CDC chronic disease indicators: chronic obstructive pulmonary disease
U.S. state-level COPD indicators from the CDC U.S. Chronic Disease Indicators set: COPD prevalence among adults, COPD mortality (45+, underlying and contributing cause), current smoking among adults with COPD, and COPD hospitalizations (Medicare beneficiaries 65+). Rows are indicator x state x year x demographic stratification.
copdrespiratorysmokingunited-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
| Column | 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 |
Sample rows
| 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 | COPD01|AK|-|Age 18-44|-|- | Alaska — Chronic obstructive pulmonary disease among adults — - — Age 18-44 | — | AK | Alaska | Chronic Obstructive Pulmonary Disease | Chronic obstructive pulmonary disease among adults | BRFSS | % | Crude Prevalence | — | — | Age | Age 18-44 | **** | Data suppressed; denominator < 50 or relative standard error > 30% |
| 2020-01-01T00:00:00 | 2020 | 2020 | COPD01|AK|-|Age 18-44|-|- | Alaska — Chronic obstructive pulmonary disease among adults — - — Age 18-44 | 2.2 | AK | Alaska | Chronic Obstructive Pulmonary Disease | Chronic obstructive pulmonary disease among adults | BRFSS | % | Crude Prevalence | 1.4 | 3.5 | Age | Age 18-44 | — | — |
| 2021-01-01T00:00:00 | 2021 | 2021 | COPD01|AK|-|Age 18-44|-|- | Alaska — Chronic obstructive pulmonary disease among adults — - — Age 18-44 | 2.1 | AK | Alaska | Chronic Obstructive Pulmonary Disease | Chronic obstructive pulmonary disease among adults | BRFSS | % | Crude Prevalence | 1.5 | 3.1 | Age | Age 18-44 | — | — |
| 2022-01-01T00:00:00 | 2022 | 2022 | COPD01|AK|-|Age 18-44|-|- | Alaska — Chronic obstructive pulmonary disease among adults — - — Age 18-44 | 2.3 | AK | Alaska | Chronic Obstructive Pulmonary Disease | Chronic obstructive pulmonary disease among adults | BRFSS | % | Crude Prevalence | 1.6 | 3.3 | Age | Age 18-44 | — | — |
| 2023-01-01T00:00:00 | 2023 | 2023 | COPD01|AK|-|Age 18-44|-|- | Alaska — Chronic obstructive pulmonary disease among adults — - — Age 18-44 | 2.8 | AK | Alaska | Chronic Obstructive Pulmonary Disease | Chronic obstructive pulmonary disease among adults | BRFSS | % | Crude Prevalence | 1.9 | 4.1 | Age | Age 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_copd" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/cdc_cdi/cdc_cdi_copd").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_copd
Tip: fetch /llms.txt for the full machine-readable catalog.