Spatial variation and correlates of raised blood pressure in Cambodia: a Gaussian-process geostatistical analysis of the 2023 STEPwise survey

Introduction Raised blood pressure is an important cardiovascular risk factor in Cambodia; however, national averages may obscure substantial local geographic heterogeneity. We assessed the spatial distribution of raised blood pressure and its demographic, metabolic, behavioural, built-environment, and environmental correlates using the 2023 Cambodia STEPwise approach to noncommunicable disease (NCD) risk factor surveillance (STEPS) survey. Methods We analysed 289 georeferenced primary sampling units (PSUs) from the 2023 Cambodia STEPS Survey. PSU-level case counts and numbers of adults with valid blood pressure data were modelled using a frequentist binomial generalised additive model with a two-dimensional Gaussian-process smooth. An explanatory model included selected PSU-level and contextual covariates; a separate mapping model used spatially continuous predictors to generate predictions on a 5-km grid. Design-based national and residence-specific prevalence estimates were calculated separately using the survey design and Step-2 weights. Results Among 4,225 adults with valid blood pressure data, unweighted prevalence of raised blood pressure was 28.6%, compared with 18.8% after Step-2 weighting; weighted prevalence was 17.5% in rural areas and 21.7% in urban/suburban areas. Mean observed unweighted PSU-level prevalence was 29.0%. In the adjusted spatial explanatory model, the proportion aged 60–69 years (β=1.969, SE=0.327; p<0.001) and overweight/obesity prevalence (β=0.996, SE=0.265; p<0.001) were positive ecological correlates. The spatial model had lower Akaike information criterion and residual deviance than its non-spatial counterpart, although Bayesian information criterion was higher. Prediction uncertainty was greater in some sparsely sampled areas. Conclusions Raised blood pressure showed significant geographic heterogeneity across Cambodia. Older age composition and overweight/obesity prevalence were positive PSU-level correlates, not individual-level causal effects. Predicted prevalence should be interpreted alongside uncertainty and should complement, rather than replace, design-based STEPS prevalence estimates for geographically informed NCD planning. WHAT IS ALREADY KNOWN ON THIS TOPIC Cambodia’s national STEPS Survey indicates a rising burden of raised blood pressure, but national averages cannot show fine-scale geographic heterogeneity or identify areas where model-based spatial estimates are least precise. WHAT THIS STUDY ADDS Using 289 georeferenced PSUs, this study distinguishes survey-weighted prevalence estimation from unweighted PSU-level geostatistical modelling, identifies older age composition and overweight/obesity as the strongest adjusted ecological correlates, and maps predicted prevalence alongside prediction standard errors and 95% confidence limits. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY The maps can complement STEPS and routine NCD indicators by identifying geographic variations in the modelled raised blood pressure burden while explicitly identifying where the uncertainty is high. Areas with elevated predicted raised blood pressure prevalence and acceptable precision may warrant closer assessment of screening and treatment capacity, whereas areas with high uncertainty may benefit from additional surveillance.