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US state chronic-disease disparity signals (CDC CDI burden & equity tracker)

State-level chronic-disease signals derived from the CDC Chronic Disease Indicators: prevalence, mortality and hospitalization trends for diabetes, cardiovascular disease, COPD and mental health across 55 US states/territories (2019-2023), with year-on-year changes, momentum, 3-sigma anomaly flags vs a trailing 3-year baseline, naive-drift 1-year forecasts, cross-state momentum ranks, and Black-White and female-male disparity gaps. The monetizable health-equity signals layer on top of raw CDC chronic-disease statistics. Raw series: CDC Chronic Disease Indicators (Socrata).

Source: US State Chronic-Disease Disparity Signals (derived)4,680 rowsUpdated: 9/22/2026
chronic-diseasediabetescardiovascularcopdmental-healthhealth-equitydisparitiesus-statescdcmomentumanomaly-detectionforecastingsignals

Quality

94.5

Attribution

Centers for Disease Control and Prevention, Chronic Disease Indicators; derived signals by Frontier Data Hub

Schema

ColumnTypeDescription
datestringReference year of the CDC Chronic Disease Indicator observation (yearstart; annual).
countrystring
country_codestring
series_idstringConnector series key: CDC CDI topic code | state/territory abbreviation | question code (e.g. DIA|CA|Q01).
series_labelstringState/territory name plus the CDC CDI question text, e.g. 'California — Diabetes among adults'.
valuefloatIndicator value as published by CDC CDI (datavalue): prevalence in %, or rate per 100,000, depending on the question; see value_type for which form.
value_typestringCDC CDI datavaluetype for this row (age-adjusted forms preferred for cross-state comparability).
yoy_change_ppfloat
yoy_change_pctfloat
volatility_30dfloat
momentum_3mfloat
anomaly_flaginteger
forecast_1mfloat
rankinteger
race_gap_black_white_ppfloat
sex_gap_female_male_ppfloat

Sample rows

datecountrycountry_codeseries_idseries_labelvaluevalue_typeyoy_change_ppyoy_change_pctvolatility_30dmomentum_3manomaly_flagforecast_1mrankrace_gap_black_white_ppsex_gap_female_male_pp
2019-01-01United StatesUSACOPD|AK|Q03Alaska — Chronic obstructive pulmonary disease among adults4.6Age-adjusted Prevalence0-0.39999999999999947
2019-01-01United StatesUSACOPD|AK|Q04Alaska — Chronic obstructive pulmonary disease mortality among adults aged 45 years and older, underlying cause81.7Age-adjusted Rate024.799999999999997
2019-01-01United StatesUSACOPD|AK|Q05Alaska — Chronic obstructive pulmonary disease mortality among adults aged 45 years and older, underlying or contributing cause173.7Age-adjusted Rate0-11.099999999999994
2019-01-01United StatesUSACOPD|AK|Q08Alaska — Current smoking among adults with chronic obstructive pulmonary disease54.4Age-adjusted Prevalence07.299999999999997
2019-01-01United StatesUSACOPD|AK|Q18Alaska — Hospitalization for chronic obstructive pulmonary disease as any diagnosis, Medicare-beneficiaries aged 65 years and older42.77Age-adjusted Rate04.2799999999999942.4399999999999977

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_chronic_signals/us_state_chronic_disease_disparity_signals" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/cdc_chronic_signals/us_state_chronic_disease_disparity_signals").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_chronic_signals/us_state_chronic_disease_disparity_signals

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