, Zhang Y, Cromar K, Shao Y, Reynolds HR,… Thurston GD.
PM2. 5 air pollution and cause-specic cardiovascular disease mortality.
International J Epidemiol. 2020;49(1):25–35. h t t p s : / / d o i . o r g / 1 0 . 1 0 9 3 / i j e / d y z 1 1
4
19. De la Torre Hernández JM, González ML, Camarero TG, Lozano DS, Cid B,
Ojeda S,… Cantarero-Prieto D. Interregional variability in the use of cardiovas-
cular technologies (2011–2019). Correlation with economic indicators, admis-
sions, and in-hospital mortality. RRev Esp Cardiol (Engl Ed). 2022;75(10):805–
15. h t t p s : / / d o i . o r g / 1 0 . 1 0 1 6 / j . r e c . 2 0 2 2 . 0 2 . 0 1 6
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