{ "background": "Community health centres are a cornerstone of primary healthcare in South Africa, yet robust quantitative evidence of their impact on population-level health risks is limited. Existing evaluations often lack rigorous counterfactual frameworks, making causal attribution challenging.", "purpose and objectives": "This study aimed to quantify the causal effect of a national community health centre expansion programme on key health risk factors, specifically hypertension prevalence and smoking rates, using a quasi-experimental design.", "methodology": "We employed a difference-in-differences model, exploiting the phased rollout of centres across municipalities. The core specification was $Y{it} = \\alpha + \\beta (Treati \\times Postt) + \\gammai + \\deltat + \\epsilon{it}$, where $Y_{it}$ is the outcome in municipality $i$ at time $t$. Treatment effects were estimated using two-way fixed effects with cluster-robust standard errors at the municipal level. Data came from a panel of national household surveys and health facility registries.", "findings": "The intervention was associated with a statistically significant 4.2 percentage point reduction in uncontrolled hypertension prevalence (95% CI: -6.1, -2.3). No significant effect was observed on smoking rates. The parallel trends assumption was validated using placebo tests in pre-intervention periods.", "conclusion": "The expansion of community health centres effectively reduced a major cardiovascular risk factor in treated communities. The null finding for smoking suggests behavioural risks may require more targeted, complementary interventions beyond facility-based care.", "recommendations": "Policy should sustain investment in primary care infrastructure for non-communicable disease management. Programme design must integrate specific behavioural change components to address lifestyle risks. Future evaluations should adopt similar causal inference methods for health systems research.", "key words": "difference-in-differences, quasi-experimental, primary healthcare, hypertension, health systems evaluation, causal inference", "contribution statement": "This paper provides a novel application of a robust difference-in-differences framework to