Introduction
Cancer is a result of cell growth[] where cells lose the
ability to respond to normal signals and become independent
of controls.[] By becoming independent
of the controls that regulate their behavior, these cells
gain the ability to invade nearby tissues and spread to distant regions.[] This condition, defined as excessive
proliferation of abnormal cells, indicates that cancer is
a complex disease associated with the inability of initially
differentiated cells to perform certain functions
of other organs or systems and the acquisition of different
cell functions.[] Cancer includes more than 200
different forms and hundreds of approved chemotherapeutic agents,[] and can have an impact on the social,
economic and psychological lives of patients and
their families.[,] It is recognized as a global problem
due to high mortality rates and limited healthcare access,
especially in developing countries.[]
In 2020, 10 million people will die from this disease,
and the debate on the factors that play a role in its occurrence
continues. Various lifestyle factors such as environmental
factors, radiation, chemicals, food, air, water,
nutrient pollution,[] tobacco use, red meat consumption,
lack of physical activity, obesity, and diet have been
found to be effective. In addition, psycho-social processes
such as social status, working conditions, life events
(depression, hopelessness, loss of a loved one, etc.) have
also been found to play a triggering role in the development
and progression of certain types of cancer[] and
that socio-economic conditions have a significant impact
on the occurrence and treatment of cancers.[-]
Poor individuals have less access to preventive,
early diagnosis and treatment services within the scope
of the fight against cancer,[] Individuals with low
socioeconomic status have low rates of participation
in cancer screening programs due to cost, which increases
the risk of late diagnosis.[] Because of these
factors, poor cancer patients have short life expectancy
and low quality of life.[] Studies show that lower socio-
economic status is associated with higher mortality
rates for various types of cancer.[] People with lower
socioeconomic status have been found to be more
likely to develop stomach, lung or cervical cancer.[]
Socioeconomic inequalities in cancer morbidity and
mortality have been observed with higher rates among
disadvantaged groups[] and socioeconomic factors
such as education and income level have been found
to be strongly associated with cancer incidence rates.
[,] It is argued that the differences in cancer incidence
and mortality rates between racial and ethnic
groups are mostly related to socioeconomic status.[]
In 2019, I empirically tested the relationship between
crises and cancer incidence with a multidisciplinary
approach and obtained evidence of this
cycle in a study I called "Crisis-Cancer Cycle", which
deals with the fact that anxiety disorder, anxiety and
depression seen in individuals who descend from
socio-economic rungs due to economic crises cause
telomere shortening, which in turn causes cancer.
The findings reveal that there is a bidirectional relationship
between cancer incidence and poverty; accordingly,
poverty is a cause of cancer incidence, and
cancer incidence is a cause of poverty.[] Similarly,
in another study I conducted in 2021, I found a unidirectional causality between unemployment and cancer
incidence in the short run from unemployment
to cancer incidence, suggesting that unemployment is
a cause of cancer incidence. In this context, my study
suggests that implementing policies to prevent unemployment
can reduce cancer costs and stress-related
incidence.[] Some studies support these findings,
showing that increasing levels of economic wealth can
affect changes in cancer incidence rates.[] However,
they emphasize both regional and gender disparities
and the need for corrective public policy measures.
Gender differences have significant impacts on cancer
incidence rates[-] and treatment outcomes.
Inequalities have been found between men and women
in the prevalence, incidence and severity of various diseases,
not only cancer.[] Sex-specific differences in
cancer incidence and mortality are regulated by genetic,
molecular and hormonal factors.[] In multiple nonreproductive
cancers, men are more likely to develop
cancer and experience worse clinical outcomes compared
to women.[] Sex differences in cancer phenotypes
should be considered when developing sensitive
cancer treatment plans.[] Gender-based disparities
in treatment allocation and overall survival have been
observed in advanced gastroesophageal cancer.[] Sex
differences in colorectal cancer affect disease incidence,
clinicopathologic characteristics, therapeutic outcomes
and tolerability to treatments. Understanding and addressing
these sex differences is crucial to improve cancer
diagnosis, treatment and outcomes.
The primary objective of this research is to explore
the correlation between cancer incidence rates, GDP
per capita, and inflation rate. The focus is on Denmark,
which holds the top position in global cancer
incidence rates, serving as a case study to comprehend
the dynamics in a developed nation with a high standard
of living. Gender differences are also integrated
into the empirical examination of these variables. The
methodology involves initiating the study with a literature
review, followed by in-depth analyses. Aligning
with the findings from the Crisis-Cancer Cycle
research conducted by,[,] this study adopts a
multidisciplinary approach, encompassing socio-economic
factors, sex dynamics, and cancer incidence.
Literature Review
This section will review the findings of previous research
by examining the key variables relevant to the
analyses to be conducted. First, the literature will be reviewed
where there are few studies, such as the gender
factor on cancer incidence.
Gross Domestic Product (GDP) Per Capita and
Cancer Incidence
GDP per capita is acknowledged as a crucial economic
factor influencing cancer incidence.[,,] Within
this context, a study conducted by Luzzati et al.[]
identified a direct correlation between GDP per capita
and cancer incidence. The researchs indicates that
individuals with lower personal income may exhibit
higher incidence rates for specific types of cancer.[]
Furthermore, insights from other studies underline a
significant correlation between cancer occurrence and
the middle-income group. It is emphasized that individuals
with higher education and income are less susceptible
to developing cancer, with the disease often diagnosed
at earlier stages.[] Additionally, studies have
revealed a notable connection between income level
and oral cancer rates. Particularly in the United States
of America (USA), Italy, Hong Kong, and Singapore,
there is evidence suggesting that the rise in real Gross
Domestic Product is inversely associated with the incidence
of oral cancer in men.[] These findings underscore
the necessity for a comprehensive evaluation
of the impact of economic factors on cancer incidence.
Inflation and Cancer Incidence
Although there are studies discussing the effect of
economic variables such as poverty,[] national
income per capita, growth,[] economic development[] on cancer incidence, there is no study in
the literature on the effect of inflation on cancer incidence.
Therefore, this study is a contribution to the
literature. Further research is needed to fully understand
the underlying mechanisms.
Gender Factor in Cancer Incidence
Gender-specific disparities in the incidence and mortality
of certain malignancies have been reported, with
differences in cancer incidence between the sexes regulated
by genetic and molecular factors as well as sex
hormones.[] Gender plays an important role in the
incidence, prognosis and mortality of cancers.[] This
means that the likelihood of developing cancer, the severity
of the disease and the chances of survival may
differ between men and women. However, despite this
knowledge, gender is often neglected in the treatment
of cancer patients. This may be due to a lack of understanding
of the differences between male and female
biology or a lack of recognition of the importance of
gender in cancer research and treatment. A study conducted
by Dong et al.[] emphasizes that gender differences
in cancer incidence and survival should not be ignored, as these differences may offer insights into
cancer biology and help personalize treatments for
men and women. Therefore, health professionals and
researchers should consider gender as an important
variable in cancer diagnosis, treatment and prevention.
Research shows that the incidence of cancer is higher
in men.[] Men have a 20% higher likelihood of
developing cancer in their lifetime compared to women,[] and men are less likely to survive a cancer diagnosis.[-] Men in China have a significantly higher
incidence than women worldwide.[]
Men are at higher risk than women for non-sexspecific
cancers, but research examining these differences
is limited. The higher incidence rates seen in men
suggest that known risk factors and factors beyond
female sex hormones may contribute to these differences.
For example, kidney cancer has a male to female
incidence rate of 2:1, which is fixed by age, year and
region. This suggests that factors other than sociocultural
habits and health behaviors are responsible for
this gender disparity.[] Specifically for lung cancer,
smoking is significantly associated with increased risk
in both men and women, but incidence is higher in
men than in women.[] According to the findings of
the study by Huang et al.,[] the mortality and incidence
of PM2.5-related lung cancer is higher in men
than in women. The incidence of colorectal cancer is
also influenced by gender and is higher in men than in
women.[] Additionally, specific cancers with higher
incidence in men (such as Kaposi's sarcoma) and specific
cancers with higher incidence in women (such as
thyroid cancers) have been identified.[] Studies have
also reported higher rates of non-reproductive cancers
in men compared to women, and these differences may
be influenced by biological factors or environmental
exposures.[] Age-specific incidence rates show that
although men have lower cancer rates at younger ages,
they increase with age, leading to a higher incidence in
men after the sixth decade of life.[]
These results demonstrate the critical importance
of gender-based variations in cancer incidence in
shaping cancer prevention and treatment strategies.
These findings suggest that gender is a complex factor
influencing cancer incidence, course and outcomes
and should not be ignored. Understanding the role
of sex differences in cancer incidence is important
to advance diagnostic and treatment strategies.[]
In this context, gender-sensitive approaches need
to be more embedded in cancer research and clinical
practice, and cancer-fighting strategies need to be
designed to take gender differences into account.
The impact of gender differences on cancer diagnosis
and treatment can positively influence the course of the
disease, emphasizing the importance of early detection.
Therefore, understanding gender-based differences can
form the basis of a patient-centred and personalized
health approach. Furthermore, reducing gender-based
health inequalities and identifying effective strategies
to cope with the disease is also crucial to ensure equity
across society in the fight against cancer. In addition to
biological and genetic factors that influence gender's
risk of cancer, social factors such as lifestyle choices, environmental
factors and access to health services, and
even economic factors need to be examined.
In conclusion, the relationships between cancer
incidence and personal income, gender, and other
socio-economic factors are complex and multifaceted.
The impact of these factors on cancer risk may
differ for different types of the disease and may vary
across regions. It is important to understand the role
of these factors in the fight against cancer worldwide.
Therefore, future studies will help us better understand
the causes and incidence of cancer and may
help to develop more effective prevention and treatment
approaches against cancer. With this approach,
the next section will begin the analysis of Denmark,
which ranks first in cancer incidence.
Methods
The examination will investigate the intricate connections
among cancer incidence, GDP per capita growth
(annual %), and inflation in Denmark, which ranks at
the top of the ranking. To accomplish this, data on male
and female cancer incidence spanning the years 1961-
2020 will be sourced from the Association of the Nordic
Cancer Registries (NORDCAN). Additionally, inflation
and GDP per capita growth (annual %) data will
be acquired from the World Bank (Table 1). This approach
ensures a comprehensive investigation into the
nuanced dynamics shaping the relationships between
health indicators and economic variables in Denmark.
Table 1 Variables
Figures 1, 2, and 3 illustrate the dynamics of the
data spanning the period 1961-2020. Furthermore,
the graphical exploration underscores the absence of
a trend structure in GDP per capita. Consequently, in
the unit root tests, a trendless structure will be selected
to accurately reflect the inherent characteristics of the
data. Figure 1 visually depicts that male incidence rates
surpass those of females, and both exhibit a parallel
trend. The graphical representation employs years on
the horizontal axis and cancer incidence rates (%) on
the vertical axis, providing a comprehensive visualization
of the temporal patterns in the dataset.
Fig. 1. Female and male incidence, Denmark (1961-2020).
LNFEM: Incidence (female)-logarithmically transformed;
LNMALE: Incidence (male)-logarithmically transformed.
Fig. 2. GDP per capita growth, Denmark (1961-2020).
GDP: Gross Domestic Product.
Fig. 3. Inflation, Denmark (1961-2020).
INF: Inflation.
An intriguing observation arises when scrutinizing
the GDP per capita trends in Denmark, particularly
during significant global crises. Specifically, a
notable downturn in GDP per capita is discerned in
the years 1974?75 (1st Oil Crisis), 1980?81 (2nd Oil
Crisis, World Debt Crisis), 2009 (2008 Global Financial
Crisis), and 2020 (COVID-19 Crisis). These
periods align with pivotal moments of global upheaval.
The temporal alignment of these economic
downturns with global crises is visually represented
in the graph, where the horizontal axis delineates the
years and the vertical axis illustrates the percentage
change in GDP per capita. This visual representation
provides a compelling insight into the interplay between Denmark's economic performance and the
overarching global economic landscape during these
crisis-ridden periods.
After reaching its second peak in 1980 and plunging
steeply until 1986, when it was brought under control,
the inflation rate had its highest point of 15.3% in
1974 (Fig. 3). The number of years is displayed on the
horizontal axis of the graph, while the inflation rate (%)
is displayed on the vertical.
Following a detailed examination of tables and
graphs, the initiation of these analyses allows for a
deeper understanding of the data and a more robust
drawing of conclusions. By clarifying the relationships
between gender, GDP per capita, and inflation variables, the analyses will provide more information
on how cancer incidence is affected.
In time series analysis, unit root tests represent a
first and necessary step. Unit root tests provide critical
information about the stationarity of data series. In this
study, The unit root properties of the data were initially
examined using the Augmented Dickey Fuller (ADF)
and Philips and Perron (PP) unit root tests. The test
outcomes are shown in Table 2.
Table 2 Unit root test results
Observing different degrees of stationarity in the
series, the Toda-Yamamoto Causality Test will be used
to examine causal relationships comprehensively. This
test provides a flexible methodology applicable to series
with different degrees of stationarity. Both the degree of integration and the existence of a cointegration
relationship are not prerequisites for the Toda-Yamamoto[] technique,[] making it an effective tool for
analyzing complex relationships and data series with
varying stationarity properties.
The Toda-Yamamoto causality analysis, based on
the Vector Autoregression (VAR) model, estimates
the causality relationship between variables using the
WALD test, regardless of the level of stationarity and
cointegration relationship between the series.[-]
This method can be applied whether a series is I(0),
I(1), or I(2), cointegrated or not.[]
Results
The results of the Toda-Yamamoto causality analysis
are presented in Table 3 and visualized in Figure 4 for
a clearer understanding of the results
Table 3 Results of Toda-Yamamoto causality analysis
Fig. 4. Results of Toda-Yamamoto causality analysis.
LNFEM: Incidence (female)-logarithmically transformed;
LNMALE: Incidence (male)-logarithmically transformed;
GDP: Gross Domestic Product; INF: Inflation.
• Bidirectional causality between LNMALE and GDP,
• Unidirectional causality from LNMALE to LNFEM,
• Unidirectional causality from LNFEM to GDP,
• Unidirectional causality from INF to LNFEM, has
been detected.
The outcomes of the intricate analysis reveal a reciprocal
causation connection between male cancer
incidence and per capita income. The influence of per
capita income on cancer incidence in men is evident, as
male cancer incidence concurrently impacts per capita
income. Furthermore, per capita income is subject to
the influence of both female and male incidence as well
as inflation. Notably, the findings underscore that female
cancer incidence is influenced by both male incidence
and inflation, whereas male incidence is solely influenced by per capita income. These results highlight
the intricate nature of the impacts of economic
factors, particularly per capita income and inflation, on
gender-specific cancer incidence.
Discussion
The global distribution of cancer presents an intricate
and complex scenario. Despite the conventional notion
that cancer prevails more prominently in developing
or underdeveloped nations, it is paradoxical that Denmark,
a country marked by high affluence, holds the
top position in cancer incidence. This anomaly underscores
the necessity for a comprehensive examination
of cancer patterns on a global scale.
In addressing the challenge of cancer, it is imperative
to undertake a thorough investigation encompassing all countries worldwide. However, a significant
impediment lies in the dearth of accessible data, hindering
a comprehensive understanding of the impact
of cancer as a global health concern.
The ramifications of this global health burden extend
beyond direct costs, encompassing expenses related
to diagnosis, treatment, care, and the losses of organs
or lives. Furthermore, there are economic losses stemming
from factors that disrupt economic stability. It is
indisputable that diseases compel individuals to disengage
from productive activities, thereby detrimentally
affecting national economies. Consequently, a nuanced
comprehension of how monetary policy decisions influence
human life becomes paramount in averting a
disease triggered, in part, by economic factors.
In conclusion, combatting cancer transcends the
realm of mere medical intervention; it evolves into a
multifaceted matter involving economic and social dimensions.
Hence, the formulation of effective strategies
to combat cancer necessitates a holistic consideration
of the intricate interplay between health, economy, and
the overall well-being of society.
Conclusion
Cancer is a leading global health issue with rising incidence
and mortality rates. It is crucial to monitor
changes in cancer registration, incidence, and survival
to develop strategies for reducing the cancer burden and
improving patient outcomes. Contrary to popular belief,
rich countries exhibit higher cancer rates than poorer
countries, with Denmark having the highest incidence.
This study examines the relationship between cancer
incidence rates, GDP per capita, and inflation, offering
a perspective that significantly diverges from
existing literature. In this context, I adopt a different
approach from previous studies such as Yang et al.[]
on socio-economic status, Luzzati et al.[] on personal
income, Bandyopadhyay[] on GDP per capita
and Chen et al.[] on the relationship between real
GDP and cancer incidence. The study investigated gender-
based causal relationships and reached remarkable
results. The study investigated gender-based causal
relationships and reached remarkable results found a
unidirectional causality from GDP per capita to male
cancer incidence, indicating that a decline in income
affects male cancer incidence.
Additionally, it was revealed that inflation influences
female cancer incidence, suggesting that economic
factors beyond GDP per capita impact cancer rates. In addition to these revelations, the research underscores
another unidirectional causality, this time from inflation
to female cancer incidence. This result suggests that
inflation, a previously ignored factor, affects female cancer
incidence. Although there are studies investigating
the relationship between income and cancer, there is no
study investigating the relationship between inflation,
which reduces the purchasing power of individuals and
impoverishes them, and cancer. This suggests that economic
factors extending beyond GDP per capita play a
role in influencing cancer incidence rates, inviting nuanced
discussions on the broader economic context.
In accordance with the Crisis-Cancer Cycle
(CCC),[,,,] this study shows that individual
impoverishment affects cancer incidence differently
based on gender: decreasing personal income affects
male incidence rates, while declining purchasing power
impacts female rates. It is surprising that biological
differences emerge at this point. In addition, causality
was found from both male and female incidence rates
to GDP per capita. Together with this finding, the bidirectional
causality between male cancer incidence rates
and GDP per capita points to a vicious circle. Cancer
incidence reduces GDP per capita. Individuals who are
diagnosed with cancer and withdraw from the labor
force experience a decline in their income. Decline in
income also affects the incidence of cancer. Individuals
who are worried about life and treatment withdraw
from the work/production process. This means that despite
the heavy costs of the disease, it causes financial
losses at national and global level. This intricate bidirectional
relationship between male cancer incidence rates
and GDP per capita underscores the need to explore the
underlying mechanisms. Does higher income contribute
to better healthcare access and, subsequently, earlier
cancer detection, or does it indicate that wealthier individuals
engage in behaviors that elevate cancer risk?
These questions necessitate further investigation. In addition
to the few studies in the literature that emphasize
gender differences and find an interaction between cancer
incidence rates, a surprising finding was obtained in
this study; unidirectional causality was found from male
incidence rates to female incidence rates. This discovery
challenges conventional assumptions and raises intriguing
questions about the potential shared risk factors and
environmental exposures that transcend gender boundaries.
Further studies are needed to explain this finding.
Kreiter et al.[] and Ly et al.[] found that breast cancer
incidence rates were related between genders, but
no explanation was provided regarding the direction of
causality in this relationship. This study fills this gap.
This study provides important findings that support
the Crisis-Cancer Cycle (CCC) hypothesis proposed by
Çiğdem[,,,] and contribute to existing research
on gender differences in cancer. It also makes a valuable
contribution to the literature by providing a new perspective
on the causes of cancer incidence from an economic
perspective. The study highlights the complexity
of the impact of economic stability on cancer epidemiology.
It also points to the need for greater consideration of
gender and economic factors in the design of anti-cancer
strategies. In particular, given that periods of economic
crisis contribute significantly to the incidence of cancer
and place a heavy burden on both the national and global
economy, and that the loss of income and productivity
experienced by cancer patients has serious consequences
at both the individual and societal levels, it is important to
raise awareness on this issue and to emphasize economic
stability. In conclusion, this study will pave the way for
further research on the relationship between cancer and
the economy and contribute to understanding the epidemiology
of cancer from an economic perspective. It is
clear that such studies will help to develop more effective
strategies in the fight against cancer.
Conflict of Interest: All authors declared no conflict of interest.
Use of AI for Writing Assistance: Artificial intelligence was
used in the English language correction of this article in parts.
Financial Support: None declared.
Peer-review: Externally peer-reviewed.
References
Rich WM. What is cancer. Contemp OB/GYN 2011.
Available at: https://www.contemporaryobgyn.net/
view/what-cancer. Accessed Sep 20, 2024.
Howell KC. Review on cancer. Res Rev J Med Health
Sci 2016;3:41-6.
Regnard C, Kindlen M. Supportive and palliative care
in cancer. London: CRC Press; 2016.
Bok SW. Cancer: A reactive mechanism in order to try
to save life. Med Hypotheses 1989;30(4):259?63.
Foote MA. Part 1. What is cancer. 2005. Available at:
https://typeset.io/papers/part-1-what-is-cancer-39ogg91ptf.
Accessed Sep 20, 2024.
Atıcı E. Cancer and empathy. JISHIM 2006;5(10):83-6.
Butler FS. The complex nature of cancer. J Am Geriatr
Soc 1960;8(9):689-97.
Mujahid M, Ghani F. Cancer is a disorder or a survival
mechanism: A review article. Res Rev J Med Health Sci
2017;6(2):1-7.
Ameri AM. Environmental causes of cancer. Am Int J
Cancer Stud 2019;1(1):27-34.
Abdurazakova KN, Magomedov M, Omarova SO, Gasanova
ZM. The role of socioeconomic and stressful
risk factors in the prevalence of malignancies. Sanit
Doctor 2022;9:700-8.
Vaccarella S, Georges D, Bray F, Ginsburg O, Charvat
H, Martikainen P, et al. Socioeconomic inequalities
in cancer mortality between and within countries
in Europe: A population-based study. Lancet Reg
Health-Europe 2023;25:100551
Tabuchi T. Cancer and Socioeconomic Status. In:
Kondo K, editor. Social Determinants of Health in
Non-communicable Diseases. Springer Ser Epidemiol
Public Health. Springer, Singapore, 2020.
Lortet-Tieulent J, Georges D, Bray F, Vaccarella S. Profiling
global cancer incidence and mortality by socioeconomic
development. Int J Cancer 2020;147(11):3029?36.
Giray H, Ünal B. Cancer epidemiology. J Health Soc
2007;3:10-8.
Schulmeister LK. Cultural Issues in cancer care. Mosby
1999:383-401.
Rouëssé J. Access to healthcare and social inequality.
2013. Available at: https://typeset.io/papers/accesaux-
soins-et-inegalite-sociale-access-to-healthcare-
523w9tlvgu. Accessed Sep 20, 2024.
Chadia Z, Hassane A, Ahmed O. The influence of
socio-economic factors on access to oncology care
among the poor and vulnerable in Morocco. Rev Black
Polit Econ 2023;50(4):424-45.
Birand AL, Knop JM. Incidence and epidemiology of
cancer. (Translation: S. Aban). Cancer Handbook for
Nurses. Ankara: IV. Evening Art School; 1996.
Çiğdem G. Is poverty another cause of cancer? An empirical
analysis. WCRJ 2019;6: e1226
Çiğdem G. The crisis-cancer cycle in the shadow
of COVID-19: Evidence from Turkey. WCRJ
2021;8:e2106.
Negoita SL, Ionescu RV, Zlati ML, Antohi VM,
Nechifor A. New regional dynamic cancer model
across the European Union. Cancers 2023;15(9):2545.
Rakshith HT, Lohita S, Rebello AP, Goudanavar PS,
Raghavendra NN. Sex differences in drug effects and/
or toxicity in oncology. Curr Res Pharmacol Drug Discov
2023;4:100152.
Tosakoon S, Lawrence WR, Shiels MS, Jackson SS. Sex
differences in cancer incidence rates by race and ethnicity:
Results from the SEER Registry (2000-2019). J
Clin Oncol 2023;41(16);10547.
Dmukauskas M, Waite K, Livinski AA, Edelson JG,
Cioffi G, Hunter C, et al. Disp-10. A systematic review
of sex differences of incidence and overall survival
in 15 non-reproductive cancers. Neuro-Oncology
2022;24(7):129.
Rubin JB, Yang W. Accounting for sex differences as a continuous
variable in cancer treatments. PREPRINT (Version
1) available at Research Square 2023. Available at:
https://assets-eu.researchsquare.com/files/rs-3120372/
v1_covered_49b74fdb-5944-4b5c-8179-b296650ea94e.
pdf?c=1688691976. Accessed Sep 20, 2024.
Dijksterhuis WPM, Kalff MC, Wagner AD, Verhoeven
RHA, Lemmens VEPP, Oijen MGH, et al. Gender
differences in treatment allocation and survival of advanced
gastroesophageal cancer: A population-based
study. J Natl Cancer Inst 2021;113(11):1551-60.
Baraibar I, Ros J, Saoudi NHA, Salvà F, García A, Tabernero
J, et al. Sex and gender perspectives in colorectal
cancer. ESMO Open 2023;8(2):101204.
Cruickshank S, McIntosh B, Fascia M. Dismay and
disparities - economic development and cancer incidence.
Int J Healthcare Policy 2019;1(1):70-88.
Luzzati T, Parenti A, Rughi T. Economic growth and
cancer incidence. Ecological Econ 2018;146:381-96.
Tope P, Morais S, El-Zein M, Franco E, Malagón T.
Differences in site-specific cancer incidence by individual-
and area-level income in Canada from 2006-2015.
Available at: https://www.medrxiv.org/content/10.1101/
2023.01.13.23284277v1.full.pdf. Accessed Sep 20, 2024.
Bandyopadhyay G, Lahiri S, Khan I, Ghosh S. A study
of 500 cancer patients to know any relation between
malignancy and socio-economic status. J Indian Med
Assoc 2010;108(11):740-2.
Chen DT, Chou Y, Wu HP, Hsu LP, Wen IS, Lee CF,
et al. Income and the incidence of oral cavity cancer:
Cross-national study. J Otolaryngol Head Neck Surg
2019;38(2):208-11.
Ly D, Forman D, Ferlay J, Brinton LA, Cook MB. An international
comparison of male and female breast cancer
incidence rates. Int J Cancer 2013;132(8):1918-26.
Zabala A. Affluence and increased cancer. Nat Sustain
2018;1(2):85.
Dong M, Cioffi G, Wang J, Kruchko C, Lathia JD, Rubin
JB, et al. Sex differences in cancer incidence and
survival: A pan-cancer analysis. Cancer Epidemiol
Biomarkers Prev 2020;29(7):1389?97.
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019.
CA Cancer J Clin 2019;69:7-34.
Oberaigner W, Siebert U. Do women with cancer have
better survival as compared to men after adjusting for
staging distribution? Eur J Public Health 2011;21:387-91.
Jung KW, Park S, Shin A, Oh CM, Kong HJ, Jun JK.
Do female cancer patients display better survival rates
compared with males? Analysis of the Korean national
registry data, 2005-2009. PLoS One 2012;7(12):e52457.
Ellison LF. Differences in cancer survival in Canada by
sex. Health Rep 2016;27:19-27.
Afshar N, English DR, Thursfield V, Mitchell PL, Te
Marvelde L, Farrugia H. Differences in cancer survival
by sex: A population-based study using cancer registry
data. Cancer Causes Control 2018;29:1059-69.
He YT, Zheng RS, Sun XB. The difference of cancer
incidence between male and female in China. China
Cancer 2013;22:174-178.
Scelo G, Li P, Chanudet E, Muller DC. Variability
of sex disparities in cancer incidence over 30 years:
The striking case of kidney cancer. Eur Urol Focus
2018;4(4):586-90.
Huang F, Pan B, Wu J, Chen E, Chen L. Relationship
between exposure to PM2.5 and lung cancer incidence
and mortality: A meta-analysis. Oncotarget
2017;8(26):43322-31.
Lee JH, Lee KS, Kim H, Jeong H, Choi MJ, Yoo HW,
et al. The relationship between metabolic syndrome
and the incidence of colorectal cancer. Environ Health
Prev Med 2020;25:6.
Bassukas ID, Tatsioni A. Age?specific versus age?adjusted
rates for the evaluation of the impact of the sex
on cancer morbidity. Cancer 2022;129(3):483.
Park B, Kim Y, Lee JH, Lee N, Jang SH. Sex difference
and smoking effect of lung cancer incidence in asian
population. Cancers 2020;13(1):113.
Toda HY, Yamamoto T. Statistical inference in vector
autoregressions with possibly integrated processes. J
Econometrics 1995;66:225-50.
Şadan Ş, Karabacak M, Meçik O The relationship between
education expenditures and economic growth
in turkish economy: Bootstrap Toda-Yamamoto Causality
Test approach. Kocaeli Üniv Sos Bilim Derg [Article
in Turkish] 2017;33:45-56.
Gazel S. The relationship between BIST industrial index
and various metals: Toda-Yamamoto Causality
Test. J Acad Soc Res [Article in Turkish] 2017;52:287-99.
Mert M, Çağlar AE. Eviews and Gauss applied time
series analysis. Ankara: Detay Publishing; 2019.
Jain A, Ghosh S. Dynamics of global oil prices, exchange
rate and precious metal prices in India. Resour
Policy 2013;38(1):88-93.
Yang L, Sun Tt, Yuan Y, Wang N. Relationship between
female breast cancer incidence and the socioeconomic
status in Beijing. Chin J Oncol [Article in Chinese]
2014;36(9):713-6.
Çiğdem G. Is an economic crisis a cancer cause? A
review of the crisis-cancer cycle. CUDES 2018, 7. International
Congress on Current Debates in Social Science,
İstanbul, Türkiye, 2018.
Çiğdem G. Is there a correlation between economic
crisis and cancer? A dilemma of crisis-cancer cycle.
Econ Admin Sci 2018;1:49-67.
Kreiter E, Richardson A, Potter JD, Yasui Y, Breast
cancer: Trends in international incidence in men and
women. Br J Cancer 2014;110(7):1891-7.
