Happiness and hypertension prevalence: A global analysis

The prevalence of hypertension around the world is high while hypertension control is relatively low. The objective of this study is to investigate the association between happiness and hypertension prevalence across countries. We used World Happiness Report (WHR) data, NCD (non-communicable disease) Risk Factor Collaboration (NCD-RisC) data, and machine learning methods (K-means clustering, XGBoost) to assess the influence of key variables that may explain variations in national happiness scores on predicting hypertension prevalence for males and females in 151 countries with complete concurrent data across all global regions for the year 2019. The K-means clustering method resulted in four clusters of countries based on the happiness features. Countries in groups with higher happiness scores had a relatively lower prevalence of Hypertension. The XGBOOST analysis showed that GDP per capita was the most important feature predicting the prevalence of hypertension for both males and females. Also, generosity and life expectancy were other important features predicting hypertension for males. Healthy life expectancy, social support, and freedom to make life choices were important features predicting hypertension for females. Social support and healthy life expectancy were stronger predictors of hypertension prevalence in males, whereas healthy life expectancy and GDP per capita were most influential for females. Sex-specific public health considerations may be valuable for better understanding patterns of hypertension prevalence worldwide. Multi-faceted, integrated policy approaches that target not only economic factors but also consider a broader societal well-being may help inform efforts to address hypertension across countries.