| Occupational Injuries and Illnesses - Characteristics Data (ca) |
| ca.txt |
|
|
| Section Listing |
|
|
| 1. Survey Definition |
| 2. FTP files listed in the survey directory |
| 3. Time series, series file, data file, & mapping file definitions and |
| relationships |
| 4. Series file format and field definitions |
| 5. Data file format and field definitions |
| 6. Mapping file formats and field definitions |
| 7. Data Element Dictionary |
|
|
| ======================================================================== |
| Section 1 |
| ======================================================================== |
|
|
| The following is a definition of: Biennial Nonfatal Occupational Injuries and Illnesses - |
| characteristics data (ca) |
|
|
| Survey Description: In addition to industry data on injuries and illnesses, |
| survey respondents also are asked to provide additional information for a |
| subset of cases that resulted in a day away from work, job transfer, or |
| restriction. Employers answer several questions about these cases, including |
| the worker demographics and occupation as well as the case circumstances |
| surrounding the injury or illness case. Beginning with the 2021-2022 reference |
| period and continuing with 2023-2024 forward, this dataset expanded from including |
| only days away from work cases, to also including cases that resulted in a day of job |
| transfer restriction, as well as the combination of the two. This dataset moved to a |
| 2-year reference period and will be released biennially (every other year). |
|
|
| Summary of Data Available: Detailed breakouts of injury and illness data by |
| a variety of characteristics, including age, category, event, sex, |
| industry, length of service, nature, occupation, part of body, race, and |
| source are available. |
|
|
| Frequency of Observations: Biennial data are available and released every other |
| year. The reference period in the files is the second year of the two-year period. |
| For example: For the biennial reference period 2023-2024, the time series data |
| indicates reference year 2024. |
|
|
| Data Characteristics: Data are reported to one decimal place for rates, rounded |
| to the nearest 10 for counts, and whole number for median days. |
|
|
| Updating Schedule: OSHS nonfatal injury and illness data characteristics data are |
| published biennially and include a reference period of 2 years. For example, |
| 2023-2024 includes cases from both years. |
|
|
| ======================================================================== |
| Section 2 |
| ======================================================================== |
|
|
| The following Biennial Nonfatal Occupational Injuries and Illnesses - characteristics data |
| files are on the BLS internet in the sub-directory pub/time.series/ca: |
|
|
| |
| ca.age - Age codes (mapping file) |
| ca.case - Case codes (mapping file) |
| ca.category - Category codes (mapping file) |
| ca.contacts - Contacts for ca survey |
| ca.data.0.Current - All current biennial year-to-date data |
| ca.data.1.AllData - All data |
| ca.datatype - Datatype codes (mapping file) |
| ca.event - Event codes (mapping file) |
| ca.footnote - Footnote codes (mapping file) |
| ca.sex - Sex codes (mapping file) |
| ca.hour - Hour codes (mapping file) |
| ca.industry - Industry codes (mapping file) |
| ca.los - Length of service (LOS) codes (mapping file) |
| ca.nature - Nature codes (mapping file) |
| ca.occupation - Occupation codes (mapping file) |
| ca.ownership - Ownership codes (mapping file) |
| ca.pob - Part of body (POB) codes (mapping file) |
| ca.race - Race codes (mapping file) |
| ca.series - All series with beginning and end dates |
| ca.source - Source codes (mapping file) |
| ca.special - Special codes (mapping file) |
| ca.state - State codes (mapping file) |
| ca.time - Time codes (mapping file) |
| ca.txt - General information |
| ca.weekday - Weekday codes (mapping file) |
| ca.medical - Codes to indicate medical treatment type (mapping file) |
| |
| ============================================================================ |
| Section 3 |
| ============================================================================ |
|
|
| The definition of a time series, its relationship to and the |
| interrelationship among series, data and mapping files is detailed below: |
|
|
| A time series refers to a set of data observed over an extended period of |
| time over consistent time intervals (i.e. monthly, quarterly, semi-annually, |
| annually). BLS time series data are typically produced at monthly intervals |
| and represent data ranging from a specific consumer item in a specific |
| geographic area whose price is gathered monthly to a category of worker in |
| a specific industry whose employment rate is being recorded monthly, etc. |
| In the case of the ca series, it is produced biennially (every other year) |
| and covers a two-year reference period (i.e. 2023-2024). The reference period |
| listed in the time series file will be the second year of the biennial reference |
| period. For example, for reference period 2023-2024, the time series file will |
| show annual 2024, reference period 2023-2024 will show annual 2024, etc. |
|
|
| The FTP files are organized such that data users are provided with the |
| following set of files to use in their efforts to interpret data files: |
|
|
| a) a series file (only one series file per survey) |
| b) mapping files |
| c) data files |
|
|
| The series file contains a set of codes which, together, compose a series |
| identification code that serves to uniquely identify a single time series. |
| Additionally, the series file also contains the following series-level |
| information: |
|
|
| a) the period and year corresponding to the first data observation |
| (in the case of ca, that is the biennial end year) |
| b) the period and year corresponding to the most recent data observation |
| (in the case of ca, that is the biennial end year) |
|
|
| The mapping files are definition files that contain explanatory text |
| descriptions that correspond to each of the various codes contained within |
| each series identification code. |
|
|
| The data file contains one line of data for each observation period |
| pertaining to a specific time series. Each line contains a reference to |
| the following: |
|
|
| a) series identification code |
| b) year in which data is observed (in the case of ca, that is the biennial end year) |
| c) period for which data is observed (M13, Q05, and S03 indicate annual |
| averages) |
| d) value |
| e) footnote code (if available) |
|
|
| ============================================================================ |
| Section 4 |
| ============================================================================ |
|
|
| File Structure and Format: The following represents the file format used |
| to define ca.series. Note the Field Numbers are for reference only; they |
| do not exist in the database. Data files are in ASCII text format. Data |
| elements are separated by spaces; the first record of each file contains |
| the column headers for the data elements stored in each field. Each record |
| ends with a new line character. |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. series_id 17 CAU00X11XXXX3E100 |
|
|
| 2. category_code 3 00X |
|
|
| 3. datatype_code 1 3 |
|
|
| 4. case_code 1 E |
|
|
| 5. age_code 6 00XXXX |
|
|
| 6. los_code 6 0XXXXX |
|
|
| 7. medical_code 6 CNYXXX |
|
|
| 8. race_code 6 0XXXXX |
|
|
| 9. sex_code 6 0XXXXX |
|
|
| 10. pob_code 6 0XXXXX |
|
|
| 11. event_code 6 0000XX |
|
|
| 12. source_code 6 0000XX |
|
|
| 13. occupation_code 6 000000 |
|
|
| 14. nature_code 6 0000XX |
|
|
| 15. industry_code 6 000000 |
|
|
| 16. time_code 6 000000 |
|
|
| 17. hour_code 6 000000 |
|
|
| 18. weekday_code 6 000000 |
|
|
| 19. special_code 6 000000 |
|
|
| 20. ownership_code 1 1 |
|
|
| 21. state_code 2 00 |
|
|
| 22. footnote_codes 10 Varies |
|
|
| 22. begin_year 4 2024 |
|
|
| 23. begin_period 3 A01 |
|
|
| 24. end_year 4 2024 |
|
|
| 25. end_period 3 A01 |
|
|
| Note that for the ca series, the begin_year and end_year fields represent |
| the second year of the biennial period. For example, if 2024 is displayed |
| for the begin_year or end_year, then that represents the 2023-2024 period. |
| If 2024 is displayed, it represents the 2023-2024 period, etc. Additionally, |
| the begin_period and end_period are represented as A01 , but data are |
| published biennially and represent two years of data. |
|
|
| The series_id (CAU00X11XXXX3E100) can be broken out into: |
|
|
| Code = Value |
|
|
| survey abbreviation = CA |
| seasonal adjustment code = U |
| category code = 00X |
| detail code = 11XXXX |
| datatype code = 3 |
| case code = E |
| ownership code = 1 |
| state code = 00 |
|
|
| ============================================================================ |
| Section 5 |
| ============================================================================ |
|
|
| File Structure and Format: The following represents the file format used |
| to define each data file. Note that the field numbers are for reference |
| only; they do not exist in the database. Data files are in ASCII text |
| format. Data elements are separated by spaces; the first record of each |
| file contains the column headers for the data elements stored in each field. |
| Each record ends with a new line character. |
|
|
| The ca.data file may be partitioned into two separate files: |
|
|
| 1. ca.data.0.Current = All current biennial year-to-date data |
| 2. ca.data.1.AllData = All data |
|
|
| Both of the above data files have the following format: |
|
|
| Field #/Data Element Length Value (Example) |
|
|
| 1. series_id 17 CAU00X11XXXX3E100 |
|
|
| 2. year 4 2024 |
|
|
| 3. period 3 A01 |
|
|
| 4. value 12 3.7 |
|
|
| 5. footnote_codes 10 Varies |
|
|
| The series_id (CAU00X11XXXX3E100) can be broken out into: |
|
|
| Code = Value |
|
|
| survey abbreviation = CA |
| seasonal adjustment code = U |
| category code = 00X |
| detail code = 11XXXX |
| datatype code = 3 |
| case code = E |
| ownership code = 1 |
| state code = 00 |
|
|
| ============================================================================ |
| Section 6 |
| ============================================================================ |
|
|
| File Structure and Format: The following represents the file format used |
| to define each mapping file. Note that the field numbers are for reference |
| only; they do not exist in the database. Mapping files are in ASCII text |
| format. Data elements are separated by tabs; the first record of each file |
| contains the column headers for the data elements stored in each field. |
| Each record ends with a new line character. |
|
|
| File Name: ca.age |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. age_code 6 000000 |
|
|
| 2. age_text 100 Text |
|
|
|
|
| File Name: ca.case |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. case_code 1 E |
|
|
| 2. case_text 100 Text |
|
|
|
|
| File Name: ca.category |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. case_code 1 3 |
|
|
| 2. category_code 3 00X |
|
|
| 3. category_text 100 Text |
|
|
|
|
| File Name: ca.datatype |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. datatype_code 1 3 |
|
|
| 2. datatype_text 100 Text |
|
|
|
|
| File Name: ca.event |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. event_code 6 0XXXXX |
|
|
| 2. event_text 100 Text |
|
|
|
|
| File Name: ca.footnote |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. footnote_code 1 P |
|
|
| 2. footnote_text 100 Text |
|
|
|
|
| File Name: ca.sex |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. sex_code 6 000000 |
|
|
| 2. sex_text 100 Text |
|
|
|
|
| File Name: ca.hour |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. hour_code 6 000000 |
|
|
| 2. hour_text 100 Text |
|
|
|
|
| File Name: ca.industry |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. industry_code 6 000000 |
|
|
| 2. industry_text 100 Text |
|
|
|
|
| File Name: ca.los |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. los_code 6 000000 |
|
|
| 2. los_text 100 Text |
|
|
|
|
| File Name: ca.medical |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. medical_code 6 CNYXXX |
|
|
| 2. medical_text 100 Text |
|
|
|
|
| File Name: ca.nature |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. nature_code 6 0XXXXX |
|
|
| 2. nature_text 100 Text |
|
|
|
|
| File Name: ca.occupation |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. occupation_code 6 000000 |
|
|
| 2. occupation_text 100 Text |
|
|
|
|
| File Name: ca.ownership |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. ownership_code 1 1 |
|
|
| 2. ownership_text 100 Text |
|
|
|
|
| File Name: ca.pob |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. pob_code 6 0XXXXX |
|
|
| 2. pob_text 100 Text |
|
|
|
|
| File Name: ca.race |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. race_code 6 000000 |
|
|
| 2. race_text 100 Text |
|
|
|
|
| File Name: ca.source |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. source_code 6 0XXXXX |
|
|
| 2. source_text 100 Text |
|
|
|
|
| File Name: ca.special |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. special_code 6 000000 |
|
|
| 2. special_text 100 Text |
|
|
|
|
| File Name: ca.state |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. state_code 2 00 |
|
|
| 2. state_name 100 Text |
|
|
|
|
| File Name: ca.time |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. time_code 6 000000 |
|
|
| 2. time_text 100 Text |
|
|
|
|
| File Name: ca.weekday |
|
|
| Field #/Data Element Length Value(Example) |
|
|
| 1. weekday_code 6 000000 |
|
|
| 2. weekday_text 100 Text |
|
|
| ============================================================================ |
| Section 7 |
| ============================================================================ |
|
|
| BIENNIAL NONFATAL OCCUPATIONAL INJURIES AND ILLNESSES--CHARACTERISTICS DATA (ca) |
| DATABASE ELEMENTS |
|
|
| Data Element Length Value(Example) Description |
|
|
| age_code 6 000000 Code identifying age of |
| subjects for which data |
| are observed. |
|
|
| age_text 100 Text Identifies age of subjects |
| Ex: 20-24 for which data are |
| observed. |
|
|
| begin_period 3 A01 Identifies first data |
| Ex: A01=2024 observation within the |
| first year for which data |
| are available for a given |
| time series. |
|
|
| begin_year 4 2024 Identifies first year for |
| which data are available |
| for a given time series. In |
| the case of ca, the begin_year |
| will represent the second year |
| of the two-year reference period. |
| For example begin_year=2024 |
| represents 2023-2024 data. |
|
|
| case_code 1 A Code identifying type of |
| Ex: A=Industry case for which data are |
| division or available for a given time |
| selected |
| characteristics |
| by age. |
| |
| case_text 100 Text Describes case. |
|
|
| category_code 3 00X Code identifying industry, |
| event, or characteristic |
| for which data are |
| available for a given time |
| series. |
|
|
| category_text 100 Text Names the industry, event, |
| Ex: MIN=Mining, or characteristic for |
| N1A=Fractures which data are available |
| for a given time series. |
|
|
| datatype_code 1 3 Code identifying the |
| datatype of the |
| observation. |
|
|
| datatype_text 100 Text Identifies the datatype for |
| any given time series. |
|
|
| end_period 3 A01 Identifies last data |
| observation within the |
| last year for which data |
| are available for a given |
| time series. |
|
|
| end_year 4 2024 Identifies last year for |
| which data are available |
| for a given time series. In |
| the case of ca, the end_year |
| will represent the second year |
| of the two-year reference period. |
| For example end_year=2024 represents |
| 2023-2024 data. |
|
|
| event_code 6 0XXXXX Code identifying the event |
| which resulted in the |
| reported injury or |
| illness. |
|
|
| event_text 100 Text Names the event which |
| Ex: Falls, slips, resulted in the reported |
| trips injury or illness. |
|
|
| footnote_code 10 It varies Identifies footnote for |
| the data series. |
|
|
| sex_code 6 000000 Code identifying sex of |
| person experiencing the |
| injury or illness. |
|
|
| sex_text 100 Text Names sex of person |
| Ex: Men experiencing the injury or |
| illness. |
|
|
| hour_code 6 000000 Code identifying the total |
| hours worked before injury |
| or illness. |
|
|
| hour_text 100 Text Number of hours worked before |
| Ex. 1 - 2 hours injury or illness occurred. |
|
|
| industry_code 6 000000 Code identifying the |
| industry for which data |
| are observed. |
|
|
| industry_text 100 Text Names the industry for |
| Ex: Construction which data are observed. |
|
|
| los_code 6 000000 Code identifying the |
| length of service of the |
| person experiencing the |
| injury or illness. |
|
|
| los_text 100 Text Names the length of |
| Ex: 1-5 years service of the person |
| experiencing the injury or |
| illness. |
|
|
| medical_code 6 CHYXXX Code identifying the |
| type of medical treatment |
| for the injury or illness, |
| if applicable. |
|
|
| medical_text 100 Text Names the medical treatment |
| Ex: Any type of the injury or illness, |
| emergency room if applicable. |
| or |
| hospitalization |
| - Yes |
|
|
| nature_code 6 0XXXXX Code identifying the |
| nature of the injury or |
| illness. |
|
|
| nature_text 100 Text Names the nature of the |
| Ex: Fractures injury or illness. |
|
|
| occupation_code 6 000000 Code identifying the |
| occupation of the person |
| experiencing the injury or |
| illness. |
|
|
| occupation_text 100 Text Names the occupation of |
| Ex: Roofers the person experiencing |
| the injury or illness. |
|
|
| ownership_code 1 1 Code identifying the |
| ownership type. |
|
|
| ownership_name 100 Text Names the type of ownership |
| Ex. Detailed of employer. |
| Private Industry |
|
|
| period 3 A01 Identifies period for which data |
| Ex: A01=2024 is observed. For ca, the A01 period |
| represents the second year in the |
| biennial reference period. For |
| example, A01=2024 represents 2023-2024 data. |
|
|
| pob_code 6 0XXXXX Code identifying the part |
| of body affected. |
|
|
| pob_text 100 Text Names the part of body |
| Ex: Knee(s) affected. |
|
|
| race_code 6 000000 Code identifying the race |
| of the person experiencing |
| the injury or illness. |
|
|
| race_text 100 Text Names the race of the |
| Ex:Asian person experiencing the |
| injury or illness. |
|
|
| series_id 17 CAU00X11XXXX3E100 Unique series identifier |
|
|
| source_code 6 0XXXXX Code identifying the |
| source of the injury or |
| illness. |
|
|
| source_text 100 Text Names the source of the |
| Ex: Corrosive injury or illness. |
| acids |
|
|
| special_code 6 000000 Code identifying specific |
| injury or illness. |
|
|
| special_text 100 Text Name of specific injury or |
| Ex. illness. |
| Musculoskeletal |
| disorders |
|
|
| state_code 2 00 Code identifying each state. |
|
|
| state_name 100 Text Names of specific state where |
| Ex. Arizona injury or illness occurred. |
|
|
| time_code 6 000000 Code identifying the time |
| of the day injury or illness |
| occurred. |
|
|
| time_text 100 Text Time of the day when injury or |
| Ex. 12:01AM-4:00AM illness occurred. |
|
|
| value 12 3.7 Observation for the series. |
|
|
| weekday_code 6 000000 Code identifying the day of |
| the week the injury or illness |
| occurred. |
|
|
| weekday_text 100 Text Day of the week the injury or |
| Ex. Sunday illness occurred. |
| |
| year 4 2024 Identifies the second year of the |
| biennial period of observation. |
| |
|
|
