Built Environment, Metabolic Risk Factors, and Self-Reported Kidney Disease in Missouri: A Population-Level Descriptive Study Using Public Health Behavioral Risk Factor Surveillance System (BRFSS) Data

Background: Chronic kidney disease (CKD) burden tracks heavily with metabolic comorbidities, yet the combined distribution of structural inequities -specifically the built environment -and physiologic risk factors has not been fully characterized at the population level in Missouri.Objective: The objective of the study is to describe self-reported kidney disease across Missouri Behavioral Risk Factor Surveillance System (BRFSS) regions, household income categories, and education levels, alongside statewide metabolic and built environment indicators.Methods: Using an ecological descriptive design and survey-weighted Missouri BRFSS aggregate data, we characterized the distribution of crude self-reported kidney disease prevalence across socioeconomic and geographic strata, alongside metabolic risks (diabetes, hypertension, and obesity) and built environment indicators.Estimates were re-extracted on October 11, 2026.The report identifies kidney disease, diabetes, BMI, and neighborhood indicators as 2024 data and high blood pressure and cholesterol as 2023 data.No inferential statistical testing was performed; all comparisons are descriptive.Results: Statewide self-reported kidney disease prevalence was 4.10%.Statewide obesity and diagnosed diabetes prevalence estimates were 34.53% and 11.31%, respectively.Geographic patterns were observed, with kidney disease prevalence highest in the Southwest BRFSS region (6.49%) and lowest in the Central region (2.73%).Socioeconomic point estimates varied; prevalence was 8.60% in households earning $15,000-$24,000 and 2.20% in households earning $75,000 or more.Perceived neighborhood safety ranged from 59.00% in the lowest-income bracket to 90.60% in the highest-income bracket.Conclusions: This descriptive analysis identifies differences in self-reported kidney disease prevalence across BRFSS regions and socioeconomic categories, alongside statewide metabolic and built environment indicators.These summaries do not establish individual-level co-occurrence, rural-versus-urban differences, or benefits of environmental interventions.This descriptive ecological design does not support individuallevel causal conclusions; future research using longitudinal and individual-level data is needed to formally evaluate these relationships.