A Global Perspective on Determinants of Cardiovascular Mortality: Linear Regression Model of 183 Countries on Nationwide Cardiovascular Policies, Socioeconomic Disparities, Universal Health Coverage and Tobacco

BackgroundCardiovascular (CV) diseases remain the leading cause of mortality worldwide. Various determinants has been indicated contributing in CV mortality, spanning from health policy, universal health coverage (UHC), tobacco and socioeconomic diversity. To date, no quantitative regression model has been established to exhibit the magnitude and prediction of CV mortality. We aimed to formulate a linear regression model of CV determinants involving healthcare insurance coverage and national policy, economic status, smoking prevalence, gender and subregional variety. MethodsA linear regression model was employed, with the percentage of cardiovascular deaths as the dependent variable. Independent variables were Universal Health Coverage (UHC), World Bank income classifications, availability of national policy on CV, gender, availability of national CV guideline, CV risk stratification in primary healthcare, smoking and sub-regions. Data were gathered from World Health Organization and The World Bank dataset. ResultsA total of 2,385 data points from 2015 to 2019 was acquired constituting 183 countries. More extensive UHC ({beta} = -0.052, t = -3.663, p <0.001) and high-income countries (-0.060, t = -2.756, p <0.001) exhibited lower predicted CV mortality. Smoking prevalence was strongly correlated with higher mortality ({beta} = 0.128, t = 8.408, p <0.001). Regional disparities were observed, with Eastern Europe presenting highest mortality rate ({beta} = 0.685, t = 32.686, p <0.001). Compared to male, female showed higher cardiovascular death ({beta} = 0.047, t = 4.017, p <0.001). The availability of national policies in cardiovascular health were associated with lower mortality ({beta} = -0.031, t = -3.211, p = 0.001). CV national guideline was the only non-significant CV determinant. ConclusionsThe development of a quantitative regression model for cardiovascular mortality incorporating multifaceted determinants was expected to promote comprehensive public health strategies, policy reforms, and national health system strengthening, which are essential to reduce the global burden of cardiovascular diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/25326323v1_fig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@14ebbf5org.highwire.dtl.DTLVardef@15e1e1org.highwire.dtl.DTLVardef@a0b130org.highwire.dtl.DTLVardef@1d0e87c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1C_FLOATNO (Graphical Abstract). Summary of the research and quantified determinants of CV death. UHC: universal health coverage, CV: cardiovascular, *[&ge;]50% availability of CV risk stratification program in primary health care. C_FIG