{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/639d7be02ceb4135abbb3976ada6288b\" frameborder=\"0\" width=\"1152\" height=\"864\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":864,"width":1152,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":864,"thumbnail_width":1152,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/639d7be02ceb4135abbb3976ada6288b-7c98134ea2656f0c.gif","duration":165.966,"title":"Socioeconomic Baselines and Diabetes Risk Insights","description":"This Loom explains how local socio-economic baselines from US Census data relate to community health outcomes using CDS health metrics. The author describes pairing ACS household income with CDS crude diabetes rates across 3,141 U.S. countries and running a continuous pivot analysis rather than relying on country aggregates, to assess regional vulnerability. From a scatter plot, adult diabetes prevalence shows a steady downward trend as country income increases, with correlation R = -0.45 and P = 0.001, indicating a statistically significant moderate relationship. The key implication is that healthcare leaders can use local income levels as a proactive signal to deploy mobile care and preventive programs in communities with the highest chronic disease burden."}