Page 153 - GHES-2-2

Global Health Econ Sustain Disparities in cancer outcomes

Table 4. Univariate associations for estimated age‑standardized cancer incidence in 2020
Variable β Standard error 95% confidence interval p
Health expenditure as a percentage of GDP 3.59 3.44 −3.48; 10.65 0.307
Universal health coverage service 1.90 1.68 −1.56; 5.37 0.269
Dedicated funding for early detection program 3.51 4.87 −6.50; 13.52 0.478
Cancer early detection program −7.78 16.74 −42.81; 27.26 0.647
Referral systems 2.81 12.11 −22.07; 27.70 0.818
Public and private cancer centers −0.71 1.73 −4.30; 2.88 0.684
Abbreviation: GDP: Gross domestic product.

Table 5. Univariate associations for estimated age‑standardized mortality in 2020

Variable β Standard error 95% confidence interval p
Health expenditure as a percentage of GDP −5.18 1.56 −8.38; −1.97 0.003
Universal health coverage service −2.75 0.74 −4.27; −1.23 0.001
Dedicated funding for early detection program 0.13 2.61 −5.23; 5.49 0.961
Cancer early detection program 8.25 8.54 −9.62; 26.12 0.346
Referral systems 8.11 6.22 −4.68; 20.90 0.204
Public and private cancer centers −1.05 0.78 −2.67; 0.57 0.193
Abbreviation: GDP: Gross domestic product.

Table 6. Univariate associations for the estimated number of prevalent cases (5‑year period) in 2020
Variable β Standard error 95% confidence interval p
Health expenditure as a percentage of GDP 3.59 3.44 −3.48; 10.65 0.307
Universal health coverage service 1.90 1.68 −1.56; 5.37 0.269
Dedicated funding for early detection program 3.51 4.87 −6.50; 13.52 0.478
Cancer early detection program −7.78 16.74 −42.81; 27.26 0.647
Referral systems 2.81 12.11 −22.07; 27.70 0.818
Public and private cancer centers −0.71 1.73 −4.30; 2.88 0.684
Abbreviation: GDP: Gross domestic product.

aims to enhance understanding of the multifaceted factors both health expenditure as a percentage of GDP and
influencing cancer outcomes. These findings can potentially UHC services. These findings suggest that as the values
inform strategies and policies aimed at optimizing health (corresponding to health expenditure as a percentage of
systems and improving overall cancer care and management. GDP and UHC services) increase, the corresponding age-
standardized mortality rates tend to decrease. Moreover,
3.2. Association between health expenditure, UHC, regression analysis revealed a pattern within Baltic
and age-standardized mortality in 2020 European countries (i.e., Latvia, Estonia, and Lithuania),
When examining the relationship between estimated age- Southeastern European countries (i.e., Bulgaria, Croatia,
standardized mortality rates in 2020 and key variables, notable and Romania), and Central Eastern European countries
correlations were observed. Specifically, health expenditure as (i.e., Czechia, Hungary, Poland, Slovakia, and Slovenia),
a percentage of GDP (p = 0.003) and UHC services (p = 0.001) indicating higher age-standardized mortality rates in 2020,
exhibited significant associations. Their unstandardized alongside lower health expenditure as a percentage of GDP
coefficients (i.e., β = −5.18 and −2.75, respectively) suggest and reduced UHC services. This analysis suggests a trend
that elevated levels of these variables correlate with reduced toward elevated age-standardized mortality rates within
estimates of age-standardized mortality in 2020 (Table 5). these regions.
Figures 1 and 2 confirm the inverse relationship Conversely, countries within continental Europe
between age-standardized mortality rates in 2020 and (including Luxembourg, Austria, Belgium, France,

Volume 2 Issue 2 (2024) 5 https://doi.org/10.36922/ghes.3216