Key result
Age, polygenic score, and BMI were the strongest determinants of hypertension, with multivariable models explaining 34.31% of variance in women and 34.28% in men.
Why the study?
Arterial hypertension is a leading cause of global premature mortality with rising prevalence, making prevention essential. This study aimed to identify sex-specific risk factors and quantify the relative contributions of genetic and non-genetic determinants of hypertension.
Cross-Sectional (n=16,411)
No
Age, genetic predisposition (polygenic score), and metabolic factors (BMI) are the strongest contributors to arterial hypertension variance in both sexes, highlighting the need for sex-specific prevention strategies that integrate genetic and metabolic risk profiling.
Should not yet change hypertension care; leaves open whether sex-specific models improve prediction or outcomes.
Background Arterial hypertension is a major driver of non-communicable diseases and the leading cause of premature mortality globally.1,2 Elevated systolic blood pressure accounts for nearly 30% of cardiovascular risk.3 With hypertension prevalence continuing to rise, prevention is essential. We therefore aimed to identify sex-specific risk factors associated with hypertension. Purpose To quantify the sex-specific relative contributions of genetic and non-genetic determinants of hypertension. Methods This cross-sectional study included 16,411 participants of the our City Health Study. Arterial hypertension, defined as systolic blood pressure >140 mmHg, diastolic blood pressure >90 mmHg, or antihypertensive medication intake, was the primary outcome. Thirty-four candidate determinants across sociodemographic, genetic, behavioural, anthropometric, psychosocial, environmental, clinical, and women’s-health domains were selected. Whole genome sequencing data was available in 7,373 individuals, in which the best performing polygenic score (PGS) selected from a homogeneous set of predefined PGS was applied. Sex-specific, age-adjusted regressions assessed associations between individual factors and hypertension. For each sex, the best-performing variable within each domain was retained for multivariable modelling. Elastic net regularization identified independent predictors, which were jointly evaluated in a multivariable linear regression model. Relative importance analysis quantified each predictor’s contribution to the explained variance in hypertension. Results In our study population (49.6% women; median age 60 years), hypertension prevalence was 55.6% in women and 67.9% in men. About half of all candidate predictors were significantly associated with hypertension, with slightly more associations in men (Table 1). Elastic net identified six shared independent predictors: age, PGS, body-mass index, diabetes, hyperlipoproteinaemia, and socioeconomic status. Pregnancy-related hypertension was an additional predictor in women, while five further predictors emerged in men (sleep apnoea, current smoking, sports, healthy diet, air pollution). Relative importance analysis showed age as the strongest contributor to explained variance (women: 14.22%; men: 9.35%), followed by PGS (women: 7.04%; men: 8.20%) and body-mass index (women: 6.29%; men: 7.53%, Figure 1). Most other variables contributed <2%. The final model explained 34.31% of variance in women and 34.28% in men. Conclusion Age, genetic predisposition, and metabolic factors were the strongest contributors to hypertension in both sexes, while lifestyle and environmental factors added little explanatory value. The identified determinants accounted for roughly one third of hypertension variance, underscoring its multifactorial nature and the need for sex-specific prevention strategies integrating genetic and metabolic risk profiling.
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Waibel et al. (2026) conducted a cross-sectional in Arterial hypertension (n=16,411). Genetic (polygenic score) and non-genetic determinants across sociodemographic, behavioural, anthropometric, psychosocial, environmental, clinical, and women's-health domains vs. Sex-specific comparison (women vs. men) was evaluated on Arterial hypertension (defined as systolic blood pressure >140 mmHg, diastolic blood pressure >90 mmHg, or antihypertensive medication intake) and explained variance. Age, polygenic score, and BMI were the strongest determinants of hypertension, with multivariable models explaining 34.31% of variance in women and 34.28% in men.
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