A Statistical Analysis Framework for Evaluating the Association Between Age and Hypertension Severity in a Primary Healthcare Setting: Evidence from Imbanagara Health Center, Ciamis

Abstract

Hypertension remains a critical public health challenge globally, with age identified as a primary determinant influencing its prevalence and severity. This study develops and applies a statistical analysis framework to evaluate the association between age and hypertension severity within a primary healthcare context, using empirical evidence from Imbanagara Health Center, Ciamis, in 2022. The research adopts an experimental research design utilizing retrospective clinical data, integrating descriptive statistics, correlation analysis, and multivariate regression modeling to assess age-dependent variations in hypertension severity. The framework incorporates stratified age categorization, severity classification based on standardized blood pressure thresholds, and adjustment for treatment adherence-related confounders. Findings indicate a statistically significant positive association between increasing age and hypertension severity, with older populations exhibiting higher probabilities of moderate to severe hypertension stages. The analysis further reveals that treatment adherence plays a moderating role in this relationship, influencing outcome variability across age groups. The study contributes a structured analytical model that enhances epidemiological understanding within primary healthcare systems and supports evidence-based policy formulation. Limitations include reliance on single-center data and absence of longitudinal tracking. The proposed framework offers a scalable methodological approach for similar community-based health assessments.