Diabetes Mortality and Quality of Life Statistics by U.S. State

Estimated diabetes mortality and health-related quality of life data for U.S. states. The toolkit reports statistics including the number of deaths, death rates per 100,000 people, years of potential life lost, and quality-adjusted life years for individuals aged 15 and older. Data is compiled from CDC, NHIS, and BRFSS sources.

Use Cases

• Analyze state-level disparities in diabetes mortality rates per 100,000 people to identify public health priorities.
• Model the relationship between years of potential life lost (YPLL) and other state-level health indicators.
• Assess the burden of diabetes by comparing quality-adjusted life years (QALY) across different geographic regions.
• Track trends in diabetes-attributable deaths using data from multiple years and sources like CDC WONDER.

Strengths

• Data originates from authoritative U.S. public health sources including the CDC and National Health Interview Survey.
• Includes multiple burden metrics such as death counts, rates, YPLL, and QALYs for comprehensive analysis.
• Covers a national scope with state-level granularity for geographic comparison.

Limitations

• Specific row counts, column definitions, and dataset size are not provided, limiting preliminary assessment.
• Relies on estimated statistics and modeling, which may introduce methodological biases.
• Data sources span different years (e.g., 1999-2021), requiring careful handling for temporal analysis.

Provenance

Source

Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), National Health Interview Survey (NHIS), Behavioral Risk Factor Surveillance System (BRFSS).

Collection Method

Compiled estimates from multiple public health surveillance systems and databases, including CDC WONDER.

Time Range

Includes data from 1999 to 2021, as referenced in the source descriptions.

Freshness

Metadata indicates a last update in February 2026, suggesting ongoing maintenance.

Geography

United States, with state-level granularity.