CDC chronic disease indicators: cardiovascular disease
U.S. state-level cardiovascular disease indicators from the CDC U.S. Chronic Disease Indicators set: coronary heart disease and stroke mortality, high blood pressure and high cholesterol prevalence, medication use, and heart-failure hospitalizations (Medicare beneficiaries 65+). Rows are indicator x state x year x demographic stratification.
Qualité
Attribution
Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | timestamp | First day of the observation year (the provider's 'Starting year' column); CDI series are annual. |
| yearstart | integer | Starting year |
| yearend | integer | Ending year |
| series_id | string | Composite key: question identifier | state abbreviation | response identifier | up to three stratification values. |
| series_label | string | Human-readable series label: location, question text, response, and any stratifications. |
| value | float | Data Value, such as 14.7 or Category 1. |
| location_abbr | string | Location abbreviation |
| location_name | string | Location description |
| topic | string | Topic |
| question | string | Question full-length text |
| data_source | string | Data source abbreviation |
| datavalue_unit | string | The unit, such as $, %, years, etc. |
| datavalue_type | string | The data type, such as prevalence or mean. |
| low_confidence_limit | float | Low confidence limit |
| high_confidence_limit | float | High confidence limit |
| stratification_category_1 | string | The category of the stratification, such as Gender |
| stratification1 | string | The stratification within the category, such as Male or Female |
| footnote_symbol | string | Footnote symbol |
| footnote | string | Footnote text |
Exemple de lignes
| date | yearstart | yearend | series_id | series_label | value | location_abbr | location_name | topic | question | data_source | datavalue_unit | datavalue_type | low_confidence_limit | high_confidence_limit | stratification_category_1 | stratification1 | footnote_symbol | footnote |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019-01-01T00:00:00 | 2019 | 2019 | CVD01|AK|-|Age 18-44|-|- | Alaska — High blood pressure among adults — - — Age 18-44 | 19 | AK | Alaska | Cardiovascular Disease | High blood pressure among adults | BRFSS | % | Crude Prevalence | 15.6 | 22.8 | Age | Age 18-44 | — | — |
| 2021-01-01T00:00:00 | 2021 | 2021 | CVD01|AK|-|Age 18-44|-|- | Alaska — High blood pressure among adults — - — Age 18-44 | 15.1 | AK | Alaska | Cardiovascular Disease | High blood pressure among adults | BRFSS | % | Crude Prevalence | 13 | 17.6 | Age | Age 18-44 | — | — |
| 2023-01-01T00:00:00 | 2023 | 2023 | CVD01|AK|-|Age 18-44|-|- | Alaska — High blood pressure among adults — - — Age 18-44 | 18.2 | AK | Alaska | Cardiovascular Disease | High blood pressure among adults | BRFSS | % | Crude Prevalence | 16.1 | 20.5 | Age | Age 18-44 | — | — |
| 2019-01-01T00:00:00 | 2019 | 2019 | CVD01|AK|-|Age 45-64|-|- | Alaska — High blood pressure among adults — - — Age 45-64 | 40.6 | AK | Alaska | Cardiovascular Disease | High blood pressure among adults | BRFSS | % | Crude Prevalence | 36.4 | 44.9 | Age | Age 45-64 | — | — |
| 2021-01-01T00:00:00 | 2021 | 2021 | CVD01|AK|-|Age 45-64|-|- | Alaska — High blood pressure among adults — - — Age 45-64 | 40.5 | AK | Alaska | Cardiovascular Disease | High blood pressure among adults | BRFSS | % | Crude Prevalence | 37.4 | 43.7 | Age | Age 45-64 | — | — |
Télécharger un échantillon
Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).
Utiliser avec un LLM
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_cardiovascular" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_cardiovascular").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API: https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_cardiovascular
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.