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CDC chronic disease indicators: diabetes

U.S. state-level diabetes indicators from the CDC U.S. Chronic Disease Indicators set: diabetes prevalence among adults, diabetes and diabetic ketoacidosis mortality (underlying or contributing cause), and gestational diabetes among women with a recent live birth. Rows are indicator x state x year x demographic stratification.

Source: CDC U.S. Chronic Disease Indicators22,599 rowsUpdated: 9/22/2026License: ODbL-1.0
diabetesunited-statescdcchronic-disease

Quality

95.8

Attribution

Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health

Schema

ColumnTypeDescription
datetimestampFirst day of the observation year (the provider's 'Starting year' column); CDI series are annual.
yearstartintegerStarting year
yearendintegerEnding year
series_idstringComposite key: question identifier | state abbreviation | response identifier | up to three stratification values.
series_labelstringHuman-readable series label: location, question text, response, and any stratifications.
valuefloatData Value, such as 14.7 or Category 1.
location_abbrstringLocation abbreviation
location_namestringLocation description
topicstringTopic
questionstringQuestion full-length text
data_sourcestringData source abbreviation
datavalue_unitstringThe unit, such as $, %, years, etc.
datavalue_typestringThe data type, such as prevalence or mean.
low_confidence_limitfloatLow confidence limit
high_confidence_limitfloatHigh confidence limit
stratification_category_1stringThe category of the stratification, such as Gender
stratification1stringThe stratification within the category, such as Male or Female
footnote_symbolstringFootnote symbol
footnotestringFootnote text

Sample rows

dateyearstartyearendseries_idseries_labelvaluelocation_abbrlocation_nametopicquestiondata_sourcedatavalue_unitdatavalue_typelow_confidence_limithigh_confidence_limitstratification_category_1stratification1footnote_symbolfootnote
2019-01-01T00:00:0020192019DIA01|AK|-|Age 18-44|-|-Alaska — Diabetes among adults — - — Age 18-442AKAlaskaDiabetesDiabetes among adultsBRFSS%Crude Prevalence1.23.5AgeAge 18-44
2020-01-01T00:00:0020202020DIA01|AK|-|Age 18-44|-|-Alaska — Diabetes among adults — - — Age 18-442.4AKAlaskaDiabetesDiabetes among adultsBRFSS%Crude Prevalence1.53.7AgeAge 18-44
2021-01-01T00:00:0020212021DIA01|AK|-|Age 18-44|-|-Alaska — Diabetes among adults — - — Age 18-442.4AKAlaskaDiabetesDiabetes among adultsBRFSS%Crude Prevalence1.53.7AgeAge 18-44
2022-01-01T00:00:0020222022DIA01|AK|-|Age 18-44|-|-Alaska — Diabetes among adults — - — Age 18-442.9AKAlaskaDiabetesDiabetes among adultsBRFSS%Crude Prevalence2.24AgeAge 18-44
2023-01-01T00:00:0020232023DIA01|AK|-|Age 18-44|-|-Alaska — Diabetes among adults — - — Age 18-442.7AKAlaskaDiabetesDiabetes among adultsBRFSS%Crude Prevalence23.8AgeAge 18-44

Download sample data

Download the full sample snapshot for this dataset (sample rows, not the complete dataset).

Use with an LLM

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_diabetes" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_diabetes").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

API endpoint: https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_diabetes

Tip: fetch /llms.txt for the full machine-readable catalog.