Dataset of Chronic Health & Risk Factors

Local Health Insights for Smarter Planning & Better Decisions

AGS’s Chronic Disease & Risk Factors dataset offers modeled estimates of major chronic health conditions and risk factors at the census block group level, giving you the local insight needed to plan health services, assess vulnerability, or make location-based decisions.

Sourced from the CDC’s PLACES project and refined using AGS’s Demographic Dimensions dataset, this product helps quantify population health in a realistic, spatially consistent way. 

It includes modeled indicators for conditions like diabetes, high blood pressure, and depression, as well as associated lifestyle and access-to-care risk factors.

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What’s Included

Modeled population counts and percentages for:

  • Chronic health conditions, including arthritis, diabetes, asthma, depression, and more
  • Risk behaviors such as smoking, binge drinking, and physical inactivity
  • Health screenings and checkups (cancer, cholesterol, cervical, dental, etc.)
  • Health coverage status and sleep duration
  • Indicators for mental health, general health, and senior preventive care
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Built for Industry

Healthcare & Public Health

Support planning for hospitals, outreach services, and community health initiatives using granular, population-level health data.

Retail & Grocery

Locate underserved areas and assess demand for wellness, pharmacy, or fitness-related products and services.

Government & Policy

Inform infrastructure investments, program funding, and social services with real-world health behavior indicators.

Insurance & Risk Analysis

Evaluate localized risk profiles to inform underwriting, product development, and pricing strategies.

Research & Education

Power epidemiological studies and cross-sector research with statistically modeled, block-level data.

Nonprofits & Advocacy Groups

Direct funding and programs to areas with higher rates of chronic disease or behavioral health risk factors.

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Methodology

This dataset is built from CDC health estimates at the census tract level, excluding small tracts.

AGS created statistical models at the tract level using AGS’s Demographic Dimensions as predictors, then applied at the block group level and scaled them to county and state control totals for consistency.

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Documentation & Support

Every AGS dataset is backed by comprehensive documentation and responsive, U.S.-based support.

We provide:

  • Methodology and modeling documentation
  • Metadata for every variable
  • Integration guidance
  • Access to AGS data scientists
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